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Establishment of Inundation Probability DB for Forecasting the Farmland Inundation Risk Using Weather Forecast Data

기상예보 기반 농촌유역 침수 위험도 예보를 위한 침수 확률 DB 구축

  • Kim, Si-Nae (Department of Rural Systems Engineering, Seoul National University) ;
  • Jun, Sang-Min (Department of Rural Systems Engineering, Seoul National University) ;
  • Lee, Hyun-Ji (Department of Rural Systems Engineering, Seoul National University) ;
  • Hwang, Soon-Ho (Research Institute of Agriculture and Life Sciences, College of Agriculture and Life Sciences, Seoul National University) ;
  • Choi, Soon-Kun (Climate Change and Agroecology Division, National Institute of Agricultural Sciences) ;
  • Kang, Moon-Seong (Department of Rural Systems Engineering, Institute of Agriculture and Life sciences, Institute of Green Bio Science and Technology, Seoul National University)
  • Received : 2020.05.15
  • Accepted : 2020.07.03
  • Published : 2020.07.31

Abstract

In order to reduce damage from farmland inundation caused by recent climate change, it is necessary to predict the risk of farmland inundation accurately. Inundation modeling should be performed by considering multiple time distributions of possible rainfalls, as digital forecasts of Korea Meteorological Administration is provided on a six-hour basis. As building multiple inputs and creating inundation models take a lot of time, it is necessary to shorten the forecast time by building a data base (DB) of farmland inundation probability. Therefore, the objective of this study is to establish a DB of farmland inundation probability in accordance with forecasted rainfalls. In this study, historical data of the digital forecasts was collected and used for time division. Inundation modeling was performed 100 times for each rainfall event. Time disaggregation of forecasted rainfall was 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 calculated by extracting the number of inundation occurrences out of the total number of simulations, and the results were stored in the DB of farmland inundation probability. The results of this study can be used to quickly predict the risk of farmland inundation, and to prepare measures to reduce damage from inundation.

Keywords

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