기상예보 기반 농촌유역 침수 위험도 예보를 위한 침수 확률 DB 구축
Establishment of Inundation Probability DB for Forecasting the Farmland Inundation Risk Using Weather Forecast Data
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In order to reduce damage from farmland inundation caused by recent climate change, it is necessary to predict the risk of farmland inundationaccurately. Inundation modeling should be performed by considering multiple time distributions of possible rainfalls, as digital forecasts of KoreaMeteorological Administration is provided on a six-hour basis. As building multiple inputs and creating inundation models take a lot of time, it isnecessary to shorten the forecast time by building a data base (DB) of farmland inundation probability. Therefore, the objective of this study is toestablish a DB of farmland inundation probability in accordance with forecasted rainfalls. In this study, historical data of the digital forecasts wascollected and used for time division. Inundation modeling was performed 100 times for each rainfall event. Time disaggregation of forecasted rainfallwas performed by applying the Multiplicative Random Cascade (MRC) model, which uses consistency of fractal characteristics to six-hour rainfall data. To analyze the inundation of farmland, the river level was simulated using the Hydrologic Engineering Center - River Analysis System (HEC-RAS). The level of farmland was calculated by applying a simulation technique based on the water balance equation. The inundation probability was calculatedby extracting the number of inundation occurrences out of the total number of simulations, and the results were stored in the DB of farmland inundationprobability. The results of this study can be used to quickly predict the risk of farmland inundation, and to prepare measures to reduce damage frominundation.
Abstract
In order to reduce damage from farmland inundation caused by recent climate change, it is necessary to predict the risk of farmland inundationaccurately. Inundation modeling should be performed by considering multiple time distributions of possible rainfalls, as digital forecasts of KoreaMeteorological Administration is provided on a six-hour basis. As building multiple inputs and creating inundation models take a lot of time, it isnecessary to shorten the forecast time by building a data base (DB) of farmland inundation probability. Therefore, the objective of this study is toestablish a DB of farmland inundation probability in accordance with forecasted rainfalls. In this study, historical data of the digital forecasts wascollected and used for time division. Inundation modeling was performed 100 times for each rainfall event. Time disaggregation of forecasted rainfallwas performed by applying the Multiplicative Random Cascade (MRC) model, which uses consistency of fractal characteristics to six-hour rainfall data. To analyze the inundation of farmland, the river level was simulated using the Hydrologic Engineering Center - River Analysis System (HEC-RAS). The level of farmland was calculated by applying a simulation technique based on the water balance equation. The inundation probability was calculatedby extracting the number of inundation occurrences out of the total number of simulations, and the results were stored in the DB of farmland inundationprobability. The results of this study can be used to quickly predict the risk of farmland inundation, and to prepare measures to reduce damage frominundation.
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