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Title Scenario-based numerical simulation to predict future water quality for developing robust water management plan: a case study from the Hau River, Vietnam
ID_Doc 69489
Authors Duc, NH; Avtar, R; Kumar, P; Lan, PP
Title Scenario-based numerical simulation to predict future water quality for developing robust water management plan: a case study from the Hau River, Vietnam
Year 2021
Published Mitigation And Adaptation Strategies For Global Change, 26.0, 7
Abstract Rapid population growth, urbanization, industrialization, and climate change are the key drivers causing serious water pollution around the globe. Considering the impacts of these key drivers, this study employed the Water Evaluation and Planning (WEAP) simulation tool to simulate the future water quality in a nearly 60-km stretch of the Hau River, Vietnam. The business-as-usual (BAU) scenario; scenarios with measures (WM), i.e., wastewater treatment plants (WWTPs) for treating 75% (WM75) and 100% (WM100) of total future wastewater generated; and the optimistic scenario (WM_Opt., i.e., WM100 + additional treatment plants for river water (RWTPs)) to achieve the desired water quality, were applied to simulate the future Hau River water quality for the year 2030. Result suggests that the average values of biochemical oxygen demand (BOD), total coliform (TC), nitrate -(NO3-), and phosphate -(PO43-) in the wet season of 2030 under BAU scenario will be increased by 16.01%, 40.85%, 30.49%, and 20.22%, respectively, in comparison to those of the current year, i.e., 2018. In the dry season, these rates will be increased by 27.80%, 65.94%, 31.05%, and 20.64%, respectively. Under the scenario with measures (WM75 and WM100), although the Hau River water quality was improved but did not reach the desired limits, especially for BOD and -PO43 levels in the downstream region. However, under the WM_Opt. scenario, the average simulated values of both BOD and -PO43- will be significantly declined by 76.53% and 63.96%, respectively as compared to the current situation and help to achieve river water quality under class A. This study is providing policy-relevant scientific information, vital for sustainable water resource management.
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