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首页> 外文期刊>Journal of hydrologic engineering >Simulation of Climate Change Impacts on Streamflow in the Bosten Lake Basin Using an Artificial Neural Network Model
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Simulation of Climate Change Impacts on Streamflow in the Bosten Lake Basin Using an Artificial Neural Network Model

机译:利用人工神经网络模型模拟气候变化对博斯腾湖流域河流的影响

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摘要

Impacts of climate change on water resource in the Bosten Lake basin in the south slope of the Tianshan Mountains in Xinjiang, China, were evaluated using an artificial neural network model. The model was trained using the error backpropagation algorithm and validated for a major catchment that covers 82% of the Bosten Lake basin and has the only available weather and streamflow data. After validating the model it was used to examine the surface hydrology responses to changes of regional temperature and precipitation. Major results showed that because of an additional effect on glacier melt in the upper reach of the basin temperature increase can cause large increases of streamflow. Model results also showed that if the current climate trend continues, the annual streamflow would increase by 38% of its current volume, and the summer and winter streamflow would increase by 71.8 and 11.4% of their respective current volume in the next 50-70 years, highlighting challenges for the basin's water resources management and flood protection.
机译:利用人工神经网络模型评估了气候变化对中国新疆天山南坡博斯腾湖流域水资源的影响。该模型使用误差反向传播算法进行了训练,并针对覆盖了博斯腾湖流域82%的主要集水区进行了验证,并具有唯一可用的天气和流量数据。验证模型后,将其用于检查地表水文学对区域温度和降水变化的响应。主要结果表明,由于流域上游对冰川融化的附加影响,温度升高会导致水流大大增加。模型结果还显示,如果当前的气候趋势持续下去,则未来50-70年内,年流量将增加其当前流量的38%,夏季和冬季的流量将分别增加其当前流量的71.8和11.4%。 ,突出了流域水资源管理和防洪方面的挑战。

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