Joint prioritization of best-management-practice projects to optimally improve agricultural-drain-outlet water quality

The judicious application of conservation funds to mitigate non-point source pollution from agricultural runoff continues to be a practical challenge, particularly when presented with multiple feasible types of best-management-practices. To address this challenge, we develop and demonstrate a joint prioritization of two best-management-practice types that are commonly implemented to reduce pollutant loads from agricultural activities: irrigation-system-efficiency-upgrades and sediment-retention-basins. The goal of the joint prioritization is to optimally apply conservation funds to maximize pollutant-load reductions at agricultural-drain outlets. We achieve large computational efficiencies in the joint prioritization by leveraging a novel, graph-based mixed-integer-nonlinear-programming model. The computational efficiencies allow the approach to be applied as a large-scale scoping analysis to identify sets of high priority projects for further investigation. We demonstrate the approach on an agricultural basin in southwestern Idaho which drains to the Snake River. For our demonstration site, the results indicate that while larger load reductions are possible using irrigation-system-efficiency-upgrades alone, including sediment-retention-basins can provide more cost-effective outcomes. We present the results in the form of cost curves that illustrate the Pareto-optimal trade-offs between load reductions and costs (i.e., multi-objective Pareto fronts). We compare solutions that only include irrigation-system-efficiency-upgrades against those that also include sediment-retention-basins. We do not consider solutions with sediment-retention-basins only due to the limited availability of potential sites compared to irrigation-system-efficiency-upgrades. In our demonstration example, the cost curves including sediment-retention-basins provide more cost-effective solutions than with irrigation-system-efficiency-upgrades alone. Therefore, the inclusion of sediment-retention-basins can increase the beneficial use of conservation funds to improve agricultural-drain-discharge water quality. Given that participation in irrigation-system-efficiency-upgrade programs is voluntary for landowners, we also explore the effect of recruitment uncertainty. We identify that as the recruitment percentage increases, the effect of sediment-retention-basin selection on project prioritization increases. The insights derived from this type of analysis can ensure that conservation funds are optimally applied to maximize benefits to water quality.