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Determining soil moisture and soil properties in vegetated areas by assimilating soil temperatures
Author(s) -
Dong Jianzhi,
SteeleDunne Susan C.,
Ochsner Tyson E.,
van de Giesen Nick
Publication year - 2016
Publication title -
water resources research
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.863
H-Index - 217
eISSN - 1944-7973
pISSN - 0043-1397
DOI - 10.1002/2015wr018425
Subject(s) - environmental science , water content , soil science , soil thermal properties , data assimilation , energy balance , pedotransfer function , moisture , soil water , water balance , hydrology (agriculture) , infiltration (hvac) , remote sensing , geotechnical engineering , meteorology , hydraulic conductivity , geology , ecology , physics , biology
This study addresses two critical barriers to the use of Passive Distributed Temperature Sensing (DTS) for large‐scale, high‐resolution monitoring of soil moisture. In recent research, a particle batch smoother (PBS) was developed to assimilate sequences of temperature data at two depths into Hydrus‐1D to estimate soil moisture as well as soil thermal and hydraulic properties. However, this approach was limited to bare soil and assumed that the cable depths were perfectly known. In order for Passive DTS to be more broadly applicable as a soil hydrology research and remote sensing soil moisture product validation tool, it must be applicable in vegetated areas. To address this first limitation, the forward model (Hydrus‐1D) was improved through the inclusion of a canopy energy balance scheme. Synthetic tests were used to demonstrate that without the canopy energy balance scheme, the PBS estimated soil moisture could be even worse than the open loop case (no assimilation). When the improved Hydrus‐1D model was used as the forward model in the PBS, vegetation impacts on the soil heat and water transfer were well accounted for. This led to accurate and robust estimates of soil moisture and soil properties. The second limitation is that, cable depths can be highly uncertain in DTS installations. As Passive DTS uses the downward propagation of heat to extract moisture‐related variations in thermal properties, accurate estimates of cable depths are essential. Here synthetic tests were used to demonstrate that observation depths can be jointly estimated with other model states and parameters. The state and parameter results were only slightly poorer than those obtained when the cable depths were perfectly known. Finally, in situ temperature data from four soil profiles with different, but known, soil textures were used to test the proposed approach. Results show good agreement between the observed and estimated soil moisture, hydraulic properties, thermal properties, and observation depths at all locations. The proposed method resulted in soil moisture estimates in the top 10 cm with RMSE values typically <0.04m 3/ m 3. This demonstrates the potential of detecting the spatial variability of soil moisture and properties in vegetated areas from Passive DTS data.