VULNERABILITY INDICATORS FOR UNITED STATES-MEXICO
TRANSBOUNDARY WATERSHEDS
PROJECT NUMBER: W-03-18
RICHARD D. WRIGHT, SAN DIEGO STATE UNIVERSITY
JOSE LUIS CASTRO, EL COLEGIO DE LA FRONTERA NORTE
ALFREDO GRANADOS OLIVAS, UNIVERSIDAD AUTÓNOMA DE CUIDAD JUÁREZ
NARRATIVE SUMMARY
There is a need for indicators to help quantify the degree of sustainability of United States-Mexican
transboundary watersheds with respect to their environmental characteristics. Although the Tijuana
River Watershed (TRW) is our primary test bed for indicator development, we cooperated closely
with colleagues from New Mexico State University who conducted similar research in the Paso del
Norte section of the Rio Grande/Rio Bravo Watershed. The TRW team also included researchers
from El Colegio de la Frontera Norte, Tijuana, and the Universidad Autónoma de Cuidad Juárez.
The project was accomplished in several phases beginning with a review and assessment of the
literature on watershed vulnerability indicators. This was followed by the identification of experts
and a two-day meeting of those experts who developed sets of indicator selection criteria and
watershed vulnerability indicators. This workshop was held on October 23-24, 2003 at New Mexico
State University under the leadership of Drs. Christopher Brown and Brian Hurd. The indicators
developed by the experts panel were then evaluated in terms of their applicability to the Tijuana
River Watershed by the research team at San Diego State University and El Colegio de la Frontera
Norte. In evaluating possible indicators particular attention was given to data availability, especially
that concerning water quantity, water quality, and water supply. Tests were conducted with a small
set of vulnerability indicators in order to better understand the pros and cons of indicator
development for cross-border drainage basins.
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VULNERABILITY INDICATORS FOR UNITED STATES-MEXICO
TRANSBOUNDARY WATERSHEDS
PROJECT NUMBER: W-03-18
RICHARD D. WRIGHT, SAN DIEGO STATE UNIVERSITY
JOSE LUIS CASTRO, EL COLEGIO DE LA FRONTERA NORTE
ALFREDO GRANADOS OLIVAS, UNIVERSIDAD AUTÓNOMA DE CUIDAD JUAREZ
INTRODUCTION
The transboundary watersheds of the United States-Mexico border are being impacted by significant,
and in some cases, overwhelming stresses (GNEB 2000; USEPA 2002). A prime example is the
Tijuana River Watershed (TRW). This largely semi-arid drainage basin is the westernmost of a set of
transboundary watersheds that help to define the character of the border region (Wright, Garfield,
and Winckell 1995). The watershed comprises an area of about 1,750 square miles that lies astride
the California-Baja California border, approximately one-third in the United States and two-thirds in
Mexico. It is located in the San Diego-Tijuana region which has received the greatest impact from
NAFTA-related growth in the form of increasing development in the industrial-economic zone along
the border. This region, which has a population of over four million, is one of the most rapidly
growing sections of the border. This growth and associated land use changes are responsible for
numerous problems in the watershed, including a decline in the quality of surface and ground water,
increased runoff from winter storms with accelerated erosion and flooding, alteration of natural
habitats, reduction in the amount of green areas, and an increase in the number of plant and animal
species that are threatened or endangered.
With this project researchers attempt to create and evaluate a set of indicators of the vulnerability of
transborder watersheds with respect to their hydrological characteristics. Although the TRW served
as the primary testbed, investigators coordinated closely with colleagues from New Mexico State
University (NMSU) who conducted similar research in the Paso del Norte (PDN) region of the Rio
Grande/Rio Bravo Watershed. The project employed a variable spatial resolution that allowed
characterization of the watershed as a whole and examine differences between the United States and
Mexican sections of the watershed and variations among the 12 sub-basins that comprise the TRW.
The involvement of Mexican researchers helped to insure that the results reflect a binational
perspective with respect to data requirements and availability. Identification of data gaps needed for
improved monitoring of watershed vulnerability was conducted along with an evaluation of the most
effective geospatial technologies for meeting data needs (Wright and Dow 2003).
RESEARCH OBJECTIVES
A watershed vulnerability indicator is a measure of the condition or health of a drainage basin
(USEPA 1997). Indicators evolve from the analysis of raw data using a geographic information
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systems (GIS). They can be aggregated with other measures to create high-level indices that form the
apex of the information pyramid (See Figure 1). Conditions are of two basic types: Those that
represent the state of the system relative to a desired state and those that measure changes in the state
of the system (Walker and Reuter 1996). An example of the former is the percent of impermeable
surface in a watershed, whereas the percent of temporal change in the area of impermeable surface is
an example of the latter.
A watershed vulnerability indicator is a variable that provides information about the conditions of a
watershed and its susceptibility to deterioration. The criteria for selecting environmental indictors
fall into three categories: technical, practical, and programmatic (Intergovernmental Task Force on
Monitoring Water Quality 1995). Technical considerations include measurability, sensitivity,
resolution, validity and accuracy, reproducibility, representiveness, scope, and data comparability.
Practical considerations are cost and difficulty factors. Programmatic considerations includes
relevance, program coverage, and understandability. For the sake of simplicity, and in order not to
get bogged down by working with a large number of sometimes conflicting criteria, researchers
employed a reduced set of environmental indicators for the study of the Tijuana River Watershed
(TRW). This reduced set, which derives from the Phoenix study, “What Matters in Greater Phoenix”
(Morrison Institute for Public Policy 1999), includes the following criteria:
 Is the indicator measurable?
 Are the data available at regularly measured intervals?
 Is the indicator relevant?
 Is the indicator understandable?
 Will the indicator respond to changes in policy and law?
In addition to the above, investigators added the following question that takes into account the
international character of the watershed: Are the data spatially comparable across the U.S.-Mexican
border?
The principal purpose of this project was to examine the degree to which environmental
vulnerability can be measured at different scales and resolution for the TRW. To accomplish this,
researchers endeavored to apply indicators for the TRW as a whole; the United States versus the
Mexican sections of the basin; urban vs. rural sections; and for the 12 sub-basins of the watershed. A
secondary purpose was to evaluate the suitability of different geospatial technologies for identifying
and monitoring vulnerability indicators at different scales, resolution and locations.
RESEARCH METHODOLOGY/APPROACHES
Vulnerability Indicators Selection Process
An important outcome of the Expert Panel Workshop held at New Mexico State on October 23-242003 was the development of a vulnerability indicators chart focusing on U.S.-Mexico border
watersheds (See Table 1). Also, as a result of a presentation by William Kepner on the Automated
Geospatial Watershed Assessment (AGWA) tool at the expert workshop, it was decided to hold a
training workshop on the characteristics and applications of AGWA software for assessing the
vulnerability of cross-border watersheds in the U.S.-Mexico border region. This workshop was
conducted at San Diego State University on June 21-22, 2004 by Dr. Darius Semmens, U.S. EPA
National Exposure Research Laboratory, Las Vegas. Twelve individuals from San Diego State
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University, El Colegio de la Frontera Norte (COLEF) and Universidad Autónoma de Cuidad Juárez
participated in the workshop. With the recommendations of the aforementioned expert panel in
mind, the project researchers at SDSU and COLEF developed an initial set of vulnerability sources
and related indicators for the TRW (See Table 2). For each indicator investigators assessed data
availability at four different levels: the TRW as a whole, the U.S. and Mexican sections of the TRW,
the 12 sub-basins of the TRW, and the urban areas of the watershed (Tijuana, Tecate, and San
Ysidro). From this table researchers selected a set of four watershed vulnerability topics for more
detailed analysis. They are described in the following section.
Vulnerability Topics
Of the many water-related problems in the Tijuana River Watershed, those concerned with flooding,
water pollution, erosion/sedimentation, and potable water supply and population expansion are the
most pressing.
While many areas of the watershed are subject to temporary inundation due to intense precipitation
events, the likelihood of flooding has increased as a result of several factors. They are urbanization,
stream channelization, vegetation modification/removal, and sand mining. The aerial expansion of
Tijuana, Tecate, and San Ysidro, in particular, has increased the percentage of impermeable surface,
especially in the lower section of the watershed. Stream channelization in the City of Tijuana has
eliminated severe flooding along the main stream and encouraged economic development in the
Zona Rio section. However, channelization has had negative effects such as decreased groundwater
recharge and increased flooding downstream in the U.S. section of the lower valley. Vegetation
removal, particularly on steep hillsides, has led to more rapid runoff. Sand mining in the Valle las
Palmas and other more accessible stream valleys has decreased the groundwater storage capacity of
the shallow aquifers and allowed surface water to flow downstream more quickly. The result of the
above is that after a storm event, streams are characterized by higher volume peak discharge,
increased total runoff volume, steeper recession of discharge, and lower base flow. Flood
vulnerability indicators include precipitation (quantity and frequency), stream flow, hypsography,
impervious surface area, quality and quantity of vegetation cover, and extent of material extraction.
The downstream effects of point and non-point source pollution in the TRW are severe. Beaches
near the mouth of the river are among the most polluted water in California (Gersberg et al. 2000).
Factors leading to polluted water in the TRW are runoff from different land uses, industrial/toxic
discharges, inadequate sewage treatment, and poor natural filtering of water. Storm water runoff
from industrial, agricultural, and residential land uses is a major contributor to water pollution in the
lower watershed. Unregulated industrial discharges contribute to poor water quality as well.
Although a program of industrial pre-treatment has been instituted in Tijuana, much needs to be
done to expand it to the entire urban area. Many areas of Tijuana and Tecate are not connected to
sewage treatment facilities and/or are subject to sewage overflows during precipitation events.
Finally, pollution of water from point and non-point sources in the TRW is exacerbated by poor
natural filtering of water owing to stream channelization and sand mining. Water quality model
inputs include many variables, including precipitation, stream flow, hypsography, land use,
impervious surfaces, number and severity of spills, percent of area not served by a municipal sewage
system, quality and quantity of vegetation cover, extent of riparian vegetation, extent of material
extraction, and industrial pre-treatment requirements.
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Intense precipitation events have contributed to severe erosion of moderate to steeply sloping terrain
and the resultant deposition of sediment on relatively flat areas. Sediment deposition has been
extremely heavy in the Tijuana River National Estuarine Research Reserve, resulting in the loss of as
much as eight acres of coastal marsh in one recent storm. Erosion has been especially severe on the
steeply sloping sides of the mesas in Tijuana. These slopes, comprised of loosely consolidated
sedimentary rocks, have become more unstable as a result of vegetation removal owing to urban
development on steep slopes. Grading in the vicinity of the U.S.-Mexican border fence in order to
accommodate the mandate of the U.S. Border Patrol for border security has exacerbated erosion in
the lower valley on the U.S. side of the border. Wildfires, such as those that occurred in different
parts of the watershed in the fall of 2003, also contribute to erosion and sedimentation through the
destruction of vegetation cover. Possible erosion/sedimentation vulnerability indicators considered in
this project include precipitation amount and intensity, slope steepness, vegetation cover, soil
characteristics, surface impermeability, and grading in the vicinity of the border fence. Relevant
models investigated are the Revised Universal Soil Loss Equation (USDA 1997), which estimates
erosion in tons per acre per year based on the physical characteristics of the environment, and the
Erosion Hazard Rating System (CDPR 1991), which rates the erosive potential of slopes based on
physical characteristics of the environment.
The lower part of the TRW, wherein more than 95 percent of its population resides, is a water deficit
area. Tijuana and Tecate rely on imported Colorado River water for more than 95 percent of their
supply, whereas the comparable figure for the urban areas of San Diego County is 85 percent or
more, depending upon precipitation and the replenishment of local reservoirs. Upstream of the urban
areas, residents are totally dependent on groundwater for household and agricultural uses. Rapid
population growth in Tijuana and Tecate is placing increasing stress on available supplies. Local
supplies, already limited in quantity, are being degraded as a result of pollution of surface water and
groundwater aquifers. Additionally, a dilapidated water delivery infrastructure means that much
water is lost due to leaks in the system. Another consequence of rapid population growth is that
water agencies are unable to expand the infrastructure fast enough to meet industrial and residential
demand. In reviewing indicators of potable water supply vulnerability those that seemed most
promising are rate of population growth, urban area and population without access to piped water,
reliance on imported water, contamination levels in groundwater, contamination levels in surface
water, and policies regarding water use.
Impervious Surface Modeling
In recent years, impervious surfaces have become recognized as a key factor in watershed planning
(Brabec et al. 2002). In many instances, impervious surfaces can act as an indicator of watershed
health, and may be used to estimate current water quality conditions. When less than 10% of a
watershed is considered to be impervious, the impacts on water quality are slight, and water quality
remains protected. Imperviousness between 10% and 25%, generally indicates that water quality is
impacted to a moderate degree. As the imperviousness of a watershed increases to 25% or greater,
water quality is considered impacted (Schueler 1994).
Early efforts to calculate the imperviousness of different land uses relied primarily on four methods.
These included: identifying impervious areas using aerial photography and a planimeter to measure
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each area; using grid overlays with aerial photos to find the number of intersections that overlaid
different land uses or impervious features; using supervised classification of remotely sensed
imagery; and equating the percentage of urbanization in a region with the percentage of surface
imperviousness (Brabec et al. 2002). More recently, research has focused on using new technologies
to accurately determine impervious surfaces. According to Yang (2003), considerable work has been
done in determining impervious surfaces using multiple regression (Forster 1980; Ridd 1995),
spectral un-mixing (Ji and Jensen 1999; Ward et al. 2000), sub-pixel impervious surface mapping
using artificial neural network and ERDAS Imagine sub-pixel classifier (Wang et al. 2000; Flanagan
and Civco 2001), classification trees (Smith et al. 2003), and the integration of remote sensing with
GIS (Prisloe et al. 2001).
A method recommended by Civco and Hurd (2004) uses percent impervious surface coefficients as a
function of land cover type to estimate imperviousness. Another option is to perform sub-pixel
percent impervious surface modeling using Landsat TM and ETM+ data. This method uses ERDAS
Imagine Sub-Pixel Classifier and performs a supervised classification. Essentially, it identifies and
removes unwanted spectral materials that contribute to the background of the pixels, and then
compares the remaining spectrum to the signature of the material of interest. An alternative method
that extracts sub-pixel imperviousness using a regression tree algorithm, Landsat-7 ETM+, and two
high spatial resolution images has recently been developed as a means of providing higher accuracy
in impervious surface measurement. This method involves the selection of an algorithm and training
data for each study area in order to represent the spectral and spatial variability of impervious
surfaces. A predictive variable is selected and the regression tree modeling is initiated. A final
regression tree model is selected and the results are mapped (Yang 2003).
Another resource and possible method for determining impervious surfaces is the Impervious
Surface Analysis Tool (ISAT). Developed by the National Oceanic and Atmospheric Administration
(NOAA) Coastal Services Center and the University of Connecticut’s Nonpoint Education for
Municipal Officials (NEMO), ISAT is a GIS software extension that uses land cover to estimate
surface imperviousness. This extension was developed for use in ArcView and uses basins,
municipal boundaries, open space lands, and satellite-derived land use and land cover (LULC). The
derived LULC is than used to determine specified impervious surface coefficients. These
coefficients represent the percentage of imperviousness for a land cover class and, although
originally developed for Connecticut, can be applied and modified for use in other geographic
regions. The model has the capability to estimate the overall imperviousness of a watershed as well
as produce watershed maps using these surface coefficients (Prisloe et al. 2000). Chabaeva et al.
(2004) noted that although there are many different techniques that can be used to measure or
estimate surface imperviousness, most are fairly time consuming as well as costly. For example,
although heads up digitizing of remotely sensed images, sub-pixel classification, artificial neural
networks, and classification and regression trees are more accurate than other methods, they require
moderate to high resolution images as well as a high degree of expertise in terms of processing and
analysis.
In this research we employed the Impervious Surface Analysis Tool (ISAT), a GIS extension
developed for ArcView. Prior to running ISAT the land use and vegetation layer were merged to
create a land cover data set. The original TRW vegetation and land use classes were reclassified to
conform to the 18 land use classes provided in ISAT. Default impervious surface coefficients (low,
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medium, high) were then assigned to these new classes. The coefficients were originally developed
based on impervious surface data for the State of Connecticut, but can be modified for use in other
geographic regions.
The ISAT model was run using the following inputs:
 Analysis Theme: Watershed sub-basins (polygon shapefile or coverage). This defines the
areas over which impervious surface estimates will be calculated
 Land Cover Grid: A combination of the land use and vegetation layer (in grid format)
 Population Density Theme: Population density for each of the sub-basins. The
imperviousness of a single land cover class is affected by population density. Depending
upon the population density (< 250 = low, 250 – 2,500 = medium, and > 2,500 = high),
different coefficients will be applied
Impervious surface coefficients are applied to determine the total as well as the percentage of
impervious surface area within specified polygons. After running the model, an imperviousness layer
was generated which listed by sub-basin the percentage of imperviousness per hectare (See Table 3).
Several assumptions were made in running ISAT:
 Stream quality is a function of the percentage of impervious surface area
 Each watershed operates independently of upstream watersheds
 Watershed characteristics such as soils, topography, and stream density are not considered
 No distinction is made between total and effective impervious area
 The spatial distribution of impervious surface and its proximity to drainage systems is
ignored
 ISAT uses Spatial Analyst to overlay polygon data (watershed boundaries) on land cover
data to calculate the area of each land cover category within each polygon
Avenue scripts are then used to apply impervious surface coefficients (ISi) to calculate the
impervious area percentage for each polygon (ISW), by using the following equation:
n
ISW = ∑ Areai * ISi
_i = 1 _________________
Total Area
Water Quality Modeling
Using ISAT, the potential impact to water quality within a watershed is based upon the estimated
percentage of surface imperviousness. Areas within a watershed that have <10% impervious surfaces
are considered protected; areas with 10% to 25% impervious surfaces are considered degraded; and
those areas that have 25% and greater imperviousness are impacted.
Although ISAT uses percent imperviousness as a measure of water quality, other studies have relied
on storm water runoff to measure water quality within a watershed. For example, in a study by
Englert (1997), impacts to water quality were associated with storm events, where water pollution
was considered to be a result of waste water discharge and storm water runoff. When determining
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storm runoff quantity, the percent imperviousness of land cover is the single most important factor.
In addition, nonpoint source pollution such as organic chemicals, metals, nutrients, and pathogens
are also commonly associated with storm water runoff.
In the Englert study, land use classifications were developed for each of the 12 sub-basins. The
percent of impervious surfaces was then determined for each of these land use types in order to
provide an estimate of runoff coefficients. These coefficients are useful since they are a measure of a
watershed's response to rainfall events. The average monthly rainfall was used to indicate runoff;
only rainfall events with a minimum of 0.10 inches were used (these are considered large enough to
generate significant runoff volumes). Storm runoff was then calculated based on the predicted
rainfall for each land use classification. The appropriate runoff coefficients were then applied in
order to calculate storm runoff. In addition to rainfall and runoff, pollutant loadings and
concentrations (non-point source) were determined. These factors were used as water quality
parameters for the study.
Erosion/Sedimentation
As mentioned previously, erosion and associated sedimentation are serious problems in the TRW. It
was determined that this indicator could be quantified through the use of AGWA (Automated
Geospatial Watershed Assessment). AGWA, a tool developed by the Environmental Protection
Agency and the Department of Agriculture, incorporates two watershed models: KINEROS for
small (<=100 km2) watersheds and SWAT for large (>100 km2). Since the Tijuana River Watershed
is considered a large watershed, the SWAT (Soil and Water Assessment Tool) model is most
appropriate for implementation. The outputs for this model include precipitation, evapotranspiration
(ET), percolation, surface runoff, transmission loss, water yield, and sediment yield. These data can
be used to evaluate various management scenarios that involve runoff and erosion.
One of the major difficulties for implementing models in a transboundary watershed is identifying
comparable datasets that can be used as input parameters (Wright and Winckell 1998; Wright et al.
2000). The AGWA model requires the following inputs: digital elevation model (DEM), land
use/land cover, soils (STATSGO), streams, precipitation gauges, and gauging stations. In case of the
Tijuana River Watershed, the major limitation is the lack of a continuous STATSGO soils dataset.
On the U.S. side of the border, soils data are organized according to the STATSGO system, while
soils data on the Mexican side are classed according to the FAO system. In order to run the model,
an improvised soil layer was used. However, this did not produce accurate results. Another weakness
of using this model in the Tijuana River Watershed results from the lack of precipitation gauges
throughout the watershed. Since there are so few gauges, the precipitation surface is highly
interpolated which decreases the accuracy of the final outputs.
Water Supply
The Tijuana River Watershed has a dynamic urban population, mostly concentrated on the Mexican
part of its territory. This population has grown steadily at a 5% annual rate for the past 30 years and
is clearly one of the major threats for the stability of the watershed. A measure that can provide
insight on the vulnerability of the TRW is the volume of water available for each inhabitant.
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The data available for the estimation of this indicator present differences when comparing the
Mexican and U.S. portions of the watershed. In the former case, the information on water supply for
the TRW is comparatively dispersed. In Baja California the agencies that manage the water at the
local level, the Comisiones Estatales de Servicios Públicos (CESPs; in English the State
Commissions of Public Services), carry their own statistics on water supply, including both surface
and underground sources, as well as local and imported ones. Two other state agencies, the
Comisión Estatal de Agua del Estado (CEA; State Water Commission) and the Comisión de
Servicios de Agua del Estado (COSAE; State Commission of Water Services), provide information
on the annual volumes transported by the Colorado River-Tijuana Aqueduct to the Tecate and
Tijuana municipalities, as well as the underground sources inside the TRW. Finally, the Comisión
Nacional del Agua (CAN; National Water Commission), is the main water agency at the federal
level and provides information on annual surface and underground yields. Besides the dispersed
sources, the data from these varied sources are not complete for comparison on a yearly basis.
In order to assemble a comparable time series data set (Table 4), two considerations were made. The
first was to eliminate the year 2004 from the data set. The second was the assumption of constant
volumes of local underground water (the data from CNA identified the three aquifers in the TRW –
Tijuana, Tecate, and Las Palmas – as in equilibrium).
A large part of the U.S. portion of the TRW is not urbanized. The data on water availability and
population are difficult to gather for this area. The urban areas represent a smaller part of the
watershed, and their water services are provided by two of the San Diego County Water Authority‘s
(SDCWA) member agencies: The City of San Diego and the Otay Water District. In order to
estimate comparable indicators with the Mexican portion, total water supplied and population served
were used for each agency for the years reported by SDCWA. The results are shown in Table 5.
Table 5 compares the three indicators estimated for the 1999-2003 period. As observed, the areas in
the U.S. portion of the TRW with regular public water service, present higher per capita volumes
than those in the Mexican side. Even if one uses urban population to calculate the indicator in the
second case (Table 4), the results do not vary notably. Another noticeable difference found between
the two sides of the TRW is the growing availability of water on the U.S. communities. One
conclusion here is that while the agencies serving the Mexican portion have kept the supply of water
constant, they will certainly be forced to consider new alternatives as a result of population growth.
Population Density
Population density and change in density are useful indicators of the pressure placed on the
environmental resources of a watershed. In the TRW, the highest densities are found in San Ysidro,
Tijuana, and Tecate. Elsewhere, except for a few small population clusters in Nueva Colonia Hindu,
Valle de las Palmas, Carmen Serdán, Vallecitos, Santa Verónica, Nejí, El Hongo, Potrero, Campo,
and Pine Valley, population is highly dispersed. Density changes are greatest in the outskirts of
Tijuana and Tecate where new homes are spreading rapidly over the rural landscape. Rosarito,
Tijuana and Tecate – with Rosarito located outside of the watershed – are expanding toward each
other and will eventually form a contiguous metropolis. Tijuana is also expanding to the southeast
and is likely to connect with the community of Valle de las Palmas in the next decade.
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Geospatial Technologies and Data Sources
Geospatial technologies offer opportunities for identifying and monitoring watershed conditions in
the U.S.-Mexican border region. This section summarizes the characteristics of geospatial
technologies and their use for monitoring watershed conditions (Stow et al. 1998).
A large suite of imagery types is available for monitoring watershed health indicators. Imagery
varies in its spatial, spectral-radiometric, and temporal dimensions. When determining which type of
imagery to utilize, there are some basic choices and trade-offs that must be made, including: aircraft
vs. satellite imagery; analog vs. direct digital imagery; panchromatic vs. multispectral; spatial
resolution vs. geographic extent; temporal resolution; and cost.
Digital orthophotos are aerial photographs that are terrain-corrected and geo-referenced.
Orthophotos are an important source of data for indicators requiring visual interpretation of highresolution imagery.
Global Positioning Systems (GPS) facilitate the determination of locations in two- and threedimensional space. With GPS the user is able to determine the location of monitoring data and
sensing instruments.
A digital elevation model is a set of elevation values for a given geographical area. Digital elevation
models are important for producing terrain-corrected imagery and for generating a variety of
products such as watershed and stream boundaries. Additionally, they may be components of some
environmental health indicators such as the percentage of impervious surface in the drainage basin.
A geographic information system (GIS) is a computer-based technology that allows the user to
convert geospatial data into information that can form the basis for decision-making. This
technology allows indicators of environmental health and vulnerability to be studied within a spatial
context.
Cartographic visualization allows users to interpret, validate, and explore spatial data. Being able to
graphically portray environmental health indicators allows environmental resource managers and
researchers to effectively communicate information to others.
PROBLEMS/ ISSUES ENCOUNTERED
Investigators encountered a number of problems and issues in carrying out this project. The first
concerned the necessity of identifying important environmental issues in different parts of the
watershed. Fortunately, a project funded by the State of California to develop a binational vision for
the TRW was carried out concurrently with this SCERP vulnerability indicators study. Stakeholders
interviewed in the binational vision project identified a set of priority issues in different parts of the
watershed. It was convenient to employ these priorities in the environmental indicators study. A
second issue concerned the difficulty of finding indicators that meet the selection criteria. Of the six
criteria previously discussed, those most problematic were:
 Is the indicator measurable?
 Are the data available at regularly measured intervals, and
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
Are the data spatially comparable across the U.S.-Mexican border?
The final criterion is especially critical given that a requirement of this study is the integration of
geospatial data for transboundary watersheds. Another issue of concern was the difficulty of settling
on a small number of relevant indicators to best characterize the watershed’s environmental
vulnerability. More than a hundred indicators have been identified in the literature. Narrowing the
list to those that are most significant involves a selection process that represents a balance between
indicators that are concept driven and those that are data driven. The final, and most difficult
problem encountered in this project was the paucity of data for desired indicators. Data gaps were of
several types. In some instances comparable data were not available for the U.S. and Mexican
portions of the watershed. In other instances, there was a lack of data comparability between the
urban and rural portions and the upstream and downstream sections. Finally, for all but a small
number of measures, adequate data were not available at the sub-basin level for the twelve principal
hydrologic subdivisions of the TRW.
RESEARCH FINDINGS
In conjunction with this research investigators experimented with indicators relevant to flooding,
water quality, erosion/sedimentation, and water supply.
Flooding
As a partial indicator of flooding vulnerability an impervious surface layer was generated using the
ISAT model. Table 3 shows that the Rio Tijuana sub-basin, with an imperviousness of 39.18%, is
the only area of the 12 drainage basins that is severely impacted.
Water Quality
In addition to using ISAT to measure impermeability as a partial indicator of water quality,
researchers compared the output from ISAT with that obtained by Englert in his storm water runoff
study. The result of his study indicate that the sub-basins of Rio Tijuana and lower Cottonwood have
the highest runoff percentage (11%), followed closely behind by Pine Valley and Upper Cottonwood
(10%). The largest pollutant loadings and concentrations came from Rio Tijuana, which incidentally
is also one of the smallest sub-basins. In addition, the border sub-basins of Upper Cottonwood and
Pine Valley had the next highest pollutant levels. The results of the two studies are roughly
comparable.
Erosion/Sedimentation
Our exploration on the use of AGWA for measuring transboundary watershed vulnerability
indicators was only partly successful. A recent beta-version of AGWA (1.42 Beta) was released that
allowed for FAO soils to be used as an input parameter; however, bugs within the software kept the
model from running. After communicating with AGWA experts at the EPA, investigators made
some progress, but not enough to actually produce meaningful output. However, work is being done
on a new version of the AGWA tool, AGWA2, which may provide a more stable transboundary
modeling environment. Project researchers plan to employ AGWA in the future, but more
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calibration experimentation will be required before it can be applied successfully in the Tijuana
River Watershed.
Water Supply
Tables 4 and 5 provide information to create an indicator on percentage of imported water in the
TRW. Table 7 presents the corresponding figures. As this table shows, the TRW is highly dependent
on imported water on both sides of the border. On the Mexican side, the data in Table 4 show some
low figures of imported water during the first half of the 1990 decade, reflecting the effects of
unusually large amounts of precipitation within the TRW during those years. However, on the
whole, the Mexican portion of the watershed relies more on imported water for its needs, with the
Colorado River water being the basic source. Since local sources are not reliable, dependence on the
Colorado River water will increase. The varying implications of this situation reinforce the need for
water agencies in this part of the TRW to emphasize their search for other alternatives beyond the
Colorado River to meet their future requirements.
The dependency indicator for the U.S. portion of the TRW also demonstrates high figures for the
agencies in charge (Table 7). While the City of San Diego shows comparable figures to those of the
Mexican portion, Otay Water District depends almost solely on imported water for its water uses. As
critical as this condition may be, a major difference is that the supply for the U.S. water districts is
guaranteed for at least the next 50 years through the agreements between SDCWA and the
Metropolitan Water District (MWD), as well as the Imperial Irrigation District (IID).
Population Density
Increases in population density and urban expansion have led to environmental degradation, as
represented by loss of natural vegetation, and is a problem in many parts of the watershed. The loss
of vegetation results in fragmentation of habitat or the process of subdividing a continuous habitat
into smaller, disconnected patches. Fragmentation, in turn, leads to a decrease in biological diversity.
Changes in land use/land cover, particularly the conversion of natural cover to agricultural and urban
uses, are seen throughout the watershed, but especially in the rapidly urbanizing Tecate-Tijuana
section.
Geospatial Technologies
Geospatial technologies can be employed to provide timely, relevant, and reliable data that are
comparable from one side of the border to the other. Many indicators cannot be identified and
measured. However, those that might be identified through the use of geospatial technologies have
not been fully utilized largely because of the high cost of imagery, software, and hardware and
insufficient training in their use.
CONCLUSIONS
Project investigators reviewed a large number of watershed vulnerability indicators and their
possible relevance to the measurement and monitoring of environmental conditions in the Tijuana
River Watershed Indicators. Flooding, water quality, erosion/sedimentation, and water supply were
12
considered to be factors of major concern in the watershed. Indicators expressive of these factors are
surface impermeability, potable water consumption, and population increase. Significant spatial
variations in quality and availability of data greatly limit the number of useful indicators. Geospatial
technologies used individually, in combination, or in combination with enumerated data and data
from in-site sensors and networks can provide cost-effective data in support of transborder
watershed health indicators. The Automated Geospatial Watershed Assessment tool has potential
utility for estimating erosion/sedimentation indicators.
RECOMMENDATIONS FOR FURTHER RESEARCH
Indicator development is a promising approach for identifying and monitoring environmental
conditions in transboundary watersheds in the U.S.-Mexican border region. However, to realize this
potential, it is necessary that improvements be made in the quality and coverage of geospatial data.
This will require additional research to determine the transboundary environmental health indicators
for which geospatial technologies are most capable of being employed to generate relevant and
timely indicator data. Additionally, exploration in the use of AGWA and other software tools for
estimating watershed indicators relating to runoff and erosion would be beneficial.
RESEARCH BENEFITS
This project is an initial exploration of techniques for developing watershed vulnerability indicators
for the United States-Mexico border region. It should assist in (a) prioritizing transborder watersheds
according to their environmental deterioration and need of rehabilitation; (b) facilitating binational
approaches in addressing water quality problems in shared water basins; (c) identifying watersheds
that require improved water quality monitoring; (d) providing guidance in the selection of imagery
and other geospatial technologies for identifying and monitoring watershed vulnerability; and (e)
providing the basis for the development, implementation, and evaluation of policies for improving
water resource conditions.
ACKNOWLEDGEMENTS
This work was sponsored by the Southwest Consortium for Environmental Research and Policy
(SCERP) through a cooperative agreement with the U.S. Environmental Protection Agency. Contact
SCERP for further information through www.scerp.org and scerp@mail.sdsu.edu.
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Brabec, E., S. Schulte, and P. Richards. 2002. “Impervious surfaces and water quality: a review of
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499-514.
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Chabaeva, A., D. Civco, and S. Prisloe. 2004. “Development of a population density and land use
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Indicators: A Systematic Approach to Measuring and Reporting on Environmental Policy
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Prisloe S., Y. Lei, and J. Hurd. 2001. “Interactive GIS-Based Impervious Surface Model.” ASPRS
2001 Annual Convention, St. Louis, MO.
Schueler T. 1994. “The Importance of Imperviousness.” Watershed Protection Techniques 1(3): 100111.
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Management. 62 (4): 429-442.
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the Potential of Geo-Spatial Technologies for Monitoring Shrubland Habitats in Southern
California.” San Diego, CA: San Diego State University. Unpublished.
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United States Department of Agriculture (USDA). 1997. “Predicting Soil Erosion by Water: A
Guide to Conservation Planning with the Revised Universal Soil Loss Equation.” Washington, DC:
Agricultural Research Service, USDA.
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Environmental Indicators.” Washington. DC: USEPA.
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Indicators.” Washington, DC: Office of Water, USEPA.
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Office of Water, USEPA.
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Australia: CSIRO Publishing.
Wright, R., N. Garfield, and A. Winckell. 1995. “Binational GIS Database Development for the
Tijuana River Watershed.” Proceedings of URISA ’95, July 1995, San Antonio, TX.
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Boundaries.” Pp. 71-93 in GIS Solutions in Natural Resource Management, S. Morain, ed. Santa Fe,
NM: OnWord Press.
Wright, R., K. Conway, D. McArthur, and C. Tague, 2000. “Integrating GIS and Flood Hazard and
Risk Modeling in a Cross-Border Data Poor Environment,” Proceedings of the Fourth International
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Wright, R. and D. Dow. 2003. “The Potential of Geospatial Technologies for Monitoring
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Yang, L., C. Huang, C. Homer, B. Wylie, and M. Coan. 2003. “An Approach for Mapping LargeArea Impervious Surface: Synergistic Use of Landsat-7 ETM+ and High Spatial Resolution
Imagery.” Canadian Journal of Remote Sensing 29(2): 230-240.
APPENDIX
Report figures and tables
15
16
Table 1. Vulnerability Indicators Chart developed from October 23-24, 2003, Expert’s Panel Workshop, Revised 15 February, 2004
(continues on next four pages)
Vulnerability Source
Population growth
Population water stress
Consumptive use
Ground water overdraft
Degree of over-allocation
Indicator
Data Source
Related to Human Population, Consumption, and Land Use Practices
Demographics/Change in growth, including
INEGI-Mexico
fertility rates and a region’s demographic
U.S. Census
structure.
Deficit of potable water supply (Vogel)
(1+g/1+r)
g= population growth
r=supply growth
(must include ground water
storage, and surface water
interaction/input)
Per capita water use + allocation/acre
Municipal utilities
consumptive use
Irrigation districts (EBID, EP#1,
Distrito Riego 009)
satellite imagery (Mexico)
current land use maps
Change in aquifer storage
Change in depth to water over
(rate of change)
time. Well attribute data (WRRI,
USGS, and NMOSE). Attempt to
attain volume estimates
(USGS,WRRI, UTEP, Texas
A&M, UACJ). CNA and JMAS
can provide data for Mexican
border cities.
Amount of groundwater pumped to meet
Rio Grande Compact, NMOSE,
demand, both agriculture and M&I
Water Rights, EBID, EP#1,
EPWU, and CONAGUA
Vulnerability Source
Economic sensitivity to water
availability
Indicator
Water use by sector and revenue generated per
direct economic use
Data Source
Las Cruces—MVEDA,
LRGWUO, City of Las Cruces. El
Paso—Ari Michelsen. Juarez—
Lucinda Vargas, JMAS, and Rene
Franco. Tijuana – CESPTijuana.
Water Quality-Related/Human Health
NAWQUA, NASQUON,
NM Environment Department.
Impairments to water quality
Salinity
DO
17
Comments/Additions
i
Satellite imagery  relative per
capita consumption for municipal
use and per acre use for agriculture
Irrigation data by different crops (at
least trees versus row crops)
Perhaps consider summer and
winter statistical surface. We won’t
have resources for modeling GWSW interaction for this study.
This indicator ignores in-stream
rights.i
Comments/Additions
Threats to public and
environmental health
Specific biological
contaminants
Vulnerability Source
Flood risk
Drought severity
Fecal coliforms
El Paso—TCEQ, EPWU,
IBWC/CILA, and Texas Clean
Rivers Program.
Mexico—
SEMARNAT/PROFEPA, INEGI,
Mexican Universities
Non-point agricultural contaminants, including
CAFO, nutrients, and agricultural chemicals
Land cover, crop type, and
pesticide intensity; EPA data on
feedlot and # of animals
TCEQ, NMED, Dona Ana County,
CESPTijuana, Junta Municipal de
Agua y Saneamiento
Bob Gilliam model at USGS
No widespread systematic testing
currently exists. Data from PAHO
and U.S.-Mexico Border Health
Commission may be helpful.
Problem is linking disease with
water quality
Extent of hook-ups for sewage and potable water
supply
Sewage discharge/river discharge
Nitrogen load
Pathogens - enteroviruses, fecal coliforms, and
cryptosporidium and their impact on morbidity
and mortality
Indicator
Data Source
Natural Events (Although effects are influenced by anthropogenic disturbance)
% of stream class that is channelized
Aerial photos/Digital images
Status of aerial photo project along
border?
Tijuana-San Diego flood control
project w/ COLEF, SDSU, and
others
% of impervious surface in watersheds
Land cover/ satellite imagery and
DEM’s,
Tijuana-San Diego flood control
project w/ COLEF, SDSU, and
others
Population in Floodplain
FEMA, maps of urbanization
# of times in past X years that drought severity
CNA/NOAA /Prism (OSU)
index has exceeded threshold value (rangeland
communities)
Coefficient of variation of streamflow
FBOR, USGS, IBWC, CNA
Ecological Concerns
18
Question remains as to how to link
water quality measures to
environmental health.
Comments/Additions
ii
Reduction in riparian and
aquatic ecosystems extent/composition
Vulnerability Source
Reduction in riparian and
aquatic ecosystems extent/composition
Threat to biodiversity – aquatic,
terrestrial, and migratory
Urbanization
Infrastructure quality
performance
Infrastructure “brittleness”
Series of landscape metrics from field counts,
and remote sensing data
Remote Sensing,
Surveys, SWREGAP,
Research literature, Fort. Bliss,
University research,
SEMARNAT, Mexican State,
Federal, and, NGO data, INE.
Explore potential use of ATtILAiii
to examine spatial variability of
landscape metrics
Diversity Indicators
Changes in # of species at risk
Changes in # of extirpated Species
Research literature, Universities,
NGOs, Federal data (USFWS and
INE), and state agencies
Use of macro-invertebrates—more
diverse.
Indicator
Degree of protected-ness
Data Source
SWREGAP
Comments/Additions
Amt of state/federally protected
lands
Adequate water flows for ecological needs
Binational federal agencies and
NGOs – RGRBBC & WWF.
Quantitative changes in habitats
NA models/GAP data
Series of landscape metrics from field counts,
Remote Sensing,
remote sensing data
surveys, SWREGAP, Fort Bliss,
SEMARNAT, Mexican State,
Federal, and NGO data, INE.
Diversity Indicators
Literature, Universities, Fort Bliss,
Changes in # of species at risk
SEMARNAT, Mexican State,
# of Extirpated Species
Federal, and NGO data, INE.
Extent/Connectivity- Landscape metrics
Land use change
Potential use of ATtILA
Hydrological response- sediment yield, surface
DEM’s- soils cover-NALC-USGS
runoff, percolation, change in land use
(soils –differences between MexUS)-SWAT
NRCS
Issues related to infrastructure and Water delivery
Age of network & condition
Municipal utilities
Transmission or conveyance and billing
Irrigation districts
efficiencies
Agricultural efficiency
Distance to water supply
Sewer and water coverages from
Redundancy of water supply
municipal utilities and possibly
Contingency plan
Census data
19
Imperviousness also tied to
ecological integrity
Explore potential use of AGWA.iv
Vulnerability Source
Infrastructure “brittleness” cont.
Indicator
Adequacy of coverage in colonias in New
Mexico, Chihuahua, and Texas
Lack of adaptive capacity
Per capita consumptive water use in I & M.
Data Source
TCEQ, NMED, Dona Ana and El
Paso County Health Departments,
and JMAS
Municipal utility data
% of total agriculture in permanent crops
(examples are pecans & vineyards).
Consumptive use over total extraction by sector
Institutional potential for transfers and maturity
of water markets
Institutional capability and effectiveness
Presence/absence, effectiveness, and
comprehensiveness of water plan
Financial capacity of water
institutions (# and nature to be
determined)
Conjunctive management of surface and ground
water resources
Bond rating
i
Acreage data from irrigation
districts
Municipal utility data
Irrigation district data
Potential for transfers —ordinal
ranking using institutional research
literature, CNA & PRONAGUA
CNA, JMAS, EPWU, and CLC
Water Utilities
Water plans themselves,
research literature that critically
reviews them, and master plans
and data related to the BECC.
Regional water plans, groundwater
and surface water codes
S+P and Moody’s ratings,
rosters/Scorecards, and possible
BECC data.
Comments/Additions
Transaction costs, import demand
ratio, spending power, legal
flexibility
Performance measures
Recognizing that some issues are not going to show variability at a sub-basin level, they are still important issues and should be included in any analysis of
vulnerability.
ii
H. Passell – magnitude and duration of annual extreme conditions and 90-day means, or magnitude of monthly water conditions, or timing of annual extreme
water conditions, or frequency and duration of high and low pulses, or rate and frequency of water condition changes.
iii
ATtILA is the USEPA GIS-based landscape metric tool discussed by William Kepner that has enjoyed wide use in the San Pedro Basin. The SCERP project
staff is exploring training on this software to support this project.
iv
AGWA is the USEPA GIS-based tool for geo-spatial watershed assessment discussed by William Kepner that has enjoyed wide use in the San Pedro Basin.
The SCERP project staff is exploring training on this software to support this project.
20
Table 2. Data Availability Assessment
Data Availability
Sub-Basin
Vulnerability Source
Indicator
TRW
Human Population
Size of population
Rate of population
growth
Population density
Estimates can be
obtained from U.S.
& Mex. censuses
U.S. & Mex. census
date not available by
sub-basin. Remote
sensing methods
required.
INEGI data available
Population Water Stress
Deficit of potable water
supply (1 + pop.
growth/1 + supply
growth)
Pop. data and surface
water data estimates
OK. Poor data on
ground water
storage. Importation
of water must be
considered
Pop. data and surface
water data OK. Same
data on ground water
storage. Importation of
water must be
considered.
Consumptive Use
Per capital water use
Estimates for U.S.
from SDCWA and
Co. of S.D. Not
certain about
estimate for Mex.
rural areas. CESPT
& CESPTE have
data for Mex. urban
areas.
Pop. data can be
obtained using
remote sensing.
Surface water data
estimates OK. Poor
data on ground water
storage. Importation
of water into some
basins must be
considered.
Estimates for U.S.
from SDCWA and
Co. of S.D. Not
certain about
estimate for Mex.
rural areas. CESPT
& CESPTE have
data for Mex. urban
areas
From CESPT and
CESPTE
To estimate this it could be
hypothesized that total supply
is equal to total consumption
both in CESPT and CESPTE
jurisdictions (total
consumption is the addition
of the volumes from each
source plus the service
looses). Total consumption
per capita is therefore equal to
total consumption divided by
total population.
Groundwater Overdraft
Change in aquifer storage
Poor data on changes
in aquifer storage for
most of watershed.
Poor data on change
in aquifer storage
from most subbasins.
Data available from
CESPT and CESPTE
Data are not reliable. The few
records that might be
available are scattered in
time. These are usually
developed by CNA (which is
rather though when it comes
to disclose its data). We
21
Tijuana/Tecate
Comments from COLEF
team
Data at the locality and
AGEB levels are available.
Estimation of population for
the Mexican part of TRW can
be accomplished by doing
calculations at the polygon
level. It is necessary to define
the time period of analysis.
Supply data from CESPT are
desegregated by source (i.e.
Colorado River Aqueduct,
wells, etc.). So the figure that
interests us is the total. The
same can be assumed from
CESPTE. The only thing is to
make sure that data are for at
least 10 years in the past.
Degree of OverAllocation
Amount of ground water
pumped to meet demand
Poor data on ground
water pumped for
most of watershed.
Poor data on ground
water pumped for
most sub-basins
Data available from
CESPT and CESPTE
Economic Sensitivity to
water availability
Water use by industrial
sector and revenue
generated per use
Data not available
for entire watershed
Data not available
for most sub-basins
Direct data may be
obtainable from CESPT
and CESPTE
Impairments to water
quality
Salinity, do, fecal
coliforms, non-point ag.
contaminants
Some data for lower
watershed collected
by Gersberg &
others. Modeling
using NURP data can
be done
Data not available
for all sub-basins.
Estimates can be
obtained with
modeling
Some data available just
downstream from
Tijuana & Tecate from
Gersberg
Water pollution (public
health-environmental
health)
Sewage hook-ups,
potable water supply,
health measures
Data on sewage &
potable water hookups available for
Tijuana, possibly
Tecate
Data not available
from most sub-basins
Data on sewage and
potable water hookups
available for Tijuana
possibly Tecate
22
(COLEF) have some
information for the year 2000
CESPT and CESPTE have
data only for those wells used
by these agencies to meet
their needs. For the rest we
face the same problems above
with CNA.
At this moment there are no
data at the municipal level.
CESPT holds data on
monthly water consumption
by business and sector only
(we do not know about
CESPTE). One way is to
estimate the numbers at the
state level and assume that the
same proportion holds for
Tijuana (and Tecate if such is
the case).
The same conditions as in the
case of groundwater overdraft
apply here. Data are old and
dispersed over time. Possible
solutions would be to work
with indicators on number of
treatment plants, levels of
treatment, and reuse volumes.
Some studies have targeted
the coast pollution and
provide measures on organic
pollutants and other
contaminants for the Tijuana
area which may be assumed
to be present at the TRW
level.
Data on sewage and potable
water coverage from CESPT
and CESPTE are available
(may be not for different
points in time for the latter).
These data only for urban
Specific BioContaminants
Flood Risk
Drought Severity
Disease, etc
See impairments to
water quality
Compute from
remotely sensed
imagery
See impairments to
water quality
Compute from
remotely sensed
imagery
Percent of Impervious
surface
Compute from
remotely sensed
imagery or land use
Compute from
remotely sensed
imagery or land use
Percent of population in
flood//plain
FEMA maps &
imagery from U.S.
Imagery for Mex.
FEMA maps &
imagery for U.S.
Imagery for Mex.
No. of times that drought
severity index has
exceeded threshold valve
Historical climate
data
Historical climate
data
Percent of stream class
that is channalized
Coefficient of variation
of stream flow
23
See impairments to
water quality
Compute from remotely
sensed imagery
Compute from remotely
sensed imagery or land
use
Compute from remotely
sensed imagery
Historical climate data
areas. The 2000 population
census from INEGI has these
data desegregated to include
the % of households that do
not have access to water or
sewage and rely on other
strategies.
Same comments as for
impairments to water quality.
Both institutions (SDSU and
COLEF) have modeling
systems that can estimate
these types of indicators.
They are currently monitoring
one section of Arroyo Alamar
to have more precise
estimations. These measures
can be extrapolated later at
the watershed level.
Historical data on
temperature, precipitation and
humidity may be obtained
from CNA through its local or
state offices. These data,
however, are in hard copy and
need to be integrated in
digital form.
Reduction in riparian
ecosystem
extent/composition
Threat to biodiversity
(not just riparian)
Urbanization
Landscape metrics
Historical remote
imagery
Historical remote
sensed imagery
Historical remote sensed
imagery
Diversity indicators
Data not available
Data not available
Data not available
Degree of protected ness
Percent of protected
open space
Percent of protected
open space
Percent of protected
open space
Same as riparian above
Same as riparian
above
Remotely sensed
imagery TRW GIS
database
Same as riparian
above
Remotely sensed
imagery TRW GIS
database
Same as riparian above
Use of ATtILA,
AGWA, and other
models
Not relevant to most
of TRW
Use of ATtILA,
AGWA, and other
models
Not relevant to most
sub-basins
Use of ATtILA,
AGWA, and other
models
Data available from
CESPT & CESPTE
Data from SDCWA,
CESPT & CESPTE
for urban areas
Data from SDCWA,
CESPT & CESPTE
for urban areas
Data from CESPT &
CESPTE
Percent of urban land
cover, growth of urban
footprint
Hydrologic response to
urbanization
Infrastructure quality
performance
Age and condition of
water & sewage
infrastructure
Infrastructure
“brittleness”
Distance to water supply
Redundancy of water
supply
Contingency Plan
24
Remotely sensed
imagery TRW GIS
database
Landscape metrics: Data
layers from Lina Ojeda’s
work with estimates for
surface by type of vegetation
are available.
Diversity: An indicator needs
to be constructed. Sources
are: Conabio, Semarnat
(technical information on the
Escalera Nautica project);
Nature Conservancy (for
Tecate), and Forest Inventory
from Semarnat (1990 and
2000)
Degree of protected ness: The
most important part is the
Estuary.
The comments on diversity
indicators apply also here.
Data are available for the
Mexican part of the Tijuana
watershed. However,
personnel training will be
needed to construct this
indicator.
At the urban level, data are
available from CESPT and
CESPTE (potable water and
sewage networks). In the case
of infrastructure outside the
cities, COSAE (State
Commission of Water
Services) and CNA itself
have information on the
operation conditions of the
aqueducts in the state.
Distance can be calculated
from the GIS system.
Contingency plan information
is available from CESPT and
CILA (urban zones). Tecate’s
case is not clear.
Percentage of water
supply that is imported
Per capita consumption
of water use in M&I
Data from SDCWA,
CESPT & CESPTE
from urban areas
Data from SDCWA,
CESPT & CESPTE
for urban areas
Data from CESPT and
CESPTE
Data at the municipal level.
Best source is
remotely sensed
imagery
Remotely sensed
imagery
Not relevant
Agricultural uses are rather
low in the watershed. An
assumption should be made.
This can be estimated from
data from CESPT and
CESPTE.
Consumptive use over
total extraction by sector
Data not available
Data not available
Data not available
Institutional potential for
transfers and maturity of
water markets
This is difficult now because
the current Law of Waters
does not support it.
?
?
?
Management indicators from
CESPT and CESPTE. CESPT
Master Water Plan
progress evaluations. State
Water Plan
Info. from CNA,
SDCWA, CESPT,
CESPTE
CESPT Master Water Plan
State Water Plan
% of ag. in permanent
crops
Lack of Adaptive
capacity
Presence/absence,
effectiveness, and
comprehensiveness of
water plan
Conjunctive management
of surface and ground
water resources
Info. from CNA,
SDCWA, CESPT,
CESPTE
Info. from CNA,
SDCWA, CESPT,
CESPTE
Financial capacity of
water institutions
Vulnerability Source
Precipitation
Bond Rating
Indicator
Precipitation Variation
Info. from CNA,
SDCWA, CESPT,
CESPTE
TRW
Interpolated
Info. from CNA,
SDCWA, CESPT,
CESPTE
Info. from CNA,
SDCWA, CESPT,
CESPTE
Info. from CNA,
SDCWA, CESPT,
CESPTE
Data Availability
Sub-Basin
Interpolated
25
Info. from CNA,
SDCWA, CESPT,
CESPTE
Info. from CNA,
SDCWA, CESPT,
CESPTE
Management indicators
CESPT and CESPTE
(municipal level)
Tijuana/Tecate
Local weather stations
Comments
Data on hard copy are
available from CNA for
Dependence on
external sources of
water
Ratio of local water used to
import water used
Data from CNA,
SDCUA, CESPT, &
CESPTE
Data from CNA,
SDCWA, CESPT, &
CESPTE where
relevant
Data from CESPT and
CESPTE
Sand & gravel
extraction
Areas in stream valley of
sand and gravel extraction
From remotely sensed
imagery
From remotely sensed
imagery
From remotely sensed
imagery
Stormwater prevention
programs
Areas covered by effective
stormwater prevention
programs
RWQCB & CNA (?)
RWQCB & CNA (?)
RWQCB & CNA (?)
Condition of sewage
infrastructure
Age of sewage lines
SDCWA, CESPT,
CESPTE, IB, City of
S.D.
SDCWA, CESPI,
CESPTE, IB, City of
S.D.
CESPT, CESPTE
Sewage Overflows
No. & volume of sewage
spills
SDCWA, CESPT,
CESPTE, IB, City of
S.D.
SDCWA, CESPT,
CESPTE, IB. City of
S.D.
CESPT, CESPTE
Soil Erosion &
Siltation
Susceptibility to soil
erosion & siltation
Model based on slope,
cover, soil and
precipitation
Model based on slope,
cover, soil and
precipitation
Model based on slope,
cover, soil and
precipitation
Standard of living
Per capita income
INEGI, Bureau of the
Census
INEGI, Bureau of the
Census
INEGI
26
the region and the
watershed.
Ratio was .059 for
2001. Historical data
from CESPT on this
may be obtained for
some time back.
Only the locations
where sand & gravel
has been removed can
be identified with
remotely sensed
imagery.
At the urban level,
CESPT and the
Contingencies
Direction in Tijuana
At most, data are at the
municipal level, from
CESPT and CESPTE
Don’t know exactly if
CESPT in Tijuana has
this kind of data updated
?
Data for Tijuana on
income is available
from the Survey on
Urban Employment
(ENEU) by INEGI
Table 3. Percent Impervious Surface by Sub-Basin
Name
Pine Valley
Upper Cottonwood
Lower Cottonwood
Campo Creek
Rio Seco
Rio Tijuana
El Florido
La Cienega
Las Palmas
Las Canoas
Las Calabazas
El Beltran
ISAT Results
% Impervious Surface
2.36
2.5
5.42
3.71
3.63
39.18
5.6
2.73
3.51
2.38
2.72
2.39
Water Quality
Protected
Protected
Protected
Protected
Protected
Impacted
Protected
Protected
Protected
Protected
Protected
Protected
27
Englert (1997)
% Impervious Surface
12
13
15
13
13
38
16
11
13
10
10
10
% Runoff
9
11
10
10
9
11
6
9
7
7
6
5
Table 4. Mexican portion of the Tijuana River Watershed. Water Availability 1991-2003
Year
1991
1992
1993
1994
1995
1996
1997
1998
1999
2000
2001
2002
2003
Water
Total
TRW
(000's
AF)
55.5
71.9
49.9
49.7
80.2
98.1
90
94.9
102.4
116.4
118.9
112.6
111
Imported Water (000's AF)
Internal Water Sources (000's AF)
Total
%
Total
TRW
Surface
%
Underground
%
26.1
36.5
15.6
14.8
2.1
22.9
59.7
21.0
27.5
91.1
93.2
86.9
84.9
47.0
50.8
31.3
29.8
2.6
23.3
66.3
22.1
26.9
78.3
78.4
77.2
76.5
23.3
39.3
13.9
12.9
0.0
20.3
58.2
20.1
26.6
89.7
91.4
85.8
83.6
89.5
107.7
89.4
87.1
0.0
88.5
97.5
95.7
96.7
98.4
98.0
98.7
98.4
2.8
2.8
1.6
1.9
2.1
2.6
1.5
0.9
0.9
1.5
1.9
1.1
1.3
10.6
7.8
10.4
12.6
100.4
11.3
2.4
4.2
3.2
1.6
2.0
1.3
1.5
Total
%
Total
CRT
Surface
%
Underground
29.4
35.4
34.3
34.9
78.1
75.2
30.3
73.9
74.9
25.3
25.7
25.7
26.1
53.0
49.2
68.7
70.2
97.4
76.7
33.7
77.9
73.1
21.7
21.6
22.8
23.5
4.7
10.7
9.6
10.1
53.3
50.4
5.6
49.2
50.2
0.6
1.0
1.0
1.4
16.0
30.2
27.9
29.0
68.3
67.1
18.5
66.6
67.0
2.2
3.8
3.8
5.3
24.7
24.7
24.7
24.7
24.7
24.7
24.7
24.7
24.7
24.7
24.7
24.7
24.7
%
Total
population
TRW
AF/
person
Urban
population
TRW
AF/
person
84.1
69.8
72.1
70.8
31.7
32.9
81.6
33.5
33.0
97.7
96.2
96.2
94.7
791069
830622
872154
915761
961549
1009627
1060108
1113113
1168769
1240150
1302158
1367265
1435629
0.07
0.09
0.06
0.05
0.08
0.10
0.08
0.09
0.09
0.09
0.09
0.08
0.08
775942
814739
855476
898249
943162
990320
1039836
1091828
1146419
1201075
1261129
1324185
1390394
0.07
0.09
0.06
0.06
0.09
0.10
0.09
0.09
0.09
0.10
0.09
0.09
0.08
Population projections based on the 1990-2000 annual growth rate for the Mexican portion of the TRW.
Sources: Comisión Estatal de Servicios Públicos de Tijuana (CESPT), Total Water Supply 1991-2004; Comisión Estatal de Servicios Públicos de Tecate (CESPTE), Total Water
Supply 1995-2005; Comisión de Servicios de Agua del Estado de BC (CEA), Mexicali-Tijuana Aqueduct annual supply, 1985-2003; Comisión Estatal de Agua de BC (COSAE),
State Water Plan 2003-2007; INEGI, Mexican Population Censuses 1990 and 2000.
28
Table 5. U.S. side of the TRW. Water availability, 2000-2004
City of San Diego
Year
Total Supply (AF)
Otay Water District
Total Supply (AF)
Total
Pop.*
AF/Person
Local
SDCWA
1999
53,135.30
169,790.00
1,224,848
2000
33,909.80
206,434.20
2001
24,794
2002
Total
Pop.*
AF/Person
Local
SDCWA
0.18
896.7
25,442.30
116,800
0.23
1,277,168
0.19
944.2
29,901.20
123,420
0.25
200,648
1,282,532
0.18
850
30,002
124,099
0.25
23,562
204,527
1,287,919
0.18
971
35,182
124,782
0.29
2003
22,914
192,641
1,293,328
0.17
1,013
34,535
125,468
0.28
2004
11,119
227,220
1,298,760
0.18
1,277
39,579
126,158
0.32
* Population projections for 2001-04 were made using the 1990-2000 annual growth rate for the corresponding service areas.
Sources: SDCWA Annual Reports 1999-2000, 2000-2001, 2001-2002, 2002-2003,
2003-2004.
Table 6. TRW Water Availability Indicators 2000-2004
Mexican portion
Year
U.S. portion
Total water
availability
(AF)
Total
population
AF per capita
AF per capita
City of San
Diego
AF per capita
Otay Water
District
1999
102400
1168769
0.09
0.18
0.23
2000
116400
1240150
0.09
0.19
0.25
2001
118900
1302158
0.09
0.18
0.25
2002
112600
1367265
0.08
0.18
0.29
2003
111000
1435629
0.08
0.17
0.28
2004
N.A.
1507410
N.A.
0.18
0.32
Sources: Tables 1 and 2.
29
30