From safe yield to sustainable development of water resources—the Kansas experience

This paper presents a synthesis of water sustainability issues from the hydrologic perspective. It shows that safe yield is a flawed concept and that sustainability is an idea that is broadly used but perhaps not well understood. In general, the sustainable yield of an aquifer must be considerably less than recharge if adequate amounts of water are to be available to sustain both the quantity and quality of streams, springs, wetlands, and ground-water-dependent ecosystems. To ensure sustainability, it is imperative that water limits be established based on hydrologic principles of mass balance. To establish water-use policies and planning horizons, the transition curves of aquifer systems from ground-water storage depletion to induced recharge of surface water need to be developed. Present-day numerical models are capable of generating such transition curves. Several idealized examples of aquifer systems show how this could be done. Because of the complexity of natural systems and the uncertainties in characterizing them, the current philosophy underlying sustainable management of water resources is based on the interconnected systems approach and on adaptive management. Examples of water-resources management from Kansas illustrate some of these concepts in a real-world setting. Some of the hallmarks of Kansas water management are the formation of local ground-water management districts, the adoption of minimum streamflow standards, the use of modified safe-yield policies in some districts, the implementation of integrated resource planning by the City of Wichita, and the subbasin water-resources management program in potential problem areas. These are all appropriate steps toward sustainable development. The Kansas examples show that local decision-making is the best way to fully account for local variability in water management. However, it is imperative that public education and involvement be encouraged, so that system complexities and constraints are better understood and overly simplistic solutions avoided.