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Updated: Jul 9, 2025

Watershed Planning within a Quantitative Scenario Analysis Framework
Published on: July 24, 2016
An optimization framework for basin-scale water environmental carrying capacity
Jue Ding1, Qiuwen Chen1, Yuchen Chen1
1State Key Laboratory of Hydrology-Water Resources & Hydraulic Engineering, Nanjing Hydraulic Research Institute, Nanjing, 210098, China; Center for Eco-Environment Research, Nanjing Hydraulic Research Institute, Nanjing, 210098, China.
Abstract:
The interaction between water environment and social economy at a basin scale is complex and challenging to quantify. To address this issue, this study proposes an integrated framework that builds parametric connections among water, contaminants, administrative regions, and social activities. The framework, known as the water environmental carrying capacity (WECC) optimization framework, effectively captures the intricacy of the interaction and integrates socio-economic parameter structure relationships, a water environmental model, a WECC optimization model, and a sensitivity analysis of regulatory parameters. Applied to the Anhui-Huaihe Basin in mid-eastern China, the framework considers nine administrative regions and three economic factors: industry, agriculture, and GDP per capita (pGDP). Results show that the current water environmental carrying capacity of the watershed is insufficient to meet socio-economic development requirements. After optimization, the WECC for industry, agriculture, and pGDP in the region increased by 22.40%, 26.59%, and 15.08% respectively. Overall COD and NH4-N discharge decreased by 13.6% and 14.7% respectively, effectively reducing pollution loads in rivers and enhancing sustainable development potential. At the regional scale, optimization for industry, agriculture, and pGDP exhibited different characteristics, but all aimed to improve efficiency by reducing the K value (pollution discharge/output value ratio). Regions with industrial treatment rates (αwt) below 0.8 should prioritize increasing treatment rates, while those above 0.8 should consider industrial upgrading for enhanced efficiency. For agriculture, important sensitive parameters for farming and livestock breeding are the proportion of high standard farmland (αs) and the scale breeding ratio (αb), which should be increased to above 0.15 and 0.83 respectively for all regions to achieve agricultural optimization. For pGDP optimization, the focus is on improving living environments and reducing pollution discharge, with crucial measures including collecting and treating rural domestic sewage, where the rural toilet improvement rate (αt) in each region should be increased to 0.78 or above. The results emphasize the need for both interregional allocation and intraregional planning to achieve comprehensive basin optimization and a harmonious balance between regional development and water environment.
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