The impact of water policy on conserving the Ogallala Aquifer in Groundwater Management District 3 (GMD3) in southwestern Kansas is analyzed using a system-level theoretical approach integrating agricultural water and land use patterns, changing climate, economic trends, and population dynamics. In so doing, we (1) model the current hyper-extractive coupled natural-human (CNH) system, (2) forecast outcomes of policy scenarios transitioning the current groundwater-based economic system toward more sustainable paths for the social, economic, and natural components of the integrated system, and (3) develop public policy options for enhanced conservation while minimizing the economic costs for the region's communities. The findings corroborate previous studies showing that conservation often leads initially to an expansion of irrigation activities. However, we also find that the expanded presence of irrigated acreage reduces the impact of an increasingly drier climate on the region's economy and creates greater long-term stability in the farming sector along with increased employment and population in the region. On the negative side, conservation lowers the net present value of farmers' current investments and there is not a policy scenario that achieves a truly sustainable solution as defined by Peter H. Gleick. This study reinforces the salience of interdisciplinary linked CNH models to provide policy prescriptions to untangle and address significant environmental policy issues.
Bibliographical noteFunding Information:
Acknowledgements. This research is funded by a grant from the National Science Foundation (NSF-CNH-0909515), with additional funding from the Ogallala Aquifer Project of the US Department of Agriculture’s Agricultural Research Service.
This research is funded by a grant from the National Science Foundation (NSF-CNH-0909515), with additional funding from the Ogallala Aquifer Project of the US Department of Agriculture's Agricultural Research Service.
© 2017 Author(s).
Aistrup, J. A., Bulatewicz, T., Kulcsar, L. J., Peterson, J. M., Steward, D. R. & Welch, S. M., Data Repository for the University of Minnesota, 2017