Explore the impacts of river flow and water quality on fish communities
Date Issued
2015
Date
2015
Author(s)
Hu, Jia-Hao
Abstract
Subject to the geographic environment and climatic conditions of Taiwan, rivers in Taiwan are of steep slopes and flow into oceans very quickly. Due to the uneven temporal and spatial distribution of rainfall and the severe intensity and short duration of typhoons and storms, sudden rainfall would easily cause huge variations and significant impacts on riverine eco-hydrological environments. The previous research on river basins indicated that river flow and water quality is closely related to each other, which influences river ecosystems simultaneously. To achieve the goal of sustainable development of water resources, rationality and integrity is essential for water resources management while planning to exploit environmental resources in consideration of ecosystem sustainability. Therefore, this study explores the complex relationship among river flow, water quality and fish communities in order to understand the interactive mechanism among each other and develop a methodology suitable for improving river ecosystems; and consequently promotes the management and sustainable development of water resources. In this study, the Xindian River, one of the three major tributaries of the Tamsui River, is chosen as the as study area, which has long-term (2005-2012) daily (river flow) and monthly (water quality) observational data as well as fishery data collected from field surveys. Based on the Taiwan Ecohydrologic Indicator System (TEIS), river flow data is converted into flow regime in a monthly scale. Statistical analyses are then conducted to explore the differences of flow regime, water quality and fish communities between the upstream and downstream areas of the Xindian River. This study next estimates fish diversity indexes by using the Adapted Network-Based Fuzzy Inference System (ANFIS) based on key input factors determined by the Gamma Test (GT), a powerful tool for reducing model complexity of artificial neural networks (ANNs). The results reveal that the constructed model with key input factors selected by the GT can effectively estimate fish diversity indexes, and the estimation performance becomes even better if flow regime can be incorporated as model inputs. Finally, the investigation on the membership functions of the ANFIS can explore the impacts of each input on fish diversity to keep abreast of the variation of the river ecosystem. The results of this study can provide valuable findings as a guiding reference for the practices of eco-hydro system management and the planning of sustainable water resources management of the whole river basin in the future.
Subjects
Eco-hydrology
Tamsui River
Adapted Network-Based Fuzzy Inference System (ANFIS)
Gamma Test (GT)
Fish Community
Flow Regime
SDGs
Type
thesis
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ntu-104-R02622025-1.pdf
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