EGU General Assembly 2020
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.

Dynamic groundwater recharge rates at field scale: how to successfully use soil moisture from cosmic-ray neutron sensing

Lena M. Scheiffele1, Matthias Munz1, Gabriele Baroni2, Sonja Bauer1, and Sascha E. Oswald1
Lena M. Scheiffele et al.
  • 1Institute of Environmental Science and Geography, University of Potsdam, Germany (
  • 2Department of Agricultural and Food Sciences, University of Bologna, Italy

Cosmic-ray neutron sensing (CRNS) is a non-invasive method that provides an average soil moisture for a large support volume (radial footprint up to 240 m, depth up to 80 cm) with high temporal resolution. It covers the most dynamic part of the vadose zone at a scale that is already a more substantial part of the landscape then local point measurements. This integral soil moisture value overcomes the limitations regarding issues of small-scale heterogeneity. Therefore, the use of CRNS soil moisture could improve the estimation of potential groundwater (GW) recharge at the field.

Besides the stochastic integration of point-scale soil moisture profiles, CRNS soil moisture estimates could be used for the inverse estimation of effective soil hydraulic properties by applying unsaturated soil hydrological models and to determine environmental fluxes such as GW recharge.

Within this study CRNS soil moisture is used to estimate the effective soil hydraulic properties within the model HYDRUS 1D. Resulting GW recharge represents the field scale because of the integrated nature of the soil moisture product, even though the model is calculating percolation fluxes for 1D - profiles. These integrated GW recharge fluxes are compared to established point scale methods of GW estimation using soil moisture from a distributed sensor network to inversely estimate the effective soil hydraulic properties within HYDRUS 1D.

CRNS is, however, sensitive to the vertical distribution of water content and this behavior should be explicitly considered. Two approaches are assessed further to account for that. On the one hand, a correction of CRNS, based on measured soil moisture profiles, is tested and CRNS soil moisture is directly used for recharge calculation in HYDRUS. On the other hand, the COSMIC-Operator, as implemented within HYDRUS, is used for calibrating the model by directly comparing neutron count rates from simulated soil moisture. Both approaches are assessed with respect to their ability to estimate natural groundwater recharge rates.

How to cite: Scheiffele, L. M., Munz, M., Baroni, G., Bauer, S., and Oswald, S. E.: Dynamic groundwater recharge rates at field scale: how to successfully use soil moisture from cosmic-ray neutron sensing, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-18563,, 2020


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  • CC1: Comment on EGU2020-18563, Katya Dimitrova Petrova, 04 May 2020

    Thanks for sharing this exciting research!

    I am curious about the massive monitoring network with soilnet and 20 CRNS sensors to measure gw recharge. What do you mean with massive? (sorry I could not see the scale on your location map)

    When looking at the different CRNS probe locations, I see that the soilnet network is mainly concentrated around one of these. How are you planning to derive the (profile) corrected CRNS data for the locations where soilnet is not present?

    Since the new CRNS network will cover a large area, would you say that using Hydrus 1d for estimating groundwater recharge is still a suitable model for the purpose (given the spatial scale difference between CRNS and Hydrus 1d) or will you be looking at other models too? Sorry, if I have overlooked the details in the presentation (I am not a groundwater recharge expert).

    Many thanks!


    • AC1: Reply to CC1, Lena M. Scheiffele, 04 May 2020

      Dear Katya,

      thanks for your interest!

      The massive network is massive in a way, that never before have so many CRNS probes been pooled at one location. In this case they are distributed over a small pra-alpine catchment of about 1 km².

      As you identified correctly, there is a dense sensor network near the outlet of the catchment (part of the TERENO network). This is operated on the long term. For our field study of pooling the CRNS probes (2 month duration, transition from wet to dry in spring time 2019), we installed additional profile probes close to each CRNS probe and they are thus distributed over the whole catchment. 
      Further details on the study site and the insturmentation can also be found in a data paper, open now  for discussion on "Earth System Science Data": 

      For estimating groundwater recharge and using CRNS soil moisture I will start of with using Hydrus 1D and derive recharge rates at the field scale based on the single CRNS stations. But you are right, the catchment is quite large considering the footprint of the single probes and also quite heterogeneous. So I will have to try different options of estimatign the recharge of the whole catchment (e.g. determining ladscape units and weighting accordingly). We will be able to validate the results mainly on recharge rates estimated from stream discharge measurements. So far, no other models are planned to use. 

      • CC2: Reply to AC1, Katya Dimitrova Petrova, 04 May 2020

        Dear Lena,

        That is indeed a massive sensing effort, thanks for the reference to the discussion paper.

        Thanks for your reply on the modelling too, I totally see the logic. I am looking forward reading more of your work.