Guangdong Basic Research Center of Excellence for Ecological Security and Green Development, Guangdong Provincial Key Laboratory of Water Quality Improvement and Ecological Restoration for Watersheds, School of Ecology, Environment and Resources, Guangdong University of Technology, Guangzhou, 510006, China; Research Centre of Ecology & Environment for Coastal Area and Deep Sea, Southern Marine Science and Engineering Guangdong Laboratory (Guangzhou), Guangzhou, 511458, China.
Guangdong Basic Research Center of Excellence for Ecological Security and Green Development, Guangdong Provincial Key Laboratory of Water Quality Improvement and Ecological Restoration for Watersheds, School of Ecology, Environment and Resources, Guangdong University of Technology, Guangzhou, 510006, China; Research Centre of Ecology & Environment for Coastal Area and Deep Sea, Southern Marine Science and Engineering Guangdong Laboratory (Guangzhou), Guangzhou, 511458, China.
J Environ Manage. 2024 Jul;363:121309. doi: 10.1016/j.jenvman.2024.121309. Epub 2024 Jun 6.
Multiple uncertainties such as water quality processes, streamflow randomness affected by climate change, indicators' interrelation, and socio-economic development have brought significant risks in managing water quantity and quality (WQQ) for river basins. This research developed an integrated simulation-optimization modeling approach (ISMA) to tackle multiple uncertainties simultaneously. This approach combined water quality analysis simulation programming, Markov-Chain, generalized likelihood uncertainty estimation, and interval two-stage left-hand-side chance-constrained joint-probabilistic programming into an integration nonlinear modeling framework. A case study of multiple water intake projects in the Downstream and Delta of Dongjiang River Basin was used to demonstrate the proposed model. Results reveal that ISMA helps predict the trend of water quality changes and quantitatively analyze the interaction between WQQ. As the joint probability level increases, under strict water quality scenario system benefits would increase [3.23, 5.90] × 10 Yuan, comprehensive water scarcity based on quantity and quality would decrease [782.24, 945.82] × 10 m, with an increase in water allocation and a decrease in pollutant generation. Compared to the deterministic and water quantity model, it allocates water efficiently and quantifies more economic losses and water scarcity. Therefore, this research has significant implications for improving water quality in basins, balancing the benefits and risks of water quality violations, and stabilizing socio-economic development.
多种不确定性，如水质过程、受气候变化影响的随机水流、指标间的相互关系以及社会经济发展，给流域的水量和水质（WQQ）管理带来了重大风险。本研究开发了一种综合模拟-优化建模方法（ISMA）来同时应对多种不确定性。该方法将水质分析模拟编程、马尔可夫链、广义似然不确定性估计和区间两阶段左手边机会约束联合概率规划纳入一个综合非线性建模框架。以东江下游和三角洲的多个取水项目为例，对所提出的模型进行了验证。结果表明，ISMA 有助于预测水质变化趋势，并定量分析 WQQ 之间的相互作用。随着联合概率水平的提高，在严格的水质情景系统下，效益将增加[3.23，5.90]×10 元，基于数量和质量的综合水资源短缺将减少[782.24，945.82]×10 m，水分配增加，污染物生成减少。与确定性和水量模型相比，它能够更有效地分配水资源，并量化更多的经济损失和水资源短缺。因此，本研究对于改善流域水质、平衡水质违规的效益和风险以及稳定社会经济发展具有重要意义。
