Integrated and Sustainable Water Management of Red–Thai Binh Rivers System Under Change
Monday, 15 December 2014: 9:40 AM
Vietnam is currently undergoing a rapid economic and demographic development, characterized by internal migrations from the rural areas to the main cities with increasing water demands to guarantee adequate energy and food productions. Hydropower is the primary renewable energy resource in the country, accounting for 33% of the total electric power production, while agriculture contributes for 18% of the national GDP and employs 70% of the population. To cope with this heterogeneous and fast-evolving context, water resources development and management have to be reconsidered by enlarging their scope across sectors and by adopting effective tools to analyze the potential of current and projected infrastructure along with their operating strategies. This work contributes a novel decision-analytic framework based on Multi-Objective Evolutionary Direct Policy Search (MOE-DPS) to support the design of integrated and sustainable water resources management strategies in the Red–Thai Binh River system. The Red River Basin is the second largest basin of Vietnam, with a total area of about 169,000 km2, and comprises three main tributaries and several reservoirs, namely SonLa and HoaBinh on the Da River, ThacBa and TuyenQuang on the Lo River. These reservoirs are regulated for maximizing hydropower production, mitigating flood primarily in Hanoi, and guaranteeing irrigation water supply to the agricultural districts in the delta. The dimensionality of the system and the number of objectives involved increase the complexity of the problem. We address these challenges by combining the MOE-DPS framework with Gaussian radial basis functions policy approximation and the Borg MOEA, which have been demonstrated to guarantee good solutions quality in such many objective policy design problems. Results show that the proposed framework successfully identified alternative management strategies for the system, which explore different tradeoffs among the multi-sector services involved. These solutions are then evaluated under various scenarios of climate change and projected socio-economic conditions to identify their vulnerabilities and, possibly, to design improved operating policies, which are more robust to the future uncertainties.