Development of the one-stop water resources operational system using data of a numerical weather prediction model

Abstract:

This research constructs the one-stop water resources operational system that is based on the connection between short-term numerical weather prediction model(LDAPS, UM3.0, RDAPS) of Korea Meteorological Administration (KMA) and runoff model(COSFIM, K-DRUM) of Korea water resources corporation (K-water) to predict runoff discharge ungagged basin which needs to provide flood and evacuation warning. K-DRUM model works online(Receiving weather forecast data, operating K-DRUM model automatically and offering forecast and warning information to flood manager through forecast monitoring system.), and COSFIM model which needs experience of flood manager and realtime condition data works off line(manager operates COSFIM model with weather forecast data and connects with monitoring system to manage water resources).

We used the values for evaluating the prediction result, which predicted cumulative value, observed cumulative value, the rate of predicted and observed cumulative values(%), predicted mean value, observed mean value, the deviation and deviation ratio of the predicted mean value and the observed mean value, standard deviation of predicted and observed value, standard deviation ratio of predicted and observed value(%). In addition, we use the index to be used mainly calculated and observed values in model for quantitative reliability assessment. It was used A dimensionless index of NSE (Nash-Sutcliffe Efficiency), statistics techniques of index errors PBIAS (Percent Bias), and the ratio of mean square error and standard deviation for observations RSR (RMSE-observations Standard deviation Ratio).

According to the results of analysis, in order to prevent the damage occurred by hydrological disasters that cannot be identified by only observations of rainfall stations, utilizing the numerical weather predictions can be significant factor in the ungagged basin flood control operations management.