Development of Soil Moisture Data Assimilation Scheme for Predicting Effective Soil Characteristics Using Remotely Sensed Data
2018
Lee, T., Kyungpook National University, Daegu, Republic of Korea | Kim, S., Kyungpook National University, Daegu, Republic of Korea | Lee, S.H., Kyungpook National University, Daegu, Republic of Korea | Choi, K.S., Kyungpook National University, Daegu, Republic of Korea | Shin, Y., Kyungpook National University, Daegu, Republic of Korea | Lim, K., Kangwon National University, Chuncheon, Republic of Korea | Park, Y., Kongju National University, Gongju, Republic of Korea
In this study, we developed the Soil Moisture Data Assimilation (SMDA) scheme to extract Effective Soil Characteristics-ESC (Sand, Silt, Clay %) from MODerate resolution Imaging Spectroradiometer (MODIS) products. The SMDA scheme was applied to the MODIS-based Soil Moisture (SM) data during the summer (July to September) period. Then the ESC and soil erosion factors (K) were predicted, respectively. Several numerical experiments were conducted to test the performance of SMDA at the study sites under the synthetic and field validation conditions. In the synthetic experiment, the estimated soil moistures values(R: greater than 0.990 and RMSE: less than 0.005) were identified well with the synthetic observations. The field validation results at the Bangdongri and Chungmicheon sites were also comparable to the TDR-based measurements with the statistics (R: 0.772/0.000 and RMSE: 0.065/0.000). The estimated ESC values were also matched well with the measurements for the synthetic and field validation conditions. Then we tested the SMDA scheme to extract the ESC from the MODIS-based soil moisture products. Although uncertainties exist in the results, the estimated soil moisture and ESC based on the SMDA were comparable to the measurements. Overall, the K factors were similarly distributed based on the derived ESC. Also, the K factors in the mountainous regions were higher than those of the relatively flat areas. Thus, the newly developed SMDA scheme can be useful to estimate spatially and temporally-distributed soil erosion and establish soil erosion management plans.
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