Multi Temporal Evaluation of Soil Moisture and Land Surface Temperature Dynamics Using in Situ and Satellite Observations
Soil moisture (SM) is an important component of the Earth's surface water balance and by extension the energy balance, regulating the land surface temperature (LST) and evapotranspiration (ET) Nowadays, there are two missions dedicated to monitoring the Earth's surface SM using L band radiometers: ESA's Soil Moisture and Ocean Salinity (SMOS) and NASA's Soil Moisture Active Passive (SMAP) LST is remotely sensed using thermal infrared (TIR) sensors on board satellites, such as NASA's Terra/Aqua MODIS or ESA EUMETSAT's MSG SEVIRI. This study provides an assessment of SM and LST dynamics at daily and seasonal scales, using 4 years (2011 2014) of in situ and satellite observations over the central part of the river Duero basin in Spain. Specifically, the agreement of instantaneous SM with a variety of LST derived parameters is analyzed to better understand the fundamental link of the SM LST relationship through ET and thermal inertia. Ground based SM and LST measurements from the REMEDHUS network are compared to SMOS SM and MODIS LST spaceborne observations. ET is obtained from the HidroMORE regional hydrological model. At the daily scale, a strong anticorrelation is observed between in situ SM and maximum LST (R 0.6 to 0.8) and between SMOS SM and MODIS LST Terra/Aqua day (R 0.7) At the seasonal scale, results show a stronger anticorrelation in autumn, spring and summer (in situ R 0.5 to 0.7; satellite R 0.4 to 0.7) indicating SM LST coupling, than in winter (in situ R +0.3; satellite R 0.3) indicating SM LST decoupling. These different behaviors evidence changes from water limited to energy limited moisture flux across seasons, which are confirmed by the observed ET evolution. In water limited periods, SM is extracted from the soil through ET until critical SM is reached. A method to estimate the soil critical SM is proposed. For REMEDHUS, the critical SM is estimated to be ~0.12 m 3 /m 3 stable over the study period and consistent between in situ and satellite observations. A better understanding of the SM LST link could not only help improving the representation of LST in current hydrological and climate prediction models, but also refining SM retrieval or microwave optical disaggregation algorithms, related to ET and vegetation status.
Remote. Sens.