Abstract
Model based on canonical correlation analysis (CCA) and group method of data handling (GMDH) are explicate to obtain a better flood quantile estimation at ungauged sites. CCA is used to build a canonical physiographical space by applying the site characteristics from gauged station. Then GMDH model is used to distinguish the functional relationship between flood quantiles and the physiographic variables in the CCA space. The proposed model is applied to 70 catchments in Peninsular Malaysia. The jackknife procedure is used to evaluate the performance of proposed model. Result of proposed model compared with Traditional CCA model, linear regression (LR) model and GMDH model. The results indicated that the proposed model CCA-GMDH deliver the best performance among all models in terms of prediction accuracy.
Highlights
Flood event is one of the most life-threatening and repeated type of natural disasters that take place in Peninsular Malaysia
The performance of each model is evaluated with the following error indices which are the mean absolute error (MAE), root mean square error (RMSE) and Nash-Sutcliffe coefficient of efficiency (CE) and correlation coefficient
The proposed model is a combination between group method of data handling and canonical correlation analysis (CCA-GMDH)
Summary
Flood undoubtedly cannot be prevented from occurring, but human being can prepare for it. This problem makes a reliable estimation of flood quantiles is necessary for planning flood risk project (e.g., roads, culverts and dams), the safe design of the river system, and it give a closed valuation budget of flood protection project. In order to acquire accurate estimation of flood quantiles, recorded historical time series data of the stream flows required. Long term historical data needed for estimation to produce a more reliable outcome compared to short term data and may reduce the risk. It usually occurs that the historical data at target site not always available. The UK Flood Estimation Handbook (FEH) notes “many flood estimation problems arise at ungauged sites that there are no flood peak data” (Reed and Robson, 1999)
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