Simulation and Analysis of Conjunctive Use with MODFLOW's

Simulation and Analysis of Conjunctive Use with MODFLOW’s Farm Process by R. T. Hanson1,W.Schmid2,C.C.Faunt3, and B. Lockwood4

Abstract The extension of MODFLOW onto the landscape with the Farm Process (MF-FMP) facilitates fully coupled simulation of the use and movement of water from precipitation, streamflow and runoff, groundwater flow, and consumption by natural and agricultural vegetation throughout the hydrologic system at all times. This allows for more complete analysis of conjunctive use water-resource systems than previously possible with MODFLOW by combining relevant aspects of the landscape with the groundwater and surface water components. This analysis is accomplished using distributed cell-by-cell supply-constrained and demand-driven components across the landscape within “water-balance subregions” comprised of one or more model cells that can represent a single farm, a group of farms, or other hydrologic or geopolitical entities. Simulation of micro-agriculture in the Pajaro Valley and macro-agriculture in the Central Valley are used to demonstrate the utility of MF-FMP. For Pajaro Valley, the simulation of an aquifer storage and recovery system and related coastal water distribution system to supplant coastal pumpage was analyzed subject to climate variations and additional supplemental sources such as local runoff. For the Central Valley, analysis of conjunctive use from different hydrologic settings of northern and southern subregions shows how and when precipitation, surface water, and groundwater are important to conjunctive use. The examples show that through MF-FMP’s ability to simulate natural and anthropogenic components of the hydrologic cycle, the distribution and dynamics of supply and demand can be analyzed, understood, and managed. This analysis of conjunctive use would be difficult without embedding them in the simulation and are difficult to estimate a priori.

Introduction resources within a watershed. Conjunctive use of water is Sustainability of water resources is subject to chang- the joint use and management of surface water and ing demands and supplies that are integrated through groundwater resources to maximize reliable supply conjunctive use and movement of all of the water and minimize damage to the quantity or quality of the resource. The use and movement of water resources also are constrained by physical properties and other 1Corresponding author: California Water Science Center, Water Resources Discipline, U.S. Geological Survey, 4165 Spruance circumstances such as governance, social, or economic Rd., Ste. 200, San Diego, CA 92101; 619-225-6139; fax: 619-225- constraints as well as urbanization; climate change and 6101; [email protected] ecological requirements; and water and soil chemistry 2 Department of Hydrology & Water Resources, 1133 E James and contamination. Increased agricultural productivity E. Rogers Way, University of Arizona, Tucson, AZ 85721. 3U.S. Geological Survey, California Water Science Center, San affects the local economy, resulting in prosperity, growth, Diego Projects Office, 4165 Spruance Road, Suite 200, San Diego, and further transformation of agri-business to more CA 92101. dynamic and intensive farming with higher profit crops, 4Pajaro Valley Water Management Agency, 36 Brennan Street, multiple croppings, and multiple annual growing sea- Watsonville, CA 95076. sons. This growth depends on a reliable source of water, Received March 2010, accepted May 2010. Journal compilation ©2010NationalGroundWaterAssociation. which may be quantified through a systematic agricul- No claim to original US government works. tural water budget. Such budgets assess the water supply doi: 10.1111/j.1745-6584.2010.00730.x from precipitation, surface water, and groundwater and

NGWA.org GROUND WATER 1 water demands of agriculture and urban areas. Critically, this is often based on invariable stream stage, based the budgets can be used to assess the potential effect of on fixed stream stages and conductances (instead of climate variations or climate change. Hydrologic budgets conductivities), and are based on line sinks/sources for complex systems are best assessed with an inte- instead of distributed cell-by-cell point sinks/sources (e.g., grated model that simulates all components of interest. MIKE-SHE). This can be accomplished with a hydrologic model that MF-FMP is a unique and versatile alternative fully links the movement and use of demand-driven and that provides fully coupled, cell-by-cell distributed, supply-constrained components of a hydrologic system. fully iterative simulation of supply-constrained and In addition to MODFLOW (Harbaugh 2005) with demand-driven conjunctive use, and movement of water the Farm Process (MF-FMP; Schmid et al. 2006a, 2006b; from natural and anthropogenic sources. MF-FMP differs Schmid and Hanson 2009a, 2009b), which is considered from the aforementioned other models in its ability to sim- in this article, a number of hydrologic models include ulate the conjunctive use of surface and subsurface water the simulation of precipitation, land use based runoff resources to meet agricultural and urban water demands processes, plant consumptive use, and their effects on in the presence of multiple constraints on surface water groundwater dynamics within the hydrologic cycle. Some and groundwater supply. Constraints might include, for link watershed or channel routing models to groundwater example, surface water rights seniorities and head con- models of finite-difference type such as SWATMOD straints on pumpage from multiaquifer wells. Additional (Sophocleous et al. 1999; Sophocleous and Perkins 2000), unique features are reviewed later in the section “Farm GSFLOW (Markstrom et al. 2008), and MF-FMP; finite- Process Features.” element type such as IWFM (California Department This article describes the major features and lim- of Water Resources 2005a, 2005b; Dogrul 2009) and itations of MF-FMP and then demonstrates MF-FMP MIKE11-FEFLOW (Liua et al. 2007; Monninkhoff et al. using two uniquely different case studies. The first case 2009; Diersch 1993); or Dupuit-Forchheimer type such as study is in the Pajaro Valley of coastal California. It WEHY (Kavvas et al. 2004). In some models, percolation involves micro-agriculture conjunctive use of predomi- aggregated over watersheds, subwatersheds, or hydrologic nantly groundwater that is to be combined with surface response units is instantly applied as groundwater recharge water from an aquifer storage and recovery (ASR) and at the water table without the option of delayed recharge recycled water. The second case study is in the Central (e.g., SWATMOD or IWFM). Others route the percolation Valley, California. It involves macro-agriculture conjunc- to the water table using methods based on Richard’s tive use with subregions dominated by surface water or equation of flow through variably saturated media. For groundwater. MF-FMP is used to evaluate the sources of example, the one-dimensional (1D) Richard’s equation is irrigation water for more than 15 years that include dry used in HYDRUS-MODFLOW (Twarakavi et al. 2008), and wet conditions. MODFLOW-SURFACT (Panday and Huyakorn 2008), MODHMS (Panday et al. 2009; Kool 2009), and MIKE- SHE (Refsgaard and Storm 1995; Graham and Butts Farm Process Features 2005). A kinematic wave approximation to the 1D The Farm Process (Schmid et al. 2006a, 2006b; Richard’s equation is used to simulate delayed recharge Schmid and Hanson 2009a, 2009b) for MODFLOW-2005 with the unsaturated zone flow (UZF) package (Niswonger (Harbaugh 2005) (MF-FMP) was developed to provide et al. 2006) of MODFLOW in GSFLOW and MF- detailed hydrologic budgets for all or part of a hydro- FMP. The three-dimensional Richard’s equation is used logic system and to examine how such budgets change in ParFlow-CLM (Maxwell and Miller 2005, Kollet over time. It represents the components of evaporation and Maxwell 2008) and Hydrogeosphere (Therrien and and transpiration derived from precipitation, irriga- Sudicky 1996; Therrien et al. 2004). In general, models tion, and groundwater on a cell-by-cell basis within using Richard’s equation directly require fine grids and user-defined water-balance subregions (WBS) (Figure 1). high computational effort, and require data about the MF-FMP provides the ability to simulate and analyze a soil-water constitutive relationships that are often not wide range of natural and anthropogenic components of readily available. The kinematic wave approximation water use and movement that collectively represent con- provides a fast alternative that is well suited to large-scale junctive use. models. Supply options in MF-FMP allow three levels Some models that link watershed or channel rout- of simulation for sources of surface water deliveries: ing models to groundwater models facilitate cell-based (1) Nonrouted deliveries may represent water transfers capillary uptake from groundwater by evapotranspiration from multiple sources to multiple users, where no (ETgw). For example, SWATMOD simulates cell-based conveyance is simulated and the demand is not driven by ETgw based on root-zone or crop-type parameters uniform local land use; (2) semi-routed surface water deliveries over larger watershed entities. For others, evapotranspira- for which the final conveyance is not explicitly simulated tion is simulated from a soil zone within the landscape and demand is driven by local land use; and (3) fully model that does not directly couple with groundwater routed surface water deliveries that can exclude or uptake (e.g., IWFM). If watershed or channel routing include the simulation of the final conveyance of surface models allow for aquifer-head-dependent seepage, then water to the WBS and demand is driven by local land use.

2 R.T. Hanson et al. GROUND WATER NGWA.org Figure 1. Schematic representation of root zone and land surface ﬂow processes simulated by MF-FMP.

MF-FMP fully couples the following system 3. Uptake from groundwater (FMP) with groundwater components: flow simulated by MODFLOW’s groundwater flow (GWF) process. 1. Precipitation (Figure 1) input (FMP). 4. Transpiration (Figure 1) through vegetation of water 2. Irrigation (Figure 1) demand supplied in order of derived from precipitation, irrigation, and groundwater decreasing priority by sources separately (FMP). 5. Evaporation (Figure 1) from bare soil of water derived • Nonrouted deliveries (FMP). from precipitation, irrigation, and groundwater sources • Semi- or fully routed surface water deliveries stream- separately (FMP). flow or surface water rights constrained stream diver- 6. Surface returnflows (Figure 1) from precipitation and sions (FMP and streamflow routing [SFR] package). irrigation in excess of consumptive use as overland • Groundwater pumpage from capacity- or head- runoff to stream network (FMP and SFR). constrained single- or multinode wells (FMP and 7. Subsurface returnflows as instant deep percolation multinode well [MNW] package). or delayed recharge (Figure 1) (FMP and UZF) and • Potential other external water supplies (FMP). optionally also as well injections (FMP and MNW).

NGWA.org R.T. Hanson et al. GROUND WATER 3 MF-FMP is based on a hydrologic accounting system nonirrigation water demands, such as municipal, indus- that is conceptualized to include a set of user-defined trial, and domestic demands, percolation requirements for WBS. There is no limit to the size of a WBS; they artificial recharge, and water for nonagricultural uses. can range from one to many model cells and each can Demands for water can also occur from natural or riparian represent an entire watershed, an irrigation district, a vegetation. single farm, or a single-cell entity. Each model cell can be MF-FMP facilitates the analysis of the following: assigned one crop, virtual crop (i.e., a composite of several similar actual crops), or land use. For example, in the • Historical and future agricultural, urban, and natural Pajaro example described later, several single-cell WBS land use and coupled surface-water/groundwater use are used to represent ASR units or wellfields and multiple- components. cells WBS are used for groups of farms that occur within • Analysis of alternative water use subject to climate subwatersheds, or as a collection of disjoint cells that changes or in response to policies and projects trying represent the urban areas. The WBS can be prioritized to adapt to climate change. in terms of the water they supply and(or) consume. • Agricultural water use based on readily available data The model algorithm is iterative and proceeds through (use MF-FMP to calculate surface water deliveries, the five steps shown in the supporting information groundwater pumpage, recharge, evapotranspiration, (Figure S1): and runoff). • Optimal or improved use of water under drought or 1. Irrigation demand—Estimate and simulate the con- nondrought conditions by simulating policies or projects sumption of water on the landscape on a cell-by-cell that balance water demand and supply. basis within each WBS by natural and agricultural veg- • Storage of water in times or regions of higher abundance etation (or other prescribed mechanisms) with water and release during peak demand (ASR systems). potentially supplied from local sources, such as pre- • Water markets between wetter supply regions and drier cipitation or direct uptake of groundwater. Irrigation demand regions. demand is estimated and simulated on a cell-by-cell basis within each WBS (Figure S1). As in MODFLOW, MF-FMP time steps are grouped 2. Identify delivery components—Identify and estimate into stress periods. Time-dependent input such as specified delivery components, defined as irrigation demand flows and heads are defined for each stress period. While produced because precipitation or local groundwater stress periods can be of any length and can include uptake do not provide supply sufficient to meet evapo- any number of time steps, time steps of long-term transpirative consumption (Figure S1). The model can regional MF-FMP models used to analyze conjunctive first provide water from nonrouted deliveries (i.e., use over decades are typically on the order of weeks deliveries without simulation of conveyance) that rep- or longer. At these time steps, and for medium root- resent water market transfers, then semi- or fully routed zone depths, MF-FMP always assumes all inflows into surface water deliveries if available and needed or the root zone to be equal to all outflows. This assumption specified, and then groundwater pumpage if available is based on the asymptotic approach of inflows and or needed. outflows simulated by the Richard’s equation-based 3. MF-FMP—MODFLOW, with the recharge estimate HYDRUS-2D (Simunek et al. 1999) simulations for and proposed pumping demands from steps 1 and 2, various crop and soil types, root zone and capillary- solves for groundwater heads and flows and resulting fringe depths, water table configurations, and levels of streamflow gains and losses (Figure S1). potential evapotranspiration after time periods common 4. Check constraints—Compare simulated streamflow, for MODFLOW time steps. These numerical experiments pumpage, and landscape flows or consumption to any are reported in Schmid (2004) and Schmid et al. (2006a). potential restrictions or priorities (Figure S1). If no To understand the meaning of this equality assump- restrictions or priorities are violated, the simulation tion, consider the flows into and out of the root zone. advances to the next stress period. If restrictions or In MF-FMP, root-zone inflows that meet the crop evapo- priorities are violated, return to step 1 to develop an transpirative requirements are precipitation, irrigation, and alternative estimate of irrigation demand. root uptake from groundwater. Outflows are the six com- 5. Returnflow components—After estimates of delivery ponents of transpiration and evaporation (Figure 1), runoff and consumption are made, returnflow components are and deep percolation beneath the root zone. Over a time estimated and simulated for recharge and runoff by step, the equality assumption means that the inflows equal both FMP and the UZF package (Niswonger et al. the outflows, but the values of the individual components 2006) to the SFR package (Niswonger and Prudic can change. 2005; Prudic et al. 2004) (Figure S1). In MF-FMP, potential crop evapotranspiration can be specified or calculated as the product of specified The multiple sources and demand components that reference evapotranspiration and crop coefficients. If the can be simulated for each WBS yield a wide spectrum of specified potential crop evapotranspiration or specified water supply and demand configurations across the area of crop coefficient are derived under nonstressed conditions, simulation. In addition, MF-FMP can be used to simulate for which water is adequate (Allen et al. 1998), MF-FMP

4 R.T. Hanson et al. GROUND WATER NGWA.org optionally can simulate the reduction of potential tran- if they are located elsewhere. Limits on infiltration can spiration due to anoxia and wilting for irrigated and occur indirectly through the linkages with the UZF pack- nonirrigated areas (Schmid et al. 2006a, 2006b). Thus age where infiltration to the uppermost aquifer may be in MF-FMP, climatic and soil conditions can change delayed by replenishment of unsaturated storage (changes crop demands owing to stressed conditions. For crop in storage are simulated in the parts of the system rep- coefficients derived under stable unstressed field condi- resented by the UZF package). Alternatively, infiltration tions, more or less water may be used. There is also a is rejected if it exceeds the saturated hydraulic conduc- user-specified evaporative fraction of evapotranspiration tivity or groundwater levels are close to land surface related to irrigation which can reflect a further reduction (Figure S1). Rejected infiltration is discharged to surface from a potential to an actual evaporation (Ec-pot to Ec-act). runoff. This further reduction is generally applied to bare-soil From a conjunctive use perspective, the flow connec- areas that are not fully wetted for each crop or land-use tions within MF-FMP can be as important as the GWF and type. pumpage components (Figure S2). The coupling of GWF The Farm Process links features in one of three to conjunctive use through multiaquifer wells, stream- ways as aquifer interaction, root uptake, and deep percolation allows for multiple sources and sinks connected to the 1. heads, where the head simulated by one feature is GWF system (Figure S2). These linkages then afford the imposed on another feature opportunity to embed the physically based constraints 2. head-dependent flows, where groundwater heads sim- from other packages within MF-FMP to store, retard, or ulated in one feature results in flow to another redirect flows (Figure S1). For example, the MODFLOW MODFLOW process or package subsidence (SUB) package (Hoffmann et al. 2003) can 3. direct transfer of flows, where flow simulated by one be used to simulate land subsidence related to increased feature is imposed on or required by another feature. irrigation (Figure S2). Jointly, these links produce a multi- faceted simulated system of interconnected hydrology that MF-FMP iterates to ensure conservation of water allows multiple hydrologic features, including the ground- and consistency of heads throughout the system. Head- water system, to account for responses of the hydrologic dependent flows and direct transfers of flows are used to system to external stresses. It also allows for the analysis simulate interaction between stream networks and over- of uncertainties in all simulated aspects of the system. land flow using the SFR package (SFR1—Prudic et al. As with any model, MF-FMP has limitations in the 2004; SFR2—Niswonger and Prudic 2005) and UZF present version (FMP2, ver 1.0, March 2010). Three package (Niswonger et al. 2006), and through multiple- potential limitations are listed here. First, MF-FMP aquifer wells through the MNW package (Halford and does not support daily or weekly, local-scale irrigation Hanson 2002; MNW2—Konikow et al. 2009). Some of scheduling: MF-FMP was designed to be used at scales these features are linked to each other and have been larger than individual fields and for periods of time linked to FMP to represent natural and engineered path- that can span months to centuries. Second, MF-FMP ways of water use and movement (Figure S1). These calculates actual evapotranspiration based on pressure- links provide a natural set of supply and demand rela- head dependent stress responses and root zone pressure tions as well as embedded physically based constraints heads. The stress response is calculated using analytical that can be imposed as part of the simulation and concep- solutions of vertical steady-state, Richard’s equation tual model of a developed hydrologic system (Figure S1). based, pressure-head distributions assumed for relatively For example, diversion of surface water deliveries can longer time steps common in groundwater modeling such be subject to availability of streamflow or diversion lim- as weeks. That is, MF-FMP assumes steady-state soil its through SFR or from water rights constraints through moisture storage within all time steps that are time periods FMP (Figure S1). Constraints on pumpage either can common in groundwater modeling and currently does occur through the pumpage capacity of wells delivering not simulate changes in soil-moisture storage. This may water to a subregion directly in FMP or can addition- result in poor approximations in some settings such as ally be constrained by head or drawdown limits imposed for dry-land farming or some climate change scenarios of through the MNW package (Figure S1). Similarly, inef- natural vegetation that do not include phreatophytic uptake ficient losses to runoff from precipitation or irrigation, of groundwater. Third, MF-FMP has simple options for or rejected infiltration can be linked to natural or artifi- runoff of inefficient losses based on fractions of applied cial supplies through the linkage with the SFR or UZF water or local slope calculations. For additional details package (Figure S1). This hierarchy of optional embed- of other potential limitations that may affect certain ded constraints builds a system of use and movement hydrologic settings or applications, the reader is referred that can include preferences such as sources of water and to Schmid et al. (2006a). physically based limits for selected components or flow linkages. These flow linkages also require specification of additional associations, such as attributing certain surface Case Studies water diversion locations to farms. Similarly, wells must Detailed conjunctive use simulations using MF-FMP be associated with the WBS, where the water is used even at the micro-agricultural scale with detailed land use and

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Soquel Creek Central Area of River and streams map Water District Water boundary CALIFORNIA District City of Watsonville Monterey boundary service area Bay SA Pa cifi boundary c Oce N an T A CRUZ MPajaro Valley Water Management Agency boundary "Urban" TS farm Monterey Bay area Area of sea water Water-balance iintrusionntrusion region boundaries AAquiferquifer StorageStorage AActivective modelmodel aandnd RecoveryRecovery gridgrid boundaryboundary

Monterey Submarine Canyon Area shown oonn ffigureigure 2B2B 0 5 Miles 0 5 Kilometers

Modified from Hanson et al., 2008

Figure 2. Maps showing selected (A) water-balance subregions used to in PVHM to assess conjunctive use, coastal pumpage, and related sea water intrusion; (B) close-up view of coastal region with the coastal distribution system, ASR, recycled water and supplemental groundwater supplies used to analyze conjunctive use and alternative supplies in Pajaro Valley, California (modiﬁed from Hanson et al. 2008). climatology have been or are in the process of being within the Pajaro Valley (Figures 2A and 2B) and have completed in the southern Rincon Valley of New Mex- resulted in overdraft and sea water intrusion (Hanson ico (Schmid et al. 2009c), Modesto Irrigation District, 2003a, 2003b). The Pajaro Valley Water Management California (Phillips 2010), Cuyama Valley, California Agency (PVWMA) developed a basin management plan (Hanson 2010), and the Pajaro Valley, California (Hanson (BMP) to provide additional local supplies to replace et al. 2008) (Figure S3). Regional hydrologic investiga- coastal pumpage, and thereby attempt to limit or reduce tions using MF-FMP include the Central Valley, Califor- sea water intrusion (The Pajaro Valley Water Management nia (Faunt et al. 2009c), lower Rio Grande, New Mexico Agency 2007; Hanson et al. 2008). The BMP includes (Christenson 2010), and High Plains (Peterson 2010) an ASR system and a coastal distribution system (CDS). (Figure S3). Even when the WBS accounting units are The ASR system captures and stores local winter runoff large, cell-by-cell designation of soils, vegetation, land and the CDS system is a pipeline network that distributes surface, and climate features within each WBS allows water from the ASR, inland supplemental city water sup- substantial detail to be represented. In this article, we ply wells, and, in the future, recycled water. The water demonstrate selected features of MF-FMP using the mod- is delivered for irrigation to replace coastal groundwa- els of the Pajaro Valley and Central Valley. ter pumpage (Figure 2B). The ASR system was initially implemented in 2002 with the ability to deliver about 1.4 million m3(1150 acre-feet) water to farms in the areas Pajaro Valley subsequently deﬁned as WBS 8, 16, and 17 for the MF- Pajaro Valley is located along the Monterey Bay, FMP model (Figure 2B). In 2007, the CDS was extended about 129 km (80 miles) south of San Francisco, Cali- to serve farms in most of the central coastal region fornia (Figures S3 and 2A). The valley comprises 31,080 (Figure 2B). In addition, completion of the recycled water ha (120 mi2), about half of which is farmland that treatment plant (RWTP) in 2009 provided an additional relies almost exclusively on groundwater to supply irri- source of water to the CDS. Treated waste water is gation water. Increases in population and cultivation have blended with groundwater supplied by City of Watsonville increased the competition for available water supplies wells (Figures 2B and 3). The completed CDS will be able (groundwater, captured surface water, and recycled water) to deliver about 8.8 million m3(7150 acre-feet) water per

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MONTEREY BAY

Figure 2. Continued. year to most of the coastal farms within the Pajaro Val- as a percolation requirement. In MF-FMP input, the ley. This could represent about 16% of the 54.6 million monthly percolation rate is entered as a water demand m3(44,230 acre-feet) average agricultural pumpage for the using the crop coefficient input variable. The PVWMA period 2004 to 2008. water right allows up to about 8700 ha/year (2000 acre- The Pajaro Valley Hydrologic Model (PVHM) was feet/year) to be diverted from Harkins Slough to the developed to analyze the BMP project components Sunset Dunes ASR recharge pond between January and as the water supply is partially converted from a May. This water is supplied to the pond after water predominantly groundwater system to a system that also provided by diverting flows from the local runoff is relies on captured runoff and reclaimed water. The PVHM captured as routed surface water flows of the Harkins uses MF-FMP to simulate the diversion, storage, and Slough from the Harkins Slough Diversion. The water redistribution of water from multiple sources to multiple delivered to the ASR is reduced during the recharge cycle farms with a hierarchy of priority of supply sources on a months (January to May) based on measured reduction of monthly basis. The operation of the CDS was simulated the infiltration rate (Schmidt et al. 2009) which reflects as part of PVHM for the 5-year period 2002 to 2006 to results in reduced deliveries that are more aligned with evaluate the potential effects of conjunctive use in lieu historical infiltration because there is no sense delivering of pumpage for WBS 8, 16, and 17 (Figure 2B) (Hanson water that cannot be infiltrated. This then constrains the et al. 2008). supply available from the ASR. Water from the ASR The aquifer-storage-and-recovery (ASR) recharge is pumped and delivered through the CDS during the pond (Sunset Dunes recharge pond), ASR well, and two growing season from May to October. supplemental wellfields are each simulated by one-cell Water from Harkins Slough is supplied as local WBS. The ASR demand for recharge water is formulated runoff, and is climatically variable. Diversion of flow

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Figure 3. Diagram showing (A) structure of the local deliveries and (B) the hierarchy of order of operation of the ASR and CDS deliveries as part of the conjunctive use simulated by MODFLOW with the Farm Process within the Pajaro Valley, California (modified from Hanson et al. 2008). from Harkins Slough to the ASR when water is available as local runoff is simulated using the SFR package linked to FMP. Another source is needed to provide water during temporary shortages. There is no in-line storage in the CDS. Shortages in delivery demand are addressed by augmenting the ASR operation with pumpage from supplemental wells (Figure 2B) that follow a prescribed priority of deliveries (Figure 3). With the completion of the RWTP in 2009, the CDS also receives deliveries of recycled treated waste water, which is blended with additional groundwater supplied by the City Figure 4. Graphs showing (A) the temporal distribution of of Watsonville wells (Figures 2B and 3). The crop water the surface water constrained supply and reported deliveries. demand in the WBS governs the delivery required from (B) The multiple farm driven demand for the combined the local supply sources (Figure 3). The user-specified simulation of the aquifer storage and recovery system and order of simulated sources for deliveries used with MF- coastal delivery system as part of the conjunctive use FMP is aligned with the priorities set by PVWMA. The simulated by MODFLOW with the Farm Process within the Pajaro Valley, California. priorities for water delivered to WBS, from highest to lowest, are (1) ASR; (2) recycled water (starting in 2009; not simulated for the results reported here); (3) remote supplemental wells; (4) blend wells; and (5) local coastal city well deliveries closely match reported deliveries farm wells. Groundwater pumpage is constrained by the for 2002 to 2006 (Figure 4). The ASR wellfield and well capacity of each CDS supply well and by well-by- other lower ranked supplemental wellfields deliver the well water-level limits defined in the MNW package. cumulative demand of the receiving WBS demand The Harkins Slough diversion supplied 4.3 hm3 locations without pumpage from the coastal farm wells. (3470 acre-feet) of metered water deliveries to the ASR Preliminary results from this simulation of conjunc- operation between 2002 and 2006 (Figure 7A). The tive use demonstrates how MF-FMP can simulate a CDS delivered 2.6 million m3 (2100 acre-feet), which complex conjunctive use plan with a climatically variable represents about 61% of the total water delivered to the source, variable priority of sources, and a variable agricul- ASR. Deliveries of water pumped back from stored ASR tural demand on a monthly basis (Figure 4B). However, recharge represent about 21% of the water recharged at matching historical deliveries can still be problematic as the ASR and 35% of the total water delivered by the other factors such as variable pumping rates and hours of CDS. Thus, some local recharge occurred from water delivery operations may also control the reported deliv- not directly recaptured by the ASR operation. Simulated eries along with estimated demand. This is the case in monthly ASR deliveries, supplemental pumpage, and the this example for the months of August through October

8 R.T. Hanson et al. GROUND WATER NGWA.org 2004 for the supplemental well deliveries where simple demand-driven deliveries overestimate actual deliveries. In addition, the simulated supply priorities can be changed N on a monthly basis, which enables evaluation of different 1 12 delivery scenarios as was done for this simulation for selected months when the ASR wells were out of service. The MF-FMP model is used to asses BMP projects 2 under different climatic conditions, including wet periods and droughts, and to test the effects of CDS deliveries to more coastal farmers. The model will help PVWMA man- 3 agers assess the effects of new BMP components to further 5 reduce coastal pumpage and sea water intrusion. The distribution and dynamics of supply and demand would be 4 difﬁcult to analyze without embedding them in the simulation and are difﬁcult to estimate a priori. Without the 7 coupling of the supply and demand components this analysis would be impractical if not nearly impossible. 6

Central Valley 8 9 California’s Central Valley is a regional watershed that covers about 52,000 km2 nestled between the Sierra Nevada Mountains to the east and the coast ranges to 11 the west (Figure 5) and is one of the most productive 12 agricultural regions in the world (Faunt et al. 2009a, 2009b, 2009d). This irrigated agriculture relies heavily on surface water diversions and groundwater pumping to 10 produce more than 250 different crops in the valley with 13 an estimated value of $17 billion/year. Approximately one-sixth of the Nation’s irrigated land is in the Central Valley, and about one-fifth of the Nation’s pumping is 16 14 from its aquifers (Great Valley Center 2005). The Central Valley is a predominantly agricultural hydrologic system. 17 15 For the period 1963 to 2003, about 89% of the total pumped groundwater was used for irrigation and the remainder for public supply (Faunt et al. 2009b). But since 18 1980, the population of the valley has nearly doubled from 2 to 3.8 million people (California Department of Finance 19 2007), and it is projected that the valley’s population 20 will continue to increase. This increase in population is increasing the competition for water within the Central Valley and statewide. Competition for water is likely to be 21 exacerbated by reduced deliveries of Colorado River water to Southern California and reduced deliveries through the Sacramento-San Joaquin Delta owing to environmental flow requirements. Because of the variability of surface water supplies, conjunctive water use remains a major issue for water management in the Central Valley. Figure 5. Maps showing selected water-balance subregions With over a century of resource development in analyzed for conjunctive use in the Central Valley, California support of agriculture and with increasing urbanization, (modified from Faunt et al. 2008). groundwater use in the Central Valley is estimated to have grown from about 2 million acre-feet per year in the mid to late 1800s to about 12 million acre-feet per year for climate variability for the period 1962 to 2003 (Faunt the engineered hydrologic system for the period 1962 to 2009a, 2009b, 2009c, 2009d). The CVHM divided the 2003 (Faunt et al. 2009b, 2009c). The features presented Central Valley into 21 WBS that include irrigated here exemplify the conjunctive use components simulated and nonirrigated croplands, urban areas, and areas of as part of the Central Valley hydrologic model (CVHM). natural vegetation (Figure 5). Historical records do not The CVHM was developed to assess aquifer-system provide details about the landscape and groundwater responses to stresses from historical human uses and hydrologic budgets. MF-FMP results provide budgets that

NGWA.org R.T. Hanson et al. GROUND WATER 9 are consistent with the available historical records. The are critical to agricultural productivity. These simulation calibrated CVHM was used to investigate hydrologic results demonstrate that MF-FMP is capable of simulating budgets for the landscape and groundwater of 21 WBS. the significant contribution of phreatophytic agriculture in Landscape hydrologic budgets include the inflows to this region surrounding the Sacramento River. and outflows from the land surface portion of the In contrast to the Sacramento Valley, agriculture model domain. Groundwater hydrologic budgets include in the eastern San Joaquin Valley relies heavily on the inflows and outflows from the saturated portion of the applied surface water and groundwater. The simulated model domain. CVHM simulated streamflow routing of components for WBS 13 (Figure 6B, top) shows that 41 major rivers and 66 main diversions from rivers with recharge is bimodal, occurring in response to precipitation the SFR package. The water available for surface water in the winter months and irrigation in the summer months. deliveries after diversion was limited by the simulated Groundwater-level decline and related storage depletion diversions. This allows the CVHM to constrain these are occurring in this area as ET from groundwater uptake historical diversions of surface water deliveries from the is about 4% (Figure 7B, inflow) and recharge to the main diversions to farms that are driven by the FMP- groundwater is about 25% on the landscape (Figure 7B, calculated demand. Furthermore, this allows verification outflow). Runoff is unimodal, occurring mostly in the that the streamflow routing in MF-FMP can in fact winter months (Figure 6B, top). Evapotranspiration from simulate the conveyance and match the historical reported groundwater and summer irrigation supplement the crop diversions of the regulated streamflow network. consumptive use because there is little available summer This article presents the simulated inflows and precipitation (Figure 6B, bottom). Hence, the annual outflows of water across the landscape for a WBS in timing of ET from groundwater, ET from applied water, the central part of the Sacramento Valley (“WBS 4,” and recharge to deep groundwater are aligned. The annual Figure 5) and along the eastern side of the San Joaquin amplitude of total applied water is relatively constant in Valley (“WBS 13”, Figure 5). In this large model, each this area from year to year (Figure 8B), because land WBS represents evaluation at the macro-agricultural scale. use is dominated by orchards and vineyards that have a Figure 6 shows all inflows and outflows for the 15- fairly similar summer-fall water requirement regardless of year period from 1975 to 1990 and Figure 7 summarizes annual climatic variability. the overall 15-year WBS hydrologic budgets. Figure 8 For each WBS represented by many model cells, the shows the temporal distribution of the sources of water results shown in Figures 6 to 8 are the aggregate of delivered to satisfy irrigation demand and the 15-year total the cells involved. Crop types, crop coefficients, potential percentages. The results clearly show that the Sacramento or specified evapotranspiration, and other characteristics Valley, which constitutes the northern part of the Central are defined for each cell, and results such as crop irrigation Valley and is represented by WBS 4, receives significantly requirements are simulated for each cell. This allows MF- more precipitation and runoff than the San Joaquin Valley, FMP to simulate different timings of supply and demand which constitutes the southern part of the Central Valley on a cell-by-cell basis. The model results indicate that and is represented by WBS 13. The following paragraphs precipitation and groundwater (pumpage deliveries and provide additional information about how the MF-FMP ET from groundwater) satisfy a significant portion of the results relate to the field conditions. irrigation demand (Figure 8D). WBS 4 in the north (Figure 5) is an agricultural Climate variability affects the relative proportions region dominated by rice paddies and winter grains. of surface water deliveries available. During drought The simulated temporal distribution of inflows and out- years there is less surface water available for delivery, flows for WBS 4 is shown in Figure 6. The timing of which requires increased groundwater pumpage. During recharge and runoff (Figure 6A, top) are aligned and the wet El Nino˜ years (1982 to 1983 and 1986 to are coincident with winter-spring precipitation. The mag- 1987) groundwater pumpage is diminished (Figure 8B). nitude of recharge and runoff are closely aligned with Over the simulation period, about 55% of the irrigation climate variability, as shown by the droughts of 1976 water came from surface water in the form of nonrouted to 1977 and 1986 to 1992 and the El Nino˜ driven transfers and routed deliveries and about 45% came wet period of 1978 to 1985 (Figure 6A, top). There is from groundwater sources (Figure 8D). Although approx- a significant component ET derived from groundwater imately equal over the long term, this source water dis- during the summer months when precipitation is minimal tribution shows large interannual variations (Figure 8B). (Figure 6A, bottom). In this precipitation-rich setting, irri- During the second year of the severe 1976 to 1977 gation from groundwater pumpage is minor (Figure 6A, drought, groundwater supplies were dominated by irriga- bottom). Groundwater recharge shows a predominantly tion (Figure 8B). Notably, groundwater and surface water unimodal annual distribution. Over the 15-year period, are used simultaneously as opposed to a preferential use of Figure 6A shows that the simulated total farm delivery one source and then another (Figure 8B). This is because requirement for irrigation is almost completely satisfied by surface water was not the dominant historical supply and surface water deliveries (Figures 8A and 8C). The minor may be due in part to the timing of regulated surface groundwater contributions are significant because they are water supplies. Snowmelt from the Sierras is stored in the sole source of water for irrigation at the beginning and large reservoirs and then released during the peak of the end of many irrigation seasons (Figure 8A) and, as such, irrigation season.

10 R.T. Hanson et al. GROUND WATER NGWA.org Figure 6. Graph showing the temporal distribution of the inﬂows and outﬂows for two water-balance areas (A) WBS-4 and (B) WBS-13 for the period 1975 to 1990 as part of the conjunctive use simulated by MF-FMP within the Central Valley, California.

The dynamics of the supply and demand components impossible to calculate a priori. This type of modeling demonstrate another aspect of the consumptive use allows hydrologic simulation to be constrained by a simulated by CVHM using MF-FMP (Figure 8). Because larger suite of observations for calibration and parameter the CVHM simulated streamflow routing, the water estimation (Schmid et al. 2008), which in turn allows available for surface water deliveries after diversion with more aspects of the system to be characterized. In the SFR was a constrained supply that was aligned with the cycle between improved data and improved models, these historical reported diversions. This allows the CVHM to types of models may well drive the need for more detailed constrain these historical surface water deliveries through observations of physical and biological conditions. For the diversions to a WBS which are driven by the example, the separate simulation of evaporation and FMP-calculated demand. Furthermore, this also allows transpiration in MF-FMP will require more detailed MF-FMP to verify through simulation that the streamflow field measurements to determine these components for routing can in fact simulate the conveyance and match various crops or natural vegetations. While the two case the historical reported diversions as part of the physical studies briefly described here provide new insight into representation of the regulated streamflow network. the timing and dynamics of these linked processes, such as bimodal recharge or irrigation-supply components, the development and application of these models raises Discussion new questions that will require additional research and MF-FMP is one of the new integrated hydrologic even better simulation methods of specific processes. models able to simulate coupled processes across the The ongoing development and applications of MF-FMP landscape, surface water and groundwater components have spurred a host of additional enhancements that will of the hydrologic cycle. These types of models are provide additional linkages and better physically based essential in the analysis of issues such as conjunctive representation of individual processes. For example, MF- use because the flows and interactions between the head- FMP will include optional linkages to the SUB package and flow-dependent components would be difficult if not for better representation of the effects of land subsidence

NGWA.org R.T. Hanson et al. GROUND WATER 11 A

Figure 7. Graph showing the percentages of total inflows and outflows for two water-balance areas (A) WBS-4 and (B) WBS- 13 for the period 1975 to 1990 as part of the conjunctive use simulated by MF-FMP within the Central Valley, California. on streamflow and runoff and will be linked to Local subsidence, economic changes, changes in water rights, Grid Refinement (Mehl and Hill 2004, 2007) to allow and changes in the engineered water systems. child models with more detailed streamflow and landscape For simple applications, MF-FMP is easy to imple- processes nested within regional models such as CVHM. ment because MF-FMP is highly modular, making it easy In addition to internal improvement, these complex to choose the needed features. MF-FMP provides for integrated models could also benefit from selected link- easy analysis even in data-deficient settings. The many ages to other models that can provide specialized features options in MF-FMP can be added incrementally to create that are best done by other associated models such as bio- more detailed simulations of complex hydrologic systems. logical, chemical, transport, climate, economic, or social Application of MF-FMP allows the scientist or engineer processes (e.g., urbanization and land-use changes or to extend their conceptualization beyond the traditional changes in governance such as water rights, Schmid and realm of the GWF system and consider aspects of all the Hanson 2007). In the context of conjunctive use, these flows including those related to climate, soils, and vege- added capabilities are important because they may alter tation. For example, the assignment of deliveries through constraints and distributions of water resources. This can associations between irrigation wells and specific agri- only be done when the physically based simulation is cultural regions or application of measured pumpage as structured in a supply-constrained and demand-driven additional calibration observations is not a traditional con- hierarchy as is done in MF-FMP. Thus, these models not struct of most GWF models. Similarly, the inclusion of only couple surface water and groundwater systems but wilting and anoxia and fractions of ET used to represent also allow the simulation of the response of these sys- water consumption provide refinements that allow for the tems to changing conditions that can alter the supply and simulation for stressed irrigation settings. demand of water. Such changing conditions can include The two case studies demonstrated the use of climate, land use, sea-level rise, sea water intrusion, land MF-FMP to derive details of historical water use in

12 R.T. Hanson et al. GROUND WATER NGWA.org Figure 8. Graph showing the temporal distribution of the Farm delivery components for two water-balance areas (A) WBS-4 and (B) WBS-13, and the percentages of total inﬂows for two water-balance areas (C) WBS-4 and (D) WBS-13 for the period 1975 to 1990 as part of the conjunctive use simulated by MF-FMP within the Central Valley, California.

distinct hydrologic settings and scales: one represents climate, soil, well, and crop data that do not require a groundwater-dominated coastal aquifer-system (Pajaro substantial external estimation of inflows and outflows Valley, micro-agriculture, local) and the other represents (pumpage, recharge, ET, runoff, surface water deliver- a surface water-dominated large-scale regional aquifer- ies, etc.) prior to simulation. If such data are avail- system (Central Valley, macro-agriculture, regional). The able, they may be used to constrain the simulation dur- two examples have different supply and demand com- ing calibration. Because these hydrologic components are ponents: ASR-CDS delivery system vs. nonrouted and simulated separately, the flows and movement can be semi-routed deliveries. The Pajaro Valley model repre- easily analyzed, which facilitates operational and fore- sents a coastal agricultural system where the capture, casting simulations as well as regional and subregional storage and reuse of local runoff and recycled water analysis. are being used to supplant coastal pumpage and related The greatest strength of MF-FMP is the physically overdraft and sea water intrusion. The Pajaro Valley based hierarchy of coupled water use and movement that application demonstrates how MF-FMP can facilitate the allows analysis of the associations related to the delivery simulation of a complex conjunctive use plan with a and return of water to and from the landscape. Know- climatically variable source, changing sources of alter- ing which wells, diversions, rivers, and drains partici- nate water supply, and agricultural demand that varies pate in the local supply and demand components of each monthly. In contrast, the Central Valley model simulates WBS become an integral part of the expanded conceptual conjunctive use over a region where land use, hydro- model. And in so doing, MF-FMP facilitates a conceptual logic settings, and conjunctive use take on different con- model of the hydrologic cycle that includes a greater con- structs within different subregions and different climate nection of the anthropogenic and natural components of regimes. conjunctive use in a physically based context. The current The example applications show how WBS can be limitations of MF-FMP include its lack of soil-moisture used to organize input data and simulated results. FMP storage change, irrigation scheduling, or dry-land farming input files are easy to build, update, and maintain using applications and a more physically based runoff structure

NGWA.org R.T. Hanson et al. GROUND WATER 13 through linkages with other models or expanded features Acknowledgments at multilevel time steps. The authors would like to acknowledge the USGS reviewers Steve Peterson, Peter Martin, and Mary Hill as well as the useful comments and reviews by the Conclusions journal reviewers Howard Reeves of the USGS and Jens The sustainability of water resources will depend, in Christian Refsgaard of the Geological Survey of Denmark part, on our ability to monitor, simulate, and analyze all and Greenland. The authors would also like to thank the components of complex hydrologic systems, includ- Larry Schneider for the illustrations. This research was ing GWF, surface water, and landscape components. supported by the NOAA funded California Applications MF-FMP provides the needed detailed representation and Program of Scripps Institution of Oceanography, and in analysis critical to the management of conjunctive use in part by the Pajaro Valley Water Management Agency and highly regulated and engineered hydrologic flow systems. the U.S. Geological Survey. MF-FMP is physically based and allows for a broad representation of supply-constrained demand of the use and movement of water. From large- to small-scale settings, Supporting Information the MF-FMP can be used to simulate and analyze histor- Additional Supporting Information may be found in ical, present, and future conditions (Schmid et al. 2008). the online version of this article: MF-FMP can be used to analyze agricultural water use where little data are available for pumpage, land use, Figure S1. Diagram showing linkages and embed- or agricultural information. MF-FMP also can be used ded constraints for supply and demand components of to analyze the effects of agricultural demand and sup- flow-dependent linkages for MODFLOW with the Farm ply from multiaquifer well pumpage, delayed recharge Process (modified from Schmid and Hanson 2009b). The through thick unsaturated zones, or rejected recharge as arrows signify the connections made with respect to pack- additional runoff. MF-FMP can forecast anticipated future ages and constraints within packages that affect the head- water demand and constrained supply in response to cli- and flow-dependent couplings. mate change scenarios. In addition, MF-FMP can estimate Figure S2. Diagram showing pathways in a physical how future water demand and supply would change sub- setting for supply and demand components of flow- ject to potential policies or infrastructure improvement dependent linkages for MODFLOW with the Farm projects that try to mitigate or adapt to climate change. Process (modified from Schmid and Hanson 2009b). For instance, for anticipated drought period or drought Figure S3. Map showing selected ongoing applica- regions, response policies can be used to bring demand tions of micro- to macro-agricultural settings of conjunc- back into balance with supply through monetary-based tive use simulated by MODFLOW with the Farm Process optimization of the cropped acreage, the use of deficit irri- across the western United States. gation prorated either over all crops within a WBS or only Please note: Wiley-Blackwell is not responsible for over user-defined priority crops (called “water stacking”), the content or functionality of any supporting information or through conservation. supplied by the authors. Any queries (other than missing The application of MF-FMP for the analysis of con- material) should be directed to the corresponding author junctive use on both the micro-agricultural (Pajaro Valley) for the article. and the macro-agricultural (Central Valley) scale is illus- trated in this article. These hydrologic issues are common in, for example, the Western United States (Figure 4), in References other big basins such as North China Plain, Punjab Region Allen, R.G., L.S. Pereira, D. Raes, and M. Smith. 1998. Crop (Pakistan-India border), and Parana´ Basin or Chilean Valle evapotranspiration—guidelines for computing crop water Central in South America, and in coastal aquifers such as requirements. Food and Agriculture Organization of the the entire circum-Pacific Rim, Mediterranean and Atlantic United Nations, Rome. Irrigation and Drainage Paper 56. coastlines, and the Mekong Delta. California Department of Finance. 2007. E-4 population estimates for cities, counties and the State 2001–2007, with In summary, MF-FMP allows the simulation of 2000 Benchmark, Sacramento, California. http://www.dof. detailed supply-constrained and demand-driven hydro- ca.gov/HTML/DEMOGRAP/ReportsPapers/Estimates/E4/ logic budgets needed to effectively evaluate complex E4-01-06/HistE-4.asp. conjunctive use strategies. MF-FMP is a unique and versa- California Department of Water Resources. 2005a. Integrated tile alternative that provides fully coupled, cell-by-cell dis- Water Flow Model (IWFM v3.1): Theoretical documentation. Hydrol. Development Unit, Modeling Support Branch, tributed, fully iterative simulation of supply-constrained Bay-Delta Office, Sacramento. http://modeling.water.ca. and demand-driven water use and movement from natu- gov/hydro/model/iwfm/documentation.html. ral and anthropogenic sources. In MF-FMP, water demand California Department of Water Resources. 2005b. Integrated and water use components are dynamically linked to nat- Water Flow Model (IWFM v3.1): User’s manual. Hydrol. ural data. This means that the forecasting tool is easy to Development Unit, Modeling Support Branch, Bay-Delta Office, Sacramento. http://modeling.water.ca.gov/hydro/ update (e.g., by remotely sensed data) and inexpensive, as model/iwfm/documentation.html. less pre-estimated data derived from human sources (e.g., Christenson, S. 2010. U.S. Geological Survey, written commu- land-use surveys or historic records) are required. nication.

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NGWA.org R.T. Hanson et al. GROUND WATER 15 Prudic, D.E., L.F. Konikow, and E.R. Banta. 2004. A new Schmid, W., R.T. Hanson, and T.M. Maddock III. 2006b. streamflow-routing (SFR1) package to simulate stream- Overview and Advances of the Farm Process for aquifer interaction with MODFLOW-2000. U.S. Geological MODFLOW-2000. MODFLOW and MORE 2006. Man- Survey Open-File Report 2004-1042. aging Groundwater Systems—Conference Proceedings, Refsgaard, J.C., and B. Storm. 1995. MIKE SHE. In: Computer 23–27. Models of Watershed Hydrology, ed. Singh, 809–846. Schmidt, C., A. Fisher, A. Racz, M. Los Huertos, and Highlands Ranch, Colorado: Water Resources Publications. B. Lockwood. 2009. Process and controls on rapid nutrient Schmid, W. 2004. A Farm Package for MODFLOW-2000: Sim- removal during managed aquifer recharge, 19–22. Califor- ulation of Irrigation Demand and Conjunctively Managed nia: Water Resources Association Hydrovisions. Surface-Water and Ground-Water Supply. PhD Disserta- Simunek, J., M. Sejna, and M.T. van Genuchten. 1999. tion. Department of Hydrology and Water Resources, The HYDRUS-2D/MESHGEN-2D. Simulating water flow and University of Arizona. solute transport in two-dimensional variably saturated Schmid, W., and R.T. Hanson. 2009a. Appendix 1, Supplemen- media. Colorado: School of Mines. International Ground- tal Information—Modifications to Modflow-2000 Packages water Modeling Center, Handbook TPS 53C, Version 2.0. and Processes. In Ground-Water Availability of California’s Sophocleous, M.A., and S.P. Perkins. 2000. Methodology and CentralValley., ed. C.C. Faunt, 213–225. U.S. Geological application of combined watershed and ground-water Survey Professional Paper 1766. models in Kansas. JournalofHydrology 236, no. 3–4: Schmid, W., and R.T. Hanson. 2009b. The Farm Process 185–201. Version 2 (FMP2) for MODFLOW-2005 - Modifications Sophocleous, M.A., J.K. Koelliker, R.S. Govindaraju, T. Birdie, and Upgrades to FMP1. U.S. Geological Survey Techniques S.R. Ramireddygari, and S.P. Perkins. 1999. Integrated in Water Resources Investigations, Book 6, Ch. A32. numerical modeling for basin-wide water management— Schmid, W., J.P. King, and T.M. Maddock III. 2009c. Con- The case of the Rattlesnake Creek Basin in South-central junctive Surface-water/groundwater model in the southern Kansas. JournalofHydrology 214, no. 1–4: 179–196. Rincon Valley using MODFLOW-2005 with the Farm Pro- The Pajaro Valley Water Management Agency (PVWMA). 2007. cess: New Mexico Water Resources Research Institute Basin management plan. http://www.pvwma.dst.ca.us/ Completion Report No. 350. basin management plan/bmp documents.shtml Schmid, W., R.T. Hanson, C.C. Faunt, and S.P. Phillips. 2008. Therrien, R., R.G. McLaren, E.A. Sudicky, and S.M. Panday. Hindcast of water availability in regional aquifer systems 2004. HydroGeoSphere—a three-dimensional numerical using MODFLOW’s Farm Process. Hydropredict 2008 model describing fully-integrated subsurface and surface Conference Proceedings, 311–314. flow and solute transport. Universite´ Laval, University of Schmid, W., and R.T. Hanson. 2007. Simulation of Intra- or Waterloo. Trans-Boundary Water-Rights Hierarchies using the Farm Therrien, R., and E.A. Sudicky. 1996. Three-dimensional anal- Process for MODFLOW-2000. ASCE JournalofWater ysis of variably saturated flow and solute transport in Resources Planning and Management 133, no. 2: 166–178. discretely-fractured porous media. JournalofContaminant Schmid, W., R.T. Hanson, T.M. Maddock III, and S.A. Leake. Hydrology 23, no. 6: 1–44. 2006a. User’s guide for the Farm Package (FMP1) for Twarakavi, N.K.C., J. Simˇ unek,˚ and H.S. Seo. 2008. Evaluating the U.S. Geological Survey’s modular three-dimensional interactions between groundwater and vadose zone using finite-difference ground-water flow model, MODFLOW- HY-DRUS-based flow package for MODFLOW. Vadose 2000. U.S. Geological Survey Techniques and Scientific Zone Journal 7, no.2: 757–768. Methods Report Book 6, Chapter A17.

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