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Rainfall-Runoff Prediction Using Dynamic Typhoon Information and Surface Weather Characteristic Considering Monsoon Effects

Wei, Chih-Chiang, Hsu, Nien-Sheng, Huang, Chien-Lin
Water resources management 2016 v.30 no.2 pp. 877-895
engineering, hydrologic models, meteorology, monsoon season, prediction, rain, rivers, runoff, stream flow, summer, typhoons, watersheds, Taiwan
In meteorology and engineering, the prediction of quantitative precipitation and streamflow during typhoon events is a vital research topic. In Southern Taiwan, typhoons often occur in the summer. The interaction between the typhoon circulation and southwesterly monsoon flow frequently transports abundant moisture into Southern Taiwan leading to the substantial pouring rains. This study proposes a rainfall-runoff prediction methodology for addressing the complicated inflow forecasts of southwest monsoon rainfall during typhoons in the upper Tsengwen River in Southern Taiwan. This paper is novel in that it incorporates various data types (reservoir inflows, watershed rainfalls, typhoon information, and ground-weather characteristics) that were applied as model inputs. The most frequently used support vector regressions were employed to construct the rainfall-runoff models on the basis of three designed data combination scenarios. Typhoons Kalmaegi (2008), Fung-wong (2008), Jangmi (2008), and Morakot (2009) were used as validation typhoons. The model cases, involving lead times of 1 h to 6 h, were evaluated. Six performance criteria were used in the three scenarios to highlight the scenario capable of identifying the optimal performance level. In addition, this study compared the error rates between accumulation observations and accumulation predictions. The results showed that Scenario 3, which considered typhoon information and ground-weather characteristics simultaneously, had superior watershed rainfall and runoff predictions to those of the other scenarios. Thus, this study demonstrated the feasibility of using the proposed methodology to increase the accuracy of rainfall-runoff predictions.