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Remote sensing activities in Southern Ontario in NRCan/ESS Groundwater Geoscience Program

Water resources and their sustainability/vulnerability are determined by climate, physiography conditions of land surface and aquifers, and human activities. Satellite remote sensing can contribute to a better understanding of water resources in various ways. In this talk, three activities
associated with remote sensing in the NRCan/ESS Groundwater Geoscience Program will be discussed. The first activity (1) is water cycle modelling and water budget assessment. This activity involves modelling the various water fluxes and storages in the atmosphere-vegetation-soil-aquifer system. It
relies on the ESS land surface model EALCO and remote sensing products, as well as a number of other datasets for climate, soil and aquifers. Major outputs include evapotranspiration, surface runoff, snow cover, soil water, diffuse recharge and discharge of groundwater, etc. The model provides a
platform to integrate the physical water processes with satellite observations, and to study water sustainability/vulnerability issues associated with climate change and human disturbances. The second activity (2) is soil moisture mapping. This activity aims at downscaling SMOS/SMAP soil moisture
products (40-50km) using Radarsat-2 data to produce soil moisture map at a higher resolution (5-10km). The method includes removing the effect of vegetation using the water-cloud model and the effect of soil surface roughness using multi-temporal Radarsat-2 data. The wavelet transform is combined
with the water-cloud model in soil moisture downscaling. The third activity (3) is characterising water storage variations using Radarsat-2 InSAR data and microgravity measurements. InSAR has been proven to be an efficient technique for measuring surface deformation. This activity investigates the
potential of using an inversion model of surface deformation to characterise water storage variations. Field microgravity and GPS measurements over the Waterloo Moraine were also conducted to investigate the potential for using gravity signal to characterise water storage. Activity (1) aims at
modelling the water cycle through integrating multiple remote sensing products that are available. Activities (2) and (3) are expected to generate new/improved water-related variables from remote sensing, which can be used in Activity (1) to further constrain the water modelling so that our
understanding of the water can be improved.

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