Articles | Volume 25, issue 2
https://doi.org/10.5194/hess-25-527-2021
© Author(s) 2021. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Special issue:
https://doi.org/10.5194/hess-25-527-2021
© Author(s) 2021. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Review article
| 
02 Feb 2021
Review article |
| 02 Feb 2021
| 02 Feb 2021
A history of TOPMODEL
Lancaster Environment Centre, Lancaster University, Lancaster, UK
Mike J. Kirkby
School of Geography, University of Leeds, Leeds, UK
Jim E. Freer
University of Saskatchewan, Centre for Hydrology, Canmore, Canada
School of Geographical Sciences, University of Bristol, Bristol, UK
JBA Trust, Broughton, UK
Lancaster Environment Centre, Lancaster University, Lancaster, UK
Related authors
Elizabeth Follett, Keith Beven, Barry Hankin, David Mindham, and Nick Chappell
Proc. IAHS, 385, 197–201, https://doi.org/10.5194/piahs-385-197-2024, https://doi.org/10.5194/piahs-385-197-2024, 2024
Short summary
Short summary
This paper presents a spreadsheet design tool for barriers in streams used for natural flood management. Retention times in such barriers should neither be too short (they fill and empty too quickly) or too long (they might already be full when a flood occurs). Previous work has shown the order of 10 h to be effective. The tool is freely available for download at https://www.jbatrust.org/how-we-help/publications-resources/rivers-and-coasts/nfm-leaky-barrier-retention-times.
Keith Beven, Trevor Page, Paul Smith, Ann Kretzschmar, Barry Hankin, and Nick Chappell
Proc. IAHS, 385, 129–134, https://doi.org/10.5194/piahs-385-129-2024, https://doi.org/10.5194/piahs-385-129-2024, 2024
Short summary
Short summary
This paper presents a method of deciding when a hydrological model might be fit for purpose given the limitations of the data that are available for model evaluation. In this case the purpose is to reproduce the peak flows for an application that is concerned with evaluating the effect of natural flood management measures on flood peaks. It is shown that while all the models fail to pass the test at all time steps, there is an ensemble of models that pass for the hydrograph peaks.
Trevor Page, Paul Smith, Keith Beven, Francesca Pianosi, Fanny Sarrazin, Susana Almeida, Liz Holcombe, Jim Freer, Nick Chappell, and Thorsten Wagener
Hydrol. Earth Syst. Sci., 27, 2523–2534, https://doi.org/10.5194/hess-27-2523-2023, https://doi.org/10.5194/hess-27-2523-2023, 2023
Short summary
Short summary
This publication provides an introduction to the CREDIBLE Uncertainty Estimation (CURE) toolbox. CURE offers workflows for a variety of uncertainty estimation methods. One of its most important features is the requirement that all of the assumptions on which a workflow analysis depends be defined. This facilitates communication with potential users of an analysis. An audit trail log is produced automatically from a workflow for future reference.
Antonio Capponi, Natalie J. Harvey, Helen F. Dacre, Keith Beven, Cameron Saint, Cathie Wells, and Mike R. James
Atmos. Chem. Phys., 22, 6115–6134, https://doi.org/10.5194/acp-22-6115-2022, https://doi.org/10.5194/acp-22-6115-2022, 2022
Short summary
Short summary
Forecasts of the dispersal of volcanic ash in the atmosphere are hampered by uncertainties in parameters describing the characteristics of volcanic plumes. Uncertainty quantification is vital for making robust flight-planning decisions. We present a method using satellite data to refine a series of volcanic ash dispersion forecasts and quantify these uncertainties. We show how we can improve forecast accuracy and potentially reduce the regions of high risk of volcanic ash relevant to aviation.
Paul C. Astagneau, Guillaume Thirel, Olivier Delaigue, Joseph H. A. Guillaume, Juraj Parajka, Claudia C. Brauer, Alberto Viglione, Wouter Buytaert, and Keith J. Beven
Hydrol. Earth Syst. Sci., 25, 3937–3973, https://doi.org/10.5194/hess-25-3937-2021, https://doi.org/10.5194/hess-25-3937-2021, 2021
Short summary
Short summary
The R programming language has become an important tool for many applications in hydrology. In this study, we provide an analysis of some of the R tools providing hydrological models. In total, two aspects are uniformly investigated, namely the conceptualisation of the models and the practicality of their implementation for end-users. These comparisons aim at easing the choice of R tools for users and at improving their usability for hydrology modelling to support more transferable research.
Keith Beven
Hydrol. Earth Syst. Sci., 25, 851–866, https://doi.org/10.5194/hess-25-851-2021, https://doi.org/10.5194/hess-25-851-2021, 2021
Short summary
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Inspired by a quotation from Howard Cook in 1946, this paper traces the evolution of the infiltration theory of runoff from the work of Robert Horton and LeRoy Sherman in the 1930s to the early digital computer models of the 1970s and 1980s. Reconsideration of the perceptual model for many catchments, partly as a result of the greater appreciation of the contribution of subsurface flows to the hydrograph indicated by tracer studies, suggests a reconsideration of hydrological nomenclature.
Keith J. Beven
Hydrol. Earth Syst. Sci., 24, 2655–2670, https://doi.org/10.5194/hess-24-2655-2020, https://doi.org/10.5194/hess-24-2655-2020, 2020
Short summary
Short summary
The concept of time of concentration in the analysis of catchment responses dates back over 150 years. It is normally discussed in terms of the velocity of flow of a water particle from the furthest part of a catchment to the outlet. This is also the basis for the definition in the International Glossary of Hydrology, but this is in conflict with the way in which it is commonly used. This paper provides a clarification of the concept and its correct useage.
Keith J. Beven, Susana Almeida, Willy P. Aspinall, Paul D. Bates, Sarka Blazkova, Edoardo Borgomeo, Jim Freer, Katsuichiro Goda, Jim W. Hall, Jeremy C. Phillips, Michael Simpson, Paul J. Smith, David B. Stephenson, Thorsten Wagener, Matt Watson, and Kate L. Wilkins
Nat. Hazards Earth Syst. Sci., 18, 2741–2768, https://doi.org/10.5194/nhess-18-2741-2018, https://doi.org/10.5194/nhess-18-2741-2018, 2018
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This paper discusses how uncertainties resulting from lack of knowledge are considered in a number of different natural hazard areas including floods, landslides and debris flows, dam safety, droughts, earthquakes, tsunamis, volcanic ash clouds and pyroclastic flows, and wind storms. As every analysis is necessarily conditional on the assumptions made about the nature of sources of such uncertainties it is also important to follow the guidelines for good practice suggested in Part 2.
Keith J. Beven, Willy P. Aspinall, Paul D. Bates, Edoardo Borgomeo, Katsuichiro Goda, Jim W. Hall, Trevor Page, Jeremy C. Phillips, Michael Simpson, Paul J. Smith, Thorsten Wagener, and Matt Watson
Nat. Hazards Earth Syst. Sci., 18, 2769–2783, https://doi.org/10.5194/nhess-18-2769-2018, https://doi.org/10.5194/nhess-18-2769-2018, 2018
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Part 1 of this paper discussed the uncertainties arising from gaps in knowledge or limited understanding of the processes involved in different natural hazard areas. These are the epistemic uncertainties that can be difficult to constrain, especially in terms of event or scenario probabilities. A conceptual framework for good practice in dealing with epistemic uncertainties is outlined and implications of applying the principles to natural hazard science are discussed.
Peter Metcalfe, Keith Beven, Barry Hankin, and Rob Lamb
Hydrol. Earth Syst. Sci., 22, 2589–2605, https://doi.org/10.5194/hess-22-2589-2018, https://doi.org/10.5194/hess-22-2589-2018, 2018
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Flooding is a significant hazard and extreme events in recent years have focused attention on effective means of reducing its risk. An approach known as natural flood management (NFM) seeks to increase flood resilience by a range of measures that work with natural processes. The paper develops a modelling approach to assess one type NFM of intervention – distributed additional hillslope storage features – and demonstrates that more strategic placement is required than has hitherto been applied.
Kevin Sene, Wlodek Tych, and Keith Beven
Hydrol. Earth Syst. Sci., 22, 127–141, https://doi.org/10.5194/hess-22-127-2018, https://doi.org/10.5194/hess-22-127-2018, 2018
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The theme of the paper is exploration of the potential for seasonal flow forecasting for large lakes using a range of stochastic transfer function techniques with additional insights gained from simple analytical approximations. The methods were evaluated using records for two of the largest lakes in the world. The paper concludes with a discussion of the relevance of the results to operational flow forecasting systems for other large lakes.
Mary C. Ockenden, Wlodek Tych, Keith J. Beven, Adrian L. Collins, Robert Evans, Peter D. Falloon, Kirsty J. Forber, Kevin M. Hiscock, Michael J. Hollaway, Ron Kahana, Christopher J. A. Macleod, Martha L. Villamizar, Catherine Wearing, Paul J. A. Withers, Jian G. Zhou, Clare McW. H. Benskin, Sean Burke, Richard J. Cooper, Jim E. Freer, and Philip M. Haygarth
Hydrol. Earth Syst. Sci., 21, 6425–6444, https://doi.org/10.5194/hess-21-6425-2017, https://doi.org/10.5194/hess-21-6425-2017, 2017
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This paper describes simple models of phosphorus load which are identified for three catchments in the UK. The models use new hourly observations of phosphorus load, which capture the dynamics of phosphorus transfer in small catchments that are often missed by models with a longer time step. Unlike more complex, process-based models, very few parameters are required, leading to low parameter uncertainty. Interpretation of the dominant phosphorus transfer modes is made based solely on the data.
Diana Fuentes-Andino, Keith Beven, Sven Halldin, Chong-Yu Xu, José Eduardo Reynolds, and Giuliano Di Baldassarre
Hydrol. Earth Syst. Sci., 21, 3597–3618, https://doi.org/10.5194/hess-21-3597-2017, https://doi.org/10.5194/hess-21-3597-2017, 2017
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Reproduction of past floods requires information on discharge and flood extent, commonly unavailable or uncertain during extreme events. We explored the possibility of reproducing an extreme flood disaster using rainfall and post-event hydrometric information by combining a rainfall-runoff and hydraulic modelling tool within an uncertainty analysis framework. Considering the uncertainty in post–event data, it was possible to reasonably reproduce the extreme event.
Rémi Dupas, Jordy Salmon-Monviola, Keith J. Beven, Patrick Durand, Philip M. Haygarth, Michael J. Hollaway, and Chantal Gascuel-Odoux
Hydrol. Earth Syst. Sci., 20, 4819–4835, https://doi.org/10.5194/hess-20-4819-2016, https://doi.org/10.5194/hess-20-4819-2016, 2016
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We developed a parsimonious topography-based hydrologic model coupled with a soil biogeochemistry sub-model in order to improve understanding and prediction of soluble reactive phosphorus (SRP) transfer in agricultural headwater catchments. The modelling approach includes an analysis of the information contained in the calibration data and propagation of uncertainty in model predictions using a GLUE "limits of acceptability" framework.
K. J. Beven, S. Almeida, W. P. Aspinall, P. D. Bates, S. Blazkova, E. Borgomeo, K. Goda, J. C. Phillips, M. Simpson, P. J. Smith, D. B. Stephenson, T. Wagener, M. Watson, and K. L. Wilkins
Nat. Hazards Earth Syst. Sci. Discuss., https://doi.org/10.5194/nhess-2015-295, https://doi.org/10.5194/nhess-2015-295, 2016
Preprint withdrawn
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Uncertainties in natural hazard risk assessment are generally dominated by the sources arising from lack of knowledge or understanding of the processes involved. This is Part 2 of 2 papers reviewing these epistemic uncertainties and covers different areas of natural hazards including landslides and debris flows, dam safety, droughts, earthquakes, tsunamis, volcanic ash clouds and pyroclastic flows, and wind storms. It is based on the work of the UK CREDIBLE research consortium.
K. J. Beven, W. P. Aspinall, P. D. Bates, E. Borgomeo, K. Goda, J. W. Hall, T. Page, J. C. Phillips, J. T. Rougier, M. Simpson, D. B. Stephenson, P. J. Smith, T. Wagener, and M. Watson
Nat. Hazards Earth Syst. Sci. Discuss., https://doi.org/10.5194/nhessd-3-7333-2015, https://doi.org/10.5194/nhessd-3-7333-2015, 2015
Preprint withdrawn
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Uncertainties in natural hazard risk assessment are generally dominated by the sources arising from lack of knowledge or understanding of the processes involved. This is Part 1 of 2 papers reviewing these epistemic uncertainties that can be difficult to constrain, especially in terms of event or scenario probabilities. It is based on the work of the CREDIBLE research consortium on Risk and Uncertainty in Natural Hazards.
I. K. Westerberg, L. Gong, K. J. Beven, J. Seibert, A. Semedo, C.-Y. Xu, and S. Halldin
Hydrol. Earth Syst. Sci., 18, 2993–3013, https://doi.org/10.5194/hess-18-2993-2014, https://doi.org/10.5194/hess-18-2993-2014, 2014
D. Leedal, A. H. Weerts, P. J. Smith, and K. J. Beven
Hydrol. Earth Syst. Sci., 17, 177–185, https://doi.org/10.5194/hess-17-177-2013, https://doi.org/10.5194/hess-17-177-2013, 2013
Shervan Gharari, Paul H. Whitfield, Alain Pietroniro, Jim Freer, Hongli Liu, and Martyn P. Clark
Hydrol. Earth Syst. Sci., 28, 4383–4405, https://doi.org/10.5194/hess-28-4383-2024, https://doi.org/10.5194/hess-28-4383-2024, 2024
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This study provides insight into the practices that are incorporated into discharge estimation across the national Canadian hydrometric network operated by the Water Survey of Canada (WSC). The procedures used to estimate and correct discharge values are not always understood by end-users. Factors such as ice cover and sedimentation limit accurate discharge estimation. Highlighting these challenges sheds light on difficulties in discharge estimation and the associated uncertainty.
Saskia Salwey, Gemma Coxon, Francesca Pianosi, Rosanna Lane, Chris Hutton, Michael Bliss Singer, Hilary McMillan, and Jim Freer
Hydrol. Earth Syst. Sci., 28, 4203–4218, https://doi.org/10.5194/hess-28-4203-2024, https://doi.org/10.5194/hess-28-4203-2024, 2024
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Reservoirs are essential for water resource management and can significantly impact downstream flow. However, representing reservoirs in hydrological models can be challenging, particularly across large scales. We design a new and simple method for simulating river flow downstream of water supply reservoirs using only open-access data. We demonstrate the approach in 264 reservoir catchments across Great Britain, where we can significantly improve the simulation of reservoir-impacted flow.
Elizabeth Follett, Keith Beven, Barry Hankin, David Mindham, and Nick Chappell
Proc. IAHS, 385, 197–201, https://doi.org/10.5194/piahs-385-197-2024, https://doi.org/10.5194/piahs-385-197-2024, 2024
Short summary
Short summary
This paper presents a spreadsheet design tool for barriers in streams used for natural flood management. Retention times in such barriers should neither be too short (they fill and empty too quickly) or too long (they might already be full when a flood occurs). Previous work has shown the order of 10 h to be effective. The tool is freely available for download at https://www.jbatrust.org/how-we-help/publications-resources/rivers-and-coasts/nfm-leaky-barrier-retention-times.
Keith Beven, Trevor Page, Paul Smith, Ann Kretzschmar, Barry Hankin, and Nick Chappell
Proc. IAHS, 385, 129–134, https://doi.org/10.5194/piahs-385-129-2024, https://doi.org/10.5194/piahs-385-129-2024, 2024
Short summary
Short summary
This paper presents a method of deciding when a hydrological model might be fit for purpose given the limitations of the data that are available for model evaluation. In this case the purpose is to reproduce the peak flows for an application that is concerned with evaluating the effect of natural flood management measures on flood peaks. It is shown that while all the models fail to pass the test at all time steps, there is an ensemble of models that pass for the hydrograph peaks.
Trevor Page, Paul Smith, Keith Beven, Francesca Pianosi, Fanny Sarrazin, Susana Almeida, Liz Holcombe, Jim Freer, Nick Chappell, and Thorsten Wagener
Hydrol. Earth Syst. Sci., 27, 2523–2534, https://doi.org/10.5194/hess-27-2523-2023, https://doi.org/10.5194/hess-27-2523-2023, 2023
Short summary
Short summary
This publication provides an introduction to the CREDIBLE Uncertainty Estimation (CURE) toolbox. CURE offers workflows for a variety of uncertainty estimation methods. One of its most important features is the requirement that all of the assumptions on which a workflow analysis depends be defined. This facilitates communication with potential users of an analysis. An audit trail log is produced automatically from a workflow for future reference.
Heidi Kreibich, Kai Schröter, Giuliano Di Baldassarre, Anne F. Van Loon, Maurizio Mazzoleni, Guta Wakbulcho Abeshu, Svetlana Agafonova, Amir AghaKouchak, Hafzullah Aksoy, Camila Alvarez-Garreton, Blanca Aznar, Laila Balkhi, Marlies H. Barendrecht, Sylvain Biancamaria, Liduin Bos-Burgering, Chris Bradley, Yus Budiyono, Wouter Buytaert, Lucinda Capewell, Hayley Carlson, Yonca Cavus, Anaïs Couasnon, Gemma Coxon, Ioannis Daliakopoulos, Marleen C. de Ruiter, Claire Delus, Mathilde Erfurt, Giuseppe Esposito, Didier François, Frédéric Frappart, Jim Freer, Natalia Frolova, Animesh K. Gain, Manolis Grillakis, Jordi Oriol Grima, Diego A. Guzmán, Laurie S. Huning, Monica Ionita, Maxim Kharlamov, Dao Nguyen Khoi, Natalie Kieboom, Maria Kireeva, Aristeidis Koutroulis, Waldo Lavado-Casimiro, Hong-Yi Li, Maria Carmen LLasat, David Macdonald, Johanna Mård, Hannah Mathew-Richards, Andrew McKenzie, Alfonso Mejia, Eduardo Mario Mendiondo, Marjolein Mens, Shifteh Mobini, Guilherme Samprogna Mohor, Viorica Nagavciuc, Thanh Ngo-Duc, Huynh Thi Thao Nguyen, Pham Thi Thao Nhi, Olga Petrucci, Nguyen Hong Quan, Pere Quintana-Seguí, Saman Razavi, Elena Ridolfi, Jannik Riegel, Md Shibly Sadik, Nivedita Sairam, Elisa Savelli, Alexey Sazonov, Sanjib Sharma, Johanna Sörensen, Felipe Augusto Arguello Souza, Kerstin Stahl, Max Steinhausen, Michael Stoelzle, Wiwiana Szalińska, Qiuhong Tang, Fuqiang Tian, Tamara Tokarczyk, Carolina Tovar, Thi Van Thu Tran, Marjolein H. J. van Huijgevoort, Michelle T. H. van Vliet, Sergiy Vorogushyn, Thorsten Wagener, Yueling Wang, Doris E. Wendt, Elliot Wickham, Long Yang, Mauricio Zambrano-Bigiarini, and Philip J. Ward
Earth Syst. Sci. Data, 15, 2009–2023, https://doi.org/10.5194/essd-15-2009-2023, https://doi.org/10.5194/essd-15-2009-2023, 2023
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As the adverse impacts of hydrological extremes increase in many regions of the world, a better understanding of the drivers of changes in risk and impacts is essential for effective flood and drought risk management. We present a dataset containing data of paired events, i.e. two floods or two droughts that occurred in the same area. The dataset enables comparative analyses and allows detailed context-specific assessments. Additionally, it supports the testing of socio-hydrological models.
Louisa D. Oldham, Jim Freer, Gemma Coxon, Nicholas Howden, John P. Bloomfield, and Christopher Jackson
Hydrol. Earth Syst. Sci., 27, 761–781, https://doi.org/10.5194/hess-27-761-2023, https://doi.org/10.5194/hess-27-761-2023, 2023
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Water can move between river catchments via the subsurface, termed intercatchment groundwater flow (IGF). We show how a perceptual model of IGF can be developed with relatively simple geological interpretation and data requirements. We find that IGF dynamics vary in space, correlated to the dominant underlying geology. We recommend that IGF
loss functionsmay be used in conceptual rainfall–runoff models but should be supported by perceptualisation of IGF processes and connectivities.
Antonio Capponi, Natalie J. Harvey, Helen F. Dacre, Keith Beven, Cameron Saint, Cathie Wells, and Mike R. James
Atmos. Chem. Phys., 22, 6115–6134, https://doi.org/10.5194/acp-22-6115-2022, https://doi.org/10.5194/acp-22-6115-2022, 2022
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Forecasts of the dispersal of volcanic ash in the atmosphere are hampered by uncertainties in parameters describing the characteristics of volcanic plumes. Uncertainty quantification is vital for making robust flight-planning decisions. We present a method using satellite data to refine a series of volcanic ash dispersion forecasts and quantify these uncertainties. We show how we can improve forecast accuracy and potentially reduce the regions of high risk of volcanic ash relevant to aviation.
Enrico Tubaldi, Christopher J. White, Edoardo Patelli, Stergios Aristoteles Mitoulis, Gustavo de Almeida, Jim Brown, Michael Cranston, Martin Hardman, Eftychia Koursari, Rob Lamb, Hazel McDonald, Richard Mathews, Richard Newell, Alonso Pizarro, Marta Roca, and Daniele Zonta
Nat. Hazards Earth Syst. Sci., 22, 795–812, https://doi.org/10.5194/nhess-22-795-2022, https://doi.org/10.5194/nhess-22-795-2022, 2022
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Bridges are critical infrastructure components of transport networks. A large number of these critical assets cross or are adjacent to waterways and are therefore exposed to the potentially devastating impact of floods. This paper discusses a series of issues and areas where improvements in research and practice are required in the context of risk assessment and management of bridges exposed to flood hazard, with the ultimate goal of guiding future efforts in improving bridge flood resilience.
Paul C. Astagneau, Guillaume Thirel, Olivier Delaigue, Joseph H. A. Guillaume, Juraj Parajka, Claudia C. Brauer, Alberto Viglione, Wouter Buytaert, and Keith J. Beven
Hydrol. Earth Syst. Sci., 25, 3937–3973, https://doi.org/10.5194/hess-25-3937-2021, https://doi.org/10.5194/hess-25-3937-2021, 2021
Short summary
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The R programming language has become an important tool for many applications in hydrology. In this study, we provide an analysis of some of the R tools providing hydrological models. In total, two aspects are uniformly investigated, namely the conceptualisation of the models and the practicality of their implementation for end-users. These comparisons aim at easing the choice of R tools for users and at improving their usability for hydrology modelling to support more transferable research.
Keith Beven
Hydrol. Earth Syst. Sci., 25, 851–866, https://doi.org/10.5194/hess-25-851-2021, https://doi.org/10.5194/hess-25-851-2021, 2021
Short summary
Short summary
Inspired by a quotation from Howard Cook in 1946, this paper traces the evolution of the infiltration theory of runoff from the work of Robert Horton and LeRoy Sherman in the 1930s to the early digital computer models of the 1970s and 1980s. Reconsideration of the perceptual model for many catchments, partly as a result of the greater appreciation of the contribution of subsurface flows to the hydrograph indicated by tracer studies, suggests a reconsideration of hydrological nomenclature.
Gemma Coxon, Nans Addor, John P. Bloomfield, Jim Freer, Matt Fry, Jamie Hannaford, Nicholas J. K. Howden, Rosanna Lane, Melinda Lewis, Emma L. Robinson, Thorsten Wagener, and Ross Woods
Earth Syst. Sci. Data, 12, 2459–2483, https://doi.org/10.5194/essd-12-2459-2020, https://doi.org/10.5194/essd-12-2459-2020, 2020
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We present the first large-sample catchment hydrology dataset for Great Britain. The dataset collates river flows, catchment attributes, and catchment boundaries for 671 catchments across Great Britain. We characterise the topography, climate, streamflow, land cover, soils, hydrogeology, human influence, and discharge uncertainty of each catchment. The dataset is publicly available for the community to use in a wide range of environmental and modelling analyses.
Barry Hankin, Ian Hewitt, Graham Sander, Federico Danieli, Giuseppe Formetta, Alissa Kamilova, Ann Kretzschmar, Kris Kiradjiev, Clint Wong, Sam Pegler, and Rob Lamb
Nat. Hazards Earth Syst. Sci., 20, 2567–2584, https://doi.org/10.5194/nhess-20-2567-2020, https://doi.org/10.5194/nhess-20-2567-2020, 2020
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With growing support for nature-based solutions to reduce flooding by local communities, government authorities and international organisations, it is still important to improve how we assess risk reduction. We demonstrate an efficient, simplified 1D network model that allows us to explore the
whole-systemresponse of numerous leaky barriers placed in different stream networks, whilst considering utilisation, synchronisation effects and cascade failure, and we provide advice on their siting.
Keith J. Beven
Hydrol. Earth Syst. Sci., 24, 2655–2670, https://doi.org/10.5194/hess-24-2655-2020, https://doi.org/10.5194/hess-24-2655-2020, 2020
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The concept of time of concentration in the analysis of catchment responses dates back over 150 years. It is normally discussed in terms of the velocity of flow of a water particle from the furthest part of a catchment to the outlet. This is also the basis for the definition in the International Glossary of Hydrology, but this is in conflict with the way in which it is commonly used. This paper provides a clarification of the concept and its correct useage.
Wouter J. M. Knoben, Jim E. Freer, and Ross A. Woods
Hydrol. Earth Syst. Sci., 23, 4323–4331, https://doi.org/10.5194/hess-23-4323-2019, https://doi.org/10.5194/hess-23-4323-2019, 2019
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The accuracy of model simulations can be quantified with so-called efficiency metrics. The Nash–Sutcliffe efficiency (NSE) has been often used in hydrology, but recently the Kling–Gupta efficiency (KGE) is gaining in popularity. We show that lessons learned about which NSE scores are
acceptabledo not necessarily translate well into understanding of the KGE metric.
Rosanna A. Lane, Gemma Coxon, Jim E. Freer, Thorsten Wagener, Penny J. Johnes, John P. Bloomfield, Sheila Greene, Christopher J. A. Macleod, and Sim M. Reaney
Hydrol. Earth Syst. Sci., 23, 4011–4032, https://doi.org/10.5194/hess-23-4011-2019, https://doi.org/10.5194/hess-23-4011-2019, 2019
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We evaluated four hydrological model structures and their parameters on over 1100 catchments across Great Britain, considering modelling uncertainties. Models performed well for most catchments but failed in parts of Scotland and south-eastern England. Failures were often linked to inconsistencies in the water balance. This research shows what conceptual lumped models can achieve, gives insights into where and why these models may fail, and provides a benchmark of national modelling capability.
Wouter J. M. Knoben, Jim E. Freer, Keirnan J. A. Fowler, Murray C. Peel, and Ross A. Woods
Geosci. Model Dev., 12, 2463–2480, https://doi.org/10.5194/gmd-12-2463-2019, https://doi.org/10.5194/gmd-12-2463-2019, 2019
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Computer models are used to predict river flows. A good model should represent the river basin to which it is applied so that flow predictions are as realistic as possible. However, many different computer models exist, and selecting the most appropriate model for a given river basin is not always easy. This study combines computer code for 46 different hydrological models into a single coding framework so that models can be compared in an objective way and we can learn about model differences.
Gemma Coxon, Jim Freer, Rosanna Lane, Toby Dunne, Wouter J. M. Knoben, Nicholas J. K. Howden, Niall Quinn, Thorsten Wagener, and Ross Woods
Geosci. Model Dev., 12, 2285–2306, https://doi.org/10.5194/gmd-12-2285-2019, https://doi.org/10.5194/gmd-12-2285-2019, 2019
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DECIPHeR (Dynamic fluxEs and ConnectIvity for Predictions of Hydrology) is a new modelling framework that can be applied from small catchment to continental scales for complex river basins. This paper describes the modelling framework and its key components and demonstrates the model’s ability to be applied across a large model domain. This work highlights the potential for catchment- to continental-scale predictions of streamflow to support robust environmental management and policy decisions.
Keith J. Beven, Susana Almeida, Willy P. Aspinall, Paul D. Bates, Sarka Blazkova, Edoardo Borgomeo, Jim Freer, Katsuichiro Goda, Jim W. Hall, Jeremy C. Phillips, Michael Simpson, Paul J. Smith, David B. Stephenson, Thorsten Wagener, Matt Watson, and Kate L. Wilkins
Nat. Hazards Earth Syst. Sci., 18, 2741–2768, https://doi.org/10.5194/nhess-18-2741-2018, https://doi.org/10.5194/nhess-18-2741-2018, 2018
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This paper discusses how uncertainties resulting from lack of knowledge are considered in a number of different natural hazard areas including floods, landslides and debris flows, dam safety, droughts, earthquakes, tsunamis, volcanic ash clouds and pyroclastic flows, and wind storms. As every analysis is necessarily conditional on the assumptions made about the nature of sources of such uncertainties it is also important to follow the guidelines for good practice suggested in Part 2.
Keith J. Beven, Willy P. Aspinall, Paul D. Bates, Edoardo Borgomeo, Katsuichiro Goda, Jim W. Hall, Trevor Page, Jeremy C. Phillips, Michael Simpson, Paul J. Smith, Thorsten Wagener, and Matt Watson
Nat. Hazards Earth Syst. Sci., 18, 2769–2783, https://doi.org/10.5194/nhess-18-2769-2018, https://doi.org/10.5194/nhess-18-2769-2018, 2018
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Part 1 of this paper discussed the uncertainties arising from gaps in knowledge or limited understanding of the processes involved in different natural hazard areas. These are the epistemic uncertainties that can be difficult to constrain, especially in terms of event or scenario probabilities. A conceptual framework for good practice in dealing with epistemic uncertainties is outlined and implications of applying the principles to natural hazard science are discussed.
Andreas Paul Zischg, Guido Felder, Rolf Weingartner, Niall Quinn, Gemma Coxon, Jeffrey Neal, Jim Freer, and Paul Bates
Hydrol. Earth Syst. Sci., 22, 2759–2773, https://doi.org/10.5194/hess-22-2759-2018, https://doi.org/10.5194/hess-22-2759-2018, 2018
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We developed a model experiment and distributed different rainfall patterns over a mountain river basin. For each rainfall scenario, we computed the flood losses with a model chain. The experiment shows that flood losses vary considerably within the river basin and depend on the timing of the flood peaks from the basin's sub-catchments. Basin-specific characteristics such as the location of the main settlements within the floodplains play an additional important role in determining flood losses.
Peter Metcalfe, Keith Beven, Barry Hankin, and Rob Lamb
Hydrol. Earth Syst. Sci., 22, 2589–2605, https://doi.org/10.5194/hess-22-2589-2018, https://doi.org/10.5194/hess-22-2589-2018, 2018
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Flooding is a significant hazard and extreme events in recent years have focused attention on effective means of reducing its risk. An approach known as natural flood management (NFM) seeks to increase flood resilience by a range of measures that work with natural processes. The paper develops a modelling approach to assess one type NFM of intervention – distributed additional hillslope storage features – and demonstrates that more strategic placement is required than has hitherto been applied.
Simon Brenner, Gemma Coxon, Nicholas J. K. Howden, Jim Freer, and Andreas Hartmann
Nat. Hazards Earth Syst. Sci., 18, 445–461, https://doi.org/10.5194/nhess-18-445-2018, https://doi.org/10.5194/nhess-18-445-2018, 2018
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In this study we simulate groundwater levels with a semi-distributed karst model. Using a percentile approach we can assess the number of days exceeding or falling below selected groundwater level percentiles. We show that our approach is able to predict groundwater levels across all considered timescales up to the 75th percentile. We then use our approach to assess future changes in groundwater dynamics and show that projected climate changes may lead to generally lower groundwater levels.
Benoit P. Guillod, Richard G. Jones, Simon J. Dadson, Gemma Coxon, Gianbattista Bussi, James Freer, Alison L. Kay, Neil R. Massey, Sarah N. Sparrow, David C. H. Wallom, Myles R. Allen, and Jim W. Hall
Hydrol. Earth Syst. Sci., 22, 611–634, https://doi.org/10.5194/hess-22-611-2018, https://doi.org/10.5194/hess-22-611-2018, 2018
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Assessing the potential impacts of extreme events such as drought and flood requires large datasets of such events, especially when looking at the most severe and rare events. Using a state-of-the-art climate modelling infrastructure that is simulating large numbers of weather time series on volunteers' computers, we generate such a large dataset for the United Kingdom. The dataset covers the recent past (1900–2006) as well as two future time periods (2030s and 2080s).
Kevin Sene, Wlodek Tych, and Keith Beven
Hydrol. Earth Syst. Sci., 22, 127–141, https://doi.org/10.5194/hess-22-127-2018, https://doi.org/10.5194/hess-22-127-2018, 2018
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The theme of the paper is exploration of the potential for seasonal flow forecasting for large lakes using a range of stochastic transfer function techniques with additional insights gained from simple analytical approximations. The methods were evaluated using records for two of the largest lakes in the world. The paper concludes with a discussion of the relevance of the results to operational flow forecasting systems for other large lakes.
Mary C. Ockenden, Wlodek Tych, Keith J. Beven, Adrian L. Collins, Robert Evans, Peter D. Falloon, Kirsty J. Forber, Kevin M. Hiscock, Michael J. Hollaway, Ron Kahana, Christopher J. A. Macleod, Martha L. Villamizar, Catherine Wearing, Paul J. A. Withers, Jian G. Zhou, Clare McW. H. Benskin, Sean Burke, Richard J. Cooper, Jim E. Freer, and Philip M. Haygarth
Hydrol. Earth Syst. Sci., 21, 6425–6444, https://doi.org/10.5194/hess-21-6425-2017, https://doi.org/10.5194/hess-21-6425-2017, 2017
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This paper describes simple models of phosphorus load which are identified for three catchments in the UK. The models use new hourly observations of phosphorus load, which capture the dynamics of phosphorus transfer in small catchments that are often missed by models with a longer time step. Unlike more complex, process-based models, very few parameters are required, leading to low parameter uncertainty. Interpretation of the dominant phosphorus transfer modes is made based solely on the data.
Katrien Van Eerdenbrugh, Stijn Van Hoey, Gemma Coxon, Jim Freer, and Niko E. C. Verhoest
Hydrol. Earth Syst. Sci., 21, 5315–5337, https://doi.org/10.5194/hess-21-5315-2017, https://doi.org/10.5194/hess-21-5315-2017, 2017
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Consistency in stage–discharge data is investigated using a methodology called Bidirectional Reach (BReach). Various measurement stations in the UK, New Zealand and Belgium are selected based on their historical ratings information and their characteristics related to data consistency. When applying a BReach analysis on them, the methodology provides results that appear consistent with the available knowledge and thus facilitates a reliable assessment of (in)consistency in stage–discharge data.
Rob Lamb, Willy Aspinall, Henry Odbert, and Thorsten Wagener
Nat. Hazards Earth Syst. Sci., 17, 1393–1409, https://doi.org/10.5194/nhess-17-1393-2017, https://doi.org/10.5194/nhess-17-1393-2017, 2017
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Scour (erosion) during floods can cause bridges to collapse. Modern design and maintenance mitigates the risk, so failures are rare. The residual risk is uncertain, but expert knowledge can help constrain it. We asked 19 experts about scour risk using methods designed to treat judgements alongside other scientific data. The findings identified knowledge gaps about scour processes and suggest wider uncertainty about scour risk than might be inferred from observation, models or experiments alone.
Diana Fuentes-Andino, Keith Beven, Sven Halldin, Chong-Yu Xu, José Eduardo Reynolds, and Giuliano Di Baldassarre
Hydrol. Earth Syst. Sci., 21, 3597–3618, https://doi.org/10.5194/hess-21-3597-2017, https://doi.org/10.5194/hess-21-3597-2017, 2017
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Reproduction of past floods requires information on discharge and flood extent, commonly unavailable or uncertain during extreme events. We explored the possibility of reproducing an extreme flood disaster using rainfall and post-event hydrometric information by combining a rainfall-runoff and hydraulic modelling tool within an uncertainty analysis framework. Considering the uncertainty in post–event data, it was possible to reasonably reproduce the extreme event.
M. J. Kirkby
SOIL, 2, 631–645, https://doi.org/10.5194/soil-2-631-2016, https://doi.org/10.5194/soil-2-631-2016, 2016
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The review paper surveys the state of the art with respect to water in the critical zone, taking a broad view that concentrates on the global range of natural soils, identifying some areas of currently active research.
Rémi Dupas, Jordy Salmon-Monviola, Keith J. Beven, Patrick Durand, Philip M. Haygarth, Michael J. Hollaway, and Chantal Gascuel-Odoux
Hydrol. Earth Syst. Sci., 20, 4819–4835, https://doi.org/10.5194/hess-20-4819-2016, https://doi.org/10.5194/hess-20-4819-2016, 2016
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We developed a parsimonious topography-based hydrologic model coupled with a soil biogeochemistry sub-model in order to improve understanding and prediction of soluble reactive phosphorus (SRP) transfer in agricultural headwater catchments. The modelling approach includes an analysis of the information contained in the calibration data and propagation of uncertainty in model predictions using a GLUE "limits of acceptability" framework.
Remko Nijzink, Christopher Hutton, Ilias Pechlivanidis, René Capell, Berit Arheimer, Jim Freer, Dawei Han, Thorsten Wagener, Kevin McGuire, Hubert Savenije, and Markus Hrachowitz
Hydrol. Earth Syst. Sci., 20, 4775–4799, https://doi.org/10.5194/hess-20-4775-2016, https://doi.org/10.5194/hess-20-4775-2016, 2016
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The core component of many hydrological systems, the moisture storage capacity available to vegetation, is typically treated as a calibration parameter in hydrological models and often considered to remain constant in time. In this paper we test the potential of a recently introduced method to robustly estimate catchment-scale root-zone storage capacities exclusively based on climate data to reproduce the temporal evolution of root-zone storage under change (deforestation).
C. E. M. Lloyd, J. E. Freer, P. J. Johnes, and A. L. Collins
Hydrol. Earth Syst. Sci., 20, 625–632, https://doi.org/10.5194/hess-20-625-2016, https://doi.org/10.5194/hess-20-625-2016, 2016
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This paper examines the current methodologies for quantifying storm behaviour through hysteresis analysis, and explores a new method. Each method is systematically tested and the impact on the results is examined. Recommendations are made regarding the most effective method of calculating a hysteresis index. This new method allows storm hysteresis behaviour to be directly compared between storms, parameters, and catchments, meaning it has wide application potential in water quality research.
K. J. Beven, S. Almeida, W. P. Aspinall, P. D. Bates, S. Blazkova, E. Borgomeo, K. Goda, J. C. Phillips, M. Simpson, P. J. Smith, D. B. Stephenson, T. Wagener, M. Watson, and K. L. Wilkins
Nat. Hazards Earth Syst. Sci. Discuss., https://doi.org/10.5194/nhess-2015-295, https://doi.org/10.5194/nhess-2015-295, 2016
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Uncertainties in natural hazard risk assessment are generally dominated by the sources arising from lack of knowledge or understanding of the processes involved. This is Part 2 of 2 papers reviewing these epistemic uncertainties and covers different areas of natural hazards including landslides and debris flows, dam safety, droughts, earthquakes, tsunamis, volcanic ash clouds and pyroclastic flows, and wind storms. It is based on the work of the UK CREDIBLE research consortium.
K. J. Beven, W. P. Aspinall, P. D. Bates, E. Borgomeo, K. Goda, J. W. Hall, T. Page, J. C. Phillips, J. T. Rougier, M. Simpson, D. B. Stephenson, P. J. Smith, T. Wagener, and M. Watson
Nat. Hazards Earth Syst. Sci. Discuss., https://doi.org/10.5194/nhessd-3-7333-2015, https://doi.org/10.5194/nhessd-3-7333-2015, 2015
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Uncertainties in natural hazard risk assessment are generally dominated by the sources arising from lack of knowledge or understanding of the processes involved. This is Part 1 of 2 papers reviewing these epistemic uncertainties that can be difficult to constrain, especially in terms of event or scenario probabilities. It is based on the work of the CREDIBLE research consortium on Risk and Uncertainty in Natural Hazards.
S. Ceola, B. Arheimer, E. Baratti, G. Blöschl, R. Capell, A. Castellarin, J. Freer, D. Han, M. Hrachowitz, Y. Hundecha, C. Hutton, G. Lindström, A. Montanari, R. Nijzink, J. Parajka, E. Toth, A. Viglione, and T. Wagener
Hydrol. Earth Syst. Sci., 19, 2101–2117, https://doi.org/10.5194/hess-19-2101-2015, https://doi.org/10.5194/hess-19-2101-2015, 2015
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We present the outcomes of a collaborative hydrological experiment undertaken by five different international research groups in a virtual laboratory. Moving from the definition of accurate protocols, a rainfall-runoff model was independently applied by the research groups, which then engaged in a comparative discussion. The results revealed that sharing protocols and running the experiment within a controlled environment is fundamental for ensuring experiment repeatability and reproducibility.
M. O. Johnson, M. Gloor, M. J. Kirkby, and J. Lloyd
Biogeosciences, 11, 6873–6894, https://doi.org/10.5194/bg-11-6873-2014, https://doi.org/10.5194/bg-11-6873-2014, 2014
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We present a soil evolution model which incorporates the major processes of pedogenesis: mineral weathering, leaching, erosion, bioturbation, nutrient cycling and organic carbon inputs. We compare the modelled soil properties with soil chronosequences from Hawaii and demonstrate that the model captures well the key components of soil development. The model also highlights the important role that vegetation plays in accelerating the weathering and the release of globally important nutrients.
F. N. Outram, C. E. M. Lloyd, J. Jonczyk, C. McW. H. Benskin, F. Grant, M. T. Perks, C. Deasy, S. P. Burke, A. L. Collins, J. Freer, P. M. Haygarth, K. M. Hiscock, P. J. Johnes, and A. L. Lovett
Hydrol. Earth Syst. Sci., 18, 3429–3448, https://doi.org/10.5194/hess-18-3429-2014, https://doi.org/10.5194/hess-18-3429-2014, 2014
I. K. Westerberg, L. Gong, K. J. Beven, J. Seibert, A. Semedo, C.-Y. Xu, and S. Halldin
Hydrol. Earth Syst. Sci., 18, 2993–3013, https://doi.org/10.5194/hess-18-2993-2014, https://doi.org/10.5194/hess-18-2993-2014, 2014
C. C. Sampson, T. J. Fewtrell, F. O'Loughlin, F. Pappenberger, P. B. Bates, J. E. Freer, and H. L. Cloke
Hydrol. Earth Syst. Sci., 18, 2305–2324, https://doi.org/10.5194/hess-18-2305-2014, https://doi.org/10.5194/hess-18-2305-2014, 2014
D. Leedal, A. H. Weerts, P. J. Smith, and K. J. Beven
Hydrol. Earth Syst. Sci., 17, 177–185, https://doi.org/10.5194/hess-17-177-2013, https://doi.org/10.5194/hess-17-177-2013, 2013
Related subject area
Subject: Catchment hydrology | Techniques and Approaches: Modelling approaches
Karst aquifer discharge response to rainfall interpreted as anomalous transport
HESS Opinions: Never train a Long Short-Term Memory (LSTM) network on a single basin
Large-sample hydrology – a few camels or a whole caravan?
Comment on “Are soils overrated in hydrology?” by Gao et al. (2023)
Multi-decadal fluctuations in root zone storage capacity through vegetation adaptation to hydro-climatic variability have minor effects on the hydrological response in the Neckar River basin, Germany
Projected future changes in the cryosphere and hydrology of a mountainous catchment in the upper Heihe River, China
On the importance of plant phenology in the evaporative process of a semi-arid woodland: could it be why satellite-based evaporation estimates in the miombo differ?
Regionalization of GR4J model parameters for river flow prediction in Paraná, Brazil
Evolution of river regimes in the Mekong River basin over 8 decades and the role of dams in recent hydrological extremes
Skill of seasonal flow forecasts at catchment scale: an assessment across South Korea
To what extent do flood-inducing storm events change future flood hazards?
When ancient numerical demons meet physics-informed machine learning: adjoint-based gradients for implicit differentiable modeling
Assessing the impact of climate change on high return levels of peak flows in Bavaria applying the CRCM5 large ensemble
Impacts of climate and land surface change on catchment evapotranspiration and runoff from 1951 to 2020 in Saxony, Germany
Quantifying and reducing flood forecast uncertainty by the CHUP-BMA method
Developing a tile drainage module for the Cold Regions Hydrological Model: lessons from a farm in southern Ontario, Canada
To bucket or not to bucket? Analyzing the performance and interpretability of hybrid hydrological models with dynamic parameterization
Widespread flooding dynamics under climate change: characterising floods using grid-based hydrological modelling and regional climate projections
HESS Opinions: The sword of Damocles of the impossible flood
Metamorphic testing of machine learning and conceptual hydrologic models
The influence of human activities on streamflow reductions during the megadrought in central Chile
Elevational control of isotopic composition and application in understanding hydrologic processes in the mid Merced River catchment, Sierra Nevada, California, USA
Enhancing long short-term memory (LSTM)-based streamflow prediction with a spatially distributed approach
Broadleaf afforestation impacts on terrestrial hydrology insignificant compared to climate change in Great Britain
Hybrid Hydrological Modeling for Large Alpine Basins: A Distributed Approach
Impacts of spatiotemporal resolutions of precipitation on flood event simulation based on multimodel structures – a case study over the Xiang River basin in China
A network approach for multiscale catchment classification using traits
Multi-model approach in a variable spatial framework for streamflow simulation
Advancing understanding of lake–watershed hydrology: a fully coupled numerical model illustrated by Qinghai Lake
Technical note: Testing the connection between hillslope-scale runoff fluctuations and streamflow hydrographs at the outlet of large river basins
Empirical stream thermal sensitivity cluster on the landscape according to geology and climate
Multi-scale soil moisture data and process-based modeling reveal the importance of lateral groundwater flow in a subarctic catchment
Deep learning for monthly rainfall–runoff modelling: a large-sample comparison with conceptual models across Australia
On optimization of calibrations of a distributed hydrological model with spatially distributed information on snow
Toward interpretable LSTM-based modeling of hydrological systems
Vegetation Response to Climatic Variability: Implications for Root Zone Storage and Streamflow Predictions
Flow intermittence prediction using a hybrid hydrological modelling approach: influence of observed intermittence data on the training of a random forest model
What controls the tail behaviour of flood series: rainfall or runoff generation?
Learning Landscape Features from Streamflow with Autoencoders
Seasonal prediction of end-of-dry-season watershed behavior in a highly interconnected alluvial watershed in northern California
Glaciers determine the sensitivity of hydrological processes to perturbed climate in a large mountainous basin on the Tibetan Plateau
Leveraging gauge networks and strategic discharge measurements to aid the development of continuous streamflow records
On the need for physical constraints in deep learning rainfall–runoff projections under climate change: a sensitivity analysis to warming and shifts in potential evapotranspiration
Evaluation of hydrological models on small mountainous catchments: impact of the meteorological forcings
Projecting sediment export from two highly glacierized alpine catchments under climate change: exploring non-parametric regression as an analysis tool
Simulation-Based Inference for Parameter Estimation of Complex Watershed Simulators
A framework for parameter estimation, sensitivity analysis, and uncertainty analysis for holistic hydrologic modeling using SWAT+
On understanding mountainous carbonate basins of the Mediterranean using parsimonious modeling solutions
Comparing quantile regression forest and mixture density long short-term memory models for probabilistic post-processing of satellite precipitation-driven streamflow simulations
Recent ground thermo-hydrological changes in a southern Tibetan endorheic catchment and implications for lake level changes
Dan Elhanati, Nadine Goeppert, and Brian Berkowitz
Hydrol. Earth Syst. Sci., 28, 4239–4249, https://doi.org/10.5194/hess-28-4239-2024, https://doi.org/10.5194/hess-28-4239-2024, 2024
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A continuous time random walk framework was developed to allow modeling of a karst aquifer discharge response to measured rainfall. The application of the numerical model yielded robust fits between modeled and measured discharge values, especially for the distinctive long tails found during recession times. The findings shed light on the interplay of slow and fast flow in the karst system and establish the application of the model for simulating flow and transport in such systems.
Frederik Kratzert, Martin Gauch, Daniel Klotz, and Grey Nearing
Hydrol. Earth Syst. Sci., 28, 4187–4201, https://doi.org/10.5194/hess-28-4187-2024, https://doi.org/10.5194/hess-28-4187-2024, 2024
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Recently, a special type of neural-network architecture became increasingly popular in hydrology literature. However, in most applications, this model was applied as a one-to-one replacement for hydrology models without adapting or rethinking the experimental setup. In this opinion paper, we show how this is almost always a bad decision and how using these kinds of models requires the use of large-sample hydrology data sets.
Franziska Clerc-Schwarzenbach, Giovanni Selleri, Mattia Neri, Elena Toth, Ilja van Meerveld, and Jan Seibert
Hydrol. Earth Syst. Sci., 28, 4219–4237, https://doi.org/10.5194/hess-28-4219-2024, https://doi.org/10.5194/hess-28-4219-2024, 2024
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We show that the differences between the forcing data included in three CAMELS datasets (US, BR, GB) and the forcing data included for the same catchments in the Caravan dataset affect model calibration considerably. The model performance dropped when the data from the Caravan dataset were used instead of the original data. Most of the model performance drop could be attributed to the differences in precipitation data. However, differences were largest for the potential evapotranspiration data.
Ying Zhao, Mehdi Rahmati, Harry Vereecken, and Dani Or
Hydrol. Earth Syst. Sci., 28, 4059–4063, https://doi.org/10.5194/hess-28-4059-2024, https://doi.org/10.5194/hess-28-4059-2024, 2024
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Gao et al. (2023) question the importance of soil in hydrology, sparking debate. We acknowledge some valid points but critique their broad, unsubstantiated views on soil's role. Our response highlights three key areas: (1) the false divide between ecosystem-centric and soil-centric approaches, (2) the vital yet varied impact of soil properties, and (3) the call for a scale-aware framework. We aim to unify these perspectives, enhancing hydrology's comprehensive understanding.
Siyuan Wang, Markus Hrachowitz, and Gerrit Schoups
Hydrol. Earth Syst. Sci., 28, 4011–4033, https://doi.org/10.5194/hess-28-4011-2024, https://doi.org/10.5194/hess-28-4011-2024, 2024
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Root zone storage capacity (Sumax) changes significantly over multiple decades, reflecting vegetation adaptation to climatic variability. However, this temporal evolution of Sumax cannot explain long-term fluctuations in the partitioning of water fluxes as expressed by deviations ΔIE from the parametric Budyko curve over time with different climatic conditions, and it does not have any significant effects on shorter-term hydrological response characteristics of the upper Neckar catchment.
Zehua Chang, Hongkai Gao, Leilei Yong, Kang Wang, Rensheng Chen, Chuntan Han, Otgonbayar Demberel, Batsuren Dorjsuren, Shugui Hou, and Zheng Duan
Hydrol. Earth Syst. Sci., 28, 3897–3917, https://doi.org/10.5194/hess-28-3897-2024, https://doi.org/10.5194/hess-28-3897-2024, 2024
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An integrated cryospheric–hydrologic model, FLEX-Cryo, was developed that considers glaciers, snow cover, and frozen soil and their dynamic impacts on hydrology. We utilized it to simulate future changes in cryosphere and hydrology in the Hulu catchment. Our projections showed the two glaciers will melt completely around 2050, snow cover will reduce, and permafrost will degrade. For hydrology, runoff will decrease after the glacier has melted, and permafrost degradation will increase baseflow.
Henry M. Zimba, Miriam Coenders-Gerrits, Kawawa E. Banda, Petra Hulsman, Nick van de Giesen, Imasiku A. Nyambe, and Hubert H. G. Savenije
Hydrol. Earth Syst. Sci., 28, 3633–3663, https://doi.org/10.5194/hess-28-3633-2024, https://doi.org/10.5194/hess-28-3633-2024, 2024
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The fall and flushing of new leaves in the miombo woodlands co-occur in the dry season before the commencement of seasonal rainfall. The miombo species are also said to have access to soil moisture in deep soils, including groundwater in the dry season. Satellite-based evaporation estimates, temporal trends, and magnitudes differ the most in the dry season, most likely due to inadequate understanding and representation of the highlighted miombo species attributes in simulations.
Louise Akemi Kuana, Arlan Scortegagna Almeida, Emílio Graciliano Ferreira Mercuri, and Steffen Manfred Noe
Hydrol. Earth Syst. Sci., 28, 3367–3390, https://doi.org/10.5194/hess-28-3367-2024, https://doi.org/10.5194/hess-28-3367-2024, 2024
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The authors compared regionalization methods for river flow prediction in 126 catchments from the south of Brazil, a region with humid subtropical and hot temperate climate. The regionalization method based on physiographic–climatic similarity had the best performance for predicting daily and Q95 reference flow. We showed that basins without flow monitoring can have a good approximation of streamflow using machine learning and physiographic–climatic information as inputs.
Huy Dang and Yadu Pokhrel
Hydrol. Earth Syst. Sci., 28, 3347–3365, https://doi.org/10.5194/hess-28-3347-2024, https://doi.org/10.5194/hess-28-3347-2024, 2024
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By examining basin-wide simulations of a river regime over 83 years with and without dams, we present evidence that climate variation was a key driver of hydrologic variabilities in the Mekong River basin (MRB) over the long term; however, dams have largely altered the seasonality of the Mekong’s flow regime and annual flooding patterns in major downstream areas in recent years. These findings could help us rethink the planning of future dams and water resource management in the MRB.
Yongshin Lee, Francesca Pianosi, Andres Peñuela, and Miguel Angel Rico-Ramirez
Hydrol. Earth Syst. Sci., 28, 3261–3279, https://doi.org/10.5194/hess-28-3261-2024, https://doi.org/10.5194/hess-28-3261-2024, 2024
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Following recent advancements in weather prediction technology, we explored how seasonal weather forecasts (1 or more months ahead) could benefit practical water management in South Korea. Our findings highlight that using seasonal weather forecasts for predicting flow patterns 1 to 3 months ahead is effective, especially during dry years. This suggest that seasonal weather forecasts can be helpful in improving the management of water resources.
Mariam Khanam, Giulia Sofia, and Emmanouil N. Anagnostou
Hydrol. Earth Syst. Sci., 28, 3161–3190, https://doi.org/10.5194/hess-28-3161-2024, https://doi.org/10.5194/hess-28-3161-2024, 2024
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Flooding worsens due to climate change, with river dynamics being a key in local flood control. Predicting post-storm geomorphic changes is challenging. Using self-organizing maps and machine learning, this study forecasts post-storm alterations in stage–discharge relationships across 3101 US stream gages. The provided framework can aid in updating hazard assessments by identifying rivers prone to change, integrating channel adjustments into flood hazard assessment.
Yalan Song, Wouter J. M. Knoben, Martyn P. Clark, Dapeng Feng, Kathryn Lawson, Kamlesh Sawadekar, and Chaopeng Shen
Hydrol. Earth Syst. Sci., 28, 3051–3077, https://doi.org/10.5194/hess-28-3051-2024, https://doi.org/10.5194/hess-28-3051-2024, 2024
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Differentiable models (DMs) integrate neural networks and physical equations for accuracy, interpretability, and knowledge discovery. We developed an adjoint-based DM for ordinary differential equations (ODEs) for hydrological modeling, reducing distorted fluxes and physical parameters from errors in models that use explicit and operation-splitting schemes. With a better numerical scheme and improved structure, the adjoint-based DM matches or surpasses long short-term memory (LSTM) performance.
Florian Willkofer, Raul R. Wood, and Ralf Ludwig
Hydrol. Earth Syst. Sci., 28, 2969–2989, https://doi.org/10.5194/hess-28-2969-2024, https://doi.org/10.5194/hess-28-2969-2024, 2024
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Severe flood events pose a threat to riverine areas, yet robust estimates of the dynamics of these events in the future due to climate change are rarely available. Hence, this study uses data from a regional climate model, SMILE, to drive a high-resolution hydrological model for 98 catchments of hydrological Bavaria and exploits the large database to derive robust values for the 100-year flood events. Results indicate an increase in frequency and intensity for most catchments in the future.
Maik Renner and Corina Hauffe
Hydrol. Earth Syst. Sci., 28, 2849–2869, https://doi.org/10.5194/hess-28-2849-2024, https://doi.org/10.5194/hess-28-2849-2024, 2024
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Climate and land surface changes influence the partitioning of water balance components decisively. Their impact is quantified for 71 catchments in Saxony. Germany. Distinct signatures in the joint water and energy budgets are found: (i) past forest dieback caused a decrease in and subsequent recovery of evapotranspiration in the affected regions, and (ii) the recent shift towards higher aridity imposed a large decline in runoff that has not been seen in the observation records before.
Zhen Cui, Shenglian Guo, Hua Chen, Dedi Liu, Yanlai Zhou, and Chong-Yu Xu
Hydrol. Earth Syst. Sci., 28, 2809–2829, https://doi.org/10.5194/hess-28-2809-2024, https://doi.org/10.5194/hess-28-2809-2024, 2024
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Ensemble forecasting facilitates reliable flood forecasting and warning. This study couples the copula-based hydrologic uncertainty processor (CHUP) with Bayesian model averaging (BMA) and proposes the novel CHUP-BMA method of reducing inflow forecasting uncertainty of the Three Gorges Reservoir. The CHUP-BMA avoids the normal distribution assumption in the HUP-BMA and considers the constraint of initial conditions, which can improve the deterministic and probabilistic forecast performance.
Mazda Kompanizare, Diogo Costa, Merrin L. Macrae, John W. Pomeroy, and Richard M. Petrone
Hydrol. Earth Syst. Sci., 28, 2785–2807, https://doi.org/10.5194/hess-28-2785-2024, https://doi.org/10.5194/hess-28-2785-2024, 2024
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A new agricultural tile drainage module was developed in the Cold Region Hydrological Model platform. Tile flow and water levels are simulated by considering the effect of capillary fringe thickness, drainable water and seasonal regional groundwater dynamics. The model was applied to a small well-instrumented farm in southern Ontario, Canada, where there are concerns about the impacts of agricultural drainage into Lake Erie.
Eduardo Acuña Espinoza, Ralf Loritz, Manuel Álvarez Chaves, Nicole Bäuerle, and Uwe Ehret
Hydrol. Earth Syst. Sci., 28, 2705–2719, https://doi.org/10.5194/hess-28-2705-2024, https://doi.org/10.5194/hess-28-2705-2024, 2024
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Hydrological hybrid models promise to merge the performance of deep learning methods with the interpretability of process-based models. One hybrid approach is the dynamic parameterization of conceptual models using long short-term memory (LSTM) networks. We explored this method to evaluate the effect of the flexibility given by LSTMs on the process-based part.
Adam Griffin, Alison L. Kay, Paul Sayers, Victoria Bell, Elizabeth Stewart, and Sam Carr
Hydrol. Earth Syst. Sci., 28, 2635–2650, https://doi.org/10.5194/hess-28-2635-2024, https://doi.org/10.5194/hess-28-2635-2024, 2024
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Widespread flooding is a major problem in the UK and is greatly affected by climate change and land-use change. To look at how widespread flooding changes in the future, climate model data (UKCP18) were used with a hydrological model (Grid-to-Grid) across the UK, and 14 400 events were identified between two time slices: 1980–2010 and 2050–2080. There was a strong increase in the number of winter events in the future time slice and in the peak return periods.
Alberto Montanari, Bruno Merz, and Günter Blöschl
Hydrol. Earth Syst. Sci., 28, 2603–2615, https://doi.org/10.5194/hess-28-2603-2024, https://doi.org/10.5194/hess-28-2603-2024, 2024
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Floods often take communities by surprise, as they are often considered virtually
impossibleyet are an ever-present threat similar to the sword suspended over the head of Damocles in the classical Greek anecdote. We discuss four reasons why extremely large floods carry a risk that is often larger than expected. We provide suggestions for managing the risk of megafloods by calling for a creative exploration of hazard scenarios and communicating the unknown corners of the reality of floods.
Peter Reichert, Kai Ma, Marvin Höge, Fabrizio Fenicia, Marco Baity-Jesi, Dapeng Feng, and Chaopeng Shen
Hydrol. Earth Syst. Sci., 28, 2505–2529, https://doi.org/10.5194/hess-28-2505-2024, https://doi.org/10.5194/hess-28-2505-2024, 2024
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We compared the predicted change in catchment outlet discharge to precipitation and temperature change for conceptual and machine learning hydrological models. We found that machine learning models, despite providing excellent fit and prediction capabilities, can be unreliable regarding the prediction of the effect of temperature change for low-elevation catchments. This indicates the need for caution when applying them for the prediction of the effect of climate change.
Nicolás Álamos, Camila Alvarez-Garreton, Ariel Muñoz, and Álvaro González-Reyes
Hydrol. Earth Syst. Sci., 28, 2483–2503, https://doi.org/10.5194/hess-28-2483-2024, https://doi.org/10.5194/hess-28-2483-2024, 2024
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In this study, we assess the effects of climate and water use on streamflow reductions and drought intensification during the last 3 decades in central Chile. We address this by contrasting streamflow observations with near-natural streamflow simulations. We conclude that while the lack of precipitation dominates streamflow reductions in the megadrought, water uses have not diminished during this time, causing a worsening of the hydrological drought conditions and maladaptation conditions.
Fengjing Liu, Martha H. Conklin, and Glenn D. Shaw
Hydrol. Earth Syst. Sci., 28, 2239–2258, https://doi.org/10.5194/hess-28-2239-2024, https://doi.org/10.5194/hess-28-2239-2024, 2024
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Mountain snowpack has been declining and more precipitation falls as rain than snow. Using stable isotopes, we found flows and flow duration in Yosemite Creek are most sensitive to climate warming due to strong evaporation of waterfalls, potentially lengthening the dry-up period of waterfalls in summer and negatively affecting tourism. Groundwater recharge in Yosemite Valley is primarily from the upper snow–rain transition (2000–2500 m) and very vulnerable to a reduction in the snow–rain ratio.
Qiutong Yu, Bryan A. Tolson, Hongren Shen, Ming Han, Juliane Mai, and Jimmy Lin
Hydrol. Earth Syst. Sci., 28, 2107–2122, https://doi.org/10.5194/hess-28-2107-2024, https://doi.org/10.5194/hess-28-2107-2024, 2024
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It is challenging to incorporate input variables' spatial distribution information when implementing long short-term memory (LSTM) models for streamflow prediction. This work presents a novel hybrid modelling approach to predict streamflow while accounting for spatial variability. We evaluated the performance against lumped LSTM predictions in 224 basins across the Great Lakes region in North America. This approach shows promise for predicting streamflow in large, ungauged basin.
Marcus Buechel, Louise Slater, and Simon Dadson
Hydrol. Earth Syst. Sci., 28, 2081–2105, https://doi.org/10.5194/hess-28-2081-2024, https://doi.org/10.5194/hess-28-2081-2024, 2024
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Afforestation has been proposed internationally, but the hydrological implications of such large increases in the spatial extent of woodland are not fully understood. In this study, we use a land surface model to simulate hydrology across Great Britain with realistic afforestation scenarios and potential climate changes. Countrywide afforestation minimally influences hydrology, when compared to climate change, and reduces low streamflow whilst not lowering the highest flows.
Bu Li, Ting Sun, Fuqiang Tian, Mahmut Tudaji, Li Qin, and Guangheng Ni
Hydrol. Earth Syst. Sci. Discuss., https://doi.org/10.5194/hess-2024-54, https://doi.org/10.5194/hess-2024-54, 2024
Revised manuscript accepted for HESS
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This paper developed hybrid distributed hydrological models by employing a distributed model as the backbone, and utilizing deep learning to parameterize and replace internal modules. The main contribution is to provide a high-performance tool enriched with explicit hydrological knowledge for hydrological prediction and improves understanding about the hydrological sensitivities to climate change in large alpine basins.
Qian Zhu, Xiaodong Qin, Dongyang Zhou, Tiantian Yang, and Xinyi Song
Hydrol. Earth Syst. Sci., 28, 1665–1686, https://doi.org/10.5194/hess-28-1665-2024, https://doi.org/10.5194/hess-28-1665-2024, 2024
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Input data, model and calibration strategy can affect the accuracy of flood event simulation and prediction. Satellite-based precipitation with different spatiotemporal resolutions is an important input source. Data-driven models are sometimes proven to be more accurate than hydrological models. Event-based calibration and conventional strategy are two options adopted for flood simulation. This study targets the three concerns for accurate flood event simulation and prediction.
Fabio Ciulla and Charuleka Varadharajan
Hydrol. Earth Syst. Sci., 28, 1617–1651, https://doi.org/10.5194/hess-28-1617-2024, https://doi.org/10.5194/hess-28-1617-2024, 2024
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We present a new method based on network science for unsupervised classification of large datasets and apply it to classify 9067 US catchments and 274 biophysical traits at multiple scales. We find that our trait-based approach produces catchment classes with distinct streamflow behavior and that spatial patterns emerge amongst pristine and human-impacted catchments. This method can be widely used beyond hydrology to identify patterns, reduce trait redundancy, and select representative sites.
Cyril Thébault, Charles Perrin, Vazken Andréassian, Guillaume Thirel, Sébastien Legrand, and Olivier Delaigue
Hydrol. Earth Syst. Sci., 28, 1539–1566, https://doi.org/10.5194/hess-28-1539-2024, https://doi.org/10.5194/hess-28-1539-2024, 2024
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Streamflow forecasting is useful for many applications, ranging from population safety (e.g. floods) to water resource management (e.g. agriculture or hydropower). To this end, hydrological models must be optimized. However, a model is inherently wrong. This study aims to analyse the contribution of a multi-model approach within a variable spatial framework to improve streamflow simulations. The underlying idea is to take advantage of the strength of each modelling framework tested.
Lele Shu, Xiaodong Li, Yan Chang, Xianhong Meng, Hao Chen, Yuan Qi, Hongwei Wang, Zhaoguo Li, and Shihua Lyu
Hydrol. Earth Syst. Sci., 28, 1477–1491, https://doi.org/10.5194/hess-28-1477-2024, https://doi.org/10.5194/hess-28-1477-2024, 2024
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We developed a new model to better understand how water moves in a lake basin. Our model improves upon previous methods by accurately capturing the complexity of water movement, both on the surface and subsurface. Our model, tested using data from China's Qinghai Lake, accurately replicates complex water movements and identifies contributing factors of the lake's water balance. The findings provide a robust tool for predicting hydrological processes, aiding water resource planning.
Ricardo Mantilla, Morgan Fonley, and Nicolás Velásquez
Hydrol. Earth Syst. Sci., 28, 1373–1382, https://doi.org/10.5194/hess-28-1373-2024, https://doi.org/10.5194/hess-28-1373-2024, 2024
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Hydrologists strive to “Be right for the right reasons” when modeling the hydrologic cycle; however, the datasets available to validate hydrological models are sparse, and in many cases, they comprise streamflow observations at the outlets of large catchments. In this work, we show that matching streamflow observations at the outlet of a large basin is not a reliable indicator of a correct description of the small-scale runoff processes.
Lillian M. McGill, E. Ashley Steel, and Aimee H. Fullerton
Hydrol. Earth Syst. Sci., 28, 1351–1371, https://doi.org/10.5194/hess-28-1351-2024, https://doi.org/10.5194/hess-28-1351-2024, 2024
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This study examines the relationship between air and river temperatures in Washington's Snoqualmie and Wenatchee basins. We used classification and regression approaches to show that the sensitivity of river temperature to air temperature is variable across basins and controlled largely by geology and snowmelt. Findings can be used to inform strategies for river basin restoration and conservation, such as identifying climate-insensitive areas of the basin that should be preserved and protected.
Jari-Pekka Nousu, Kersti Leppä, Hannu Marttila, Pertti Ala-aho, Giulia Mazzotti, Terhikki Manninen, Mika Korkiakoski, Mika Aurela, Annalea Lohila, and Samuli Launiainen
Hydrol. Earth Syst. Sci. Discuss., https://doi.org/10.5194/hess-2024-81, https://doi.org/10.5194/hess-2024-81, 2024
Revised manuscript accepted for HESS
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We used hydrological models, field measurements and satellite-based data to study the soil moisture dynamics in a subarctic catchment. The role of groundwater was studied with different ways to model the groundwater dynamics, and via comparisons to the observational data. The choice of groundwater model was shown to have a strong impact, and representation of lateral flow was important to capture wet soil conditions. Our results provide insights for ecohydrological studies in boreal regions.
Stephanie R. Clark, Julien Lerat, Jean-Michel Perraud, and Peter Fitch
Hydrol. Earth Syst. Sci., 28, 1191–1213, https://doi.org/10.5194/hess-28-1191-2024, https://doi.org/10.5194/hess-28-1191-2024, 2024
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To determine if deep learning models are in general a viable alternative to traditional hydrologic modelling techniques in Australian catchments, a comparison of river–runoff predictions is made between traditional conceptual models and deep learning models in almost 500 catchments spread over the continent. It is found that the deep learning models match or outperform the traditional models in over two-thirds of the river catchments, indicating feasibility in a wide variety of conditions.
Dipti Tiwari, Mélanie Trudel, and Robert Leconte
Hydrol. Earth Syst. Sci., 28, 1127–1146, https://doi.org/10.5194/hess-28-1127-2024, https://doi.org/10.5194/hess-28-1127-2024, 2024
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Calibrating hydrological models with multi-objective functions enhances model robustness. By using spatially distributed snow information in the calibration, the model performance can be enhanced without compromising the outputs. In this study the HYDROTEL model was calibrated in seven different experiments, incorporating the SPAEF (spatial efficiency) metric alongside Nash–Sutcliffe efficiency (NSE) and root-mean-square error (RMSE), with the aim of identifying the optimal calibration strategy.
Luis Andres De la Fuente, Mohammad Reza Ehsani, Hoshin Vijai Gupta, and Laura Elizabeth Condon
Hydrol. Earth Syst. Sci., 28, 945–971, https://doi.org/10.5194/hess-28-945-2024, https://doi.org/10.5194/hess-28-945-2024, 2024
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Long short-term memory (LSTM) is a widely used machine-learning model in hydrology, but it is difficult to extract knowledge from it. We propose HydroLSTM, which represents processes like a hydrological reservoir. Models based on HydroLSTM perform similarly to LSTM while requiring fewer cell states. The learned parameters are informative about the dominant hydrology of a catchment. Our results show how parsimony and hydrological knowledge extraction can be achieved by using the new structure.
Nienke Tessa Tempel, Laurene Bouaziz, Riccardo Taormina, Ellis van Noppen, Jasper Stam, Eric Sprokkereef, and Markus Hrachowitz
EGUsphere, https://doi.org/10.5194/egusphere-2024-115, https://doi.org/10.5194/egusphere-2024-115, 2024
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This study explores the impact of climatic variability on root zone water storage capacities thus on hydrological predictions. Analysing data from 286 areas in Europe and the US, we found that despite some variations in root zone storage capacity due to changing climatic conditions over multiple decades, these changes are generally minor and have a limited effect on water storage and river flow predictions.
Louise Mimeau, Annika Künne, Flora Branger, Sven Kralisch, Alexandre Devers, and Jean-Philippe Vidal
Hydrol. Earth Syst. Sci., 28, 851–871, https://doi.org/10.5194/hess-28-851-2024, https://doi.org/10.5194/hess-28-851-2024, 2024
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Modelling flow intermittence is essential for predicting the future evolution of drying in river networks and better understanding the ecological and socio-economic impacts. However, modelling flow intermittence is challenging, and observed data on temporary rivers are scarce. This study presents a new modelling approach for predicting flow intermittence in river networks and shows that combining different sources of observed data reduces the model uncertainty.
Elena Macdonald, Bruno Merz, Björn Guse, Viet Dung Nguyen, Xiaoxiang Guan, and Sergiy Vorogushyn
Hydrol. Earth Syst. Sci., 28, 833–850, https://doi.org/10.5194/hess-28-833-2024, https://doi.org/10.5194/hess-28-833-2024, 2024
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In some rivers, the occurrence of extreme flood events is more likely than in other rivers – they have heavy-tailed distributions. We find that threshold processes in the runoff generation lead to such a relatively high occurrence probability of extremes. Further, we find that beyond a certain return period, i.e. for rare events, rainfall is often the dominant control compared to runoff generation. Our results can help to improve the estimation of the occurrence probability of extreme floods.
Alberto Bassi, Marvin Höge, Antonietta Mira, Fabrizio Fenicia, and Carlo Albert
Hydrol. Earth Syst. Sci. Discuss., https://doi.org/10.5194/hess-2024-47, https://doi.org/10.5194/hess-2024-47, 2024
Revised manuscript accepted for HESS
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The goal is to remove the impact of meteorological drivers in order to uncover the unique landscape fingerprints of a catchment from streamflow data. Our results reveal an optimal two-feature summary for most catchments, with a third feature needed for challenging cases, associated with aridity and intermittent flow. Baseflow index, aridity, and soil/vegetation attributes strongly correlate with learned features, indicating their importance for streamflow prediction.
Claire Kouba and Thomas Harter
Hydrol. Earth Syst. Sci., 28, 691–718, https://doi.org/10.5194/hess-28-691-2024, https://doi.org/10.5194/hess-28-691-2024, 2024
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In some watersheds, the severity of the dry season has a large impact on aquatic ecosystems. In this study, we design a way to predict, 5–6 months in advance, how severe the dry season will be in a rural watershed in northern California. This early warning can support seasonal adaptive management. To predict these two values, we assess data about snow, rain, groundwater, and river flows. We find that maximum snowpack and total wet season rainfall best predict dry season severity.
Yi Nan and Fuqiang Tian
Hydrol. Earth Syst. Sci., 28, 669–689, https://doi.org/10.5194/hess-28-669-2024, https://doi.org/10.5194/hess-28-669-2024, 2024
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This paper utilized a tracer-aided model validated by multiple datasets in a large mountainous basin on the Tibetan Plateau to analyze hydrological sensitivity to climate change. The spatial pattern of the local hydrological sensitivities and the influence factors were analyzed in particular. The main finding of this paper is that the local hydrological sensitivity in mountainous basins is determined by the relationship between the glacier area ratio and the mean annual precipitation.
Michael J. Vlah, Matthew R. V. Ross, Spencer Rhea, and Emily S. Bernhardt
Hydrol. Earth Syst. Sci., 28, 545–573, https://doi.org/10.5194/hess-28-545-2024, https://doi.org/10.5194/hess-28-545-2024, 2024
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Virtual stream gauging enables continuous streamflow estimation where a gauge might be difficult or impractical to install. We reconstructed flow at 27 gauges of the National Ecological Observatory Network (NEON), informing ~199 site-months of missing data in the official record and improving that accuracy of official estimates at 11 sites. This study shows that machine learning, but also routine regression methods, can be used to supplement existing gauge networks and reduce monitoring costs.
Sungwook Wi and Scott Steinschneider
Hydrol. Earth Syst. Sci., 28, 479–503, https://doi.org/10.5194/hess-28-479-2024, https://doi.org/10.5194/hess-28-479-2024, 2024
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We investigate whether deep learning (DL) models can produce physically plausible streamflow projections under climate change. We address this question by focusing on modeled responses to increases in temperature and potential evapotranspiration and by employing three DL and three process-based hydrological models. The results suggest that physical constraints regarding model architecture and input are necessary to promote the physical realism of DL hydrological projections under climate change.
Guillaume Evin, Matthieu Le Lay, Catherine Fouchier, David Penot, Francois Colleoni, Alexandre Mas, Pierre-André Garambois, and Olivier Laurantin
Hydrol. Earth Syst. Sci., 28, 261–281, https://doi.org/10.5194/hess-28-261-2024, https://doi.org/10.5194/hess-28-261-2024, 2024
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Hydrological modelling of mountainous catchments is challenging for many reasons, the main one being the temporal and spatial representation of precipitation forcings. This study presents an evaluation of the hydrological modelling of 55 small mountainous catchments of the northern French Alps, focusing on the influence of the type of precipitation reanalyses used as inputs. These evaluations emphasize the added value of radar measurements, in particular for the reproduction of flood events.
Lena Katharina Schmidt, Till Francke, Peter Martin Grosse, and Axel Bronstert
Hydrol. Earth Syst. Sci., 28, 139–161, https://doi.org/10.5194/hess-28-139-2024, https://doi.org/10.5194/hess-28-139-2024, 2024
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How suspended sediment export from glacierized high-alpine areas responds to future climate change is hardly assessable as many interacting processes are involved, and appropriate physical models are lacking. We present the first study, to our knowledge, exploring machine learning to project sediment export until 2100 in two high-alpine catchments. We find that uncertainties due to methodological limitations are small until 2070. Negative trends imply that peak sediment may have already passed.
Robert Hull, Elena Leonarduzzi, Luis De La Fuente, Hoang Viet Tran, Andrew Bennett, Peter Melchior, Reed M. Maxwell, and Laura E. Condon
Hydrol. Earth Syst. Sci. Discuss., https://doi.org/10.5194/hess-2023-264, https://doi.org/10.5194/hess-2023-264, 2024
Revised manuscript accepted for HESS
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Large-scale hydrologic a needed tool to explore complex watershed processes and how they may evolve under a changing climate. However, calibrating them can be difficult because they are costly to run and have many unknown parameters. We implement a state-of-the-art approach to model calibration with a set of experiments in the Upper Colorado River Basin.
Salam A. Abbas, Ryan T. Bailey, Jeremy T. White, Jeffrey G. Arnold, Michael J. White, Natalja Čerkasova, and Jungang Gao
Hydrol. Earth Syst. Sci., 28, 21–48, https://doi.org/10.5194/hess-28-21-2024, https://doi.org/10.5194/hess-28-21-2024, 2024
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Research highlights.
1. Implemented groundwater module (gwflow) into SWAT+ for four watersheds with different unique hydrologic features across the United States.
2. Presented methods for sensitivity analysis, uncertainty analysis and parameter estimation for coupled models.
3. Sensitivity analysis for streamflow and groundwater head conducted using Morris method.
4. Uncertainty analysis and parameter estimation performed using an iterative ensemble smoother within the PEST framework.
Shima Azimi, Christian Massari, Giuseppe Formetta, Silvia Barbetta, Alberto Tazioli, Davide Fronzi, Sara Modanesi, Angelica Tarpanelli, and Riccardo Rigon
Hydrol. Earth Syst. Sci., 27, 4485–4503, https://doi.org/10.5194/hess-27-4485-2023, https://doi.org/10.5194/hess-27-4485-2023, 2023
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We analyzed the water budget of nested karst catchments using simple methods and modeling. By utilizing the available data on precipitation and discharge, we were able to determine the response lag-time by adopting new techniques. Additionally, we modeled snow cover dynamics and evapotranspiration with the use of Earth observations, providing a concise overview of the water budget for the basin and its subbasins. We have made the data, models, and workflows accessible for further study.
Yuhang Zhang, Aizhong Ye, Bita Analui, Phu Nguyen, Soroosh Sorooshian, Kuolin Hsu, and Yuxuan Wang
Hydrol. Earth Syst. Sci., 27, 4529–4550, https://doi.org/10.5194/hess-27-4529-2023, https://doi.org/10.5194/hess-27-4529-2023, 2023
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Our study shows that while the quantile regression forest (QRF) and countable mixtures of asymmetric Laplacians long short-term memory (CMAL-LSTM) models demonstrate similar proficiency in multipoint probabilistic predictions, QRF excels in smaller watersheds and CMAL-LSTM in larger ones. CMAL-LSTM performs better in single-point deterministic predictions, whereas QRF model is more efficient overall.
Léo C. P. Martin, Sebastian Westermann, Michele Magni, Fanny Brun, Joel Fiddes, Yanbin Lei, Philip Kraaijenbrink, Tamara Mathys, Moritz Langer, Simon Allen, and Walter W. Immerzeel
Hydrol. Earth Syst. Sci., 27, 4409–4436, https://doi.org/10.5194/hess-27-4409-2023, https://doi.org/10.5194/hess-27-4409-2023, 2023
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Across the Tibetan Plateau, many large lakes have been changing level during the last decades as a response to climate change. In high-mountain environments, water fluxes from the land to the lakes are linked to the ground temperature of the land and to the energy fluxes between the ground and the atmosphere, which are modified by climate change. With a numerical model, we test how these water and energy fluxes have changed over the last decades and how they influence the lake level variations.
Cited articles
Adriance, A., Pantoja, M., and Lupo, C.: September. Acceleration of Hydrology
Simulations Using DHSVM for Multi-thousand Runs and Uncertainty Assessment,
in: Latin American High Performance Computing Conference, Springer, Cham, 179–193, 2018.
Ambroise, B., Beven, K. J., and Freer, J.: Towards a generalisation of the
TOPMODEL concepts: topographic indices of hydrological similarity, Water Resour. Res., 32, 2135–2145, 1996a.
Ambroise, B., Freer, J., and Beven, K. J.: Application of a generalised TOPMODEL to the small Ringelbach catchment, Vosges, France, Water Resour. Res., 32, 2147–2159, 1996b.
Aryal, S. K., O'Loughlin, E. M., and Mein, R. G.: A similarity approach to
determine response times to steady-state saturation in landscapes, Adv. Water Res., 28, 99–115, 2005.
Band, L. E., Patterson, P., Nemani, R., and Running, S. W.: Forest ecosystem
processes at the watershed scale: incorporating hillslope
hydrology, Agr. For. Meteorol., 63, 93–126, 1993.
Barling, R. D., Moore, I. D., and Grayson, R. B.: A quasi-dynamic wetness
index for characterizing the spatial distribution of zones of surface
saturation and soil water contents, Water Resour. Res., 30, 1029–1044,
https://doi.org/10.1029/93WR03346, 1994.
Bergstrom, A., Jencso, K., and McGlynn, B.: Spatiotemporal processes that
contribute to hydrologic exchange between hillslopes, valley bottoms, and
streams, Water Resour. Res., 52, 4628–4645, https://doi.org/10.1002/2015WR017972, 2016.
Berne, A., Uijlenhoet, R., and Troch, P. A.: Similarity analysis of
subsurface flow response of hillslopes with complex geometry, Water Resour. Res., 41, 1–10, https://doi.org/10.1029/2004WR003629, 2005.
Best, M. J., Pryor, M., Clark, D. B., Rooney, G. G., Essery, R. L. H., Ménard, C. B., Edwards, J. M., Hendry, M. A., Porson, A., Gedney, N., Mercado, L. M., Sitch, S., Blyth, E., Boucher, O., Cox, P. M., Grimmond, C. S. B., and Harding, R. J.: The Joint UK Land Environment Simulator (JULES), model description – Part 1: Energy and water fluxes, Geosci. Model Dev., 4, 677–699, https://doi.org/10.5194/gmd-4-677-2011, 2011.
Betson, R. P.: What is watershed runoff, J. Geophys. Res., 69, 1541–1551, 1964.
Beven, K. J.: The hydrological response of headwater and sideslope areas,
Hydrol. Sci. B., 23, 419–437, 1978.
Beven, K. J.: On the generalised kinematic routing method, Water Resour. Res., 15, 1238–1242, 1979.
Beven, K. J.: On Subsurface Stormflow: an analysis of response times,
Hydrol. Sci. J., 27, 505–521, 1982a.
Beven, K. J.: Introducing spatially variable conductivities into Topmodel,
Unpublished Research Report, Department of Environmental Sciences,
University of Virginia, Charlottesville, VA, 1982b.
Beven, K. J.: Infiltration into a class of vertically non-uniform soils,
Hydrol. Sci. J., 29, 425–434, 1984.
Beven, K. J.: Hillslope runoff processes and flood frequency characteristics,
in: Hillslope Processes, edited by: Abrahams, A. D., Allen and Unwin, Boston, 187–202, 1986a.
Beven K. J.: Runoff production and flood frequency in catchments of order n:
an alternative approach, in: Scale Problems in Hydrology, edited by: Gupta, V. K., Rodriguez-lturbe, I., and Wood, E. F., Reidel, Dordrecht, 117–131, 1986b.
Beven, K. J.: Towards the use of catchment geomorphology in flood frequency
predictions, Earth Surf. Process. Landf., 12, 69–82., 1987.
Beven, K. J.: Prophecy, reality and uncertainty in distributed hydrological
modelling, Adv. Water Res., 16, 41–51, 1993.
Beven, K. J.: TOPMODEL: a critique, Hydrol. Process., 11, 1069–1086, 1997.
Beven, K. J.: Robert Horton and abrupt rises of groundwater, Hydrol. Process., 18, 3687–3696, 2004.
Beven, K. J.: Searching for the Holy Grail of scientific hydrology:
Beven, K. J.: Towards integrated environmental models of everywhere: uncertainty, data and modelling as a learning process, Hydrol. Earth Syst. Sci., 11, 460–467, https://doi.org/10.5194/hess-11-460-2007, 2007.
Beven, K. J.: I believe in climate change but how precautionary do we need
to be in planning for the future?, Hydrol. Process., 25, 1517–1520, https://doi.org/10.1002/hyp.7939, 2011.
Beven, K. J.: Rainfall-Runoff Modelling: The Primer, 2nd edition, Wiley-Blackwell, Chichester, 2012
Beven, K. J.: EGU Leonardo Lecture: Facets of Hydrology – epistemic error, non-stationarity, likelihood, hypothesis testing, and communication, Hydrol. Sci. J., 61, 1652–1665, https://doi.org/10.1080/02626667.2015.1031761, 2016.
Beven, K. J.: Towards a methodology for testing models as hypotheses in the
inexact sciences, P. Roy. Soc. A-Math. Phy., 475, 20180862, https://doi.org/10.1098/rspa.2018.0862, 2019a.
Beven, K. J.: How to make advances in hydrological modelling, Hydrol. Res., 50, 1481–1494, https://doi.org/10.2166/nh.2019.134, 2019b
Beven, K. J.: A history of the concept of time of concentration, Hydrol. Earth Syst. Sci., 24, 2655–2670, https://doi.org/10.5194/hess-24-2655-2020, 2020.
Beven, K. J. and Alcock, R.: Modelling everything everywhere: a new approach
to decision making for water management under uncertainty, Freshwater Biol., 56, 124–132, https://doi.org/10.1111/j.1365-2427.2011.02592.x, 2012.
Beven, K. J. and Binley, A. M.: The future of distributed models: model
calibration and uncertainty prediction, Hydrol. Process., 6, 279–298, 1992.
Beven, K. J. and Binley, A. M.: GLUE, 20 years on, Hydrol. Process., 28, 5897–5918, https://doi.org/10.1002/hyp.10082, 2014.
Beven, K. J. and Blazkova, S.: Estimating changes in flood frequency under
climate change by continuous simulation (with uncertainty), in: RIBAMOD, River Basin Modelling, Management and Flood Mitigation, edited by: Balbanis, P., Bronstert, A., Casale. R., and Samuels, P., EU Publication EUR 18287,
269–285, 1999.
Beven, K. J. and Callen, J. L.: HYDRODAT: A system of FORTRAN computer programs for the preparation and analysis of hydrological data from charts, British Geomorphological Research Group, Technical Bulletin, 23, 1979.
Beven, K. J. and Chappell, N. A.: Perceptual perplexity and parameter
parsimony, WIRES Water, submitted, 2020.
Beven, K. J. and Freer, J.: A Dynamic TOPMODEL, Hydrol. Process., 15, 1993–2011, 2001.
Beven, K. J. and Germann, P. F.: Macropores and water flow in soils, Water Resour. Res., 18, 1311–1325, 1982.
Beven, K. J. and Germann, P. F.: Macropores and water flow in soils
revisited, Water Resour. Res., 49, 3071–3092, https://doi.org/10.1002/wrcr.20156, 2013.
Beven, K. J. and Kirkby, M. J.: A physically-based variable contributing area
model of basin hydrology, Hydrol. Sci. Bull., 24, 43–69, 1979.
Beven, K. J. and Quinn, P. F.: Similarity and scale effects in the water
balance of heterogeneous areas, in: The balance of Water – present and future, edited by: Keane, T. and Daly, E., AGMET, Dublin, 69–86 1994.
Beven, K. J. and Wood, E. F.: Catchment geomorphology and the dynamics of
runoff contributing areas, J. Hydrol., 65, 139–158, 1983.
Beven, K. J., Kirkby, M. J., Schofield, N., and Tagg, A.: Testing a
physically-based flood forecasting model (TOPMODEL) for three UK catchments,
J. Hydrol., 69, 119–143, 1984.
Beven, K. J., Lamb, R., Quinn, P., Romanowicz, R., and Freer, J.: TOPMODEL, in: Computer Models of Watershed Hydrology, edited by: Singh, V. P., Water Resource Publications, Colorado, 627–668, 1995.
Beven, K. J., Smith, P. J., and Freer, J. E.: So just why would a modeller choose to be incoherent?, J. Hydrol., 354, 15–32, 2008.
Beven, K. J., Asadullah, A., Bates, P. D., Blyth, E., Chappell, N. A.,
Child, S., Cloke, H., Dadson, S., Everard, N., Fowler, H. J., Freer,
J., Hannah, D. M., Heppell, C., Holden, J., Lamb, R., Lewis, H., Morgan, G.,
Parry. L., and Wagener, T.: Developing observational methods to drive future
hydrological science: can we make a start as a community?, Hydrol. Process., 34, 868–873, https://doi.org/10.1002/hyp.13622, 2020.
Blair, G. S., Beven, K. J., Lamb, R., Bassett, R., Cauwenberghs, K., Hankin,
B., Dean, G., Hunter, N., Edwards, E., Nundloll, V., Samreen, F., Simm, W., and Towe, R.: Models of Everywhere Revisited: A Technological Perspective,
Environ. Modell. Softw., 122, 104521, https://doi.org/10.1016/j.envsoft.2019.104521, 2019.
Blazkova, S. and Beven, K. J.: Flood Frequency Prediction for data limited
catchments in the Czech Republic using a stochastic rainfall model and
TOPMODEL, J. Hydrol., 195, 256–278, 1997.
Blazkova, S., Beven, K., Tacheci, P., and Kulasova, A.: Testing the distributed water table predictions of TOPMODEL (allowing for uncertainty in model calibration): the death of TOPMODEL?, Water Resour. Res., 38, W01257,
https://doi.org/10.1029/2001WR000912, 2002.
Blazkova, S. and Beven, K. J.: Flood Frequency Estimation by Continuous
Simulation for a Catchment treated as Ungauged (with Uncertainty), Water Resour. Res., 38, 14.1–14.14, https://doi.org/10.1029/2001WR000500, 2002.
Blazkova, S. and Beven, K. J.: Flood frequency estimation by continuous
simulation of subcatchment rainfalls and discharges with the aim of
improving dam safety assessment in a large basin in the Czech Republic, J. Hydrol., 292, 153–172, 2004.
Blazkova, S. and Beven, K. J.: A limits of acceptability approach to model
evaluation and uncertainty estimation in flood frequency estimation by
continuous simulation: Skalka catchment, Czech Republic, Water Resour. Res., 45, W00B16, https://doi.org/10.1029/2007WR006726, 2009a.
Blazkova, S. and Beven, K. J.: Uncertainty in Flood Estimation, Struct. Infrastruct. E., 5, 325–332, https://doi.org/10.1080/15732470701189514, 2009b.
Buytaert, W.: topmodel: Implementation of the Hydrological Model TOPMODEL in
R, Rpackage version 0.7.3, available at: https://CRAN.R-project.org/package=topmodel (last access: 21 January 2021), 2018.
Calder, I. R., Harding, R. J., and Rosier, P. T. W.: An objective assessment of soil moisture deficit models, J. Hydrol, 185, 363–378, 1983.
Calver, A. and Lamb, R.: Flood frequency estimation using continuous
rainfall-runoff modelling, Phys. Chem. Earth, 20, 479–483, 1995.
Cameron, D., Beven, K. J., Tawn, J., Blazkova, S., and Naden, P.: Flood frequency estimation by continuous simulation for a gauged upland catchment (with uncertainty), J. Hydrol., 219, 169–187, 1999.
Cameron, D., Beven, K., Tawn, J., and Naden, P.: Flood frequency estimation by continuous simulation (with likelihood based uncertainty estimation), Hydrol. Earth Syst. Sci., 4, 23–34, https://doi.org/10.5194/hess-4-23-2000, 2000a.
Cameron, D., Beven, K., and Naden, P.: Flood frequency estimation by continuous simulation under climate change (with uncertainty), Hydrol. Earth Syst. Sci., 4, 393–405, https://doi.org/10.5194/hess-4-393-2000, 2000b.
Cameron, D., Beven, K. J., and Tawn, J.: An evaluation of three stochastic
rainfall models, J. Hydrol., 228, 130–149, 2000c.
Chaney, N. W., Metcalfe, P., and Wood, E. F.: HydroBlocks: a field-scale
resolving land surface model for application over continental
extents, Hydrol. Process., 30, 3543–3559, 2016.
Chirico, G. B., Grayson, R. B., and Western, A. W.: On the computation of the
quasi-dynamic wetness index with multiple-flow-direction algorithms, Water Resour. Res., 39, 1115, https://doi.org/10.1029/2002WR001754, 2003.
Choi, H. T. and Beven, K. J.: Multi-period and Multi-criteria Model
Conditioning to Reduce Prediction Uncertainty in Distributed Rainfall-Runoff
Modelling within GLUE framework, J. Hydrol, 332, 316–336, 2007.
Ciarapica, L. and Todini, E.: TOPKAPI: A model for the representation of the
rainfall–runoff process at different scales, Hydrol. Process., 16, 207–229, 2002.
Clark, M. P., Slater, A. G., Rupp, D. E., Woods, R. A., Vrugt, J. A., Gupta,
H. V., Wagener, T., and Hay, L. E.: Framework for Understanding Structural
Errors (FUSE): A modular framework to diagnose differences between
hydrological models, Water Resour. Res., 44, W00B02, https://doi.org/10.1029/2007WR006735, 2008.
Coxon, G., Freer, J., Wagener, T., Odoni, N. A., and Clark, M.: Diagnostic
evaluation of multiple hypotheses of hydrological behaviour in a
limits-of-acceptability framework for 24 UK catchments, Hydrol. Process., 28, 6135–6150, 2014.
Coxon, G., Freer, J., Lane, R., Dunne, T., Knoben, W. J. M., Howden, N. J. K., Quinn, N., Wagener, T., and Woods, R.: DECIPHeR v1: Dynamic fluxEs and ConnectIvity for Predictions of HydRology, Geosci. Model Dev., 12, 2285–2306, https://doi.org/10.5194/gmd-12-2285-2019, 2019.
Crave, A. and Gascuel-Odoux, C.: The Influence of topography on time and
space distribution of soil surface water content, Hydrol. Process., 11,
203–210, 1997.
Crawford, N. H. and Burges, S. J.: History of the Stanford watershed
model, Water Resour. Impact, 6, 1–3, 2004.
Davies, J. and Beven, K. J.: Hysteresis and scale in catchment storage, flow,
and transport, Hydrol. Process., 29, 3604–3615, https://doi.org/10.1002/hyp.10511, 2015.
Duan, J. and Miller, N. L.: A generalized power function for the subsurface
transmissivity profile in TOPMODEL, Water Resour. Res., 33, 2559–2562, 1997.
Ducharne, A.: Reducing scale dependence in TOPMODEL using a dimensionless topographic index, Hydrol. Earth Syst. Sci., 13, 2399–2412, https://doi.org/10.5194/hess-13-2399-2009, 2009.
Dunne, T. and Black, R. D.: Partial area contributions to storm runoff in a
small New England watershed, Water Resour. Res., 6, 1296–1311, 1970.
Eagleson, P. S.: Dynamics of flood frequency, Water Resour. Res., 8, 878–898, 1972.
Essery, R. L. H., Best, M. J., Betts, R. A., Cox, P. M., and Taylor, C. M.:
Explicit representation of subgrid heterogeneity in a GCM land surface
scheme, J. Hydrometeorol., 4, 530–543, 2003.
Famiglietti, J. and Wood, E. F.: Multiscale modeling of spatially variable
water and energy balance process, Water Resour. Res., 30, 3061–3078,
https://doi.org/10.1029/94WR01498, 1994.
Fenicia, F., Kavetski, D., and Savenije, H. H. G.: Elements of a flexible
approach for conceptual hydrological modeling: 1. Motivation and theoretical
development, Water Resour. Res., 47, W11510, https://doi.org/10.1029/2011WR010748, 2011.
Fisher, J. I. and Beven, K. J.: Modelling of streamflow at Slapton Wood using
TOPMODEL within an uncertainty estimation framework, Field Studies Journal, 8, 577–584, 1996.
Franchini, M., Wendling, J., Obled, C., and Todini, E.: Physical interpretation and sensitivity analysis of the TOPMODEL, J. Hydrol., 175,
293–338, 1996.
Franks, S., Beven, K. J., Quinn, P. F., and Weight, I.: On the sensitivity of soil-vegetation-atmosphere transfer (SVAT) schemes: equifinality and the
problem of robust calibration, Agr. For. Meteorol., 86, 63–75, 1997.
Franks, S. W., Gineste, P., Beven, K. J., and Merot, P.: On constraining the
predictions of a distributed model: the incorporation of fuzzy estimates of
saturated areas into the calibration process, Water Resour. Res., 34, 787–797, 1998
Freer, J., Beven, K., and Ambroise, B.: Bayesian estimation of uncertainty in
runoff prediction and the value of data: An application of the GLUE
approach, Water Resour. Res., 32, 2161–2173, 1996.
Freer, J., McDonnell, J., Beven, K. J., Brammer, D., Burns, D., Hooper, R. P., and Kendal, C.: Topographic controls on subsurface stormflow at the hillslope scale for two hydrologically distinct small catchments, Hydrol. Process., 11, 1347–1352, 1997.
Freer, J., McDonnell, J., Beven, K. J., Peters, N. E., Burns, D., Hooper, R. P., Aulenbach, B., and Kendal, C.: The role of bedrock topography on subsurface stormflow, Water Resour. Res., 38, W01269, 10.1029/2001WR000872, 2002.
Freer, J. E., Beven, K. J., and Peters, N. E.: Multivariate seasonal period
model rejection within the generalised likelihood uncertainty estimation
procedure, in: Calibration of Watershed Models, edited by: Duan, Q., Gupta, H., Sorooshian, S., Rousseau, A. N., and Turcotte, R., AGU Books, Washington, 69–87, 2003.
Freer, J., McMillan, H., McDonnell, J. J., and Beven, K. J.: Constraining Dynamic TOPMODEL responses for imprecise water table information using fuzzy rule based performance measures, J. Hydrol., 291, 254–277, 2004.
Freeman, T. G.: Calculating catchment area with divergent flow based on a
regular grid, Comput. Geosci., 17, 413–422, 1991.
Freeze, R. A. and Harlan, R. L.: Blueprint for a physically-based,
digitally-simulated hydrologic response model, J. Hydrol., 9, 237–258, 1969.
Fu, X., Luo, L., Pan, M., Yu, Z., Tang, Y., and Ding, Y.: Evaluation of
TOPMODEL-based land surface–atmosphere transfer scheme (TOPLATS) through a
soil moisture simulation, Earth Interact., 22, 1–19, 2018.
Gallart, F., Latron, J., Llorens, P., and Beven, K. J.: Using internal catchment
information to reduce the uncertainty of discharge and baseflow predictions,
Adv. Water Res., 30, 808–823, 2007
Gallart, F., Latron, J., Llorens, P., and Beven, K. J.: Upscaling discrete
internal observations for obtaining catchment-averaged TOPMODEL parameters
in a small Mediterranean mountain basin, Phys. Chem. Earth, 33, 1090–1094, 2008.
Gao, J., Holden, J., and Kirkby, M.: A distributed TOPMODEL for modelling
impacts of landcover change on river flow in upland peatland catchments,
Hydrol. Process, 29, 2867–2879, https://doi.org/10.1002/hyp.10408, 2015.
Gao, J., Holden, J., and Kirkby, M.: The impact of land-cover change on flood
peaks in peatland basins, Water Resour. Res., 52, 3477–3492, https://doi.org/10.1002/2015WR017667, 2016.
Gao, J., Holden, J., and Kirkby, M.: Modelling impacts of agricultural
practice on flood peaks in upland catchments: An application of the
distributed, TOPMODEL, Hydrol. Process., 31, 4206–4216, 2017.
Gharari, S., Hrachowitz, M., Fenicia, F., and Savenije, H. H. G.: Hydrological landscape classification: investigating the performance of HAND based landscape classifications in a central European meso-scale catchment, Hydrol. Earth Syst. Sci., 15, 3275–3291, https://doi.org/10.5194/hess-15-3275-2011, 2011.
Graham, C. B., Woods, R. A., and McDonnell, J. J.: Hillslope threshold response to rainfall. (1) A field based forensic approach, J. Hydrol., 393, 65–76, 2010.
Güntner, A., Uhlenbrook, S., Seibert, J., and Leibundgut, C.:
Multi-criterial validation of TOPMODEL in a mountainous catchment,
Hydrol. Process., 13, 1603–1620, 1999.
Habets, F. and Saulnier, G. M.: Subgrid runoff parameterization, Phys. Chem. Earth Pt.B, 26, 455–459, 2001.
Hjerdt, K. N., McDonnell, J. J., Seibert, J., and Rodhe, A.: A new
topographic index to quantify downslope controls on local drainage, Water Resour. Res., 40, 1–6, https://doi.org/10.1029/2004WR003130, 2004.
Hollaway, M. J., Beven, K. J., Benskin, C. McW. H., Collins, A. L., Evans, R., Falloon, P. D., Forber, K. J., Hiscock, K. M., Kahana, R., Macleod, C. J. A., Ockenden, M. C., Villamizar, M. L., Wearing, C., Withers, P. J. A., Zhou, J. G., and Haygarth, P. M.: Evaluating a processed based water quality model on a UK headwater catchment: what can we learn from a “limits of acceptability” uncertainty framework?, J. Hydrol., 558, 607–624, https://doi.org/10.1016/j.jhydrol.2018.01.063, 2018.
Hopp, L. and McDonnell, J. J.: Connectivity at the hillslope scale:
Identifying interactions between storm size, bedrock permeability, slope
angle and soil depth, J. Hydrol., 376, 378–391, 2009.
Hornberger, G. M. and Spear, R. C.: An approach to the preliminary analysis
of environmental systems, J. Environ. Manag., 12, 7–18, 1981.
Horton, R. E.: Maximum groundwater levels, EOS T. Am. Geophys. Un., 17, 344–357, 1936.
Huang, J.-C., Lee, T.-Y., and Kao, S.-J.: Simulating typhoon-induced storm hydrographs in subtropical mountainous watershed: an integrated 3-layer TOPMODEL, Hydrol. Earth Syst. Sci., 13, 27–40, https://doi.org/10.5194/hess-13-27-2009, 2009.
Ibbitt, R. P. and O'Donnell, T.: Fitting methods for conceptual catchment
models, J. Hydraul. Diov. ASCE., 97, 1331–1342, 1971.
Ibbitt, R. P. and O'Donnell, T.: Designing conceptual catchment models for
automatic fitting methods, IAHS-AISH P., 101, 461–475, 1974.
Ibbitt, R. P. and Woods, R.: Re-scaling the topographic index to improve the
representation of physical processes in catchment models, J. Hydrol., 293,
205–218, 2004.
Jencso, K. G. and McGlynn, B. L.: Hierarchical controls on runoff
generation: Topographically driven hydrologic connectivity, geology, and
vegetation, Water Resour. Res., 47, W11527, https://doi.org/10.1029/2011WR010666, 2011.
Iorgulescu, I. and Musy, A.: Generalization of TOPMODEL for a power law
transmissivity profile, Hydrol. Process., 11, 1353–1355, 1997.
Johnston, P. R. and Pilgrim, D. H.: Parameter optimization for watershed
models, Water Resour. Res., 12, 477–486, 1976.
Kirchner, J. W.: Getting the right answers for the right reasons: Linking
measurements, analyses, and models to advance the science of
hydrology, Water Resour. Res., 42, W03S04, https://doi.org/10.1029/2005WR004362, 2006.
Kirkby, M.: Hydrograph modelling strategies, in: Processes in Human and Physical Geography, edited by: Peel, R., Chisholm, M., and Haggett, P., Heinemann, London, 69–90, 1975.
Kirkby, M.: Implications for sediment transport, in: Hillslope Hydrology, John Wiley and Sons, Chichester, 325–363, 1978.
Kirkby, M. J.: A runoff simulation model based on hillslope topography, in:
Scale problems in Hydrology: runoff generation and response, edited by: Gupta, V. K., Rodriguez-Iturbe, I., and Wood, E. F., Reidel, Dordrecht, 39–56, 1986.
Kirkby, M. J.: Topmodel: a personal view, Hydrol. Process., 11, 1087–1098, 1997
Klemeš, V.: Dilettantism in hydrology: Transition or destiny?, Water Resour. Res., 22, 177S–188S, 1986.
Knoben, W. J. M., Freer, J. E., Fowler, K. J. A., Peel, M. C., and Woods, R. A.: Modular Assessment of Rainfall–Runoff Models Toolbox (MARRMoT) v1.2: an open-source, extendable framework providing implementations of 46 conceptual hydrologic models as continuous state-space formulations, Geosci. Model Dev., 12, 2463–2480, https://doi.org/10.5194/gmd-12-2463-2019, 2019.
Lamb, R.: Calibration of a conceptual rainfall-runoff model for flood
frequency estimation by continuous simulation, Water Resour. Res., 35, 3103–3114, 1999.
Lamb, R. and Beven, K.: Using interactive recession curve analysis to specify a general catchment storage model, Hydrol. Earth Syst. Sci., 1, 101–113, https://doi.org/10.5194/hess-1-101-1997, 1997.
Lamb, R., Beven, K. J., and Myrabø, S.: Discharge and water table predictions using a generalised TOPMODEL formulation, Hydrol. Process., 11, 1145–1168, 1997.
Lamb, R., Beven, K. J., and Myrabø, S.: Use of spatially distributed
water table observations to constrain uncertainty in a rainfall-runoff
model, Adv. Water Res., 22, 305–317, 1998.
Lan, T., Lin, K. R., Liu, Z. Y., He, Y. H., Xu, C. Y., Zhang, H. B., and
Chen, X. H.: A clustering preprocessing framework for the subannual
calibration of a hydrological model considering climate-land surface
variations, Water Resour. Res., 54, 10034–10052,
https://doi.org/10.1029/2018WR023160, 2018.
Lane, S. N., Brookes, C. J., Kirkby, M. J., and Holden, J.: A
network-index-based version of TOPMODEL for use with high-resolution digital
topographic data, Hydrol. Process., 18, 191–201, 2004.
Lane, S. N. and Milledge, D. G.: Impacts of upland open drains upon runoff
generation: a numerical assessment of catchment-scale impacts, Hydrol. Process., 27, 1701–1726, 2013.
Lane, S. N., Reaney, S. M., and Heathwaite, A. L.: Representation of landscape hydrological connectivity using a topographically driven surface flow index, Water Resour. Res., 45, W08423, https://doi.org/10.1029/2008WR007336, 2009.
Larsen, J. E., Sivapalan, M., Coles, N. A., and Linnet, P. E.: Similarity
analysis of runoff generation processes in real-world catchments, Water Resour. Res., 30, 1641–1652, 1994.
Liu, Y., Freer, J. E., Beven, K. J., and Matgen, P.: Towards a limits of
acceptability approach to the calibration of hydrological models: extending
observation error, J. Hydrol., 367, 93–103, https://doi.org/10.1016/j.jhydrol.2009.01.016, 2009.
Liu, Z. and Todini, E.: Assessing the TOPKAPI non-linear reservoir cascade
approximation by means of a characteristic lines solution, Hydrol. Process., 19, 1983–2006, 2005.
Liu, Z., Martina, M. L. V., and Todini, E.: Flood forecasting using a fully distributed model: application of the TOPKAPI model to the Upper Xixian Catchment, Hydrol. Earth Syst. Sci., 9, 347–364, https://doi.org/10.5194/hess-9-347-2005, 2005.
Loritz, R., Gupta, H., Jackisch, C., Westhoff, M., Kleidon, A., Ehret, U., and Zehe, E.: On the dynamic nature of hydrological similarity, Hydrol. Earth Syst. Sci., 22, 3663–3684, https://doi.org/10.5194/hess-22-3663-2018, 2018.
Marthews, T. R., Dadson, S. J., Lehner, B., Abele, S., and Gedney, N.: High-resolution global topographic index values for use in large-scale hydrological modelling, Hydrol. Earth Syst. Sci., 19, 91–104, https://doi.org/10.5194/hess-19-91-2015, 2015.
McDonnell, J. J. and Beven, K. J.: Debates – The future of hydrological
sciences: A (common) path forward? A call to action aimed at understanding
velocities, celerities, and residence time distributions of the headwater
hydrograph, Water Resour. Res., 50, 5342–5350, https://doi.org/10.1002/2013WR015141, 2014.
Metcalfe, P., Beven, K. J., and Freer, J.: Dynamic Topmodel: a new
implementation in R and its sensitivity to time and space steps,
Environ. Modell. Softw., 72, 155–172, 2015.
Metcalfe, P., Beven, K. J., Hankin, B., and Lamb, R.: A modelling framework for evaluation of the hydrological impacts of nature-based approaches to flood risk management, with application to in-channel interventions across a
29-km2 scale catchment in the United Kingdom, Hydrol. Process., 31, 1734–1748, https://doi.org/10.1002/hyp.11140, 2017.
Michel, C, Perrin, C, and Andréassian, V.: The exponential store: a correct formulation for rainfall—runoff modelling, Hydrolog. Sci. J., 48, 109–124, 2003.
Milledge, D. G., Lane, S. N., Heathwaite, A. L., and Reaney, S. M.: A Monte Carlo approach to the inverse problem of diffuse pollution risk in agricultural catchments, Sci. Total Environ., 433, 434–449, 2012.
Montgomery, D. R. and Dietrich, W. E.: A physically based model for the
topographic control on shallow landsliding, Water Resour. Res., 30, 1153–1171, 1994.
Montgomery, D. R. and Dietrich, W. E.: Runoff generation in a steep,
soil-mantled landscape, Water Resour. Res., 38, 7–17, 2002.
Moore, I. D., O'Loughlin, E. M., and Burch, G. J.: A contour-based topographic model for hydrological and ecological applications, Earth Surf. Proc. Land., 13, 305–320, 1988.
Moore, R. D. and Thompson, J. C.: Are water table variations in a shallow
forest soil consistent with the TOPMODEL concept?, Water Resour. Res., 32, 663–669, 1996.
Morris, D. G. and Heerdegen, R. G.: Automatically derived catchment boundaries and channel networks and their hydrological
applications, Geomorphology, 1, 131–141, 1988.
O'Loughlin E. M.: Saturation regions in catchments and their relation to soil
and topographic properties, J. Hydrol., 53, 229–246, 1981.
O'Loughlin, E. M.: Prediction of surface saturation zones in natural
catchments by topographic analysis, Water Resour. Res., 22, 794–804, 1986.
Pan, F., Peters-Lidard, C. D., Sale, M. J., and King, A. W.: A comparison of
geographical information systems–based algorithms for computing the
TOPMODEL topographic index, Water Resour. Res., 40, W06303, https://doi.org/10.1029/2004WR003069, 2004.
Pappenberger, F., Frodsham, K., Beven, K., Romanowicz, R., and Matgen, P.: Fuzzy set approach to calibrating distributed flood inundation models using remote sensing observations, Hydrol. Earth Syst. Sci., 11, 739–752, https://doi.org/10.5194/hess-11-739-2007, 2007.
Pauwels, V. R. N. and Wood, E. F.: A soil-vegetation-atmosphere transfer
scheme for the modeling of water and energy balance process in high
latitudes: 2. Application and validation, J. Geophys. Res., 104, 27823–27839, https://doi.org/10.1029/1999JD900004, 1999.
Peters N. E., Freer J. E., and Beven K. J.: Modelling hydrologic responses in
a small forested catchment (Panola Mountain, Georgia, USA): A comparison of
the original and a new dynamic TOPMODEL, Hydrol. Process., 17, 345–362, 2003.
Peters-Lidard, C. D., Zion, M. S., and Wood, E. F.: A
soil-vegetation-atmosphere transfer scheme for modeling spatially variable
water and energy balance process, J. Geophys. Res., 102, 4303–4324, https://doi.org/10.1029/96JD02948, 1997.
Piñol, J., Beven, K. J., and Freer, J.: Modelling the hydrological response of mediterranean catchments, Prades, Catalonia – the use of distributed models as aids to hypothesis formulation, Hydrol. Process., 11, 1287–1306, 1997.
Porter, K. D., Reaney, S. M., Quilliam, R. S., Burgess, C., and Oliver, D. M.: Predicting diffuse microbial pollution risk across catchments: The
performance of SCIMAP and recommendations for future development, Sci. Total Environ., 609, 456–465, 2017.
Pradhan, N. R., Tachikawa, Y., and Takara, K.: A downscaling method of
topographic index distribution for matching the scales of model application
and parameter identification, Hydrol. Process., 20, 1385–1405, 2006.
Pradhan, N. R., Ogden, F. L., Tachikawa, Y., and Takara, K.: Scaling of slope, upslope area, and soil water deficit: Implications for transferability and regionalization in topographic index modeling, Water Resour. Res., 44, W12421, https://doi.org/10.1029/2007WR006667, 2008.
Quinn, P. F., Beven, K. J., Chevallier, P., and Planchon, O.: The Prediction of Hillslope Flow paths for distributed hydrological modelling using digital
terrain models, Hydrol. Process., 5, 59–79, 1991.
Quinn, P., Beven, K. J., and Lamb, R.: The ln(a∕tanβ) index: how to
calculate it and how to use it within the TOPMODEL framework,
Hydrol. Process., 9, 161–182, 1995a.
Quinn, P., Beven, K. J., and Culf, A.: The introduction of macroscale
hydrological complexity into land surface-atmosphere transfer models and the
effect of planetary boundary layer development, J. Hydrol., 166, 421–444, 1995b.
Quinn, P. F., Ostendorf, B., Beven, K., and Tenhunen, J.: Spatial and temporal predictions of soil moisture patterns and evaporative losses using TOPMODEL and the GASFLUX model for an Alaskan catchment, Hydrol. Earth Syst. Sci., 2, 51–64, https://doi.org/10.5194/hess-2-51-1998, 1998.
Reggiani, P. and Rientjes, T. H. M.: Flux parameterization in the
representative elementary watershed approach: Application to a natural
basin, Water Resour. Res., 41, W04013, https://doi.org/10.1029/2004WR003693, 2005.
Rennó, C. D., Nobre, A. D., Cuartas, L. A., Soares, J. V., Hodnett, M.
G., Tomasella, J., and Waterloo, M. J.: HAND, a new terrain descriptor using
SRTM-DEM: Mapping terra-firme rainforest environments in Amazonia, Remote Sens. Environ., 112, 3469–3481, https://doi.org/10.1016/j.rse.2008.03.018, 2008.
Robson, A., Beven, K. J., and Neal, C.: Towards identifying sources of
subsurface flow: a comparison of components identified by a physically-based
runoff model and those determined by chemical mixing techniques,
Hydrol. Process., 6, 199–214, 1992.
Romanowicz, R., Beven, K. J., and Tawn, J.: Evaluation of predictive uncertainty in non-linear hydrological models using a Bayesian approach, in: Statistics for the Environment II. Water Related Issues, edited by: Barnett, V. and Turkman, K. F., Wiley, Chichester, 297–317, 1994.
Saulnier, G. M., Obled, C., and Beven, K.: Analytical compensation between dtm grid resolution and effective values of saturated hydraulic conductivity
within the Topmodel framework, Hydrol. Process., 11, 1331–1346, 1997a.
Saulnier, G. M., Beven, K., and Obled, C.: Digital elevation analysis for
distributed hydrological modeling: Reducing scale dependence in effective
hydraulic conductivity values, Water Resour. Res., 33, 2097–2101, 1997b.
Saulnier, G.-M., Beven, K. J., and Obled, C..: Including spatially variable soil depths in TOPMODEL, J. Hydrol., 202, 158–172, 1997c.
Saulnier, G. M. and Datin, R.: Analytical solution to a bias in the TOPMODEL
framework balance, Hydrol. Process., 18, 1195–1218, 2004.
Scanlon, T. M., Raffensperger, J. P., Hornberger, G. M., and Clapp, R. B.:
Shallow subsurface storm flow in a forested headwater catchment:
Observations and modeling using a modified TOPMODEL, Water Resour. Res., 36, 2575–2586, 2000.
Seibert, J., Bishop, K., and Nyberg, L.: Testing TOPMODEL's ability to
predict spatially distributed groundwater levels, Hydrol. Process., 11, 1131–1144, 1997.
Seibert, J., Bishop, K., Rodhe, A., and McDonnell, J. J.: Groundwater dynamics along a hillslope: A test of the steady state hypothesis, Water Resour. Res., 39, 1014, https://doi.org/10.1029/2002WR001404, 2003.
Shreve, R. L.: Infinite topologically random channel networks, J. Geology, 75, 178–186, 1967.
Sivapalan, M., Beven, K. J., and Wood, E.F.: On Hydrologic Similarity 2: A
scaled model of storm runoff production, Water Resour. Res., 23, 2266–2278, 1987.
Sivapalan, M., Wood, E. F., and Beven, K. J.: On Hydrologic Similarity, 3. A
dimensionless flood frequency distribution, Water Resour. Res., 26, 43–58, 1990.
Sorensen, R. and Seibert, J.: Effects of DEM resolution on the
calculation of topographical indices: TWI and its components, J. Hydrol., 347, 79–89, 2007.
Tague, C. L. and Band, L. E.: RHESSys: Regional Hydro-Ecologic Simulation
System – An object-oriented approach to spatially distributed modeling of
carbon, water, and nutrient cycling, Earth Interact., 8, 1–42, 2004.
Tarboton, D. G.: A new method for the determination of flow directions and
upslope areas in grid digital elevation models, Water Resour. Res., 33, 309–319, 1997.
Tetzlaff, D., Birkel, C., Dick, J., Geris, J., and Soulsby, C.: Storage dynamics in hydropedological units control hillslope connectivity, runoff generation and the evolution of catchment transit time distributions, Water Resour. Res., 50, 969–985, https://doi.org/10.1002/2013WR014147, 2014.
Thomas Jr., W. O.: An evaluation of flood frequency estimates based on
rainfall/runoff modelling, J. Am. Water Resour. As., 18, 221–229, 1982.
Todini, E.: New trends in modelling soil processes from hillslope to GCM
scales, in: The Role of Water and the Hydrological Cycle in Global Change, edited by: Oliver, H. R. and Oliver, S. A., Global Environmental Change, NATO ASI Series, Series I, vol. 31, Springer-Verlag, Berlin, 317–347, 1995.
Vincendon, B., Ducrocq, V., Bouilloudd, L., Saulnier, G.-M., Chancibaulte, K., Habets, F. and Noilhan, J.: Benefit of coupling the ISBA land surface model with a TOPMODEL hydrological model version dedicated to Mediterranean flash floods, J. Hydrol., 394, 256–266, 2010.
Walter, M. T., Steenhuis, T. S., Mehta, V. K., Thongs, D., Zion, M., and
Schneiderman, E.: Refined conceptualization of TOPMODEL for shallow
subsurface flows, Hydrol. Process., 16, 2041–2046, 2002.
Weyman, D. R.: Throughflow on hillslopes and its relation to the stream
hydrograph, Hydrol. Sci. B., 15, 25–33, 1970.
Weyman, D. R.: Measurements of the downslope flow of water in a
soil, J. Hydrol., 20, 267–288, 1973.
Western, A. W., Grayson, R. B., Blöschl, G., Willgoose, G. R.,
and McMahon, T. A.: Observed spatial organisation of soil moisture and its
relation to terrain indices, Water Resour. Res., 35, 797–810, https://doi.org/10.1029/1998WR900065, 1999.
Wigmosta, M. S., Vail, L. W., and Lettenmaier, D. P.: A distributed
hydrology-vegetation model for complex terrain, Water Resour. Res., 30, 1665–1679, 1994.
Wolock, D. M. and McCabe Jr., G. J.: Comparison of single and multiple flow
direction algorithms for computing topographic parameters in
TOPMODEL, Water Resour. Res., 31, 1315–1324, 1995.
Wood, E. F., Sivapalan, M., Beven, K. J., and Band, L.: Effects of spatial
variability and scale with implications to hydrologic modelling, J. Hydrol., 102, 29–47, 1988.
Woods, R. A., Sivapalan, M., and Robinson, J. S.: Modeling the spatial
variability of subsurface runoff using a topographic index, Water Resour. Res., 33, 1061–1073, 1997.
Zulkafli, Z., Buytaert, W., Onof, C., Lavado, W., and Guyot, J. L.: A critical assessment of the JULES land surface model hydrology for humid tropical environments, Hydrol. Earth Syst. Sci., 17, 1113–1132, https://doi.org/10.5194/hess-17-1113-2013, 2013.
Short summary
The theory that forms the basis of TOPMODEL was first outlined by Mike Kirkby some 45 years ago. This paper recalls some of the early developments: the rejection of the first journal paper, the early days of digital terrain analysis, model calibration and validation, the various criticisms of the simplifying assumptions, and the relaxation of those assumptions in the dynamic forms of TOPMODEL, and it considers what we might do now with the benefit of hindsight.
The theory that forms the basis of TOPMODEL was first outlined by Mike Kirkby some 45 years ago....
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