High resolution soil moisture drought monitoring over Luxembourg

With the emergence of accurate high resolution remotely sensed datasets of hydrological variables, opportunities arise to study hydrological processes at an unprecedented scale and resolution. We took this opportunity to study spatiotemporal drought patterns over the country of Luxembourg. A daily 100x100 m² soil moisture dataset based on the VanderSat technology^a will be analysed in conjunction with a 6-day 60x60 m² soil moisture dataset retrieved from Sentinel-1 data (Pulvirenti et al., 2018; van Hateren et al., 2021), and the Copernicus 1x1 km² daily soil moisture product based on the TU Wien algorithm^b. First of all, the consistency between the different products will be tested, as well as their ability to resolve small-scale variability in soil moisture. Then, the soil moisture products are compared to in situ soil moisture data, meteorological data and vegetation indices during major droughts in the last decade (2018, 2022). We will compare small scale spatial and temporal patterns of drought indices with land use, geology and elevation to see how the indices developed during these droughts and how they depend on the local landscape.

^ahttps://data.public.lu/en/datasets/soil-humidity-in-luxembourg-2002-2022/

^bhttps://land.copernicus.eu/global/products/ssm

Pulvirenti, L. et al., ‘A Surface Soil Moisture Mapping Service at National (Italian) Scale Based on Sentinel-1 Data’, Environmental Modelling & Software 102 (April 2018): 13–28, https://doi-org.ezproxy.library.wur.nl/10.1016/j.envsoft.2017.12.022.

van Hateren, T.C. et al., ‘Optimal Spatial Resolution of Sentinel-1 Surface Soil Moisture Evaluated Using Intensive in Situ Observations’, in 2021 IEEE International Geoscience and Remote Sensing Symposium IGARSS, 2021, 6311–14, https://doi-org.ezproxy.library.wur.nl/10.1109/IGARSS47720.2021.9553041.