Assessment of hydrology and nutrient losses in a changing climate in a subsurface-drained watershed.

Studies assessing the impact of subsurface drains on hydrology and nutrient yield in a changing climate are limited, specifically for Western Lake Erie Basin. This study aimed to evaluate the impact of changing climate on hydro-climatology and nutrient loadings in agricultural subsurface-drained areas on a watershed in northeastern Indiana. The study was conducted using a hydrologic model - the Soil and Water Assessment Tool (SWAT) - under two different greenhouse gas emission scenarios (RCP 4.5 and RCP 8.5). Based on analysis, annual subsurface drain flow totals could increase by 70% with respect to the baseline by the end of the 21st century. Surface runoff could increase by 10 to 140% and changes are expected to be greater under RCP 8.5. Soluble phosphorus yield over the basin in a year via subsurface drains could decrease by 30 to 60% under either emission scenarios. Annual total soluble phosphorus yield (soluble phosphorus loading to stream) from subsurface drains and surface runoff could vary from 0.041 to 0.058 kg/ha under RCP 4.5 and 0.035 to 0.064 kg/ha under RCP 8.5 by the end of the 21st century while the values from the baseline model were 0.051 kg/ha. This was attributable to the fact that future climate could have a greater increase in surface runoff than subsurface drain flow based on analysis of the different climate scenarios. Outputs from individual climate model data rather than ensembles provided a band of influence of watershed responses, while outputs from different timelines provided details for evaluating management practice suitability with respect to anticipated differences in climate. Results provide valuable information for stakeholders and policy makers for planning management practices to protect water quality.

A SWAT-based optimization tool for obtaining cost-effective strategies for agricultural conservation practice implementation at watershed scales.

To address the harmful algal blooms problem in Lake Erie, one solution is to determine the most cost-effective strategies for implementing agricultural best management practices (BMPs) in the Maumee River watershed. An optimization tool, which combines multi-objective optimization algorithms, SWAT (Soil and Water Assessment Tool), and a computational efficient framework, was created to optimally identify agricultural BMPs at watershed scales. The optimization tool was demonstrated in the Matson Ditch watershed, an agricultural watershed in the Maumee River basin considering critical areas (25% of the watershed with the greatest pollutant loadings per area) and the entire watershed. The initial implementation of BMPs with low expenditures greatly reduced pollutant loadings; beyond certain levels of pollutant reductions, additional expenditures resulted in less significant reductions in pollutant loadings. Compared to optimization for the entire watershed, optimization in critical areas can greatly reduce computational time and obtain similar optimization results for initial reductions in pollutant loadings, which were 10% for Dissolved Reactive Phosphorus (DRP) and 38% for Total Phosphorus (TP); however, for greater reductions in pollutant loadings, critical area optimization was less cost-effective. With the target of simultaneously reducing March-July DRP/TP losses by 40%, the optimized scenario that reduced DRP losses by 40% was found to reduce 51.1% of TP; however, the optimized scenario that reduced TP losses by 40% can only decrease 11.3% of DRP. The optimization tool can help stakeholders identify optimal types, quantities, and spatial locations of BMPs that can maximize reductions in pollutant loadings with the lowest BMP costs.