Abstract
Summary The highly dynamic nature of preferential flow in time and space makes it challenging to identify and analyze its occurrence at the catchment scale. Novel analysis methods using soil moisture sensor response times offer an opportunity to investigate catchment-wide controls on preferential flow. The aim of this study was to identify factors that control preferential flow occurrence based on 3-year soil moisture monitoring using a wireless sensor network in the Wustebach catchment, Germany. At 101 locations, the sensor response times at three depths (5, 20, and 50 cm) were classified into one of four classes: (1) non-sequential preferential flow, (2) velocity-based preferential flow, (3) sequential flow, and (4) no response. A conceptual model, postulating that preferential flow in the Wustebach catchment is dominated by differences in soil type, landscape position, and rainfall input, was proposed for hypothesis testing. To test the conceptual model, the classification results were combined with spatial and event-based data to understand and identify controlling factors. Spatial parameters consisted of hydrological, topographical, and soil physical and chemical parameters. Temporal factors included precipitation characteristics and antecedent soil moisture conditions. The conceptual model as proposed could only be partly confirmed. Event-based occurrence of preferential flow was highly affected by precipitation amount, with a nearly catchment-wide preferential response during large storm events. During intermediate events, preferential flow was controlled by small-scale heterogeneity, instead of showing catchment-wide patterns. The effect of antecedent catchment wetness on the occurrence of preferential flow was generally less profound, although a clear negative relationship was found for precipitation events with more than 25 mm. It was found that spatial occurrence of preferential flow was however governed by small-scale soil and biological features and local processes, and showed no obvious relationship with any of the selected spatial parameters. Overall, the results demonstrate that sensor response time analysis can offer innovative insights into the spatial–temporal interrelationship of preferential flow occurrence.
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