Details

Autor(en) / Beteiligte

• Kandala, Rajsekhar
• Franssen, Harrie‐Jan Hendricks
• Chaudhuri, Abhijit
• Sekhar, M.

Titel

The value of soil temperature data versus soil moisture data for state, parameter, and flux estimation in unsaturated flow model

Ist Teil von

• Vadose zone journal, 2024-01, Vol.23 (1), p.n/a

Ort / Verlag

Wiley

Erscheinungsjahr

2024

Link zum Volltext

Quelle

Wiley Blackwell Single Titles

Beschreibungen/Notizen

• This synthetic study explores the value of near‐surface soil moisture and soil temperature measurements for the estimation of soil moisture and soil temperature profiles, soil hydraulic and thermal parameters, and latent heat and sensible heat fluxes using data assimilation (ensemble Kalman filter) in combination with unsaturated zone flow modeling (HYDRUS‐1D), for 12 United States Department of Agriculture soil textures in a homogeneous and bare soil scenario. The soil moisture profile is estimated with a root mean square error (RMSE) of 0.04 cm3/cm3 for univariate soil temperature assimilation and 0.01 cm3/cm3 for univariate soil moisture assimilation. Soil temperature assimilation performs better for soils with higher clay content compared to soils with higher sand content. The latent and sensible heat fluxes are estimated with smaller RMSE for univariate soil temperature assimilation compared to univariate soil moisture assimilation for 8 out of 12 soil types. As the climate condition changes from hot semi‐arid to sub‐humid climate, the soil moisture assimilation performs better for high permeable soil but worse for low permeable soil. In summary, the findings suggest that for most soil texture classes, assimilating soil temperature in vadose zone models is skillful to improve latent heat flux, soil moisture profile, and soil hydraulic parameters. Joint assimilation with soil moisture can further enhance the accuracy of the model outputs for all range of soil texture and climate conditions. Core Ideas Soil moisture can be estimated with good accuracy using soil temperature assimilation. Soil temperature data assimilation is superior for estimating soil hydraulic parameters in clayey soils. Heat flux is better estimated by soil temperature assimilation than soil moisture assimilation. Assimilating both soil moisture and soil temperature improved estimation of state, parameter and heat fluxes. Soil moisture assimilation performs better for high (low) permeable soil in humid (arid) climate.