Evaluation of climate and land use change impacts on discharge variability in the Mekong River's largest tributary
Year: 2025
Type: article
Abstract: The Mekong River Basin faces significant challenges in streamflow variability, driven by climate change and human activities. This study evaluates the climate and land use/cover (LULC) variation effects on discharge in the Mun River, the greatest branch of the Mekong River, utilizing advanced climate projections and accurated future LULC maps. MPI-ESM1-2-LR is recommended as the optimal Global Climate Model under the Coupled Model Intercomparison Project Phase 6 for projecting discharge in the Mun River. An analysis reveals future LULC transformations, with the conversion of croplands into forests and urbanized areas. Annual discharge contributing to the Mekong River are projected to rise slightly up to 4 %, with temporal variations indicating wetter wet seasons and drier dry seasons. Wet-season discharge is projected to rise by 5 %–24 %, while the dry season may experience a reduction of 3 %–17 % between 2023 and 2050. These fluctuations are more pronounced in mountainous and upstream regions, highlighting potential risks of severe drought during dry periods and intensified flooding in wet periods. Such changes emphasize challenges for hydropower operations and water resource management in this basin and downstream countries. Therefore, effective and targeted LULC policies and water regulation are essential for ensuring the sustainable management of this catchment and the broader Mekong region. • Bias-corrected MPI-ESM1-2-LR is recommended as the optimal CMIP6 GCM for future flow simulations in the Mekong region. • Forest areas will increase along the Mun River but decrease along the Chi River. • Flow contributing to the Mekong mainstream will increase for 24 % in wet season, while decrease for −17 % in dry season.
Language: English
Subfield: Water Science and Technology
Field: Environmental Science
Domain: Physical Sciences
Open Access status: gold
Estimated APC paid: $1,200
Awards: G3880707209, G7822113901, G8524578551
OpenAlex ID: W4414804392
