Preprints
https://doi.org/10.5194/egusphere-2023-1548
https://doi.org/10.5194/egusphere-2023-1548
19 Jul 2023
 | 19 Jul 2023

Improved representation of soil moisture simulations through incorporation of cosmic-ray neutron count measurements in a large-scale hydrologic model

Eshrat Fatima, Rohini Kumar, Sabine Attinger, Maren Kaluza, Oldrich Rakovec, Corinna Rebmann, Rafael Rosolem, Sascha Oswald, Luis Samaniego, Steffen Zacharias, and Martin Schrön

Abstract. Profound knowledge of soil moisture and its variability plays a crucial role in hydrological modeling to support agricultural management, flood and drought monitoring and forecasting, and groundwater recharge estimation. Cosmic-ray neutron sensing (CRNS) have been recognized as a promising tool for soil moisture monitoring due to their hectare-scale footprint and decimeter-scale measurement depth. Different approaches exists that could be the basis for incorporating CRNS data into distributed hydrologic models, but largely still need to be implemented, thoroughly compared, and tested across different soil and vegetation types. This study establishes a framework to accommodate neutron count measurements and assess the accuracy of soil water content simulated by the mesoscale Hydrological Model (mHM) for the first time. It covers CRNS observations across different vegetation types in Germany ranging from agricultural areas to forest. We include two different approaches to estimate CRNS neutron counts in mHM based on the simulated soil moisture: a method based on the Desilets equation and another one based on the Cosmic-ray Soil Moisture Interaction Code (COSMIC). Within the Desilets approach, we further test two different averaging methods for the vertically layered soil moisture, namely uniform vs. non-uniform weighting scheme depending on the CRNS penetrating depth. A Monte Carlos simulation with Latin hypercube sampling approach (with N = 100,000) is employed to explore and constrain the (behavioral) mHM parameterizations against observed CRNS neutron counts. Overall, the three methods perform well with Kling-Gupta efficiency > 0.8 and percent bias < 1 % across the majority of investigated sites. We find that the non-uniform weighting scheme in the Desilets method provide the most reliable performance, whereas the more commonly used approach with uniformly weighted average soil moisture overestimates the observed CRNS neutron counts. We then also demonstrate the usefulness of incorporating CRNS measurements into mHM for the simulations of both soil moisture and evapotranspiration and add a broader discussion on the potential and guidelines of incorporating CRNS measurements in large-scale hydrological and land surface models.

Eshrat Fatima, Rohini Kumar, Sabine Attinger, Maren Kaluza, Oldrich Rakovec, Corinna Rebmann, Rafael Rosolem, Sascha Oswald, Luis Samaniego, Steffen Zacharias, and Martin Schrön

Status: final response (author comments only)

Comment types: AC – author | RC – referee | CC – community | EC – editor | CEC – chief editor | : Report abuse
  • RC1: 'Comment on egusphere-2023-1548', Anonymous Referee #1, 29 Aug 2023
    • AC1: 'Reply on RC1', Eshrat Fatima, 02 Nov 2023
  • RC2: 'Comment on egusphere-2023-1548', Anonymous Referee #2, 12 Sep 2023
    • AC2: 'Reply on RC2', Eshrat Fatima, 02 Nov 2023
  • CC1: 'Comment on egusphere-2023-1548', Markus Köhli, 13 Sep 2023
    • AC3: 'Reply on CC1', Eshrat Fatima, 02 Nov 2023
Eshrat Fatima, Rohini Kumar, Sabine Attinger, Maren Kaluza, Oldrich Rakovec, Corinna Rebmann, Rafael Rosolem, Sascha Oswald, Luis Samaniego, Steffen Zacharias, and Martin Schrön
Eshrat Fatima, Rohini Kumar, Sabine Attinger, Maren Kaluza, Oldrich Rakovec, Corinna Rebmann, Rafael Rosolem, Sascha Oswald, Luis Samaniego, Steffen Zacharias, and Martin Schrön

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Short summary
This study establishes a framework to incorporate cosmic-ray neutron measurements into the mesoscale Hydrological Model (mHM). We evaluate different approaches to estimate neutron counts within mHM, using the Desilets equation with uniformly and with non-uniformly weighted average soil moisture, and the physically-based code COSMIC. The data not only improved soil moisture simulations, but also the parameterization of evapotranspiration in the model.