Modifying the SWAT Model to Simulate Hydrological Processes in Arid and Alpine Grassland Ecosystems

Abstract Grassland vegetation coverage is spatially heterogeneous in arid and alpine areas due to the terrain, impacts of climate, and anthropogenic activities. Differences in vegetation coverage lead to variations in canopy interception and transpiration ability, which can influence eco-hydrological processes. The Soil and Water Assessment Tool (SWAT) is one of the most widely used semi-distributed catchment-scale eco-hydrological models. The leaf area index (LAI) is one of the vegetation coverage indexes and is incorporated in the SWAT model. However, in SWAT, the LAI is calculated based on the average plant density in hydrologic response units (HRUs). Moreover, LAI accumulation is controlled by heat, and neglects other relevant factors such as precipitation and terrain. To address the drawbacks of the SWAT in simulating vegetation coverage and plant patterns, we modified it using remotely sensed LAI data with high temporal and spatial resolution. We used this to better simulate eco-hydrological processes in grassland basins with different vegetation coverages in the upper reaches of the Bayin River Basin. Site-based streamflow, sediment yield data and remotely sensed actual evapotranspiration data (ET, measured at the subbasin and HRU levels) were used to estimate performances of the original and modified SWAT models. Results showed that for the original SWAT model, the simulated LAI was homogeneous within each land use/cover type, whereas the remotely sensed LAI was spatially heterogeneous and better captured the vegetation coverage of the entire basin. The proper estimation of the LAI was reflected in the improved simulation of the monthly streamflow and sediment yield at the basin outlet and the monthly ET at the subbasins and HRU levels. These findings indicate that the modified SWAT could better simulate hydrological processes in arid and alpine grasslands with different vegetation coverages.