Transboundary river basins across developing countries, such as the Lower Mekong River Basin (LMB), are challenging to manage given frequent divergences on development and conservation priorities. Driven by needs to sustain economic performance and reduce poverty, the LMB countries are embarking on significant land use changes in the form of more hydropower dams, to satisfy growing energy demands. This pathway could lead to irreversible changes to the ecosystem of the Mekong River, if not properly managed. Given the uncertain environmental externalities and trade-offs associated with further hydropower development and operation in the LMB, this research develops four plausible scenarios of future hydropower operation, and assesses their likely impact on streamflow and instream total suspended solids and nitrate loads of the Mekong River. The findings suggest that further hydropower operations on either tributary or mainstream could result in annual and wet season flow reduction between 11 and 25% while increase dry season flows by 1 to 15%, when compared to a business-as-usual scenario. Conversely, hydropower operation on both tributary and mainstream could result in dry season flow reduction between 10 and 15%. Both instream TSS and nitrate loads are forecasted to reduce under all three scenarios by as much as 78 and 20%, respectively, compared to the business-as-usual one. These effects are predicted to magnify under extreme climate conditions with dry season flow, TSS, and nitrate levels reduced by as much as 44, 81 and 35%, respectively, during a projected extreme dry climate condition, but less severe under improved operational alternatives. With further hydropower development in the LMB being highly unavoidable, these findings can inform effective transboundary management pathways for balancing electricity generation and protection of riverine ecology, water and food security, and people livelihoods.
Keywords: Lower Mekong Basin; Nitrate; Streamflow; Total suspended solids; Transboundary river basin management; eWater's source modelling framework.
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