Simulating high resolution soil moisture distribution using TOPMODEL-based Land Surface-Atmosphere Transfer Scheme (TOPLATS) model

Wednesday, 17 December 2014
Xiaolei Fu1,2, Lifeng Luo2, Ming Pan3, Zhongbo Yu4, Huiqing Huang2, Yang Lang5 and Ying Tang2, (1)Hohai University, State Key Laboratory of Hydrology-Water Resources and Hydraulic Engineering, College of Hydrology and Water Resources, Nanjing, China, (2)Michigan State University, East Lansing, MI, United States, (3)Princeton University, Princeton, NJ, United States, (4)Univ Nevada, Las Vegas, NV, United States, (5)Beijing Normal University, Beijing, China
Better quantification of the spatial and temporal distribution of soil moisture across different spatial scales can greatly help us understanding the Earth as an integrated system. To obtain high resolution root zone soil moisture (RZSM), we applied the TOPMODEL-based Land Surface-Atmosphere Transfer Scheme (TOPLATS) over the Oklahoma region driven by coarse scale (0.125 degree) meteorological forcing from NLDAS. The simulated RZSM is then evaluated against in-situ observations from 16 stations in the study domain, and the model performance is assessed using the average relative error (RE) and the root mean square error (RMSE). The simulated spatial distribution of soil moisture is largely consistent with the distribution of topographic index (TI) in most part of Oklahoma as topography has traditionally been considered the dominant factor in horizontal redistribution of soil moisture. Evaluation over individual stations show that RE is generally smaller than 10% and RMSE is mostly smaller than 0.05 m3/m3. At daily, monthly and seasonal time scales, the simulation was able to capture the observed variation of RZSM at most stations. In addition to topographic index and precipitation distribution, our analysis also suggested that surface temperature plays an important role in determining soil moisture distribution through regulating the evapotranspiration. The overall evaluation confirms that the TOPLATS model can be a useful downscaling tool for obtaining high resolution soil moisture.