SWAP (Statewide Agricultural Production Model)
General Description | The Statewide Agricultural Production Model (SWAP) is a multi-region, multi-input and output programming optimization model of agricultural production and water use, which self-calibrates using the method of to a base input dataset using Positive Mathematical Programming (PMP). PMP simulates SWAP predicts the effects of policy changes on cropping patterns at the extensive and intensive margins by integrating observed data into model calibration. The model chooses the optimal amounts land, water, economics and/or policy scenarios, on cropping patterns with respect to baseline calibration conditions. The model chooses amount of land, water, labor, and other input use subject to these constraints and definitions. Profit is revenue minus costs, where revenue is price x yield per acre times total acres. |
Model Domain | Agricultural economics of crops in California |
Developer | Howitt, Medellin-Azuara, MacEwan, and Lund. Originally at the University of California at Davis (UC Davis) |
Hardware computing requirementsNot specified | Runs in MS windows environment. |
Code language | Generalized Algebraic Modeling System (GAMS) |
Original application | Developed as an agricultural economic component of ancillary model to the CALVIN model of California water systems. supply system ( http://calvin.ucdavis.edu ), providing economic value of water in agriculture. |
Public/proprietary and cost | For research-related applications available through UC Davis Center for Watershed Sciences or UC Merced (public). Water Systems Management Group Business application applications through ERA Economics (proprietary). |
Physically or empirically based | Empirical calibrated to predetermined baseline agricultural land and water use conditions. |
Mathematical methods used | Based on Positive Mathematical Programming (Howitt 1995, Howitt et al. 2012) calibrated to a base datasets on crop production input use, prices, costs and yields. Constant Elasticity of Substitution (CES) production functions are generated for every crop in every region. |
Input data requirements | (brackets include example datasets) Input data requirements include (values in parentheses refer to source datasets, these can vary):
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Outputs | Outputs Cropping patterns for 27 base regions (within 21 CVPM regions) in the Central Valley, and irrigated agriculture in selected coastal and inland areas (Medellin-Azuara et al. 2015) for 20 crop groups following DWR and CalSIMETAW classification.
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Pre-processing and post-processing tools | None specified. |
Representation of uncertainty | None specified. |
Prevalence | Used in policy analysis by both academic and state agencies. |
Ease of use for public entities | Requires knowledge of GAMS software and access to program through UC Daviscode through the University of California. Alternatively, ERA Economics provides paid access to model interface and modelling services for SWAP. |
Ease of obtaining information and availability of technical support | Through UC Davis Selected modeling applications can be obtained through the University of California, Center for Watershed Sciences for research purposes. or the Water Systems Management group at UC Merced (Medellin-Azuara). ERA Economics provides services to run scenarios. Freely available manuals or information on technical model runs is not currently available. |
Source code availability | Not freely available. |
Status of model development | Model Version 6.1 is available for collaborative research and other application through UC Davis Center for Watershed Sciences. Version RTS (decreasing returns to scale) is available through ERA economics.Economics. Model continues updating and development as new land, water, and economic information is available. |
Challenges for integration | Currently integrated with CALVIN, IMPLAN, C2VSim and CALSIM II models . Detailed inputs. Constrained crop groups may not map well to other models. New crop groups or updated crop valuation requires calibration for economics as well as land use. Model is data driven, can be run without recoding by changing input data. Model output scale may not match with other models. |
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in various applications, but running simultaneously within other platforms can be a challenge due to the GAMS native platform. Nevertheless, models outputs such as cropping patterns and economic value can be easily cascaded into other models (e.g. REMI, IMPLAN). Model spatial scale is easily changeable, yet the native temporal scale is annual cropping decisions. Substantial changes with respect to the baseline input use conditions may require a model recalibration. |
References
Bureau of Reclamation. (2012). Coordinated Long-Term Operation of the Central Valley Project and State Water Project: Appendix 12 - Statewide Agricultural Production Model (SWAP) Documentation. Retrieved from https://www.usbr.gov/mp/nepa/nepa_project_details.php?Project_ID=21883.
CH2M Hill (2012). Statewide Agricultural Production (SWAP) Model: Agricultural Economics Technical Appendix. California State Department of Water Resources.
Howitt, R. (1995). A calibration method for agricultural economic production models. Journal of Agricultural Economics, 46(2), 147–159. https://doi.org/10.1111/j.1477-9552.1995.tb00762.x
Howitt, R., Medellín-Azuara, J., & MacEwan, D. (2009). Estimating the Economic Impacts of Agricultural Yield Related Changes for California. California Climate Change Center.
Howitt, R. E., Macewan, D., Medellín-Azuara, J., & Lund, J. R. (2010). Economic Modeling of Agriculture and Water in California using the Statewide Agricultural Production Model. California Water Plan Update 2009, 4, 1–25.
Howitt, R. E., Medellín-Azuara, J., MacEwan, D., & Lund, J. R. (2012). Calibrating disaggregate economic models of agricultural production and water management. Environmental Modelling and Software, 38, 244–258.
Medellín-Azuara J, MacEwan D, Howitt R, Kourakos G, Dogrul E, Brush C, Kadir T, Harter T, Melton F, Lund J (2015) Hydro-economic analysis of groundwater pumping for irrigated agriculture in California’s Central Valley, USA. Hydrogeology Journal 23: 1205-1216 DOI 10.1007/s10040-015-1283-9.
Russo C., R. Green, and R. Howitt. (2008). Estimation of Supply and Demand Elasticities of California Commodities. Working Paper No. 08-001. Davis, California: Department of Agricultural and Resource Economics, University of California at Davis.