The Smart Coverage (SC) module explores the applicability of CRNS across scales. At the field scale (up to 1 km²), we aim to resolve soil moisture variability by using dense CRNS networks (downscaling). For that purpose, we build on the work of the research module Massive Coverage (MC) from phase I and capitalize on the unique data sets obtained from our Joint Field Campaigns in Fendt and Wüstebach, from our permanent cluster at the ATB Field Lab in Marquardt, and from the Virtual Joint Field Campaign planned for phase II.
In phase II, SC will also step forward to investigate the potential of CRNS networks at the meso-scale (up to 100 km², upscaling). How can we represent the variability of soil moisture at a scale where an exhaustive CRNS coverage is no longer feasible? To that end, we will use machine learning algorithms to identify "smart" combinations of stationary CRNS observations with proxy variables that allow for meso-scale coverage, such as remote sensing products, hydrological model data, and landscape metrics. In a Meso-Scale Joint Field Campaign in the Selke catchment, we will put these concepts to the test.