Estimation of field-scale soil moisture content and its uncertainties using Sentinel-1 satellite imagery

H.F. Benninga

Research output: ThesisPhD Thesis - Research UT, graduation UT

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Abstract

The soil moisture content (SMC) expresses the amount of water in the unsaturated zone. The variable is essential for vegetation growth and hydrological processes. SMC can be retrieved from satellite microwave observations. The uncertainties in field-scale SMC retrievals were studied and decomposed in uncertainties originating from in situ references (Usp and Us,S1), satellite observations (US1) and model parameters (Up).
Two regional networks were employed for the in situ monitoring of SMC, namely the Twente network in the east (Chapter 2) and the Raam network in the south (Chapter 3) of the Netherlands. From soil-specific calibrations follow station probe measurement uncertainties (Usp) of 0.018 m3 m-3 to 0.028 m3 m-3. In Chapter 4, using measurements inside four agricultural fields, the spatial mismatch uncertainty between SMC retrievals from satellites and station measurements (Us,S1) is estimated at 0.051 m3 m-3. Chapter 5 focuses on the microwave backscatter observations provided by the Sentinel-1 satellites. The retrieval uncertainty due to their radiometric uncertainty (US1) is low (-0.01 m3 m-3 to +0.01 m3 m-3) for dry soils and large surface areas and high (-0.10 m3 m-3 to +0.17 m3 m-3) for wet soils and small surface areas. The uncertainties involved in surface scattering simulations and SMC retrievals were investigated in Chapter 6. The main uncertainty originates from the in situ references (Usp and Us,S1) and the Sentinel-1 observations (US1), whereas the contribution from the surface roughness parameters (Up) is small. For two meadows the surface roughness parameter distributions are similar, time-invariant and independent of Sentinel-1's ascending/descending orbits. Hence, SMC retrieval over meadows was implemented as an operationally applicable scheme in Chapter 7. The performances without and with a vegetation correction were found to be similar.
The quantification of uncertainty contributions helps to comprehend SMC retrieval accuracy. Future research could focus on the uncertainty sources with the largest contributions to effectively improve the SMC retrievals, assessing the general applicability and improvement of the SMC retrieval scheme, functionally evaluating the SMC retrievals in potential applications, and representing field-scale SMC as an ensemble of SMC products.
Original languageEnglish
QualificationDoctor of Philosophy
Awarding Institution
  • Faculty of Geo-Information Science and Earth Observation
  • University of Twente
Supervisors/Advisors
  • Su, Bob, Supervisor
  • van der Velde, Rogier, Co-Supervisor
Award date24 Mar 2022
Place of PublicationEnschede
Publisher
Print ISBNs978-90-365-5338–4
DOIs
Publication statusPublished - 24 Mar 2022

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