The High Plains region hosts some of the most productive irrigated agricultural land in the United States due to the vast Ogallala-High Plains aquifer (HPA) complex, but much of this system is on a fundamentally unsustainable path due to extensive groundwater withdrawals since the 1930s. The future of this region will be dictated by a range of state and local laws and regulations, complex economic drivers, variable soil productivity and saturated thicknesses, and a changing climate that is forecast to increase the severity of existing regional precipitation and evapotranspiration gradients. This interdisciplinary project examines the coupled landscape, atmospheric and socioeconomic systems (CLASS) associated with the HPA through linking process-based climate, hydrology, dynamic vegetation, and econometrics models. Exploiting data from decades of intense study of the region, the investigators are applying the CLASS modeling suite to better understand historical changes, system interactions, and the feedbacks among climate, hydrology, and agroecosystems. With insights from this historical context, the impacts of a range of possible future social, economic, climate, agroengineering, and land-management conditions on the sustainability of the region's hydrology and economy can be quantified. Diurnal processes are simulated over seasonal to century timescales to investigate the likely impacts of both short-term perturbations and long-term trends. This project broadly integrates across engineering and the physical, biological, and social sciences. It provides a newly-coupled set of physical process models that will together simulate the terrestrial and atmospheric hydrologic cycles. These physical models are coupled to a biological systems model describing the dynamic growth of both natural and managed agricultural vegetation, and how those biological systems respond to climatic or hydrologic variability. Models that simulate agroengineering decisions about irrigation, management practices, and crop rotations in response to social and economic drivers are then used to both drive the biophysical models and incorporate feedbacks among the systems. The research provides a powerful modeling system that can inform better management of regional water usage, yields, nutrients applications, and soil carbon sequestration, and offer transformative insights into the sustainability of one of the world's most important agricultural regions. The linked models also allow for better understanding and quantification of interactions among landscape, atmospheric, agroengineering, and socioeconomic systems over the HPA that will be relevant to irrigated agricultural systems worldwide. High resolution simulations will provide policy makers and managers with local information within a regional context. Results of the project will also help raise public awareness of critical links between climate change and biophysical, agroengineering, and socioeconomic systems. Summarized results will be presented to policy makers, planners, and the public via interactive web sites to inform policies that can improve the sustainability of the HPA and other aquifer systems. Students working on the project team will be embedded in science at the interface among multiple disciplines, providing them with both in-depth knowledge within their fields and an ability to work in broad interdisciplinary physical and social science teams. The models and linkages used here can be applied to agricultural systems worldwide and will be made freely available to the research community.
