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Data from: Development and calibration of a novel sensor to quantify the water content of surface soils and biological soil crusts

Citation

Weber, Bettina et al. (2016), Data from: Development and calibration of a novel sensor to quantify the water content of surface soils and biological soil crusts, Dryad, Dataset, https://doi.org/10.5061/dryad.605j6

Abstract

The surface layer of soil as transition zone between pedosphere and atmosphere plays a crucial role in exchange processes of nutrients, atmospheric gases and water. Knowledge of its water content is essential, as it governs both physiological and transport mechanisms. In arid and semi-arid regions, this uppermost soil layer is commonly colonized by biological soil crusts (biocrusts), which play major roles in the global terrestrial carbon and nitrogen cycles. The water status of biocrusts is essential as it controls the activity, productivity and surface exchange of these poikilohydric communities. On-site analyses of the water content of both bare and crusted soils are thus urgently needed to correctly model the exchange processes of water, nutrients and trace gases at the soil surface. In this study, we present the biocrust wetness probe (BWP), which is the first to reliably measure the water content within biocrusts or the uppermost 5 mm of a substrate. Using a weak alternating current, the electrical conductivity is assessed over time. With an automatic calibration routine, conductivity values are temperature- corrected and converted into water contents and precipitation equivalents. During 1 year of continuous field measurements at 5-min intervals, 60 BWPs worked reliably without any failure. The probes responded immediately and individually upon rain events, showing substrate-specific water response curves, which are well represented by linear and exponential calibration curves. The BWP facilitates the spatio-temporal assessment and interpolation of surface soil wetness and thus bio- crust activity, which governs nutrient fluxes, trace gas release and biogeochemical cycles. Its implementation in distributed sensor networks is under development.

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