STREAMFLOW SIMULATION BASED ON LAND USE/COVER CHANGE USING INTEGRATED GOOGLE EARTH ENGINE AND SWAT+ IN AN AGRICULTURE-DOMINATED BASIN, NORTHEAST THAILAND
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Abstract
Streamflow is a fundamental component of the hydrological cycle, and land use/land cover (LULC) significantly influences runoff processes. This study investigates the impacts of Land Use and Land Cover Change (LUCC) on streamflow in the Upper Songkhram River Basin (USRB), Northeast Thailand using Google Earth Engine (GEE) and the SWAT+ hydrological model. GEE facilitated high accuracy LULC classification (overall accuracy: 83-91%, Kappa coefficient: 0.76-0.85), revealing a marked increase in para rubber plantations and built-up areas, and
a decrease in paddy fields and forests between 2003 and 2023. The calibrated and validated SWAT+ model (NSE: 0.86/0.79, R²: 0.91/0.89, PBIAS: -24.5%/-36.7%) simulated the streamflow changes associated with LUCC. Results indicate a substantial increase in wet season streamflow, particularly in August (28.9 m³/s) and September (25.6 m³/s), primarily due to the decline of paddy fields and their water retention capacity. This study emphasizes the link between land use and hydrology, showcasing the combined utility of GEE and SWAT+ for assessing LUCC impacts. These findings offer valuable insights for sustainable water resource management and land use planning in Thailand and comparable regions worldwide.
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