H030-0013
Simulating the Integrated Surface and Groundwater Resources of the Mekong River Basin at High Resolution
Simulating the Integrated Surface and Groundwater Resources of the Mekong River Basin at High Resolution
Tuesday, 8 December 2020
Poster
Abstract:
The Mekong River is one of the largest river systems worldwide, supporting diverse species of flora and fauna and supplying prosperous fisheries and agricultural industries. Over the past few decades, natural and human interventions, from altered monsoon precipitation patterns to constructions of many dams and land use and land cover changes, across the basin have led to considerable variations in streamflow, flood pulse, and wet and dry season period. These changes threaten the security of food, water, energy resources across the basin. A wide range of hydrological studies have been conducted using large scale land surface models which predominantly oversimplify surface and subsurface hydrological processes and their linked interactions. Those simplifications narrow their ability to forecast consequences of projected changes to hydrological components basin wide. High-resolution models of hydrological processes including both surface and subsurface water interactions are needed to better quantify the effects of human activities on water, food and energy nexus over portions of large basins such as Mekong River. This study develops a high spatial- and temporal-resolution model using the Landscape Hydrology Model (LHM), which is a process-based model that implements the full energy and water balance to predict hydrologic fluxes. LHM has successfully simulated and projected streamflow and groundwater fluctuations for multiple basins across the United States at sub-km spatial and hourly time scale resolution. Here, we apply LHM to the Mekong River Basin at 2 km spatial scale, with sub-daily temporal resolution. We apply this model to simulate water budget trends and fluxes both basin-wide and within focus watersheds including the Tonle Sap and Chiang Saen. These results could present a foundation for advanced land surface modeling and expand our awareness of natural and anthropogenic impacts.