Recent studies by the United Nations Environment Programme (UNEP) and the Intergovernmental Panel on Climate Change (IPCC) indicate that Vietnam is one of the countries most affected by climate change. The variability of climate in this region, characterized by large fluctuations in precipitation and temperature, has caused significant changes in surface water resources. This study aims to project the impact of climate change on the seasonal availability of surface water of the Huong River in Central Vietnam in the twenty-first century through hydrologic simulations driven by climate model projections. To calibrate and validate the hydrologic model, the model was forced by the rain gage-based gridded Asian Precipitation–Highly Resolved Observational Data Integration Towards Evaluation of water resources (APHRODITE) V1003R1 Monsoon Asia precipitation data along with observed temperature, humidity, wind speed, and solar radiation data from local weather stations. The simulated discharge was compared to observations for the period from 1951 until present. Three Global Climate Models (GCMs) ECHAM5-OM, HadCM3 and GFDL-CM2.1 integrated into Long Ashton Research Station-Weather Generator (LARS-WG) stochastic weather generator were run for three IPCC–Special Report on Emissions Scenarios (IPCC-SRES) emissions scenarios A1B, A2, and B1 to simulate future climate conditions. The hydrologic model simulated the Huong River discharge for each IPCC-SRES scenario. Simulation results under the three GCMs generally indicate an increase in summer and fall river discharge during the twenty-first century in A2 and B1 scenarios. For A1B scenario, HadCM3 and GFDL-CM2.1 models project a decrease in river discharge from present to the 2051–2080 period and then increase until the 2071–2100 period while ECHAM5-OM model produces opposite projection that discharge will increase until the 2051–2080 period and then decrease for the rest of the century. Water management impacts, such as irrigation or dam regulation, were not considered in this study. However, the results provide local policy makers with quantitative data to consider possible adjustment of future dam capacities for development of flood control policies.
This is an open access article distributed under the Creative Commons Attribution License
which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited