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Techniques of Real-Time Flood Forecasting and Low Flow Prediction for Reservoir Operation

水库调度实时洪水预报和低流量预报技术

基本信息

批准号：
07660322
负责人：
NAGAI Akihiro
金额：
$ 1.41万
依托单位：
Okayama University
依托单位国家：
日本
项目类别：
Grant-in-Aid for Scientific Research (C)
财政年份：
1995
资助国家：
日本
起止时间：
1995 至 1997
项目状态：
已结题

项目摘要

Main results obtained in this study are as follows :1. A questionnaire on actual circumstances of reservoir operation was carried out in cooperation with government agencies. It is outlined by summarizing the information on 201 reservoirs with catchment over 50km^2 that real-time forecasting up to 3 hours ahead is of critical importance for flood flow, and that runoff models are used for flood forecasting in about half of the reservoirs, but the filtering techniques are rarely used in actual reservoir operation.2. In order to examine the performance of Long-and Short-Term Runoff model (LST-II) and Tank model used in real-time flood forecasting, both runoff models were applied to the data of 18 years (1979-1996) observed in the Kuroki Dam basin. It is shown that observed hydrographs both in long-term runoff and flood runoff were simulated with good accuracy by both runoff models.3. Such filtering techniques as extended Kalman filter, statistical linearization techniques and back calculation method were applied to real-time flood forecasting with lead time of 1 and/or 3 hours in the Kuroki Dam basin. The results of 19 floods in the basin demonstrate that more accurate flood prediction is attained by adopting the filtering techniques, and that the accuracy evaluated by relative error of predicted discharge by each technique is almost same.4. The performance of several methods for rainfall prediction in real-time flood forecasting was compared by using flood data in the Kuroki Dam basin. It is shown that the simplest method, in which future rainfall are assumed to be constant with the present intensity, gives best results, and that setting the limitations of values of coefficients is necessary for applysing the AR (auto-regressive) method.

本研究取得的主要结果如下：1。与政府机构合作进行了关于水库运行实际情况的调查问卷。通过对201座集水面积在50 km^2以上的水库资料的总结，可以看出，洪水流量实时预报的重要性在于提前3 h，约半数水库采用径流模型进行洪水预报，但滤波技术在实际水库调度中应用较少.为了检验长期和短期径流模型（LST-Ⅱ）和Tank模型在实时洪水预报中的性能，将这两种径流模型应用于黑木大坝流域18年（1979-1996）的观测数据。结果表明，两种径流模型均能较好地模拟长期径流和洪水径流的实测过程.将扩展卡尔曼滤波、统计线性化技术和反算方法等滤波技术应用于黑木坝流域的实时洪水预报，预报提前期为1和/或3 h。对该流域19次洪水的预报结果表明，采用滤波技术预报洪水的精度较高，且以预报流量相对误差评价的精度基本相同.利用黑木大坝流域的洪水资料，对实时洪水预报中几种降雨预报方法的性能进行了比较。结果表明，最简单的方法，其中未来的降雨量被假定为与目前的强度是恒定的，给出了最好的结果，并设置的系数值的限制是必要的applysing AR（自回归）方法。