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Groundwater Rights in Mexican Agriculture: Spatial Distribution and
Demographic Determinants
Christopher A. Scott a; Sandy Dall'erba a; Rolando Díaz Caravantes b
a
University of Arizona, b Universidad Autónoma de Ciudad Juárez,
First published on: 04 December 2009
To cite this Article Scott, Christopher A., Dall'erba, Sandy and Caravantes, Rolando Díaz(2010) 'Groundwater Rights in
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ARTICLES
Groundwater Rights in Mexican Agriculture: Spatial
Distribution and Demographic Determinants∗
Christopher A. Scott and Sandy Dall’erba
University of Arizona
Downloaded By: [Scott, Christopher A.] At: 16:23 7 January 2010
Rolando Dı́az Caravantes
Universidad Autónoma de Ciudad Juárez
Groundwater use intensity and aquifer depletion increase from south to north with decreasing rainfall
and increasing economic activity in Mexico. To heighten scholarly understanding and offer new insights
that strengthen policy responses to aquifer depletion, we analyze the spatial distribution of agricultural
groundwater use from irrigation well titles in 2,429 municipalities and its relation to agricultural surface water
and population employed in agriculture. Exploratory spatial data analysis reveals spatial dependence among
all three variables implying that policy initiatives to address intensive groundwater use must be targeted at
clusters of aquifers and municipalities. Key Words: groundwater, Mexico, spatial statistics, water rights.
La intensidad del uso de agua subterránea y el agotamiento de los acuı́feros en México se incrementan de
sur a norte en relación con la disminución de la lluvia y el incremento de la actividad económica. Para
mejorar la comprensión de estos problemas y explorar nuevas ideas que fortalezcan las polı́ticas de respuesta al
agotamiento de acuı́feros, analizamos la distribución espacial del uso agrı́cola de agua subterránea extraı́da de
pozos autorizados en 2.429 municipios, y su relación con el uso de agua agrı́cola de superficie y la población
empleada en agricultura. El análisis exploratorio de los datos espaciales revela una dependencia espacial entre
todas las tres variables, lo cual implica que las iniciativas sobre polı́ticas que afronten el uso intensivo de agua
subterránea deben concentrarse en agrupamientos especı́ficos de acuı́feros y municipalidades. Palabras clave:
agua subterránea, México, estadı́stica espacial, derechos del agua.
L
and, population, and economic development are concentrated in arid and
semiarid northern Mexico, whereas much of
the south has abundant water supplies and is
prone to flooding (witness the catastrophic
late 2007 floods in Tabasco and Chiapas).
Despite sustained investment in infrastructure
to store surface water and in the development
of groundwater, the availability of water in
absolute terms or in relation to states’ economic ranking is severely limited in the north;
however, due to land concentration and the
∗ This work was carried out with the aid of a grant from the Inter-American Institute for Global Change Research (IAI) SGP-HD No. 005, which
is supported by the U.S. National Science Foundation (Grant GEO-0642841), and by the National Oceanic and Atmospheric Administration’s
Sectoral Application Research Program. The study design, data collection and analysis, and preparation of this article were entirely determined
by the authors.
C Copyright 2010 by Association of American Geographers.
The Professional Geographer, 62(1) 2010, pages 1–15 Initial submission, April 2008; revised submissions, December 2008 and March 2009; final acceptance, June 2009.
Published by Taylor & Francis Group, LLC.
Downloaded By: [Scott, Christopher A.] At: 16:23 7 January 2010
2 Volume 62, Number 1, February 2010
structure of commercial farming in the north,
this is where water use per person employed in
agriculture tends to be the greatest. The distribution of access to water varies by use, by type
of user, and spatially across the country and
within regions and river basins. Throughout
the twentieth-century development of water
resources in Mexico, however, water use was
not quantified in sufficient detail to permit assessment of socioeconomic or location-specific
differences. This changed with water rights
titling beginning in 1992, a process described
in further detail in what follows. This process
allows us to provide a detailed analysis of the
distribution of groundwater across Mexican
municipalities.
It was during the 1990s that groundwater
received increased attention in Mexico and
faced growing demand as a critical resource
(Vázquez Rodrı́guez 1999; Marañon-Pimentel
and Wester 2000). At the national level,
groundwater currently accounts for two thirds
of the water supplied for urban populations,
half of the water for industry, and a third of the
water for agriculture (Comisión Nacional del
Agua [CONAGUA] 2008). Driven by rising
demand and pumping of groundwater coupled
with variable recharge, many regions of the
country, particularly the Baja California peninsula and the adjoining northwest region of
Mexico, are experiencing aquifer overexploitation, leading to depletion and deterioration of
water quality in this critical resource. One hundred and four of Mexico’s principal aquifers
are overexploited, up from thirty-two in 1975
(CONAGUA 2008), a trend that is seen in
numerous regions around the world (Shah et al.
2003; Kettle, Harrington, and Harrington
2007; Giordano and Villholth 2007). Mexico is
the largest user of groundwater in Latin America, with more than 100,000 large-capacity
pumps for agriculture alone (Scott and Shah
2004). Each of these groundwater wells must
be titled to the individual, commercial, or
public owner, in distinction from surface water
rights, which are granted to groups of users.
Spatially explicit data on groundwater titles
represent an important decision-making input
to address aquifer exploitation and the related
policy challenge of safeguarding societal dependence on groundwater. Spatial tools for water
resources management in Mexico are being developed and applied, such as canal irrigation op-
erations and management (Ojeda-Bustamante
et al. 2007) and Global Positioning System
locational inventorying of infrastructure for
operational purposes. However, despite innovation with spatially explicit groundwater models for decision support, for example, in the
central state of Guanajuato (Sandoval-Minero
2001), the Mexican government’s official estimates of groundwater availability and depletion
are estimated based on aquifer-wide average
water balances of supply (recharge) and demand (pumping). Decision makers have paid
inadequate attention to the potential presence
of spatial dependence in the distribution of
groundwater levels across municipalities, to the
relationship between groundwater and population employed in agriculture, and to the conjunctive role of surface irrigation (important
both for recharge of underlying aquifers and
as an alternative source of irrigation water).
This article presents specific spatial analyses
that might permit decision makers to address
these policy gaps.
The article is organized as follows. The introduction has provided a brief overview of water resources in Mexico with an emphasis on
aquifer depletion and associated management
and policy challenges. We augment this with a
section discussing water rights, particularly in
agriculture. Next we set forth our conceptual
approach and specific objectives, identifying
the contribution this article makes to the relevant literature as well as potential policy uptake
to address aquifer depletion in Mexico. The
analysis follows, with an exploratory spatial data
analysis of the distribution of ground and surface water rights, coupled with labor in agriculture across Mexico’s municipalities. The article
concludes with a discussion of Mexico’s intensive groundwater use and aquifer depletion
challenges and highlights policy implications.
Water Rights in Agriculture
In Mexico, the Public Register of Water Rights
(Registro Público de Derechos de Agua [REPDA]
2008) codifies water rights as mandated by the
Law of the Nation’s Waters (Ley de Aguas
Nacionales [LAN]) and its regulations. The
REPDA is managed by CONAGUA. Although
the LAN was promulgated in 1992, the REPDA
has only recently become operational as a reliable database (Garduño 2005). As of the end of
Downloaded By: [Scott, Christopher A.] At: 16:23 7 January 2010
Groundwater Rights in Mexican Agriculture 3
2006, over 97 percent of the water rights titling
process was completed (CONAGUA 2008).
It is instructive to review other provisions
of the LAN that influence water management
and access, namely, the role of CONAGUA,
the structure and functioning of river basin
councils as a mechanism for the management
of water resources, and public participation in
water management. A federal agency within
the environment ministry, CONAGUA is responsible for administering and managing water resources. Water is considered property
of the nation; however, there is some definitional ambiguity regarding “state” waters (surface sources that originate and are depleted
within a state). All groundwater is national
property. During the 1990s, CONAGUA’s
principal mandate was to manage surface water resources. In 1992, it initiated the transfer of large irrigation districts (3.2 million
hectares in total, largely relying on surface
water sources) to water users. For the purposes of our analysis, it is important to note
that rights to surface water in this case were
granted at the level of the water user association, which typically encompasses thousands
of individual users (Rap, Wester, and PérezPrado 2003). Small surface water irrigation systems and some collective groundwater systems
called irrigation units (unidades de riego) continued under user management with group water
rights (Palerm Viqueira and Martı́nez Saldaña
2000; Silva-Ochoa 2000; Scott and Silva-Ochoa
2001). Water users along with federal and
state agencies are represented on Mexico’s river
basin councils, which have achieved considerable acclaim internationally. Representation on
the councils and a series of related public participation initiatives for water management are
based on the water users holding rights codified
in the REPDA.
CONAGUA administers the titling and concessioning of all water rights, both to surface
and groundwater sources, which are written
into the REPDA. Concessions are granted
for a specified annual volume over the period of the concession (typically ten years
for groundwater) and must be renewed. The
application process requires that no damage
to third parties be substantiated; however, in
practice this is just a formality. It has been
noted that for some aquifers, the sum total of volumetric concession titles may exceed sustainable yield (Moreno Vásquez 2006),
indicating overexploitation with negative implications for other groundwater users. In a bid
to bring the actual use of groundwater in line
with the concessioned volume, all agricultural
titles now specify that the user must install
a volumetric flow meter and report pumped
volumes to CONAGUA. Our primary observations based on fieldwork in Sonora, Chihuahua,
Guanajuato, and other states using large volumes of groundwater in agriculture indicate
that flow meters and volumetric reporting are
beginning to be enforced, but these records
are not systematically kept or made available
for research purposes.
The principal uses of groundwater recognized in the REPDA include public and urban, industry, aquaculture, agricultural, and
livestock use. Public and urban and industrial
users pay for water rights. This represents an
increasingly important source of revenue for
CONAGUA (Scott et al. 2004). Growth in demand must be met by acquiring additional water rights. Industrial users are similarly allotted
an annual volume and must pay for water rights.
Agriculture, which represents the largest share
of groundwater extraction, does not have to pay
CONAGUA for rights. However, individual
well owners (or groups of users) must formalize their concessions with a title. In addition
to specifying the annual volume concessioned
based on the discharge of the well and the area
of irrigable land reported, the title spells out
the norms regarding repositioning of the well,
cessation of rights for unutilized volumes (over
three consecutive years), and the transfer (sale)
of rights, among other provisions.
Irrigation plays a critical role in agricultural and livestock production, particularly in
arid and semiarid regions such as northern
Mexico, where rain-fed agriculture is severely
constrained by soil moisture and changing climate (Loaiciga 2003). Surface water irrigation
conveyed from reservoirs through canals to
farmers’ fields tends to be inflexible in terms
of timing and delivery; as a result, farmers’ decision making on which crops to plant, when,
and in what area is limited by the supply of canal
water. Groundwater irrigators, on the other
hand, enjoy considerable flexibility in this regard. However, a major benefit associated with
receiving surface water is that irrigation fees
tend to be relatively low given that federal or
state governments have incurred the cost of infrastructure development and in many cases
4 Volume 62, Number 1, February 2010
continue to subsidize canal irrigation operational costs (Wester 2008).
Downloaded By: [Scott, Christopher A.] At: 16:23 7 January 2010
Conceptual Approach and Objectives
Llamas and Custodio (2003, 5, 16–17) held
that “intensive use of groundwater” provides
better explanatory insight into the sustainability of human dependence on aquifers than
“safe yield” or related extraction-to-recharge
ratios. Their intensive use framework assesses
human demand and technology in the contexts of physical hydrogeological process and
spatial and temporal scale. Sustained “overexploitation” of aquifers that drops water levels and deteriorates water quality may only be
viewed as an adaptation strategy in the short
term. Intensive use of groundwater that relies
on technology, such as more efficient pumps
and desalination, or spatially shifts demand to
other locations within the aquifer without reducing overall extraction will generate serious
medium- and long-term impacts. They assess
intensive groundwater use in central Spain,
which they explicitly acknowledge bears similarity with northwest Mexico. For the purposes
of this article, we follow Llamas and Custodio
by assessing the human drivers of aquifer depletion, and we expand on their spatial characterization of intensive groundwater use by
analyzing detailed data from Mexico using the
tools of exploratory spatial data analysis that
allow us to identify and measure spatial dependence across our observations. Whereas these
authors eschew value-based judgments in assessing groundwater management in Spain and
leave policy implications to national and local
authorities (Llamas and Custodio 2003), we attempt to draw out specific policy implications.
To augment the intensive use framework
with specific management and policy considerations, we turn to Shah (2009), who provided
a nuanced and extended historical view of
groundwater use in South Asia where agriculture (irrigation) represents the dominant use,
similar to Mexico. Shah’s analysis of the human
drivers and institutional dynamics in response
to the development of aquifers with distinct
hydrogeological characteristics has applicability beyond South Asia. Based on data from
Mexico, we assess two of Shah’s propositions
on irrigation development and the interrelation
between ground and surface water. First, as
distinct from South Asia, surface water remains
the principal source of irrigation in Mexico in
aggregate terms. However, groundwater can
be intensively used instead of surface water
at a specific location, although we recognize
that the interactions between irrigation uses
of these two sources of water are complex
and depend on hydrologic, economic, and
other variables not fully captured by the spatial
analysis for Mexico we present in this article.
Second, Shah contends that population and
its spatial density drive intensive groundwater
use. Although our goal here is not to assess the
direction or the extent of the causality between
both variables, we provide in the sections
that follow a discussion of their relationship.
Based on our field experience, groundwater
use and socioeconomic data from Mexico, and
analysis in this article, we selectively interpret
relevant conceptual frameworks advanced by
Llamas and Custodio (2003) and Shah (2009).
As objectives, we posit that intensive use of
groundwater for agriculture and livestock in
Mexico follows two dependent relations.
Groundwater use tends to substitute for surface water use in Mexico; that is, areas with high
access to groundwater do not necessarily have
high access to surface water, in contrast to other
regions in which surface water irrigation plays
an important complementary role in recharging underlying groundwater aquifers through
irrigation return flows (Gale 2005). Additionally, groundwater access should be clustered,
with adjacent areas sharing similar characteristics in access to groundwater. Given the complexity in the human uses of ground and surface
water, we expect these results to be mixed and
that definitive claims will be localized based
on irrigation practice and hydrological processes and must therefore be supported by fieldbased evidence. Access to ground and surface
water is posited to increase with agrarian labor population, despite significant variation in
mechanization, agricultural labor absorption,
and farm enterprise scale across regions in
Mexico; in other words, areas with access to water for agriculture have a high percentage of the
labor force employed in agriculture. Whether
labor is the determining variable, following
Boserup’s (1965) contention that population
pressure drives innovation in food production,
or the reverse, that water availability facilitates
Downloaded By: [Scott, Christopher A.] At: 16:23 7 January 2010
Groundwater Rights in Mexican Agriculture 5
labor absorption in agriculture (White 1994),
remains an intriguing question.
The final objective of this article is to elucidate geographical (both physical and human)
drivers of aquifer depletion with a view to informing policy. We consciously employ spatial and statistical tools to analyze the large
REPDA database given our intent to observe
patterns across Mexico’s irrigated agricultural
landscapes, identify the potential presence of
spatial dependence in the distribution of the
characteristics of these landscapes, and provide
policy implications based on our findings. Additional analyses based on fieldwork (e.g., of
aquifer properties or agrarian labor dynamics)
are the necessary next step to gain a detailed
contextual knowledge of the Mexican agricultural sector. In addition, we intend at a later
stage to combine this approach with a formal econometric estimation of the dynamics
at stake in this sector. The goal of this article,
then, is to elucidate the complexities and the
spatial characteristics of the Mexican agricultural landscape by means of exploratory spatial
data analysis but to leave more complete exploration to future research.
Data and Methods
The municipality (municipio) is the administrative unit below the state that was chosen as
the unit of analysis to permit cross-comparison
of REPDA data with census data reported
by the National Institute for Statistics, Geography, and Information Science (Instituto
Nacional de Estadı́stica, Geografı́a e Informática).
The following REPDA data were downloaded
in November 2006 for 423,179 records: number and volume (cubic meters per year) of water rights titles by use category (aquaculture,
agriculture, agroindustrial, domestic, power
generation, industrial, multiple use, livestock,
public and urban, or services). Each record
distinguishes groundwater or surface water as
the source. Agricultural groundwater (AGW)
and agricultural surface water (ASW) were
summed as the respective totals of agriculture and livestock uses and were aggregated at
the level of 2,429 municipalities and thirty-two
states.
In this article, we perform an exploratory
spatial data analysis (ESDA) of the distribution
of water access across Mexican municipalities.
The strength of ESDA lies in its capacity to discover patterns of spatial association, clusters, or
hot spots and to suggest the presence of spatial
heterogeneity (Haining 1990; Anselin 1995).
The patterns we are particularly interested in
are whether locations in close proximity register similar AGW levels with respect to ASW
and population employed in agriculture (PEA).
GeoData Analysis software (GeoDa 0.9.5i5) was utilized for ESDA of groundwater
and surface water access in Mexico. With
an explicit focus on the geographical characteristics of the data, ESDA is an increasingly popular GIScience-based technique that
allows users to describe and visualize spatial distributions; identify atypical locations
or spatial outliers; discover patterns of spatial association, clusters, or hot spots; and suggest spatial regimes or other forms of spatial
heterogeneity. It utilizes a wide range of largely
graphical methods that explore the properties
of data sets without the need for formal model
building (Anselin 1988, 1999; Haining 1990).
Results and Discussion
Figure 1 shows the states in Mexico and
complements Table 1, the municipality-level
summary data of the variables of primary
interest for our analysis, grouped by states
in northern and southern Mexico. States
with high mean municipality AGW include
Baja California Norte (BCN), which has the
country’s largest area municipalities and high
standard deviations across AGW, ASW, and
PEA; Guanajuato; Baja California South (BCS);
and Chihuahua, all of which are northern states
facing aquifer depletion. By contrast, the states
with low mean AGW are Oaxaca (with the
smallest area municipalities that account for almost a quarter of the country’s total number
of municipalities), Guerrero, and Veracruz in
the south, leading to a principal observation
that high AGW is an important driver of aquifer
depletion. In fact, no southern state experiences aquifer depletion. The distribution of
mean municipality ASW values presents mixed
results, with neither high nor low values corresponding to aquifer depletion, with the exception of urbanized Distrito Federal (Mexico
City), which has little agriculture to exert much
demand for ASW or AGW, yet still experiences
Downloaded By: [Scott, Christopher A.] At: 16:23 7 January 2010
6 Volume 62, Number 1, February 2010
Figure 1
Mexican states.
depletion. The mean AGW/ASW ratios similarly are unclear in patterns that would shed
light on pressure and response to aquifer depletion. As discussed in more detail later, another finding is that across Mexico’s regions
AGW appears independent of ASW; that is,
AGW can be high in the presence or absence
of ASW.
States with high mean municipality total
population include Distrito Federal, BCN,
and Mexico state, as well as agriculturally
important Sinaloa, Tabasco, and Guanajuato.
From our interest in agriculture and irrigation, states with high mean municipality PEA
include Sinaloa, BCN, Tabasco, and Chiapas.
These observations on population—total or
agricultural—in themselves are not noteworthy for our analysis of intensive groundwater
use, so to better understand aquifer depletion
we must consider AGW and its relation to both
PEA and ASW. Table 1 shows high mean municipality AGW for BCN, Guanajuato, BCS,
and Chihuahua—all with recognized aquifer
depletion problems. To support our hypothesis that agricultural population correlates with
intensive use, an additional finding is that sim-
ple regression of mean AGW versus mean
PEA yields a positive relationship significant
at p < 0.05. The AGW/PEA ratio is highest in Chihuahua, Aguascalientes, and Sonora.
Aguascalientes represents the particular case of
a small area state dominated by a large city
where aquifer depletion appears more related to
concentrated urban and industrial groundwater
pumping. Coahuila and Zacatecas have high
AGW/PEA ratios and are experiencing aquifer
depletion, whereas the lowest ratios are found
in Guerrero, Veracruz, and Tabasco, which
do not currently face depletion. We find,
therefore, that high AGW with low PEA
in northern Mexico corresponds to aquifer
depletion.
Figures 2 through 4 show the spatial distribution of AGW, ASW, and PEA by municipality. It is apparent that AGW is concentrated
in northwestern and north-central Mexico
(Figure 2), with some additional AGW in the
southeastern Yucatan Peninsula, largely for
plantation agriculture including tropical fruits.
As mentioned earlier, because rainfall declines
from south to north in Mexico, in the northern
areas of high AGW, agriculture is only possible
7
101
National total
2,429
1,324
11
5
6
67
38
10
16
39
46
84
123
121
113
33
21
51
217
18
58
18
70
43
60
56
1,105
9
110
76
570
9
17
208
106
M
SD
Population
in 2000
M
SD
PEA in
2000
M
SD
AGW/ASW
M
SD
AGW/PEA
M
SD
ASW/PEA
25,715,795
2,946,131
684,391
308,490
9,058,474
2,131,113
887,824
3,139,697
41,515,186
15,448,544
2,032,029
1,123,040
21,459,976
3,208,728
2,911,786
11,030,595
3,530,777
5,719,410
3,705,041
566,877
43,201
2,824,417
2,254,553
0
10,223,560 50,869 66,356
30,246,051 35,077 51,989
15,537,039 40,522 84,883
1,877,660
6,003 14,680
124,998 97,218 135,712
5,105,748 111,284 118,553
12,990,068 32,934 52,824
0
15,643 68,636
4,275
5,071
3,127
766
4,062
9,842
3,544
1,002
3,236 5,005,126 7,266,455
4,278
4,438
42,131
2,800
5,156
37,299
1,092
37,340
267,322
4,849 249,304
571,570
5,623
91,730
289,144
3,399
98,746 1,066,481
1,146 3,139,697 11,030,595
4,480
499
143
537
857
398
252
2,255
5,412
1,634
459
1,540
1,429
1,022
762
3,010
2,552
1,379
888
1,290
3.6
341
636
—
7,602
8,675
2,967
4,260
8.6
553
4,648
—
21,646,462 26,199,725 10,238,282 16,962,956 85,844 185,775 2,217 1,815
7.3
6.1 13,530 16,947 3,307 2,914
87,743,494 111,000,000 3,743,321 5,013,947 497,473 490,106 11,512 14,357
32.0
12.2 8,615 7,647
335
334
35,813,496 47,322,348 3,886,983 4,912,446 70,674 72,472 3,356 2,700
12.0
12.0 6,899 7,694
749
762
31,553,068 63,917,947 6,642,497 12,931,606 45,566 167,813 1,480 1,370 847,722 6,714,356 15,671 26,125 6,222 13,138
17,316,939 34,161,406 3,778,317 6,380,514 60,476 125,183 1,147 1,307 4,136,717 11,300,043 11,680 10,965 6,583 13,473
20,054,559 36,037,283 40,778,536 61,204,247 54,263 49,279 3,390 3,182
0.7
1.0 5,295 10,597 10,879 13,716
1,330,053
2,309,350
211,522
259,923 537,827 422,092 1,288 1,584 134,377
298,886 3,973 8,378
530
991
11,107,156 19,436,377 3,455,072 4,864,502 37,145 87,159 1,708 1,608 1,731,240 5,431,096 5,016 5,591 2,412 3,376
36,349,157 38,720,647 7,098,857 17,588,856 101,370 178,166 4,200 3,275 5,175,517 20,395,409 7,283 5,016 2,665 11,119
1,198,849
3,743,876 2,853,662 6,371,097 26,614 32,014 2,189 2,058
41,319
299,760
687 1,738 1,679 2,777
5,771,702 10,426,479 3,257,959 6,347,992 50,938 178,629 1,890 1,556
49,115
476,327 2,224 3,428 1,726 3,025
1,429,628
3,661,308 3,985,827 7,843,172 105,564 224,462 1,918 2,005 220,497
957,150 1,322 2,991 2,531 8,702
7,190,823 15,107,234 9,754,271 22,987,187 35,271 66,716 2,573 2,075 566,123 2,903,060 2,538 3,990 3,024 6,873
2,200,376
3,819,606 1,919,151 3,624,583 47,130 65,348 2,257 1,413 486,114 1,149,374
875 1,203
898 1,524
2,843,693
3,374,998 10,101,890 15,506,495 43,818 63,850 4,223 3,861
2.0
6.0
783
903 1,819 1,901
9,352,961 18,928,196 10,028,571 21,123,088 75,179 193,443
950 1,097 2,441,308 12,025,164 8,961 26,371 11,396 24,938
2,666,040
6,217,664 2,717,707 12,408,459 23,395 93,430 2,142 2,063 900,939 2,524,633 1,312 2,024 1,804 7,710
15,634,022 27,668,265 4,788,403 5,496,233 78,017 145,878 2,304 1,294
10.2
22.1 5,466 7,367 2,341 2,777
8,375,893 15,986,697 5,915,284 17,738,560 39,644 90,081 2,630 2,278 1,328,640 4,422,149 4,518 7,695 1,928 3,629
13,846,164 14,157,812 18,572,505 38,381,865 140,936 188,905 13,744 13,328
16.2
33.3 1,391 1,545
911 1,457
15,922,674 39,968,621 5,974,319 18,755,914 31,671 88,772 1,839 3,858
66,466
277,780 12,075 16,687 11,340 30,916
5,805,225 16,124,190 15,530,075 25,389,838 64,028 110,870 2,161 1,682
21,746
99,956 2,081 5,455 7,296 12,061
1,723,865
4,440,494
709,841 1,564,884 16,044 16,851
997 1,012 1,071,115 4,424,617 1,577 2,018
679 1,284
15,921,976 31,497,623 3,103,753 4,769,510 23,938 32,456 1,298 1,340 1,861,795 10,206,403 9,853 11,776 3,534 8,990
SD
M
M
SD
ASW (cubic
meters/year)
AGW (cubic
meters/year)
Note: AGW = agricultural groundwater; ASW = agricultural surface water; PEA = population engaged in agriculture.
101
4
6
4
7
9
0
2
6
8
1
1
4
5
2
0
1
2
4
6
0
17
0
3
9
0
0
0
0
0
0
0
0
0
Northern Mexico
Aguascalientes
Baja California N.
Baja California S.
Chihuahua
Coahuila
Colima
Distrito Federal
Durango
Guanajuato
Hidalgo
Jalisco
Mexico
Michoacan
Morelos
Nayarit
Nuevo Leon
Puebla
Queretaro
San Luis Potosi
Sinaloa
Sonora
Tamaulipas
Tlaxcala
Zacatecas
Southern Mexico
Campeche
Chiapas
Guerrero
Oaxaca
Quintana Roo
Tabasco
Veracruz
Yucatan
No. over
exploited
No.
aquifers municipios
Municipality-level water and population summary data by northern and southern states
State
Table 1
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8 Volume 62, Number 1, February 2010
Figure 2
Agricultural groundwater (volume per municipality per year).
with irrigation. This raises a critical resource
dependence issue: Without surface water as
an alternative source, agriculture in northern
Mexico is based primarily on groundwater irrigation. It should also be noted that northern
Mexico’s proximity to the United States gives
it a strategic commercial advantage over other
regions of the country for export agriculture in
the context of the North American Free Trade
Agreement. We have primary evidence from
the northwestern state of Sonora of agricultural
investment and trade (through contract farming), not just of U.S. capital but also of Chilean
investors seeking a year-round supply of table
grapes for U.S. markets; that is, November and
December production in Chile complemented
by May and June production in Mexico. The irrigation water requirements during these summer production seasons are extremely high, and
aquifers in Sonora continue to face depletion.
It should also be noted that, even if surface
water were available, high-precision drip irrigation is better suited to on-demand groundwater from the farms’ own pumps, whereby
farmers seek to protect themselves from erratic supplies that characterize public sur-
face irrigation systems. For example, the large
ASW rights in north-central Mexico (Durango
and Coahuila) are predominantly to irrigate
sorghum and alfalfa as fodder for the important
dairy industry in the La Laguna region. Nevertheless, there are notable examples of ASW
used for high-value commercial agriculture,
such as tomato and fresh vegetable farming
in Sinaloa that makes significant use of ASW
(Figure 3).
However, intensive farming operations of
the kind already described require significant
farm labor. Figure 4 shows PEA. It is evident
that the spatial distribution of PEA across
Mexico corresponds more closely to AGW
than to ASW, suggesting that labor absorption
is higher in AGW-based farming than ASWbased farming. To quantitatively analyze the
data based on the spatial and demographic
objectives we have set out for this article, we
turn next to ESDA of spatial clustering and
spatial autocorrelation of the ratios of AGW
with ASW and PEA as described later. Spatial
autocorrelation refers to the coincidence of
attribute similarity and locational similarity
(Anselin 1988). In the context of our study,
Downloaded By: [Scott, Christopher A.] At: 16:23 7 January 2010
Groundwater Rights in Mexican Agriculture 9
Figure 3
Agricultural surface water (volume per municipality per year).
Figure 4
Population employed in agriculture (2000).
10 Volume 62, Number 1, February 2010
Downloaded By: [Scott, Christopher A.] At: 16:23 7 January 2010
positive spatial autocorrelation indicates
that municipalities with high use of AGW
relative to ASW tend to be geographically
clustered, whereas municipalities with low
AGW/ASW also tend to be clustered. Spatial
autocorrelation may be due to (1) “substantive”
factors, such as proximity to U.S. markets
for agricultural exports, climatic conditions,
and agricultural production structure that
physically adjacent municipalities tend to
share; or (2) to a “nuisance” factor due to
a mismatch between the boundaries of the
municipalities used to organize the data and
the actual boundaries of the processes we are
trying to capture (Anselin 1988).
Spatial Weight Matrix
The definition of a spatial weight matrix is
necessary to carry out the successive steps of
ESDA. Spatial dependence can occur in any direction, so weight matrices are computed with
reference to the k = 10 nearest neighbors as
follows:
⎧
wi j (k) = 0 if i = j
⎪
⎪
∗
⎪
⎪
⎨wi j (k) = 1 if d i j ≤ Di (k) and w(k) = wi j (k)
ij
(1)
⎪
w (k) for k = 10
⎪
⎪ j ij
⎪
⎩
wi j (k) = 0 if d i j > Di (k)
where d i j is the great circle (arc) distance between centroids of region i and j. Di (k) is the
critical cutoff distance defined for each region
i, above which interactions are assumed negligible. In other words, Di (k) is the kth-order
smallest distance between regions i and j such
that each region i has exactly k neighbors. Each
matrix is row-standardized so that distance is
relative and not absolute, yielding the matrix
∗
∗
w. Each nonzero entry in w is therefore 0.1.
The choice of a spatial weight matrix is always
somewhat arbitrary. To limit the influence of
the choice of the matrix on our results, we also
compute a contiguity and two distance-based
matrices (with cutoffs of 320 km and 800 km)
to verify whether our findings are sensitive to
the choice of the weight matrix.
Spatial Autocorrelation Using Moran’s I
Based on the spatial weight matrix defined in
Equation 1, we proceed to analyze the spatial
distribution of our variables using Moran’s I,
which captures the global spatial autocorrelation of the variables of interest; that is, for each
variable, Moran’s I gives the degree of linear
association between its value at one location
and the spatially weighted average of neighboring values. To draw inferences, we use a
random permutation procedure that recalculates the statistic to generate a reference distribution and a pseudo-significance level from
10,000 permutations (Anselin 1995). For each
variable of interest, Moran’s I is given by:
n
n I=
∗
wi j (k)xi x j
i=1 j =1
n n
i=1 j =1
(2)
xi x j
∗
where w is the (row-standardized) degree
ij
of connection between the spatial units i
and j, and xi and x j are the variable of
interest in regions i and j (measured as a
deviation from the mean value). Moran’s I
values larger (or smaller) than the expected
value E(I ) = −1/(n − 1) indicate positive
(or negative) spatial autocorrelation. The
results indicate the presence of positive spatial
autocorrelation; that is, regions with high
AGW/ASW (Moran’s I = 0.1151), high
AGW/PEA (I = 0.3687), and high ASW/PEA
(I = 0.1714) tend to be geographically clustered, whereas regions with low values tend to
be close to each other as well. All the Moran’s
I values just given have an expected value of
–0.0004 and are significant ( p value = 0.0001).
These results are consistent with all the spatial
weight matrices defined previously. As a result,
the value of these variables in one location is
significantly related to the value of the same
variables in neighboring locations. If found to
be significant, spatial dependence is an important factor that needs to be included in policy
formulation and assessment of regulations. We
recommend that groundwater management in
Mexico systematically include the characteristics of the agricultural landscape and water
demand of the individual municipality but also
those of neighboring municipalities where the
aquifer is located. Some efforts have been made
in this direction in recent years (SandovalMinero 2001), but this is the first time that the
Groundwater Rights in Mexican Agriculture 11
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extent of spatial dependence across Mexican
municipalities is formally measured.
Significance of Spatial Clustering Using
Local Indicator of Spatial Association
Although very useful, the Moran’s I does
not give any indication of the significance or
localization of spatial clustering. To address
this problem, we continue our analysis with
a local indicator of spatial association (LISA).
The calculation of LISA statistics for each
observation allows us to obtain an indication of significant local spatial clusters (also
called hot spots) as well as for the diagnostics
of local instability, significant outliers, and
spatial regimes. Anselin (1995) formalizes the
local Moran’s statistics for each region i as:
Ii =
xi
m0
j
∗
wi x j
with m0 =
xit2 /n
i
(3)
where xi and x j are the variable of interest
in regions i and j (measured as a deviation
from the mean value). As for the preceding Moran’s I, the significance level is based
Figure 5
on a conditional permutation approach with
10,000 random permutations of the neighboring municipalities for each observation. Figures
5 through 7 are the LISA maps for AGW/ASW,
AGW/PEA, and ASW/PEA with k = 10 nearest neighbors. Note that the municipalities in
white are those where the Moran’s statistics are
not significant at 5 percent.
Figure 5 demonstrates multiple clusters of
AGW/ASW spatial association. Low values
of AGW/ASW surrounded by low values of
the same variable in south-central Mexico and
along the Pacific Ocean and Gulf of Mexico
coastal regions result from high surface water availability. The low–high cluster in northcentral Chihuahua appears to derive from
municipalities with ASW from the Rı́o Conchos, a Mexican tributary to the Rio Grande
that forms the border with the United States,
surrounded by others that are AGW dependent. Four clusters of high–high municipalities surrounded by low–high municipalities
are important for our discussion of intensive
groundwater use and the targeted clusters of
municipalities that require additional policy
and groundwater attention as alluded to earlier. The first such hot spot is centered on
LISA map of agricultural groundwater/agricultural surface water.
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12 Volume 62, Number 1, February 2010
Figure 6
LISA map of agricultural groundwater/population employed in agriculture.
Figure 7
LISA map of agricultural surface water/population employed in agriculture.
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Groundwater Rights in Mexican Agriculture 13
La Laguna in north-central Mexico, where
Irrigation District DR017 has a concentration of surface water use from the canal system embedded with pockets of high-AGW
groundwater use that are resulting in aquifer
depletion. The second high–high cluster
surrounded by low–high municipalities is in the
state of Guanajuato, also experiencing aquifer
depletion. An additional hot spot is located to
the southeast of Guanajuato in the Mixteca region of Puebla, which has the interesting feature of groundwater use from galerı́as (variants
of qanats, or sloped horizontal tunnels to intercept groundwater within the hillside). The
galerı́as are at risk from groundwater pumping
that threatens to lower aquifer levels and reduce or entirely stop their flow. These three
hot spots require particular emphasis to address groundwater depletion through increasing ASW or, if limited physically, through
reduction in AGW. The final hot spot is in
the Yucatan Peninsula, where the clustering of
interest is driven by high AGW but without
depletion effects mentioned for the other three
clusters.
Figure 6 shows marked results of spatial
clustering of AGW/PEA, which is expected
from the increasing south-to-north trend of
reliance on groundwater as an irrigation source
with south-to-north decreases in percentage
of population in agriculture. Figure 7 indicates
clustering of high–high values of ASW/PEA in
the north-central states of Sonora, Chihuahua,
Coahuila, and Tamaulipas, where most of
Mexico’s large surface water canal irrigation
districts are located. As mentioned earlier, we
interpret these clusters to be closely related
to the physical availability of surface water for
irrigation and low PEA values in the north.
Uniformly, ASW/PEA clustering is low–low
in the south.
Conclusions
Spatial analyses of access to groundwater and
surface water for agriculture in Mexico demonstrate clear patterns of spatial dependence and
north–south heterogeneity. Spatial dependence
results from similar climatic conditions and
agricultural production structure that physically adjacent municipalities share. In addition,
we have detected the presence of several clus-
ters of municipalities in similar agricultural
landscapes. However, these clusters are not
randomly distributed across the Mexican territory but are located in specific areas that
reflect the heterogeneity in the country’s climatic, geographic, and economic conditions.
More precisely, spatial heterogeneity takes
the form of a relatively high groundwater
use in proportion to population in agriculture
in northern Mexico as compared to southern
Mexico, whereas surface water allocation in
proportion to population in agriculture is more
homogeneous. As a result, the spatial distribution of access to groundwater in particular,
together with evidence on aquifer depletion,
demonstrates that the northern and northwestern regions represent Mexico’s major intensive use challenge. Three important hot spots
in Coahuila-Durango, Guanajuato, and Puebla
present particular depletion risks.
Groundwater is an important source of farm
income and employment for agricultural laborers. Mexico has long experienced south-tonorth agricultural labor migration within its
own borders and further into the United States.
This trend and the spatial data on groundwater and population in agriculture suggest
that irrigated farming in the north is a labor
magnet, in a manner similar to that observed
by White (1994). As a result, irrigation development by commercial farmers appears to
drive agricultural groundwater demand and depletion, as well as influence labor migration.
Notwithstanding the results presented in this
article that groundwater sustainability in southern Mexico would permit intensification as a
means to relieve pressure on aquifers in the
north, we do not expect the commercial interests engaged in export agriculture for North
American (U.S.) markets to pursue this option,
although this supposition would require further
investigation.
From a policy viewpoint, the presence of spatial dependence we have highlighted in this
article means that groundwater management
should systematically include the characteristics of the agricultural landscape and water
demand of adjacent municipalities that share
access to the same aquifer. Some efforts seem
to have been made in this direction: Water that
is managed across municipalities requires regulatory and participatory approaches (SandovalMinero 2001), coupled with changes in demand
Downloaded By: [Scott, Christopher A.] At: 16:23 7 January 2010
14 Volume 62, Number 1, February 2010
behavior of pumpers (for early literature on
groundwater governance, see Blomquist 1992).
Where groundwater use is largely agricultural,
cropping changes and water demand can be influenced by commodity prices; however, energy pricing and supply can be determinants of
pumping behavior (Scott and Shah 2004). Regionally targeted caps to limit power supply as
a groundwater demand management option to
address clusters of groundwater depletion can
face social and political challenges. Prices must
be high enough to be in the elastic range of demand response, which is taking place in Mexico as power tariffs are raised (although not in a
depletion-targeted sense) and pumping depths
increase. Given high latent demand, however,
noncommercial smallholder farmers who are
first affected might choose to sell or rent
groundwater to commercial farmers (Wilder
and Romero-Lankao 2006; Wester 2008) instead of shutting down (“retiring”) wells that
would reduce overall demand on the aquifer.
Either course of action has important agricultural production and social implications; therefore, targeted well retirement programs must
be viewed from the perspective of interregional
equity.
Water savings and efficiency measures
through government cost-share programs (e.g.,
Uso Eficiente del Agua y la Energı́a Eléctrica [Efficient Water and Electrical Energy Use]) have
been implemented in Mexico; however, the water saved is very often used to extend the area
irrigated with little change in the amount of water extracted from the aquifer. The appropriate
policy response would be to pursue efficiency
with conservation of the water saved, for example, through caps on planted area.
In Mexico, regulatory approaches to groundwater management have been in place—and
have been largely unsuccessful in addressing groundwater depletion—for more than
fifty years (Wester, Hoogesteger, and Vincent
2009). The current well concessioning and
licensing drive is important; now that this
process has largely been completed, users and
regulators (whether government agencies or
farmers’ self-regulatory bodies) have the information required to formulate regionalized
plans to address aquifer overdraft that account for, among other variables, agricultural
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CHRISTOPHER A. SCOTT is an Assistant Professor in the School of Geography and Development and Assistant Research Professor at the
Udall Center for Studies in Public Policy at the
University of Arizona, Tucson, AZ 85721. E-mail:
cascott@email.arizona.edu. His research interests include water management and policy, climate and
water variability, urban water demand, water reuse,
the energy–water nexus, and groundwater in the
Southwest United States, Mexico, and South Asia.
SANDY DALL’ERBA is an Assistant Professor in
the School of Geography and Development at the
University of Arizona, Tucson, AZ 85721. E-mail:
dallerba@email.arizona.edu. His research interests
include economic growth, economic geography, regional and local development, and public policy with
special emphasis on the European Union.
ROLANDO DÍAZ CARAVANTES is a ProfessorInvestigator at the Universidad Autónoma de Ciudad
Juárez, Oyameles #3016, Colonia FOVISSSTE, C.
P. 31560, Ciudad Cuauhtémoc, Chihuahua, Mexico.
E-mail: diazrol@gmail.com. His research interests
include human–environment interactions, water
management and policy, and spatial analysis with emphasis on Mexico.