Abstract

Abstract. This study presents an application of an innovative sampling strategy to assess soil moisture dynamics in a headwater of the Weißeritz in the German eastern Ore Mountains. A grassland site and a forested site were instrumented with two Spatial TDR clusters (STDR) that consist of 39 and 32 coated TDR probes of 60 cm length. Distributed time series of vertically averaged soil moisture data from both sites/ensembles were analyzed by statistical and geostatistical methods. Spatial variability and the spatial mean at the forested site were larger than at the grassland site. Furthermore, clustering of TDR probes in combination with long-term monitoring allowed identification of average spatial covariance structures at the small field scale for different wetness states. The correlation length of soil water content as well as the sill to nugget ratio at the grassland site increased with increasing average wetness and but, in contrast, were constant at the forested site. As soil properties at both the forested and grassland sites are extremely variable, this suggests that the correlation structure at the forested site is dominated by the pattern of throughfall and interception. We also found a very strong correlation between antecedent soil moisture at the forested site and runoff coefficients of rainfall-runoff events observed at gauge Rehefeld. Antecedent soil moisture at the forest site explains 92% of the variability in the runoff coefficients. By combining these results with a recession analysis we derived a first conceptual model of the dominant runoff mechanisms operating in this catchment. Finally, we employed a physically based hydrological model to shed light on the controls of soil- and plant morphological parameters on soil average soil moisture at the forested site and the grassland site, respectively. A homogeneous soil setup allowed, after fine tuning of plant morphological parameters, most of the time unbiased predictions of the observed average soil conditions observed at both field sites. We conclude that the proposed sampling strategy of clustering TDR probes is suitable to assess unbiased average soil moisture dynamics in critical functional units, in this case the forested site, which is a much better predictor for event scale runoff formation than pre-event discharge. Long term monitoring of such critical landscape elements could maybe yield valuable information for flood warning in headwaters. We thus think that STDR provides a good intersect of the advantages of permanent sampling and spatially highly resolved soil moisture sampling using mobile rods.

Highlights

  • Soil moisture is a key state variable that controls hydrological dynamics at various spatial scales

  • This study presents an application of the outlined Spatial TDR clusters (STDR) technology (the underlying theory is well explained in Graeff et al (2010), in a headwater of the Weißeritz in the German eastern Ore Mountains, where two TDR clusters have been installed since summer 2007

  • The most downslope TDR probe at C2 is influenced by shallow groundwater and is very wet during the entire period

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Summary

Introduction

Soil moisture is a key state variable that controls hydrological dynamics at various spatial scales. Experimental studies that relate observations of spatio-temporal soil moisture dynamics at the field or headwater scale to observed flows, either at the surface or in the stream, are rare (Burt and Butcher, 1985, Grayson et al, 1997; Starr and Timlin, 2004; McNamara et al, 2005; Lin, 2006; Frisbee et al, 2007). Notwithstanding that they could offer additional – probably unexpected – pieces of information to the puzzle that up to now has largely comprised model extrapolations. Soil moisture at the headwater scale exhibits huge spatial variability and single or even distributed TDR measurements yield nonrepresentative data

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