Assessing the collection of soil moisture estimates in the scope of AgriSens Demmin 4.0: Comparison of in-situ measurements and AMBAV model results

The project AgriSens Demmin 4.0 aims to explore applications of remote sensing products for the agricultural sector. The developed methods and acquired knowledge will be made available for farmers and the public. Experiments and case studies are carried out in the project area, which is located about 180 kilometres north of Berlin and covers approximately 800 square kilometres with a large part of arable farming land. For this area, a rich collection of different data sources exists: Besides remote sensing data (from satellites, aircrafts and UAV systems), meteorological and soil data is collected by a dense network of environmental measuring stations. Additionally, comprehensive field measurement campaigns are conducted.

In the project, the agrometeorological department of the German National Meteorological Service prepares and processes the meteorological data and provides agrometeorological simulations to the project partners. The basis for these simulations is the SVAT model AMBAV (AgrarMeteorologische Berechnung der Aktuellen Verdunstung), which computes estimates for soil moisture and evapotranspiration based on the atmospheric conditions, soil types and current vegetation.

The above-mentioned richness of data for the project area enables the comparison of soil moisture estimates of different sources, each having specific scales, strengths, and weaknesses: Soil cores for gravimetric soil moisture samples have a high degree of accuracy, but only have limited spatial and temporal validity because of their sparsity. Installed soil sensors offer time-continuous measurements, but are prone to calibration errors and offsets. Satellite-derived products promise extensive monitoring of areas of interest, but provide only indirect and area-integrated measurements of surface soil water, which have limited informative value for deeper soil layers. Soil moisture modelling can be used to bridge the gap in scales since it is more flexible and may provide soil moisture estimation in arbitrary resolution if the relevant input data is available.

In our study, we compare in-situ soil moisture measurements and AMBAV model estimates for the AgriSens Demmin 4.0 area in order to evaluate the model but also asses the comparability of the different data sources. Preliminary results show that intercomparisons of soil core samples and AMBAV model results are satisfactory when there is good knowledge about the soil texture, whereas the agreement with automatic soil sensors remains problematic, most likely due to installation and calibration aspects.

High-quality in-situ data is generally important for the adjustment and verification of remote sensing products, and this includes the area of soil-vegetation-atmosphere transfer of water. Model validation and development is viewed as critical in order to provide an efficient linkage between the two domains.