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1.
武斌 《水利与建筑工程学报》2005,3(3):33-36
水情自动测报可为水库安全渡讯和防洪调度提供可靠的依据。本文以张峰水库工程水情自动测报系统为例,介绍流域水文模型的建立,供相关工程参考。 相似文献
2.
The artificial neural network (ANN) theory has been widely applied to practical applications in hydrology. Since watershed
rainfall–runoff processes are nonlinear and exhibit spatial and temporal variability, the ANN model, which considers watershed
nonlinear characteristics, can usually but not always obtain satisfactory simulation results. The training of an ANN network
is based completely on the reliability of the available hydrologic records. The objective of this study was to provide deterministic
insight into the limitations of storm runoff simulation when using ANN. Hydrologic records of 42 storm events from two watersheds
in Taiwan were adopted for analysis. A deterministic runoff model was used to classify the hydrologic records into “usual”
and “unusual” storm events. The analytical results show that the ANN model could provide good simulation results for “usual”
storm events; however, its performance was poor when it was applied to “unusual” storm events because no consistent hydrologic
characteristics could be extracted from the storm event records using ANN. The success of the ANN model in usual storm discharge
simulations may be mainly due to the input vectors including the previous observed discharge. Moreover, the number of past
periods of rainfall that were set as the input vectors of the ANN model was found to be highly correlated with the watershed
time of concentration. It can be used to efficiently determine the ANN network structure instead of using iterative network
training. 相似文献