• Title/Summary/Keyword: radar rainfall synthetic technique

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Analysis on the Effect of Spatial Distribution of Rainfall on Soil Erosion and Deposition (강우의 공간분포에 따른 침식 및 퇴적의 변동성 분석)

  • Lee, Gi-Ha;Lee, Kun-Hyuk;Jung, Kwan-Sue;Jang, Chang-Lae
    • Journal of Korea Water Resources Association
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    • v.45 no.7
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    • pp.657-674
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    • 2012
  • This paper presents the effect of spatially-distributed rainfall on both rainfall-sediment-runoff and erosion or deposition in the experimental Cheoncheon catchment: upstream of Yongdam dam basin. The rainfall fields were generated by three rainfall interpolation techniques (Thiessen polygon: TP, Inverse Distance Weighting: IDW, Kriging) based only on ground gauges and two radar rainfall synthetic techniques (Gauge-Radar ratio: GR, Conditional Merging: CM). Each rainfall field was then assessed in terms of spatial feature and quantity and also used for rainfall-sediment-runoff and erosion-deposition simulation due to the spatial difference of rainfall fields. The results showed that all the interpolation methods based on ground gauges provided very similar hydrologic responses in spite of different spatial pattern of erosion and deposition while raw radar and GR rainfall fields led to underestimated and overestimated simulation results, respectively. The CM technique was acceptable to improve the accuracy of raw radar rainfall for hydrologic simulation even though it is more time consuming to generate spatially-distributed rainfall.

Estimation of High-Resolution Soil Moisture Using Sentinel-1A/B SAR and Soil Moisture Data Assimilation Scheme (Sentinel-1A/B SAR와 토양수분자료동화기법을 이용한 고해상도 토양수분 산정)

  • Kim, Sangwoo;Lee, Taehwa;Chun, Beomseok;Jung, Younghun;Jang, Won Seok;Sur, Chanyang;Shin, Yongchul
    • Journal of The Korean Society of Agricultural Engineers
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    • v.62 no.6
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    • pp.11-20
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    • 2020
  • We estimated the spatio-temporally distributed soil moisture using Sentinel-1A/B SAR (Synthetic Aperture Radar) sensor images and soil moisture data assimilation technique in South Korea. Soil moisture data assimilation technique can extract the hydraulic parameters of soils using observed soil moisture and GA (Genetic Algorithm). The SWAP (Soil Water Atmosphere Plant) model associated with a soil moisture assimilation technique simulates the soil moisture using the soil hydraulic parameters and meteorological data as input data. The soil moisture based on Sentinel-1A/B was validated and evaluated using the pearson correlation and RMSE (Root Mean Square Error) analysis between estimated soil moisture and TDR soil moisture. The soil moisture data assimilation technique derived the soil hydraulic parameters using Sentinel-1A/B based soil moisture images, ASOS (Automated Synoptic Observing System) weather data and TRMM (Tropical Rainfall Measuring Mission)/GPM (Global Precipitation Measurement) rainfall data. The derived soil hydrological parameters as the input data to SWAP were used to simulate the daily soil moisture values at the spatial domain from 2001 to 2018 using the TRMM/GPM satellite rainfall data. Overall, the simulated soil moisture estimates matched well with the TDR measurements and Sentinel-1A/B based soil moisture under various land surface conditions (bare soil, crop, forest, and urban).

An analysis of land displacements in terms of hydrologic aspect: satellite-based precipitation and groundwater levels (수문학적 관점에서의 지반 변위 분석: 인공위성 강우데이터와 지하수위 연계)

  • Oh, Seungcheol;Kim, Wanyub;Kang, Minsun;Yoon, Hongsic;Yang, Jungsuk;Choi, Minha
    • Journal of Korea Water Resources Association
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    • v.55 no.12
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    • pp.1031-1039
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    • 2022
  • As one of the hydrological factors closely related to landslides, precipitation indirectly affects slope stability by generating external forces. Groundwater level fluctuations have attracted more attention lately as factors that directly affect slope stability have become more prominent. Therefore, this study attempted to analyze the relationship between variables through changes in precipitation, groundwater levels, and land displacement. A time series-based analysis was conducted using satellite-based precipitation and point-based groundwater levels in conjunction with the PSInSAR technique to simulate land displacement in urban and mountainous areas. There was a sharp rise in groundwater levels in both urban and mountain areas during heavy rainfall, and a continuous decrease in urban areas when rainfall was low. 6 mm of displacements was observed in the mountainous area as a results of soil outflow from the topsoil layer, which was accompanied by an increased groundwater level. Meanwhile, different results were found in urban area. In response to the rise in groundwater level, the land displacement increases due to the expansion of soil skeletons, while the decrease seems to be attributed to anthropogenic influences. Overall, there was no consistent relationship between groundwater levels and land displacement, which appears to be caused by factors other than hydrological factors. Additional consideration of environmental factors could contribute to a deeper understanding of the relationship between the two factors.