Estimation of Catchment‐Scale Soil Moisture Patterns Based on Terrain Data and Sparse TDR Measurements Using a Fuzzy C‐Means Clustering Approach

Abstract

Accurate characterization of spatial soil moisture patterns and their temporal dynamics is important to infer hydrological fluxes and flow pathways and to improve the description and prediction of hydrological models. Recent advances in ground‐based and remote sensing technologies provide new opportunities for temporal information on soil moisture patterns. However, spatial monitoring of soil moisture at the small catchment scale (0.1–1 km2) remains challenging and traditional in situ soil moisture measurements are still indispensable. This paper presents a strategic soil moisture sampling framework for a low‐mountain catchment. The objectives were to: (i) find a priori a representative number of measurement locations, (ii) estimate the soil moisture pattern on the measurement date, and (iii) assess the relative importance of topography for explaining soil moisture pattern dynamics. The fuzzy c‐means sampling and estimation approach (FCM SEA) was used to identify representative measurement locations for in situ soil moisture measurements. The sampling was based on terrain attributes derived from a digital elevation model (DEM). Five time‐domain reflectometry (TDR) measurement campaigns were conducted from April to October 2013. The TDR measurements were used to calibrate the FCM SEA to estimate the soil moisture pattern. For wet conditions the FCM SEA performed better than under intermediate conditions and was able to reproduce a substantial part of the soil moisture pattern. A temporal stability analysis shows a transition between states characterized by a reorganization of the soil moisture pattern. This indicates that, at the investigated site, under wet conditions, topography is a major control that drives water redistribution, whereas for the intermediate state, other factors become increasingly important.

Cosmic‐ray Neutron Rover Surveys of Field Soil Moisture and the Influence of Roads

“…The field campaigns highlight characteristic hydrological features, e.g., the mentioned contact springs near the creek, that are especially prominent during dry periods and were identified also by other researchers using conventional measurement techniques (Graeff et al, ; Schröter et al, ). The experiment shows that the rover can efficiently contribute to hydrological process understanding, while the assumption of spatially constant parameters is considered acceptable for the relatively homogeneous Schäfertal site.…”

“…Porosity and organic content are higher in the riparian zone. For more information about the local hydrology, see Martini et al (2015) and Schröter et al (2015).…”

“…Within the Schäfertal, Schröter et al (2015Schröter et al ( , 2017 performed regular TDR campaigns by foot using 94 locations in the whole catchment area. During several campaigns from 2014 to 2016, the CRNS rover accompanied their team.…”

Repeated electromagnetic induction measurements for mapping soil moisture at the field scale: validation with data from a wireless soil moisture monitoring network

“…Interflow is known to play a relevant role within the runoff processes (Borchardt, 1982), and part of it can result in return flow. The slopes of the catchment are intensively used for agriculture, whilst meadow occupies the valley bottom (Schröter et al, 2015).…”

A Multi‐Scale Soil Moisture Monitoring Strategy for California: Design and Validation

“…Soil moisture patterns have been described using cluster analysis at the watershed (Lin et al 2006;Schroter et al 2015) and hillslope-scale (Lee and Kim 2017;Liao et al 2017). Hydrologic-based soil classifications have been developed using conceptual models of soil response (Boorman et al 1995).…”