Abstract
A method for calibrating models of agricultural production and resource use for policy analysis is proposed to leverage multidisciplinary agricultural research at the National Center for Alluvial Aquifer Research (NCAAR). An illustrative example for Sunflower County, MS, is presented to show how plot-level research can be extended to draw systemic region or basin wide implications. A hypothetical improvement in yields for dryland soybean varieties is incorporated into the model and shown to have a positive impact on aquifer outcomes and producer profits. The example illustrates that a change in one practice-crop combination can have system-wide impacts, as evidenced by the change in acreages for all crops and practices.
Highlights
The National Center for Alluvial Aquifer Research (NCAAR) was created to conduct research aimed at developing novel irrigation and agricultural water management technologies to improve water productivity, and decrease irrigation water withdrawal from and increase the groundwater recharge to the Mississippi River Valley Alluvial Aquifer (MRVAA) with the overall objective of ensuring sustainable agricultural water supplies in the Lower Mississippi River Basin (LMRB)
The dynamic simulation was run under the two scenarios for 20 simulated years
The typical economic analysis of agronomic research is limited to the partial budget analysis associated with implementing an experimental practice
Summary
The National Center for Alluvial Aquifer Research (NCAAR) was created to conduct research aimed at developing novel irrigation and agricultural water management technologies to improve water productivity, and decrease irrigation water withdrawal from and increase the groundwater recharge to the Mississippi River Valley Alluvial Aquifer (MRVAA) with the overall objective of ensuring sustainable agricultural water supplies in the Lower Mississippi River Basin (LMRB). This paper presents a methodology that can bridge the inter-disciplinary obstacles to translate plot and field-level research results to regional or basin-wide potential outcomes that incorporate implicit producer behavior with minimal data requirements: positive mathematical programming. Qureshi et al [13] developed a biophysical-economic mathematical model with PMP that calibrated against the observed multi-period land use data to evaluate the impacts of droughts and a set of policy options on agricultural production in the Murray-Darling Basin, Australia. Far from being an integration of multidisciplinary models, positive mathematical programming is an economic analysis tool that allows the incorporation of otherwise disjoint disciplinary research into economic analyses and simulation of biophysical and socio-economic impacts that may result if certain practices or policies are adopted (see Figure 3). We describe the type of disciplinary research that can be fed into a PMP model to draw aquifer and policy implication insights
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