Abstract
Information on the soil moisture content in the soil is important for planning both for farmers and
agricultural water managers. The availability of this information is however limited owing to the expensive
nature of in-situ soil moisture measurements and cloud conditions that limits satellite derivation of soil
moisture and the availability of satellite derived soil moisture at coarse resolutions limiting their application
at local scale. This study applies existing downscaling technique which makes use of vegetation indices and
land surface temperature. The study compounds the technique with Harmonic Analysis of Time Series
(HANTS) to provide continuous high-resolution soil moisture. The case study area is the state of Nebraska
and the low-resolution soil moisture used is advanced Scatterometer (ASCAT). The use of HANTS
successfully produced daily soil moisture estimates without degrading the accuracy of the soil moisture at
0.09m3/m3. The Precision however, was observed to be slightly degraded owing to seasonal variations and
the different rooting depths within which the vegetation draws soil moisture from. Whereas the study has
been conducted in Nebraska, the same can be replicated in regions with limited soil moisture measurements.
The information is paramount for crop production forecasting, drought assessment and crop water
management since it provides near real time information. This study shows that soil moisture downscaling
can improve the resolution without degrading the accuracy. This accuracy was found to be within the
threshold required for global climate observation systems (GCOS) which is set at 20% of the saturated
water content.
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