| 袁喆,杨志勇,史晓亮,严登华.灰色微分动态自记忆模型在径流模拟及预测中的应用[J].水利学报,2013,44(7): |
| 灰色微分动态自记忆模型在径流模拟及预测中的应用 |
| Differential Hydrological Grey Self-memory Model for runoff simulation and prediction |
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| DOI： |
| 中文关键词: 灰色模型 自记忆理论 季节/年际性指数 径流 |
| 英文关键词: Grey model self-memory theory annual/seasonal index runoff |
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| 中文摘要: |
| 在灰色微分动态模型的基础之上，采用季节/年际性指数对原始降水和实测径流进行预处理，并引入自记忆函数，构建灰色微分动态自记忆模型，将其应用于滦河流域径流过程的模拟和预测。结果表明：（1）采用预处理前的降水径流数据所构建的DHGM（2，2）模型和DHGM（2，2）自记忆模型在年尺度和月尺度上的径流模拟效果较差，难以反映径流的变化过程，对输入数据进行预处理后，构建的DHGM（2，2）自记忆模型模拟精度得到了很大的提高，三道河子站和滦县站年径流和月径流模拟序列的Nash-Sutcliffe系数和相关系数均达到了0.6以上；（2）模型在年尺度和月尺度的径流预测中具有一定的适用性，且结构简单、计算方便，但需要进一步考虑蒸发、土地利用和人类活动等因素，使模型更为完善。 |
| 英文摘要: |
| Based on the differential hydrological grey-model， the annual/seasonal indexes were applied to data pre-processing of precipitation and runoff for establishing the Differential Hydrological Grey Self-memory Model with the self-memory theory. The model was used to simulate and predict the runoff in different time scales. The results show that （a） DHGM （2， 2） and Self-memory DHGM （2， 2） which constructed by initial data cannot described the runoff processes in annual and monthly scales. With the pre-processing data of precipitation and runoff，the Self-memory DHGM （2，2） performed better both in Shandaohezi and Luanxian discharges， and Nash-Sutcliffe and correlation coefficients reached more than 0.6；（b） the model was applicable to predicting the runoff especially on an annual time scale. The structure model was simple and easy to operate，nevertheless，the factors of evaporation，land-use and human activity should be taken into consideration so that the model can be more perfect. |
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