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RISS 인기검색어
- 검색키워드
- 저자 : Dasang Ko (검색결과 3 건)
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고다상(Ko, Dasang),주영철(Joo, Yeongcheol),이태삼(Lee, Taesam) 한국방재학회 2020 한국방재학회논문집 Vol.20 No.1
Recently, the frequency of drought occurrence and the resulting damage has increased due to climate change. Frequent severe droughts induce water shortages in agricultural reservoirs. The role of drought monitoring and prediction is critical for mitigating the effects of severe drought in agricultural areas. In this study, a compound standardized storage and precipitation index (CSSPI) was developed that adapted the existing drought index-the standardized precipitation index (SPI)-by adding hydrological data on storage rate. Furthermore, the future storage rate was simulated using autoregressive models (AR) to estimate the future CSSPI. A dataset containing records of reservoirs and precipitation at the three areas of Jungbu, Youngnam, and Honam was applied to estimate the current and future status of the CSSPI. The results indicate that the CSSPIs generated accurately present the past pattern of the observed data and that they can be considered as inputs for predicting future drought conditions. 최근 기후변화에 따라 가뭄의 발생빈도와 그 피해가 점차 증가하고 있다. 요즈음 극심한 가뭄으로 인한 관개저수지의 물부족으로 인해 농업의 피해가 많이 발생하였다. 가뭄의 모니터링과 예측은 농업에서 심각한 가뭄의 영향을 완화시키는 것에목적을 두고 있다. 이번 연구를 통하여 기존의 가뭄지수인 표준 강수 지수(Standardized Precipitation Index)에 수문학적인저수율의 정보를 추가하여 복합 표준 저수 및 강수 지수(Compound Standardized Storage and Precipitation Index, CSSPI)가개발되었다. 더불어, 미래 CSSPI를 예측하기 위해서 미래 저수율은 AR모델을 사용하여 시뮬레이션 되었다. 중부지역, 영남지역, 호남지역의 각 3곳의 저수지와 각 3곳의 강수량 자료의 데이터세트가 현재와 미래의 CSSPI를 예측하기 위하여 사용되었다. 그 결과 생성된 CSSPI는 관측된 자료의 패턴을 잘 보여주었고, CSSPI는 미래의 가뭄상태를 예측할 수 있는 기초자료가될 것으로 사료된다.
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Error influence of radar rainfall estimate on rainfall runoff
Taewoong Park,Taesam Lee,Sora Ahn,Dongyul Lee,Jungchan Kim,Dasang Ko 한국방재학회 2014 한국방재학회 학술발표대회논문집 Vol.2014 No.-
Radars have been widely employed to detect precipitation and to predict rainfall. However, the radar-based estimate of rainfall is affected by uncertainties or errors such as mis-calibration, beam blockage, anomalous propagation, and ground cutter. Even though these uncertainties of radar rainfall estimate (RRE) have been studied, their effect on a runoff simulation especially to the peak discharge and peak time have not been much focused. Therefore, the objective of current study is to analyze the effect of the RRE uncertainties or errors based on synthetic simulation of RRE and its effect on peak discharge. First of all, mean of modeled radar rainfall is fixed (e.g., 100mm) and its error variance was set as ±10mm, ±20mm, ±40mm, and ±50mm independent to each grid cell. This independent simulation is based on white-noise process. The second simulation included a spatial-correlation between grid cells in simulating the error variance. The relationship between the distances of rain gauges and the corresponding correlations was modeled with the power law function. The parameters of the function were estimated through meta-heuristic method (specifically harmony search). Moreover, in order to find the correlation of observed data, the whole data from 27 rain gauges in the basin and the corresponding RRE from the dual polarization radar on Mt. Bisl in Korea were employed. The results of the former simulation (independent errors to each grid cell) show that the bias of the peak discharge is increased along with the variance increased, which is caused by influence of zero values. In the latter simulation (spatially correlated errors between grid cells), the results show that the peak discharge variance from the latter presents much larger than that of the former. Furthermore, the spatial distribution pattern of the modeled radar rainfall exhibited very similar to that of the real rainfall. Finally, we concluded that the error variance of RRE on runoff simulation leading bias and high uncertainty.
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