Santa Barbara Coastal Long Term Ecological Research (LTER): Nutrient
Concentrations in Coastal Streams and Variations with Land Use in the
Carpinteria Valley, California
T. H. Robinson1, A. Leydecker2, J. M. Melack3, A. A. Keller4
Abstract
Along the southern California coast, near Santa Barbara, we are (1) measuring
nutrient loading to the nearshore environment from representative watersheds, and (2)
developing a model to predict export from changes in land use. The area is
characterized by a Mediterranean climate and short steep catchments producing
flashy runoff; a majority of the annual nutrient export occurs within a few days each
year. Six land use classes within the drainages of the Carpinteria Valley are being
sampled to develop a nutrient export coefficient model within the context of a
geographic information system (natural/undisturbed chaparral vegetation, avocado
orchards, greenhouse agriculture, open-field nursery agriculture, residential
development, and commercial and light industrial development). The sites chosen
represent relatively homogeneous areas for each of the land use classes and are large
enough to have defined drainages.
Stream water samples were collected either manually, just below the water surface in
the thalweg, or by auto-samplers. Water samples were taken every two weeks during
the dry season, approximately May through October, once a week during the rainy
season, and every one to four hours during storms. At most sites, stage was measured
with pressure transducers at 5-minute intervals, and staff gauges have been installed
to visually observe stage during sampling.
Nitrate concentrations during baseflow varied over three orders of magnitude, from a
few micromoles per liter (µmol/L) in undeveloped catchments, to hundreds of
µmol/L in agricultural and urban watersheds, to thousands of µmol/L where intensive
1
Doctoral Student, Donald Bren School of Environmental Science and Management, University of
California, Santa Barbara, Ca. 93106-5131; Phone: (805) 893-8356; Fax: (805) 893-7612; E-mail:
trobinson@bren.ucsb.edu
2
Researcher, Marine Science Institute, U.C. Santa Barbara; Phone: (805) 569-1748; Fax: (805) 8937612; E-mail: al.leydecker@cox.net
3
Professor, Donald Bren School of Environmental Science and Management, U.C. Santa Barbara;
Phone: (805) 893-3879; Fax: (805) 893-7612; E-mail: melack@lifesci.ucsb.edu
4
Associate Professor, Donald Bren School of Environmental Science and Management. U.C. Santa
Barbara; Phone: (805) 340-0360; Fax: (805) 456-3807; E-mail: keller@bren.ucsb.edu
1
greenhouse agriculture dominates. Nitrate loading ranged from a few moles per
hectare per storm at undeveloped and residential sites to hundreds of moles per
hectare per storm at the greenhouse site. Phosphate concentrations had a similar, but
smaller, variation from 1 to 100 µmol/L. Stormflow concentrations fluctuated with
the storm hydrograph: phosphate increased with flow, while nitrate typically
decreased due to dilution from impervious surface runoff. Future research will entail
implementing nutrient export coefficient modeling techniques to enable a regional
analysis of nutrient loading to the ocean .
Literature citation:
Robinson, Timothy H., Al Leydecker, John M. Melack and Arturo A. Keller. 2003. Santa Barbara Coastal Long Term
Ecological Research (LTER): Nutrient concentrations in coastal streams and variations with land use in the Carpinteria Valley,
California. California and the World Oceans ’02 Conference. American Society of Civil Engineers. Santa Barbara, California.
October.
Introduction
Nutrient loading to the near-shore oceanic environment and coastal estuaries can be a
significant source of pollution, causing excessive algal growth, depletion of dissolved
oxygen and degradation of aquatic ecosystems (Howarth et al., 2000). Agricultural
and urban development often result in elevated concentrations of nitrogen (N) and
phosphorus (P) in adjacent streams, lakes and estuaries (Frink, 1991; Johnes, 1996;
Pionke et al., 1996).
Eutrophication, a natural process, is accelerated by
anthropogenic inputs particularly from urban and agricultural development (Rast et
al., 1983; Carpenter et al., 1998; Correll, 1998).
As southern California coastal watersheds undergo increased conversion to urban and
agricultural land uses, nutrient loading can be expected to increase. In the Santa
Barbara area, short stream lengths, a growing urban population and a Mediterranean
climate are likely to magnify the impacts of nutrient pollution. These characteristics
can reduce in-stream uptake, limit dilution of concentrated wastewaters and enhance
wet-season flushing. Our objectives, as part of the Santa Barbara Coastal Long Term
Ecological Research project (SBC-LTER), are to measure and model nutrient export
as a function of discharge and land use, and estimate the increased nutrient loading
caused by possible changes in land use (Worrall et al., 1999). Here we describe
studies in three watersheds in the Carpinteria Valley of southern California, a subset
of catchments within the SBC-LTER.
Determining nutrient loading requires a sampling strategy that captures the
hydrologic and chemical variance over time. The difficulty and cost of data
acquisition prompted the development of nutrient export coefficient modeling
techniques. Export coefficients represent the mass of nutrient exported per unit land
area per time, for example, kg NO3-N ha-1 yr-1. Estimates of nutrient loading are
based on the assumption that for a given climate, specific land uses (e.g., agriculture
or residential) will yield characteristic and replicable quantities of nitrogen and
phosphorus to a stream or a receiving waterbody over time.
To reduce
biogeochemical complexities and temporal variability, an annual time-step has
2
traditionally been used . From the spatial extent of each land use class in a watershed
and the nutrient export per unit area per time of each class, the total annual loading of
nitrogen and phosphorus to the drainage from nonpoint sources, natural and
anthropogenic, can be estimated (Winter et al., 2000).
Study Area
The three main drainages in the Carpinteria Valley (located approximately 160
kilometers northwest of Los Angeles, California), Carpinteria, Franklin and Santa
Monica creeks, have headwaters in steep mountainous terrain within the Los Padres
National Forest (Figure 1 and Table 1). Upon leaving National Forest lands and
entering the coastal plain, the creeks flow through multiple-use agricultural lands and,
within one or two kilometers of the coast, residential and commercial areas.
Carpinteria Creek has the least developed drainage, flowing through a natural channel
with an almost continuous riparian corridor. Franklin Creek is a shorter, lowerelevation watershed with little undeveloped land. Its drainage area is dominated by
intensive multi-use agriculture and an abrupt transition to residential and light
commercial development prior to discharging into the Carpinteria Salt Marsh, one of
the largest estuarine systems in the region. Three-quarters of the stream is
channelized and concrete lined. Santa Monica Creek has characteristics between
Franklin and Carpinteria creeks, a relatively large undisturbed upper watershed with a
narrow lower catchment channelized through the urban area and some intensive
agriculture. It also discharges into the salt marsh.
Figure 1: Map of watersheds and sampling sites.
3
Table 1 presents characteristics of the catchments. Physical data were generated from
a 30-m digital elevation model (DEM). The major land use categories were derived
by interpretation of high-resolution aerial photographs (1:42,000 with a resolution of
1.8 meter) using an Anderson Level III land use classification (Anderson et al.,
1976). Land uses were grouped into broad categories and percentages calculated for
the entire basin area.
Table 1. Basin characteristics and the extent of urban, agriculture and forested lands
in Carpinteria Valley creeks. Missing percentages are from water and riparian areas.
Watersheds
Drainage Area Max-Elevation
2
(km )
(m)
Carpinteria
39.2
1424
Franklin
11.6
533
Santa Monica
9.8
1192
Average Slope
Urban
(%)
38
20
45
(%)
2
29
3
Agriculture Chaparral/Forest
(%)
11
30
3
(%)
85
40
93
Methodology
We conducted intensive stream water-sampling using manual (grab) samples and
auto-samplers to measure nutrient concentrations and calculate nutrient loading to the
near-shore coastal environment. We measured nitrogen (dissolved organic, nitrate
and ammonium) and phosphorus (soluble reactive phosphate (SRP)) concentrations
in runoff. Samples were assayed for nitrate (NO3), ammonium (NH4) and phosphate
(SRP) concentrations by colorimetric determination using standard methods on a
Lachat-Zellweiger auto-analyzer (Keeney et al., 1982). Total dissolved nitrogen
(TDN) was determined as nitrate after persulfate digestion (Valderrama, 1981) and
dissolved organic nitrogen (DON) was computed as the difference between TDN and
dissolved inorganic nitrogen (DIN: nitrate and ammonium). Stream stage was
measured with a pressure transducer and converted to discharge using rating curves
or mathematical relationships based on channel cross-sections, slope and roughness.
Staff gauges have been installed at each sampling point to visually observe stage
during water sampling. Nutrient loading was calculated by multiplying nutrient
concentrations by stream discharge.
Intensive stream sampling began in water-year 2001 (October 2000 through
September 2001, written as WY2001) at basin outlets and for specific land uses in
WY2002. Manual samples of creek or storm drain water were collected below the
surface in the thalweg. At difficult to access sampling sites, auto-samplers collected
samples through a suction hose fastened to the bottom of the channel. Water samples
were taken every two weeks during the dry season, approximately May through
October, once a week during the rainy season, and every one to four hours during
storms. The frequency of sampling during a storm was hourly throughout the rising
limb of the hydrograph to capture the flashy nature of these streams and then
extended to a frequency of several hours as flow subsided to pre-storm levels.
Fifteen sites have been instrumented to measure stream discharge and determine
nutrient fluxes from six principal land use classes identified for the study: (1) natural
or undisturbed chaparral/forest vegetation, (2) avocado orchards, (3) greenhouse
4
agriculture, (4) open-field nursery agriculture, (5) residential development, and (6)
commercial and light industrial development. Sampling and stream gauging
locations were sited in relatively homogeneous areas for each of the classes and in
areas large enough to have a defined drainage.
Table 2: Land use distribution in sampled sub-catchments (percentages based on an
Anderson Level III land use classification). 1998 aerial photographs were used for
the land use classification.
LU
Area
% Area of Land Use by sub-catchment (LU-Code)*:
Percent
Code
(hectares)
1
2
3
4
5
6
20
60
Impervious**
1
1873
100
0
0
0
0
0
0
0
0
1
1210
100
0
0
0
0
0
0
0
0
1
902
100
0
0
0
0
0
0
0
0
2
747
42
36
1
2
0
4
12
2
7
3
17
3
0
97
0
0
0
0
0
68
4
80
12
21
4
47
0
2
15
0
11
5
6
0
0
0
0
100
0
0
0
30
6
32
9
0
0
0
0
91
0
0
77
* Land use by sub-catchment and their associated percentage of impervious surfaces.
LU-Code
% Imp
Sub-catchment class:
1
0
Chaparral/Forest (undeveloped)
** References for calculating the percentage of
2
5
Avocados
impervious area by land use class:
3
70
Greenhouse
1. Soil Conservation Service, Urban
4
10
Nursery
Small Watersheds, Technical Release 55,
5
30
Residential
Washington, DC, 1986
6
85
Commercial
2. US Army Corps of Engineers. 2000. HEC-HMS
20
10
Other agriculture
Technical Manual Hydrologic Engineering
60
0
Forested Riparian
Center, Davis, Ca, pp. 123
3. Interpretation by T.H. Robinson and R.E. Beighley
The percentage of each land use within sampled sub-catchments is shown in Table 2.
Two additional broad land use classes (20 and 60) were identified to provide 100 %
coverage. The table includes an estimate of the amount of impervious surface in each
sub-catchment. The larger the percentage of a specific land use within a subcatchment, the greater the homogeneity of that land use class and the possibility of
identifying a specific nutrient export signal.
Stage data was compiled from pressure transducers and observations. Stagedischarge relationships are developed for each site in HEC-RAS (USACE, 2002)
using channel surveys centered around the sampling points. Discharge was
determined at a 5-minute time step. When stage data were unavailable, hydrologic
data from other areas in close proximity were used. Chemical data were adjusted to
the nearest hour and merged with the discharge data. Data for unsampled storms and
baseflow intervals were modeled using concentrations from similar events and flow
regimes during the same year. Hourly stream concentrations were derived by linear
interpolation between analyzed samples and multiplied by discharge to calculate
hourly flux.
Results and Discussion
The three streams in the study have a wide range of nutrient concentrations (Figure
2). Baseflow nitrate concentrations in Franklin Creek were over four times greater
5
than in Carpinteria Creek, which was significantly higher than Santa Monica Creek.
This pattern matches the percentage of urban and intensive agricultural development
in the three basins. In all the streams there was a decrease in nitrate concentrations
(see below) as discharge increased due to low nitrate runoff from impervious
surfaces. The contrast between Franklin and the other two creeks is due to far higher
baseflow concentrations and greater proportional impervious surface extent, which
results in significant dilution. Additionally, Carpinteria and Santa Monica creeks,
with larger and higher elevation catchment areas, produce greater amounts of low
nitrate upper catchment runoff .
2500
50
baseflow
baseflow
stormflow
phosphate (SRP, µM)
nitrate (µM)
2000
1500
1000
500
0
40
stormflow
30
20
10
0
Franklin
Carpinteria
Santa Monica
Franklin
Carpinteria
Santa Monica
Figure 2: Nitrate and phosphate (SRP) baseflow and discharge-weighted stormflow
mean concentrations for Franklin, Carpinteria and Santa Monica creeks (WY2001).
Error bars show the standard error of the mean (Endlich et al., 1988).
Typically, phosphate concentrations are positively correlated with stormflow
(McFarland et al., 2001). However, we found either no significant difference
between baseflow and stormflow concentrations (Carpinteria Creek), or significantly
lower stormflow values (Franklin and Santa Monica creeks).
During the largest storm in WY2001, nitrate concentrations in Franklin Creek were
four times higher than in Carpinteria Creek, while phosphate was higher by a factor
of 2 (Figure 3). The similarity of the temporal variation in phosphate concentrations
with the hydrograph in both streams indicates that phosphate is probably being
exported from the entire catchment and not from any particular land use. In contrast,
the decrease in nitrate concentrations with increased stormflow in Franklin Creek
indicates dilution, probably from impervious area runoff, as the primary mechanism
reducing concentrations. Avocado orchards may be responsible for increased nitrate
in Carpinteria Creek during the storm. Ammonium concentrations in Carpinteria
Creek remained low throughout the storm and peaked at 0.6 µM with the crest of the
hydrograph. In Franklin Creek, ammonium rose rapidly at the initiation of the rising
limb of the hydrograph only to decrease quickly and stay at relatively low
concentrations until a day after the storm, when it began to rise back to base flow
levels.
6
60
8
+
nitrate
4
phosphate
3+
ammonium
20
2
5-Mar
6-Mar
7-Mar
1000
24
phosphate
21
stage
18
ammonium
15
600
12
400
9
6
200
+
800
and NH4 (µM)
nitrate
Franklin Creek
Nitrate (µM)
0
8-Mar
3+
0
4-Mar
PO4
stage
PO4
Nitrate (µM)
6
40
and NH4 (µM)
Carpinteria Creek
3
0
4-Mar
5-Mar
6-Mar
7-Mar
0
8-Mar
Figure 3. Nutrient concentrations at Carpinteria and Franklin creeks during the largest
storm of the winter of WY2001. Stage is included as an indication of variations in
stormflow (no scale). The EPA safe drinking water standard is 714 µM NO3- (10 mg/l
NO3-N).
Figure 4 illustrates examples of the variation in stormflow nutrient concentrations
from several land use classes. The storm of October 30-31, 2001, the first rain after
six months, deposited approximately 12.7 mm of rain in the Carpinteria Valley.
There was almost no storm runoff from the undeveloped upper catchments, and
nutrient concentrations in streamflow from these areas remained low. Nitrate
concentrations from the residential area also remained relatively low throughout the
storm (maximum value of 81 µM). High pre-storm nitrate concentrations from the
commercial area were diluted by runoff from imperious urban surfaces. Thus, high
concentrations at the creek outlet indicate that other land uses must be major
contributors of nitrate on the coastal plain. That the highest nitrate concentrations
occur on the receding limb of the hydrograph may indicate principal contributions
from soil and ground waters, as well as nutrient build up in near-stream vegetative
areas during the preceding dry period. Others have observed the same phenomenon
(Wong et al., 1997). Phosphate concentrations from all urban sources increased
during the storm. The highest concentrations occurred on the second, lower,
7
hydrograph peak or during receding flow, indicating that flashier, surface runoff is
relatively low in phosphate and that soilwater drainage was likely a major
contributor.
1200
0.40
outlet
residential
0.30
300
0.25
0.20
11/1
10/31
50
0.40
45
outlet
40
commercial
35
residential
30
chaparral/forest
25
stage-recorded
0.35
0.30
20
15
0.25
Stage at outlet (m)
Nitrate (µM)
stage-recorded
600
0
10/30
Phosphate (µM)
0.35
chaparral/forest
Stage at outlet (m)
commercial
900
10
5
0
10/30
0.20
11/1
10/31
Figure 4. Nitrate and phosphate concentrations in Carpinteria Creek during the first
storm of WY2002.
Our sampling has gaps and uncertainties requiring assumptions and extrapolations to
calculate nutrient fluxes per hour. We assumed that a grab sample is representative
of concentrations throughout the entire cross-section, i.e., that channel water is well
mixed. This has not always been found to be the case with phosphate and particulate
concentrations, although the assumption appears reasonable for nitrate (Hem, 1992;
Milligan et al., 2001).
The integration of field data to calculate and model stream nutrient flux is essential to
our understanding of stream nutrient export. Figure 5 shows cumulative nutrient
export for the outlet of Franklin Creek for the winter months of WY2001. All
dissolved nutrient constituents show a strong relationship to storm flow events,
reinforcing the importance of event-based sampling.
8
10000
8
7
NO3
100
6
-1
TDN
5
3
1000
4
3
PO4
10
2
1
NH4
1
5-Jan
discharge (m s )
flow
(Kmol)
cumulative export
WY 2001
0
15-Jan
25-Jan
4-Feb
14-Feb
24-Feb
6-Mar
Figure 5: Cumulative nutrient export for Franklin Creek watershed, winter WY2001.
The magnitude of nutrient flux being discharged from the three Carpinteria creeks is
presented in Table 3 and Figure 6. Franklin Creek exports almost twice as much
nitrate as the other two streams combined. The kilograms per hectare leaving
Franklin Creek is significant and far exceeds any other coastal watershed in the
region. For comparison, studies of nutrient export from Chesapeake Bay watersheds
range from 0.07-4 kg ha-1yr-1 total phosphorus and 1.2-5.8 kg ha-1yr-1 total nitrogen
(Beaulac et al., 1982; Jordan et al., 1997).
Table 3: Summary of nutrient export for winter of WY2001.
WY 2001
Santa Monica
Area
ha
980
3
3
10
m
Discharge
1090
Nutrient loading
kg ha-1yr-1
NH4-N
0.0
-1 -1
kg ha yr
NO3-N
2.0
-1 -1
DON-N kg ha yr
0.5
-1 -1
kg ha yr
PO4-P
0.1
9
Franklin
1160
1135
Carpinteria
3920
3362
0.2
9.7
3.3
0.9
0.0
1.2
0.4
0.2
12,000
NH4-N
Nutrient Export (kg yr-1)
10,000
NO3-N
8,000
DON-N
PO4-P
6,000
4,000
2,000
0
Santa Monica
Franklin
Carpinteria
Figure 6: WY2001 nutrient export at the outlets for the three principal watersheds in
the Carpinteria Valley.
Nutrient fluxes vary among land use classes and from storm to storm during any
given year. As an example, export of nitrate and phosphate from three land use
classes (residential, commercial and greenhouse) is shown for three successive storms
during the beginning of WY2002 (Figure 7). The fluxes were normalized with
individual storm runoff at each site to facilitate the comparison. These three storms
were relatively small and the increased spatial and temporal variability of light runoff
makes trend analysis difficult.
1000
NO3-residential
NO3-commercial
NO3-greenhouse
Export (g ha-1 mm-1)
Export (g ha-1 mm-1)
100
10
1
PO4-residential
PO4-commercial
PO4-greenhouse
100
10
1
0
Oct. 30
Nov. 29
Oct. 30
Dec. 20
Nov. 29
Dec. 20
Date of Storms
Date of Storms
Figure 7: Comparison of the nutrient flux from three land use sub-catchments for
three consecutive storms at the beginning of the WY2002 rainy season. Data are
normalized by storm runoff.
For nitrate, the commercial and residential signals had a decreasing relationship with
consecutive storms. The downward trend could be caused by the flushing of nutrients
10
built up over the dry season, i.e., initial flushing that might eventually level off after a
series of storms. The opposite trend was seen at the greenhouse site, possibly
indicating an increase in soilwater contribution with subsequent storms. Phosphate
export lacked a clear trend, except for the greenhouse sub-catchment where the flux
increased with subsequent storms. The lack of any pattern at the other sites may be
caused by the confounding relationship between phosphate concentrations, sediment
load and rainfall intensity. The three different land use classes had nearly order-ofmagnitude flux differences. The greenhouse phosphate increased with sequential
storms and was not as pronounced as the nitrate increase, which may indicate a
leveling off of phosphate export. Residential phosphate was significantly higher than
at the commercial site.
The next phase of the project will be to identify nutrient export coefficients for each
land use class and apply them in a catchment scale model to predict nutrient export
from Mediterranean coastal watersheds. The nutrient export coefficient model will
be a semi-distributed lumped model where sub-basins are defined by land use class
and routed to the ocean by the nearest stream channel. A downstream nutrient decay
term, derived from the literature, will be included. The general nutrient loss equation
is:
Li   E i A I i K i  Datm
i
Ki = e-t
Li – Nutrient loss (mass/area-time) for land use i.
Ei – Export Coefficient (mass/area-time) for land use i.
Ai – Area of land use i.
Ii – Anthropogenic nutrient input to land use i.
Ki – Decay coefficient (units) for land use i that includes the distance decay
from the particular land use downstream to the outlet (Ki).
Datm – Wet and dry atmospheric nutrient deposition input.
 – Coefficient (no units) used for scaling.
t – travel time or distance (length) to receiving water body divided by
velocity.
Field data will be used first to calibrate, and secondly to validate the model for
prediction of nutrient fluxes. The export coefficient will be designed as a function
based on land use type and catchment response, i.e., a watershed response function to
identify when, and at what rate, the watershed will leak nutrients to the stream.
Conclusion
Stream nutrient concentrations can only partially indicate possible downstream
impacts to estuaries and the near-shore coastal zone. Determining the nutrient flux is
essential for analysis of adverse effects and as a basis for management decisions.
Stream hydrology is the critical element in any flux calculation and careful attention
should be given to obtain the most accurate data possible. A sampling strategy that
11
captures the rise and fall of the hydrograph will yield informative results, particularly
for the short, steep and hydrologically flashy streams that characterize California’s
southern coastal region. It is crucial to develop a dedicated and enthusiastic group of
stream samplers that can carry out the necessary hourly sampling regime. However,
this type of effort is both time-consuming and expensive. To obtain the maximum
benefit from such research it is important that a modeling effort allowing
extrapolation of findings to other similar watersheds be incorporated. We have
chosen to develop an event-based, export coefficient model, from our Carpinteria
sampling program, to characterize nutrient export from Mediterranean coastal
streams.
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