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Assimilation of Cosmogenic Neutron Counts for Improved Soil Moisture Prediction in a Distributed Land Surface Model

Patil, Amol; Fersch, Benjamin ORCID iD icon; Hendricks Franssen, Harrie-Jan; Kunstmann, Harald


Cosmic-Ray Neutron Sensing (CRNS) offers a non-invasive method for estimating soil moisture at the field scale, in our case a few tens of hectares. The current study uses the Ensemble Adjustment Kalman Filter (EAKF) to assimilate neutron counts observed at four locations within a 655 km$^{2}$ pre-alpine river catchment into the Noah-MP land surface model (LSM) to improve soil moisture simulations and to optimize model parameters. The model runs with 100 m spatial resolution and uses the EU-SoilHydroGrids soil map along with the Mualem–van Genuchten soil water retention functions. Using the state estimation (ST) and joint state–parameter estimation (STP) technique, soil moisture states and model parameters controlling infiltration and evaporation rates were optimized, respectively. The added value of assimilation was evaluated for local and regional impacts using independent root zone soil moisture observations. The results show that during the assimilation period both ST and STP significantly improved the simulated soil moisture around the neutron sensors locations with improvements of the root mean square errors between 60 and 62% for ST and 55–66% for STP. ... mehr

Verlagsausgabe §
DOI: 10.5445/IR/1000140533
Veröffentlicht am 03.12.2021
DOI: 10.3389/frwa.2021.729592
Zitationen: 5
Zitationen: 5
Cover der Publikation
Zugehörige Institution(en) am KIT Institut für Meteorologie und Klimaforschung – Atmosphärische Umweltforschung (IMK-IFU)
Publikationstyp Zeitschriftenaufsatz
Publikationsdatum 16.09.2021
Sprache Englisch
Identifikator ISSN: 2624-9375
KITopen-ID: 1000140533
HGF-Programm 12.11.33 (POF IV, LK 01) Regional Climate and Hydrological Cycle
Erschienen in Frontiers in Water
Verlag Frontiers Media SA
Band 3
Seiten Art.-Nr. 729592
Nachgewiesen in Dimensions
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