beyond the year of water: living within our water ...social, economic, and environmental systems in...

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Climate Change and Its Implications for New Mexico’s Water Resources and Economic Opportunities

BEYOND THE YEAR OF WATER: LIVING WITHIN OUR WATER LIMITATIONSNOVEMBER NEW MEXICO WATER RESOURCES RESEARCH INSTITUTE 2007

Julie Coonrod obtained a B.E. in civil engineeringfrom Vanderbilt University in 1987, an M.S. in civilengineering from the University of New Mexico in1991, and a Ph.D. in environmental and waterresources engineering from the University of Texasat Austin in 1998 under Dr. Ed Holley and Dr.David Maidment. Prior to her doctoral work, Juliespent five years working as a consultant withScanlon & Associates in Albuquerque and SantaFe, New Mexico. She worked on a variety of civilengineering projects around the state and is aregistered professional engineer in the state of NewMexico. Since becoming a faculty member in theDepartment of Civil Engineering at the Universityof New Mexico in 1997, Julie’s research hasfocused on issues relating to the Middle RioGrande. She started a research program with GISand is teaching a graduate level course thatemphasizes the modeling capabilities of GIS. Julieis a member of the American Society of CivilEngineers and the American Water ResourcesAssociation. She serves as the faculty advisor forSociety of Women Engineers.

CLIMATE CHANGE AND ITS IMPLICATIONS FOR NEW MEXICO’SWATER RESOURCES AND ECONOMIC OPPORTUNITIES

Brian H. HurdDepartment of Agricultural Economics and Agricultural Business

New Mexico State UniversityLas Cruces, New Mexico 88003

Julie CoonrodDepartment of Civil Engineering

University of New MexicoAlbuquerque, New Mexico 87131

ABSTRACT

Social, economic, and environmental systems inwater scarce New Mexico and throughout the aridsouthwest are vulnerable to disruptions in watersupplies that are likely to accompany future climatechanges. With a particular focus on New Mexico andits potential economic consequences, this paper uses a

hydro-economic model of the Rio Grande watershedto integrate plausible changes in climate, hydrologicresponses, and water demands within a frameworkthat optimizes water use allocations for the greatesteconomic benefit. The study uses three climate changescenarios across two future time periods selected to

Originally printed by the National Commission on Energy Policy. Reprinted with permission.

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Brian H. Hurd and Julie Coonrod

represent the range of effects indicted by the outputsacross 18 GCMs using the SRES A1B emissionsscenario. These six climate change scenarios werethen used to model runoff changes using the WATBALhydrologic model (Yates, 1996), which integratesclimate and hydrologic variables, and to change waterdemand parameters in the hydro-economic model.Primary findings confirm that ecosystems are atgreatest risk in New Mexico followed by agriculturalwater users, as water is increasingly transferred tomaintain urban and industrial users with greatereconomic productivity. While total annual economiclosses are estimated in the vicinity of $300 million, undersevere climate changes where runoff is reduced bynearly 30%, in actuality, both economic and non-economic losses are likely to be significantly higher.This is due primarily to both the effects of some stronglyoptimistic model assumptions, e.g., assuming noconflicts over water rights or water transfers, and toseveral significant and valuable omissions in theanalysis, e.g., the environmental and social servicesthat agriculture and the environment provide.

INTRODUCTION

New Mexico has a unique blend of cultures andlandscapes, of agrarian values and high-tech economies,of rare ecosystems, fertile valleys, and expansivedesert rangelands. It is a place where people havelong settled and where growing numbers still long tosettle as migration trends illustrate and highlight growingcommunities praised for their quality of life, climate,and retirement opportunities. The Rio Grande valley,which bi-sects New Mexico, has industry, tourism,residents old and new, and agriculture which all stakeclaims to water resources. These water resources mustalso serve the traditions and economic needs of twenty-three Native American tribes and pueblos, and whichalso flow through traditional acequias – i.e., canals –felt by many to be the ‘lifeblood’ of four hundred year-old Hispanic communities. The Rio Grande is also hometo endangered silvery minnows where is found the lastremnant of their historical habitat, and where flocks ofmigrating cranes and geese gather in vast numbers torest and find refuge in riparian bosques – i.e.,woodlands.

The Rio Grande, and the subterranean aquifersthat it feeds in some regions, are the principal – andoften only – water sources for cities and farms fromSouthern Colorado through New Mexico and into far

West Texas, as shown in Figure 1. The vulnerabilitythat these water users face together – especially inlight of potential climatic and hydrologic changes – isnot only indicated by this high level of dependence ona sole source of supply, but by the oversubscribed natureand exhaustive use of this source (Hurd et al., 1999;Hurd et al., 2006). The level of use is so exhaustive ofsurface supplies that after the thirst is satisfied it is, infact, normal for the Rio Grande to trickle with salt-laden return flows and summer storm runoff for 180miles until its confluence with Mexico’s Rio Conchos– just above Big Bend National Park near Presidio,Texas – where, newly reconstituted, it continues itsremaining 1,100 mile journey to the Gulf of Mexico.

The future health of New Mexico’s economy,traditions and cultures, and riparian ecosystems is sotightly hinged, in the long run, to the flows of the RioGrande that it may not be even necessary, as is theaim of this study, to monetize the economicconsequences as distinct from the hydrologicconsequences of potential climate change. And, ashighlighted throughout this paper, there are manylimitations in the capability to measure and expresseven the economic consequences from changes that

Figure 1. The Upper Rio Grande Watershed and StudyArea

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affect the regional character and economy in suchprofound ways.

The paper begins with a discussion of NewMexico’s climate and the approaches used to modeland identify appropriate scenarios of climate change.Next, the State’s hydrologic situation is described,reviewing key studies that have tried to understandthe climate influences on the State’s rivers, anddescribing the hydrologic modeling used to examinethe climate change scenarios and estimate streamflowchanges. This is followed by a description of theeconomic approach used to estimate impacts. Inestimating these consequences, a hydro-economicmodel of the Rio Grande watershed is used thatoptimizes the allocation of available water, and asnecessary, readjusts water-use patterns such thateconomic losses are minimized during, for example, along-run downturn in streamflow. The final sections ofthe paper present and discuss key findings andconclusions.

CLIMATE VARIABILITY AND CHANGE INNEW MEXICO

Tree-ring analysis indicates that New Mexico hasa long and highly variable history of precipitation andstreamflow that is punctuated with periods of highrunoff and drought. Nearly five hundred years of RioGrande streamflow has been reconstructed and isshown in Figure 2. This reconstruction is long enoughto illustrate that the period of recorded streamflow,roughly 100 years, does not fully account for the naturalrange of extremes. For example, neither the recent

drought from 2001-2005 nor the 1950s drought – themost severe in recent memory – match the severity of8 or 9 previous drought episodes within thisreconstructed record. Some anthropologists speculatethat droughts, in periods even earlier than shown in theFigure, were severe enough in this region to cause thecollapse of early pre-Columbian civilizations in theregion (Plog, 1997).1 Such observations indicate thatsignificant climate anomalies are not unprecedented inthis region; and, that it is entirely plausible that withcontinued greenhouse gas forcing of the atmosphere,and its rising effects on the earth’s energy balance,there can be a reasonable expectation of exceedingthese natural extremes in the future (IPCC, 2007).

In assessing climate change impacts, selectedscenarios should be based on climate models that reflectthe range of plausible regional outcomes. By choosingacross the available range, uncertainty about theregional climate change is conveyed more accuratelythan would be if selections were narrowly targeted.For example, use of only model outcomes estimatingprecipitation increases would be misleading if somemodels project a decrease. Differences across climatemodels tend to indicate the minimum uncertaintyconcerning possible regional climate change. Therefore,to capture the plausible range of climate outcomesassociated with continued atmospheric forcing, Smithand Wagoner (2006) – with guidance and technicalassistance from scientists at the National Center forAtmospheric Research (NCAR) – selected threeclimate models, from the 18 used in the IPCC’s FourthAssessment report (IPCC, 2007), that were mostrepresentative of the range of precipitation response

Figure 2. Long-run Tree-ring Reconstructed Streamflow of the Rio Grande near Del Norte (Source: NationalClimate Data Center, NOAA, http://www.ncdc.noaa.gov/paleo/streamflow/riogrande.html Accessed: February10, 2007)

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from relatively wet to relatively dry with oneapproximating the median. In this comparison eachclimate model used the same underlying greenhousegas emissions scenario, the Intergovernmental Panelon Climate Change (IPCC) emission scenario referredto as ‘A1B’.2 This emissions scenario is generallyregarded as “neither too optimistic nor pessimistic,”and is commonly associated with ‘business as usual’economic activity levels. Furthermore, the spatialresolution of climate model output is coarse relative tothe regional scales most of interest, with grid cell sizescovering approximately 5.6° in latitude and longitude,i.e., very large areas of approximately 300 miles across,as shown in Figure 3 for the New Mexico. Thislimitation means that local differences in climatechange, for example, by altitude or on the leeward andwindward side of mountain ranges is not wellrepresented and contributes uncertainty to the modelresults.

Based on this process, the following three climatemodels were selected to represent the range ofoutcomes projected for New Mexico:

1. Wet: Hadley Centre for Climate Predictionand Research Met Office (hadcm3)

2. Middle:Atmospheric Research Australia(CSIRO)

3. Dry: U.S. Department of Commerce (NOAA)Geophysical Fluid Dynamics Laboratory(GFDL0)

Using the temperature and precipitation outcomesestimated by each of these three models, Smith andWagner (2006) develop six climate change scenarios,a Wet, Middle, and Dry scenario for each of two futuretime periods, a closer time frame, simulating years2020-2039, and one further, simulating years 2070-2089,referred to as “2030” and “2080” scenarios in theanalysis, respectively. Figure 4 (panels ‘A’ through ‘D’)illustrate the estimated temperature and precipitationchanges for New Mexico for each of the six scenarios.

CONSTRUCTING SCENARIOS FOR SOCIO-ECONOMIC TRENDS AND BASELINECHANGES

Economies develop, technologies advance, andpopulations grow and change, together altering thesocio-economic setting in which the future climate isrealized. In the future, will New Mexico residents,industries, and cultural traditions be more or lessvulnerable to a changing climate? Population growth,for example, in New Mexico cities – and throughoutthe cities of the southwestern U.S. – has beensignificant and appears not to be slowing. Studiessuggest that this growth amplifies exposure and thevulnerability of these communities to risks from severedroughts and flash floods (Hurd et al., 2006, 1999). AsFrank Pinto, the Executive Director for the UNDP’sGlobal Environment Facility, writes in his forward to aUNDP handbook on developing socio-economicscenarios:

Developing socioeconomic scenarios of thefuture is important because socioeconomicchanges may substantially increase or decreasevulnerability to climate change. For example,as populations grow, human activities thatpollute may increase and habitats may befragmented. Together, these changes mayincrease the vulnerability of some aspects ofhuman welfare. If the economy grows andtechnologies can be developed, vulnerabilitymay be reduced in some sectors but possiblyincreased in others. These interactive changescan be explored (although not predicted)through the development of alternativesocioeconomic scenarios of the future (Maloneet al., 2004, p. 5).

Figure 3. Approximate Location of the GCM Grid CellUsed to Estimate Temperature and PrecipitationChanges for the New Mexico Climate ChangeScenarios

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Figure 4. Temperature and Precipitation Change Scenarios for New Mexico (Source: Smith, M.B. and C.Wagner. 2006. Scenarios for the National Commission on Energy Policy. Memorandum to Brian Hurd fromStratus Consulting Inc., Boulder, CO. August 1.)

Figure 4a. Temperature Change in 2030

Figure 4b. Temperature Change in 2080

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Figure 4c. Precipitation Change in 2030

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Impacts from future climate changes are bestperformed against baseline estimates of expectedsocio-economic conditions in the relevant futuretimeframe. In other words, it would not be consistentto measure impacts by comparing conditions expected20 or 70 years in the future to those that currentlyexist. To construct socio-economic baseline scenarios,Smith and Wagner (2006) collected demographic trenddata on population and income growth for New Mexicofrom the U.S. Census, to which was added additionaldata from the New Mexico Bureau of Business andEconomic Research (NM BBER, 2004) on populationgrowth trends within the counties of the Rio Grandewatershed.

Using county-level population growth rateprojections developed by NM BBER (2004) for five-year incremental periods out to 2030, annual populationgrowth rates for the counties in the Rio Grandewatershed were estimated. The population growthtrend was further extrapolated to 2080 by fitting aquadratic trend to the data. The results show thatpopulation growth in the Rio Grande corridor isprojected to decline fairly steadily over the study period,falling from current annual rates just under 2% toapproximately 1% in 2030 and 0.5% by 2080, as shownin Figure 5. To insure consistency of the populationestimates with the SRES A1B scenario used indeveloping the climate change scenarios, the estimateswere compared to those developed by Smith andWagoner (2006) – which were SRES A1B rescaledU.S. Census estimates – and were found nearly

identical at the State level. Figure 6 shows the estimatedpopulation in these counties for the years 2000, 2030and 2080 using the extrapolated growth rates.

Estimated population change is the primary driverused to shift aggregate urban water demand in theanalysis and to provide an appropriate baseline againstwhich future climate change impacts can be compared.Although per capita income and regional economicdevelopment are also expected to increase andcontribute to wealth formation over the relevanttimeframe, their effect on aggregate municipal andindustrial water demand is much less clear than thosefrom population changes. Household water demandscan rise with income reflecting, for example, an increasein the size of homes. However, estimated incomeelasticities are generally quite low and to a significantdegree are expected to be offset by improvements inhousehold water-use efficiency.

ESTIMATING THE HYDROLOGIC ANDSTREAM-FLOW CHANGES UNDERCLIMATE CHANGE

Estimating changes in streamflow and wateravailable is the result of hydrologic simulation of theclimate change scenarios. These simulations are runusing the conceptual rainfall-runoff model calledWATBAL that simulates changes in soil moisture andrunoff as a result of changes in temperature and

Figure 5. Projected Growth Rates of Rio GrandeWatershed Counties in New Mexico (Source: NMBureau of Business and Economic Research, rev. 2004.Counties include: Bernalillo, Doña Ana, Los Alamos,Rio Arriba, Sandoval, Santa Fe, Sierra, Socorro, Taos,Torrance, and Valencia)

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Figure 6. Projected Populations of Rio GrandeWatershed Counties in New Mexico (Source: NMBureau of Business and Economic Research, rev. 2004.Counties include: Bernalillo, Doña Ana, Los Alamos,Rio Arriba, Sandoval, Santa Fe, Sierra, Socorro, Taos,Torrance, and Valencia)

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precipitation (Yates, 1996, 1997). WATBAL isconceptualized as a one-dimensional water balancemodel comprised of two elements. First is a waterbalance component that describes water movementinto and out of a basin consisting of three sub-processesdescribing i) surface runoff, ii) sub-surface flow andiii) maximum catchment water-holding capacity. Thesecond models the system energy balance and usesthe Blaney-Criddle relationship to simulate evapo-transpiration (FAO, 1992) and to model the snowstorage and runoff. Parameters in WATBAL includethe size of catchment areas, and the rate wateradditions and removals, which are based on historicalrunoff relationships, calibrated changes, physicalcharacteristics, and input data such as monthly rainfalland temperature. Water is added by precipitation, canbe accumulated to some extent, and is removed byevapotranspiration, surface runoff or sub-surfacerunoff.

The simplified representation of soil moisturedynamics has been shown to adequately representrunoff changes due to climate fluctuations (Yates andStrzepek, 1994; Yates, 1996, 1997). WATBAL wasapplied to each catchment area in the Rio Grandewatershed to simulate runoff and streamflow such thatit is spatially and temporally consistent with the hydro-economic model described in the next section.

For each watershed corresponding to the hydro-economic model (see Figure 7), historical monthlyvalues for stream flow, precipitation, and temperaturewere required. Monthly stream flow values areavailable from the USGS (waterdata.usgs.gov).Historical precipitation and temperature grids (4 kmgrid cells) are available for the contiguous United Statesfrom the PRISM group (www.ocs.orst.edu/prism). Thehistorical 30-year climatic period of 1971 to 2000 waschosen. This period of time contains some of thewettest years on record. However, this period of timealso has the most complete record. Any 30-year climateperiod will contain sufficient variability to calibrateWATBAL, but the calibrated models for the same basinwill differ based on the climate period selected.

Downloading stream flow data is straight forwardas the data correspond to a single point. Conversely,precipitation and temperature are spatially distributedacross the watersheds that drain to the gage locations.From the PRISM website, 1,080 monthly data fileswere extracted: 360 precipitation, 360 maximumtemperature, and 360 minimum temperature files for1971-2000. Each file contained data for the entire

contiguous United States. ArcGIS™ was used tocreate watershed zones based on the contributing areasof the gages selected to be modeled. These zones werethen used with ArcGIS™ to spatially average theprecipitation and temperature over the watershed foreach gage. As this procedure was required for eachof the 1080 files, the process was automated by writinga Python script that could be used in ArcGIS to convertthe PRISM file grids to rasters, clip the rasters to thewatershed zones, and calculate average values acrossthe watersheds. The ArcToolbox>Spatial AnalystTools>Extraction>Sample tool was then used to extracta .dbf table of the attributes for each of the spatiallyaveraged grids. Using Excel, the ArcGIS output fileswere arranged and consolidated by watershed. Theaverage monthly temperature was calculated byaveraging the maximum temperature and minimumtemperature for every month. This method wasvalidated by researchers at the University of Dayton,who studied 53,004 daily temperature records(www.engr.udayton.edu/weather/source.htm).

WATBAL was calibrated for each individualwatershed using the historical data (monthly valuesfor stream flow, spatially averaged precipitation, andspatially averaged temperature). The future climatechange scenarios were applied to each watershed toobtain possible 30-year scenarios of monthly valuesfor precipitation and temperature for each watershed.WATBAL was then used to estimate the correspondingmonthly values of stream flow associated with eachclimate scenario for each watershed.

A HYDRO-ECONOMIC MODEL OF THERIO GRANDE

Modeled runoff and streamflow, the principaloutputs from the hydrologic model, are key drivers inestimating changes in water use and allocation, aquiferand reservoir storage, and changes in economicwelfare. To estimate these changes, a river basin-scalehydro-economic model (RBHE) of the Rio Grandewatershed is used, which simulates the managementof water systems from watershed-wide perspective.The model optimizes the allocation, use, storage, andmanagement of available water such that the greatestlong-run economic benefits are achieved within thelegal boundaries of river compacts and treaties, andwith available resources, technologies, andinfrastructure.

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Figure 7. Schematic Diagram of the Rio Grande Hydro-Economic Model

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One of the key aspects of the RBHE model is theexplicit treatment of the underlying value of water, oftenrepresented as mathematical functions that relate themarginal economic value of water to the quantity ofwater use, i.e., ‘water demand functions.’ By specifyingthis relationship, the modeler is implicitly specifying theflexibility of the particular water user to changes inwater prices. Economists often refer to this as the‘price elasticity of demand’ – in other words how thequantity of water use changes in percentage terms toa percentage change in price. As climate changeinteracts with economic markets by affecting resourcesupplies and demands, ultimately resource prices arealtered and signal to water users that a change in wateruse is indicated – providing that institutions and policiespermit the direct and transparent relay of these implicitprices to water users. Adaptation to a water shortage,for example, occurs as some water users that are lesstolerant of price increases begin to curtail their use.

Hydro-economic models have several advantagesfor long-term planning and assessment over alternativewater budget and system simulation type models. First,by using an optimization framework RBHE modelsreplicate an active decision environment that explicitlyrecognizes the opportunity costs and economictradeoffs inherent in any given water allocation andstorage decision. Second, simulation and water budgetmodels use a “what if” perspective to assess theconsequences that would follow from a given allocationdecision; however, only an optimization framework cansystematically sift through all the permutations ofpossible allocation decisions and identify those that arepotentially ‘best’ and worthy of more closer scrutiny.This is a distinct advantage when examining andcomparing the effects of large-scale, system-widechanges, especially if behavior within the system isdynamic and roughly follows the optimizationobjectives. Third, RBHE models provide explicitinformation regarding the value of water, how it isaffected by water supply changes, how it varies bothtemporally and spatially, and how it is altered by physicallimitations and institutional constraints. As a result,RBHE models excel in their capacity to identifystrategies that can improve water-use efficiency,infrastructure designs, investment decisions, andinstitutional arrangements.

Vaux and Howitt (1984) pioneered thedevelopment and use of RBHE models for regionalwater assessment in examining water transfer issuesin California. Booker and Young (1991, 1994) extended

the approach by more realistically capturing theextensive network characteristics of a watershed intheir study of the Colorado River basin. More recently,climate change impacts have been assessed using theapproach by Hurd et al. (1999, Hurd and Harrod 2001,2004), and in California by Tanaka et al. (2006). Andin the upper Rio Grande basin, Ward et al. (2001)developed an RBHE model and used it to examine theconsequences of sustained drought, which was furtherextended by Ward et al. (2006) to assess the combinedeffects of drought and endangered species protectionon the water economy of the Rio Grande. Descriptionsof the conceptual foundations and use of RBHE canbe found in Hurd (1999, 2004), Null and Lund (2006),JWRPM (2006), Draper et al. (2003), Jenkins et al.,(2004), and in Cai et al. (2003).

This study builds on the Rio Grande hydro-economic (RGHE) model of Ward et al. (2001) bymaking several important modifications, the mostimportant of which is the reduction in time-step fromannual to monthly. By increasing the temporal resolutionto monthly, the RGHE is better able to capture theeffects of an expected shift in the streamflowhydrograph toward an earlier snowmelt and peak runoffas a result of climate change. This extension alsoimproves the model’s capability to simulate changes inseasonal water use patterns, instream flowrequirements for endangered species, and recreationaluse patterns at reservoirs.

As with all hydro-economic models, the RGHEmodel is oriented towards economizing available waterresources by identifying the most valued use andstorage, conveyance, and water quality decisionspossible within the existing physical, institutional andinfrastructure limitations. In addition, two importantbehavioral assumptions are implicit in the modelingframework that can significantly affect the nature andinterpretation of the results. First, competition betweenwater users is assumed, and furthermore, these waterusers aim to maximize their expected net economicreturns. This implies that water is freely transferableacross uses with no restrictions or transaction costs,and subject only to the physical and institutionalrestraints of the system (i.e., logical mass-balancerelationships must be satisfied between the flows ofwater from upstream to downstream locations andbetween adjacent time-periods in storage conditions).By ignoring the significant transactions costs of watertransfers and, indeed, some of the underpinnings ofthe institution of prior appropriation in defining water

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rights, the model understates the economic costs ofadjustment and adaptation to changing water supplies.Another artifact of this assumption is that theoptimization framework is not necessarily a ‘good’predictor of current and actual patterns of water use.This limitation, however, does not detract from theinsightful and useful results that focus less on theabsolute level of economic output and instead focuson the magnitude of change – a measure that is likelyto be more robust (Draper et al., 2003; Tanaka et al.,2006).

Second, the model design allows for ‘perfectforesight’ across the 30 year sequence of runoff andstreamflow conditions. By assuming away futureuncertainty in runoff and streamflow, adjustments andadaptations – in the form of storage and use decisions– are optimally executed without errors in the amountor timing of adjustment. As a result, this assumptioncontributes further to the model tendency to understateeconomic adjustment costs and hence the economicimpacts of water supply changes under climate change.

A conceptual diagram of the model is given inFigure 7, which depicts key physical characteristics ofthe watershed, including tributaries, inflows from thehydrologic model outputs, return flows from users,diversion points, and reservoirs. The model is developedand executed using the General Algebraic ModelingSystem (GAMS, Brooke et al. 1988). In summary, themodel consists of:

1. A nonlinear objective function that aggregatesall the sources of economic value and cost inthe watershed as a function of water use andreservoir storage, including the cost of pumpedgroundwater, the benefits associated withreservoir recreation, and the shifting waterdemands due to population and climatechanges. Figures 8a and 8b illustrate the urbansector aggregate and household benefitfunctions, respectively. Figures 8c and 8d showexamples of the aggregate and per acrefunctions for the agricultural sector. And Figure8e shows net economic benefits for flatwaterrecreation on reservoirs as a function of storagelevel.

2. A system of linear constraints that characterize:• Spatial network and streamflow continuity

of monthly runoff into the basin, main stemand tributary streamflow, surface waterdiversions, and sub-basin water transfers,

i.e., where water enters the system, howit travels and is distributed, where it is used,and how it leaves the system.

• Inter-temporal balances in reservoirs andaquifers between adjacent time periods(i.e., months), and mass-balances withineach time period that balance additions andextractions, including storage releases andevaporation losses.3

• Institutional limitations of compacts, treatiesand intergovernmental agreements, forexample, the Rio Grande Compactbetween Colorado, New Mexico andTexas; the 1906 Treaty with the Republicof Mexico requiring the annual delivery of60 kaf/yr; and operational rules betweenthe Elephant Butte Irrigation District(EBID) and the El Paso WaterConservancy District #1 (EPWCD#1).See Ward et al. (2001) for details.

Incorporating the Climate Change and Socio-Economic Baseline Scenarios into the RioGrande Hydro-Economic Model (RGHE)

In modeling the climate change and socio-economicbaseline scenarios previously described, several keychanges in the model inputs and parameters arehighlighted that coincide with changes in scenarios and,in the process, introduce the scenario terminology thatis used subsequently to report the key results andfindings.

A total of nine scenarios were run using the RGHEmodel. Three baseline scenarios were modeled withoutthe effects of climate change but with the projectedchanges in population and its attendant shift in urbanwater demand, referred to as: 2000 Baseline, 2030Baseline, and 2080 Baseline. In addition, six climatechange scenarios were run, one for each of thecombinations of the three representative climate changepatterns and the two time periods, referred to as: 2030Dry, 2030 Middle, 2030 Wet, 2080 Dry, 2080 Middle,and 2080 Wet. In presenting the results, the relativeeffect of each climate change scenario is comparedagainst the appropriate baseline time period, forexample, all 2030 climate scenarios are comparedagainst the 2030 Baseline using the same populationchange assumptions.

Key changes in model inputs and parametersacross the climate change and socio-economic baselinescenarios are summarized as follows:

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Figure 8. Examples of Economic Benefit Functions in the RGHE Model

Figure 8a. Example of a Municipal and Industrial (M & I) Aggregate Benefit Function

Figure 8b. Example of Annual Household Water Demand and Total Net Benefits

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Figure 8c. Example of an Agricultural Aggregate Benefit Function

Figure 8d. Example of Annual Agricultural Water Demand and Total Net Benefits per Acre

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1. Streamflow and runoff input is altered.Using the output from the hydrologicsimulations, the 30 year sequence of monthlyrunoff for each inflow point is modifiedaccording to the selected climate changescenario.4

2. Reservoir evaporation rates are changed.Using estimated changes in potentialevapotranspiration rates from simulating theenergy-balance changes in the WATBALhydrologic model, adjustments are made to themonthly water losses for each reservoir in theupper, middle, and lower watershed,respectively, for under each climate changescenario, as shown in Figures 9a through 9f.

3. Agricultural consumptive water use isshifted. Reflecting the increased irrigationrequirements associated with highertemperatures, consumptive agricultural waterdemands are raised consistent with agronomicneeds but without implying an increase in neteconomic benefits.5 The assessment implicitlyassumes changes in the mix of crops grown –consistent with current crop technologies.There are many changes in New Mexicoagriculture that are plausible over the next 50

years, including changes in genetic technologiesand crop yields, incidence of pests and diseases,and loss of arable land due to urbandevelopment. Each of these changes couldalter the agricultural demand and value ofwater, however, owing to the speculative natureof these changes they are not included in thepresent analysis.

4. Urban water demands shift in responseto population changes. Population changeis accounted for in each scenario that is run ina future time period, either for the 2030’s or2080’s. These changes result in an increase inaggregate household water demand and,hence, in the estimated value of economicservices generated. Although landscapeirrigation requirements for non-native grasseswould be expected to rise similar withagricultural demands, these increases wouldbe expected to be offset by improvements inhousehold water-use efficiency and incontinued trends of reduced turf landscapes.6

Therefore, in the present analysis, householdwater demand is assumed to be invariant toclimate changes. It should be noted that thereare many issues related to urban water use

Figure 8e. Example of Total Benefits from Reservoir Flat-Water Recreation

Elephant Butte ReservoirMa x. Ca p. = 2065 ka f

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Figure 9. Relative Change in Regional Monthly Reservoir Evaporation across the Six Climate Change Scenarios

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Figure 9b. 2030 Middle

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that can be expected to affect urban waterdemands and values over the coming 50 years,such as water re-use and recycling, availabilityof alternative water supplies from, for example,desalination of extensive brackish aquiferresources. These changes, which would beincreasingly used as water prices rise, areincluded in the present assessment, and would,if included most likely reduce some of the neteconomic impacts.

Endangered Species ConcernsThe Rio Grande, especially the Middle region

between Cochiti and Elephant Butte Reservoirs, is thelast remaining habitat for the endangered SilveryMinnow. As a result, the U.S. Fish and Wildlife Service(USFWS) has determined that a minimum instreamflow of 50 cfs is necessary at the San Acacia gaugefor species protection. Aggregating this flow level intoa monthly estimate and using a 100% safety factor toaccount for daily variability results in a streamflowminimum of 6 kaf/month. This constraint is maintainedin the analysis all model runs.

ASSESSMENT RESULTS AND FINDINGS

WATBAL and the RGHE model were run tosimulate and optimize the management of a 30-yearsequence of monthly streamflows for each of threebaseline scenarios (Base 2000, Base 2030, and Base2080) and for each of the six climate change scenarios(2030 Dry, 2030 Mid, 2030 Wet, 2080 Dry, 2080 Mid,and 2080 Wet). Model results are presented anddescribed in the first two sections below. This isfollowed by a section summarizing the possible effectsof model assumptions, uncertainties, and notableomissions all of which caution against the unqualifieduse of the estimated impacts from the models alone.

Streamflow and Hydrologic AssessmentConsistent with the RGHE model schematic shown

in Figure 7, WATBAL modeled streamflows for eachof seven tributary inflows within the Rio Grandewatershed (in addition, two inter-basin transfer inflowsare also included but are not assumed to vary asdescribed earlier in endnote 6). The most importanttributary inflow to the Rio Grande is the mainstemheadwaters coming from the San Juan Mountains ofsouthern Colorado and passing the river gage at DelNorte, accounting for more than 35% of annual

streamflow. The relative contribution of each of theseven modeled tributaries is shown in Figure 10, whichalso highlights the peak streamflow months of Mayand June under current climate. Most of the flow inthe Rio Grande is the result of snowmelt in the higherelevations during late spring. Flow from the Rio Puercoand Rio Salado are mostly driven by July and Augustmonsoons. These rivers are perennial and quite erraticin nature. A monthly time step cannot adequatelyrepresent perennial streams as flow is event driven,yet monthly time does account for the time periodswhen the Puerco and Salado have been responsiblefor consistent increased Rio Grande flows.

To see how climate change might affect thestreamflow hydrograph, average monthly streamflowsfor each tributary were aggregated and plotted for eachscenario as shown in Figure 11. Two results showclearly in this figure. First, peak flow and totalstreamflow declines for all of the climate changescenarios, whether or not they are relatively ‘wet’.The apparent robustness of this result could haveimportant implications for the management of waterresources in the region. Although, there is a potentialfor summer monsoonal activity to increase, assuggested by the 2080 Wet scenario, this is not likely,according to the model results, to offset the losses fromdiminished snowpack levels in the headwater regions.Second, there is a pronounced shift in later periods(i.e., 2080s time frame) in the peak runoff month byabout 30 days. In all of the 2080 period runs, the peakoccurs in April and, perhaps, equally as important, thereis a significant increase in late winter runoff comparedto current conditions.

To further illustrate potential changes in the relativelikelihood of basin streamflow, Figure 12 presents thetotal runoff data for each scenario in the form of acumulative probability function. This figure shows, forexample, the substantial change in the distribution ofrunoff between present and changed climates. Thesevere dryness of the 2080 Dry scenario is apparentin the figure where median runoff drops by nearly 1/3,from approximately 1.6 maf/yr to less than 1.1 maf/yr.7

With the hydrograph shift indicating lower runofftotals and a shift toward a greater share of runoffoccurring earlier, i.e., reflecting both an earlier snowmeltand lower snowfall totals, water availability during peakuse periods is likely to be significantly more dependenton stored water management in reservoirs and aquifersthan at present. Further implications of these possible

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changes in water availability are found in the resultsof the RGHE model below.

Assessment of Water Use and Economic ImpactsAs illustrated by the changes in both the amount

and timing of annual snowmelt and runoff, there is asignificant potential for climate change to disrupt thecurrent allocation and management of New Mexico’swater resources. How these changes might affectcurrent and future water users is the primary focus ofthe hydro-economic model, and its capacity to highlightadaptive changes in allocation and storage – withinthe existing infrastructure and technology – to minimizedisruption and economic losses to the region as a whole.The assessment results are presented in two sections.First modeled changes in consumptive use aredescribed, highlighting shifts in allocation betweenagriculture and urban use by scenario. The secondsection presents the estimated economic effects ofthese changes in allocations and patterns of use byscenario.

Changes in Water Use and AllocationAs might be expected for water use in a basin that

exhausts even the present water supply in normal years,any reduction in long-run, average supply necessarilyleads to a reduction in long-run average use. Figure 13

shows the modeled changes in aggregate water useacross the scenarios. Heavily influenced by the patternof agricultural irrigation that peaks in June, the figureshows how total water use is curtailed as total suppliesdiminish with the severity of climate change. The dryscenarios lead to declines in total water use of nearly10% and over 25% for the respective periods of 2030and 2080. Declines of 2% and 18% accompany themiddle scenarios, respectively; and for the wetscenarios water use declines of nearly 4% and 6.3%are projected, respectively. Note that the ‘middle’scenario is wetter than the ‘wet’ scenario in the earlier2030 time period, thus explaining the estimated higherloss of 4% for the wet scenario compared with themiddle scenario.

As stated earlier, hydro-economic models are veryadaptively efficient – they anticipate water supplychanges perfectly and execute allocative changes withperfect timing and efficiency. As a result, the modeledchanges in water use by sector will strongly reflectdifferences in the relative economic value of water ineach sector. These differences are most stronglyevidenced in Figure 14, which shows the modeledchanges in streamflow, agricultural sector, and urbansector allocated use, by climate change scenario. Forall but the two most severe scenarios, reductions inmodeled water allocation and use are less than

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Figure 10. Average Monthly Streamflow for the Upper Rio Grande Basin Tributaries under Baseline Conditions(historical period: 1971-2000)

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Figure 11. Average Aggregate Streamflow by Month for Each Climate Change Scenario

Figure 12. Cumulative Distributions of Total Basin Streamflow across the Climate Change Scenarios

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79


reductions in streamflow. For example, in the 2030 dryscenario, streamflow falls by nearly 14%, which leadsto a drop in agricultural use of 12% and 0.3% in urbanwater use, respectively. Each of the wetter scenarios– i.e., 2030 middle, 2030 wet, and 2080 wet – result invirtually no allocated reductions to the urban sectors,with agriculture absorbing the reduction in runoff nearlyentirely. Each of the two drier scenarios – i.e., 2080middle and 2080 dry – show quite significant reductionsin agriculture and to some degree in urban water use.

As expected, these results illustrate the relativelyhigh modeled demand for urban water as compared toagricultural water, as evidenced by the exampledemand curves shown by Figures 8b and 8d,respectively, and the high share of agricultural wateruse in the Rio Grande basin, approximately 87.5% inthe modeled baseline year of 2000.

Reductions in modeled runoff and water supplyare not equally shared across water users. Rather, byconsidering the relative economic contribution,reductions are allocated to minimize long-run, expectedlosses to total regional economic production. In otherwords, the optimization framework used here enablesthe system to avert potentially much greater economiclosses that would follow if water use reductions werenecessary in other non-agricultural economic sectors.

Estimated Changes in the Marginal Value of WaterFrom an economic perspective, a rising price is

the clearest signal of increasing relative scarcity. Water

resources in New Mexico are increasingly scarce asa result of two processes, increasing demands fromgrowing populations and, potentially, falling watersupplies given the estimated effects of climate change.Both effects are evidenced in Table 1, which showsthe change in the marginal value (i.e., modeled price)of water at two points in the watershed, the Rio Grandeheadwaters in Del Norte, Colorado and the Sangre deCristo headwaters in Northern New Mexico. Theestimated values for Colorado are much higher thanfor New Mexico as a result of the Rio Grande Compactand the relatively high value of agricultural productionin the San Luis Valley. For New Mexico, the Sangrede Cristo values are much more representative of themarginal value of water, which is primarily measuredby the marginal value for agricultural uses.

The pronounced effect of population increases onthe marginal value of water in New Mexico is clearlyshown in Table 1. For example, as population alonegrows by 45.7% and 75.7% for 2030 and 2080,respectively, the implicit price of raw, untreated, andundelivered water is seen to rise by 47% and 81%,respectively. This shows, in effect, the necessary pricerise for bidding water away from agriculture and intomunicipal service.

Climate change introduces water supply changes– in these cases, reductions – that exacerbate relativescarcity and result in even larger price increases inorder to induce water transfers from agriculture tourban water users. Table 1 shows the effects on

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Figure 13. Average Monthly Aggregate Water Use for Each Climate Chnage Scenario

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marginal values (or implicit model prices – notnecessarily observed ‘market prices’) across theclimate change scenarios relative to the appropriatebaseline scenario.8 For example, projecting climatechange into the decade of the 2030s, results inestimated price changes ranging from 15% to 60%,with the marginal value of raw water rising from anestimated $25/af to between $30/af and $40/af.Projections to the decade of the 2080’s finds still greaterpotential scarcity with price increases ranging from11% under ‘wet’ conditions to nearly 200% under ‘dry.’

Direct Changes in Economic ProductivityWater is important to the economy of New Mexico

by providing drinking water to residents and supportingcommercial, industrial, and recreational activities. In2006, the total gross domestic product of New Mexicowas estimated at $76 billion (NMBBER, 2006), roughlyone-half of one percent of the $13,000 billion GDP ofthe United States in 2006. The largest contributors toNew Mexico’s economy include government (18.4%),manufacturing (13.8%), retail and wholesale trade(11.2%), real estate (10.6%), mining (8.2%), andforestry and agriculture (1.7%). Within the agriculturalsector, crop production accounts for approximately20% of total cash receipts while dairy and livestockproduction accounting for nearly 40% each (NMDA,2005).

In considering the economic impacts of populationand water supply changes on New Mexico’s economy,it is useful to address both direct and indirect (orsecondary) changes. Direct effects result from changesin economic output as a result of changes in operatingconditions, for example, diminished water supply.Indirect effects reflect the consequences for relatedeconomic activities and services, and are described ingreater detail in the next section.

Modeling the baseline water use and economy forthe year 2000, RGHE generates $387 million in directagricultural sector benefits (which includes someagriculture outside of New Mexico but within the RioGrande watershed, including agriculture in Colorado’sSan Luis Valley, and agriculture in far West Texas).Even including agricultural income generated inColorado and Texas, this amounts to less than 0.8% ofNew Mexico’s GDP, a slim slice of the economy thatuses more than 87% of the water.

Consistent with the expectations of the model,continued population growth must necessarily competewith existing water users for available supplies. Withthe estimated increases in population for 2030, and2080, the future baseline scenarios show decreases inagricultural water use and economic production of1.3% and 2.5%, respectively. Agriculture is and willbe in the future the overwhelming source for thiscontinued population and economic growth.

Figure 14. Streamflow and Water Use Changes by Sector and Scenario

-35%

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With climatic change and the expected decreasein available runoff shown above across all the scenarios– even the relatively ‘wet’ ones – the competition forwater will be exacerbated and the pressure to increasewater transfers from agriculture further heightened.Figure 15 shows, in percentage terms, and Table 2 inestimated direct economic losses (in 2000$), the relativedistribution of economic impacts among agriculture,municipal, and recreational users across the climatechange scenarios.

Under the most extreme scenario (2080 Dry), forexample, average agricultural water use declines by

33% and results in an average economic reduction of$82.6 million (22%) compared to the population adjusted2080 baseline run; whereas, water use in the urbansector falls less than 2%, with estimated economiclosses of $12 million (0.6%) from a baseline value of$2.1 billion. Add to this estimated losses of $6.1 millionfor reservoir recreation, and total modeled economiclosses under this severe scenario reach nearly $101million (2000$) – approximately 4% of the estimatedtotal $2.5 billion in water generated direct economicbenefits.

Table 1. Estimated Value of Rio Grande Water by Climate Change Scenario

Climate ChangeScenario

% Change inAverage AnnualRunoff

Rio Grande Del Norte(Colorado)

Sangre de Cristo(New Mexico)

Marginal Value of Water in Rio Grande Headwaters#

$ per acre foot(% difference from baseline)

2000 Baseline

2030 Baseline

2080 Baseline

$66.82(0%)

$67.40(0.9%)

$67.77(1.4%)

$17.23(0%)

$25.38(47%)

$31.25(81%)

(0%)

2030 Dry

2030 Mid

2030 Wet

2080 Dry

2080 Mid

2080 Wet

-13.7%

-3.5%

-6.3%

-28.7%

-22.8%

-8.3%

$101.43(50%)

$72.56(8%)

$73.76(9%)

$129.02(90%)

$106.78(58%)

$74.46(10%)

$40.66(60%)

$29.22(15%)

$30.78(21%)

$93.18(198%)

$63.37(103%)

$34.79(11%)

#Estimates based on the Rio Grande Hydro-Economic model shadow values averaged for water for primary tributaryinflows to the Rio Grande at Del Norte and from Sangre de Cristo headwaters. Differences in the estimated marginal valueof water at these two locations in the watershed highlight the effects of the Rio Grande Compact requiring water deliveriesto New Mexico and the relatively high marginal value of agriculture in the San Luis Valley of Colorado.

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Though direct economic losses to the agriculturalsector are potentially substantial, there may beconsiderable economic consequences that follow fromthese potential changes in the character andcomposition of New Mexico’s economy, and are thesubject of indirect and secondary effects.

Indirect and Secondary Economic EffectsIndirect and secondary impacts take the form, for

example, of ‘losses’ in income or employment inagricultural-related industries and locations, and of‘gains’ in industries and locations to where water istransferred. For example, water that leaves agricultureand reduces irrigated acreage not only reduces farmincomes (i.e., the direct effect) but also reduces thedemand for supporting economic services, includingupstream activities such as farm machinery and repair,seed and chemical inputs, and labor, and downstreamactivities such as farm product processing andmanufacturing. This can generate significant economichardship and dislocation.

Although many economists consider an indirect(or secondary) economic effect to be the result ofeconomic restructuring that merely shifts or transfers

economic activities – i.e., changes in the types orlocation of jobs with no measurable effect on overalleconomic performance and, therefore, of no neteconomic consequence – rather, there are manyreasons why these effects should not be readilydismissed. First, though population changes may propelwater transfers to urban areas with perhaps a shift inpotential employment opportunities from the farm tothe city, climate change induced water transfers arefundamentally concerned with an absolute reductionin water supply, not simply relocating an economicactivity. Second, as Howe (1997) points out indescribing inter-basin water transfers, there are likelyto be severe and lasting economic repercussions in theregions where water is leaving. People are not so easilyuprooted and retrained. It is likely to require substantialtransition costs to provide the needed ‘safety net’ ofsupport to rural economies that must adapt toreductions or loss of agriculture. Many ruralcommunities in New Mexico include disadvantagednative and Hispanic communities that are likely tosuffer disproportionately in attempting to adjust to theloss of income and a lack of viable alternatives foreconomic development and employment.

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Figure 15. Streamflow and Economic Output Changes by Sector and Climate Change Scenario

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Such indirect effects are difficult to measure andto account for accurately. Most often, these effectsare estimated as economic multipliers to the estimateddirect effects. Hall and Skaggs (2003), for example,estimate an economic output multiplier of 1.61 forvegetable production in Southern New Mexico. In otherwords, for each $1 of vegetables produced, anadditional $0.61 is contributed to the economy byupstream and downstream economic activities.Lillywhite et al. (2007a, 2007b) estimate multipliers forother agricultural industries ranging from 1.55 to 1.8.Allowing for a bit wider range in economic impactsand dislocation e.g., a range in multiplier effects from1.5 to 3, Table 3 shows estimated direct, indirect, andtotal economic effects of climate change on NewMexico’s water resources. These impacts range froma loss of $15 million to $114 million in the 2030’s to asmuch as $302 million in the 2080’s under the relativelysevere, 2080 ‘Dry’ scenario.

Assumptions, Uncertainties, Omissions andOther Potential Biases

The presentation of the estimated potentialeconomic consequences from climate change closeswith a discussion and concern for the unaccounted foreffects that flow from model assumptions,uncertainties, and omissions. Here, are highlighted –at least qualitatively – the nature of some significantadditional concerns that condition the quantitativeassessment. The following may not exhaust all thepotential concerns but, highlight key areas andlimitations.

The costs of water transfers, respect for ‘propertyrights,’ and the potential costs of conflict are notrepresented well at all. This is perhaps the mostcontentious and undervalued of all the ‘omissions’ inthe assessment. The modeling framework assumesneatly organized and efficiently functioning watermarkets in which buyers and sellers behave rationallyand cooperatively with perfect information, foresight,and knowledge. In actuality, the potential for significant

Table 2. Estimated Changes in Direct Economic Output by Sector and by Climate Change Scenario



Agriculture Municipal/Industrial

Economic Sectormillions of 2000$(% of sector total)

2030 Dry

2030 Mid

2030 Wet

2080 Dry

2080 Mid

2080 Wet

-13.7%

-3.5%

-6.3%

-28.7%

-22.8%

-8.3%

*In 2006, New Mexico’s total gross domestic product was estimated at $76 billion (NMBBER, 2006), and therefore, evenestimated direct losses greater than $100 million are less than 1/2 of the 1% of the regional economic output.

ReservoirRecreation

Total*

-33.8(-8.9%)

-7.1(-1.9%)

-8.8(-2.3%)

-82.6(-21.9%)

-50.9(-13.5%)

-13.2(-3.5%)

-1.3(-0.1%)

-0.6(-0.04%)

-0.6(-0.04%)

-12.0(-0.6%)

-5.5(-0.3%)

0.0(0%)

-3.0(-14.7%)

-0.7(-3.3%)

-0.9(-4.6%)

-6.1(-31.7%)

-5.3(-27.3%)

-1.0(-5.1%)

-38.1(-2.0%)

-8.4(-0.4%)

-10.3(-0.5%)

-100.7(-4.0%)

-61.7(-2.4%)

-14.2(-0.6%)

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economic and legal conflict is not only real but likelyunavoidable and very difficult to measure a priori.Absent a publicly and politically acceptable form ofeminent domain and an accepted framework for‘compensable takings’ there will likely be long,protracted litigation that will make water transfers fromagriculture to municipal users anything but ‘frictionless’as the model assumes. Consider, for example, the tensof millions of dollars spent to date in attempting toaccommodate stakeholder concerns in a ‘cooperative,consensus building exercise’ to address the waterproblems of the San Francisco Bay-Delta in California.Without any promise of resolution – after more thantwelve years of trying – the so-called ‘Cal-Fed’ processis, like most western water issues, more and more likelyto resort to litigation. Unresolved water rights’ issuesflourish in the Rio Grande. Adjudication of water rightsis long and contentious, and not likely to be clearlyresolved in the foreseeable future. Add to this the ‘priorand paramount’ water rights reserved under the‘Winter’s Doctrine’ for the many tribes and pueblos ofthe Rio Grande region and there are legal knots within

knots that will add to water transfer costs – perhapsby many multiples.

Agriculture provides many valuable butuncompensated – and often unrecognized – servicesthat will also be lost as water is transferred. Farmsscattered throughout the Rio Grande region creategreen, open spaces enjoyed for their scenic beautyand by flocks of birds and other wildlife that migrateand traverse the arid rangelands of New Mexico insearch of food, water, and refuge. Farming andagriculture are natural-based activities that areconsistent with core public values such as stewardshipof the land and water. Pastoral activities andlandscapes are valuable for their ability to stimulateimagination, calm anxiety, restore connections tonature, and remind people of their long-enduringconnection to the land and to the food it provides.Withering the agricultural lands of the Rio Grande willhave unmeasured costs as land fragments into otheruses or reverts to desert rangeland.

Adequacy and reliability of expected inter-basintransfers is called into question by recent studies and

Table 3. Impact of Climate Change on the Direct and Indirect Economic Output of New Mexico



Direct Impacts Indirect Impacts#

Direct and Indirect Economic Impactsmillions of 2000$

2030 Dry

2030 Mid

2030 Wet

2080 Dry

2080 Mid

2080 Wet

-13.7%

-3.5%

-6.3%

-28.7%

-22.8%

-8.3%#Indirect economic impacts are estimated at 0.5 to 2.0 of the direct impacts. This is arrived at by subtracting the directimpacts from estimates of total output impacts using a range of total output impact multipliers from 1.5 to 3.0 based onavailable studies and incorporating a margin of safety. For example, Hall and Skaggs (2003) estimate a total output impactmultiplier of 1.61 for vegetable production in Southern New Mexico, Lillywhite et al. (2007) estimate an impact multiplier of1.55 for the New Mexico dairy industry and an estimate of 1.80 for the state’s pecan industry (Lillywhite et al., 2007)

*In 2006, New Mexico’s total gross domestic product was estimated at $76 billion (NMBBER, 2006), and therefore, evenestimated total economic losses greater than $300 million are less than 1% of the regional economic output.

Total Impacts*

-38.1

-8.4

-10.3

-100.7

-61.7

-14.2

-19.1 to -76.2

-4.2 to -16.8

-5.2 to -20.6

-50.4 to -201.4

-30.9 to -123.4

-7.1 to -28.4

-57.2 to -114.3

-12.6 to -25.2

-15.5 to -30.9

-151.1 to -302.1

-92.6 to -185.1

-21.3 to -42.6

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reports. For example, the 94,200 acre-feet of annualdeliveries to the San Juan Chama system – accountingfor 5% and 7.3% of native tributary inflow under current‘baseline’ and ‘2080 Dry’ scenarios, respectively –might be overly optimistic of available future flows(Christensen et al., 2004; NRC, 2007). After investing$275 million directly for its construction and making ita principal source of municipal water supply, the cityof Albuquerque is, for example, particularly vulnerableto a reduction in this diversion. Replacing reductionsin San Juan Chama water will exacerbate the conflictsand costs with agricultural users and potentially withnearby pueblos and tribes.

The effects of increased flooding are not addressedand could be a very important and damaging featureof climate change. As the ‘wet’ scenarios show andas indicated by both other climate change researchand even recent experience, there is a measurablelikelihood that summer precipitation associated withmonsoonal flow and thunderstorm activity couldincrease across the Southwest and in the Rio Grandebasin, in particular.9 The year 2006, for example, wasthe worst year in recent history for flooding and flooddamages in the Southern Rio Grande of New Mexicoand the El Paso, Texas region. The Rio Grande notonly left its banks but breached the levee in some areascausing millions in flood damages in El Paso and nearHatch, New Mexico. Recent assessments by theFederal Emergency Management Agency (FEMA)indicate that aging levee and flood control infrastructureis degrading in the region and provides much less floodprotection than previously indicated by 100 year flood-plain maps. With increasing numbers of both peopleand economic assets at risk, climatic changes thatincrease the frequency and intensity of summermonsoonal storms in the Southwest are surely toexacerbate the severity and frequency of flooddamages in the region.

Maintaining water quality is likely to be moredifficult under climate change. Reduced streamflowlowers assimilative capacity for both point and non-point pollutants. In non-attainment reaches of the riverlower TMDLs (total maximum daily load) might beexpected and could raise control costs. Climate changemight also lead some river reaches to fall out ofattainment and require TMDLs and higher pollutioncontrol costs. Salinity is of particular concern inSouthern New Mexico. Salinity concentrationscontinually rise as the Rio Grande journeys south,picking up loadings not only from urban wastewater

and agricultural return flows but from upwelling of saltconcentrated spring waters. With lower streamflowand runoff to dilute salinity concentrations could beexpected to rise. Currently, salinity is damaging only inthe extreme southern part of the watershed, particularlynear El Paso where concentrations in excess of 2000ppm are common. But without sufficient irrigationwater to leach and resist the buildup of salts, salinityproblems could become more common and severe forNew Mexico water users in the future. For example,each acre of irrigated farmland in Southern NewMexico can expect to receive 2-3 tons of salt eachyear from surface irrigation water (presently containingconcentrations between 500 ppm and 800 ppm). Ifsalinity concentrations rise as a result of reduced flows,additional irrigation water for salt leaching would beneeded to maintain agriculturally productive soils.

Climate change will affect New Mexico insignificant ways beyond dewatering rivers and streams.Increased drying of soils and significant reductions insoil moisture are likely with climate change as potentialevapotranspiration rises with increasing temperatures(Wang, 2005).10 These effects will compound theadverse effects of changes in the hydrology of runoffand water availability throughout New Mexico. Suchchanges will affect the quality and condition of NewMexico’s significant range- and forest-lands, which islikely to accelerate the severity and extent of forestfires but will likely diminish forage production onrangelands that will adversely impact livestock andwildlife across the region (Hurd et al., 2007). Suchchanges in range productivity and livestock productiondue to climate change will likely add to the estimatedagricultural sector impacts in New Mexico bydamaging its most important agricultural activity, beefcattle, accounting for about 40% of agricultural income,or $2 billion in cash receipts (NMDA, 2005).

Additional impacts of climate change on NewMexico’s people and resources are found in two recentassessments of climate change.11 Watkins (2006)surveys the literature on climate change, hydrology,and water-related impacts and their potential inferencesfor New Mexico. Her findings are substantiallyconsistent with those in this study, for example, shefinds a consensus on the likelihood for risingtemperatures and resulting hotter summers and milderwinters. Regarding snowpack and snowmelt, sheobserves that snowpack would be less enduring of risingwinter temperatures leading to earlier snowmelt andearlier peak runoff by 4 to 6 weeks, and a relative

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shift from snow to rain. Furthermore, her findingsconfirm the likelihood of increased evaporation lossesfrom streams, soils, and reservoirs, and increasedevapotranspiration. Finally, she even finds support forthe increased likelihood of more frequent and severeextreme events – both floods and droughts.

Ecological and cultural impacts are uncounted inthe assessment. Substantial changes in the naturalhydrograph and intensification of managed uses willseverely disrupt stream ecology and health, which mayhave additional implications for managing theendangered Rio Grande Silvery Minnow (Meyer, 1997).Additionally, long-standing Hispanic acequiascommunities will likely be early targets of watertransfers – causing local economic dislocation andincreased poverty (Rivera, 1996; Selcraig, 2002).Those communities that resist water transfers – eitherdue to restrictions that the State Engineer might placeon their water rights – for example, under New Mexicowater statutes that require consideration of the ‘publicwelfare’ when a water transfer is permitted (Bokum,1991), or owing to a particularly powerful degree ofcooperation among farmers, may also suffer as a resultof a hydrographic shift. Because of a lack of storageinfrastructure and vulnerable delivery systems, earlierand higher peak runoff could inundate acequias systemsand fields early in the season and provide insufficientwater during peak growing needs.

Additional related industries could also be negativelyaffected by climate changes and the loss of agriculture,ecosystem health, and damages to cultural resources.For example, tourism, arts, and recreation, whichtogether contribute $360 million to New Mexico’seconomy, might decline as the States’ uniquelandscapes, environment, and scenic opportunities arepotentially degraded by changes in riparian ecosystemsand agrarian land use (Rivera, 1996).

Each of these concerns taken individually addsconsiderably to the expected economic impacts fromclimate change. Taken together, there is sizableuncertainty in the extent to which economic damages,quality of life, ecosystem effects, and the overallseverity of potential harm are unaccounted for by themodel results. At least on a qualitative basis, there issignificant cause for concern about the nature andmagnitude of potential changes to New Mexico’seconomy, landscape, and quality of life as a result ofclimatic change.

FINDINGS AND CONCLUSIONS

Ultimately, water is used by people, plants andanimals – either directly consumed or indirectly usedin growing food and providing economic and ecologicalservices.

Under current climate there is virtually no sparewater in New Mexico. Imagine a very plausible future,as this study attempts, of significantly less water andat the same time significantly more people. Thoughimprovements in water-use efficiency will beincreasingly important to adopt and use – and whichwill likely be further stimulated by economic pricesthat are allowed to signal increasing scarcity – thisassessment puts light on the likely need to reorganizepatterns of water use or else risk significant disruptionin some of the important services provided by theState’s water resources.

A particular strength of the hydro-economicapproach is its capacity to identify where and to whatextent significant reorganizing of water uses will bepotentially most rewarding from a watershedperspective. In this case, the results indicate the mostexpedient and least economically disruptive adaptationis to transfer water from agriculture as it is needed tomaintain urban uses, growth, and economicdevelopment. In some ways these results highlight theobvious, there is a lot of water in New Mexico – 87%or more if lawns, parks and golf courses are included– that is consumed by plants. Plants that no doubtprovide food for people, for dairy cows, and for otherlivestock, but nonetheless plants; and the food theyprovide can almost surely be replaced by purchasesfrom other places. Of course, if water transfers fromagriculture are not as forthcoming as the hydro-economic model assumes, there could be significantlymore economic dislocation in other sectors of theeconomy.

As described previously, agriculture’s real value –and potentially the real loss New Mexico’s residents,tourists, and wildlife may experience – may not be somuch in the market value of its agricultural producebut in the auxiliary services that agriculture providesto the environment and quality of life. Losses andtransfers – amounting to perhaps more than 30% ofcurrent water use levels – will dramatically anddeleteriously affect agricultural systems, communities,and environments across the region. Therefore, in ourview, such losses as must be accommodated shouldbe regarded with both respect and regret, and

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fundamentally matched with an equal regard and effortto eliminate and guard against wasteful and capricioususes by urban and industrial water users. Absent thissentiment and action, farmers and rural communities– along with their political allies and representatives –will most certainly fight to defend their way of life andtheir legal and constitutional rights to use and controlwater for their benefit. And if farmers and ruralcommunities adopt this perspective, all the more likelythat it will also emanate from the pueblos, tribes, andacequias as well.

The following summarizes most of the key pointsdeveloped in this assessment:

• Climate change scenarios result in lesssnowpack, earlier snow melt, and higherevaporative demands. The resulting change inrunoff will affect vegetative cover in thewatershed and habitat for various species.

• Substantial and transformational disruption toNew Mexico’s agricultural and rural economycan be expected in the future as climatechanges. Under the best economic andinstitutional assumptions, direct economic lossesof up to $100 million are estimated and largelysuffered in the agricultural sector underrelatively severe climate changes by 2080, withan additional $200 million in indirect economiclosses anticipated.

• These economic estimates almost surelyunderstate the severity and extent of economic,social, and ecological disruption that is likely toresult from moderate to severe changes inclimate. For example, water transfers are likelyto entail significant transactions costs becauseof unsettled water right issues, includingprotracted litigation, water right adjudication,and transfer approval procedures that mustprotect against adverse effects on third-partiesand the ‘public welfare.’

• In addition, many sources of value and thatare potentially at risk under climate change havenot been captured in the analysis. Examplesof values that are not reflected include, theexpansive ecological and social services thatagriculture provides, additional ecological andenvironmental services by flowing water inriparian systems, and further erosion and lossof cultural values and services from historicalacequias and community irrigation systems.

The research findings suggest, particularly so whenthe limitations are given consideration, that NewMexico’s social, economic, and environmental systemsare highly vulnerable to changes and disruptions towater supplies potentially caused by climate change.Thus, the need is highlighted for water users,communities, organizations, and institutions in NewMexico at every level and in every sector to beginconsidering possible adaptive strategies for makingbetter use of their water resources.

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Booker, J. F. & Young, R. A. (1994). ModelingIntrastate and Interstate Markets for ColoradoRiver Water Resources. Journal ofEnvironmental Economics and Management, 26,66-87.

Booker, J. F. & Young Robert A. (1991). EconomicImpacts of Alternative Water AllocationInstitutions in the Colorado River Basin (Rep.No. 161).

Brooke, A., Kendrick, D., & Meeraus, A. (1988).GAMS: A User’s Guide. San Francisco, CA: TheScientific Press.

Cai, X. M., McKinney, D. C., & Lasdon, L. S. (2003).Integrated hydrologic-agronomic-economic modelfor river basin management. Journal of WaterResources Planning and Management-Asce,129, 4-17.

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Hall, T. Y. & Skaggs, R. K. (2003). Economic Impactof Southern New Mexico Vegetable Productionand Processing (Rep. No. Report 9). Las Cruces,NM: College of Agriculture and Home Economics,New Mexico Chili Task Force.

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Hurd, B. H. (2006). Water conservation and residentiallandscapes: Household preferences, householdchoices. Journal of Agricultural and ResourceEconomics, 31, 173-192.

Hurd, B. H., Brown, C., Greenlee, J., Grandados, A.,& Hendrie, M. (2006). Assessing Water ResourceVulnerability for Arid Watersheds: GIS-basedResearch in the Paso del Norte Region. NewMexico Journal of Science, 44, 39-61.

Hurd, B. H., Callaway, J. M., Smith, J. B., & Kirshen,P. (1999). Economic Effects of Climate Changeon U.S. Water Resources. In R.Mendelsohn & J.Neumann (Eds.), The Impact of Climate Changeon the United States Economy (pp. 133-177).Cambride, UK: Cambridge University Press.

Hurd, B. H., Callaway, M., Smith, J., & Kirshen, P.(2004). Climatic change and US water resources:From modeled watershed impacts to nationalestimates. Journal of the American WaterResources Association, 40, 129-148.

Hurd, B. H. & Harrod, M. (2001). Water Resources:Economic Analysis. In R.Mendelsohn (Ed.), GlobalWarming and the American Economy: ARegional Assessment of Climate ChangeImpacts (pp. 106-131). Northhampton, MA:Edward Elgar Publishing.

Hurd, B. H., Leary, N., Jones, R., & Smith, J. (1999).Relative regional vulnerability of water resourcesto climate change. Journal of the American WaterResources Association, 35, 1399-1409.

Hurd, B. H., Torell, L. A., & McDaniel, K. C. (2007).Ranch and Rangeland Management: Perspectivesof the Rangeland Economy and Its Relationship toWeather Information. 1-12. Las Cruces, NM.Ref Type: Unpublished Work

IPCC, Intergovernmental Panel on Climate Change,Working Group I (2007). Climate Change 2007:The Physical Science Basis, Summary ForPolicymakers Geneva, Switzerland: IPCC.

Jenkins, M. W., Lund, J. R., Howitt, R. E., Draper, A.J., Msangi, S. M., Tanaka, S. K. et al. (2004).Optimization of California’s water supply system:Results and insights. Journal of Water ResourcesPlanning and Management-Asce, 130, 271-280.

JWRPM. (2006). Special Issue: Economic-EngineeringAnalysis of Water Resource Systems. Journal ofWater Resources Planning and Management-Asce132[6], 399-512.Ref Type: Journal (Full)

Lillywhite, J. M., Crawford, T., Libbin, J., & Peach, J.(2007a). New Mexico’s Pecan Industry:Estimated Impacts on the State’s Economy (Rep.No. Bulletin-791). Las Cruces, NM: New MexicoState University, Agricultural Experiment Station.

Lillywhite, J. M., Sullivan, H., Crawford, T., & Ashcroft,N. (2007b). New Mexico Milk Production:Estimated Impacts on the State’s Economy (Rep.No. Bulletin-790). Las Cruces, NM: New MexicoState University, Agricultural Experiment Station.

Malone, E. L., Smith, J. B., Brenkert, A. L., Hurd, B.H., Moss, R. H., & Bouille, D. (2004). DevelopingSocioeconomic Scenarios: For Use inVulnerability and Adaptation Assessments 9New York: United Nations Development Program(UNDP), Global Environment Facility.

Meyer, J. (1997). Stream Health: Incorporating theHuman Dimension to Advance Stream Ecology.Journal of the North American BenthologicalSociety, 16, 439-447.

Nakicenovic, N. e. al. (2000). Special Report onEmissions Scenarios: A Special Report ofWorking Group III of the IntergovernmentalPanel on Climate Change Cambridge, UK:Cambridge University Press.

NM BBER (2004). Projected Annual PopulationGrowth Rates: New Mexico CountiesAlbuquerque, NM: Bureau of Business andEconomic Research, University of New Mexico.

NM BBER (2006). Real New Mexico Gross DomesticProduct by Industry. http://www.unm.edu/~bber/economy.htm [On-line]. Available: http://www.unm.edu/~bber/economy.htm

NMDA (2005). New Mexico Agricultural Statistics,2004 Las Cruces, NM: New Mexico Departmentof Agriculture.

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Nohara, D., Kitoh, A., Hosaka, M., & Oki, T. (2006).Impact of climate change on river dischargeprojected by multimodel ensemble. Journal ofHydrometeorology, 7, 1076-1089.

NRC (2007). Colorado River Basin WaterManagement: Evaluating and Adjusting toHydroclimatic Variability. Washington, D.C.:National Academies Press.

Null, S. E. & Lund, J. R. (2006). Reassembling HetchHetchy: Water Supply Without O’ShaughnessyDam. Journal of the American Water ResourcesAssociation, 42, 395-408.

Plog, S. (1997). Ancient Peoples of the AmericanSouthwest. London: Thames and Hudson.

Rivera, J. A. (1996). Irrigation Communities of theUpper Rio Grande Bioregion: Sustainable ResourceUse in the Global Context. Natural ResourcesJournal, 36, 491-520.

Selcraig, B. (2002). Digging Ditches: Narrow, HumbleIrrigation Ditches Called Acequias Sustain anEndangered Way of Life. Smithsonian, 32, 54-63.

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Tanaka, S. K., Zhu, T. J., Lund, J. R., Howitt, R. E.,Jenkins, M. W., Pulido, M. A. et al. (2006). Climatewarming and water management adaptation forCalifornia. Climatic Change, 76, 361-387.

Vaux, H. J. Jr. & Howitt, R. E. (1984). Managing WaterScarcity: An Evaluation of Interregional Transfers.Water Resources Research, 20, 785-792.

Wang, G. L. (2005). Agricultural drought in a futureclimate: results from 15 global climate modelsparticipating in the IPCC 4th assessment. ClimateDynamics, 25, 739-753.

Ward, F. A., Hurd, B. H., Rahmani, T., & Gollehon, N.(2006). Economic impacts of federal policyresponses to drought in the Rio Grande Basin.Water Resources Research, 42, W03420.

Ward, F. A., Young, R., Lacewell, R., King, J. P., Frasier,M., McGuckin, J. T. et al. (2001). InstitutionalAdjustments for Coping with Prolonged andSevere Drought in the Rio Grande Basin LasCruces, NM: New Mexico Water ResourcesResearch Institute.

Watkins, A. (2006). The Impact of Climate Changeon New Mexico’s Water Supply and Ability toManage Water Resources Santa Fe, NM: NewMexico Office of the State Engineer.

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Balance Model for Climate Impact Assessment ofRiver Basin Runoff. Water ResourcesDevelopment, 12, 121-139.

Yates, D. & Strzepek, K. (1994). Comparison ofmodels for climate change assessment of riverbasin runoff (Rep. No. WP-94-46). Laxenburg,Austria: (IIASA) International Institute for AppliedSystems Analysis.

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ACKNOWLEDGEMENTS

This research was supported by a grant from theWilliam and Flora Hewlett Foundation, which madecollaborations possible and provided the opportunity towork with such a gifted and talented group ofresearchers and academics. Of these we are entirelygrateful for the support and encouragement of JoelSmith of Stratus Consulting and Dr. Ken Strzepek ofthe University of Colorado. Special appreciation to Dr.Coonrod’s graduate assistants, Alandren Etlantus, KellyIsaacson, and Isaiah Pedro, for their expertise inapplying the WATBAL model. Thanks and appreciationis extended to Anne Watkins of the New Mexico Officeof the State Engineer and to Dr. Dave Gutzler of theEarth & Planetary Sciences Department at theUniversity of New Mexico for their work andcontributions addressing potential climate changeimpacts on New Mexico’s water resources, and toDrs. Jim Booker of Siena College and Frank Ward ofNew Mexico State University, whose work Dr. Hurdproudly stands upon as a result of their efforts tocarefully model the hydro-economy of the upper RioGrande. Our appreciation extends to Drs. Jay Lund(UC Davis) and Bonnie Colby (U of Ariz.) for theirconsiderate and careful review of the final manuscriptand very helpful suggestions. Finally, Dr. Hurd wouldlike to thank the leadership of the AgriculturalExperiment Station of New Mexico State Universityfor their ongoing support of his research program.

ENDNOTES

1A growing consensus among anthropologists attributesthe regional collapse of indigenous settlements priorto European arrival to multiple factors, amongwhich importantly include climatic extremes (Plog,1997). Peoples such as the Anasazi, Hohokam and

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Mogollon abandoned long-held settlements duringa period that tree-ring analysis has identified as‘the Great Drought’ at the end of the 13th century.

2The Intergovernmental Panel on Climate Change(IPCC) published a Special Report on EmissionsScenarios (SRES, Nakicenovic et al. 2000), whichconsisted of four families of emissions scenariosthat ranged from very low population and very higheconomic growth (A1), to very high population andsomewhat low economic growth (A2), tosomewhat low economic growth and moderatepopulation (B2), and to moderate economic growthand low population (B1). Of these, the A1Bscenario comes closest to U.S. governmentprojections for population and income growth andto the ‘business as usual’ emissions projection,known as IS92a. Note, however, that the A1Bscenario also has the highest emissions of sulfateaerosols of all the SRES scenarios, with a peak in2030 and rapid decline thereafter.

3In addition to the limitations and assumptions previouslydiscussed, the RGHE model uses a simplifiedrepresentation of groundwater and aquifer storageand its connectivity to surface water systems. Forexample, Albuquerque currently relies ongroundwater for its public water supply system.However, the hydrologic connectivity of surface-and ground-water systems is well recognized,including the requirement that future groundwaterdevelopment requires offsetting retirement ofsurface water rights. The model assumes that overthe long-run, water use is constrained by availablesurface water supplies. To implement thisperspective, in the model groundwater and aquiferuse must be offset such that by the terminal modeltime period (i.e., after 30 years) aquifer volumesare returned to their initial storage volumes.

4Exception is made for the managed transfers fromthe Closed Basin Project (CBP) and from the SanJuan Chama (SJC) trans-basin diversion. For theCBP and SJC, annual deliveries of 21 kaf/yr and94.2 kaf/yr are assumed (the latter is based onaverage importations since 1970; however, 110 kaf/yr is authorized). Imported water is distributedacross months in approximate proportion to systemwater demands. Furthermore, imports are assumednot to vary with climate change. According torecent research on the effects of climate changeon the Colorado River (NRC, 2007; Christensenet al., 2004) – the source of the SJC water – it

may be a strong assumption that this amount ofwater will be available in the event of significantclimate change. The potential reduction or loss ofthis water will have a significant impact onAlbuquerque water users.

5This stands in contrast to earlier studies (e.g., Hurd etal. 1999) where the modeled shift in agriculturaldemand resulted in an expansion of so-calledproducers’ surplus. Here, the value of agriculturalproduction is maintained on the condition that thenecessary water is supplied to meet the change inirrigation requirements. As water is then reduced,so then is the generated economic value. It is alsoassumed that relative agricultural prices are NOTaffected by climate changes – a strong assumptionthat depends on sector-wide market effects thatare beyond the present scope of analysis.

6See Hurd (2006) for discussion of current trends inNew Mexico residential landscapes.

7The slopes of the curves in Figure 12 are relativelyconstant. This constancy reflects the assumedabsence of changes in streamflow variability, andthe primary focus of the present analysis onchanges in average conditions. There is quitesignificant natural variability in the Rio Grandewatershed, variability that is captured in the currentanalysis. Climate change, however, could changerunoff variability and, if increased, furtherexacerbate the relative likelihood of drought and/or flood events. Changes that increase runoffvariability would result, for example, in a relativeflattening of the scenario curves shown in Figure12.

8Implicit model prices are the marginal values that areestimated by observing the ‘shadow price’ on watersupply constraints in the model. Though these‘values’ are illustrative of the relative values underdifferent population and water supply conditions,they are not necessarily indicative of actual marketprices that are a complex function of many factorsaffecting local water demand and water supplyconditions, including speculative development.These estimated values are most reflective of themarginal value of water in agriculture and notindicative of the willingness to pay for water by,for example, municipal and industrial water users.

9Nohara et al. (2006) examine the effects of climatechange using 19 GCMs simulating the SRES A1Bscenarios (just as in this study) on the hydrologyand river discharge of 24 of the world’s most

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important river basins, including the entire RioGrande system. Results for the Rio Grande showwide divergence in seasonal runoff across theGCMs, with several showing pronounced summerrunoff that is most closely associated with intensesummer storms and the likelihood of regional flashfloods.

10Wang (2005) examines changes in soil moistureconditions across 15 GCMs and finds substantialconsistency across the models in projectingsignificant reductions in soil moisture in all seasonsfor the southwestern United States.

11These assessments were initiated under GovernorRichardson’s Climate Change and GreenhouseGas Reduction Executive Order (05-033) and wereconducted by New Mexico’s Office of the StateEngineer on potential impacts on the waterresources (Watkins, 2006) and by the New MexicoEnvironment Department (ATWG, 2005).

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