Funding Agency:
NASA

Soil moisture in the partially saturated zone is a critical state variable in hydrology. It serves to partition the energy and water budget on the land surface. The signature and amount of soil moisture in the near-surface and the root zone influences key hydrological processes like overland runoff, infiltration, and percolation, plant-available moisture content, and evapotranspiration. It also has a direct implication in the storage and transfer of pollutants to the deeper groundwater zone. Due to the spatio-temporal dynamic nature of this soil moisture, it requires continuous monitoring which has been made possible through various remote sensing satellites like NASA’s AMSR-E, ESA’s SMOS and the upcoming SMAP mission by NASA.
However, the soil moisture thus estimated has a very coarse spatial resolution which might not be useful in a modeling scenario. In order to use the extensively monitored soil moisture products it is required to scale them to useful scales. However, past studies have established that a single scaling scheme is not applicable for all scenarios since the inherent heterogeneity in land surface and its consequent effect on soil moisture spatial distribution is not unique for all study domains. A variety of scaling schemes based on statistics is available in the literature which is mostly domain-specific. Besides statistics, some scaling schemes employ various land surface models that utilize soil moisture movement parameterizations developed for the Darcy scale.
In the proposed study, a novel standardized heterogeneity triangle will be developed. This triangle will link the correlation structure of soil moisture spatial distribution to a normalized spatial index, a normalized wetness index and a normalized heterogeneity index at scales coarser than Darcy scales at which remote sensing data is collected. This unique heterogeneity index will encompass the hierarchy of dominance that the physical controls exert over soil moisture. The most dominant physical control will be decided by minimizing the Shannon entropy of the soil moisture based on different controls.
This study is unique and futuristic in terms of its methodology. It will help solve pertinent issues in hydrology which include resolution of the energy and water balance at finer scales and fine-scale estimation of root zone soil moisture. This will enable better climate and weather forecasts and enhance precise agriculture. Since water is a major concern for the world today, this research can contribute towards managing our water resources better.

• Gaur, N. and Mohanty, B.P., 2019. A Nomograph to Incorporate Geophysical Heterogeneity in Soil Moisture Downscaling. Water Resources Research, 55(1), pp.34-54.
• Gaur, N. and Mohanty, B.P., 2016. Land‐surface controls on near‐surface soil moisture dynamics: Traversing remote sensing footprints. Water Resources Research, 52(8), pp.6365-6385.
• Gaur, N. and Mohanty, B.P., 2013. Evolution of physical controls for soil moisture in humid and subhumid watersheds. Water Resources Research, 49(3), pp.1244-1258.