비정상성 강우모의기법을 이용한 가뭄 예측기법 개발
Development of Drought Forecasting Techniques Using Nonstationary Rainfall Simulation Method
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Drought is a slow-varying natural hazard that is characterized by various factors such that reliable drought forecasting along with uncertainties estimationhas been a major issue. In this study, we proposed a stochastic simulation technique based scheme for providing a set of drought scenarios. Morespecifically, this study utilized a nonstationary Hidden markov model that allows us to include predictors such as climate state variables and globalclimate model’s outputs. The simulated rainfall scenarios were then used to generate the well-known meteorological drought indices such as SPI, PDSIand PN for the three dam watersheds in South Korea. It was found that the proposed modeling scheme showed a capability of effectively reproducing keystatistics of the observed rainfall. In addition, the simulated drought indices were generally well correlated with that of the observed.
Abstract
Drought is a slow-varying natural hazard that is characterized by various factors such that reliable drought forecasting along with uncertainties estimationhas been a major issue. In this study, we proposed a stochastic simulation technique based scheme for providing a set of drought scenarios. Morespecifically, this study utilized a nonstationary Hidden markov model that allows us to include predictors such as climate state variables and globalclimate model’s outputs. The simulated rainfall scenarios were then used to generate the well-known meteorological drought indices such as SPI, PDSIand PN for the three dam watersheds in South Korea. It was found that the proposed modeling scheme showed a capability of effectively reproducing keystatistics of the observed rainfall. In addition, the simulated drought indices were generally well correlated with that of the observed.
참고문헌 (25)
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