Assessing hydrological and water quality responses to dynamic landuse change at watershed scale in Mississippi

Abstract

The hydrology and water quality modeling in a watershed are affected by land use land cover (LULC) input. This study differs from numerous LULC change studies by introducing multi-year LULC input in a single simulation of Soil and Water Assessment Tool (SWAT) model. The proposed approach highlighted the outperformance of the model with dynamic LULC input (DM) over static LULC input (SM) based on the magnitude and direction of the hydrological responses. The difference between DM and SM outputs allowed for studying effects of historical LULC change. Additionally, agricultural management operation inputs enabled more realistic simulation of runoff, sediments, total nitrogen (TN), and total phosphorus (TP). The SM used static landuse data layers for 2009, and DM used landuse data layers for 2009, 2015, and 2018 to represent changes in LULC distribution over time. The expansion of agricultural land (0.9%) and forest cover (0.5%), as well as the reduction of grassland, water, and barren areas (1.4%), were the significant LULC changes from 2009 to 2018. Even though the expansion of forest cover was identified from 2009 to 2015, a declining trend was observed from 2015 to 2018. The agricultural land cover increased consistently from 2009 to 2018. The expansion of agricultural land increased average annual surface runoff, sediment yield, TN, and TP loads by 1.3%, 5.4%, 5.8%, and 5.9% respectively at watershed scale as determined by DM model simulation results. At sub-watershed scale, agricultural land expansion increased runoff, sediment, TN, and TP loads by up to 5%, 16%, 15%, and 15% respectively whereas, the expansion of forest cover resulted in reduction in same parameters by up to 5%, 15%, 23%, and 26% respectively. In general, the study determined that the integration of dynamic LULC and agricultural operations in SWAT allows a more accurate representation of agricultural watersheds for hydrological and water quality analysis.