58 citations as recorded by crossref.

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2. Closing the water balance with cosmic-ray soil moisture measurements and assessing their relation to evapotranspiration in two semiarid watersheds A. Schreiner-McGraw et al. https://doi.org/10.5194/hess-20-329-2016
3. High-resolution drought simulations and comparison to soil moisture observations in Germany F. Boeing et al. https://doi.org/10.5194/hess-26-5137-2022
4. Assimilation of Cosmic‐Ray Neutron Counts for the Estimation of Soil Ice Content on the Eastern Tibetan Plateau S. Mwangi et al. https://doi.org/10.1029/2019JD031529
5. A Novel Lithium Foil Cosmic-Ray Neutron Detector for Measuring Field-Scale Soil Moisture A. Patrignani et al. https://doi.org/10.3389/frwa.2021.673185
6. Field-scale moisture estimates using COSMOS sensors: A validation study with temporary networks and Leaf-Area-Indices E. Coopersmith et al. https://doi.org/10.1016/j.jhydrol.2014.07.060
7. A scaling approach for the assessment of biomass changes and rainfall interception using cosmic-ray neutron sensing G. Baroni & S. Oswald https://doi.org/10.1016/j.jhydrol.2015.03.053
8. Simultaneous soil moisture and properties estimation for a drip irrigated field by assimilating cosmic-ray neutron intensity X. Han et al. https://doi.org/10.1016/j.jhydrol.2016.05.050
9. Cosmic-Ray neutron Sensor PYthon tool (crspy 1.2.1): an open-source tool for the processing of cosmic-ray neutron and soil moisture data D. Power et al. https://doi.org/10.5194/gmd-14-7287-2021
10. SWAT‐Based Hydrological Data Assimilation System (SWAT‐HDAS): Description and Case Application to River Basin‐Scale Hydrological Predictions Y. Zhang et al. https://doi.org/10.1002/2017MS001144
11. Using data assimilation to optimize pedotransfer functions using field-scale in situ soil moisture observations E. Cooper et al. https://doi.org/10.5194/hess-25-2445-2021
12. The Potsdam Soil Moisture Observatory: high-coverage reference observations at kilometer scale P. Grosse et al. https://doi.org/10.5194/essd-18-1703-2026
13. Mesoscale soil moisture survey by mobile cosmic-ray neutron sensor across various landscapes in the Heihe River Basin S. Wu et al. https://doi.org/10.1016/j.rcar.2024.01.001
14. Correction of systematic model forcing bias of CLM using assimilation of cosmic-ray Neutrons and land surface temperature: a study in the Heihe Catchment, China X. Han et al. https://doi.org/10.5194/hess-19-615-2015
15. Evaluation of the soil water content of two managed ecosystems using cosmic‐ray neutron sensing on China's Loess Plateau C. Liu et al. https://doi.org/10.1111/ejss.13339
16. Improving Soil Moisture Profile Prediction With the Particle Filter-Markov Chain Monte Carlo Method H. Yan et al. https://doi.org/10.1109/TGRS.2015.2432067
17. Monitoring and Modeling the Terrestrial System from Pores to Catchments: The Transregional Collaborative Research Center on Patterns in the Soil–Vegetation–Atmosphere System C. Simmer et al. https://doi.org/10.1175/BAMS-D-13-00134.1
18. Evapotranspiration prediction for European forest sites does not improve with assimilation of in situ soil water content data L. Strebel et al. https://doi.org/10.5194/hess-28-1001-2024
19. Spatio-temporal soil moisture retrieval at the catchment scale using a dense network of cosmic-ray neutron sensors M. Heistermann et al. https://doi.org/10.5194/hess-25-4807-2021
20. Comparison of Different Machine Learning Approaches for Monthly Satellite-Based Soil Moisture Downscaling over Northeast China Y. Liu et al. https://doi.org/10.3390/rs10010031
21. On the Information Content of Cosmic‐Ray Neutron Data in the Inverse Estimation of Soil Hydraulic Properties G. Brunetti et al. https://doi.org/10.2136/vzj2018.06.0123
22. Accuracy and precision of the cosmic‐ray neutron sensor for soil moisture estimation at humid environments J. Iwema et al. https://doi.org/10.1002/hyp.14419
23. Evaluation of a cosmic-ray neutron sensor network for improved land surface model prediction R. Baatz et al. https://doi.org/10.5194/hess-21-2509-2017
24. Assimilation of Cosmogenic Neutron Counts for Improved Soil Moisture Prediction in a Distributed Land Surface Model A. Patil et al. https://doi.org/10.3389/frwa.2021.729592
25. Estimating field-scale root zone soil moisture using the cosmic-ray neutron probe A. Peterson et al. https://doi.org/10.5194/hess-20-1373-2016
26. Dynamic groundwater recharge simulations based on cosmic‐ray neutron sensing in a tropical wet experimental basin L. Barbosa et al. https://doi.org/10.1002/vzj2.20145
27. Footprint characteristics revised for field‐scale soil moisture monitoring with cosmic‐ray neutrons M. Köhli et al. https://doi.org/10.1002/2015WR017169
28. Emerging methods for noninvasive sensing of soil moisture dynamics from field to catchment scale: a review H. Bogena et al. https://doi.org/10.1002/wat2.1097
29. Investigating the Potential of Cosmic-Ray Neutron Sensing for Estimating Soil Water Content in Farmland and Mountainous Areas Y. Jiang et al. https://doi.org/10.3390/w15081500
30. Comprehensive quality assessment of satellite- and model-based soil moisture products against the COSMOS network in Germany T. Schmidt et al. https://doi.org/10.1016/j.rse.2023.113930
31. Use of cosmic-ray neutron sensors for soil moisture monitoring in forests I. Heidbüchel et al. https://doi.org/10.5194/hess-20-1269-2016
32. Improving soil moisture prediction of a high-resolution land surface model by parameterising pedotransfer functions through assimilation of SMAP satellite data E. Pinnington et al. https://doi.org/10.5194/hess-25-1617-2021
33. A new approach for joint assimilation of cosmic-ray neutron soil moisture and groundwater level data into an integrated terrestrial model F. Li et al. https://doi.org/10.5194/hess-29-6419-2025
34. Incorporation of globally available datasets into the roving cosmic-ray neutron probe method for estimating field-scale soil water content W. Avery et al. https://doi.org/10.5194/hess-20-3859-2016
35. An empirical vegetation correction for soil water content quantification using cosmic ray probes R. Baatz et al. https://doi.org/10.1002/2014WR016443
36. A change in perspective: downhole cosmic-ray neutron sensing for the estimation of soil moisture D. Rasche et al. https://doi.org/10.5194/hess-27-3059-2023
37. Improved representation of soil moisture processes through incorporation of cosmic-ray neutron count measurements in a large-scale hydrologic model E. Fatima et al. https://doi.org/10.5194/hess-28-5419-2024
38. Cosmic-ray neutron sensors provide scale-appropriate soil water content and vegetation observations for eddy covariance stations in agricultural ecosystems C. Brogi et al. https://doi.org/10.1016/j.agrformet.2025.110731
39. Continuous monitoring of snowpack dynamics in alpine terrain by aboveground neutron sensing P. Schattan et al. https://doi.org/10.1002/2016WR020234
40. Employing NDVI as vegetation correction variable to improve soil moisture measurements of mobile cosmic-ray neutron sensor near the Qilian Mountains S. Wu et al. https://doi.org/10.1016/j.geoderma.2023.116764
41. Combined assimilation of streamflow and satellite soil moisture with the particle filter and geostatistical modeling H. Yan & H. Moradkhani https://doi.org/10.1016/j.advwatres.2016.06.002
42. Translating aboveground cosmic-ray neutron intensity to high-frequency soil moisture profiles at sub-kilometer scale R. Rosolem et al. https://doi.org/10.5194/hess-18-4363-2014
43. Changes of Soil Moisture from Multiple Sources during 1988–2010 in the Yellow River Basin, China D. Lou et al. https://doi.org/10.1155/2018/1950529
44. Large-Scale Boron-Lined Neutron Detection Systems as a 3He Alternative for Cosmic Ray Neutron Sensing J. Weimar et al. https://doi.org/10.3389/frwa.2020.00016
45. Signal contribution of distant areas to cosmic-ray neutron sensors – implications for footprint and sensitivity M. Schrön et al. https://doi.org/10.5194/hess-27-723-2023
46. Soil Moisture and Air Humidity Dependence of the Above-Ground Cosmic-Ray Neutron Intensity M. Köhli et al. https://doi.org/10.3389/frwa.2020.544847
47. Monitoring Irrigation in Small Orchards with Cosmic-Ray Neutron Sensors C. Brogi et al. https://doi.org/10.3390/s23052378
48. Calibration of a catchment scale cosmic-ray probe network: A comparison of three parameterization methods R. Baatz et al. https://doi.org/10.1016/j.jhydrol.2014.02.026
49. Land surface model performance using cosmic-ray and point-scale soil moisture measurements for calibration J. Iwema et al. https://doi.org/10.5194/hess-21-2843-2017
50. Application and accuracy of cosmic-ray neutron probes in three soil textures on the Loess Plateau, China Q. Wang et al. https://doi.org/10.1016/j.jhydrol.2018.11.073
51. A profile shape correction to reduce the vertical sensitivity of cosmic‐ray neutron sensing of soil moisture L. Scheiffele et al. https://doi.org/10.1002/vzj2.20083
52. Can a Sparse Network of Cosmic Ray Neutron Sensors Improve Soil Moisture and Evapotranspiration Estimation at the Larger Catchment Scale? F. Li et al. https://doi.org/10.1029/2023WR035056
53. Modeling the impact of tillage and consolidation on the vadose zone hydrological behavior for data-limited conditions G. Brunetti et al. https://doi.org/10.1016/j.geoderma.2025.117607
54. Status and Perspectives on the Cosmic‐Ray Neutron Method for Soil Moisture Estimation and Other Environmental Science Applications M. Andreasen et al. https://doi.org/10.2136/vzj2017.04.0086
55. Feasibility of irrigation monitoring with cosmic-ray neutron sensors C. Brogi et al. https://doi.org/10.5194/gi-11-451-2022
56. Soil moisture measurements by Cosmic-Ray neutron sensing: A critical review M. Köhli https://doi.org/10.1016/j.geoderma.2025.117626
57. Application of cosmic-ray neutron sensing to monitor soil water content in an alpine meadow ecosystem on the northern Tibetan Plateau X. Zhu et al. https://doi.org/10.1016/j.jhydrol.2016.02.038
58. Investigating temporal field sampling strategies for site-specific calibration of three soil moisture–neutron intensity parameterisation methods J. Iwema et al. https://doi.org/10.5194/hess-19-3203-2015