Impact of the Drought in the
San Joaquin Valley of California
A Study Funded by Wells Fargo Foundation
California State University, Fresno
July 2015
OvergrownBoatRamp
LakeSuccess:SierraReservoir,EasternSanJoaquinValley
Wildflowersgrowwherewatershouldbe.Arecentrainhasgreenedthehillsidesand
thelakebedbuthasdonelittletoreversethedwindlingwaterlevel.Theboatrampisa
full100yardsshyofthecurrentwaterlevel.
GeographicArea:TownofPortervillewhichhasrunoutofwater.
Photograph:NeilChowdhury
Principal Investigator
Dr. Lynnette Zelezny, Provost
Co-Principal Investigator, Project Director
Dr. Xuanning Fu, Associate Dean of College of Social Sciences
Editor
Dr. Gillisann Harootunian, Director, University Initiatives
Co-Project Director
David Drexler, Henry Madden Library
Faculty/Staff Researchers
Dr. Antonio Avalos, Department of Economics
Neil Chowdhury, MFA, Department of Art and Design
Dr. Fayzul Pasha, Department of Civil and Geomatics Engineering
Dr. Samendra Sherchan, Department of Public Health
Jes Therkelsen, MFA, Department of Mass Communication and Journalism
Dr. Chih-Hao Wang, Department of Geography and City and Regional Planning
Dr. David Zoldoske, California Water Institute
Sargeant Green, California Water Institute
Photographer
Cary Edmondson, University Communications Department
Table of Contents
Introduction …………………………………………………………………………..... i
1. Severity of the Drought and its Impact on Agriculture and Use of Energy ……... 1
Editorial Snapshot: Is There a “Central” Valley? ……………………………... 53
Photo Spread: The Vineyard ………………………………………………….... 54
Video Vignette: Switching to Almonds: Drought Impact on Farming
and People ……………………………………………………………………... 57
2. The Economic Impact of the Drought in the California San Joaquin Valley …...58
Editorial Snapshots:
Who Are They?: Moving from Economic Impact to Human Impact ….. 72
The Shadow Economy: How to Document the Un-Documented? ….…. 73
Food Insecurity in the San Joaquin Valley, with a video vignette …...… 74
Sharing the Bounty: Fresno State Food Insecurity Project
3. Water Usage and Residential Water Consumption in the California San
Joaquin Valley …………………………………………………..………...….. 75
Intra-Chapter Snapshot: A Census-Designated Place: A Glimpse into One
Disadvantaged Community ………………………………………….… 89
4. Public Health Implications of Drought ...........................................................……. 90
Editorial Snapshots:
The Health Drought ……………………………………………..……. 112
From Economic Distress to Psychological Distress …………..……… 113
Map: San Joaquin Valley: Environmental Justice Areas ……………..………. 114
Video Vignette: East Porterville: Drought Impact on one Disadvantaged
Community ………………………………………………………………..…. 115
Conclusion and Recommendations ………………………………………………… 116
References ……………………………………………………………………….….. 121
Appendices
Appendix 1 Maps …………………………………………………………….…….… 129
Appendix 2 Annotated bibliography …………………………………………….…… 134
Appendix 3 Stakeholder organizations, with contact information ……………….….. 145
Appendix 4 Data Sources (URL links) ……………………………………………..… 151
INTRODUCTION
For the past three years (2012–2014), California has experienced the most severe drought
conditions in its recorded history. When examined by using two paleoclimate reconstructions of
drought and precipitation for Central and Southern California to place this current event in the
context of the last millennium, the current drought was determined to be the most severe in the
last 1,200 years, with 2014 moisture deficits worse than any previous continuous span of dry
years (Griffin & Anchukaitis, 2014).
The rainy season of 2014–15 has resulted in disappointment for the fourth straight year: the
drought has deepened. The Sierra Nevada snowpack is only 5% of average, one-fifth the size of
the smallest ever recorded, prompting Governor Jerry Brown to announce the state’s first
mandatory water reductions, aiming at cutting water use by 25%. Brown promised more
enforcement in cities and actions against water agencies in groundwater-depleted areas that have
not shared data with the state (Grossi, 2015).
Historically, the state of California has faced many droughts, and several studies have been
completed to assess the impacts on different sectors. These studies have considered the entire
state, and not focused on the San Joaquin Valley, the center of agriculture in the state. The
impact of late 1980s drought in California on the societal and environmental costs was assessed
by Gleick and Nash (1991). The Institute for Water Resources (IWR) of the U.S. Army Corps of
Engineers also published a report on the 1987–1992 drought, focusing on all of California. The
lessons that were learned from this study were published in Dziegielewski, Garbharran &
Langowski, 1993. The Pacific Institute published a report on the drought from 2007 to 2009. The
report analyzed the impacts on California’s economy and environment (Christian-Smith, Levy,
& Gleick, 2011). Recently the Center for Watershed Science, University of California Davis (UC
Davis) published “Economic Analysis of the 2014 Drought on for California Agriculture,” a
report focusing on the current drought’s impact on the state’s agriculture (Howitt, MedellínAzuara, MacEwan, Lund, & Sumner, 2014). This was followed on May 31, 2015 by
“Preliminary Analysis: 2015 Drought Economic Impact Study.” Also issued was the
“Preliminary 2014 Drought Economic Impact Estimates in Central Valley Agriculture” (Howitt,
Medellín-Azuara, MacEwan, & Lund, 2014) which studied all 25 counties of the Central Valley.
None of the reports focused on the San Joaquin Valley’s agriculture, an industry of significance.
The story of the San Joaquin Valley has largely gone untold, being included as one chapter
within the history of the State of California. The drought has changed that, with the story of the
San Joaquin Valley, complete with interactive maps and high tech reader resources, published
almost weekly in the New York Times and other major media. The San Joaquin Valley has
become the focus of a national conversation. To better understand the impact of drought on the
San Joaquin Valley, and so to inform the national conversation, Fresno State conducted a
drought impact study in spring 2015, funded by the Wells Fargo Foundation.
The study was conducted by a selected team of faculty and staff at Fresno State, focused on the
goal of delivering usable information for public officials, private officials, and the general public,
on the range of impacts (economic, public health, municipal) resulting from the drought.
i
Chapter 1
Severity of the Drought and its Impact on Agriculture and
Use of Energy
Dr. Fayzul Pasha, Department of Civil and Geomatics Engineering
Abstract
The San Joaquin Valley of California is historically known for its agricultural production and
ranks as one of the highest agricultural producers in the world. It produces a wide variety of
crops, livestock, and poultry. Agriculture contributes significantly towards the economy of the
San Joaquin Valley (SJV). Adverse events in agriculture will result in multiple adverse effects in
the region’s economy, which can impact employment, population migration, and wage levels and
food prices which the most vulnerable residents can experience in the most direct and harshest
manner. For this reason, this study of the drought’s impact on agriculture and use of energy sets
the stage for this report.
Although there are numerous studies conducted on the economic impacts of the historical
droughts in California, there are a limited number of studies to assess the economic impact
focusing on the SJV. This study focuses on a key economic impact of the recent drought on the
SJV, specifically the impact on energy usage and agricultural revenue, in its eight counties
(Fresno, Kern, Kings, Madera, Merced, San Joaquin, Stanislaus, and Tulare).
Agriculture consumes a huge amount of water and energy. The availability of surface water,
which is directly affected by the amount of precipitation, is decreasing as a result of the lower
precipitation in recent years. A year that has the mean annual precipitation much lower than the
historical mean precipitation can be defined as a drought year. With this definition, a tremendous
drought has been affecting the SJV in recent years starting in 2012. This drought is not only
lowering the surface water availability but also affecting the groundwater depth, as there is not
enough surface water to recharge the groundwater basins. SJV agriculture is heavily dependent
on groundwater which needs to be pumped from a significant depth, causing high energy
consumption. It is therefore expected that the drought has a significant impact on energy
consumption.
By examining the historical trends related to precipitation, streamflow, reservoir water storage,
irrigation water use, and groundwater depth, the impact of the drought was assessed. Agriculture,
water, and energy usage are highly correlated. As noted, energy consumption increases from
heavier pumping as a result of lower groundwater levels, lower streamflow, and lower water
levels in lakes and reservoirs due to the drought. Therefore, this study is structured as follows:
1. Examining the impacts of drought on surface water availability including streamflow and
water storage in lakes and reservoirs and groundwater storage.
2. Examining the impacts of the above decreased surface water availability and groundwater
storage on agriculture and energy consumption.
1
3. Assessing the final impact of increased energy consumption on agricultural revenue.
Different statistical analysis including the correlation and regression analysis and geospatial
processing have been used to conduct this study.
Analysis shows that the last few years’ mean annual precipitations in all eight counties are about
30–60% lower than the historical means. This lower precipitation has a tremendous impact on
surface water availability in terms of streamflow and reservoir storage. Data from a total of
twenty (20) stream gauge locations has been analyzed, and it is found that streamflow at all of
these locations throughout the study area is significantly lower than the historical average.
Similarly to precipitation, the streamflow is about 30–60% lower than the historical average. The
historical reservoir storage data for the 10 largest reservoirs in the study area was analyzed. It is
found that in recent years, the reservoir levels are significantly lower than the historical average
storage. If future years’ precipitations are as low as 2014, the impact on reservoir storage will be
severe, ranging from 0.003 million acre-feet in Courtright Reservoir to 1.02 million acre-feet in
San Luis Reservoir in the month of February.
The impact of groundwater depth has been predicted considering precipitation amounts ranging
from 2 inches to 5 inches. If the drought continues, the groundwater depletion rate will be higher.
The higher depletion rate will cause additional change in the groundwater depth. If annual
precipitation is as low as 4 inches, the groundwater depths in each county will be lowered by
about 9.1 (Fresno), 21.5 (Kern), 13.9 (Kings), 15.1 (Madera), 5.5 (Merced), 8.3 (San Joaquin),
6.8 (Stanislaus), and 14.7 (Tulare) more feet per year than the historical rate of groundwater
change in each county. The additional groundwater depth will consume additional energy.2
Considering the Tulare basin low energy consumption estimate, this study found that if rainfall
in a given year is 4 inches, the additional energy requirement will be approximately 147,765
(Fresno), 51,013 (Kern), 60,722 (Kings), 27,616 (Madera), 71,661 (Merced), 60,735 (San
Joaquin), 70,072 (Stanislaus), and 133,877 (Tulare) megawatt-hours.
The impact on irrigation water usage has also been assessed, also using rainfall in a given year at
4 inches. Considering both surface and groundwater usage for irrigation, the total shortages in
millions gallons per day (mgd) may be approximately 1,337 (Fresno), 130 (Kern), 123 (Kings),
526 (Madera), 206 (Merced), 768 (San Joaquin), 370 (Stanislaus), and 377 (Tulare).
Accordingly, the yearly revenues from agricultural productions in these counties will suffer. For
the annual precipitation of 4 inches in a given year, the reduction in agricultural revenue in
billion dollars will be 0.676 (Fresno), 0.358 (Kern), 0.197 (Kings), 0.395 (Madera), 0.271
(Merced), 0.254 (San Joaquin), 0.220 (Stanislaus), 0.456 (Tulare). The total loss in agricultural
revenue will be $2,827,000,000 (Table 1).
It is important to note that population and other parameters that affect agricultural production,
water usage, energy consumption, and revenue were assumed to be constant in this study.
2
Editor’s note: “Groundwater depth” is used to indicate the depth from the land surface to the groundwater surface.
This use differs from the popular use of “groundwater depth” which is taken as a reference to the volume of the
groundwater: in that popular parlance, an increasing “depth” would indicate an increased groundwater supply.
2
SJV County
Fresno
Kern
Kings
Madera
Merced
San Joaquin
Stanislaus
Tulare
TOTAL
Increased
Groundwater
Depths (feet)
Additional Energy
Requirement
(megawatt hours)
9.1
21.5
13.9
15.1
5.5
8.3
6.8
14.7
94.9
147,765
51,013
60,722
27,616
71,661
60,735
70,072
133,877
623,461
Lower
Agricultural
Revenue (billions
of dollars)
0.676
0.358
0.197
0.395
0.271
0.254
0.220
0.456
2.827
Table 1 Estimated impact per year at 4 inches precipitation depth
3
1. Introduction
1.1 Background
The SJV is historically known for its agriculture and ranks as one of the highest agricultural
producers in the world. It produces a wide variety of crops, livestock, and poultry. While
agriculture contributes significantly towards the SJV economy, it also consumes a huge amount
of water and energy. Both surface and groundwater are heavily used in agricultural production
and as a consequence wield an effect on agricultural revenue.
The availability of surface water, which is directly affected by the amount of precipitation, is
decreasing as a result of the lower precipitation in recent years. A year that has the mean annual
precipitation much lower than the historical mean precipitation can be defined as a drought year.
With this definition, a tremendous drought has been affecting the SJV in recent years starting in
2012. This drought is not only lowering the surface water availability but also affecting the
groundwater depth, as there is not enough surface water to recharge the groundwater basins. This
scarcity of water will adversely impact the agricultural sector which is heavily dependent on
water, with the damage to agricultural revenue impacting the entire region.
1.2 Objectives
This study focused on the impact of the current drought on the SJV’s agriculture, specifically the
impact on agricultural water and energy usage and so on agricultural revenue, in the eight
counties of Fresno, Kern, Kings, Madera, Merced, San Joaquin, Stanislaus, and Tulare. By
examining the historical trends related to precipitation, streamflow, reservoir water storage,
irrigation water use, and groundwater depth, the impact of the drought was assessed.
4
2. Study Area and Data
2.1 Study Area
For the purposes of this study, the SJV study area consists of the eight counties: Fresno, Kern,
Kings, Madera, Merced, San Joaquin, Stanislaus, and Tulare.
2.2 Data
Historical data for different time ranges and resolutions were collected to evaluate the drought
impacts. Data sets include precipitation, streamflow, reservoir storage, groundwater depth,
irrigation water use, and, finally, agricultural revenue. The longest data set is that for
precipitation, which ranges from 1901 to March 2015. Each of these data sets is described below.
2.2.1
Precipitation Data
Monthly precipitation recorded by National Weather Service (2015) was collected from 28
stations throughout the SJV. The data was downloaded from the Weather Warehouse (2015).
Stations were chosen based on two criteria: proximity within the counties of interest and length
of record. It was expected that the stations would be spread throughout each county rather than
clumped in small clusters. It was required that each station should have at least 50 years of
historical data. Many of the chosen stations met and exceeded this requirement, with some
having records from as far back as 1900. The data of interest was the total precipitation for each
month. The total precipitation was a sum of all the precipitation events in a month in inches.
Figure 1 shows the locations of precipitation stations.
The data was processed to find the total annual precipitation (for the water year spanning
October to September) for each station first. Then it was further processed to find the average
annual precipitation of all the stations in each county, and then finally to calculate the mean
annual average precipitation for each county. Figure 1 below presents the Data Collection
Locations. Figure 2 to Figure 9 show yearly average precipitation and mean annual average
precipitation for each of the eight counties. The mean annual precipitation ± one standard
deviation is also shown on the figures to estimate the width of the statistical confidence bounds
and provide an assessment of drought. While Madera County has the highest mean annual
precipitation, Kern County has the lowest.
5
Figure 1 Data collection locations
6
Figure 2 Historical precipitation in Fresno County
Figure 3 Historical precipitation in Kern County
7
Figure 4 Historical precipitation in Kings County
Figure 5 Historical precipitation in Madera County
8
Figure 6 Historical precipitation in Merced County
Figure 7 Historical precipitation in San Joaquin County
9
Figure 8 Historical precipitation in Stanislaus County
Figure 9 Historical precipitation in Tulare County
10
2.2.2
Surface Water Data
Monthly mean streamflow data was collected from major rivers and streams within or near to the
study area. The majority of the streams studied were located in Stanislaus and Fresno counties,
primarily due to the availability of historical data. Total twenty (20) stream gauges maintained
and operated by the United States Geological Survey [USGS] (2015a) that have long historical
data lengths were considered for this study. Some of the stream gauges have data ranging from
1899 to 2014. Monthly mean streamflow data has been processed to calculate the historical
monthly mean for all the stream gauges and is shown in Table 2. (Figure 1 has shown the
locations of the stream gauges.)
USGS
Stream
gauge ID
11261100
11200800
11251000
11224500
11253310
11254000
11242400
11267350
11274000
11274500
11274630
11290000
11303000
11289000
11289650
11289500
11303500
11261100
11261500
11262900
Historical mean streamflow (cfs)
County
Kern
Tulare
Fresno
Fresno
Fresno
Fresno
Fresno
Fresno
Stanislaus
Stanislaus
Stanislaus
Stanislaus
Stanislaus
Stanislaus
Stanislaus
Stanislaus
San
Joaquin
Merced
Merced
Merced
Jan
Feb
Mar
Apr
May
Jun
Jul
Aug
Sep
Oct
Nov
Dec
68
49
672
13
7
822
29
9
2257
45
18
1828
1183
55
1434
82
93
66
962
22
10
1222
29
11
2993
82
31
2054
1219
87
1757
137
162
73
1094
19
12
1095
39
18
2929
45
22
2049
1361
298
1800
504
344
64
1663
9
4
1350
50
23
2954
21
9
1960
1483
642
1694
1022
424
41
1842
3
2
1912
78
29
2808
3
4
1949
1948
808
1570
1246
168
22
1639
1
1
1895
49
17
2146
1
2
1538
1356
876
814
1363
48
8
955
0
0
707
16
4
954
0
0
642
523
796
450
1334
23
4
542
0
0
351
6
1
519
0
0
382
383
655
249
1117
18
3
433
0
0
240
4
1
603
0
0
540
364
441
448
700
24
5
333
0
0
208
5
1
710
0
0
809
425
252
600
309
38
13
249
1
0
255
9
3
685
1
1
901
461
105
347
133
55
22
363
3
2
466
14
6
1153
11
4
1400
839
73
795
126
5051
6912
7269
7137
7590
6309
2577
1452
1760
2278
2262
3433
175
498
163
273
759
200
342
1400
183
230
1980
83
191
1175
57
189
930
54
204
297
50
204
232
44
135
188
35
139
180
91
166
197
105
138
199
119
Table 2 Statistics of historical monthly streamflow (cfs) in main rivers and streams
The ten largest surface water reservoirs within the study area were considered for this study. The
larger reservoirs tend to have more historical data available than the smaller reservoirs. The
reservoirs vary in size from approximately 13,000 acres to 1,100 acres. Most of the reservoirs are
located in Fresno County with others scattered in Tulare, Madera, Kern, and San Joaquin
Counties. Monthly storage data from 1940s to 2015 was collected from the California
Department of Water Resource’s data exchange center (CDEC) (DWR, 2015). Some of the data
sets begin in the late 1950s or early 1960s. The monthly storage data was processed to calculate
the historical mean monthly storage in each reservoir. Table 3 shows the calculated historical
mean monthly reservoir storage for each reservoir considered in this study. Figure 10 through 15
11
show the fluctuations of historical mean monthly storage for six of the reservoirs. The San Luis
reservoir is the largest reservoir studied, and the Success reservoir is the smallest. (Figure 1 on
has shown the locations of these reservoirs.)
Reservoir
Area
(ac)
Jan
Feb
Mar
Apr
May
Jun
Jul
Aug
Sep
Oct
Nov
Dec
San Luis
13,000
1.57
1.70
1.81
1.79
1.59
1.28
1.00
0.87
0.96
1.04
1.19
1.36
Isabella
11,400
0.16
0.17
0.18
0.21
0.27
0.29
0.25
0.19
0.17
0.15
0.14
0.14
Camanche
7,700
0.25
0.25
0.26
0.27
0.28
0.31
0.29
0.27
0.25
0.24
0.23
0.24
Pine Flat
5,970
0.44
0.49
0.52
0.57
0.68
0.66
0.48
0.36
0.33
0.33
0.36
0.40
Friant
4,900
0.31
0.31
0.33
0.34
0.39
0.41
0.32
0.23
0.20
0.18
0.20
0.26
Success
2,450
0.02
0.02
0.03
0.04
0.05
0.05
0.03
0.02
0.01
0.01
0.01
0.01
Terminus
1,945
0.02
0.02
0.04
0.08
0.12
0.10
0.05
0.02
0.01
0.01
0.01
0.02
Hidden
1,500
0.02
0.03
0.04
0.05
0.05
0.04
0.03
0.02
0.02
0.02
0.02
0.02
Courtright
1,480
0.04
0.04
0.04
0.05
0.08
0.09
0.09
0.07
0.06
0.05
0.05
0.05
970
0.04
0.04
0.04
0.05
0.09
0.10
0.09
0.08
0.07
0.06
0.05
0.04
Wishon
Table 3 Historical water storage in million acre-ft (M ac-ft) in major reservoirs
Figure 10 Water storage in Millerton Lake
12
Figure 11 Water storage in San Luis Reservoir
Figure 12 Water storage in Isabella Lake
13
Figure 13 Water storage in Camanche Reservoir
Figure 14 Water storage in Pine Flat Lake
14
Figure 15 Water storage in Lake Success
2.2.3
Groundwater Data
The groundwater depth data was collected from monitoring wells located throughout the study
area. For the county of Fresno, a total of 40 monitoring wells were chosen. For the seven other
counties, 30 monitoring wells were chosen from each county. Therefore, a total of 250
monitoring stations were chosen. While selecting the wells, emphasis was given to two criteria:
(1) the locations of the monitoring wells should be distributed as uniformly as possible and (2)
the length of the historical data should be around 50 years or longer. Data was downloaded from
the California State Water Resources Control Board (CSWRCB, 2015) website, including data
from 1921 to 2014. Some of the data set begins from late 1940s.
In any given year, the groundwater depth from a particular monitoring station was collected at
irregular intervals. This data was used to find the average groundwater depth in each year for
each monitoring well. This process was completed for all of the wells in each county. The county
yearly average groundwater depth for each year was then computed from the average depths at
all the monitoring stations in each county. In order to observe the historical change in
groundwater depth, a moving average over 10 year periods was then calculated. The difference
between the yearly average and moving average for a given year is a good indicator of
groundwater depletion or recharge. Yearly average depth to groundwater (“groundwater depth”)
higher than the moving average is an indicator of depletion. Similarly, yearly average
groundwater depth lower than the moving average is an indicator of groundwater recharge.
Table 4 lists the statistics on groundwater depth.
Figure 16 through 23 show the per-county yearly average and 10-year moving average
groundwater depths.
15
Number of
monitoring
wells used
Start year
Fresno
40
1921
Kern
30
Kings
Statistics
End year
Historical Average Depth (ft)
Min
Max
2014
10.4
65.3
1936
2014
3.4
304.4
30
1936
2014
9.7
138.5
Madera
30
1920
2014
23.6
171.6
Merced
30
1958
2014
18.0
45.0
San Joaquin
30
1947
2015
54.0
105.8
Stanislaus
30
1940
2014
29.4
63.6
Tulare
30
1921
2014
5.7
102.1
Table 4 Statistics of groundwater data
16
The line graphs for Figures 16-23 provide for each county a long-term trend line (dashed)
measuring the distance from the surface to the aquifer, with the surface represented by “0” depth
and the descent measured by negative numbers/feet:
Figure 16 Average depth to groundwater in Fresno County
Figure 17 Average depth to groundwater in Kern County
17
Figure 18 Average depth to groundwater in Kings County
Figure 19 Average depth to groundwater in Madera County
18
Figure 20 Average depth to groundwater in Merced County
Figure 21 Average depth to groundwater in San Joaquin County
19
Figure 22 Average depth to groundwater in Stanislaus County
Figure 23 Average depth to groundwater in Tulare County
20
2.2.4
Agricultural Data
Three types of agricultural data were collected:
1) groundwater water usage for irrigation,
2) surface water usage for irrigation, and
3) crop revenue.
Irrigation water usage data for 1985 to 2010 was collected from the USGS website (USGS,
2015b). For quality control, the data downloaded from the USGS website was compared with the
data presented in the California Water Plan (DWR, 2013a, 2013b, & 2013c). Table 5 lists mean
groundwater and surface water usage in million gallons per day (mgd), listed alongside each
county’s amount of irrigated land. Fresno, Kern, and Tulare counties use more water total
(surface and groundwater combined) for irrigation than the rest of the counties in the study area.
Groundwater Usage
County
Irrigated
land
(acres*103)
Start year
End year
Fresno
1093.78
1985
2010
Kern
737.79
1985
Kings
558.95
Madera
Mean
(mgd)
Surface Water Usage
Max
(mgd)
Min
(mgd)
Mean
(mgd)
Max
(mgd)
Min
(mgd)
1,149
1,640
707
1,951
2,574
1,765
2010
1,183
1,501
780
1,222
1,549
1,030
1985
2010
609
791
469
754
882
641
297.84
1985
2010
409
693
286
484
666
162
Merced
613.34
1985
2010
517
751
393
1,064
1,184
981
San Joaquin
740.77
1985
2010
498
727
83
1,064
1,576
903
Stanislaus
659.31
1985
2010
371
496
189
902
1,160
701
Tulare
974.67
1985
2010
1,153
1,432
986
1,005
1,269
443
Table 5 Irrigation water usage statistics
Crop revenue data was collected from annual agricultural crop reports. As required by the State
of California, counties must produce and make available these reports.3 The county reports are
available online from the websites for all of the eight counties in the study area. The data covers
3
The State of California Food and Agricultural Code requires county Ag Commissions the work to compile, record,
report, and make available information on the gross production and value of crop and livestock. The State of
California does not duplicate this effort but instead works closely with the counties to complete this effort. State
reporting is aligned with federal reporting (see USDA National Agricultural Statistics Service:
http://www.nass.usda.gov/Data_and_Statistics/index.asp). Table 5: Fresno County Agricultural Commissioner,
2015; Kern County Department of Agriculture and Measurement Standards, 2015; Kings County Department of
Agriculture/Measurement Standards, 2015; Madera County Department of Agriculture, 2015; Merced County
Department of Agriculture, 2015; San Joaquin County Office of the Agricultural Commissioner, 2015; Stanislaus
County Agricultural Commissioner & Weights and Measures, 2015; Tulare County Agricultural
Commissioner/Sealer, 2015
21
from 1950 to 2013. The total revenue value for each county was calculated from the rounded
sum of the revenue from all agricultural products including fruit and nuts, field crops, vegetables,
nursery crops, industrial and wood crops, seeds, livestock, and poultry. In total agricultural
revenue, Fresno, Tulare, and Kern counties consistently rank significantly higher than the other
counties included in this study. The top individual sources of revenue for each county are Fresno:
almonds; Tulare: milk; and Kern: grapes.
Table 6 lists statistics on crop revenue for all counties in billions of dollars ($B). For fair
comparison, all the yearly revenues are converted into their present values in 2015 considering a
historical inflation rate of 3.32%. Generally the agricultural revenue increases over time, with
some exceptions. However the rate of increase in the revenue may not be consistent each year.
To observe this rate of increment in different years, a 5-year moving average has been calculated
and compared with the yearly revenue. The yearly revenue and the moving average for each
county are depicted in Figure 24 and Figure 25.
Statistics
Fresno
Kern
Kings
Madera
Merced
San Joaquin
Stanislaus
Tulare
Start year
End year
Historical
mean ($B)
Max
($B)
Min
1950
1950
1950
1999
1974
1950
1950
1950
2013
2013
2013
2013
2013
2013
2013
2013
4.52
3.10
1.28
1.46
2.59
1.81
1.83
3.64
7.76
7.23
2.53
2.02
4.06
3.25
3.91
8.34
2.06
1.37
0.48
1.03
1.33
0.99
0.78
1.61
Yearly revenue in recent years ($B)
2010
2011
2012
2013
7.00
7.76
7.27
6.87
5.60
6.11
7.01
7.23
2.02
2.53
2.44
2.42
1.59
1.79
1.92
2.02
3.22
3.71
3.62
4.06
2.31
2.55
3.25
3.12
3.03
3.50
3.60
3.91
5.73
6.42
6.85
8.34
Table 6 Statistics of agricultural revenue (all numbers are calculated in 2015 dollars)
Figure 24 Yearly revenue in Fresno, Kings, Madera, and Tulare counties (all values in 2015 dollars)
22
Figure 25 Yearly revenue in Kern, Merced, San Joaquin and Stanislaus counties (all values in 2015
dollars)
3. Impact Analysis
3.1 Impact on Surface Water Availability
The impact of drought on surface water availability was evaluated by looking at three different
data sets: precipitation, streamflow, and reservoir storage. Table 7 compares the mean annual
precipitation with the total yearly precipitation in recent years (2010–2014) for each county,
(noting also the standard deviation/Stdev and the coefficient in variation/CV). While 2010 and
2011 are shown to be wet years, 2012 to 2014 were dry years. The yearly precipitation in these
dry years was found to be even lower than the lower bound of the confidence interval (less than
one-third of the normal level) for most of the counties, indicating drought conditions. 4 As
precipitation is the main source of water, decreased precipitation can be expected to have adverse
impacts on streamflow and reservoir storage.
4
In plain English, the “confidence interval” is the range (more or less) that the findings might fluctuate.
23
Statistics
Fresno
Kern
Kings
Madera
Merced
San Joaquin
Stanislaus
Tulare
Total
Rainfall
Station
Start
year
End
year
Mean
(in)
Stdev.
(in)
CV
4
3
4
2
3
4
2
6
1912
1901
1900
1904
1900
1900
1906
1900
2015
2015
2015
2015
2015
2015
2015
2015
12.0
5.7
6.0
23.7
9.1
13.4
10.7
14.1
4.9
5.6
3.1
10.0
3.6
6.2
4.6
6.6
0.4
1.0
0.5
0.4
0.4
0.5
0.4
0.5
Yearly Precipitation (in)
2010
2011
2012
2013
2014
14.2
6.6
9.2
28.2
11.5
14.9
14.5
18.2
20.5
7.9
12.1
26.4
12.0
17.1
14.5
24.0
9.4
3.8
5.0
5.8
5.8
7.5
7.6
11.4
6.6
2.6
4.2
9.0
4.7
8.0
4.5
8.4
3.5
2.0
2.2
8.4
3.3
5.7
5.4
5.7
Table 7 Historical rainfall
To observe the impact of drought on streamflow, historical mean monthly streamflow has been
plotted with recent years’ streamflow on the same figure (2010–2013 or 2010-2014, depending
on available data). Sample plots are shown in Figure 26 to Figure 31. As expected, the drought
has a tremendous adverse impact on streamflow, as shown by mean monthly flow lower than the
historical mean for the years shown at each stream gauge location. The streamflow was found to
be directly related to the precipitation as shown by lower streamflow from 2012 to 2014, the
worst three years of the drought, versus the higher streamflow in 2011, which had the highest
precipitation levels in 2010-2015.
Figure 26 Monthly mean streamflow at USGS 11251000 San Joaquin in Fresno County
24
Figure 27 Monthly mean streamflow at USGS 11254000 San Joaquin in Fresno County
Figure 28 Monthly mean streamflow at USGS 11261100 Salt Slough in Kern County
25
Figure 29 Monthly mean streamflow at USGS 11261100 Salt Slough in Merced County
Figure 30 Monthly mean streamflow at USGS 11303500 San Joaquin in San Joaquin County
26
Figure 31 Monthly mean streamflow at USGS 11274000 San Joaquin in Stanislaus County
27
Similarly to streamflow, the historical mean monthly reservoir storage was plotted with recent years’ monthly storage on the same
figure (Figure 26 to Figure 31) in order to observe the impact on storage. Storage in recent years was found to be significantly lower
than the historical mean. An attempt was made to calculate the likely water shortage in coming years. This calculation is based on the
assumption that the amount of precipitation in 2015 will be same as the amount of precipitation in 2014. These likely reservoir water
shortages for all of the studied reservoirs are listed in Table 8.
Note: Positive numbers in the table represent water shortage, and negative numbers represent atypical higher storage than the
historical mean.
Reservoir
San Luis
Isabella
Camanche
Pine Flat
Friant
Success
Terminus
Hidden
Courtright
Wishon
Area (ac)
13,000
11,400
7,700
5,970
4,900
2,450
1,945
1,500
1,480
970
Jan
0.959
0.099
0.033
0.265
0.110
0.010
0.009
0.019
0.004
-0.003
Feb
1.022
0.106
0.049
0.297
0.147
0.016
0.006
0.024
0.003
-0.007
Mar
0.958
0.122
0.072
0.302
0.165
0.022
0.012
0.034
0.007
-0.016
Apr
0.834
0.146
0.095
0.266
0.111
0.029
0.021
0.039
0.005
-0.019
May
0.741
0.193
0.133
0.254
0.069
0.038
0.035
0.040
-0.012
0.035
Jun
0.623
0.216
0.163
0.304
0.080
0.036
0.058
0.036
0.000
0.058
Jul
0.543
0.188
0.149
0.340
0.043
0.022
0.024
0.026
0.051
0.009
Aug
0.492
0.140
0.135
0.241
-0.002
0.013
-0.001
0.018
0.015
0.039
Sep
0.498
0.118
0.118
0.211
0.012
0.008
-0.005
0.015
0.024
0.022
Oct
0.649
0.102
0.105
0.221
0.004
0.005
-0.003
0.012
0.017
0.020
Table 8 Likely water storage shortage in million acre-feet (M ac-feet) in major reservoirs
28
Nov
0.698
0.095
0.109
0.239
0.029
0.005
-0.003
0.011
0.018
0.013
Dec
0.540
0.100
0.101
0.272
0.077
0.008
-0.006
0.012
0.015
0.007
3.2 Impact on Groundwater Depth
The historical change in groundwater depth was calculated by subtracting the county yearly
average groundwater depth from 10-year moving average depth. This change in groundwater
depth data was correlated with the total precipitation to observe the relationship between
precipitation and groundwater recharge or depletion. The precipitation data was lagged from 0 to
4 years. While zero year lag refers the relationship in the same year, the 4 year lag refers to the
relationship between the precipitation that occurred 4 years ago and the current year’s
groundwater depth change. A linear relationship was assumed. It was also assumed that the water
usage for all purposes will remain the same.
Table 9 lists the linear model coefficients for the best model for each county, which is defined as
the model that has the highest correlation coefficient (CC).5 Note: A positive number indicates
depletion and a negative number indicates recharge.
Figure 32 to Figure 39 show the relationship between the groundwater change and the total
precipitation for each county with a best fit linear model.
County
CC
Fresno
Kern
Kings
Madera
Merced
San Joaquin
Stanislaus
Tulare
0.65
0.45
0.58
0.50
0.45
0.50
0.62
0.45
Lag
year
1
1
1
1
1
1
1
0
Intercept
11.88
38.04
22.79
16.93
7.40
10.29
8.98
16.97
Slope
-0.70
-4.13
-2.23
-0.45
-0.47
-0.49
-0.55
-0.66
Table 9 Coefficients in the groundwater depth prediction models
5
A high “correlation coefficient” indicates that the strength and direction of the linear relationship is very good.
29
Figure 32 Relationship between average groundwater depth and
total annual precipitation in Fresno County
Figure 33 Relationship between average groundwater depth and
total annual precipitation in Kern County
30
Figure 34 Relationship between average groundwater depth and
total annual precipitation in Kings County
Figure 35 Relationship between average groundwater depth and
total annual precipitation in Madera County
31
Figure 36 Relationship between average groundwater depth and
total annual precipitation in Merced County
Figure 37 Relationship between average groundwater depth and
total annual precipitation in San Joaquin County
32
Figure 38 Relationship between average groundwater depth and
total annual precipitation in Stanislaus County
Figure 39 Relationship between average groundwater depth and
total annual precipitation in Tulare County
33
The linear model coefficients (Table 9) were used to calculate the predicted change in the
average groundwater depth for a given total precipitation in a year. Considering recent
precipitation trends, the annual total precipitation was assumed to be from two to five inches.
Table 10 shows the impacts of these amounts of precipitation on groundwater depth in each
county. As expected the change is greater with lower precipitation. The highest change in
groundwater depth is predicted in Kern County, and the lowest change in groundwater depth is
predicted in Merced County for all precipitation amounts.
Figure 40 depicts the impacts of total precipitation on the change in average groundwater depth
by county.
Change in depth to groundwater level (ft) at
given precipitation (in)
County
Fresno
Kern
Kings
Madera
Merced
San Joaquin
Stanislaus
Tulare
Irrigated land
(acres*103)
1093.78
737.79
558.95
297.84
613.34
740.77
659.31
974.67
2 in.
3 in.
4 in.
5 in.
10.5
29.8
18.3
16.0
6.5
9.3
7.9
15.7
9.8
25.6
16.1
15.6
6.0
8.8
7.3
15.0
9.1
21.5
13.9
15.1
5.5
8.3
6.8
14.3
8.4
17.4
11.6
14.7
5.0
7.8
6.2
13.7
Table 10 Predicted change in groundwater depth
34
Figure 40 Impact of total precipitation on the change in average groundwater depth.
35
3.3 Impact on Agriculture
The drought impact on three important sectors of agriculture was assessed:
1) energy usage,
2) total irrigation water usage, and
3) agricultural revenue.
Each of them is described below.
3.3.1
Impact on Energy Usage
It is expected that the drought will increase the groundwater depth assuming that groundwater
usage and other parameters will remain the same. As groundwater depth increases, the energy
consumption required for pumping also increases. Considering the impact of the drought on
groundwater depth (Table 10), the additional energy required for pumping can be calculated.
Yeasmin and Zoldoske (2014) used low and high estimates of average energy consumption to
determine the energy consumption for pumping in California. The low and high estimates are
based on an analysis made by the California Public Utility Commission (CPUC). The average
low and high estimates of energy consumption are 283 and 431 kWh to lift one acre-foot of
groundwater in the Tulare region. The same assumption has been used in this study. Again
following Yeasmin and Zoldoske, annual use of 3.1 acre feet of groundwater was assumed.
Table 11 and Table 12 list the predicted additional energy requirements in megawatt-hours
(mWh) due to the drought. The impact is also depicted on a map in Figure 41 and Figure 42.
Additional energy requirement (mWh)
at given precipitation (in)
County
2 in.
3 in.
4 in.
5 in.
Fresno
170,532
159,149
147,765
136,381
Kern
70,618
60,815
51,013
41,210
Kings
80,290
70,506
60,722
50,938
Madera
29,251
28,433
27,616
26,798
Merced
83,928
77,794
71,661
65,527
San Joaquin
67,862
64,298
60,735
57,171
Stanislaus
81,420
75,746
70,072
64,398
Tulare
146,176
140,027
133,877
127,728
Table 11 Predicted additional energy requirement (mWh) for pumping groundwater
based on Tulare Basin Low Estimate (283 kWh to life one ac-ft of groundwater)
36
Additional energy requirement (mWh)
at given precipitation (in)
County
2 in.
3 in.
4 in.
5 in.
Fresno
259,715
242,378
225,041
207,704
Kern
107,549
92,620
77,690
62,761
Kings
122,280
107,378
92,477
77,576
Madera
44,549
43,303
42,058
40,813
Merced
127,820
118,478
109,137
99,795
San Joaquin
103,352
97,925
92,497
87,069
Stanislaus
124,000
115,359
106,717
98,076
Tulare
222,622
213,256
203,891
194,525
Table 12 Predicted additional energy requirement (mWh) for pumping groundwater
based on Tulare Basin High Estimate (431 kWh to life one ac-ft of groundwater)
37
Figure 41 Impact of precipitation on additional energy requirement for pumping groundwater
Tulare Basin Low Estimate
38
Figure 42 Impact of precipitation on additional energy requirement for pumping groundwater
Tulare Basin High Estimate
39
3.3.2
Impact on Irrigation Water Usage
To observe the historical relationships between irrigation water usage and total precipitation,
scatter plots have been plotted. As with the groundwater impact analysis, a zero to four year lag
in precipitation data was used to observe the best relationship. It was found that a linear model
can describe the relationship between irrigation water usage and mean annual precipitation. The
relationship between surface water usage and precipitation and between groundwater usage and
precipitation were both found to be linear. Table 13 and Table 14 list the linear prediction model
parameters used for calculating both for groundwater and surface water future usage (see Table
15 and 16 on next page).
County
Lag year
CC
Intercept
Slope
Fresno
2
0.928
229.16
52.85
Kern
2
0.572
855.45
55.49
Kings
2
0.810
254.15
61.71
Madera
4
0.464
143.80
12.04
Merced
3
0.831
241.44
41.70
San Joaquin
2
0.773
77.91
22.00
Stanislaus
2
0.845
152.75
14.02
Tulare
4
0.330
1077.22
3.97
Table 13 Coefficients in groundwater use (for irrigation) prediction models
County
Lag year
CC
Intercept
Slope
Fresno
4
0.614
1049.55
68.04
Kern
3
0.444
917.16
70.17
Kings
3
0.444
917.16
70.17
Madera
3
0.771
101.68
18.29
Merced
2
0.935
905.80
15.16
San Joaquin
4
0.674
480.63
37.07
Stanislaus
4
0.501
596.09
24.69
Tulare
3
0.561
562.79
31.35
Table 14 Coefficients in the surface water use (for irrigation) prediction model
40
The linear models were used to predict surface and groundwater usages for total precipitation
ranging from 2 to 5 inches. Average historical irrigation water usages were then used to calculate
the water shortage at each precipitation amount. The model parameters listed above and the
procedure mentioned here can be used predict the water shortage for any precipitation depth.
Table 15 and 16 list the predicted water shortages at different precipitation amounts. These
impacts are mapped in Figure 43 and Figure 44.
Table 17 lists the total water shortage from adding groundwater shortage and surface water
shortage. Figure 45 depicts in a plot and Figure 46 depicts in a map the total irrigation water
shortage. As expected, the water shortage is higher when precipitation is lower.
Predicted water shortage (gpd/acre)1
at given precipitation (in)
County
2 in.
3 in.
4 in.
5 in.
Fresno
1093.78
744
696
647
599
Kern
737.79
293
218
143
67
Kings
558.95
415
304
194
83
Madera
297.84
809
769
728
688
Merced
613.34
313
245
177
109
San Joaquin
740.77
508
479
449
419
Stanislaus
659.31
289
268
247
225
Tulare
974.67
70
66
62
58
1
“gpd” = gallons per day and “mgd” = million gallons per day.
Irrigated land
(acres*103)
Predicted water shortage (mgd)1
at given precipitation (in)
2 in.
3 in.
4 in.
5 in.
814
761
708
655
216
161
105
50
232
170
108
47
241
229
217
205
192
150
109
67
377
355
333
311
191
177
163
149
68
64
60
56
Table 15 Predicted groundwater shortage for irrigation
Predicted water shortage (gpd/acre)1
at given precipitation (in)
County
2 in.
3 in.
4 in.
5 in.
Fresno
1093.78
699
637
575
513
Kern
737.79
224
128
33
62
Kings
558.95
182
105
27
50
Madera
297.84
1160
1098
1037
975
Merced
613.34
208
184
159
134
San Joaquin
740.77
687
637
587
537
Stanislaus
659.31
389
351
314
276
Tulare
974.67
390
358
325
293
1
“gpd” = gallons per day and “mgd” = million gallons per day.
Irrigated land
(acres*103)
Predicted water shortage (mgd)1
at given precipitation (in)
2 in.
3 in.
4 in.
5 in.
765
697
629
561
165
95
25
46
102
58
15
28
345
327
309
291
128
113
97
82
509
472
435
398
256
232
207
182
380
348
317
286
Table 16 Predicted surface water shortage for irrigation
41
Figure 43 Impact of precipitation on groundwater shortage for irrigation
42
Figure 44 Impact of precipitation on surface water shortage for irrigation
43
County
Irrigated land
(acres*103)
Predicted water shortage (gpd/acre)1
at given precipitation (in)
Predicted water shortage (mgd)1
at given precipitation (in)
2 in.
3 in.
4 in.
5 in.
2 in.
3 in.
4 in.
5 in.
Fresno
1093.78
1443
1333
1222
1112
1579
1458
1337
1216
Kern
737.79
516
346
176
129
381
255
130
95
Kings
558.95
597
409
221
134
333
228
123
75
Madera
297.84
1969
1867
1765
1663
586
556
526
495
Merced
613.34
522
429
336
243
320
263
206
149
San Joaquin
740.77
1196
1116
1036
957
886
827
768
709
Stanislaus
659.31
678
619
560
502
447
408
370
331
Tulare
974.67
460
423
387
351
448
413
377
342
1
“gpd” = gallons per day and “mgd” = million gallons per day.
Table 17 Predicted total irrigation water shortage
Figure 45 Predicted total irrigation water shortage for different total annual precipitation
44
Figure 46 Impact of precipitation on total irrigation water shortage
45
3.3.3
Impact on Agricultural Revenue ($B)
The historical yearly revenue, calculated at today’s (2015) prices at an inflation rate of 3.32%,
shows a general trend of increase as time progresses (Figure 24 and Figure 25). However, the
rate of increase in revenue is not consistent throughout the period from approximately 1950 to
2013. To observe this rate in different years a five-year moving average was calculated and
compared with the yearly revenue. The difference between yearly revenue and the five-year
moving average indicates the relative change in revenue for a particular year. A positive number
indicates relative reduction in revenue and negative indicates relative increase in the revenue.
Again, revenues are given in billions of dollars.
There are many parameters that can contribute towards the change of rate of revenue increase.
However water was considered to be the most important one as water directly affects the
agricultural production. As such, the relationship between the relative change in yearly revenue
and total mean annual precipitation was observed for all the counties. Figure 47 to Figure 54
show these relationships for different counties.
Figure 47 Relationship between relative change in yearly revenue and
total mean annual precipitation in Fresno County
46
Figure 48 Relationship between relative change in yearly revenue and
total mean annual precipitation in Kern County
Figure 49 Relationship between relative change in yearly revenue and
total mean annual precipitation in Kings County
47
Figure 50 Relationship between relative change in yearly revenue and
total mean annual precipitation in Madera County
Figure 51 Relationship between relative change in yearly revenue and
total mean annual precipitation in Merced County
48
Figure 52 Relationship between relative change in yearly revenue and
total mean annual precipitation in San Joaquin County
Figure 53 Relationship between relative change in yearly revenue and
total mean annual precipitation in Stanislaus County
49
Figure 54 Relationship between relative change in yearly revenue and
total mean annual precipitation in Tulare County
A linear model with relative change in revenue as dependent variable and mean annual
precipitation as independent variable was found to be the best fit to describe these relationships.
Table 18 lists the prediction model parameters used to calculate future reductions agricultural
revenues.
Table 19 lists the predicted reductions in agricultural revenue due to lower precipitation. Figure
55 maps the predicted reductions in revenues due to lower precipitation. The reduction in
revenue due to lower precipitation was found to be highest for the County of Fresno.
County
Fresno
Kern
Kings
Madera
Merced
San Joaquin
Stanislaus
Tulare
CC
0.50
0.39
0.62
0.63
0.42
0.43
0.45
0.57
Lag year
3
0
4
4
0
3
3
3
Intercept
0.868
0.622
0.406
0.449
0.373
0.315
0.284
0.553
Slope
-0.048
-0.066
-0.052
-0.013
-0.026
-0.015
-0.016
-0.024
Table 18 Coefficients in agricultural revenue prediction models
50
County
Fresno
Kern
Kings
Madera
Merced
San Joaquin
Stanislaus
Tulare
TOTAL
2 in.
0.772
0.490
0.302
0.422
0.322
0.285
0.252
0.505
3.35
3 in.
0.724
0.424
0.249
0.409
0.297
0.269
0.236
0.481
3.089
4 in.
0.676
0.358
0.197
0.395
0.271
0.254
0.220
0.456
2.827
5 in.
0.628
0.291
0.144
0.382
0.245
0.239
0.203
0.432
2.564
Table 19 Predicted reduction in yearly agricultural revenues ($B at today’s price) at given precipitation
amount (in)
51
Figure 55 Impact of precipitation on yearly revenue reduction at today’s price ($B)
52
SNAPSHOT: IS THERE A “CENTRAL” VALLEY?
By G. Harootunian, PhD
The preceding chapter measures the billions of dollars in costs to farm revenue from the
drought in the SJV. But is there a “Central Valley” farm? A “San Joaquin Valley” farm?
What qualitative differences are there among categories of farms, for example a giant
agribusiness; a modest family-owned farm; a limited resource minority/immigrant
farmer; and a farmer with senior and land-inherited water rights?
The intent of the U.S. Bureau of Reclamation limiting federal water supply availability to
farms of 160 acres or less was a democratizing one. What is the value to be assigned to
preserving the model of democratized agriculture or encouraging new entrepreneurs
versus other models, including those involving the national food supply or global
competitiveness? To what extent should the dialogue about the future of water in the SJV
include the qualitative differences among farms within the SJV?
“West Side” farmers versus “East Side” farmers exemplify this issue. The “East Side”
was farmed early and eagerly for good reason: the rivers of the Sierra Nevada Mountains
cascaded down every spring, at times roaring and deep, and watered the lands. The “West
Side” however was harshly dry. In the “Largest Alteration of the Earth’s Surface,” USGS
researchers describe water sources for the West Side as “intermittent and ephemeral,
flowing only episodically.”
West Side
East Side
Westlands Water District - Largest
Friant Water Authority – Large coalition of
agricultural water authority in the U.S.
smaller, family farms.
Farms served: About 700
Farms served: About 15,000
Average size of farms: 875 acres
Average size of farms: 20-200 acres
Typical Labor: The 875-acre farm would Typical Labor: The 100-acre farm would
have permanent labor (e.g., farm
have family members working it, with farm
managers), with farm workers (including workers (including crop workers) secured
crop workers) secured from contractors at from contractors at peak demand times, such
peak demand times, such as harvest.
as harvest.
Portrait of a West Side Emperor
The King of California is a 531-page book detailing the rise of a secret American empire:
the J.G. Boswell Company. J.G. Boswell II was the biggest private farmer in U.S. His
family travelled due west from their old plantation in Georgia to the SJV and built what
was to be California’s first giant agribusiness model (estimates range from 150,000200,000 acres). Boswell and another giant, Clarence “Cockeye” Salyer, dominated the
Westlands Water District for years. Boswell’s agribusiness was so huge he is also
credited with dominating the Tulare Water District.
Portrait of Well-Being
When Measure of America published its groundbreaking report on the well-being of
Americans in 2008, the 20th congressional district, which included the Westlands Water
District, ranked at the absolute bottom of the list. California saw re-districting for the
2012 elections, and the 21st congressional district now includes the Westlands Water
District. For 2013-2014, the state of California had both the lowest and the highest scores
for the nation: 3.04 (congressional district 21) and 8.18 (congressional district 18, the San
Francisco Bay Area).
53
THE VINEYARD: Launched by Richard Erganian, the son of Armenian immigrants, farmers, and entrepreneurs, The Vineyard farmers’
market offers local produce. Its farmers typify the smaller “East Side” farmer. Photographer Cary Edmondson offers a ‘window’ into their
world on the next few pages.
Sun Smiling Valley Farm – Farmers Juro Watanuki and Nine Abe from
Sanger selling another pound of their variety of mushrooms.
Top of the Hill – This farmer, jam-maker, and pickler from
Reedley puts up handmade signs for that week’s harvest.
Thao Produce – This family is one of many Hmong
immigrant families who started small farms in Fresno.
54
Vine Ripe Farms – Rocio and Agustin Agraz run this family farm in Hanford, CA
Triple Delight Blueberries – Three daughters of the Sorenson
family (raisin growers) operate this 20-acre farm in
Caruthers, CA
Berry Lady Farms - Farmer Gayle Willems with her son Matt
and daughter-in-law Cassie, pastry chef, operate this family
farm growing blueberries, blackberries, and boysenberries in
Kingsburg, CA.
55
Mediterranean To Go – Maha Muhawi and husband Ellias sell
Mediterranean specialty dishes (many of which are now Fresnan,
too).
Ms. Felix Muzquiz, Executive Director of The Vineyard, sports
her signature farmer’s hat and smile.
MOA – The 10-acre Oasis Garden in Clovis embodies the
philosophy and methods of Nature Farming created by Mokichi
Okada. The Mokichi Okada Association (MOA) carries on the
founder’s system of shizen nōhō (“no fertilizer farming”). Above is
Bruno Luconi who operates the Oasis Garden as a form of art.
K.M.K. Organic Farms – This 70 acre organic farm in
Kingsburg, CA sells a range of produce.
56
Switching to Almonds:
A Video Narrative of Drought Impact on Farming and People
By Jes Therkelsen, MFA, Department of Mass Communication and Journalism
Russ Wilson, a fourth generation farmer in Fowler, California, decides to plant almonds
on 35 acres of his 120-acre farm. Russ is an “East Sider” though his switch to almonds is
common throughout the SJV. The reason is simple: farmers have long switched to
higher-value crops during droughts. Crop substitutions and crop introductions are a
typical and a critical response to water markets.
Some recent media coverage has pointed out almonds need twice the amount of water as
do grapes, the traditional crop of the SJV. Almonds do not produce any fruit for three
years, during which time they need to be watered. They are also a permanent crop,
meaning once farmers plant almonds, they stay in the ground for 20–30 years, needing
water constantly. Annual plants (ex. lettuce) are not permanent, and lettuce fields can be
let fallow, for short or long periods of time. These reasons make it easy to criticize
almonds and the farmers who decide to plant them.
In this video vignette, you can follow Russ as he watches all of his neighbors tear up
their fields and plant almonds. Faced with the financial responsibility to maintain his
business as a viable entity, Russ knows he must diversify, and almonds are the direction
he decides to go in.
https://vimeo.com/124495171. Password: almonds
“The law of the land and the custom has been you can use the water you need on your
own land as much as you need. That’s our history.” Russ Wilson, 4th generation
farmer (from Scotland to the San Joaquin Valley).
57
Chapter 2
The Economic Impact of the Drought in the California San
Joaquin Valley: An Expanded Look
Dr. Antonio Avalos, Department of Economics
Abstract
This segment of the report aims at expanding the scope of the UC Davis Study (Howitt,
Medellín-Azuara, MacEwan, Lund, & Sumner, 2014)6 in four areas critical to understanding the
economic impact of the drought in the San Joaquin Valley (SJV) by:
1. Focusing on the San Joaquin Valley eight counties (Fresno, Kern, Kings, Madera,
Merced, San Joaquin, Stanislaus and Tulare).
2. Examining the possibility that in addition to a decline in farm employment as
consequence of the drought, the observed reduction in household income is due to farm
workers working fewer hours per day, fewer days per week, and receiving a lower wage
rate.
3. Exploring the economic impact of the drought in selected cities within each of the SJV
counties, paying particular attention to a selected list of Disadvantaged Communities
(DACs).
4. Assessing the impact of the drought on food prices and its impact on low-income
households.
Unemployment and Median Household Income (MHI) data at the county level conceal valuable
and useful information that only becomes apparent when examining more refined geographical
units. Thus this segment also examines available data at the city level, with particular emphasis
on Disadvantaged Communities (DACs). The findings indicate that the observed fall in the MHI
in some counties and in most disadvantaged communities during the drought years is due to a
combination of job loss, lower hourly wage, and lower annual wages paid to farm workers, as
well as working fewer days per year. The evidence also suggests that as a consequence of the
drought some workers migrated to locations outside the SJV, possibly in pursuit of better
working and living conditions. These patterns could at least partially explain why the MHI is
falling at the same time that the unemployment rate is decreasing. In addition, although it is not
totally clear at what extent overall food prices will go up as consequence of the drought, the data
indicates that the price of some food items has increased during the dry years. This is relevant
from the consumer perspective, particularly for low-income households that spend a larger share
of their income on food, because a surge in food prices can significantly impact their disposable
income.
6
Economic analysis of the 2014 drought for California agriculture. This Study is the first of three reports released
by UC, Davis on the economic analysis of the drought’s impact on California agriculture. The subsequent two are a
preliminary report of the economic impact on agriculture in all 25 counties of the Central Valley (2014, May 19) and
a preliminary economic analysis of the 2015 drought’s impact on California agriculture (2015, May 31). .
58
Unemployment and Household Median Income (MHI) in the SJV
During the past three years, unemployment rates at the county level in the SJV have shown a
declining trend. Although no county has returned to the unemployment rate levels before the
2007–2009 Great Recession (when this rate averaged 8%), it is not evident that the ongoing
drought has caused unemployment rates to increase. Figure 1 below illustrates this falling
unemployment trend during the drought years of 2012, 2013, and 2014 (shadowed rectangle).7 It
is important to notice that although unemployment rates have declined in recent years in SJV
counties, at the State level the unemployment rate is still much lower, currently at 7%. This
indicates that SJV counties are still lagging behind the state unemployment rates and, apparently,
the drought does not help to close the gap.
20.0%
18.0%
16.0%
14.0%
12.0%
10.0%
8.0%
6.0%
4.0%
2.0%
0.0%
2006
2007
2008
2009
2010
2011
2012
Fresno
Kern
Kings
Madera
Merced
San Joaquin
Stanislaus
Tulare
2013
2014
Figure 1 Unemployment Rates in SJV Counties (2006-2014)8
(California Employment Development Department [CA EDD], 2015a)
7
The UC Davis Study (2014) mentioned 17,100 jobs lost, which represents a small percentage of total employment
in the region (p. 9). Even if all those jobs were lost in the SJV, which is a radical assumption since the UC Davis
Study defines the Central Valley as comprising 25 counties, they would only represent around 1% of total
employment in the SJV counties at the end of 2014. In other words, annual unemployment rates at the county level
do not capture unemployment variations of such magnitude, particularly when other economic recovery factors are
driving the unemployment rate down.
8
Shadow indicates drought years (2012, 2013, and 2014).
59
In terms of the median household income (MHI) at the county level, the data portray a mixed
record. First, however, it must be noted that Table 1 shows overall that with the exception of San
Joaquin County, the average MHI in all eight counties is below the $48,706 threshold required to
be classified as a Disadvantaged Community (DAC)9, even including those counties where the
MHI increased during dry years. This categorization suggests that in terms of MHI, the San
Joaquin Valley as a whole is a region in economic distress. That is the context within which
recent and increasing declines in MHI are taking place.
Table 1 shows for four counties, following a seemingly counterintuitive trend, the MHI increased
during the drought years of 2012 and 201310 (Fresno, Kern, San Joaquin and Stanislaus) while it
fell for four counties (Kings, Madera, Merced and Tulare). Although numerous economic and
non-economic factors can explain the behavior of the MHI, this difference partially reflects that
counties with a more diversified industrial base (which are thus less dependent on agriculture)
also have economies that are more resilient during dry conditions. In the case of Tulare County
for example, where agriculture represents a core industry sector, in 2013 the MHI fell to $39,422
from its peak of $43,397 (in 2011). This represents a significant fall in income of more than 9%
in only 3 years. Similarly in Madera, the MHI fell to $39,758, which is below the $44,975 level
it had at the onset of the 2007–2009 Great Recession, representing an income reduction of more
than 11% in 6 years.
County
2006
2007
2008
2009
2010
2011
2012
2013
Fresno
$42,732
$47,298
$43,737
$45,661
$45,221
$42,807
$41,627
$43,925
Kern
$43,106
$47,105
$44,733
$47,368
$45,524
$45,224
$45,910
$46,879
Kings
$43,178
$46,756
$50,962
$44,506
$44,609
$50,345
$45,935
$45,774
Madera
$39,068
$44,975
$47,394
$44,135
$48,268
$46,570
$42,039
$39,758
Merced
$40,447
$44,410
$42,303
$39,535
$42,449
$40,055
$43,597
$40,687
San Joaquin
$51,951
$52,470
$54,882
$52,789
$50,011
$50,853
$50,722
$51,432
Stanislaus
$48,566
$50,616
$50,359
$48,716
$48,044
$44,076
$46,405
$47,962
Tulare
$41,933
$40,595
$45,117
$39,997
$43,397
$41,167
$40,302
$39,422
Table 1 Median Household Income (MHI) in SJV Counties (2006-2013)
(Inflation-adjusted dollars)11 (U.S. Census Bureau, 2015)
9
As defined by the California Department of Water Resources (DWR)’s Propositions 84 and 1E Integrated Regional
Water Management (IRWM) Guidelines (dated August 2010).
10
MHI county level data for 2014 is not yet available.
11
Shadow indicates drought years 2012 and 2013 only since 2014 data are not available yet.
60
Although illustrative of the challenging economic conditions that the SJV has endured in recent
years, particularly during the ongoing dry years, unemployment and MHI data at the county level
conceal valuable and useful information that only becomes apparent when examining more
refined geographical units. At the city level for example, for which some data is available,
evidence reveals a more dramatic picture than at the county level. Table 2 shows the MHI for 15
SJV selected cities classified as DACs. At this geographical level, data earlier than 2009 is not
available and thus it is not possible to compare current MHI levels with levels before the 2007–
2009 Great Recession. However, the data illustrate at least two salient facts.
First, in all these communities the 2013 MHI fell from either the preceding year or from 2 years
ago, in some cases to dramatic levels. According to the U.S. Census Bureau (2013), the federal
poverty threshold for a household composed of 5 people (2 adults and 3 related children under
18) is $27,801. This means that in communities, such as Mendota and Tranquility for instance, in
2013 more than 50% of the households in these cities were officially classified as poor. Second,
with the exception of Coalinga and Porterville, which historically exhibit a relatively larger
income than other disadvantaged communities, the 2013 MHI for all other communities is below
the lowest average MHI at county level, which corresponds to Tulare County at $39,422. This
suggests that while the economic distress is generalized across the SJV, it is more acute in some
agricultural communities, particularly in those most affected by reductions in surface water.
DAC12
County
2009
2010
2011
2012
2013
Avenal
Kings
$34,273
$33,350
$29,183
$27,927
$28,794
Chowchilla
Madera
$39,561
$39,902
$41,858
$41,373
$37,466
Coalinga
Fresno
$43,114
$46,229
$47,101
$46,712
$46,500
Corcoran
Kings
$31,728
$35,051
$31,641
$34,594
$32,914
Delano
Kern
$37,394
$35,673
$37,810
$35,507
$35,122
Dinuba
Tulare
$39,845
$39,165
$40,463
$39,228
$39,328
Dos Palos
Merced
$41,120
$40,121
$39,959
$34,522
$33,898
Exeter
Tulare
$45,363
$43,690
$42,446
$39,987
$39,063
Kettleman City
Kings
$25,488
$25,988
$34,323
$36,111
$35,625
Keyes
Stanislaus
$40,905
$35,130
$34,423
$34,819
$34,967
Mendota
Fresno
$25,422
$25,216
$25,807
$26,061
$24,264
Parlier
Fresno
$33,523
$34,405
$36,388
$36,161
$35,327
Porterville
Tulare
$38,079
$39,838
$39,933
$42,628
$41,905
Tranquility
Fresno
$31,763
$32,532
$24,293
$26,250
$24,609
Wasco
Kern
$38,096
$40,054
$40,295
$42,221
$39,061
Table 2 Median Household Income (MHI) in Selected SJV Cities (2009-2013)
(Inflation-adjusted dollars)13 (U.S. Census Bureau, 2015)
12
DAC = Disadvantaged Community.
13
Shadow indicates drought years 2012 and 2013 only, since 2014 data are not available yet.
61
When looking at unemployment in DACs (Figure 2), the unemployment rates show a declining
trend during the drought years, which mirrors what is happening at the county level as shown in
Figure 1. However, it is important to notice that the 2014 average unemployment rate for DACs
is significantly higher (18.4%) than the average for the SJV (11.5%). In a few cases the
difference is not large, such as in Coalinga, Chowchilla, or Porterville, but in other cases the
difference is substantial, such as in Avenal, Delano, or Mendota.14 This suggests that the
industrial composition as well as other factors unique to each DAC determine its economic
performance as well as its resilience when facing water challenges. Further, similarly to the path
shown at the county level, none of these DACs has been able to return to the unemployment rate
before the 2007–2009 Great Recession.
14
See Editorial Snapshot: “Who Are They: Moving from Economic Impact to Human Impact” following this
chapter for more information on Avenal, Delano, and Mendota.
62
45.0%
Avenal
Chowchilla
40.0%
Coalinga
35.0%
Corcoran
Delano
30.0%
Dinuba
25.0%
Dos Palos
Ke leman City
20.0%
Keyes
Mendota
15.0%
Parlier
10.0%
Porterville
Tranquillity
5.0%
Wasco
0.0%
2006
SJV
2007
2008
2009
2010
2011
2012
2013
2014
Figure 2 Unemployment Rates in Selected SJV Cities/Disadvantaged Communities 2006-2014)15 (CA EDD, 2015a)
15
Shadow indicates drought years (2012, 2013, and 2014).
63
Based on the data examined so far, an intriguing observation emerges which needs to be
addressed: How can the MHI be falling at the same time that the unemployment rates are
declining, which seems to be case in all DACs and also in some counties? In other words, if
fewer workers are unemployed, the logical expectation is higher MHI (not lower MHI), at both
the city and county levels. This expectation however implies some assumptions that do not
always hold. This matter is examined in the next section.
Changing Employment Conditions and Migration Patterns
Expecting that lower unemployment rates will increase the MHI assumes that the number of
hours per day worked, the number of days per week worked, as well as the wage rate paid to
workers do not change. If either one or more of these variables fall, higher employment does not
necessarily imply an increase in the MHI: a larger number of workers would be employed but
they would be earning less labor income. In addition, although the unemployment rate falls as
more workers are employed, it can also fall when fewer people look for jobs, either because they
drop out of the labor force when discouraged or because they migrate to other locations. The
necessary data to explore these issues is only available at the state and county levels, and not at
the city level. However, the existing evidence sheds significant light to explain the seemingly
contradictory observation of declining MHI while unemployment rates are falling.
At the state level, the data shown in Table 3 indicates that although the number of farm workers
is slightly lower during the dry years (compared to farm labor before the 2007–2009 Great
Recession and also during the first recovery years of 2009 and 2010), the number of hours
worked per week does not change much. The data also show, however, that the number of farm
laborers expected to work more than 150 days per year is slightly lower during the dry years. So,
statewide the evidence suggests lower farm employment working fewer days per year but
working the same number of hours per week.
64
Number of Employed
Expected to be Employed
Number of Hours
Workers
150+ days
<149 days
Worked
2006
183,000
149,000
34,000
44.6
2007
177,000
139,000
38,000
45.7
2008
173,000
139,000
34,000
45.8
2009
157,000
124,000
33,000
42.1
2010
192,000
156,000
36,000
44.3
2011
185,000
150,000
35,000
43.6
2012
162,000
129,000
33,000
46.5
2013
181,000
144,000
37,000
43.8
2014
169,000
133,000
36,000
45.1
Table 3 California Farm Labor (2006-2014)16 (USDA, 2015)
At the county level, the data is mixed but also more enlightening in some cases as shown in
Table 4. Data on farm labor reveal at least three salient facts:
1. With the exception of Tulare, in all other counties the farm employment estimates show
an increasing trend during the drought. This observation mirrors the behavior of the
overall unemployment rate.
2. In five of eight SJV counties (Kern, Madera, Merced, San Joaquin and Tulare) the mean
hourly wage of farm workers fell during the dry years below its peak in either 2010 or
2011.
3. In the same counties where the mean hourly wage of farm workers fell, the mean annual
wage also fell during the dry years below its peak in either 2010 or 2011.
The importance of these observations cannot be overstated. Both falling hourly wage and annual
wage, as well as working fewer days per year, could partially explain the fall in MHI despite
declining unemployment rate, particularly in those disadvantaged communities that heavily
depend on agriculture and that have faced significant reductions in surface water for the last
three years.
In Table 4, the dry years (2012, 2013, 2014) are shaded in grey, with the peak year (2010, 2011)
immediately above for comparison.
16
Shadow indicates drought years (2012, 2013, and 2014).
65
2006
2007
2008
2009
2010
2011
2012
2013
2014
FRESNO
Employment Mean Hourly Mean Annual
Estimates
Wage
Wage
17,350
$8.00
$16,632
16,960
$8.01
$16,664
21,360
$8.49
$17,680
22,990
$8.83
$18,375
25,220
$8.98
$18,670
23,440
$9.03
$18,785
22,670
$9.05
$18,821
25,440
$9.00
$18,724
24,870
$9.18
$19,085
2006
2007
2008
2009
2010
2011
2012
2013
2014
KERN
Employment Mean Hourly Mean Annual
Estimates
Wage
Wage
19,340
$8.00
$16,634
26,100
$7.94
$16,521
25,820
$8.34
$17,350
25,990
$8.67
$18,033
25,890
$9.05
$18,825
20,560
$9.21
$19,148
25,390
$9.12
$18,968
29,840
$8.95
$18,630
36,590
$8.98
$18,680
2006
2007
2008
2009
2010
2011
2012
2013
2014
KINGS
Employment Mean Hourly Mean Annual
Estimates
Wage
Wage
2,490
$8.51
$17,706
3,700
$8.55
$17,780
5,220
$9.43
$19,621
3,240
$9.66
$20,107
2,860
$9.81
$20,417
2,970
$9.60
$19,963
1,980
$9.52
$19,786
2,710
$9.75
$20,284
2,190
$10.18
$21,170
2006
2007
2008
2009
2010
2011
2012
2013
2014
MADERA
Employment Mean Hourly Mean Annual
Estimates
Wage
Wage
4,120
$8.34
$17,351
5,380
$8.30
$17,268
5,470
$8.41
$17,495
5,300
$8.76
$18,219
5,090
$8.98
$18,658
4,810
$9.04
$18,807
3,680
$8.96
$18,639
5,590
$8.92
$18,559
6,180
$8.92
$18,549
2006
2007
2008
2009
2010
2011
2012
2013
2014
MERCED
Employment Mean Hourly Mean Annual
Estimates
Wage
Wage
2,430
$7.96
$16,537
2,050
$7.82
$16,265
3,000
$8.56
$17,794
2,770
$8.90
$18,521
2,770
$9.22
$19,167
1,740
$9.08
$18,869
2,200
$8.88
$18,467
2,560
$8.77
$18,240
3,570
$8.81
$18,336
2006
2007
2008
2009
2010
2011
2012
2013
2014
SAN JOAQUIN
Employment Mean Hourly Mean Annual
Estimates
Wage
Wage
6,570
$7.95
$16,535
4,910
$8.12
$16,879
6,090
$8.69
$18,073
5,790
$9.13
$18,992
5,120
$9.31
$19,373
4,880
$9.05
$18,842
4,970
$8.89
$18,493
4,650
$8.80
$18,310
6,170
$8.82
$18,356
2006
2007
2008
2009
2010
2011
2012
2013
2014
STANISLAUS
Employment Mean Hourly Mean Annual
Estimates
Wage
Wage
5,730
$8.21
$17,085
4,630
$8.27
$17,206
3,470
$8.48
$17,639
3,890
$8.83
$18,371
4,330
$9.29
$19,325
4,610
$9.43
$19,612
5,060
$9.12
$18,986
4,820
$9.33
$19,403
5,860
$9.52
$19,814
2006
2007
2008
2009
2010
2011
2012
2013
2014
TULARE
Employment Mean Hourly Mean Annual
Estimates
Wage
Wage
12,540
$8.37
$17,418
17,530
$8.35
$17,380
16,620
$8.84
$18,362
19,040
$9.16
$19,044
17,180
$9.45
$19,648
20,170
$9.70
$20,187
21,730
$9.55
$19,859
19,780
$9.33
$19,399
18,280
$9.56
$19,895
Table 4 Farm Labor in SJV Counties (2006-2014) (CA EED, 2015b)
66
As discussed earlier, it is possible that a number of workers in the SJV, discouraged by the
challenging economic and labor conditions generated by the drought, decide to migrate to other
places. Some migrate to other cities within the SJV while others migrate to other states and even
other countries, as is the case of many foreign workers either temporarily or permanently
returning to their home countries.
As shown in Table 5, the data show a mixed record:
1. In all SJV counties the population increased at an average growth rate of 0.7% during the
three years of the drought. This figure is not much different from the population growth
rates registered before the drought. However, the average population growth rate for the
SJV disguises what happened in individual counties. For example in Kings County, the
population actually decreased during the last three years.
2. With the exception of Madera and San Joaquin counties, all other counties show a
significant large net number of people leaving during the three drought years (net
domestic migration). This suggests that some residents decided to move somewhere else
within the country, possibly in pursuit of better working and living conditions.
3. All SJV counties exhibit a large net number of foreign immigrants during the three
drought years. The motivation to migrate into the counties from abroad during the
drought years is not clear. For some migrant workers, the working and living conditions
in their home countries are worse than in the SJV despite the drought. For others, perhaps
the drought coincided with other non-economic factors such as those undergoing family
reunification processes.
4. During the drought years, in most of the counties the balance between net domestic
migration and net foreign migration is negative, which means a decrease in the county
population. The population decrease due to immigration is relative small in some
counties (like in Fresno, San Joaquin, and Stanislaus counties) and relatively large in
others (such as Kings and Tulare counties).
In sum, the evidence indicates that in those counties where agriculture plays a relatively major
role in the economy, the decrease in MHI can be partially explained by a decrease in the mean
hourly wage paid to farm workers as well as a fall in the number of farmers expected to work
more than 150 days per year. Also, the evidence suggests that, as consequence of the drought and
in pursuit of better working and living conditions, some workers decided to migrate to locations
outside the SJV.
67
FRESNO
2010
2011
2012
2013
2014
KERN
2010
2011
2012
2013
2014
841,158
848,880
855,974
865,511
872,322
0.2%
0.9%
0.8%
1.1%
0.8%
1,527
7,722
7,094
9,537
6,811
3,485
14,400
14,204
14,416
13,926
1,316
5,391
5,228
5,642
5,814
2,169
9,009
8,976
8,774
8,112
‐642
‐1,287
‐1,882
763
‐1,301
114
741
1,447
1,926
1,865
‐756
‐2,028
‐3,329
‐1,163
‐3,166
KINGS
2010
2011
2012
2013
2014
152,693
151,685
150,643
150,507
149,788
‐0.2%
‐0.7%
‐0.7%
‐0.1%
‐0.5%
‐289
‐1,008
‐1,042
‐136
‐719
568
2,576
2,394
2,464
2,356
192
752
813
801
849
376
1,824
1,581
1,663
1,507
‐665
‐2,832
‐2,623
‐1,799
‐2,226
14
99
197
235
229
‐679
‐2,931
‐2,820
‐2,034
‐2,455
MADERA
2010
2011
2012
2013
2014
151,318
152,019
151,242
152,857
154,278
0.3%
0.5%
‐0.5%
1.1%
0.9%
453
701
‐777
1,615
1,421
574
2,438
2,376
2,288
2,284
276
1,007
1,045
1,048
1,116
298
1,431
1,331
1,240
1,168
155
‐730
‐2,108
375
253
13
93
172
235
227
142
‐823
‐2,280
140
26
MERCED
2010
2011
2012
2013
2014
255,886
259,186
261,002
262,336
265,069
0.0%
1.3%
0.7%
0.5%
1.0%
93
3,300
1,816
1,334
2,733
1,067
4,299
4,303
4,188
4,240
373
1,452
1,580
1,612
1,686
694
2,847
2,723
2,576
2,554
‐601
453
‐907
‐1,242
179
31
215
414
566
548
‐632
238
‐1,321
‐1,808
‐369
2010
2011
SAN JOAQUIN 2012
2013
2014
686,576
692,713
697,758
702,669
711,797
0.2%
0.9%
0.7%
0.7%
1.3%
1,270
6,137
5,045
4,911
9,128
2,546
10,545
10,081
10,047
9,940
1,155
4,719
4,957
4,957
5,057
1,391
5,826
5,124
5,090
4,883
‐121
311
‐79
‐179
4,245
123
858
1,605
2,018
1,954
‐244
‐547
‐1,684
‐2,197
2,291
STANISLAUS
2010
2011
2012
2013
2014
515,183
518,178
523,126
526,549
530,327
0.1%
0.6%
1.0%
0.7%
0.7%
730
2,995
4,948
3,423
3,778
1,922
7,781
7,694
7,503
7,462
927
3,650
3,787
3,844
4,052
995
4,131
3,907
3,659
3,410
‐265
‐1,136
1,041
‐236
368
78
520
995
1,224
1,187
‐343
‐1,656
46
‐1,460
‐819
TULARE
2010
2011
2012
2013
2014
443,086
447,591
452,301
455,376
459,176
0.2%
1.0%
1.1%
0.7%
0.8%
907
4,505
4,710
3,075
3,800
1,852
8,149
8,019
7,764
7,531
688
2,847
2,820
2,850
2,956
1,164
5,302
5,199
4,914
4,575
‐257
‐797
‐489
‐1,839
‐775
49
358
700
970
939
‐306
‐1,155
‐1,189
‐2,809
‐1,714
County
Percent Numeric
Change Change Births
0.2%
1,893
3,893
0.8%
6,986 16,312
1.0%
9,124 15,946
0.9%
8,514 15,721
1.1%
10,524 16,016
Net
Net
Natural
Net
Foreign
Domestic
Increase Migration Immigration Migration
2,354
‐461
121
‐582
10,337
‐3,351
847
‐4,198
9,695
‐571
1,570
‐2,141
9,207
‐693
2,172
‐2,865
9,313
1,211
2,104
‐893
Population
(July 1)
932,343
939,329
948,453
956,967
967,491
Deaths
1,539
5,975
6,251
6,514
6,703
Table 5 Population Estimates and Components of Change by County (2010-2014)17
(California Department of Finance, Demographic Research Unit, 2015)
17
Shadow indicates drought years (2012, 2013 and 2014).
Natural increase = Births - Deaths
Net Migration = Net Foreign Migration - Net Domestic Migration
Numeric Change = Natural Increase + Net Migration
68
Impact of the Drought on Food Prices
According to the USDA Economic Research Service [USDA ERS], it is not totally clear yet the
extent at which the ongoing drought will drive up current and future food prices. While it is clear
that “…the impact of the drought on food prices depends on its severity, the impact it has on
production, and the acreage and planting decisions of California farmers” is less clear, and less
able to be clarified (USDA ERS, 2014). It is reasonable to expect that higher production costs—
due to the cost and availability of water—will drive food prices up. Droughts in California are
typically linked to higher retail food prices. However, the price effects of higher production costs
do not occur immediately. As the USDA ERS further explains, “…price increases associated
with a drought are lagged due to the time it takes for weather conditions and planting decisions
to alter crop production.” The complexity in isolating the effect of the California drought on food
prices is compounded by an assorted list of domestic and international factors. These include for
example the pressure observed in the cattle and beef markets after the cold weather of 2013, the
ongoing drought conditions in Texas and Oklahoma, and the domestic and foreign appetite for
non-traditional crops driving demand and prices up and thus influencing farming decisions.
Although neither the extent nor the timing at which the ongoing drought will drive food prices up
is fully understood yet, examining the behavior of food prices and its impact on residents in the
SJV is relevant for at least two reasons. First, the magnitude, duration, and point in time in which
food prices go up vary across the several droughts that California has sustained over the years.
Yet, California droughts have historically been associated with higher food prices, that is, food
prices eventually increase. Second, the evidence regarding the negative impact of higher food
prices on low-income people is undeniable. Low-income people spend a larger share of their
income on food and thus, when facing a food price spike, the income available to buy other items
is reduced. Conversely, people with higher income levels spend a smaller share of their income
on food and thus a food price surge does not impact them as much as low-income people.18 This
means that the economic impact of the drought is felt in two ways, as producers of food (the
impact is felt through job loss, working less, receiving a lower wage), and as consumers of food
(the impact is felt through having to purchase food at higher prices).
Food inflation for the period 2006–2014 is shown in Table 6 for a variety of items classified by
the U.S. Bureau of Labor Statistics (BLS). The forecast figures are produced by the USDA ERS.
The forecast for 2015 looking at “All food” items indicates normal food price inflation, with
retail prices expected to rise 2.5% to 3.0% over 2014 levels, which is ordinary according to its
20-year historical average. In fact, the forecast is for most individual food price categories to
increase around their historical average.
18
Economists call this observation Engel’s Law, according to which as income rises, the proportion of income spent
on food falls, even if actual expenditure on food rises.
69
Item
20-Year Forecast
Historical
2006 2007 2008 2009 2010 2011 2012 2013 2014 Average
2015
All food
2.4
4.0
5.5
1.8
0.8
3.7
2.6
1.4
2.4
2.6
2.0 to 3.0
Food away from home
3.1
3.6
4.4
3.5
1.3
2.3
2.8
2.1
2.4
2.7
2.0 to 3.0
Food at home
Meats, poultry, and fish
Meats
Beef and veal
Pork
Other meats
Poultry
Fish and seafood
Eggs
Dairy products
1.7
0.8
0.7
0.8
-0.2
1.8
-1.8
4.7
4.9
-0.5
4.2
3.8
3.3
4.4
2.0
2.3
5.1
4.6
29.2
7.4
6.4
4.2
3.5
4.5
2.3
3.1
5.0
5.9
14.0
8.0
0.5
0.3
0.5
1.9
-0.6
2.8
-1.0
2.9
-2.0
4.7
2.3
-0.1
1.7
-0.1
3.6
1.1
-14.7 1.5
-6.4
1.1
4.8
7.4
8.8
10.2
8.5
6.4
2.9
7.1
9.2
6.8
2.5
3.6
3.4
6.4
0.3
1.7
5.5
2.4
3.2
2.1
0.9
2.1
1.2
2.0
0.9
-0.1
4.7
2.5
3.3
0.1
2.4
7.2
9.2
12.1
9.1
3.9
2.0
5.8
8.4
3.6
2.6
3.1
3.3
4.1
2.8
2.4
2.6
2.9
4.3
2.8
2.0 to 3.0
3.0 to 4.0
3.5 to 4.5
5.0 to 6.0
2.0 to 3.0
2.5 to 3.5
2.5 to 3.5
2.5 to 3.5
2.5 to 3.5
2.5 to 3.5
0.2
4.8
5.3
6.0
4.6
2.9
3.8
1.8
2.1
1.4
2.9
3.8
3.9
4.5
3.2
3.6
3.1
4.4
4.1
1.8
13.8
6.2
5.2
4.8
5.6
9.5
5.5
10.2
4.3
5.2
2.3
-2.1
-4.8
-6.1
-3.4
6.6
5.6
3.2
1.9
3.7
9.3
4.1
4.5
3.3
5.6
2.9
3.3
3.9
3.2
2.3
6.1
-0.6
-2.0
1.0
-5.1
3.8
3.3
2.8
1.1
3.5
-1.4
2.5
3.3
2.0
4.7
0.3
-1.7
1.0
-1.0
0.5
0.1
1.5
1.9
4.8
-1.3
0.1
-0.8
0.2
-0.5
1.0
2.8
3.0
3.1
3.0
3.2
2.8
2.2
2.6
1.5
2.0
0.0 to 1.0
2.5 to 3.5
2.5 to 3.5
2.5 to 3.5
2.0 to 3.0
2.5 to 3.5
1.5 to 2.5
0.5 to 1.5
2.0 to 3.0
1.5 to 2.5
Fats and oils
Fruits and vegetables
Fresh fruits & vegetables
Fresh fruits
Fresh vegetables
Processed fruits & vegetables
Sugar and sweets
Cereals and bakery products
Nonalcoholic beverages
Other foods
-0.3
0.2
0.7
-0.6
2.0
-1.3
2.2
-0.8
-0.9
-0.5
Table 6 Changes in Food Price Indexes (2006-2015)19
(U.S. Department of Labor, Bureau of Labor Statistics 2015, USDA ERS, 2015)
However, the data also illustrate at least three more salient facts. First, prices in the “All food”
category increased 2.4% in 2014, which is closer to the 20-year historical average of 2.6% than
in 2013. Although still premature to call it a trend, the actual price increase in 2015 is likely to
reveal more information about the impact of the drought on all food prices, particularly if it
surpasses the historical average. Second, similarly to the all food category, prices in the fresh
fruits category increased 4.8% in 2014, which is not only above the 20-year historical average of
3.0%, but also shows an upward trend during the drought years. Third, the forecast by USDA
ERS indicates that the price of meats in general is expected to increase beyond the 20-year
historical average. The price forecast for beef and veal in particular is predominantly high, and
the price forecast for pork almost as high.
In summary, although for some food categories the data suggest that prices are increasing during
drought years, the USDA ERS’s overall assessment regarding the unknown nature of the extent
of the impact of the drought on overall food prices seems appropriate. The evidence is still
19
Shadow indicates drought years (2012, 2013, and 2014).
70
inconclusive and the complexity to separate the impact of the drought on prices from other
important factors represents a major challenge.
The current inability to accurately evaluate the impact of the drought on food prices, however, is
independent from the impact of increasing food prices on households (regardless of whether food
price increases are drought-driven or not), particularly among low-income residents of the SJV.
Assessing this impact has its own complexities and thus represents an entirely different
challenge. For example, since poor households can be both producers and consumers of food,
they are impacted in different ways by food price increases depending on their net consumption
status and on the food items they consume and produce. In general, it can be expected that food
price increases hurt poor households that are net food buyers while benefiting those that are net
food sellers. Thus, it can be argued that the net impact on welfare in any given community
(either a county or a city in the eight counties) depends of the magnitude of these two forces.
Further, it can also be argued that the impact on welfare substantially depends on the products
involved and the policy response of different communities. An analysis of this nature falls
outside the scope of this report, but it is mentioned as a potential future line of research.
Summary
This segment of the report examined the behavior of unemployment rates, MHI levels, migration
patterns, and food prices in the eight counties that comprise the SJV. A more comprehensive
economic impact analysis should look beyond agriculture to include other sectors such as
manufacturing, recreation and tourism, and energy production, among others. That more
inclusive examination should also look at the impact of the drought on urban areas and on the
environment. During the drought of 1987–1992 for example, the Institute for Water Resources,
Water Resources Support Center, and the U.S. Army Corps of Engineers commissioned a study
aimed at articulating the lessons learned from the drought (Dziegielewski, Garbharran, &
Langowski, 1993). The structure and content of this report could be the starting point of a similar
analysis of the current drought.
Despite the more limited scope of this segment of the report however, the analysis provides
valuable information. The findings indicate that the observed fall in MHI in some counties and in
most disadvantaged communities during the drought years is due to a combination of job loss,
lower hourly wage, and lower annual wages paid to farm workers, as well as working fewer days
per year. The evidence also suggests that as a consequence of the drought some workers decided
to migrate to locations outside the SJV, possibly in pursuit of better working and living
conditions. These patterns could explain why the MHI is falling at the same time that the
unemployment rate is decreasing. In addition, although it is not totally clear at what extent
overall food prices will go up as consequence of the drought, the data indicates that the price of
some food items has increased during the dry years. This is relevant from the consumer
perspective, particularly for low-income households that spend a larger share of their income on
food, because a food price surge can significantly impact their disposable income.
71
SNAPSHOT: WHO ARE THEY?
Moving from Economic Impact to Human Impact
by Gillisann Harootunian, PhD
In the preceding chapter, the author clarifies how the 2014 average unemployment rates for
Disadvantaged Communities such as Avenal, Delano, and Mendota are significantly higher than
those for the San Joaquin Valley. The unemployment (and under-employment) rates discussed in
that chapter constitute one of the economic impacts of the drought. What of the human impact
from those economic ones? Who lives in Avenal, Delano, and Mendota? Who are they? How
will the reduced—or eliminated—wages affect them? Their families? Their ability to pay for
medical care? Or for a post-high school work certificate so they can re-enter the workforce? One
way to begin to think about the answers to such questions is to take a demographic “snapshot” of
the populations of Avenal, Delano, and Mendota. When a water drought occurs, how thick or
thin is the margin of safety for those residents who are already living in a financial drought?
Avenal
Delano
Mendota
CA State
Population: General Profile
Total
15,505
53,041
11,014
37,253,956
Male
72.4%
59.9%
55.3%
49.7%
Female
27.6%
40.1%
44.7%
50.3%
Ethnicity/Race (alone or combination)
Hispanic or Latino
71.8%
71.5%
96.6%
37.6%
White
40.8%
39.1%
55.6%
57.6%
African American
10.8%
8.2%
1.4%
7.2%
Institutionalized [male prison]
41.4%
20%
N/A
0.8%
Institutionalized [female prison]
N/A
0.2%
N/A
0.3%
Foreign born (5 years and older)
44.8%
41.3%
60.7%
28.8%
Not a U.S. citizen
38.6%
29.7%
53.2%
15.2%
Naturalized U.S. citizen
6.1%
11.6%
7.5%
13.6%
Economic Profile
Unemployed
20.4%
16.2%
27.1%
11.5%
No Health Insurance (civilian non30.4%
27.4%
39.4%
17.8%
institutionalized population)
No Health Insurance – Employed
43.9%
38.8%
64.2%
21.2%
Median Household Income
$28,794
$35,122
$24,264
$61,094
Median Family Income
$29,811
$35,643
$24,621
$69,661
Income Below Poverty Level in Past 12
40%
27.6%
44.3%
12%
Months – All Families
Educational Profile: Population 25 years and older
Less than 9th grade
29.3%
26.9%
57.2%
10.2%
High school graduate (includes equivalency)
23.5%
27.6%
15.5%
20.7%
Associate’s Degree
3%
3.3%
2.4%
7.8%
Bachelor’s Degree or Higher
4%
6.8%
1.6%
30.7%
Sources: U.S. Census 2010; 2009-2013 American Community Survey 5-Year Estimates
72
SNAPSHOT: THE SHADOW ECONOMY
How To Document the Undocumented?
By G. Harootunian, PhD
Many farm workers are undocumented in the San Joaquin Valley. How to grasp the
impact of the under-employment described in the preceding chapter on people who live in
the shadow economy? One way would be to look at the raw data available from the U.S.
Department of Labor. Below, selected data is given for both U.S. Farm Workers and for
Farm Labor Contractors (the intermediaries who supply farm labor to the farmers).
Also, the categories used by California Farm Labor Contractor Association provide a lens
to view the economic tier structure: In good years, large farmers and farm labor
contractors make billions. Medium farmers and farm labor contractors make millions.
Small farmers and farm labor contractors can make tens or even hundreds of thousands.
The undocumented farm worker: $10,000 per year, or less, with minimal use of benefits.
U.S. DOL: Registered Farm Labor Contractor Listing # U.S.
% U.S. % CA
Farm Labor Contractors Headquartered in U.S.
9,336
100%
N/A
Farm Labor Contractors Headquartered in CA
4,060
43%
100%
Farm Labor Contractors Headquartered in Avenal, CA
79
0.85%
1.94%
Farm Labor Contractors Headquartered in Delano, CA
116
1.24%
2.86%
Farm Labor Contractors Headquartered in Mendota, CA
127
1.36%
3.13%
California Farm Labor Contractor Association – Categories [May 2015]
Small Farm Labor Contractor1
Under $2M annual total payroll
Medium Farm Labor Contractor
$2M - $5M annual total payroll
Large Farm Labor Contractor
Over $5M annual total payroll
U.S. Department of Labor: “National Agricultural Workers Survey”
Annual Median Income: Farm Workers
Permanent Resident/Green Card Holder
$7,500-$10,000
Work Authorization (e.g., Amnesty, Family Unity)
$5,000-$7,500
2
Unauthorized
$2,500-$5,000
Living Below Poverty Line: Farm Workers
U.S. Citizen
46%
Legal Permanent Resident
54%
Work Authorization (e.g., Amnesty, Family Unity)
68%
Unauthorized
80%
Unemployment Insurance [used]: Farm Workers
U.S. Citizen (able to secure non-farm work)
17%
Legal Permanent Resident
46%
Other Work Authorized
32%
Unauthorized
5%
The “Small Farm Labor Contractor” category hides the smallest of these, ex-farm workers who create their own
small business as farm labor contractors. See Philip L. Martin’s “Migration and U.S. Agricultural Competitiveness”
for an analysis of the precarious situation of these small farm labor contractors.
2
Editor’s Note: While such families can survive and send money back home by doubling up in good times, in bad
times, families might have to squeeze in 3 or 4 together in a small house.
1
73
SNAPSHOT: Food Insecurity in the San Joaquin Valley
By Gil Harootunian
The preceding chapter also analyzed a potential surge in food prices, which impacts most low
income households who spend a larger proportion of their income on food. What is the state of
food insecurity in the San Joaquin Valley? These percentages are given by the UCLA Center
for Health Policy Research’s “Health Profiles” in 2012-201322 (the beginning of the drought).
State/County
Food Insecurity*
California
15.7%
Fresno
25.2%
Kern
26%
Kings
18.6%
Madera
29.3%
Merced
19.2%
San Joaquin
20%
Stanislaus
21.8%
Tulare
23.6%
*Defined as adults who had difficulty reliably putting food on the table in the past year. The
question assumes that adults who are above 200% of the federal poverty level are food secure.
A Video Vignette
Sharing the Bounty: The Fresno State Student Cupboard [Food Pantry] In November 2014, Fresno State opened “The Student Cupboard” as one of many initiatives in
its new Food Security Project. The project aims to be a national model for universities and
colleges to keep students fed and focused. The video vignette below captures its opening day:
http://www.fresnostate.edu/magazine/sharing-the-bounty/.
22
Most recently available data
74
Chapter 3
Water Usage and Residential Water Consumption in the
California San Joaquin Valley (SJV)
Dr. Chih-Hao Wang, Department of Geography and City and Regional Planning
Abstract
In the San Joaquin Valley, water use for agriculture is much larger than that for other land uses
(e.g. residential, industrial, and commercial). For this reason, this study begins with a
preliminary analysis to assess and compare agricultural, industrial, and residential water use in
all 58 counties of California, in the eight San Joaquin Valley counties, and in the remaining 50
counties outside of the San Joaquin Valley, throughout the previous decade.
This preliminary assessment reveals that residential water use in the San Joaquin Valley is not
very significant when compared to agricultural water use. Documenting the level of residential
water use in the SJV area, however, is important to inform public dialogue and policy making
when the aim is to target precious time and resources to manage a potential long-term drought
and long-term water use in general. Furthermore, the level of significance of residential water
use does not preclude efforts to encourage residential awareness and use of water as a finite
resource, nor does it preclude application of the analysis at different levels (especially county
level vs. municipal level).23 Nor does the level of significance of residential water use mitigate
the fact that every person is a stakeholder in a situation of water scarcity.
Finally, residential water use is important because it is a factor in water scarcity. From 2000 to
2010, California’s population increased by 10%, and the San Joaquin Valley’s population
doubled that rate at 20%. The San Joaquin Valley population is predicted to increase further, and
such growth exacerbates water scarcity in a drought. Less and less water can be used to support
all uses of water (agriculture, industrial, and residential) for the increased population. Therefore,
improving residential water use efficiency plays an important part in comprehensive planning
and preparation for a potential long-term drought.
Coping with municipal water scarcity has become a new research focus in city and regional
planning. To mitigate the impacts of water scarcity, it is extremely important to improve our
understanding of the relationships between development-induced water consumption and
demographic characteristics and features of the built environment (building attributes, the
presence or absence of pools, and yard sizes). A spatial statistical analysis on residential water
23
Editor’s Note: Residential water use can be significant at the municipal level when keen and immediate economic
and human impacts can be felt from water scarcity. For example, the City of Fresno, the 5th largest city in California,
struggled during the recent and prolonged recession, and as the aquifer levels have dropped, the costs of pumping
water from increasing depth became increasingly punitive for the City. As the case of East Porterville shows, water
scarcity—to the point of running out of water for domestic consumption-—can have dramatic immediate human
impact (see video vignette, page 126).
75
consumption in Fresno neighborhoods will illustrate these relationships to help inform policy
makers about water conservation strategies.
A small water consumption survey was conducted as a Fresno State class project (Geography
184) in spring 2015. The “Residential Consumption Water Survey” was administered to 60
households in Fresno and Clovis during the months of February and March.24 Survey questions
related to water consumption include indoor and outdoor physical conditions of the house and
socioeconomic factors of the household. Below are the multiple interesting findings, with
recommendations to encourage residential water savings through incentives based on the
understanding of water-use behavior and through innovations being integrated into the policymaking process.
Findings related to outdoor physical conditions, with summary recommendations:
1. Houses facing south consumed more water in the summer. This could be improved by
better site planning to consider the effects of summer sunshine on water demand,
including the setting of buildings and yards.
2. Houses with sprinkler irrigation systems consumed more water, particularly in the
summer. Improved sprinkler design for all landscape plants (including water wise plants)
could help to reduce water consumption.
3. Houses with a pool consume slightly more water than those without a pool in both
summer and winter. This also could be improved through incentives to encourage water
conservation (e.g., use of pool covers to reduce evaporation).
Findings related to indoor physical conditions:
1. More water consumption was measured by the number of bathrooms, with a strong
positive relationship found in both the winter and summer. Water saving innovations for
toilets and all faucets would be helpful for reducing this aspect of water consumption.
2. Household size does not seem to have clear impacts on water consumption, though this
lack of finding may result from the small size of the survey.
3. Household income also does not seem to have clear impacts on water consumption
except for the highest category ($60,000-plus), most likely from the presence of a pool
and the size and condition of the yard (outdoor physical conditions). This lack of finding
may also results from the small size of the survey.
Findings related to non-physical conditions:
1. Self-perception. Respondents who ranked themselves as moderate water users actually
consume as much or more water than those who ranked themselves as heavy water users.
Therefore, water use education to correct self-perception would be helpful to promote
awareness of water scarcity.
2. Neighborhood social effects. Water consumption of a given household is likely affected
by its neighbors for winter water consumption. The timing of the survey precluded
findings for summer water consumption. Moreover, the size of the survey used is small
for the spatial regression modeling. The spatial lag model, however, clearly shows that
residential winter water use is positively affected by the way your neighbors use water (as
24
This is the end of the cooler rainy season.
76
well as by the number of bathrooms). Integrating neighborhood social effects with water
saving innovations may be helpful in the policy-making process.
Finally, findings in this survey indicate a need to conduct a large-scale residential summer water
consumption survey to gather sufficient data for further analyses and to provide sufficient
planning information for the potential long-term drought. The resulting information could help
with reducing water consumption not only in the San Joaquin Valley, but in all of California.
San Joaquin Valley (SJV) vs. Non-SJV Water Use Changes from 2000
to 2010
A preliminary analysis was conducted to assess and compare agricultural, industrial, and
residential water use within the SJV throughout the previous decade, and then to compare those
findings with levels of water use in the rest of the state. This makes clear longer term patterns of
water use and provides a good lens through which to view the results of the Fresno State survey.
Simply put, the analysis will reveal the SJV consumes more water for a smaller population, and
the rate of population increase in the SJV is more significant than in non-SJV. The potential
long-term drought will eventually have huge impacts in this region not only on agriculture but
also on the increased population.
The analysis also suggests both the extent of water scarcity in the SJV and its heavy dependence
on water. The analysis also reiterates that in the SJV residential water use is insignificant
compared to agricultural water use but as a discrete category residential water use is significant
and presents an opportunity for savings. The scale is also important to ascertain to inform public
discussion and prioritize effort in policy making. We examine changes in water use from 20002010. Unfortunately, we do not have data to examine changes in water use from 2010 to 2015.
The county level was selected as the geographical unit for regional water-use analysis, with a
total of 58 observations in California (58 counties). The US Geological Survey (USGS) Water
Data from 2000 to 2010 was used for the spatial analysis. Table 1 presents descriptive statistics
for all the water uses for the SJV and non-SJV regions over different time periods. California’s
population increased by 3.4 million in 2000-2010, with about a 3% (1.1 million) increase from
2005 to 2010 and approximately 6% (2.3 million) from 2000 to 2005. The population growth
rate in the SJV (20%) is much larger than that (9%) in the non-SJV region during this 10-year
time period. With California’s total population increase of 3.4 million, an increase in water use
would be expected. Surprisingly, total water use decreased by 11% from 2000 to 2005, and
decreased even more (-17%) from 2005 to 2010. The reasons for this water use reduction might
include changes in water use behavior, new technologies, and economic changes. However, it
might be simply caused by water scarcity in recent years. In other words, the water demand for
the increased population is mostly likely not satisfied. From 2005 to 2010, it is interesting that
the reduction of total water use in the SJV (-3%) is much smaller than that in the non-SJV region
(-24%). This implies that the SJV strongly depends on water (mostly likely due to its intensive
agricultural activities).
77
Year
2010
2005
2000
#
%
#
%
#
CA - total population (millions)
37254
3%
36132
6%
33872
San Joaquin Valley population (8 counties)
3972
6%
3743
13%
3303
Other County (OT) population (50 counties)
33282
3%
32389
6%
30569
CA - total water use (Mgal/day)
37962
(-17%)
45720
(-11%)
51173
SJV water use (8 counties)
14512
23450
(-3%)
(-24%)
14980
30739
(-11%)
(-11%)
16810
34363
OT water use (50 counties)
Table 1 Total Water-Use Growth in California (SJV vs. Non-SJV) from 2000 to 2010
The above analysis on all water use can be analyzed further by examining water use separately in
the two major sources: groundwater and surface water. Table 2 shows that statewide
groundwater use decreased by 29% from 2000 to 2005, but increased by 16% from 2005 to 2010,
most likely due to the drought. However, groundwater use in 2010 is still lower than that in
2000. On the other hand, statewide surface-water use decreased by approximately 30% in total
from 2000 to 2010, more evidence for recent water scarcity. In the SJV, surface water use
decreased at a lower rate (-9%) than in the non-SJV region (-34%) from 2005-2010. Moreover,
in 2010, the SJV relied more on surface water (8825 Mgal/day) than on groundwater (5687
Mgal/day) to maintain its economic activities. Farmers might use surface water as much as
possible to lower their costs (e.g., more energy is consumed to pump groundwater from
increasing depths). However, interview results indicated that small farmers have been able to
access only groundwater in recent years.
From the regional policy-making viewpoint, it is an extremely important to improve the
efficiency of the surface water delivery system particularly in the SJV where reliance on it can be
pronounced. This does not mitigate the need to regulate groundwater use also since it has
become the major water source for agriculture. Moreover, both recommendations though given
urgency by the extent of agriculture in the SJV would also improve results in water use
efficiency and conservation for all uses, including residential and industrial.
Finally, examining irrigation water use in the State, in the eight SJV counties, and in the 50 nonSJV counties indicates the importance of the role that water for irrigation plays in the SJV. From
2000 to 2010, California’s total irrigation water use decreased by 24%. In the SJV, irrigation
water use decreased by 17% from 2000 to 2005, but increased by 2% from 2005 to 2010. In the
non-SJV region, irrigation water use decreased by a total of 34% from 2000-2010. In 2010, for
instance, irrigation water used in the eight SJV counties (13,184 mgal/day) is about 1.3 times the
amount used in the other 50 counties total in 2010 (9,872 mgal/day), reinforcing the heavy
economic dependence in the SJV on it.
78
Year
2010
2005
2000
#
%
#
%
#
CA - groundwater use (Mgal/day)
12652
16%
10951
(-29%)
15395
SJV groundwater use (8 counties)
5687
(-9%)
5236
(-34%)
7977
OT groundwater use (50 counties)
6965
(-22%)
5721
(-23%)
7419
CA - surface-water use (Mgal/day)
25311
(-27%)
34763
(-3%)
35777
SJV surface-water use (8 counties)
8825
(-9%)
9745
10%
8833
OT surface-water use (50 counties)
16486
(-34%)
25018
(-7%)
26944
CA - Irrigation water use
23056
(-5%)
24364
(-20%)
30497
SJV irrigation water use (8 counties)
13184
2%
12940
(-17%)
15503
OT irrigation water use (50 counties)
9872
(-14%)
11424
(-24%)
14994
Table 2 Ground, Surface, and Irrigation Water-Use Growth in California (SJV vs. Non-SJV) from
2000 to 2010
Before moving into the discussion of the regional patterns revealed by this preliminary analysis
of water use intra-SJV and extra-SJV, it should be noted that as compared to agriculture, changes
in domestic and industrial water use are not very significant in all regions (Table 3). The USGS
does not even provide complete data on public-supplied water use. In the SJV, public-supplied
and self-supplied domestic water use is a smaller percentage of total water use than in the nonSJV. Both public-supplied and self-supplied domestic water use show a decrease from 20052010 while self-supplied industrial water use shows a sharp increase.
Year
CA - total water use (Mgal/day)
2010
37962
2005
45720
2000
51173
SJV water use (8 counties)
14512
14980
16810
OT water use (50 counties)
23450
30739
34363
CA - domestic public-supplied water use
SJV domestic public-supplied water use (8 counties)
OT domestic public-supplied water use (50 counties)
CA - domestic self-supplied water use
SJV domestic self-supplied water use (8 counties)
OT domestic self-supplied water use (50 counties)
CA - industrial self-supplied water use
SJV industrial self-supplied water use (8 counties)
OT industrial self-supplied water use (50 counties)
3866
530
3335
172
31
141
400
81
319
3984
590
3393
486
181
304
96
2
94
−
−
−
286
40
246
202
52
150
Table 3 Public- and Self- Supplied Water-Use Growth in California (SJV vs. Non-SJV) from 2000 to
2010
79
Water-Use Patterns: San Joaquin Valley (SJV) vs. Non-SJV in 2010
The average population of a county in the SJV (496,000) is slightly smaller than that in the nonSJV region (666,000), even though the population growth of the entire SJV from 2000 to 2010
(20%) is the double of the rate in the non-SJV region (9%) for the same period. However, the
eight SJV counties use much more water (1,814 Mgal/day), on average, than the other 50
counties (469 Mgal/day). Simply put, the SJV consumes more water for a smaller population.
The potential long-term drought will eventually have huge impacts in this region not only on
agriculture but also on the increased population. Surface water use in the SJV makes up on
average about 61% of total water use while groundwater use accounts for the other 39%.
Similarly, surface water makes up about 64% of total water use in the non-SJV region while
groundwater use represents the remanding 36%. Table 4 shows average population and water use
for 2010.
The 2010 average irrigation water use of SJV counties (1,648 Mgal/day) is about eight times the
average of non-SJV counties (197 Mgal/day). It is interesting to look at the share of water used
for irrigation. Irrigation water use (1,648 Mgal/day) represents about 91% of the total water use
(1,814 Mgal/day) for a county in the SJV while irrigation water use (197 Mgal/day) makes up
only about 42% of the total (469 Mgal/day) for the other counties. Of irrigation water use (1,648
Mgal/day) in the SJV, about 64% (1,056 Mgal/day) is from surface water while the other 36%
(592 Mgal/day) is from groundwater. For counties in the non-SJV region, about 60% of
irrigation water (197 Mgal/day) is from surface water (118 Mgal/day), and 40% comes from
groundwater (79 Mgal/day).
Average domestic water use is only 4% of total use in the SJV, but it is about 15% of total use
for non-SJV counties. It should be noted that the average amount of domestic water use (70
Mgal/day) in the SJV is the same as that in the rest of California. Industrial water use is not a
large share of total water use in either SJV or non-SJV counties. The difference in domestic and
industrial water use between the SJV and the non-SJV region is mostly caused by irrigation use.
To conclude this preliminary analysis, in the SJV the importance of reducing residential water
consumption through water-saving incentives is to help manage water through the potential longterm drought. This indicates the need for more research on residential water-use behavior and
industrial water-use processes so that policy makers can design effective incentives to reduce
water consumption.
Average water use in 2010
Population (000s)
Total water use
Total groundwater use
Total surface water use
Irrigation water use
Irrigation groundwater use
Irrigation surface water use
Domestic water use
Industrial water use
SJV Counties (8)
496
1814
711
1103
1648
592
1056
70
10
Other Counties (50)
666
469
139
330
197
79
118
70
6
Table 4 The Average Water Use in California (SJV vs. Non-SJV) in 2010
80
Residential Water Consumption in Fresno Neighborhoods
To mitigate drought impacts, residential water consumption needs to be reduced in the most
efficient ways. Therefore, the ability to analyze water consumption behavior at the household
level would help planners to target initiatives aimed at reducing water consumption (Troy and
Holloway, 2004). Residential water consumption is affected by physical and socioeconomic
factors. The physical factors can be separated into outdoor and indoor factors, such as lot size,
the presence of pool, landscaping practices, number of bathrooms, and aspect, which is the
direction a house faces (Domene and Sauri, 2006; Wentz and Gober, 2007; Janmaat, 2013). The
socioeconomic characteristics related to household water consumption include household size,
income, and family members’ perceptions of water use (Domene and Sauri, 2006; Wentz and
Gober, 2007; Shandas and Parandvash, 2010; Janmaat, 2013).
A small survey on residential water consumption was conducted for neighborhoods around the
Fresno State campus. Participants were asked to report their winter and summer water
consumption in Hundred Cubic Fee/HCF (1 HCF = 100 cubic feet = 748.5 gallons) along with
the aforementioned physical and socioeconomic factors. Summer water consumption might be
affected more significantly than winter consumption by the aspect of the house and by use for
pools and yard irrigation. Other factors included the size of the house, bathroom count,
household size, and family income. The questionnaire is shown in the Appendix. Tables 5 and 6
present the descriptive statistics for the continuous and discrete water use factors, respectively.
The average water consumption in the winter is 13 HCF while average summer use is 23 HCF,
most likely due to increased water use for pools and yards. The house sizes range from 850 to
3300 square feet. The average house has two bathrooms and three household members.
Continuous variable
Observation
Mean
Minimum
Maximum
Winter water consumption (wwc)
49
13
4
34
Summer water consumption (swc)
37
23
9
68
House size
49
1790
850
3300
Bathroom number
49
2
1
4
Household size
49
3
1
6
Table 5 Descriptive Statistics of Continuous Water Consumption Factors
81
Discrete variable
Pool
Water yard by sprinkler
Water yard by drip
Facing the north
Facing the west
Facing the east
Facing the south
Income larger than $60,000
Income between $40,000 and $60,000
Income between $25,000 and $40,000
Income between $15,000 and $25,000
Light water user
Moderate water user
Heavy water user
Share (%)
41%
84%
10%
31%
28%
22%
19%
44%
25%
19%
12%
28%
59%
13%
Table 6 Descriptive Statistics of Discrete Water Consumption Factors
Winter (wwc) and summer (swc) water consumption were compared against various factors
(e.g., number of bathrooms, presence of pool), with the results shown in Figures 1 to 7.
Physical indoor conditions. Among indoor physical conditions, there is a clear linear trend
between water consumption and number of bathrooms in both the winter and summer (Figure 1).
The number of bathrooms can therefore be used to measure the indoor physical conditions. The
bathroom count might be more suitable for representing the household-scale effects also because
no clear patterns were found for other household size (number of persons) and household income
(Figures 5 and 6). For example, three bathrooms in a house might drive water use more than
there being four or five persons (household size) or an income of $40,000. Only household
incomes exceeding $60,000 appeared to have a significant effect on water usage, most likely
from the presence of a pool and/or the size and condition of the yard.
Outdoor physical conditions. The presence of a pool and the method of yard watering can be
used to measure the outdoor physical conditions. Figure 2 shows households with a pool
consume slightly more water than those without a pool in both summer and winter. Figure 3
clearly reflects the need to water landscape plants and yards in summer. The results show that
using sprinklers is likely to consume more water than other yard-watering means such as hand
watering and drip irrigation. House aspect is another physical factor related to water
consumption. Figure 4 shows that south-facing houses consume more water, particularly in the
summer.
82
0
10
20
30
40
50
Self-perception. Figure 7 indicates that participants’ perceptions of their water use are mostly
consistent with their actual water consumption. However, the actual water consumption of selfdescribed moderate users is no different from those who perceive themselves as heavy water
users. Education on water conservation could improve the perceptions of self-described moderate
water users, who are the majority (59%) compared to self-perceived light water users (28%) and
self-perceived heavy water users (13%).
1
2
3
mean of wwc
4
mean of swc
Figure 1. Winter water consumption (wwc) and summer water consumption (swc) by number of
bathrooms
83
25
20
15
10
5
0
0
1
mean of wwc
mean of swc
0
5
10
15
20
25
Figure 2. Winter water consumption (wwc) and summer water consumption (swc) by the presence
of pool
(1: pool present; 0: no pool present)
0
1
mean of wwc
mean of swc
Figure 3. Winter water consumption (wwc) and summer water consumption (swc) by the
use of sprinklers
(1: sprinklers used; 0: sprinklers not used)
84
40
30
20
10
0
1
2
3
mean of wwc
4
mean of swc
0
10
20
30
40
Figure 4. Winter water consumption (wwc) and summer water consumption (swc) by house aspect
(1: East; 2: South; 3: West; 4: North)
$15000 to $25000 $25000 to $40000 $40000 to $60000
mean of wwc
> $60000
mean of swc
Figure 5. Winter water consumption (wwc) and summer water consumption (swc) by household
income
85
25
20
15
10
5
0
1
2
3
4
mean of wwc
5
6
mean of swc
0
5
10
15
20
25
Figure 6. Winter water consumption (wwc) and summer water consumption (swc) by household
size
1
2
mean of wwc
3
mean of swc
Figure 7. Winter and summer water consumption by water-use perception
(1: light water user; 2: moderate water user; 3: heavy water user)
86
The most interesting part of this small survey was to apply spatial statistics to examine
neighborhood social effects on residential water consumption. The basic assumption is that the
water consumption of a given household will be affected by its neighbors’ water consumption. A
spatial statistical model can capture such spatial autocorrelation between individuals or
neighborhoods on a variety of factors (Wang, Akar, & Guldmann, 2015). Relevant water use
research has found neighborhood social effects on summer water use for yard maintenance
(Janmaat, 2013) and on policy-making for water saving innovations (Wentz and Gober, 2007).
The presence of spatial autocorrelation could imply a spatial multiplier in connection with water
saving innovations. Water policy makers might therefore want to consider neighborhood effects
in conjunction with efforts to reduce water use.
Based on the small survey, a spatial lag model for winter water consumption has been
constructed as shown in Equation 1.
Equation 1
WWC = 0.057·W·WWC+3.06·Bathroom Count
where WWC represents the household winter water consumption, and W represents a spatial
weight matrix based on a defined neighborhood structure to capture the neighborhood social
effects. The spatial lag term W·WWC represents the neighbors’ water consumption within a 1.5mile buffer around a given household.
Only the spatial lag term W·WWC and the variable Bathroom Count are statistically significant
in this case, even though we have observed clear relationships between seasonal water
consumption and several other physical and socioeconomic factors. This may be due to the small
size of the survey we used for the spatial regression modeling. The spatial lag model, however,
clearly shows that residential winter water use is positively affected by the number of bathrooms
and the way your neighbors use water.
The methods of this model could be applied to neighborhood social effects on summer water use
as well. Unfortunately, the responses to our survey were not sufficient to support. An important
factor is the timing of conducting a water consumption survey is important. We found that many
household participants could not provide their summer water consumption because they did not
keep their summer water bills. Studying summer water use would likely prove valuable since
people tend to use more water in the summer in the SJV. A further large-scale residential water
consumption survey is needed to provide necessary water planning information.
Summary
California has been suffering from a severe drought problem, particularly the SJV where less and
less water can be used to support existing activities. Obviously, agriculture takes the lion’s share
of water use in the SJV and is definitely the first area of concern in a drought, representing about
91% of total water use. The findings outlined above demonstrating that residential water use is
not very significant, however, can in itself inform public dialogue and education and inform
policy making, especially when debating how to target precious time and resources when
addressing a potential long-term drought.
87
In addition, while on the county level in the SJV municipal water use might be of little overall
significance that does not preclude efforts to help improve residential awareness and use of water
as a finite resource. Residential water saving could be encouraged by incentives based on the
understanding of water use behavior. Residential water saving innovations could be integrated
into a comprehensive policy-making process. Finally, residential water use is a factor in water
scarcity.
A small water consumption survey from a class project was conducted to serve the abovementioned purpose. The factors related to water consumption included indoor and outdoor
physical conditions of the house and socioeconomic characteristics of the household. The results
revealed several interesting findings. Among the outdoor physical conditions, the presence of
pools and sprinkler systems resulted in higher water consumption, particularly in the summer.
Also, the houses facing south used more water in the summer. These results all indicate that
summer water use is highly related to outdoor physical conditions, implying the need for
innovation related to summer water use. The indoor physical conditions related to water
consumption are best measured by the number of bathrooms. A strong positive relationship has
been found between the number of bathrooms and both the winter and summer water use. Again,
water saving innovations for toilets and faucets would be most helpful for reducing water
consumption. Household size and income do not seem to have clear impacts on water
consumption. This result might be due to the small survey size, a problem which could be
resolved by conducting a large-scale residential water consumption survey.
Two other important factors were included. First, examining people’s perception of their water
use showed interesting results in that people who rank themselves as moderate water users
actually consume as much or more water than those who think of themselves as heavy water
users. Water conservation education could help to promote awareness of water scarcity.
Second, and most importantly, neighborhood social effects have become a new research focus
for residential water use. The water consumption of a given household is likely affected by its
neighbors, resulting in similar water use patterns across neighborhoods. This result was found in
our spatial statistical model for winter water consumption. Modeling summer residential water
consumption might have more interesting results, especially in a region such as the SJV, and was
only precluded due to timing of this study. It would be helpful to have knowledge of
neighborhood social effects on summer residential water consumption for policy making.
In sum, a large-scale residential water consumption survey is needed to provide sufficient
planning information for the potential long-term drought. The resulting information could help
with reducing water consumption not only in the San Joaquin Valley but in all of California.
88
Intra-Chapter Snapshot
By G. Harootunian and N. Chowdhury
Mohammed Alrihimi, who travelled from Yemen, predicted to be the first nation in the
world to run out of water, to search for a better future in the San Joaquin Valley.
A Census-Designated Place: A Glimpse into One Disadvantaged Community
Strathmore is typical of the rural nature of many parts of the Valley, where small towns
formally exist only as “census-designated places” for the purpose of counting U.S. citizens every
10 years. Strathmore’s population (2,819) reflects the SJV’s population: majority-minority,
predominately Latino with a sizable chunk of Caucasians and a sprinkling of other populations
such as American Indian or African American. The U.S. Census shows that Median Family
Income is $25,236.
Photographer Neil Chowdhury ended up in Strathmore on March 8th 2015 while driving
to take a look at the former site of Tulare Lake, drained in the early 20th century to be used for
cotton fields, though the area seemed devoid of any crops that day. Neil met Mohammed
Alrihimi, and his two young sons tending his general store on the Strathmore’s tiny main street,
which boasted few other occupied buildings. Neil is not sure where the other 2,816 people of
Strathmore were hiding on that particular Sunday afternoon, as other than Mohammed and his
family, the place seemed deserted. When Neil asked Mohammed if he thought the drought had
changed things in Strathmore, the reply was simple: Sundays used to be very busy for the general
store, but now hardly anyone comes in to shop.
Editor’s Note: See Boucek, Christopher. “Yemen: Avoiding a Downward Spiral.” Carnegie Endowment for
International Peace. http://carnegieendowment.org/2009/09/10/yemen-avoiding-downward-spiral [accessed 2015,
21 May]. See U.S. Census American Fact Finder (2009-2013) for Strathmore demographics.
89
Chapter 4
Public Health Implications of Drought
Dr. Samendra Sherchan, Department of Public Health
Abstract
Drought leads to many environmental issues that affect human health and the ecosystem. Healthrelated issues that can arise from drought include infectious diseases, chronic diseases, and
vector-borne diseases, themselves exacerbated by the sanitation and hygiene, food and nutrition,
and water limitation issues also caused by the drought. Changes in air quality have a tendency to
cause respiratory health issues and can increase the risk of diseases such as Chronic Obstructive
Pulmonary Disease and asthma. Other drought-related factors can affect air quality, including the
presence of toxins originating from freshwater blooms of cyanobacteria, which can become
airborne and can lead to adverse public health. Outbreaks of West Nile Virus are common during
drought and can pose many health issues. West Nile Virus is a virus where birds are the
reservoirs and humans and horses become the hosts. A person can become infected when bitten
by a mosquito that has fed off an infected bird. Mosquitos tend to reproduce in areas where there
is stagnant water, and this has become a huge problem in California where the drought results in
shrunken standing pools and reservoirs of water. Drought can also impact human health through
its impact on agricultural production. Low crop yields can result in rising food prices and
shortages, potentially leading to malnutrition. In addition, severe drought poses an immediate
and severe threat to freshwater sources. Over time, reduced precipitation and increased
evaporation of surface water mean that groundwater supplies are not replenished at a typical rate.
As a result, water utilities around the State are planning to augment their current drinking water
supplies with treated wastewater, but in order to implement direct potable reuse they have to
overcome public health risks and public perception regarding “toilet to tap” water. 25
Key Findings
Coccidioidomycosis (Valley Fever)
1. The annual rates of Coccidioidomycosis (Valley Fever) in California increased by 67.7
percent from 2009 (6.5 per 100,000 population) to 2012 (10.9 per 100,000). The San Joaquin
Valley is the major region of Coccidioidomycosis endemicity in California.
2. Five of those six counties with the highest average annual incidence rates from 2009–2012
are in the San Joaquin Valley: Kern (205.1 per 100,000), Kings (191.7 per 100,000), Fresno
(64.5 per 100,000), San Luis Obispo (47.2 per 100,000), Tulare (39.2 per 100,000), and
Madera (20.7 per 100,000).
25
Drought impacts can also include mental and behavioral health issues for those most at-risk. For example, the
National Farm Medicine Center conducted a study during nine years of an epic drought in Upper Midwest. Findings
included that more than 900 male farmers and ranchers in Wisconsin, Minnesota, North Dakota, South Dakota, and
Montana committed suicide in the 1980s. In some years, the suicide rate was nearly double the national average for
white men (cited in “Public Health and Drought: Challenges for the 21st Century, Centers for Disease Control and
Prevention, http://www.cdc.gov/features/drought/index.html).
90
West Nile Virus (WNV)
3. WNV was also detected at an all-time high in 44 counties in California, with 379 human
cases reported (2013).
4. In 2013, the baseline incidence statewide for WNV Disease was 1.00 (1 case per 100,000
persons) though the incidence for WNV infection is 1.14.26 The incidence for San Joaquin
Valley counties were Stanislaus (3.25); Kern (2.90); Madera (1.97); San Joaquin (1.14);
Tulare (1.10); Fresno (0.84); Kings (0.66); and Merced (0.00).
5. In 2013, WNV was detected in 2,528 mosquito pools from 27 counties (CDPH, 2013b). The
baseline incidence Minimum Infection Rate statewide was 3.2. In the San Joaquin Valley,
the rate were Madera (8.7), Kings (6.2), Kern (5.4), Tulare (4.8), San Joaquin (4.6),
Stanislaus (3.2), Merced (3.0), and Fresno (2.2) counties.
6. Fresno County observed rate increases in WNV and Campylobacteriosis (Diarrheal Illness)
infections.
Campylobacteriosis (Diarrheal Illness)
7. In 2012, Fresno Country observed a significant increase in Campylobacteriosis cases with
an incidence of 40.3 per 100,000 populations.
8. The Campylobacteriosis statewide incidence rate was 20.1 (per 100,000) in 2013. Seven out
of the eight San Joaquin Valley counties’ incidences were higher than the statewide
incidence. The incidence rates in Fresno County (43.6) and Tulare County (42.3) were over
twice the statewide rate (20.1). The incidence rate in Kern (39.7) was almost twice as high
as the statewide rate. The incidence rates in the four other counties were above the statewide
rate to varying degrees: Madera (33.3), San Joaquin (26.6), Merced (23.2), and Stanislaus
(22.0). The eighth county, Kings, had a potentially unreliable rate.
The San Joaquin Valley (SJV)
1. Air quality
The dry, dusty conditions associated with drought can lead to infectious disease, such as Coccidioidomycosis (Valley Fever). This fungal infection is associated with inhaling spores of the
fungus, Coccidioides spp., that become airborne when soil is disrupted. Coccidioidomycosis
causes a range of symptoms, including fever, chest pain, coughing, rash, and muscle aches. The
SJV is the major region of Coccidioidomycosis endemicity in California.
Air quality issues created by the drought can also cause illnesses such as Chronic Obstructive
Pulmonary Disease and asthma, which are very common with people residing in the California’s
SJV. People who are at higher risk for developing respiratory issues include those who are
26
WNV infection identifies infections that are detected through blood bank screen, but no associated illness is
reported.
91
immunocompromised, older, in their third trimester of pregnancy, or of African-American,
Asian, Hispanic, or Filipino descent.27
Fresno County observed significant increase in cases of reported Coccidioidomycosis in 2010
and 2011 with total community and institutional cases of 726 and 720 respectively. After
implementation of active control measures such as spraying soil sealants, the number of cases
decreased significantly to 502 in 2012 (Figure 1). From 2007–2012, the 25–64 year age group
was at higher risk and represented the highest number of Coccidioidomycosis cases (Table 1).
The annual incidence rates of Coccidioidomycosis reported among African Americans, Whites,
and Hispanics decreased significantly by 31.65%, 42.2%, and 22.6% respectively. However,
during 2007–2012, the rate of Coccidioidomycosis reported among Native Americans/Alaskan
natives and Asian/Pacific Islanders increased significantly by 380% and 97.67% respectively
(Figure 2).
In all of California, the annual rate of Coccidioidomycosis increased by 67.7 percent from 2009
(2,399 case-patients; 6.5 per 100,000 population) to 2012 (4,094 case-patients; 10.9 per
100,000). The annual incidence rate was highest in 2011 with 13.9 per 100,000 population and
from 2009–2012, 213 case-patients were reported to have died with Coccidioidomycosis
(California Department of Public Health, 2012).
Approximately 73.6% of case-patients with Coccidioidomycosis were reported from only six
counties in California, however, which are established Coccidioides-endemic areas in the state of
California. Five of those six counties with the highest average annual incidence rates from 2009–
2012 are in the SJV: Kern (205.1 per 100,000), Kings (191.7 per 100,000), Fresno (64.5 per
100,000), San Luis Obispo (47.2 per 100,000), Tulare (39.2 per 100,000), and Madera (20.7 per
100,000) counties (Figure 3). The one county—San Luis Obispo—not within the SJV region of
this study abuts it (Kern County).
27
Editor’s Note: The SJV has a majority population of Hispanic descent, as well as sizable populations of Filipino
and Asian descent, followed by large numbers of persons with African descent. The predominant SJV population,
therefore, is at higher risk for respiratory issues such as COPD and asthma. Moreover, the SJV is already
experiencing serious challenges with these health issues. Vast tracts of the San Joaquin Valley have been designated
as Environmental Justice areas by the San Joaquin Valley Air Pollution Control District. See Editor’s Insert: San
Joaquin Valley Air Pollution Control District: Environmental Justice Map (8 June 2015) and Editor’s Snapshot:
“The Health Drought” following this chapter.
92
Figure 1 Annual trend of reported cases of Coccidioidomycosis in Fresno County from 2007-2012
(Rutledge, 2013)
Table 1 Annual trend of reported cases of Coccidioidomycosis in Fresno County from 2007-2012,
stratified by age group (Rutledge, 2013)28
**Total includes both institutional and community cases.
28
The totals in Table 1 may not add up to annual totals due to incomplete data.
93
Figure 2 Annual trend of reported cases of Coccidioidomycosis in Fresno County
from 2007-2012, stratified by race/ethnicity (Rutledge, 2013)
94
Figure 3 California county-specific coccidioidomycosis incidence rates
(California Department of Public Health [CDPH], 2012)
95
2. Water quality and mosquito-borne diseases
The conditions caused by a drought can lead to breeding grounds for mosquitoes and a potential
increase in mosquito-borne diseases, such as Western Equine encephalomyelitis virus, St. Louis
encephalitis virus, and West Nile Virus (WNV).
For example, the SJV like many parts of California depends on groundwater as a primary source
of drinking water. Reduced precipitation and increased evaporation of surface water can impact
the recharge of groundwater supplies over time. Several areas throughout the SJV have reported
decreased levels of water in wells in the face of drought. A USGS monitoring well in Mendota is
an illustration, where water depth has been significantly reduced due to drought (Figure 4).
Decreased reliance on groundwater levels during a drought results in increased reliance on
surface water (already experiencing reduction from the drought). The Merced River flow is an
example of surface water affected by the drought (Figure 5). The discharge and quality of water
from rivers such as the Merced River have broad effects on several factors such as water
availability and ecosystem health. Mosquito-borne diseases, such as Western Equine
encephalomyelitis virus, St. Louis encephalitis virus, and WNV, are a prime concern.
96
Figure 4 Monitoring well in Mendota (United States Geological Survey [USGS], 2014)
97
Figure 5 Surface water monitoring in Merced River (USGS, 2014)
98
West Nile Virus (WNV)
WNV is one of the major environmental health issues associated with a drought in California.
WNV activity was detected in 44 counties in 2013 with 379 human cases reported, the highest
since surveillance began for WNV in California in 2000. Over the ten-year period from 2004–
2013, over 4,000 human WNV cases, including 145 fatalities, have been detected in the state of
California.
Table 2 provides the 2013 baseline incidence statewide for WNV Disease (1.00, or 1 case per
100,000 persons) though the incidence for WNV infection is 1.14.29 The incidence for SJV
counties was Stanislaus (3.25); Kern (2.90); Madera (1.97); San Joaquin (1.14); Tulare (1.10);
Fresno (0.84); Kings (0.66); and Merced (0.00). Five of the eight SJV counties—Stanislaus,
Kern, Madera, Tulare, and San Joaquin—have incidence rates equal to or above the statewide
rate. 30
In June 2013, Aedes aegypti (Yellow Fever mosquito), an exotic mosquito species, was also
detected, first in Madera County and subsequently in Fresno and San Mateo counties (CDPH,
2013b).
Mosquito surveillance
In 2013, WNV was detected in 2,528 mosquito pools from 27 counties (CDPH, 2013b). Table 3
provides the 2013 baseline incidence Minimum Infection Rate statewide as 3.2.31 In the SJV, the
rates were Madera (8.7), Kings (6.2), Kern (5.4), Tulare (4.8), San Joaquin (4.6), Stanislaus
(3.2), Merced (3.0), and Fresno (2.2) counties.32 Six of these counties—Madera, Kings, Kern,
Tulare, San Joaquin, and Stanislaus—have minimum infection rates equal to or above the
statewide rate.33 Of the counties with the highest minimum infection rates in the entire state, one
was in a northern cluster, Glen (7.6), but the other three were in the SJV: Madera (8.7), Kings
(6.2), and Kern (5.4).
29
WNV infection identifies infections that are detected through blood bank screen, but no associated illness is
reported.
30
Editor’s Note: A northern cluster of California counties have sharply high incidence rates: Glenn County (31.7);
Yuba (17.7) Butte (10.8); Sutter (10.4); Colusa (9.24); and Tehama (7.87).
31
The “Minimum Infection Rate” = (No. of positive pools x No. mosquitos in pool) x 1,000.
32
Again, a northern cluster of counties have high rates, such as Glen (7.6), Butte (4.7), Yolo (4.7), and Yuba (4.6).
33
Editor’s Note: Five of these counties also have the highest average annual incidence rates of Valley Fever in
California from 2009–2012: Kern (205.1 per 100,000), Kings (191.7 per 100,000), Fresno (64.5 per 100,000), San
Luis Obispo (47.2 per 100,000), Tulare (39.2 per 100,000), and Madera (20.7 per 100,000) counties (see pg. 103;
Figure 3, pg. 106). As noted, the one county—San Luis Obispo—not within the SJV region of this study abuts it
(specifically, Kern County).
99
Table 2 Reported WNV human cases by county of residence, California, 2004-2013 (CDPH, 2013b)
100
Table 3 Results of testing mosquitoes for West Nile virus, California 2013 (CDPH, 2013b)
101
Animal surveillance
In 2013, out of 16,849 chicken blood samples that were tested, 485 seroconversions to WNV
were detected among 112 flocks in 26 counties. WNV was detected 1,416 (43%) dead bird
carcasses out of 3,306 from 40 counties, and of these, 1,251 (37.8%) were acute infections,
meaning the infection occurred within the 2013 surveillance season, from 37 counties. Of 97
dead squirrels carcasses tested, WNV was detected in eight (8.2%) carcasses from 7 counties
(Table 4). The California Animal Health and Food Safety Laboratory tested horses displaying
neurological signs and detected WNV in 13 horses from seven counties (Table 4). The statewide
WNV infection rate in mosquitoes was higher in 2013 than in any other year (CDPH, 2013b).
Table 4 also shows WNV human infections in California in 2013. Out of the state’s total fifty
eight counties, twenty five counties (43%) had no reported WNV human infection, and 10
counties (17%) had 1 reported WNV infection. The highest numbers of WNV infections were in
Los Angeles (172), Kern (30), Stanislaus (19), San Joaquin (10), Tulare (9), Fresno (8), and
Madera (4) counties. Kings had only 1 infection, and, again, Merced had no reported WNV
human infection. In the entire state, of the five counties with the highest human WNV infection
rate, two are in the SJV: Kerns (30) and Stanislaus (19). The three other counties are Los
Angeles (172) and nearby Riverside (40), and Butte (24) in the northern cluster.
102
Table 4 Infection with West Nile virus in California, 2013 (CDPH, 2013b)
103
Fresno County
Table 5 shows an across the board increase in WNV confirmed cases from 2011 to 2012. Of note
are the following:
1) 24 total confirmed WNV cases of in 2012 compared to 9 total confirmed WNV cases in
2011.
2) 19 confirmed WNV hospitalized cases in 2012 compared to 5 confirmed WNV
hospitalized cases in 2011.
3) 16 confirmed WNV neuroinvasive cases in 2012 compared to 6 confirmed WNV
neuroinvasive cases in 2011 (Rutledge, 2013).
Figure 6 shows the historical trends of WNV cases from 2005–2012. All non-neuroinvasive,
neuroinvasive and presumptive (PVDs) cases have increased since 2006. Ethnic/race differences
presented in Figure 7 illustrates that white and Hispanic/Latino populations were at higher risk
and reported the greatest burden of WNV. Age also enters into a person’s risk. 54% of the total
reported cases in 2012 were in people over 60 years old, 37.5% were people from 40-59 years of
age, and 8.5% were in people from 20-39 years of age. There were no reported cases in people
from 0–19 years of age. A unique characteristic of this disease is it occurs during specific times
of the year, mostly in fall (Figure 8).
Table 5 WNV 2011 and 2012 comparison, Fresno County (Rutledge, 2013)
104
Figure 6 WNV annual trend 2005–2013 by disease severity, Fresno County (Rutledge, 2013).
Figure 7 WNV ethnic/race difference by age group, Fresno County (Rutledge, 2013).
105
Figure 8 WNV seasonal trend 2012 in cases, Fresno County (Rutledge, 2013).
3. Food-borne illnesses
The quality and quantity of the nation’s food supply can be affected by drought conditions,
which can potentially lead to several types of adverse health effects. The SJV is primarily known
for being the bread basket of the United States but due to inadequate rainfall and precipitation,
crop yields have decreased. Also, substantial amounts of water are needed to produce and
prepare food at the industrial level; water shortages can then affect food safety and potentially
cause an increase in food-borne diseases. In California, Campylobacteriosis (a diarrheal illness)
has increased significantly.
Fresno County
In 2012, Fresno Country observed a significant increase in Campylobacteriosis cases with an
incidence of 40.3 per 100,000 populations, which stands in contrast to the clear but slower
increase in Salmonellosis (Figure 9). The annual incidence rate of Campylobacteriosis observed
in 2012 is significant with a p-value of 0.0000 and a rate ratio of 1.63 whereas the rate ratio of
Salmonellosis is 0.9731 with an insignificant p-value of 0.7609 (Rutledge, 2013). These p-values
represent the probability of getting the observed or more extreme results, given that the null
hypothesis is true, so the low p-value for Campylobacteriosis indicates that the observed 2012
results are not probable whereas the high p-value for Salmonellosis means that the observed
2012 results were probable. Figure 10 depicts the monthly trend of reported cases of
Salmonellosis and Campylobacteriosis in Fresno County in 2012 and summer months (May,
June, and July), which have the greatest cases of both foodborne illnesses. Children are more
106
susceptible to these foodborne illnesses as shown in Figure 11. Ethnic/race differences presented
in Table 6 illustrate that Hispanic/Latino populations appear to have a higher rate of
Campylobacteriosis (42.44 per 100,000 population); followed by white (38.61 per 100,000
population); and Black/African American (34.51 per 100,000 population).
For the state of California, Campylobacteriosis was detected in 55 counties in 2013 with 7,698
cases reported, with an incidence rate of 20.1 per 100,000, whereas Salmonellosis was detected
in 52 counties in 2013 with 5,046 cases reported, with an incidence rate of 13.2 per 100,000
(CDPH, 2013a). Over the three-year period from 2011–2013, Campylobacteriosis cases
increased from 6,758 to 7,698, whereas Salmonellosis cases increased from 4,034 to 5,046
(CDPH, 2013 a).
Figure 12 shows the Campylobacteriosis incidence rate for the SJV counties compared to the
statewide rate of 20.1 (per 100,000) in 2013. The highest incidence was in San Francisco County
(47.4). Seven out of the eight San Joaquin Valley counties’ incidences were higher than the
statewide incidence. The incidence rates in Fresno County (43.6) and Tulare County (42.3) were
over twice the statewide rate (20.1). The incidence rate in Kern (39.7) was almost twice as high
as the statewide rate. The incidence rates in the four remaining SJV counties were above the
statewide rate to varying degrees: Madera (33.3), San Joaquin (26.6), Merced (23.2), and
Stanislaus (22.0). The eighth county, Kings, had a potentially unreliable rate.
Figure 13 shows the Salmonellosis incidence rate for the SJV counties compared to the statewide
rate of 13.2 (per 100,000 persons). The highest incidence was in Yuba County (34.1). Four SJV
counties’ incidences were above the statewide rate: Fresno (20.5 per 100,000), San Joaquin
(15.2) Madera (15.0), and Stanislaus (13.7). The incidence rates in the remaining two other SJV
counties were below the statewide rate: Merced (12.9) and Tulare (12.3). One SJV county has
the lowest reliable incidence rate: Kern (7.8).
107
Figure 9 Annual trend of reported cases of Salmonellosis and Campylobacteriosis
in Fresno County from 2004–2012 (Rutledge, 2013). 34
Figure 10 Monthly trend of reported cases of Salmonellosis and Campylobacteriosis
in Fresno County in 2012 (Rutledge, 2013)
34
Editor’s Note: Rutledge notes that public health campaigns may have contributed to the reported increase for a
variety of factors (more people are aware of the infection and seek treatment, more physicians test for it, and so on).
108
Figure 11 Age Group trend of reported cases of Salmonellosis and Campylobacteriosis
in Fresno County from 2012 (Rutledge, 2013).
Table 6 Cases and Rates of Salmonellosis and Campylobacteriosis stratified by Ethnicity and
Race in 2012. Rates are per 100,000 population (Rutledge, 2013).
109
Year of Estimated Illness Onset
Fresno
Kern
Madera
Merced
San Joaquin
Stanislaus
Tulare
CALIFORNIA TOTAL
0
5
10
15
2013
20
25
2012
2011
30
35
40
45
50
Figure 12 Campylobacteriosis, Cases and Rates by Health Jurisdiction, California, 2011–2013 (CDPH, 2013a)35
Year of Estimated Illness Onset
Fresno
Kern
Madera
Merced
San Joaquin
Stanislaus
Tulare
CALIFORNIA TOTAL
0
5
10
2013
2012
15
20
25
2011
Figure 13 Salmonellosis, Cases and Rates by Health Jurisdiction, California, 2011–2013 (CDPH, 2013a)
35
Editor’s Note: Kings County had a “potentially unreliable rate, relative standard error 23 percent of more” (pg. 22).
110
Key Findings
Coccidioidomycosis (Valley Fever)
1. The annual rates of Coccidioidomycosis (Valley Fever) in California increased by 67.7
percent from 2009 (6.5 per 100,000 population) to 2012 (10.9 per 100,000). The San
Joaquin Valley is the major region of Coccidioidomycosis endemicity in California.
2. For the SJV counties, the annual incidence rates from 2009–2012 were Kern (205.1 per
100,000), Kings (191.7 per 100,000), Fresno (64.5 per 100,000), Tulare (39.2 per 100,000),
and Madera (20.7 per 100,000).
West Nile Virus (WNV)
3. WNV was also detected at an all-time high in 44 counties in California, with 379 human
cases reported (2013).
4. In 2013, the baseline incidence statewide for WNV Disease was 1.00 (1 case per 100,000
persons) though the incidence for WNV infection is 1.14.36 The incidence for SJV counties
were Stanislaus (3.25); Kern (2.90); Madera (1.97); San Joaquin (1.14); Tulare (1.10);
Fresno (0.84); Kings (0.66); and Merced (0.00).
5. In 2013, WNV was detected in 2,528 mosquito pools from 27 counties (CDPH, 2013b). The
baseline incidence Minimum Infection Rate statewide was 3.2. In the SJV, the rate were
Madera (8.7), Kings (6.2), Kern (5.4), Tulare (4.8), San Joaquin (4.6), Stanislaus (3.2),
Merced (3.0), and Fresno (2.2) counties.
6. Fresno County observed rate increases in West Nile Virus and Campylobacteriosis
(Diarrheal Illness) infections.
Campylobacteriosis (Diarrheal Illness)
7. In 2012, Fresno Country observed a significant increase in Campylobacteriosis cases with
an incidence of 40.3 per 100,000 populations.
8. The Campylobacteriosis statewide incidence rate was 20.1 (per 100,000) in 2013. Seven out
of the eight SJV counties’ incidences were higher than the statewide incidence. The
incidence rates in Fresno County (43.6) and Tulare County (42.3) were over twice the
statewide rate (20.1). The incidence rate in Kern (39.7) was almost twice as high as the
statewide rate. The incidence rates in the four other SJV counties were above the statewide
rate to varying degrees: Madera (33.3), San Joaquin (26.6), Merced (23.2), and Stanislaus
(22.0). The eighth county, Kings, had a potentially unreliable rate.
36
WNV infection identifies infections that are detected through blood bank screen, but no associated illness is
reported.
111
SNAPSHOT: The Health Drought
By Gil Harootunian, PhD
While the preceding chapter explores the public health impact of the drought, one need
only click on the “Environmental Justice” map of the San Joaquin Valley Air Pollution
Control District to see that map blankets the entire region (as it has for a long, long time):
http://valleyair.org/Programs/EnvironmentalJustice/Environmental_Justice_idx.htm.
Some questions that might arise are these:
How does a region already in a health drought absorb more impacts?
How does a region already in a financial drought absorb more costs of health care?
“California Health Profiles” UCLA Center for Health Policy Fresno County California
Adults (18 years-+) (2012-2013)
Uninsured
35%
26.1%
No usual source of care
24.9%
16.8%
Medi-Cal or Health Families
27.7%
11.7%
Fair or Poor Health
29.2%
19.6%
Current Asthma
12.4%
7.9%
Children (0-17 years) (2011-2012)
Uninsured (all or part of year)
11%
7.7%
No usual source of care
4.7%
8.8%
Medi-Cal or Health Families
49.9%
40.5%
Current Asthma
15.7%
10.1%
The American Lung Association rates the cleanest and the most polluted cities in U.S. For all
three measures―ozone pollution, short-term particle pollution, and year-round particle
pollution―four of the five worst cities are in the Central Valley.37
As far back as 2008, the William and Flora Hewett Foundation funded a study, The Benefits of
Meeting Federal Clean Air Standards in the South Coast and San Joaquin Valley Air
Basins (see Hall). Findings include the following:
 Air pollution is a particularly detrimental situation in an enclosed air basin like the SJV.
Ozone levels typically exceed during warmer months, and PM2.5 typically exceeds during
the cooler fall and winter months, so there is no “clean” season.
 In the SJV overall, the cost of air pollution is more than $1,600 per person per year, which
translates into a total of nearly $6 billion in savings if federal ozone and PM2.5 standards
were met (5).
 The documented health effects include both infant and premature adult mortality, plus events
such as nonfatal heart attacks and conditions such as chronic bronchitis and asthma. Related
consequences include school absenteeism and work loss days. There is no measure for the
“value of avoiding the pain and anxiety caused by the underlying condition” (58-75).
 In the SJV, “…the overall benefits of attaining the NAAQS are dominated by premature
mortality…. [O]ver 800 people are estimated to avoid premature death annually, accounting
only for the effect of PM2.5 and only for the population aged 30 and older. With a value for
each life of $6.63 million, this effect alone offers a benefit of attainment of over $5 billion
each year” (77).
37
http://www.stateoftheair.org/2015/city-rankings/most-polluted-cities.html
112
SNAPSHOT: From Economic Distress to Psychological Distress
By Gil Harootunian
The National Farm Medicine Center conducted a study during nine years of an epic
drought in Upper Midwest in the 1980s. Findings included that more than 900 male
farmers and ranchers in Wisconsin, Minnesota, North Dakota, South Dakota, and
Montana committed suicide. In some years, the suicide rate was nearly double the
national average for white men.38 The CDC’s “Drought Toolkit” for vulnerable
populations includes those experiencing mental illness (particularly stress, anxiety, and
depression).39
The question is posed for this final time: when water distress hits, how thick or thin is the
margin for those areas already experiencing higher than average psychological distress?
The UCLA Center for Health Policy Research provides information on Serious
Psychological Distress (SPD)* in county populations for 2012-2013 (the beginning of the
drought). Measure of America’s well-being profiles provide the number of practicing
physicians per county (2013-2014 data sets), one indicator of the community’s capacity
to meet medical demands.
Below, three counties—Kern, Kings, Madera—have the highest percentage of persons
experiencing Serious Psychology Distress and the lowest number of practicing
physicians. This in itself raises another set of questions, e.g., among such limited medical
personnel, are there enough Spanish and Hmong speakers to handle crisis situations?
State/County
Serious Psychological
Practicing Physicians
Distress
Per County (per 10,000
population)
California
8.1%
Fresno
8.8%
6
Kern
13.9%
4
Kings
14.4%
3
Madera
12.4%
4
Merced
4.7%
4
San Joaquin
11.8%
5
Stanislaus
7.0%
6
Tulare
8.8%
4
San Francisco (high)
14
Los Angeles
7
San Diego
7
*Serious Psychological Distress (SPD) is often used as a proxy measure for severe
mental illness in a population. Adult respondents were asked 6 questions, known as the
“Kessler 6,” to assess symptoms of distress during a 30-day period in the past year.
Cited in “Public Health and Drought: Challenges for the 21st Century,” Centers for Disease
Control and Prevention: http://www.cdc.gov/features/drought/index.html.
38
39
See http://www.cdc.gov/nceh/drought/toolkit/vulnerable_populations.htm.
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San Joaquin Valley Air Pollution Control District: Environmental Justice Areas (green areas do not meet standards).
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East Porterville:
A Video Vignette of Drought Impact on one Disadvantaged Community
By Jes Therkelsen, MFA, Department of Mass Communication and Journalism
“[T]his is global.” Donna Johnson, Porterville resident.
The preceding chapter addressed the public health impacts from the drought. What happens
when drinking water actually runs out?
East Porterville, California, is a small, economically Disadvantaged Community whose
residents rely on wells for their potable water. In 2014, wells in East Porterville began to
dry up. County officials found themselves responding to an emergency they have never
faced before: a community without water.
International media attention soon came. Resident Donna Johnson explains, “I pushed for
[the media attention] because everyone wanted to brush it under the carpet.” Porterville
became the poster child for the California drought, having been reported by every major
news organization in the U.S. and abroad.
This video vignette follows the work of Donna Johnson, a Porterville resident who began
buying bottled water for her neighbors who could not afford it. Andrew Lockman, a county
official, works with Donna Johnson and the residents to establish temporary solutions until
a more permanent resolution is determined. Lockman notes that residents with only 10’ of
water left in their wells began giving this “last little bit of water” to help neighbors who
wells have gone dry. The community’s response has inspired others who might face similar
situations as the drought worsens in other parts of the state.
https://vimeo.com/124558471. Password: Porterville.
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Conclusion and Recommendations
Overview: Severity and Impact of the California Drought
Researchers from NASA and Cornell and Columbia Universities recently warned of major water
shortages that will dry out vegetation, leading to monster wildfires in Arizona and California
(Fears, February 12, 2015). These studies were forecasting mega-droughts over the next 35 years
in the western United States.
A study led by Noah Diffenbaugh at Stanford University concluded that California should get
used to extended drought conditions (Diffenbaugh, Swain, & Touma, 2015). Diffenbaugh and his
team explored the role temperature has played in California’s drought for the last 120 years.
Between 1896 and 1994, climate patterns in the state created a 50 percent chance that a year of
extremely warm temperatures would merge with a year of moderately dry conditions. But
between 1995 and 2014, extreme temperature years were so common that the chance of
combining with a dry year increased to 80 percent.
The lowest precipitation year on record in the state was between 2013 and 2014, and 2014 was
the single hottest year in California’s recorded history. These conditions are expected to persist
in the years to come. In other words, before we experience mega-droughts in a few decades, it is
very likely we will be living with regularly hot and dry years.
The economic impact of the drought in the San Joaquin Valley will have wider impacts.
California supplies nearly half of all U.S. fruits, vegetables, and nuts. The San Joaquin Valley is
the source of roughly 25 percent of the nation’s table food. This means California’s agriculture is
concentrated where the drought has hit the hardest. If drought continues, agriculture may soon
play a less important role in California’s economy, as the more water-intensive segment of
agriculture move to the South and the Midwest, where water for irrigation is more available.
Production levels for thirsty crops like alfalfa and cotton have already diminished significantly in
the last few years. Between 2006 and 2010 alone, the amount of land irrigated for cotton fell by
46 percent. Continued drought may eventually force the U.S. to import products that have been
produced in California, such as select vegetables, fruits, and hard nuts.
A serious consequence of reduced precipitation and resulting decreased surface water availability
is the overdraft of groundwater. Three years ago, groundwater made up one-third of California’s
total supply. Today, groundwater makes up a full 75 percent of California’s total supply. It is
estimated that 15 to 20 percent of the nation’s groundwater use is coming from the Central
Valley alone. The total economic impact of this factor is beyond the scope of this report, but it is
noted that in some groundwater aquifers, excessive extraction causes subsidence (ground
sinking), potentially damaging infrastructure such as canals, roads, and buildings (Shalby, 2015).
Our Findings from this Study: The San Joaquin Valley
An examination of the historical trends of precipitation, streamflow, reservoir storage, irrigation
water use, and changes in groundwater depth clearly indicates the unprecedented impact of
drought in California, with a disproportionate heavy blow to the San Joaquin Valley (SJV)
116
region that has a high concentration of irrigated agriculture. In the past three years, precipitation
has dropped to less than one-third (over one standard deviation) of its normal level during the
past one hundred years. If subsequent years have precipitation ranges approaching those of 2014,
the state’s reservoir storage shortage will continue to worsen. As a result, SJV water use will
likely come under additional scrutiny. The SJV has higher-than-average water consumption
compared to the rest of the state, largely due to its hotter climate and agricultural activities. On
average, the SJV counties use more water (1,814 Mgal/day) per county than non-SJV counties
(469 Mgal/day), due to agricultural activities.40 Recent news reports have already reflected
concerns by some citizens and pundits about water use and agricultural investments in the SJV.
The issue is that it takes more water in the SJV to sustain the equivalent living conditions found
in other parts of the state. Decreased water availability in the SJV could cause collapse of both
the economy and government, forcing the balance of the state to support the remaining
population that cannot leave. Growers are now relying more on groundwater than in the past, and
this consumption pattern is not sustainable long-term.
Agriculture, water, and energy usages are highly correlated. While water shortage due to drought
has a direct adverse impact on water availability and thus crop production, it also increases
energy consumption as a result of extended lift that is required for groundwater extraction. On
top of this, California loses significant hydropower energy production due to reductions in
surface water supplies that drive the turbines.
In the SJV, the economic impact on agricultural revenue alone will be billions of dollars. Dr.
Fayzul Pasha’s findings (chapter 1) on the impact of the drought on agricultural revenue solely
from escalating pumping costs were as follows:
5 inches of precipitation (annual): $2.564 billion loss in agricultural revenue
4 inches of precipitation (annual): $2.827 billion loss in agricultural revenue
3 inches of precipitation (annual): $3.098 billion loss in agricultural revenue
2 inches of precipitation (annual): $3.35 billion loss in agricultural revenue
The continued drought also affects local economies (chapter 2). This can result in reduced/lost
household income and negatively impacted tax bases for local governments. The combination of
these effects is especially felt in families living in Disadvantaged Communities. Dr. Antonio
Avalos’s analysis indicates that although the unemployment rate hasn’t risen during the drought,
people suffered real wage loss and related household economic hardships. Decline in household
income in Disadvantaged Communities during this time is largely due to a combination of job
loss, lower hourly wage, and lower annual wages paid to farm workers, as well as working less
days per year. As a consequence of the drought some workers migrated away from the SJV in
pursuit of better working and living conditions. These patterns explain why household income is
falling without a rise of the unemployment rate: there are fewer people looking for work and
those who have jobs work on a reduced basis. Low income households can also be particularly
impacted indirectly through rising food prices during a drought because these households spend
a larger share of their income on food, so a food price surge can significantly impact their
disposable income. Disadvantaged Communities, whose residents include both domestic and
40
US Geological Survey (USGS) Water Data from 2000 to 2010 (see chapter III by Dr. Chih-hao Wang).
117
migrant workers, have long experienced a “financial” drought, and the economic impact from the
current water drought will be added to their financial distress.
Dr. Chih-Hao Wang addressed a key municipal use of water: residential (chapter 3). From 2000
to 2010, the state population in California increased by 10% with the SJV doubling this rate at
20%. Water use dropped by 26% in the same period (-14% in the SJV and -32% in the rest of the
state) due to better irrigation technology and conscientious conservation. However, in face of the
severe drought in the past three years, less water will be available to support municipal water
demand from the increased population. In the SJV, there is so little water this year that some
municipalities are in danger of running out it. Dr. Wang and his team conducted a survey of
urban residents that revealed many physical and social factors affect water consumption.
Physical factors include directions of a house (those facing south consume more water), size of
the house, and number of bathrooms per house. In addition to these physical factors,
neighborhood social patterns also affect water consumption. How much water a given household
uses can correlate with how its neighbors use water after home sizes are controlled, resulting in
similar water consumption patterns in neighborhoods. These findings led to the recommendation
for a large scale survey of residential water use, a valuable tool to produce actionable data that
can inform comprehensive municipal water policy and planning.
Dr. Samendra Sherchan examined how the continued drought introduces health-related problems
due to environmental deterioration (chapter 4). Drought can induce poor air quality and higher
risk of spreading infectious diseases, besides worsening conditions of sanitation and hygiene.
Poorer air quality causes respiratory health problems, increasing incidences of Chronic
Obstructive Pulmonary Disease and asthma. Other drought-related public health impacts include
higher levels of airborne toxins originating from freshwater blooms of cyanobacteria, and
outbreaks of West Nile Virus. These impacts are occurring in a region that has already been
declared an “Environmental Justice” area, with well documented health impacts, by the state Air
Resources Board.
Finally, we need to keep in mind that although the drought has continued for three years, its
worst impact may as yet to come. There is usually a time lag between the occurrence of the
drought (reduced precipitation) and its impact on human life. We are still living on the
“inheritance” of normal precipitation years although this is being quickly depleted. The impact
and effects we are describing in this study are anticipated to deepen and worsen, even if
precipitation levels were to improve soon.
The Future: Water Budgets
Evidence is currently incomplete, but the drought we are facing maybe primarily thought of as a
human and social problem.
There is much discussion on how the previous rules allocating water to growers, cities, and the
environment should be extended going forward. Critics say the governor is only asking urban
areas to reduce consumption while outlining no tangible restriction on agriculture. Supporters
argue that farmers are slated to receive zero Federal project water and only 20% of State Project
water in 2015; far less the than the presumptive 75% supply available to urban water users.
118
Again, critics will argue that agricultural activities use 80% of the state’s developed water
supply, but fail to mention that this excludes environmental water releases and uses. When this is
added back into the equation, agricultural use is closer to 40%. In addition, a seldom mentioned
aspect of water consumption related to population growth is production of meat, dairy products,
and beverages. Only focusing on agricultural production for food, vegetables, and fruits does not
give us a complete review of water consumption. In the end, both urban and agricultural
communities should be recognized for reducing per capita water use and reducing the water footprint (more crop per drop) of food and fiber produced, respectively.
In fact, given the reduction in water availability, it is imperative that the state determine the level
of long-term sustainable water supply availability. This decision will impact all water users, and
the environmental, urban, and agricultural sectors, significantly. The water world going forward
will most likely be one of water budgets for all concerned.
Recommendations
The findings of this study of the San Joaquin Valley lead us to return to all Californians these
recommendations. We need to change our established paradigm when thinking about water and
water use. Based on the findings of this study, we ask that all Californians consider these
recommendations.





Spark deep political discussions about the future availability of water in California and
how it is impacted by the current laws and policies on water. Emphasize four
components:
o Developing water budgets as both a smart growth strategy for population increases
and a sustainable management strategy.
o Creating a broad-based consensus on California’s water future, with the appropriate
leadership. Citizens should understand that competing ideas for water use will
continue to exist and a broad-based consensus with good leadership is an immense
benefit.
o Understanding every single citizen should have and know his or her water budget and
use it appropriately.
o Understanding that groundwater, our largest water storage system and water savings
account, is a finite resource. Continued overuse of groundwater will cause long-term
damage in the form of subsidence. Deeper pumping levels of extraction will become
unaffordable except for the highest income-producing uses or affluent users.
Increase funding in water education and technology at all levels to raise awareness of the
role of water in our society, and inspire the next generation of water leaders.
Avoid single uses of water. Water should be reclaimed and used again and again
wherever possible. The culture of water in our society must be changed to reflect the new
reality of less water for all. Dual plumbing for houses, gray water use, rainwater
harvesting, and water recycling must be adopted by all communities.
Explore non-conventional sources of water, including saline or brackish aquifers and
produced water from oil fields that may be reclaimed for agricultural or other uses.
Recognize the true value of water and price it accordingly.
119
Our water sources, watersheds, are a system. Understanding our systems, their components and
complex needs and how they work, will be imperative in order to come to agreement on how to
manage water properly in the future, especially to establish a comprehensive California water
budget.
120
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2015. Retrieved May 27, 2015 from http://www.dol.gov/whd/regs/statutes/FLCList.htm
Westlands Water District. Retrieved May 28, 2015 from http://wwd.ca.gov/about-westlands
Wichelns, Daniel (2010). Agricultural water pricing: United States. Sustainable management of
water resources in agriculture. The Organisation for Economic Co-operation and
Development. Retrieved June 10, 2015 from
http://www.oecd.org/unitedstates/45016437.pdf
Conclusion and Recommendations
Cart, Julie. (2015, May 2). Central Valley’s growing concern: crops raised with oil field water.
Los Angeles Times. Retrieved May 20, 2015 from
http://www.latimes.com/local/california/la-me-drought-oil-water-20150503story.html#page=1
Diffenbaugh, N. S., Swain, D. L., & Touma, D. (2015). Anthropogenic warming has increased
drought risk in California. Proceedings of the National Academy of Sciences, 112(13),
3931-3936. Retrieved from
http://www.pnas.org/content/112/13/3931.abstract?sid=9cfa7dea-8123-4091-bf8da541772dea30
Fears, D. (2015, February 12). A ‘mega drought’ will grip U.S. in the coming decades, NASA
researchers say. The Washington Post. Retrieved from
http://www.washingtonpost.com/national/health-science/todays-drought-in-the-west-is-
127
nothing-compared-to-what-may-be-coming/2015/02/12/0041646a-b2d9-11e4-854ba38d13486ba1_story.html
Fears, D. (2015, March 2). California’s terrifying climate forecast: It could face droughts nearly
every year. The Washington Post. Retrieved from
http://www.washingtonpost.com/news/energy-environment/wp/2015/03/02/californiasterrifying-forecast-in-the-future-it-could-face-droughts-nearly-every-year/
Hayden, A. (2015, April 10). California’s drought is real, but it’s dusted up a lot of hot air.
Growing Returns. Retrieved from
http://blogs.edf.org/growingreturns/2015/04/10/californias-drought-is-real-but-its-dustedup-a-lot-of-hot-air/
Meeks, A. (2015, March 25). Bill would let $1 billion in drought relief flow in bone-dry
California. CNN. Retrieved from http://www.cnn.com/2015/03/19/us/california-droughtgov-jerry-brown/index.html
Shalby, C. (2015, March 20). Even scarier than California’s shrinking reservoirs is its shrinking
groundwater supply. PBS Newshour: The Rundown. Retrieved from
http://www.pbs.org/newshour/rundown/californias-groundwater-loss-mean-entire-u-s/ 128
Appendix 1 Maps
Appendices compiled by
David Drexler, Digital Initiatives Librarian
The Henry Madden Library
California State University, Fresno
129
California State Water Project (SWP)
i f t
t
Map 1 Water storage and distribution in California
Data from U.S. Geological Survey, retrieved from http://nhd.usgs.gov/,
http://water.usgs.gov/GIS/metadata/usgswrd/XML/pp1766_cvhm_sfr_network.xml, and
http://water.usgs.gov/lookup/getspatial?reservoir, and California Department of Transportation
retrieved from http://earth.dot.ca.gov/
130
Map 2 Depth to groundwater, Spring 2014
Data from California Department of Water Resources Groundwater Information Center,
retrieved from https://gis.water.ca.gov/app/groundwater/, and California Department of
Transportation, retrieved from http://earth.dot.ca.gov/.
131
Map 3 Overview of public water agencies in the
San Joaquin Valley, from the California
Department of Water Resources
Retrieved from
http://www.water.ca.gov/pubs/drainage/2008_bo
undaries_of_public_water_agencies__san_joaqui
n_valley/pwa08_sjv.pdf
Note: This is an oversized file and is properly
viewed by accessing the site above.
132
Online Interactive Maps
Geospatial Information Services, Henry Madden Library. GIS Projects Showcase.
http://libguides.csufresno.edu/content.php?pid=624414&sid=5164578
This collection of demonstration geospatial projects at Fresno State’s Henry Madden
Library includes interactive maps dealing with groundwater depth, recharge, current
reservoir storage, and drought intensity.
New California Water Atlas. http://ca.statewater.org/
This work-in-progress to produce a series of interactive maps that will explain water
issues in California. The first completed map shows water rights by locations, amount,
and purpose.
USGS Center for Integrated Data Analytics. California drought, visualized with open data.
http://cida.usgs.gov/ca_drought/
This interactive map visualizes the effects of the drought over time on reservoir storage
and area.
133
Appendix 2 Bibliography
134
Scholarly studies and policy reports
Aghakouchak, A., Feldman, D., Stewardson, M. J., Saphores, J.-D., Grant, S., & Sanders, B.
(2014). Australia’s drought: lessons for California. Science, 343(6178), 1430–1431.
http://doi.org/10.1126/science.343.6178.1430
A letter describes water reforms that helped mitigate drought impacts in Australia,
including well-developed water markets, modernization of irrigation infrastructure, and
water allotments for environmental purposes.
Alyssa J. Galik. (2015, April 3). Water poverty in California’s rural Disadvantaged
Communities. Pepperdine University, Malibu, CA. Retrieved from
http://digitalcommons.pepperdine.edu/sturesearch/91/
This study used an international measure known as the Water Poverty Index to determine
how water availability in rural Disadvantaged Communities in the San Joaquin Valley
relates to community relations with government and non-profit organizations.
Amos, C. B., Audet, P., Hammond, W. C., Bürgmann, R., Johanson, I. A., & Blewitt, G. (2014).
Uplift and seismicity driven by groundwater depletion in central California. Nature,
509(7501), 483–486. http://doi.org/10.1038/nature13275
Groundwater depletion, which is associated with land subsidence in the Central Valley,
also reduces the weight on the earth’s crust in the area of the depleted aquifer. This study
suggests that depletion of groundwater is associated with an uplift of 1-3 mm per year
around the southern Central Valley, possibly increasing the risk of earthquake.
Association of California Water Agencies. (2005). No time to waste: A blueprint for California
water. Sacramento, CA: Association of California Water Agencies. Retrieved from
http://www.acwa.com/spotlight/no-time-waste
A water policy document produced by public water agencies with a suite of
recommendations for California’s water system.
Balazs, C. L., & Ray, I. (2014). The drinking water disparities framework: On the origins and
persistence of inequities in exposure. American Journal of Public Health, 104(4), 603–
611. http://doi.org/10.2105/AJPH.2013.301664
The authors used data from the San Joaquin Valley to develop the Drinking Water
Disparities Framework, which attempts to model social disparities in exposure to
drinking water contaminants.
California Council on Science and Technology. (2014). Achieving a sustainable California water
future through innovations in science and technology. Sacramento, CA: California
Council on Science and Technology. Retrieved from
http://www.calstate.edu/water/documents/Achieving-Sustainable.pdf
135
This report recommends viewing and managing the California water system as a whole,
and identifies policy recommendations and technology opportunities as well as barriers to
implementation.
California Department of Water Resources. (2013a). 2013 Draft Bay Delta conservation plan.
Sacramento, CA: California Department of Water Resources. Retrieved from
http://baydeltaconservationplan.com/20132014PublicReview/2013PublicReviewDraftBDCP.aspx
Draft version of a comprehensive conservation plan for the Sacramento-San Joaquin
Delta, a critical region for California’s water infrastructure. The plan seeks to balance
two goals: water supply reliability and ecosystem restoration.
California Department of Water Resources. (2013b). Final California water plan update 2013.
Sacramento, CA. Retrieved from http://www.waterplan.water.ca.gov/cwpu2013/final/
Substantial strategic plan produced by the California Department of Water Resources
provides a framework for water resource management and planning along with 300
action recommendations.
Christian-Smith, J., Levy, M., & Gleick, P. (2011). Impacts of the California drought from 2007
to 2009: Surprising outcomes for California’s agriculture, energy, and environment.
Oakland, CA: Pacific Institute. Retrieved from http://pacinst.org/publication/impacts-ofthe-drought-2007-2009/
An assessment of agricultural, economic, and environmental impacts of the 2007-2009
California drought.
Cook, B. I., Ault, T. R., & Smerdon, J. E. (2015). Unprecedented 21st century drought risk in the
American Southwest and Central Plains. Science Advances, 1(1), e1400082.
http://doi.org/10.1126/sciadv.1400082
Several climate models predict conditions in California and the southwest in the late 21st
century will be much drier than anything seen in the historical record or in paleoclimate
reconstructions.
Diffenbaugh, N. S., Swain, D. L., & Touma, D. (2015). Anthropogenic warming has increased
drought risk in California. Proceedings of the National Academy of Sciences, 112(13),
3931–3936. http://doi.org/10.1073/pnas.1422385112
Analysis of historical climate observations from California and computer models both
indicate that anthropogenic global warming is increasing the probability of drought
occurrences in California.
136
Dziegielewski, B., Garbharran, H. P., & Langowski, J. F. (1993). Lessons learned from the
California drought (1987-1992). Fort Belvoir, VA: Institute for Water Resources, U.S.
Army Corps of Engineers. Retrieved from
http://www.iwr.usace.army.mil/Portals/70/docs/iwrreports/93-NDS-5.pdf
Substantial report makes strategic recommendations for water management and policy in
California based on experiences during the 1987-1992 drought.
Famiglietti, J. S., Lo, M., Ho, S. L., Bethune, J., Anderson, K. J., Syed, T. H., … Rodell, M.
(2011). Satellites measure recent rates of groundwater depletion in California’s Central
Valley. Geophysical Research Letters, 38(3). http://doi.org/10.1029/2010GL046442
A study conducted just before the current California drought used satellite data to
estimate groundwater depletion.
Gleick, P. (2015). Impacts of California’s ongoing drought: Hydroelectricity generation (p. 13).
Oakland, CA: Pacific Institute. Retrieved from http://pacinst.org/publication/impacts-ofcalifornias-ongoing-drought-hydroelectricity-generation/
Reduced river flows reduce hydroelectric power generation and increase reliance on
natural gas, leading to higher costs and environmental consequences.
Griffin, D., & Anchukaitis, K. J. (2014). How unusual is the 2012–2014 California drought?
Geophysical Research Letters, 41(24), 2014GL062433.
http://doi.org/10.1002/2014GL062433
The current California drought is the most severe in the last 1200 years. Precipitation
from 2012-2014 has been extremely low but not within the range of natural variability.
Hanak, E., Lund, J., Dinar, A., Gray, B., Howitt, R., Mount, J., … Thompson, B. “Buzz.” (2001).
Managing California’s water: From Conflict to reconciliation. San Francisco, CA:
Public Policy Institute of California. Retrieved from
http://www.ppic.org/main/publication.asp?i=944
This lengthy report provides a brief history of water use in California, a description of
current challenges, and a series of policy recommendations.
Hanak, E., Mount, J., Lund, J., Cayan, D., Davis, F., DeShazo, J. R., … Wilkinson, R. (2015).
California’s water. San Francisco, CA: Public Policy Institute of California. Retrieved
from http://www.ppic.org/main/publication.asp?i=1130
Briefing kit from PPIC discusses policy challenges around water in California, from
climate change to agricultural use.
Herring, S. C., Hoerling, M. P., Peterson, T. C., & Stott, P. A. (2014). Explaining extreme events
of 2013 from a climate perspective. Bulletin of the American Meteorological Society,
95(9), S1–S104. http://doi.org/10.1175/1520-0477-95.9.S1.1
137
A supplement to the Bulletin of the American Meteorological Society with reports from
several groups attempting to assess the role of climate change in extreme weather events.
Three groups looked at the California drought and, though all agree that climate change
has the potential to make droughts more frequent, none find a causal role for climate
change in the current drought.
Howitt, R., Medellin-Azuara, J., Lund, J. R., & MacEwan, D. (2014). Preliminary 2014 drought
economic impact estimates in Central Valley agriculture. Davis, CA: Center for
Watershed Sciences, University of California Davis. Retrieved from
https://watershed.ucdavis.edu/files/biblio/DroughtReport_23July2014_0.pdf
Preliminary release of the UC Davis report on the drought’s economic impact on
agriculture, this version focuses on the Central Valley.
Howitt, R., Medellín-Azuara, J., MacEwan, D., Lund, J., & Sumner, D. (2014). Economic
analysis of the 2014 drought for California agriculture. Davis, CA: Center for Watershed
Sciences, University of California Davis. Retrieved from
http://meteora.ucsd.edu/cap/pdffiles/Howitt2014_Economics_CA_2014drought.pdf
UC Davis report uses a variety of economic models to assess the impact of the drought on
California’s agriculture.
Howitt, R., Medellín-Azuara, J., MacEwan, D., Lund, J., & Sumner, D. (2015, May 31).
Preliminary analysis: 2015 drought economic study. Davis, CA: Center for Watershed
Sciences, University of California, Davis. Retrieved from
https://watershed.ucdavis.edu/library/preliminary-analysis-2015-drought-economicimpact-study
Lo, M.-H., & Famiglietti, J. S. (2013). Irrigation in California’s Central Valley strengthens the
southwestern U.S. water cycle. Geophysical Research Letters, 40(2), 301–306.
http://doi.org/10.1002/grl.50108
Computer simulations suggest that evaporated water from irrigation in the Central Valley
causes increased precipitation in the Colorado River basin resulting in an increase of
around 30% in Colorado River streamflow.
Seaton, P. S., Brodfuehrer, K., & Beaman, M. (2011). Furthering the fight to make clean water a
right in California. Clearinghouse Review: Journal of Poverty Law and Policy, 45, 187–
501. Retrieved from
http://www.crla.org/sites/all/files/content/uploads/Resources/CleanWater_JrnlPvrtLaw_2
011.pdf
Reviews many issues with water quality in rural California and San Joaquin Valley
communities in support of (now enacted) legislation to declare a right to safe drinking
water.
138
Shahbazbegian, M., & Bagheri, A. (2010). Rethinking assessment of drought impacts: a systemic
approach towards sustainability. Sustainability Science, 5(2), 223–236.
http://doi.org/10.1007/s11625-010-0110-4
The authors note that assessments of drought impacts typically focus on direct effects on
agriculture and the economy, and they propose a systemic approach to deal with
secondary social and environmental effects in areas such as migration, education,
conflicts, and ecosystem degradation.
Wang, S.-Y., Hipps, L., Gillies, R. R., & Yoon, J.-H. (2014). Probable causes of the abnormal
ridge accompanying the 2013–2014 California drought: ENSO precursor and
anthropogenic warming footprint. Geophysical Research Letters, 41(9), 2014GL059748.
http://doi.org/10.1002/2014GL059748
Computer models suggest a link between increased greenhouse gases and weather
patterns that led to the 2013-2014 California drought.
Zilberman, D., Dinar, A., MacDougall, N., Khanna, M., Brown, C., & Castillo, F. (2011).
Individual and institutional responses to the drought: the case of California agriculture.
Journal of Contemporary Water Research and Education, 121(1), 17. Retrieved from
http://opensiuc.lib.siu.edu/cgi/viewcontent.cgi?article=1142&context=jcwre
An examination of responses to the 1987-1991 California drought from an economic
perspective shows that agriculture managed with stored water for three years, then turned
to increased groundwater pumping, conservation, and leaving land fallow. The
introduction of water trading was an important institutional change.
Background reading
These books provide background on water issues and history of water use in the western U.S.,
California, and the San Joaquin Valley.
Carle, D. (2009). Introduction to water in California. Berkeley, CA: University of California
Press.
A guide written for general audiences to the state’s water resources and how they’ve been
developed.
Fishman, C. (2011). The big thirst: The secret life and turbulent future of water. New York: Free
Press.
General introduction to many aspects of water from a global perspective, from its
physical properties to industrial and agricultural use to attitudes towards the economics of
water. Fishman is optimistic that water problems are solvable.
Hundley, N. (2001). The great thirst: Californians and water, a history. Berkeley, CA:
University of California Press.
139
Comprehensive history of water in California from before European settlers through the
late 20th century.
Ingram, B. L., & Malamud-Roam, F. (2013). The West without water: What past floods,
droughts, and other climatic clues tell us about tomorrow. Berkeley, CA: University of
California Press.
Examines historical floods and droughts and paleoclimate research to try to define
“normal” climate in California and the western U.S., with implications for future
reliability of water supply.
Lassiter, A. (Ed.). (2015). Sustainable water: Challenges and solutions from California (First
edition). Berkeley, CA: University of California Press.
Collection of writings by experts from many academic disciplines, government, and nonprofits covering many different issues and challenges around creating more resilient
water supplies. Forthcoming July 2015.
Pearce, F. (2006). When the rivers run dry: Water, the defining crisis of the twenty-first century.
Boston, MA: Beacon Press.
A journalist explores water systems in crisis in more than thirty countries.
Reisner, M. (1993). Cadillac desert: The American West and its disappearing. New York:
Penguin Books.
The definitive economic, political, and environmental history of the development of
water resources in the American west.
Smith, W., & Secrest, W. B. (2004). Garden of the sun: A history of the San Joaquin Valley,
1772-1939 (2nd ed). Fresno, CA: Linden Publishing Co.
The most thorough history available of the San Joaquin Valley, first published in 1939
and updated in 2004. Begins with Native Americans in the area and includes the growth
of agriculture in the valley.
News articles and sources
Selected articles
Newspaper, magazine, and blog articles that offer in-depth coverage of the drought or document
specific drought impacts.
Famiglietti, J. (2015, March 13). California has about one year of water stored. Will you ration
now? Los Angeles Times. Los Angeles, CA. Retrieved from
http://www.latimes.com/opinion/op-ed/la-oe-famiglietti-drought-california-20150313story.html
140
Op-ed by UC Irvine professor calls for water rationing, speeding timetables in the
Sustainable Groundwater Management Act, and developing long-term water management
strategies.
Madrigal, A. C. (2014, February 24). American Aqueduct: The Great California Water Saga. The
Atlantic. Retrieved from http://www.theatlantic.com/features/archive/2014/02/americanaqueduct-the-great-california-water-saga/284009/
Long article about the Bay Delta Conservation Plan with lots of background on
California water history and issues.
Marcum, D. (2015). Scenes from California’s Dust Bowl. Los Angeles Times. Los Angeles, CA.
Retrieved from http://www.latimes.com/local/great-reads/la-me-c1-drought-timeline20141210-html-htmlstory.html
Pulitzer Prize winning series of articles on the effects of drought in the Central Valley.
Mark Grossi. (2015, April 29). Drought is making San Joaquin Valley’s bad air worse, report
says. Fresno Bee. Fresno, CA. Retrieved from
http://www.fresnobee.com/news/local/news-columns-blogs/earthlog/article20925525.html
The American Lung Association’s “State of the Air” report indicates that PM 2.5
pollution has gotten worse with the drought.
Medina, J. (2014, October 2). With Dry Taps and Toilets, California Drought Turns Desperate.
New York Times. New York. Retrieved from
http://www.nytimes.com/2014/10/03/us/california-drought-tulare-county.html
New York Times description of impacts of wells drying up in East Porterville.
Nidever, S. (2015, January 30). Almonds: Good or bad? Hanford Sentinel. Hanford, CA.
Retrieved from http://hanfordsentinel.com/news/local/almonds-good-orbad/article_fbf8c37a-4ae5-526a-ab7d-597140ef8155.html
Series of articles examining the public relations issues with water required for almonds.
Nijhuis, M. (2014, September 18). Amid drought, new California law will limit groundwater
pumping for first time. National Geographic News. Retrieved from
http://news.nationalgeographic.com/news/2014/09/140917-california-groundwater-lawdrought-central-valley-environment-science
Brief account of issues surrounding the Sustainable Groundwater Management Act.
Parker, D., & Kearns, F. California’s water paradox: Why enough will never be enough.
Retrieved from https://theconversation.com/californias-water-paradox-why-enough-willnever-be-enough-40889
141
University of California authors suggest that increased water supply will always lead to
increased demand, meaning there will never be “enough” water.
Ritchel, Matt. (2015, June 5) California farmers dig deeper for water, sipping their neighbors dry
- NYTimes.com. New York Times. New York. Retrieved from
http://www.nytimes.com/2015/06/07/business/energy-environment/california-farmersdig-deeper-for-water-sipping-their-neighbors-dry.html?smprod=nytcoreiphone&smid=nytcore-iphone-share&_r=0
Discussion of the “well drilling boom” in California as more and more wells dry up and
new ones have to be drilled or old ones have to be drilled deeper. Includes analysis of
subsidence in Central Valley as aquifer is depleted.
Schwartz, N. D. (2015, May 6). Water pricing in two thirsty cities: In one, guzzlers pay more,
and use less - NYTimes.com. New York Times. New York. Retrieved from
http://www.nytimes.com/2015/05/07/business/energy-environment/water-pricing-in-twothirsty-cities.html?_r=0
Discussion of tiered rates for municipal water that compares use in Fresno, CA with
Santa Fe, NM.
Sommer, L. (2015, June 1). Car washes and pools: Winners and losers of California’s drought.
Retrieved from http://ww2.kqed.org/science/2015/06/01/car-washes-and-pools-winnersand-losers-of-californias-drought/
Anecdotes documenting how municipal water customers are reacting to new statewide
water use restrictions.
Xia, R. (2015, May 15). Drought cuts power production of California dams. Los Angeles Times.
Los Angeles, CA. Retrieved from http://www.latimes.com/local/california/la-medrought-hydro-20150517-story.html
Low water levels and streamflow mean reduced generation of hydroelectric power.
News sources
A selection of newspaper portals and news aggregators where current coverage of water and
drought issues can be found.
Association of California Water Agencies. Water News. Retrieved from
http://www.acwa.com/mediazone/water_news
Regular updates on statewide water issues from the water agency perspective.
California Institute for Water Resources. Confluence. Retrieved from
http://ucanr.edu/blogs/confluence/
142
Blog published by the California Institute for Water Resources gathers water- and
drought-related posts from many sources.
Fresno Bee. Water & Drought news. Retrieved from
http://www.fresnobee.com/news/state/california/water-and-drought/
Drought coverage from the Fresno Bee, including wire service stories.
Los Angeles Times. California Drought. Retrieved from http://www.latimes.com/local/drought/
Portal gathering Los Angeles Times coverage of the California drought. Much of the
content is focused on the Los Angeles area, but occasional articles cover the Central
Valley and many issues covered are of statewide interest.
New York Times. The Parched West. Retrieved from
http://www.nytimes.com/interactive/2015/04/05/us/DroughtSeriesBox.html
Articles in “ The Parched West” series explore the impact of the drought that has hit
states from the Pacific Coast to the Great Plains, with a majority on the drought, its
history, and its impacts in California.
Pacific Institute. Pacific Institute Media Center. Retrieved from http://pacinst.org/media-center/
Includes press releases from and media appearances by the Pacific Institute along with
new updates that collect articles from many sources about water issues.
Sacramento Bee. Water & Drought news. Retrieved from
http://www.sacbee.com/news/state/california/water-and-drought/
Drought coverage from the Sacramento Bee.
San Francisco Chronicle. California Drought - SFGate. Retrieved from
http://www.sfgate.com/drought/
Collected coverage of California drought from the San Francisco Chronicle.
UC Davis Center for Watershed Sciences. California Water Blog. Retrieved from
http://californiawaterblog.com/
A blog on water policy issues written by researchers and students from the UC Davis
Center for Watershed Sciences in collaboration with “experts from other universities,
research institutes, government agencies and NGOs.”
Valley Public Radio. Drought. Retrieved from http://kvpr.org/term/drought
Stories on the “trending topic” of drought from Valley Public Radio.
143
Water Education Foundation. Aquafornia. Retrieved from
http://www.watereducation.org/aquafornia
The Water Education Foundation’s blog aggregates news reports on California water
issues.
Media and artwork related to drought and its impacts
Black, M. Matt Black Photography. Retrieved from http://www.mattblack.com
Central Valley photographer explores impacts of drought in several projects. “The Dry
Land” depicts agriculture during the drought, and “The Dispossesion” deals with poverty
resulting from recession and drought.
Corcoran, T. Western Water Luv. Retrieved from
https://www.youtube.com/channel/UCE63IFloqt2kd3Kb-DB07CA
YouTube channel of a Los Angeles man who takes video when he encounters water
being wasted, sometimes using the hashtag #droughtshaming.
Dawson, R. Robert Dawson Photography. Retrieved from
http://www.robertdawson.com/portfolio.html?folio=Projects
Photographer with a number of water-themed projects, including “Water in the West”
and the “Great Central Valley Project.”
Little, J. Jennifer Little Photography. Retrieved from http://www.jenniferlittle.net/
Photographer and faculty member at University of the Pacific in Stockton does waterrelated art photography, including projects “Conduits” and “Owens Lake and the Los
Angeles Aqueduct.”
Osequera, J. C. (2014). The fight for water: A farm worker struggle. Retrieved from
http://www.thefightforwaterfilm.com
Documentary showing effects on the agricultural community of water restrictions during
the 2009 drought. See a review at http://hanfordsentinel.com/ontap/documentary-shedslight-on-drought/article_114aef9c-dd2d-11e3-a7dc-001a4bcf887a.html
Valley Public Radio. Voices of the Drought. Retrieved from http://kvpr.org/programs/voicesdrought
This series of programs by Valley Public Radio covers drought impacts in California’s
Central Valley and invites public participation through the use of the hashtag
#droughtvoices on Instagram, Twitter, and Facebook. A tumblr page at
http://voicesofthedrought.tumblr.com/ highlights some of these contributions along with
Valley Public radio stories.
144
Appendix 3 Stakeholder organizations
145
Association of California Water Agencies.
The Association of California Water Agencies (ACWA) is a coalition of 430 public water
agencies working to promote water management with good quality, low cost, and
environmental balance.
910 K Street, Suite 100
Sacramento, CA 95814
tel. (916) 441-4545
fax (916) 325-4849
http://www.acwa.com/
ACWA and the Department of Water Resources have partnered on the Save Our Water
program, which includes a tool for finding local water agencies.
http://saveourwater.com/find-your-water-agency/
California Department of Water Resources.
The DWR is the state agency responsible for managing and protecting California’s water.
P.O. Box 942836
Sacramento, CA 94236
Public Affairs Office tel. (916) 653-6192
fax (916) 653-4684
http://www.water.ca.gov/
California Farm Water Coalition.
CFCW is a non-profit educational organization representing the interests of agricultural
water users.
6133 Freeport Boulevard, 2nd Floor
Sacramento, CA 95822
tel. 916-391-5030
http://farmwater.org/
California Governor’s Office of Emergency Services (CalOES).
CalOES has prepared a brochure with information on assistance for those affected by the
drought, including assistance with food, utilities, health care, and employment; grants and
loans for drinking water emergencies and home repairs; and programs for farmers,
ranchers, and small businesses.
http://ca.gov/drought/pdf/Drought-Assistance-Brochure-2015.pdf
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California State University. Water Resources and Policy Initiatives.
The California State University’s Water Resources and Policy Initiatives (WRPI)
coordinates system-wide efforts to create effective water managers.
Boykin Witherspoon III
Executive Director
5500 University Parkway
San Bernardino, CA 92407
tel. (909) 537-7681
fax (909) 537-7682
http://www.calstate.edu/water/
California State University, Fresno.
Fresno State is at the heart of the most important agricultural region in the nation, and is
committed to positively addressing water and agricultural issues. Water research related
resources at Fresno State are listed at http://www.fresnostate.edu/water-research and
includes the following resources:
California Water Institute, an academic center of excellence for research, education, and
policy analysis of issues involving water resources.
6014 N. Cedar Ave, M/S OF 18
Fresno, CA 93710
tel. (559) 278-8650
fax (559) 278-8655
http://www.californiawater.org/cwi/index1.htm
The Center for Irrigation Technology, a leading independent testing laboratory and
applied research facility for the irrigation industry.
5370 N. Chestnut Avenue M/S OF 18
Fresno, CA 93740
tel. (559) 278-2066
fax (559) 278-4496
http://www.fresnostate.edu/jcast/cit/
The Faculty Water Cohort, which has as its mission to engage the campus and
community in discussions and activities to build awareness and develop understanding of
water issues and challenges.
http://www.fresnostate.edu/academics/water-cohort/
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The International Center for Water Technology, established to provide education and
research to assist in developing and adopting innovative solutions and technologies that
improve water use efficiency.
California State University, Fresno
5370 N. Chestnut Avenue, M/S OF 18
Fresno, CA 93740-8021
tel. (559) 278-2066
fax (559) 278-6033
http://www.icwt.net/
The Water, Energy, and Technology (WET) Center, which supports innovators and
entities working towards building sustainable technologies in the water, energy, and
agricultural sectors.
2911 E. Barstow Avenue, M/S OF 144
Fresno, CA 93710
tel. (559) 278-4540
fax (559) 278-8401
http://wetcenter.org/
California Urban Water Conservation Council.
CUWCC is a partnership between urban water agencies, non-profit groups, private
organizations, and government that seeks to promote best practices in urban water
conservation.
716 10th Street, Suite 200
Sacramento, CA 95814
tel. (916) 552-5885
fax (916) 552-5877
http://www.cuwcc.org/
Great Valley Center.
A nonprofit that seeks to support economic, social, and environmental well-being in
California's Central Valley.
1120 13th Street, Suite C
Modesto, CA 95354
tel. (209) 522-5103
http://www.greatvalley.org/
The Nature Conservancy California Program.
The worldwide conservation organization has several programs in California related to
sustainable management of fresh water, described here:
http://www.conserveca.org/our-stories/water/term/summary
201 Mission Street, 4th Floor
San Francisco, CA 94105-1832
tel. (415) 777-0487
fax (415) 777-0244
http://www.conserveca.org/
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Pacific Institute: Water Program.
The Pacific Institute is a non-profit organization which “works to create a healthier planet
and sustainable communities.” Their water program engages with many issues around
water efficiency, access, and environmental protection.
654 13th St.
Preservation Park
Oakland, CA 94612
(510) 251-1600
http://pacinst.org/about-us/programs/water-program/
PPIC Water Policy Center.
The Public Policy Institute of California (PPIC) is a nonprofit, nonpartisan organization.
The PPIC Water Policy Center produces publications focused on reliable water supplies,
healthy ecosystems, and preparing for droughts and floods.
500 Washington Street, Suite 600
San Francisco, CA 94111
tel. (415) 291-4400
fax (415) 291-4401
http://www.ppic.org/water/
Revive the San Joaquin.
Non-profit organization which has as its mission “To promote a collective stewardship
that sustains the economic, environmental, and recreational benefits of a healthy San
Joaquin River, including adequate flows, habitat, and native fisheries. ”
5132 N. Palm, PMB 121
Fresno, CA 93704
tel. (559) 226-0733
fax (559) 228-0547
http://www.revivethesanjoaquin.org/
Self-Help Enterprises
Community development organization that seeks “to build and sustain healthy homes and
communities.” They have many programs dealing with affordable housing along with
programs aimed at access to water, including drought response efforts described here:
http://www.selfhelpenterprises.org/programs/community-development/drought-response/
P.O. Box 6520
Visalia, CA 93290
tel. (559) 651-1000
fax (559) 651-3634
http://www.selfhelpenterprises.org/
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Water Education Foundation.
A non-partisan, nonprofit organization dedicated to improving public understanding of
water resources and water resource issues.
1401 21st Street, Suite 200
Sacramento, CA 95811
tel. (916) 444-6240
fax (916) 448-7699
http://www.watereducation.org/foundation
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Appendix 4 Data sources
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California Department of Finance. Research. http://www.dof.ca.gov/research/
Demographic, Economic, and Financial research units provide data on topics such as
population, births, migration, housing, public school enrollment, income, and state
revenues.
California Department of Public Health. Data & Statistics.
http://www.cdph.ca.gov/DATA/Pages/default.aspx
Gateway to California public health data in many forms, including downloadable files,
online queries, and spatial data and maps.
California Department of Water Resources. California Data Exchange Center.
http://cdec.water.ca.gov/index.html
Hydrologic data from the California Department of Water Resources, including
precipitation, snowpack, streamflow, and reservoir storage.
California Department of Water Resources. Groundwater Information Center.
www.water.ca.gov/groundwater/gwinfo/
Data collected from 35,000 wells and from partner organizations provides information on
groundwater levels and quality and land subsidence.
National Climatic Data Center (NCDC). Data Access. https://www.ncdc.noaa.gov/data-access
Climate data including observations from land-based stations, marine stations, satellites,
radar, and weather balloons, along with climate models and paleoclimate data.
National Oceanic and Atmospheric Administration. U.S. Drought Portal - National Integrated
Drought Information System. http://www.drought.gov/drought/
NOAA-led program involving drought information from many federal agencies,
universities, and private organizations.
State of California Employment Development Department. Labor Market Information.
http://www.labormarketinfo.edd.ca.gov/
California labor market indicators such as the unemployment rate and labor force size,
with detail by industry, occupation, counties, and metropolitan areas.
State Water Resources Control Board. Sources of Groundwater Information.
http://www.waterboards.ca.gov/water_issues/programs/gama/grid.shtml
State Water Resources Control Board’s compilation of their data related to groundwater
along with pointers to groundwater data from many other sources.
152
U.S. Census Bureau. American FactFinder.
http://factfinder.census.gov/faces/nav/jsf/pages/index.xhtml
Portal to finding and downloading data from the U.S. Census and the American
Community Survey.
USDA National Agricultural Statistics Service. Data and Statistics.
http://www.nass.usda.gov/Data_and_Statistics/index.asp
Agricultural commodity data aggregated nationally from county-level reports.
U.S. Department of Labor Bureau of Labor Statistics. Consumer Price Index (CPI).
http://www.bls.gov/cpi/
Data on changes to prices of consumer goods as a measure of economic inflation.
U.S. Geological Survey. National Hydrography Dataset. http://nhd.usgs.gov/
Geographic information systems datasets representing surface water features and
watershed boundaries for the U.S.
U.S. Geological Survey. USGS Water Data for the Nation. http://waterdata.usgs.gov/nwis
Water resources data on surface water, ground water, water quality, and water use
gathered at around 1.5 million locations across the United States and its territories.
USGS California Water Science Center. California Drought Information.
http://ca.water.usgs.gov/data/drought/index.html
Portal for drought information includes description of drought impacts from a hydrologic
point of view and data on streamflow, groundwater, surface water, and water quality.
County crop reports
The California Food and Agriculture Code requires county agriculture commissioners to compile
annual crop and livestock reports on the amount and value of the county’s commodities.
References to historical reports are provided for each of the eight counties in the study area.
County of Fresno - Agricultural Commissioner. Crop Report History.
http://www.co.fresno.ca.us/DepartmentPage.aspx?id=54231
County of Madera Department of Agriculture. Crop Reports. http://www.maderacounty.com/index.php/publications/crop-reports
Kern County Department of Agriculture and Measurement Standards. Annual Crop Reports.
http://www.kernag.com/caap/crop-reports/crop-reports.asp
153
Kings County Agriculture Department. Crop Reports 1941-2013.
http://www.countyofkings.com/departments/agricultural-commissioner/crop-reports1941-2011
Merced County Department of Agriculture. Ag Commissioner - Annual Reports.
http://www.co.merced.ca.us/Archive.aspx?AMID=36
San Joaquin County - Office of the Agricultural Commissioner. Annual Crop Reports.
http://www.sjgov.org/agcomm/annualrpts.aspx
Stanislaus County Agricultural Commissioner. Crop Reports. http://www.stanag.org/cropreports.shtm
Tulare County Agricultural Commissioner/Sealer. Crop Reports.
http://agcomm.co.tulare.ca.us/default/index.cfm/standards-and-quarantine/crop-reports1/
154