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OpenAlex Citation Counts

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OpenAlex is a bibliographic catalogue of scientific papers, authors and institutions accessible in open access mode, named after the Library of Alexandria. It's citation coverage is excellent and I hope you will find utility in this listing of citing articles!

If you click the article title, you'll navigate to the article, as listed in CrossRef. If you click the Open Access links, you'll navigate to the "best Open Access location". Clicking the citation count will open this listing for that article. Lastly at the bottom of the page, you'll find basic pagination options.

Requested Article:

Towards a methodology for testing models as hypotheses in the inexact sciences
Keith Beven
Proceedings of the Royal Society A Mathematical Physical and Engineering Sciences (2019) Vol. 475, Iss. 2224, pp. 20180862-20180862
Open Access | Times Cited: 84

Showing 26-50 of 84 citing articles:

Stochastic Watershed Model Ensembles for Long‐Range Planning: Verification and Validation
Ghazal Shabestanipour, Zachary Paul Brodeur, William Farmer, et al.
Water Resources Research (2023) Vol. 59, Iss. 2
Closed Access | Times Cited: 15
Controls on the Spatial and Temporal Patterns of Rainfall‐Runoff Event Characteristics—A Large Sample of Catchments Across Great Britain
Yanchen Zheng, Gemma Coxon, Ross Woods, et al.
Water Resources Research (2023) Vol. 59, Iss. 6
Open Access | Times Cited: 14
Uncertainties in measuring and estimating water‐budget components: Current state of the science
Sara B. Levin, Martin A. Briggs, Sydney S. Foks, et al.
Wiley Interdisciplinary Reviews Water (2023) Vol. 10, Iss. 4
Open Access | Times Cited: 13
rSHUD v2.0: advancing the Simulator for Hydrologic Unstructured Domains and unstructured hydrological modeling in the R environment
Lele Shu, Paul Ullrich, Xianhong Meng, et al.
Geoscientific model development (2024) Vol. 17, Iss. 2, pp. 497-527
Open Access | Times Cited: 4
Evaluation of hydrological models at gauged and ungauged basins using machine learning-based limits-of-acceptability and hydrological signatures
Abhinav Gupta, Mohamed M. Hantush, Rao S. Govindaraju, et al.
Journal of Hydrology (2024) Vol. 641, pp. 131774-131774
Open Access | Times Cited: 4
Escape from model-land
Erica Thompson, Leonard A. Smith
Economics (2019) Vol. 13, Iss. 1
Open Access | Times Cited: 41
Budyko‐Based Long‐Term Water and Energy Balance Closure in Global Watersheds From Earth Observations
Akash Koppa, Sarfaraz Alam, Diego G. Miralles, et al.
Water Resources Research (2021) Vol. 57, Iss. 5
Open Access | Times Cited: 31
Bayesian network modelling of phosphorus pollution in agricultural catchments with high-resolution data
Camilla Negri, Per‐Erik Mellander, Nick Schurch, et al.
Environmental Modelling & Software (2024) Vol. 178, pp. 106073-106073
Open Access | Times Cited: 3
A global hydrology research agenda fit for the 2030s
Robert L. Wilby
Hydrology Research (2019) Vol. 50, Iss. 6, pp. 1464-1480
Open Access | Times Cited: 33
An epistemically uncertain walk through the rather fuzzy subject of observation and model uncertainties1
Keith Beven
Hydrological Processes (2020) Vol. 35, Iss. 1
Open Access | Times Cited: 28
HESS Opinions: Participatory Digital eARth Twin Hydrology systems (DARTHs) for everyone – a blueprint for hydrologists
Riccardo Rigon, Giuseppe Formetta, Marialaura Bancheri, et al.
Hydrology and earth system sciences (2022) Vol. 26, Iss. 18, pp. 4773-4800
Open Access | Times Cited: 18
Large variations in global irrigation withdrawals caused by uncertain irrigation efficiencies
Arnald Puy, Bruce Lankford, Jonas Meier, et al.
Environmental Research Letters (2022) Vol. 17, Iss. 4, pp. 044014-044014
Open Access | Times Cited: 16
Identification of Dominant Hydrological Mechanisms Using Bayesian Inference, Multiple Statistical Hypothesis Testing, and Flexible Models
Cristina Prieto, Dmitri Kavetski, Nataliya Le Vine, et al.
Water Resources Research (2021) Vol. 57, Iss. 8
Open Access | Times Cited: 21
The Role of Prior Probabilities on Parameter Estimation in Hydrological Models
Abhinav Gupta, Rao S. Govindaraju, Renato Morbidelli, et al.
Water Resources Research (2022) Vol. 58, Iss. 5
Open Access | Times Cited: 15
Comparing the Runoff Decompositions of Small Experimental Catchments: End-Member Mixing Analysis (EMMA) vs. Hydrological Modelling
А. Н. Бугаец, Б. И. Гарцман, Т. С. Губарева, et al.
Water (2023) Vol. 15, Iss. 4, pp. 752-752
Open Access | Times Cited: 8
Evaluating a conceptual hydrological model at gauged and ungauged basins using machine learning-based limits-of-acceptability and hydrological signatures
Abhinav Gupta, Mohamed M. Hantush, Rao S. Govindaraju
EarthArXiv (California Digital Library) (2024)
Open Access | Times Cited: 2
UPH Problem 20 – reducing uncertainty in model prediction: a model invalidation approach based on a Turing-like test
Keith Beven, Trevor Page, Paul J. Smith, et al.
Proceedings of the International Association of Hydrological Sciences (2024) Vol. 385, pp. 129-134
Open Access | Times Cited: 2
A short history of philosophies of hydrological model evaluation and hypothesis testing
Keith Beven
Wiley Interdisciplinary Reviews Water (2024)
Open Access | Times Cited: 2
Interpolation of rainfall observations during extreme rainfall events in complex mountainous terrain
Trevor Page, Keith Beven, Barry Hankin, et al.
Hydrological Processes (2022) Vol. 36, Iss. 11
Open Access | Times Cited: 10
Assessing water dynamics and net percolation rates within engineered cover systems for mine waste rock piles: A long-term field monitoring study
Deanna Hersey, Christopher Power
Journal of Hydrology (2023) Vol. 627, pp. 130471-130471
Closed Access | Times Cited: 5
An agent-based model that simulates the spatio-temporal dynamics of sources and transfer mechanisms contributing faecal indicator organisms to streams. Part 2: Application to a small agricultural catchment
Aaron J. Neill, Doerthe Tetzlaff, Norval J. C. Strachan, et al.
Journal of Environmental Management (2020) Vol. 270, pp. 110905-110905
Open Access | Times Cited: 15
Issues in generating stochastic observables for hydrological models
Keith Beven
Hydrological Processes (2021) Vol. 35, Iss. 6
Closed Access | Times Cited: 13
Application of Different Structures of HBV Model to Studying Runoff Formation Processes: Case Study of Experimental Catchments
S. Yu. Lupakov, А. Н. Бугаец, В. В. Шамов
Water Resources (2021) Vol. 48, Iss. 4, pp. 512-520
Closed Access | Times Cited: 12
Impacts of observational uncertainty on analysis and modelling of hydrological processes: Preface
Hilary McMillan, Gemma Coxon, Anna E. Sikorska‐Senoner, et al.
Hydrological Processes (2022) Vol. 36, Iss. 2
Open Access | Times Cited: 8
Benchmarking Hydrological Models for an Uncertain Future
Keith Beven
Authorea (Authorea) (2023)
Open Access | Times Cited: 4

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