期刊
JOURNAL OF WATER AND CLIMATE CHANGE
卷 13, 期 8, 页码 3046-3060出版社
IWA PUBLISHING
DOI: 10.2166/wcc.2022.106
关键词
climate change; DO; flow regime; semi-arid prairies; TDS
资金
- IWHR Open Research Fund of State Key Laboratory of Simulation and Regulation of Water Cycle in River Basin [IWHR-SKL-201916]
- Agriculture Development Fund (ADF) of Saskatchewan
- NSERC Discovery Grant of Canada
In this study, the impacts of climate change on the water quantity and quality of the Qu'Appelle River in Saskatchewan, Canada were investigated using the artificial neural network (ANN) method. The study found that climate change would lead to a heterogeneous change in precipitation and temperature patterns, causing serious degradation in the river discharge as well as dissolved oxygen (DO) and total dissolved solids (TDS) concentration levels, resulting in deterioration in the sustainability of the river system and ecological health of the region.
In this study, the artificial neural network (ANN) method was applied to investigate the impacts of climate change on the water quantity and quality of the Qu'Appelle River in Saskatchewan, Canada. First, the second-generation Canadian earth system model (CanESM2) was adopted to predict future climate conditions. The Statistical DownScaling Model (SDSM) was then applied to downscale the generated data. To analyze the water quality of the river, concentrations of dissolved oxygen (DO) and total dissolved solids (TDSs) from the river were collected. Using the collected climate and hydrometric data, the ANNs were trained to simulate (i) the ratio of snowfall-to-total precipitation based on the temperature, (ii) the river flow rate based on the temperature and precipitation; and (iii) DO and TDS concentrations based on the river flow and temperature. Finally, the generated climate change data were used as inputs to the ANN model to investigate the climate change impacts on the river flow as well as DO and TDS concentrations within the selected region. Hydrologic alteration of the river was evaluated via the Range of Variability Approach (RVA) under historical and climate change scenarios. The results under climate change scenarios were compared with those under historical scenarios and indicated that climate change would lead to a heterogeneous change in precipitation and temperature patterns. These changes would have serious degrading impacts on the river discharge as well as DO and TDS concentration levels, causing deterioration in the sustainability of the river system and ecological health of the region.
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