Assessment of soil water conditions using microwave remote sensing data

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Summary Soil water conditions affect directly the processes (infiltration, runoff, evaporation, etc.) governing the water and energy cycles. Several environmental domains such as agriculture, hydrology, meteorology, are closely related to soil water conditions. However, despite its importance, the understanding of the spatial and temporal variability in soil water conditions still remains a challenge. The general objective of the proposed research program is to improve the access to frequent spatial and temporal distributions of soil water conditions for a better understanding of the water cycle. It will be achieved through the following specific objectives: a) Develop and analyze a multifrequency passive and active microwave soil moisture retrieval method; b) Estimate and analyze a multitemporal fine-scale soil moisture content; and c) Characterize the saturated areas over agricultural fields in Quebec. The focus is on the extraction and the analysis of surface soil moisture, soil moisture profiles and the depth of saturated soils with respect to the characteristics of passive/active microwave data (frequency, spatial resolution) and the changes in both soil roughness and vegetation. The research program will benefit from the huge dataset of SMAPVEX16-MB field campaign that took place in Manitoba in the summer 2016 (http://smapvex16-mb.espaceweb.usherbrooke.ca/). It is composed of ground measurements of soil (moisture, temperature and roughness) and vegetation (types, height, water content, etc.) characteristics which were collected quasi-simultaneously with spaceborne passive and active microwave data (SMOS, SMAP, RADARSAT-2, Sentinel-1, TerraSAR-X, and ALOS-PALSAR), airborne measurements of PALS (Passive/Active L-band Sensor), and ground microwave radiometer measurements. The proposed methodology includes: inversion of passive and active microwave models, adaptation of an existing soil moisture disaggregation method, synergistic studies for soil moisture estimation at different scales, and the combination of radar model/soil model/assimilation model for the characterisation of saturated agricultural fields at both the soil surfaces and along a certain depth. Results will be validated using ground measurements. They will be very useful for the early detection of droughts, floods, and fires and for the development of warning systems. In addition, with the use of Sentinel-1 high temporal frequency synthetic aperture radar data, the proposed research program presents interesting examples of using the future RADARSAT Constellation Mission (launch date scheduled for July 2018) data for operational applications.