Future hydrological alterations in the Mekong Delta under the impact of water resources development, land subsidence and sea level rise

Study region: The Mekong floodplains and delta are among the most agriculturally productive and biologically diverse waterscapes of the world, but sea level rise, land subsidence, and the proposed upstream development of over 126 hydropower dams and extensive delta-based water infrastructure have raised concern due to potential impacts on the hydrology of the region. Study focus: This study aims to quantify the effects of water infrastructure development, land subsidence and sea level rise on hydrological regimes of the Mekong floodplains and delta through the development and application of a hydrodynamic model. New hydrological insights for the region: Depending on hydrological characteristics of each region (river-dominated, transitional or tidal), the influence of each potential driver may vary. The operation of proposed hydropower dams would change river-dominated upper floodplain’s water levels by 26 to 70% and −0.8 to −5.9% in the dry and wet season respectively, but the impact diminishes throughout the floodplains. In the wet season, the upper Vietnamese Delta changes from a transitional stage to a river-dominated stage, and localized water infrastructure development in the upper delta has the greatest effect on water levels in the region. Land subsidence combined with sea level rise could have the greatest future influence on flooding in the delta if current rates are extrapolated. Sustainable water management strategies are thus necessary to mitigate changes in the floodplains and delta and increase resilience to sea level rise and land subsidence

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Farmers are the key actors of land-use change processes. It is thus essential to choose a suitable architecture for farmer behavior to model such processes. In this paper, we compared three models with different architectures to model the farmer behavior in the coastal areas of the Ben Tre province: (i) The first one is a probabilistic model that allows farmer to select the land-use pattern based on land change probability; (ii) The second model is based on multi-criteria decision making and takes into account the land suitability of the parcel and the farmer benefit; (iii) The third model used a BDI (Beliefs - Desires - Intentions) architecture. For each of these models, we have compared the difference between simulated data and real data by using the Fuzzy Kappa coefficient. The results show the suitability of the BDI architecture to build land-use change model and to support decision-making on land-use planning