INTEGRATION OF SPATIALLY AGGREGATED PHYSICAL PROCESS MODELS WITHIN A SYSTEMS DYNAMICS FRAMEWORK TO ASSIST THE POLICY DEVELOPMENT AND DECISION SUPPORT PROCESS

The complexity of water resource issues, its interconnectedness to other systems, and the inter-relation of competing requirements often overwhelm decision-makers and inhibit the creation of clear management strategies. This difficulty has led to the development of various modeling tools to support the decision making process. These tools are typically based on a systems dynamics approach that brings together disparate yet connected systems, such as water resources and economics, by using a lumped-parameter ‘commodity balance' approach and are designed to examine the consequences of various decisions through facilitated deliberation and aggregation of both hard and soft data. While these approaches represent significant advancement over past efforts, and current efforts have become increasingly sophisticated and useful, none of them are able to assess spatially variable consequences of different policy decisions. For example, will urban development in one area have a higher or lower impact than urban development in another area? This study addresses the spatial limitations of the systems dynamics approach by combining spatially aggregated physical models, in the form of a MODFLOW groundwater model, with a systems dynamics model developed in the POWERSIM environment. This is a collaborative research effort between Sandia National Laboratories and The University of Texas at Austin and uses the Barton Springs segment of the Edwards Aquifer in Austin, Texas as its test case. The process involves the creation of a ‘data exchange manager' that serves as the central communication hub for the two groundwater simulation models, linking the input and output of each model to a centralized geodatabase. The geodatabase in turn is accessed by analysts, decision makers, and stakeholders via a user-friendly graphical user interface. The data exchange manager is designed in a modular fashion to permit the incorporation of additional types of models beyond the example models, MODFLOW and POWERSIM. The final structure provides a higher fidelity modeling approach that utilizes real-time information to facilitate and assist in the policy development and decision making process. The integration of the modeling structure into the decision making process is also presented.