Sustainable Water Resource Management by Considering Both Human and Ecosystem Needs
关键词: 河川流量管理； 台湾生态水文指针系统； 人工智能技术； 非支配排序基因遗传算法II； 永续水资源管理； Streamflow Regime Management； Taiwan Eco-Hydrologic Indicator System (TEIS)； Artificial Intelligence Techniques； Non-Dominated Sorting Genetic Algorithm II (NSGA-II)； Sustainable Water Resources Management摘要:
Abstract: In response to global climate change and the raise of eco-environmental restoration concept, the equity between ecosystems, environment and human beings gains increasing attention for the past years. The concept of streamflow regime management is to incorporate ecological sustainability into flow regime management by taking the needs of both human and river ecosystems into consideration. The Taiwan Eco-hydrologic Indicator System (TEIS) is an important guiding reference for sustainable water resources management, which confines water resources development to environmental load for maintaining sus-tainable development principles. This study uses artificial intelligence techniques to build up a hybrid ANN that combines the self-organizing feature map (SOM) and the radial basis function neural networks (RBFNNs) into the self-organizing radial basis network (SORBN) for estimating fish bio-diversity based on TEIS statistics. The results show that this model not only can categorize stream flow data but also can es-timate fish bio-diversity quickly, efficiently and precisely. Then, the concept of improving riverine biodi-versity is implemented to develop sustainable water resource management by considering both human and ecosystem needs by using the non-dominated sorting genetic algorithm II (NSGA-II). For the mul-ti-objective algorithm, the objective function for human requirements expects to provide the least volume of total water deficit and the smallest water shortage index, and avoid the occurrence of serious drought periods due to over-concentrated water shortage in certain period; while the objective function, i.e., the biodiversity estimated by ANN, for ecological requirements expects to satisfy human requirements as well as riverine biodiversity based on flow regime management. This study also provides a sustainable water resources management which can satisfy human and ecosystem needs simultaneously.
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