DEVELOPMENT OF INTEGRATED PREDICTIVE WATER QUANTITY AND QUALITY MODELS TO SUPPORT HEALTHY AGROECOSYSTEMS AND WATER RESOURCE MANAGEMENT.

In arid snow-dominated watersheds, water quantity is a significant driver of water quality and the ecological health of freshwater resources. This is particularly true in watersheds where surface and groundwater systems are tightly connected, and where agricultural uses compete for limited water resources. Management of water resources in these systems has been hindered by a lack of conjunctive management strategies that relate water quantity and quality issues. We will investigate connections between water quantity and quality in the Silver Creek watershed, which hosts substantial agricultural usage and a highly valuable trout fishery. Specifically, we propose to improve a predictive water quantity model and develop a combined model that elucidates the stream health implications of predicted water quantity dynamics. Pre-existing data sources will support the examination of empirical relationships between water quantity, stream temperature, and dissolved oxygen. Open-source code for data visualization and interactive modeling tools provide a reproducible mechanism to increase data-informed management regionally. We will develop an online interface for the suite of predictive modelling tools to inform and facilitate discussion among resource managers and stakeholders to improve the health of this agroecosystem. This project meets the Water Quantity and Quality Program Area Priorities by creating innovative modeling tools for irrigators and water resources managers to gain a deeper understanding of physical and biogeochemical fluxes from agroecosystems and their impact on natural resources and environment. This is the first step in meeting our long-term goal of evaluating how adaptive management of agroecosystems may conserve water and improve water quality.