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\begin{document}

\title{Monitoring Relative Surface Soil Moisture Changes Across the Thames
Basin using Sentinel-1}



\author[1]{William Maslanka}%
\author[2]{Kevin White}%
\author[2]{Anne Verhoef}%
\author[2]{Joanna Clark}%
\author[2]{Keith Morrison}%
\affil[1]{University of Reading,University of Reading,Environment Agency}%
\affil[2]{University of Reading}%


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  \date{May 22, 2024}


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\begin{abstract}
Soil moisture is a critical component in many meteorological,
hydrological, and agricultural applications, and understanding its
spatial and temporal dynamics is vital for the understanding of these
processes. Satellite-based remote sensing offers the ability to
synoptically capture this spatiotemporal information over large areas,
compared to more site-based in-situ field measurements. In this study,
we use Sentinel-1 SAR imagery of the River Thames catchment, United
Kingdom, over the period 2015 - 2020. A backscatter normalisation
process is applied to account for the use of multiple satellite viewing
geometries. A change-detection algorithm utilising backscatter power is
then applied to the timeseries, to estimate relative surface soil
moisture (rSSM) across the study area. To determine information across
the large river watershed, smaller sub-catchments, and intra-field
scales, the rSSM time series is replicated at multiple spatial scales (1
km, 500m, 250m, and 100m). Although positive biases are present during
the growing season of arable farmland, comparison with rainfall data and
in-situ soil moisture probes shows there is good agreement with the
temporal cycle of soil moisture. These data are being used to evaluate
natural flood management by land use and management across a wide area
to better understand relationships between surface wetness and water
storage in relation to land cover and underlying geology for the
Landwise project (Landwise-NFM.org).%
\end{abstract}%



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