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首页> 外文会议>Flood Forecasting and Water Resources Assessment for IAHS(International Association of Hydrological Sciences)-PUB >Development of a Moving Average Model for Predicting monthly Runoff in the Heihe River
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Development of a Moving Average Model for Predicting monthly Runoff in the Heihe River

机译：黑河径流预测的滑动平均模型的建立。

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摘要

Estimating monthly runoff from monthly rainfall is very important for water resources management in the inland river basin. In this study, firstly, the monthly rainfall data from 12 stations was processed and completed for a long time monthly series of 40 years. Based on the statistical analysis and double mass analysis, the tests on homogeneity and consistency show that none of the annual rainfall and runoff series has a linear trend and the mean of the series appear to be stable at 95% confidence level. Secondly, the monthly series of area rainfall over the study catchment area was calculated through Thiessen Polygon method by using the annual rainfall at 11 stations. Thirdly, the moving average model for predicting monthly runoff using threshold losses was developed with a multiple linear regression method. The model was calibrated with the first 20 years' monthly data series with a high coefficient of efficiency (CE) of 0.91 and validated with second 20 years' data series with a better CE of 0.85. Finally, the results of model performance show that the relation between the monthly area rainfall and the runoff is better and that the correlation substantially improves by taking into account the threshold rainfall losses of 20 mm. Model results improved most significantly by including the first month back.
机译：根据内陆流域的水资源管理，根据月降雨量估算月径流量非常重要。在这项研究中，首先，对12个站的月降雨量数据进行了处理，并完成了长达40年的长时间每月序列。基于统计分析和双重质量分析，均质性和一致性的测试表明，年降水量和径流序列均没有线性趋势，并且该序列的均值在95％的置信水平下似乎稳定。其次，利用蒂森多边形法，利用11个站点的年降水量，计算了研究集水区的月降水量序列。第三，采用多元线性回归方法建立了利用阈值损失预测月径流量的移动平均模型。该模型使用前20年的每月数据系列进行了校准，效率系数（CE）为0.91，并使用后20年的数据系列进行了验证，其较好的CE为0.85。最后，模型性能的结果表明，每月降雨与径流之间的关系更好，并且通过考虑20 mm的阈值降雨损失，相关性得到了显着改善。通过将第一个月算在内，模型结果得到了最大的改善。

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