Based on the basic principles of BP artificial neural network model and the fundamental law of water and sediment yield in a river basin, a BP neural network model is developed by using observed data, with rainfall co...Based on the basic principles of BP artificial neural network model and the fundamental law of water and sediment yield in a river basin, a BP neural network model is developed by using observed data, with rainfall conditions serving as affecting factors. The model has satisfactory performance of learning and generalization and can be also used to assess the influence of human activities on water and sediment yield in a river basin. The model is applied to compute the runoff and sediment transmission at Xingshan, Bixi and Shunlixia stations. Comparison between the results from the model and the observed data shows that the model is basically reasonable and reliable.展开更多
Hydropower resources in river basins are typically developed in a cascade manner. The cascade hydropower stations use water from the same river; in a sense, they form a cluster of hydropower stations which are linked ...Hydropower resources in river basins are typically developed in a cascade manner. The cascade hydropower stations use water from the same river; in a sense, they form a cluster of hydropower stations which are linked together by the river stream. The dispatch and management of the cascade hydropower stations in a river basin differ from those of an ordinary single hydropower station. Without doubt, unified dispatch can facilitate the full harnessing of hydraulic resources and is in a better position to fulfill the objectives in the development of river basin. As a result, more and more river-basin cascade power stations around the world implement unif ied dispatching.展开更多
为揭示变化环境下长江和黄河流域不同区域枯水遭遇对国家水网工程的规划、设计与运行的影响,采用Copula函数、空间插值、冷热点分析、SWAT模型等方法,分析了两流域枯水遭遇概率的时空演变特征并预测其未来趋势。结果表明:上游大金-兰州...为揭示变化环境下长江和黄河流域不同区域枯水遭遇对国家水网工程的规划、设计与运行的影响,采用Copula函数、空间插值、冷热点分析、SWAT模型等方法,分析了两流域枯水遭遇概率的时空演变特征并预测其未来趋势。结果表明:上游大金-兰州组合、雅江-兰州组合枯水遭遇概率以每10 a 1.46%~1.57%的速率显著上升,而大通-花园口组合以每10 a 1.04%的速率显著下降;大金站与雅江站的热点区域主要位于长江中上游与长三角地区,冷点区域位于黄河“几字弯”及长江两湖地区;兰州站与花园口站的热点区域位于黄河中游黄土高原以南,冷点区域集中于长江中下游;未来各站点组合枯水遭遇概率的多模式平均值均超过20%,其中大金-兰州组合与大通-花园口组合呈先减小后增大的趋势,雅江-兰州组合呈线性增大趋势,黄家港-花园口组合呈先减小后缓升趋势。展开更多
文摘Based on the basic principles of BP artificial neural network model and the fundamental law of water and sediment yield in a river basin, a BP neural network model is developed by using observed data, with rainfall conditions serving as affecting factors. The model has satisfactory performance of learning and generalization and can be also used to assess the influence of human activities on water and sediment yield in a river basin. The model is applied to compute the runoff and sediment transmission at Xingshan, Bixi and Shunlixia stations. Comparison between the results from the model and the observed data shows that the model is basically reasonable and reliable.
文摘Hydropower resources in river basins are typically developed in a cascade manner. The cascade hydropower stations use water from the same river; in a sense, they form a cluster of hydropower stations which are linked together by the river stream. The dispatch and management of the cascade hydropower stations in a river basin differ from those of an ordinary single hydropower station. Without doubt, unified dispatch can facilitate the full harnessing of hydraulic resources and is in a better position to fulfill the objectives in the development of river basin. As a result, more and more river-basin cascade power stations around the world implement unif ied dispatching.
文摘为揭示变化环境下长江和黄河流域不同区域枯水遭遇对国家水网工程的规划、设计与运行的影响,采用Copula函数、空间插值、冷热点分析、SWAT模型等方法,分析了两流域枯水遭遇概率的时空演变特征并预测其未来趋势。结果表明:上游大金-兰州组合、雅江-兰州组合枯水遭遇概率以每10 a 1.46%~1.57%的速率显著上升,而大通-花园口组合以每10 a 1.04%的速率显著下降;大金站与雅江站的热点区域主要位于长江中上游与长三角地区,冷点区域位于黄河“几字弯”及长江两湖地区;兰州站与花园口站的热点区域位于黄河中游黄土高原以南,冷点区域集中于长江中下游;未来各站点组合枯水遭遇概率的多模式平均值均超过20%,其中大金-兰州组合与大通-花园口组合呈先减小后增大的趋势,雅江-兰州组合呈线性增大趋势,黄家港-花园口组合呈先减小后缓升趋势。
