On the Potential of Sentinel-1 for High Resolution Monitoring of Water Table Dynamics in Grasslands on Organic Soils

Abstract

For soils with shallow groundwater and high organic carbon content, water table depth (WTD) is a key parameter to describe their hydrologic state and to estimate greenhouse gas emissions (GHG). Since the microwave backscatter coefficient (σ0) is sensitive to soil moisture, the application of Sentinel-1 satellite data might support the monitoring of these climate-relevant soils at high spatial resolution (~100 m) by detecting spatial and temporal changes in local field and water management. Despite the low penetration depth of the C-band, σ0 is influenced by shallow WTD fluctuations via the soil hydraulic connection between the water table and surface soil. Here, we analyzed σ0 at 60 monitoring wells in a drained temperate peatland with degraded organic soils used as extensive grassland. We evaluated temporal Spearman correlation coefficients between σ0 and WTD considering the soil and vegetation information. To account for the effects of seasonal vegetation changes, we used the cross-over (incidence) angle method. Climatologies of the slope of the incidence angle dependency derived from two years of Sentinel-1 data and their application to the cross-over angle method did improve correlations, though the effect was minor. Overall, averaged over all sites, a temporal Spearman correlation coefficient of 0.45 (±0.17) was obtained. The loss of correlation during summer (higher vegetation, deeper WTD) and the effects of cuts and grazing are discussed. The site-specific general wetness level, described by the mean WTD of each site was shown to be a major factor controlling the strength of the correlation. Mean WTD deeper than about −0.60 m lowered the correlations across sites, which might indicate an important limit of the application.

A Multiscale Productivity Assessment of High Andean Peatlands across the Chilean Altiplano Using 31 Years of Landsat Imagery

“…As a result, we believe that the combination of 30 m Landsat data and 10 m Sentinel 2 data are the most promising remote sensing sources for studying long-term high Andean peatland productivity (30+ years) at high spatiotemporal resolutions moving forward. These decadal studies can be further complemented with detailed assessments of peatland biomass [46,47], functional traits and plant composition [48,49], soil moisture [50,51] and water table measurements [52][53][54][55] using active radar or LiDAR systems, hyperspectral sensors, optical sensors on unmanned vehicles or multi-sensor approaches recently developed for other regions around the world.…”

Statistical Exploration of SENTINEL-1 Data, Terrain Parameters, and in-situ Data for Estimating the Near-Surface Soil Moisture in a Mediterranean Agroecosystem

“…ML approaches are increasingly used to estimate θ in agricultural watersheds across humid to arid climate regimes and at different scales (e.g., Quesney et al, 2000;Hachani et al, 2019). They are reported to improve hydrological modeling in wetlands (Dabrowska-Zielinska et al, 2018) and to support the monitoring of water tables dynamics (Asmuß et al, 2019), and the estimation of crop water stress (El-Shirbeny and Abutaleb, 2017), and the water use efficiency (Efremova et al, 2019).…”

A Comparison of Three Trapezoid Models Using Optical and Thermal Satellite Imagery for Water Table Depth Monitoring in Estonian Bogs

“…The longer wavelength (L band) of the passive microwave satellite missions that are currently dedicated to soil moisture monitoring are less sensitive to vegetation than the operational active microwave missions. However, the passive observations have a coarse resolution (~40 km) [25,26], whereas some active missions allow high spatial resolution mapping (<100 m) [29,30]. A few studies have analyzed and used passive [31][32][33] and active [34,35] microwave measurements for the purpose of soil moisture monitoring in peatlands.…”