| Summary: | 碩士 === 國立中興大學 === 土木工程學系 === 93 === In the past few years, debris flow had caused heavy losses of lives and properties. Therefore, it becomes important to predict rainfalls which may cause mudflows. In 2002, the Water Resources Agency, Ministry of Economic Affairs set up the “runoff prediction system for the Jhuoshuei river basin” to predict short-term rainfalls using an analogical precipitation prediction model and a Grey theory prediction model. The accuracy of rainfall predictions is very important because the predicted rainfall amount is one of the most important input and indices for the rainfall-runoff calculations and debris flow warning systems.
This study only focuses on the Grey theory and analogical precipitation prediction models. The original GM(1,1) prediction model requires four items of data. In this study, we add the conjectured GM(1,1) three data model which combines the moving average and data accumulation techniques to make predictions. For the analogical precipitation prediction model, we use different periods of time, data contenting typhoons (if any), accumulative prediction results (if any), and different sizes of area to make predictions. The predicted results were compared with the real rainfall amount. Helpfully the rainfall related disasters can be reduced with these revised models.
In this study, we found that the GM(1,1) three data model had better prediction results than the four data model. Predictions using the accumulative data also gave better results for the first hour. Here, we suggest the GM(1,1) three data model with the moving average and data accumulation techniques to replace the GM(1,1) four data model. As for the predictions after the second hour, the analogical precipitation prediction model gave better results than the GM(1,1) model. These two prediction methods were not based on the hydrological physics, so, we suggest not making any predictions for more than three hours. When using the prediction results, we also suggest using other strategic decisions to assist in making a final, accurate decision.
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