보간법에 따른 기상레이더 강수자료와 지상 강수자료의 합성기법 평가 = Assessment of merging weather radar precipitation data and ground precipitation data according to various interpolation method

다국어 초록 (Multilingual Abstract)

The increased frequency of meteorological disasters has been observed due to increased extreme events such as heavy rainfalls and flash floods. Numerous studies using high-resolution weather radar rainfall data have been carried out on the hydrological effects. In this study, a conditional merging technique is employed, which makes use of geostatistical methods to extract the optimal information from the observed data. In this context, three different techniques such as kriging, inverse distance weighting and spline interpolation methods are applied to conditionally merge radar and ground rainfall data. The results show that the estimated rainfall not only reproduce the spatial pattern of sub-hourly rainfall with a relatively small error, but also provide reliable temporal estimates of radar rainfall. The proposed modeling framework provides feasibility of using conditionally merged rainfall estimation at high spatio-temporal resolution in ungauged areas.

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