부산대학교 도서관

Accurate soil moisture (SM) data are key for climate and surface-atmosphere simulations associated with prediction and analysis of weather and climate variability. Here, we assessed in situ vs. remotely sensed SM discrepancies in a humid watershed during an extreme drought and an arid watershed under peak dry-season conditions. Using in situ SM measurements from the Soil and Climate Analysis Network (SCAN) we compared timeseries data with two remotely sensed data sources: The National Aeronautics and Space Administration's Soil Moisture Active Passive (SMAP) and the European Space Agency's Soil Moisture Ocean Salinity (SMOS) radiometers. Over a nearly three-year period (31 March, 2015 to 31 December, 2017), SMAP timeseries had a higher correlation with SCAN data (R2 = 0.24 to 0.75) compared to SMOS estimates (R2 = 0.04 to 0.68) with lower average RMSE (0.03 vs. 0.19 cm3 cm-3). Possible sources of error were identified related to underlying assumptions in the SM retrieval algorithm, principally that soil and vegetation canopy temperatures are in equilibrium during satellite retrievals and that vegetation scattering and attenuation may be accurately represented when using static, long-term averages of NDVI. We concluded that although SMAP SM retrievals reflect dry periods observed in in situ SM timeseries, the magnitude of extreme conditions were underestimated. [ABSTRACT FROM AUTHOR]