Hydrologic drought and declining water availability are among the foremost stressors of stream ecosystems in the Red River basin. Resource managers face the challenge of apportioning scarce water resources among competing uses, but they lack a systematic framework for comparing the costs and benefits of proposed water management decisions and conservation actions.
In 2016, Co-PIs Neeson and Moreno were funded by the Great Plains LCC to develop a decision support model for identifying the most cost-effective water conservation alternatives across the Red River basin. Here, we propose to extend this optimization model in three significant ways to support cost-effective conservation decisions in the face of climate change and drought. First, we will incorporate SC CSC-developed predictions of rainfall, runoff, and stream flows through the year 2099 into our hydrologic database. Using this database, our enhanced optimization model will enable decision-makers to visualize and evaluate multiple competing water use scenarios under future drought conditions. Second, we will use SC-CSC predictions of stream flows and temperature through the year 2099 to estimate the future distributions of 28 fish species of conservation concern across the Red River. These future distribution maps will enable conservation practitioners to proactively manage species projected to be at greatest risk from declining water availability. Third, we will extend our optimization model to enable decision-makers to explicitly quantify trade-offs between competing water uses and ecological outcomes under multiple use scenarios. In doing so, our optimization model will provide resource managers with a means to identify conservation strategies that maximize outcomes for Great Plains stream ecosystems while meeting growing societal needs for water.
