Large portions of the Ogallala-High Plains aquifer (henceforth, HPA) complex, underlying approximately 450,000 km2 from Texas to South Dakota, are experiencing fundamentally unsustainable groundwater withdrawals due to large scale irrigation [McMahon 2000]. Since pumping began in earnest in the 1930’s [Weeks et al. 1988], storage in the HPA, the largest aquifer in North America [Jackson et al. 2001], has declined by 333 km3 [McGuire 2009]. Despite rapid water table drawdown and near depletion of some portions of the aquifer [McGuire 2009], irrigated acreage continues to expand [NASS 2007, 2002, 1997]. Underlying natural and socioeconomic drivers of this expansion are heterogeneous in time and space, driven by changes in climate, product demand (due to biofuels development, global population expansion, etc.), energy costs, and other factors [i.e. Peterson and Bernardo 2003]. Although a range of management and policy actions could help move this region toward sustainability, such efforts are complicated by a diverse range of state laws and regulations, economic drivers and agricultural production systems, variable soil productivity and aquifer storage, and forecast changes in temperature and precipitation [e.g., Ashley and Smith 1999; McGuire et al. 2003; Sophocleous 2010].
We propose to address the sustainability of HPA irrigated agriculture by simulating the linked physical, agroengineering, and socioeconomic systems of the region using a suite of climate, hydrology, and biophysical models coupled to socioeconomic models that simulate crop rotation and irrigation decisions in response to markets, policies, and physical drivers. This linked set of models will allow us to characterize and quantify interactions and feedbacks between social and natural systems, provide a thorough understanding of drivers of historical changes, and offer predictive forecasts of the sustainability of various land management alternatives under a range of climate conditions. In particular, we will investigate the social, economic, agricultural, climatological, and hydrologic impacts of land management scenarios ranging from business-as-usual, to managed aquifer depletion, to full sustainability under both static and changing climate conditions. This work will build on related efforts including the coupling of land use, hydrology, and ecosystem models to predict the changes in hydrology and ecosystems in lower Michigan [e.g., Wiley et al, 2010, Kendall and Hyndman, in review], and the CLIP project that coupled socioeconomic models with a regional climate model (RCM) to predict the feedbacks between land use, agriculture, and climate change in East Africa [e.g., Olson et al. 2008; Moore et al. 2009; Moore et al. in review].