Power 모형을 이용한 비정상성 확률강수량 산정
Estimates the Non-Stationary Probable Precipitation Using a Power Model
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In this study, we performed a non-stationary frequency analysis using a power model and the model was applied for Seoul, Daegu,Daejeon, Mokpo sites in Korea to estimate the probable precipitation amount at the target years (2020, 2050, 2080). We used the annualmaximum precipitation of 24 hours duration of precipitation using data from 1973 to 2009. We compared results to that of nonstationaryanalyses using the linear and logistic regression. The probable precipitation amounts using linear regression showed verylarge increase in the long term projection, while the logistic regression resulted in similar amounts for different target years becausethe logistic function converges before 2020. But the probable precipitation amount for the target years using a power model showedreasonable results suggesting that power model be able to reflect the increase of hydrologic extremes reasonably well.
Abstract
In this study, we performed a non-stationary frequency analysis using a power model and the model was applied for Seoul, Daegu,Daejeon, Mokpo sites in Korea to estimate the probable precipitation amount at the target years (2020, 2050, 2080). We used the annualmaximum precipitation of 24 hours duration of precipitation using data from 1973 to 2009. We compared results to that of nonstationaryanalyses using the linear and logistic regression. The probable precipitation amounts using linear regression showed verylarge increase in the long term projection, while the logistic regression resulted in similar amounts for different target years becausethe logistic function converges before 2020. But the probable precipitation amount for the target years using a power model showedreasonable results suggesting that power model be able to reflect the increase of hydrologic extremes reasonably well.
참고문헌 (11)
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