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http://dx.doi.org/10.14770/jgsk.2018.54.5.545

Estimation of deep percolation using field moisture observations and HYDRUS-1D modeling in Haean basin  

Kim, Jeong Jik (Department of Geology, Kangwon National University)
Jeon, Woo-Hyun (Department of Geology, Kangwon National University)
Lee, Jin-Yong (Department of Geology, Kangwon National University)
Publication Information
Journal of the Geological Society of Korea / v.54, no.5, 2018 , pp. 545-556 More about this Journal
Abstract
This study was conducted to estimate the deep percolation using numerical modeling and field observation data based on rainfall in Haean basin. Soil moisture sensors were installed to monitoring at 30, 60 and 90 cm depths in four sites (YHS1-4) and automatic weather station was installed to around YHS3. Soil moisture and meteorological data was observed from March 25, 2017 to March 25, 2018 and May 06, 2016 to May 06, 2018, respectively. Numerical analysis was performed from June to August, 2017 using the HYDRUS-1D. Average soil moisture contents were high to generally in YHS3 for 0.300 to $0.334m^3/m^3$ and lowest in YHS1 for 0.129 to $0.265m^3/m^3$ during the soil moisture monitoring period. The results of soil moisture flow modeling showed that field observations and modeling values were similar but the peak values were larger in the modeling result. Correlation analysis between observation and modeling data showed that r, $r^2$ and RMSE were 0.88, 0.77, and 0.0096, respectively. This show high correlation and low error rate. The total deep percolation was 744.2 mm during the period of modelling at 500 cm depth. This showed that 61.3% of the precipitation amount (1,214 mm) was recharged in 2017. Deep percolation amount was high in the study area. This study is expected to provide basic data for the estimation of groundwater recharge through unsaturated zone.
Keywords
soil moisture; weather observation; deep percolation; HYDRUS-1D; correlation analysis;
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