Articles | Volume 24, issue 1
https://doi.org/10.5194/hess-24-349-2020
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/hess-24-349-2020
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
24 Jan 2020
Research article |
| 24 Jan 2020
| 24 Jan 2020
On the configuration and initialization of a large-scale hydrological land surface model to represent permafrost
Mohamed E. Elshamy
CORRESPONDING AUTHOR
Global Institute for Water Security, University of Saskatchewan, 11
Innovation Blvd, Saskatoon, SK, Canada
Daniel Princz
Environment and Climate Change Canada, 11 Innovation Blvd, Saskatoon, SK, Canada
Gonzalo Sapriza-Azuri
Departamento del Agua, Centro Universitario Regional Norte (CENUR), Litoral Norte,
Universidad de la República, Salto, Uruguay
Mohamed S. Abdelhamed
Global Institute for Water Security, University of Saskatchewan, 11
Innovation Blvd, Saskatoon, SK, Canada
Al Pietroniro
Global Institute for Water Security, University of Saskatchewan, 11
Innovation Blvd, Saskatoon, SK, Canada
Environment and Climate Change Canada, 11 Innovation Blvd, Saskatoon, SK, Canada
Howard S. Wheater
Global Institute for Water Security, University of Saskatchewan, 11
Innovation Blvd, Saskatoon, SK, Canada
Saman Razavi
Global Institute for Water Security, University of Saskatchewan, 11
Innovation Blvd, Saskatoon, SK, Canada
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Mohamed S. Abdelhamed, Mohamed E. Elshamy, Saman Razavi, and Howard S. Wheater
The Cryosphere Discuss., https://doi.org/10.5194/tc-2023-20, https://doi.org/10.5194/tc-2023-20, 2023
Preprint withdrawn
Short summary
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Prior to any climate change assessment, it is necessary to assess the ability of available models to reliably reproduce observed permafrost and hydrology. Following a progressive approach, various model set-ups were developed and evaluated against different data sources. The study shows that different model set-ups favour different sources of data and it is challenging to configure a model faithful to all data sources, which are at times inconsistent with each other.
Chris M. DeBeer, Howard S. Wheater, John W. Pomeroy, Alan G. Barr, Jennifer L. Baltzer, Jill F. Johnstone, Merritt R. Turetsky, Ronald E. Stewart, Masaki Hayashi, Garth van der Kamp, Shawn Marshall, Elizabeth Campbell, Philip Marsh, Sean K. Carey, William L. Quinton, Yanping Li, Saman Razavi, Aaron Berg, Jeffrey J. McDonnell, Christopher Spence, Warren D. Helgason, Andrew M. Ireson, T. Andrew Black, Mohamed Elshamy, Fuad Yassin, Bruce Davison, Allan Howard, Julie M. Thériault, Kevin Shook, Michael N. Demuth, and Alain Pietroniro
Hydrol. Earth Syst. Sci., 25, 1849–1882, https://doi.org/10.5194/hess-25-1849-2021, https://doi.org/10.5194/hess-25-1849-2021, 2021
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This article examines future changes in land cover and hydrological cycling across the interior of western Canada under climate conditions projected for the 21st century. Key insights into the mechanisms and interactions of Earth system and hydrological process responses are presented, and this understanding is used together with model application to provide a synthesis of future change. This has allowed more scientifically informed projections than have hitherto been available.
Zilefac Elvis Asong, Mohamed Ezzat Elshamy, Daniel Princz, Howard Simon Wheater, John Willard Pomeroy, Alain Pietroniro, and Alex Cannon
Earth Syst. Sci. Data, 12, 629–645, https://doi.org/10.5194/essd-12-629-2020, https://doi.org/10.5194/essd-12-629-2020, 2020
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This dataset provides an improved set of forcing data for large-scale hydrological models for climate change impact assessment in the Mackenzie River Basin (MRB). Here, the strengths of two historical datasets were blended to produce a less-biased long-record product for hydrological modelling and climate change impact assessment over the MRB. This product is then used to bias-correct climate projections from the Canadian Regional Climate Model under RCP8.5.
Fuad Yassin, Saman Razavi, Mohamed Elshamy, Bruce Davison, Gonzalo Sapriza-Azuri, and Howard Wheater
Hydrol. Earth Syst. Sci., 23, 3735–3764, https://doi.org/10.5194/hess-23-3735-2019, https://doi.org/10.5194/hess-23-3735-2019, 2019
Zilefac Elvis Asong, Mohamed Elshamy, Daniel Princz, Howard Wheater, John Pomeroy, Alain Pietroniro, and Alex Cannon
Hydrol. Earth Syst. Sci. Discuss., https://doi.org/10.5194/hess-2019-249, https://doi.org/10.5194/hess-2019-249, 2019
Publication in HESS not foreseen
Zilefac Elvis Asong, Howard Simon Wheater, John Willard Pomeroy, Alain Pietroniro, Mohamed Ezzat Elshamy, Daniel Princz, and Alex Cannon
Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2018-128, https://doi.org/10.5194/essd-2018-128, 2018
Preprint withdrawn
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Cold regions hydrology is very sensitive to the impacts of climate warming. We need better hydrological models driven by reliable climate data in order to assess hydrologic responses to climate change. Cold regions often have sparse surface observations, particularly at high elevations that generate a major amount of runoff. We produce a long-term dataset that can be used to better understand and represent the seasonal/inter-annual variability of hydrological fluxes and the the timing of runoff.
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Hydrol. Earth Syst. Sci., 27, 4595–4608, https://doi.org/10.5194/hess-27-4595-2023, https://doi.org/10.5194/hess-27-4595-2023, 2023
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Wetlands are important ecosystems that store carbon and play a vital role in the water cycle. However, hydrological computer models do not always represent wetlands and their interaction with groundwater accurately. We tested different possible ways to include groundwater–wetland interactions in these models. We found that the optimal method to include wetlands and groundwater in the models is reliant on the intended use of the models and the characteristics of the land and soil being studied.
Reyhaneh Hashemi, Pierre Javelle, Olivier Delestre, and Saman Razavi
Hydrol. Earth Syst. Sci. Discuss., https://doi.org/10.5194/hess-2023-282, https://doi.org/10.5194/hess-2023-282, 2023
Manuscript not accepted for further review
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Here, we have tackled the challenge of estimating water flow in areas without direct measurements, a crucial task in hydrology. We have applied deep learning techniques to a large sample of French catchments with various hydrological regimes. We have also compared our approach with traditional methods. We found that incorporating more data improves the accuracy of our deep learning predictions. Notably, our method outperforms traditional approaches in certain regimes, though not universally.
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.
Mohamed S. Abdelhamed, Mohamed E. Elshamy, Saman Razavi, and Howard S. Wheater
The Cryosphere Discuss., https://doi.org/10.5194/tc-2023-20, https://doi.org/10.5194/tc-2023-20, 2023
Preprint withdrawn
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Prior to any climate change assessment, it is necessary to assess the ability of available models to reliably reproduce observed permafrost and hydrology. Following a progressive approach, various model set-ups were developed and evaluated against different data sources. The study shows that different model set-ups favour different sources of data and it is challenging to configure a model faithful to all data sources, which are at times inconsistent with each other.
Mohammad Ghoreishi, Amin Elshorbagy, Saman Razavi, Günter Blöschl, Murugesu Sivapalan, and Ahmed Abdelkader
Hydrol. Earth Syst. Sci., 27, 1201–1219, https://doi.org/10.5194/hess-27-1201-2023, https://doi.org/10.5194/hess-27-1201-2023, 2023
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The study proposes a quantitative model of the willingness to cooperate in the Eastern Nile River basin. Our results suggest that the 2008 food crisis may account for Sudan recovering its willingness to cooperate with Ethiopia. Long-term lack of trust among the riparian countries may have reduced basin-wide cooperation. The model can be used to explore the effects of changes in future dam operations and other management decisions on the emergence of basin cooperation.
Chris M. DeBeer, Howard S. Wheater, John W. Pomeroy, Alan G. Barr, Jennifer L. Baltzer, Jill F. Johnstone, Merritt R. Turetsky, Ronald E. Stewart, Masaki Hayashi, Garth van der Kamp, Shawn Marshall, Elizabeth Campbell, Philip Marsh, Sean K. Carey, William L. Quinton, Yanping Li, Saman Razavi, Aaron Berg, Jeffrey J. McDonnell, Christopher Spence, Warren D. Helgason, Andrew M. Ireson, T. Andrew Black, Mohamed Elshamy, Fuad Yassin, Bruce Davison, Allan Howard, Julie M. Thériault, Kevin Shook, Michael N. Demuth, and Alain Pietroniro
Hydrol. Earth Syst. Sci., 25, 1849–1882, https://doi.org/10.5194/hess-25-1849-2021, https://doi.org/10.5194/hess-25-1849-2021, 2021
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This article examines future changes in land cover and hydrological cycling across the interior of western Canada under climate conditions projected for the 21st century. Key insights into the mechanisms and interactions of Earth system and hydrological process responses are presented, and this understanding is used together with model application to provide a synthesis of future change. This has allowed more scientifically informed projections than have hitherto been available.
Zilefac Elvis Asong, Mohamed Ezzat Elshamy, Daniel Princz, Howard Simon Wheater, John Willard Pomeroy, Alain Pietroniro, and Alex Cannon
Earth Syst. Sci. Data, 12, 629–645, https://doi.org/10.5194/essd-12-629-2020, https://doi.org/10.5194/essd-12-629-2020, 2020
Short summary
Short summary
This dataset provides an improved set of forcing data for large-scale hydrological models for climate change impact assessment in the Mackenzie River Basin (MRB). Here, the strengths of two historical datasets were blended to produce a less-biased long-record product for hydrological modelling and climate change impact assessment over the MRB. This product is then used to bias-correct climate projections from the Canadian Regional Climate Model under RCP8.5.
Andrew R. Slaughter and Saman Razavi
Earth Syst. Sci. Data, 12, 231–243, https://doi.org/10.5194/essd-12-231-2020, https://doi.org/10.5194/essd-12-231-2020, 2020
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Water management faces the challenge of non-stationarity in future flows. To extend flow datasets beyond the gauging data, this study presents a method of generating an ensemble of weekly flows from tree-ring reconstructed flows to represent uncertainty that can overcome certain long-standing data challenges with paleo-reconstruction. An ensemble of 500 flow time series were generated for the four sub-basins of the Saskatchewan River basin, Canada, for the period 1600–2001.
Christopher B. Marsh, John W. Pomeroy, and Howard S. Wheater
Geosci. Model Dev., 13, 225–247, https://doi.org/10.5194/gmd-13-225-2020, https://doi.org/10.5194/gmd-13-225-2020, 2020
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The Canadian Hydrological Model (CHM) is a next-generation distributed model. Although designed to be applied generally, it has a focus for application where cold-region processes, such as snowpacks, play a role in hydrology. A key feature is that it uses a multi-scale surface representation, increasing efficiency. It also enables algorithm comparisons in a flexible structure. Model philosophy, design, and several cold-region-specific examples are described.
Razi Sheikholeslami, Saman Razavi, and Amin Haghnegahdar
Geosci. Model Dev., 12, 4275–4296, https://doi.org/10.5194/gmd-12-4275-2019, https://doi.org/10.5194/gmd-12-4275-2019, 2019
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The ever-growing complexity of Earth and environmental system models can pose many types of software development and implementation issues such as parameter-induced simulation crashes, which are mainly caused by the violation of numerical stability conditions. Here, we introduce a new approach to handle crashed simulations when performing sensitivity analysis. Our results show that this approach can comply well with the dimensionality of the model, sample size, and the number of crashes.
Fuad Yassin, Saman Razavi, Mohamed Elshamy, Bruce Davison, Gonzalo Sapriza-Azuri, and Howard Wheater
Hydrol. Earth Syst. Sci., 23, 3735–3764, https://doi.org/10.5194/hess-23-3735-2019, https://doi.org/10.5194/hess-23-3735-2019, 2019
Zilefac Elvis Asong, Mohamed Elshamy, Daniel Princz, Howard Wheater, John Pomeroy, Alain Pietroniro, and Alex Cannon
Hydrol. Earth Syst. Sci. Discuss., https://doi.org/10.5194/hess-2019-249, https://doi.org/10.5194/hess-2019-249, 2019
Publication in HESS not foreseen
Fuad Yassin, Saman Razavi, Jefferson S. Wong, Alain Pietroniro, and Howard Wheater
Hydrol. Earth Syst. Sci. Discuss., https://doi.org/10.5194/hess-2019-207, https://doi.org/10.5194/hess-2019-207, 2019
Preprint withdrawn
William Quinton, Aaron Berg, Michael Braverman, Olivia Carpino, Laura Chasmer, Ryan Connon, James Craig, Élise Devoie, Masaki Hayashi, Kristine Haynes, David Olefeldt, Alain Pietroniro, Fereidoun Rezanezhad, Robert Schincariol, and Oliver Sonnentag
Hydrol. Earth Syst. Sci., 23, 2015–2039, https://doi.org/10.5194/hess-23-2015-2019, https://doi.org/10.5194/hess-23-2015-2019, 2019
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This paper synthesizes nearly three decades of eco-hydrological field and modelling studies at Scotty Creek, Northwest Territories, Canada, highlighting the key insights into the major water flux and storage processes operating within and between the major land cover types of this wetland-dominated region of discontinuous permafrost. It also examines the rate and pattern of permafrost-thaw-induced land cover change and how such changes will affect the hydrology and water resources of the region.
Bruce Davison, Vincent Fortin, Alain Pietroniro, Man K. Yau, and Robert Leconte
Hydrol. Earth Syst. Sci., 23, 741–762, https://doi.org/10.5194/hess-23-741-2019, https://doi.org/10.5194/hess-23-741-2019, 2019
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This paper explores a new method of predicting streamflow using a complex model. It makes use of streamflow observations to reduce an existing ensemble of model runs for predictive purposes. The study illustrated that the method could work given the proper constraints, which were only possible if there was enough knowledge about how the river responded to precipitation in the previous months. Ideas were discussed to allow the method to be used in a way to predict future streamflow.
Zilefac Elvis Asong, Howard Simon Wheater, John Willard Pomeroy, Alain Pietroniro, Mohamed Ezzat Elshamy, Daniel Princz, and Alex Cannon
Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2018-128, https://doi.org/10.5194/essd-2018-128, 2018
Preprint withdrawn
Short summary
Short summary
Cold regions hydrology is very sensitive to the impacts of climate warming. We need better hydrological models driven by reliable climate data in order to assess hydrologic responses to climate change. Cold regions often have sparse surface observations, particularly at high elevations that generate a major amount of runoff. We produce a long-term dataset that can be used to better understand and represent the seasonal/inter-annual variability of hydrological fluxes and the the timing of runoff.
Gonzalo Sapriza-Azuri, Pablo Gamazo, Saman Razavi, and Howard S. Wheater
Hydrol. Earth Syst. Sci., 22, 3295–3309, https://doi.org/10.5194/hess-22-3295-2018, https://doi.org/10.5194/hess-22-3295-2018, 2018
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Arctic and subarctic regions are amongst the most susceptible regions on Earth to climate change. There, models require a proper representation of the interactions between climate and hydrology. Typically these model represent the soil with shallow depths, whereas for cold regions, deep soil is needed. To address this, we run model experiments to characterize the effect of soil depth and temperature soil initialization. Our results demonstrate that 20 m of soil profile is essential.
Zilefac Elvis Asong, Howard Simon Wheater, Barrie Bonsal, Saman Razavi, and Sopan Kurkute
Hydrol. Earth Syst. Sci., 22, 3105–3124, https://doi.org/10.5194/hess-22-3105-2018, https://doi.org/10.5194/hess-22-3105-2018, 2018
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Canada is very susceptible to recurrent droughts, which have damaging impacts on regional water resources and agriculture. However, nationwide drought assessments are currently lacking and impacted by limited ground-based observations. We delineate two major drought regions (Prairies and northern central) over Canada and link drought characteristics to external factors of climate variability. This study helps to determine when the drought events occur, their duration, and how often they occur.
José-Luis Guerrero, Patricia Pernica, Howard Wheater, Murray Mackay, and Chris Spence
Hydrol. Earth Syst. Sci., 21, 6345–6362, https://doi.org/10.5194/hess-21-6345-2017, https://doi.org/10.5194/hess-21-6345-2017, 2017
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Lakes are sentinels of climate change, and an adequate characterization of their feedbacks to the atmosphere could improve climate modeling. These feedbacks, as heat fluxes, can be simulated but are seldom measured, casting doubt on modeling results. Measurements from a small lake in Canada established that the model parameter modulating how much light penetrates the lake dominates model response. This parameter is measurable: improved monitoring could lead to more robust modeling.
Xicai Pan, Warren Helgason, Andrew Ireson, and Howard Wheater
Hydrol. Earth Syst. Sci., 21, 5401–5413, https://doi.org/10.5194/hess-21-5401-2017, https://doi.org/10.5194/hess-21-5401-2017, 2017
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In this paper we present a case study from a heterogeneous pasture site in the Canadian prairies, where we have quantified the various components of the water balance on the field scale, and critically examine some of the simplifying assumptions which are often invoked when applying water budget approaches in applied hydrology. We highlight challenges caused by lateral fluxes of blowing snow and ambiguous partitioning of snow melt water into runoff and infiltration.
Yoshihide Wada, Marc F. P. Bierkens, Ad de Roo, Paul A. Dirmeyer, James S. Famiglietti, Naota Hanasaki, Megan Konar, Junguo Liu, Hannes Müller Schmied, Taikan Oki, Yadu Pokhrel, Murugesu Sivapalan, Tara J. Troy, Albert I. J. M. van Dijk, Tim van Emmerik, Marjolein H. J. Van Huijgevoort, Henny A. J. Van Lanen, Charles J. Vörösmarty, Niko Wanders, and Howard Wheater
Hydrol. Earth Syst. Sci., 21, 4169–4193, https://doi.org/10.5194/hess-21-4169-2017, https://doi.org/10.5194/hess-21-4169-2017, 2017
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Rapidly increasing population and human activities have altered terrestrial water fluxes on an unprecedented scale. Awareness of potential water scarcity led to first global water resource assessments; however, few hydrological models considered the interaction between terrestrial water fluxes and human activities. Our contribution highlights the importance of human activities transforming the Earth's water cycle, and how hydrological models can include such influences in an integrated manner.
Jefferson S. Wong, Saman Razavi, Barrie R. Bonsal, Howard S. Wheater, and Zilefac E. Asong
Hydrol. Earth Syst. Sci., 21, 2163–2185, https://doi.org/10.5194/hess-21-2163-2017, https://doi.org/10.5194/hess-21-2163-2017, 2017
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This study was conducted to quantify the spatial and temporal variability of the errors associated with various gridded precipitation products in Canada. Overall, WFDEI [GPCC] and CaPA performed best with respect to different performance measures, followed by ANUSPLIN and WEDEI [CRU]. Princeton and NARR demonstrated the lowest quality. Comparing the climate model-simulated products, PCIC ensembles generally performed better than NA-CORDEX ensembles in terms of reliability in four seasons.
Chris M. DeBeer, Howard S. Wheater, Sean K. Carey, and Kwok P. Chun
Hydrol. Earth Syst. Sci., 20, 1573–1598, https://doi.org/10.5194/hess-20-1573-2016, https://doi.org/10.5194/hess-20-1573-2016, 2016
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This paper provides a comprehensive review and up-to-date synthesis of the observed changes in air temperature, precipitation, seasonal snow cover, mountain glaciers, permafrost, freshwater ice cover, and river discharge over the interior of western Canada since the mid- or late 20th century. Important long-term observational networks and data sets are described, and qualitative linkages among the changing Earth system components are highlighted.
A. Nazemi and H. S. Wheater
Hydrol. Earth Syst. Sci., 19, 33–61, https://doi.org/10.5194/hess-19-33-2015, https://doi.org/10.5194/hess-19-33-2015, 2015
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Activities related to water resource management perturb terrestrial water cycle with hydrologic and land-atmospheric implications. By defining water resource management as the integration of water demand with water supply and allocation, this paper critically reviews current schemes for representing human water demands in models relevant to Earth system modelling. We conclude that current representations are limited due to uncertainties in data support, demand algorithms and large-scale models.
A. Nazemi and H. S. Wheater
Hydrol. Earth Syst. Sci., 19, 63–90, https://doi.org/10.5194/hess-19-63-2015, https://doi.org/10.5194/hess-19-63-2015, 2015
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Human water supply and allocation are major drivers of change in terrestrial water cycle. Considering current schemes for representing water supply and allocation in large-scale models, we review the state of the art and highlight various sources of uncertainty. Considering the opportunities for improving available schemes, we argue that the time is right for a global initiative based on a set of regional case studies to improve the inclusion of water resource management in large-scale models.
Related subject area
Subject: Catchment hydrology | Techniques and Approaches: Modelling approaches
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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.
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.
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.
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.
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.
Maik Renner and Corina Hauffe
Hydrol. Earth Syst. Sci. Discuss., https://doi.org/10.5194/hess-2024-6, https://doi.org/10.5194/hess-2024-6, 2024
Revised manuscript accepted for HESS
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Climate and land-surface conditions influence the availability of fresh water resources. Their impact is quantified with data of 71 catchments in Saxony/Germany, for which distinct signatures in the joint water and energy budgets are found: (i) past forest dieback caused a decrease 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.
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.
Huy Dang and Yadu Pokhrel
EGUsphere, https://doi.org/10.5194/egusphere-2023-3158, https://doi.org/10.5194/egusphere-2023-3158, 2024
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By examining basin-wide simulations of the 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 Mekong’s flow regime and annual flooding patterns at major downstream areas in recent years. These findings could help rethink the planning of future dams and water resource management in the MRB.
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.
Diego Araya, Pablo A. Mendoza, Eduardo Muñoz-Castro, and James McPhee
Hydrol. Earth Syst. Sci., 27, 4385–4408, https://doi.org/10.5194/hess-27-4385-2023, https://doi.org/10.5194/hess-27-4385-2023, 2023
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Dynamical systems are used by many agencies worldwide to produce seasonal streamflow forecasts, which are critical for decision-making. Such systems rely on hydrology models, which contain parameters that are typically estimated using a target performance metric (i.e., objective function). This study explores the effects of this decision across mountainous basins in Chile, illustrating tradeoffs between seasonal forecast quality and the models' capability to simulate streamflow characteristics.
Pamela E. Tetford and Joseph R. Desloges
Hydrol. Earth Syst. Sci., 27, 3977–3998, https://doi.org/10.5194/hess-27-3977-2023, https://doi.org/10.5194/hess-27-3977-2023, 2023
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An efficient regional flood frequency model relates drainage area to discharge, with a major assumption of similar basin conditions. In a landscape with variable glacial deposits and land use, we characterize varying hydrological function using 28 explanatory variables. We demonstrate that (1) a heterogeneous landscape requires objective model selection criteria to optimize the fit of flow data, and (2) incorporating land use as a predictor variable improves the drainage area to discharge model.
Yalan Song, Wouter J. M. Knoben, Martyn P. Clark, Dapeng Feng, Kathryn E. Lawson, and Chaopeng Shen
Hydrol. Earth Syst. Sci. Discuss., https://doi.org/10.5194/hess-2023-258, https://doi.org/10.5194/hess-2023-258, 2023
Revised manuscript accepted for HESS
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Wouldn't it be nice to have both the accuracy of neural networks (NNs) and the interpretability of process-based models (PBMs)? Differentiable modeling gives you the best of both worlds by connecting NNs with PBMs. However, there was previously a major issue that iterative solution schemes would run into memory use trouble. This paper presents an operator called adjoint, which liberates all the iterative solvers. This is the first time adjoint is applied to large-scale hydrologic modeling.
Ana Ramos Oliveira, Tiago Brito Ramos, Lígia Pinto, and Ramiro Neves
Hydrol. Earth Syst. Sci., 27, 3875–3893, https://doi.org/10.5194/hess-27-3875-2023, https://doi.org/10.5194/hess-27-3875-2023, 2023
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This paper intends to demonstrate the adequacy of a hybrid solution to overcome the difficulties related to the incorporation of human behavior when modeling hydrological processes. Two models were implemented, one to estimate the outflow of a reservoir and the other to simulate the hydrological processes of the watershed. With both models feeding each other, results show that the proposed approach significantly improved the streamflow estimation downstream of the reservoir.
Yongshin Lee, Francesca Pianosi, Andres Peñuela, and Miguel Angel Rico-Ramirez
EGUsphere, https://doi.org/10.5194/egusphere-2023-2169, https://doi.org/10.5194/egusphere-2023-2169, 2023
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Following recent advancements in weather prediction technology, we explored how seasonal weather forecasts (one 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.
Zhihua He, Kevin Shook, Christopher Spence, John W. Pomeroy, and Colin Whitfield
Hydrol. Earth Syst. Sci., 27, 3525–3546, https://doi.org/10.5194/hess-27-3525-2023, https://doi.org/10.5194/hess-27-3525-2023, 2023
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This study evaluated the impacts of climate change on snowmelt, soil moisture, and streamflow over the Canadian Prairies. The entire prairie region was divided into seven basin types. We found strong variations of hydrological sensitivity to precipitation and temperature changes in different land covers and basins, which suggests that different water management and adaptation methods are needed to address enhanced water stress due to expected climate change in different regions of the prairies.
Nicolás Cortés-Salazar, Nicolás Vásquez, Naoki Mizukami, Pablo A. Mendoza, and Ximena Vargas
Hydrol. Earth Syst. Sci., 27, 3505–3524, https://doi.org/10.5194/hess-27-3505-2023, https://doi.org/10.5194/hess-27-3505-2023, 2023
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This paper shows how important river models can be for water resource applications that involve hydrological models and, in particular, parameter calibration. To this end, we conduct numerical experiments in a pilot basin using a combination of hydrologic model simulations obtained from a large sample of parameter sets and different routing methods. We find that routing can affect streamflow simulations, even at monthly time steps; the choice of parameters; and relevant streamflow metrics.
Dung Trung Vu, Thanh Duc Dang, Francesca Pianosi, and Stefano Galelli
Hydrol. Earth Syst. Sci., 27, 3485–3504, https://doi.org/10.5194/hess-27-3485-2023, https://doi.org/10.5194/hess-27-3485-2023, 2023
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The calibration of hydrological models over extensive spatial domains is often challenged by the lack of data on river discharge and the operations of hydraulic infrastructures. Here, we use satellite data to address the lack of data that could unintentionally bias the calibration process. Our study is underpinned by a computational framework that quantifies this bias and provides a safe approach to the calibration of models in poorly gauged and heavily regulated basins.
Francesco Fatone, Bartosz Szeląg, Przemysław Kowal, Arthur McGarity, Adam Kiczko, Grzegorz Wałek, Ewa Wojciechowska, Michał Stachura, and Nicolas Caradot
Hydrol. Earth Syst. Sci., 27, 3329–3349, https://doi.org/10.5194/hess-27-3329-2023, https://doi.org/10.5194/hess-27-3329-2023, 2023
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A novel methodology for the development of a stormwater network performance simulator including advanced risk assessment was proposed. The applied tool enables the analysis of the influence of spatial variability in catchment and stormwater network characteristics on the relation between (SWMM) model parameters and specific flood volume, as an alternative approach to mechanistic models. The proposed method can be used at the stage of catchment model development and spatial planning management.
Olivier Delaigue, Pierre Brigode, Guillaume Thirel, and Laurent Coron
Hydrol. Earth Syst. Sci., 27, 3293–3327, https://doi.org/10.5194/hess-27-3293-2023, https://doi.org/10.5194/hess-27-3293-2023, 2023
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Teaching hydrological modeling is an important, but difficult, matter. It requires appropriate tools and teaching material. In this article, we present the airGRteaching package, which is an open-source software tool relying on widely used hydrological models. This tool proposes an interface and numerous hydrological modeling exercises representing a wide range of hydrological applications. We show how this tool can be applied to simple but real-life cases.
Florian Willkofer, Raul Roger Wood, and Ralf Ludwig
EGUsphere, https://doi.org/10.5194/egusphere-2023-2019, https://doi.org/10.5194/egusphere-2023-2019, 2023
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Severe flood events pose threat to riverine areas, yet robust estimates about the dynamics of these events in the future due to climate change are rarely available. Hence, this study uses and benefits from data from a RCM SMILE to drive a high-resolution hydrological model for 98 catchments of the Hydrological Bavaria to exploit 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.
Mariam Khanam, Giulia Sofia, and Emmanouil N. Anagnostou
EGUsphere, https://doi.org/10.5194/egusphere-2023-1969, https://doi.org/10.5194/egusphere-2023-1969, 2023
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Due to climate change, flooding is expected to become more frequent globally in the coming decades. Locally, storm-induced channel geometry changes can drastically affect flood hazards, yet rivers are mostly treated as static elements in flood studies. This study tried to gain an understanding of the effects of major storm events on future flood hazards, promoting a framework for incorporating channel conveyance adjustments into flood hazard assessment.
Siyuan Wang, Markus Hrachowitz, Gerrit Schoups, and Christine Stumpp
Hydrol. Earth Syst. Sci., 27, 3083–3114, https://doi.org/10.5194/hess-27-3083-2023, https://doi.org/10.5194/hess-27-3083-2023, 2023
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This study shows that previously reported underestimations of water ages are most likely not due to the use of seasonally variable tracers. Rather, these underestimations can be largely attributed to the choices of model approaches which rely on assumptions not frequently met in catchment hydrology. We therefore strongly advocate avoiding the use of this model type in combination with seasonally variable tracers and instead adopting StorAge Selection (SAS)-based or comparable model formulations.
Louise Akemi Kuana, Arlan Scortegagna Almeida, Emilio Graciliano Ferreira Mercuri, and Steffen Manfred Noe
EGUsphere, https://doi.org/10.5194/egusphere-2023-1755, https://doi.org/10.5194/egusphere-2023-1755, 2023
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The authors compared different regionalization methods for river flow prediction in watersheds with few data. We collected data on precipitation, evapotranspiration, river flow, and geographical and climatic factors for 126 catchments in the Paraná state, Brazil. The regionalization method based on physiographic-climatic similarity showed to be the most robust for predicting daily and Q95 reference flow. We also found patterns in data, grouping locations based on similarities.
Arianna Borriero, Rohini Kumar, Tam V. Nguyen, Jan H. Fleckenstein, and Stefanie R. Lutz
Hydrol. Earth Syst. Sci., 27, 2989–3004, https://doi.org/10.5194/hess-27-2989-2023, https://doi.org/10.5194/hess-27-2989-2023, 2023
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We analyzed the uncertainty of the water transit time distribution (TTD) arising from model input (interpolated tracer data) and structure (StorAge Selection, SAS, functions). We found that uncertainty was mainly associated with temporal interpolation, choice of SAS function, nonspatial interpolation, and low-flow conditions. It is important to characterize the specific uncertainty sources and their combined effects on TTD, as this has relevant implications for both water quantity and quality.
Yves Tramblay, Patrick Arnaud, Guillaume Artigue, Michel Lang, Emmanuel Paquet, Luc Neppel, and Eric Sauquet
Hydrol. Earth Syst. Sci., 27, 2973–2987, https://doi.org/10.5194/hess-27-2973-2023, https://doi.org/10.5194/hess-27-2973-2023, 2023
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Mediterranean floods are causing major damage, and recent studies have shown that, despite the increase in intense rainfall, there has been no increase in river floods. This study reveals that the seasonality of floods changed in the Mediterranean Basin during 1959–2021. There was also an increased frequency of floods linked to short episodes of intense rain, associated with a decrease in soil moisture. These changes need to be taken into consideration to adapt flood warning systems.
Yanfeng Wu, Jingxuan Sun, Boting Hu, Y. Jun Xu, Alain N. Rousseau, and Guangxin Zhang
Hydrol. Earth Syst. Sci., 27, 2725–2745, https://doi.org/10.5194/hess-27-2725-2023, https://doi.org/10.5194/hess-27-2725-2023, 2023
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Reservoirs and wetlands are important regulators of watershed hydrology, which should be considered when projecting floods and droughts. We first coupled wetlands and reservoir operations into a semi-spatially-explicit hydrological model and then applied it in a case study involving a large river basin in northeast China. We found that, overall, the risk of future floods and droughts will increase further even under the combined influence of reservoirs and wetlands.
Peishi Jiang, Pin Shuai, Alexander Sun, Maruti K. Mudunuru, and Xingyuan Chen
Hydrol. Earth Syst. Sci., 27, 2621–2644, https://doi.org/10.5194/hess-27-2621-2023, https://doi.org/10.5194/hess-27-2621-2023, 2023
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We developed a novel deep learning approach to estimate the parameters of a computationally expensive hydrological model on only a few hundred realizations. Our approach leverages the knowledge obtained by data-driven analysis to guide the design of the deep learning model used for parameter estimation. We demonstrate this approach by calibrating a state-of-the-art hydrological model against streamflow and evapotranspiration observations at a snow-dominated watershed in Colorado.
Guillaume Cinkus, Naomi Mazzilli, Hervé Jourde, Andreas Wunsch, Tanja Liesch, Nataša Ravbar, Zhao Chen, and Nico Goldscheider
Hydrol. Earth Syst. Sci., 27, 2397–2411, https://doi.org/10.5194/hess-27-2397-2023, https://doi.org/10.5194/hess-27-2397-2023, 2023
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The Kling–Gupta Efficiency (KGE) is a performance criterion extensively used to evaluate hydrological models. We conduct a critical study on the KGE and its variant to examine counterbalancing errors. Results show that, when assessing a simulation, concurrent over- and underestimation of discharge can lead to an overall higher criterion score without an associated increase in model relevance. We suggest that one carefully choose performance criteria and use scaling factors.
Cited articles
Alexeev, V. A., Nicolsky, D. J., Romanovsky, V. E., and Lawrence, D. M.: An
evaluation of deep soil configurations in the CLM3 for improved
representation of permafrost, Geophys. Res. Lett., 34, L09502,
https://doi.org/10.1029/2007GL029536, 2007.
Arboleda-Obando, P.: Determinando los efectos del cambio climático y del
cambio en usos del suelo en la Macro Cuenca Magdalena Cauca utilizando el
modelo de suelo-superficie e hidrológico MESH, available at:
http://bdigital.unal.edu.co/69823/1/1018438123.2018.pdf (last access: 18 April
2019), 2018.
Bachu, S.: Basement heat flow in the Western Canada Sedimentary Basin,
Tectonophysics, 222, 119–133, https://doi.org/10.1016/0040-1951(93)90194-O, 1993.
Bahremand, A., Razavi, S., Pietroniro, A., Haghnegahdar, A., Princz, D.,
Gharari, S., Elshamy, M., and Tesemma, Z.: Application of MESH Land
Surface-Hydrology Model to a Large River Basin in Iran Model Prospective
works, in: Canadian Geophysical Union General Assembly, 10–14 June 2018, Niagara Falls, Canada, p. 3, 2018.
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.
Bonsal, B. R., Peters, D. L., Seglenieks, F., Rivera, A., and Berg, A.:
Changes in freshwater availability across Canada, in: Canada's Changing
Climate Report, 261–342, available at:
https://www.nrcan.gc.ca/sites/www.nrcan.gc.ca/files/energy/Climate-change/pdf/CCCR-Chapter6-ChangesInFreshwaterAvailabilityAcrossCanada.pdf, last access: 27 August 2019.
Burke, E. J., Dankers, R., Jones, C. D., and Wiltshire, A. J.: A
retrospective analysis of pan Arctic permafrost using the JULES land surface
model, Clim. Dynam., 41, 1025–1038, https://doi.org/10.1007/s00382-012-1648-x,
2013.
Burn, C. R. and Nelson, F. E.: Comment on “A projection of severe
near-surface permafrost degradation during the 21st century” by David M.
Lawrence and Andrew G. Slater, Geophys. Res. Lett., 33, L21503,
https://doi.org/10.1029/2006gl027077, 2006.
Calmels, F., Laurent, C., Brown, R., Pivot, F., and Ireland, M.: How
Permafrost Thaw May Impact Food Security of Jean Marie River First Nation,
NWT, GeoQuebec 2015 Conf. Pap., 20–23 September 2015, Quebec City, Canada, 2015.
Canada Centre for Remote Sensing (CCRS), Nacional para el Conocimiento y Uso
de la Biodiversidad (CONABIO), Comisión Nacional Forestal (CONAFOR),
Insituto Nacional de Estadística y Geografía (INEGI), and U.S.
Geological Survey (USGS): 2005 North American Land Cover at 250 m spatial
resolution, available at:
http://www.cec.org/tools-and-resources/map-files/land-cover-2005 (last access: 15 January 2016), 2010.
Centre for Land and Biological Resources Research: Soil Landscapes of Canada, v.2.2, Research Branch, Agriculture and Agri-Food Canada, Ottawa, Canada, 1996.
Changwei, X. and Gough, W. A.: A Simple Thaw-Freeze Algorithm for a
Multi-Layered Soil using the Stefan Equation, Permafrost Periglac.,
24, 252–260, https://doi.org/10.1002/ppp.1770, 2013.
Côté, J., Gravel, S., Méthot, A., Patoine, A., Roch, M.,
Staniforth, A., Côté, J., Gravel, S., Méthot, A., Patoine, A.,
Roch, M., and Staniforth, A.: The Operational CMC–MRB Global Environmental
Multiscale (GEM) Model. Part I: Design Considerations and Formulation, Mon.
Weather Rev., 126, 1373–1395, https://doi.org/10.1175/1520-0493(1998)126<1373:TOCMGE>2.0.CO;2, 1998a.
Côté, J., Desmarais, J.-G., Gravel, S., Méthot, A., Patoine, A.,
Staniforth, A., and Roch, M.: The Operational CMC – MRB Global Environmental
Multiscale (GEM) Model. Part II: Results, Mon. Weather Rev., 126,
1397–1418, https://doi.org/10.1175/1520-0493(1998)126<1397:TOCMGE>2.0.CO;2, 1998b.
Dankers, R., Burke, E. J., and Price, J.: Simulation of permafrost and seasonal thaw depth in the JULES land surface scheme, The Cryosphere, 5, 773–790, https://doi.org/10.5194/tc-5-773-2011, 2011.
DeBeer, C. M., Wheater, H. S., Carey, S. K., and Chun, K. P.: Recent climatic, cryospheric, and hydrological changes over the interior of western Canada: a review and synthesis, Hydrol. Earth Syst. Sci., 20, 1573–1598, https://doi.org/10.5194/hess-20-1573-2016, 2016.
Dobinski, W.: Permafrost, Earth-Sci. Rev., 108, 158–169,
https://doi.org/10.1016/J.EARSCIREV.2011.06.007, 2011.
Duan, L., Man, X., Kurylyk, B. L., and Cai, T.: Increasing winter baseflow in
response to permafrost thaw and precipitation regime shifts in northeastern
China, Water, 9, 25, https://doi.org/10.3390/w9010025, 2017.
Durocher, M., Requena, A. I., Burn, D. H., and Pellerin, J.: Analysis of
trends in annual streamflow to the Arctic Ocean, Hydrol. Process., 33,
1143–1151, https://doi.org/10.1002/hyp.13392, 2019.
Ednie, M., Wright, J. F., and Duchesne, C.: Establishing initial conditions
for transient ground thermal modeling in the Mackenzie Valley: a
paleo-climatic reconstruction approach, in: Proceedings of the Ninth
International Conference on Permafrost, edited by: Kane, D. L. and Hinkel, K. M., 29 June–3 July 2008, Institute of Northern Engineering, University of Alaska
Fairbanks, Fairbanks, Alaska, USA,
403–408, 2008.
Elshamy, M. E., Pietroniro, A., and Wheater, H. S.: Development and validation of a large-scale hydrological land surface model for the Mackenzie River Basin, in preparation, 2020.
Garland, G. D. and Lennox, D. H.: Heat Flow in Western Canada, Geophys. J.
Roy. Astr. S., 6, 245–262, https://doi.org/10.1111/j.1365-246X.1962.tb02979.x,
1962.
Haghnegahdar, A., Tolson, B. A., Craig, J. R., and Paya, K. T.: Assessing the
performance of a semi-distributed hydrological model under various watershed
discretization schemes, Hydrol. Process., 29, 4018–4031,
https://doi.org/10.1002/hyp.10550, 2015.
Hegginbottom, J. A., Dubreuil, M. A., and Harker, P. T.: Permafrost, in:
National Atlas of Canada, MCR 4177, Natural Resources Canada, https://doi.org/10.4095/294765, 1995.
Husain, S. Z., Alavi, N., Bélair, S., Carrera, M., Zhang, S., Fortin,
V., Abrahamowicz, M., Gauthier, N., Husain, S. Z., Alavi, N., Bélair,
S., Carrera, M., Zhang, S., Fortin, V., Abrahamowicz, M., and Gauthier, N.:
The Multibudget Soil, Vegetation, and Snow (SVS) Scheme for Land Surface
Parameterization: Offline Warm Season Evaluation, J. Hydrometeorol., 17,
2293–2313, https://doi.org/10.1175/JHM-D-15-0228.1, 2016.
IPCC: Climate Change 2014 Impacts, Adaptation, and Vulnerability Part B:
Regional Aspects, edited by: Barros, V. R., Field, C. B., Dokken, D. J.,
Mastrandrea, M. D., Mach, K. J., Bilir, T. E., Chatterjee, M., Ebi, K. L.,
Estrada, Y. O., Genova, R. C., Girma, B., Kissel, E. S., Levy, A. N., MacCracken, S., Mastrandrea, P.
R., and White, L. L., Cambridge University Press, Cambridge,
UK and New York, NY, USA, 2014.
Keshav, K., Haghnegahdar, A., Elshamy, M., Gharari, S., and Razavi, S.:
Aggregated gridded soil texture dataset for Mackenzie and Nelson-Churchill
River Basins, Federated Research Data Repository (FRDR), Canada, https://doi.org/10.20383/101.0154, 2019a.
Keshav, K., Haghnegahdar, A., Elshamy, M., Gharari, S., and Razavi, S.:
Bedrock depth dataset for Nelson-Churchill and Mackenzie River Basin based
on bedrock data by Shangguan et al. (2016), Federated Research Data Repository (FRDR), Canada,
https://doi.org/10.20383/101.0152, 2019b.
Kouwen, N.: WATFLOOD: a Micro-Computer Based Flood Forecasting System Based
on Real-Time Weather Radar, Can. Water Resour. J., 13, 62–77,
https://doi.org/10.4296/cwrj1301062, 1988.
Kouwen, N., Soulis, E. D., Pietroniro, A., Donald, J., and Harrington, R. A.:
Grouped Response Units for Distributed Hydrologic Modeling, J. Water Resour.
Plan. Manag., 119, 289–305, https://doi.org/10.1061/(ASCE)0733-9496(1993)119:3(289),
1993.
Krogh, S. A., Pomeroy, J. W., and Marsh, P.: Diagnosis of the hydrology of a
small Arctic basin at the tundra-taiga transition using a physically based
hydrological model, J. Hydrol., 550, 685–703,
https://doi.org/10.1016/j.jhydrol.2017.05.042, 2017.
Kujala, K., Seppälä, M., and Holappa, T.: Physical properties of peat
and palsa formation, Cold Reg. Sci. Technol., 52, 408–414,
https://doi.org/10.1016/j.coldregions.2007.08.002, 2008.
Lawrence, D. M. and Slater, A. G.: A projection of severe near-surface
permafrost degradation during the 21st century, Geophys. Res. Lett., 32,
L24401, https://doi.org/10.1029/2005GL025080, 2005.
Lawrence, D. M., Slater, A. G., Romanovsky, V. E., and Nicolsky, D. J.:
Sensitivity of a model projection of near-surface permafrost degradation to
soil column depth and representation of soil organic matter, J. Geophys.
Res.-Earth, 113, 1–14, https://doi.org/10.1029/2007JF000883, 2008.
Lawrence, D. M., Slater, A. G., and Swenson, S. C.: Simulation of present-day
and future permafrost and seasonally frozen ground conditions in CCSM4, J.
Climate, 25, 2207–2225, https://doi.org/10.1175/JCLI-D-11-00334.1, 2012.
Letts, M. G., Roulet, N. T., Comer, N. T., Skarupa, M. R., and Verseghy, D.
L.: Parameterization of Peatland Hydraulic Properties for the Canadian Land
Surface Scheme, Atmos.-Ocean, 38, 141–160, https://doi.org/10.1080/07055900.2000.9649643,
2000.
Luo, Y., Arnold, J., Allen, P., and Chen, X.: Baseflow simulation using SWAT model in an inland river basin in Tianshan Mountains, Northwest China, Hydrol. Earth Syst. Sci., 16, 1259–1267, https://doi.org/10.5194/hess-16-1259-2012, 2012.
Mahfouf, J.-F., Brasnett, B., and Gagnon, S.: A Canadian Precipitation
Analysis (CaPA) Project: Description and Preliminary Results,
Atmos.-Ocean, 45, 1–17, https://doi.org/10.3137/ao.v450101, 2007.
McBean, G., Alekseev, G., Chen, D., Førland, E., Fyfe, J., Groisman, P.
Y., King, R., Melling, H., Vose, R., and H.Whitfield, P.: Arctic Climate:
Past and Present, in: Impacts of a Warming Arctic: Arctic Climate Impact
Assessment, Cambridge University Press, Canada, p. 140, 2005.
Nicolsky, D. J., Romanovsky, V. E., Alexeev, V. A., and Lawrence, D. M.:
Improved modeling of permafrost dynamics in a GCM land-surface scheme,
Geophys. Res. Lett., 34, 2–6, https://doi.org/10.1029/2007GL029525, 2007.
Nishimura, S., Martin, C. J., Jardine, R. J., and Fenton, C. H.: A new
approach for assessing geothermal response to climate change in permafrost
regions, Geotechnique, 59, 213–227, https://doi.org/10.1680/geot.2009.59.3.213,
2009.
Oleson, K. W., Lawrence, D. M., Bonan, G. B., Drewniak, B., Huang, M.,
Charles, D., Levis, S., Li, F., Riley, W. J., Zachary, M., Swenson, S. C.,
Thornton, P. E., Bozbiyik, A., Fisher, R., Heald, C. L., Kluzek, E.,
Lamarque, F., Lawrence, P. J., Leung, L. R., Muszala, S., Ricciuto, D. M.,
and Sacks, W.: Technical Description of version 4.5 of the Community Land
Model (CLM), National Center For Atmospheric Research, Boulder, Colorado, USA, 2013.
Park, H., Iijima, Y., Yabuki, H., Ohta, T., Walsh, J., Kodama, Y., and Ohata,
T.: The application of a coupled hydrological and biogeochemical model
(CHANGE) for modeling of energy, water, and CO2 exchanges over a larch
forest in eastern Siberia, J. Geophys. Res., 116, D15102,
https://doi.org/10.1029/2010JD015386, 2011.
Park, H., Walsh, J., Fedorov, A. N., Sherstiukov, A. B., Iijima, Y., and Ohata, T.: The influence of climate and hydrological variables on opposite anomaly in active-layer thickness between Eurasian and North American watersheds, The Cryosphere, 7, 631–645, https://doi.org/10.5194/tc-7-631-2013, 2013.
Park, H., Sherstiukov, A. B., Fedorov, A. N., Polyakov, I. V., and Walsh, J.
E.: An observation-based assessment of the influences of air temperature and
snow depth on soil temperature in Russia, Environ. Res. Lett., 9, 064026,
https://doi.org/10.1088/1748-9326/9/6/064026, 2014.
Pietroniro, A., Fortin, V., Kouwen, N., Neal, C., Turcotte, R., Davison, B., Verseghy, D., Soulis, E. D., Caldwell, R., Evora, N., and Pellerin, P.: Development of the MESH modelling system for hydrological ensemble forecasting of the Laurentian Great Lakes at the regional scale, Hydrol. Earth Syst. Sci., 11, 1279–1294, https://doi.org/10.5194/hess-11-1279-2007, 2007.
Pomeroy, J. W., Gray, D. M., Brown, T., Hedstrom, N. R., Quinton, W. L.,
Granger, R. J., and Carey, S. K.: The cold regions hydrological model: a
platform for basing process representation and model structure on physical
evidence, Hydrol. Process., 21, 2650–2667, https://doi.org/10.1002/hyp.6787, 2007.
Quinton, W. L. and Marsh, P.: A conceptual framework for runoff generation
in a permafrost environment, Hydrol. Process., 13, 2563–2581,
https://doi.org/10.1002/(SICI)1099-1085(199911)13:16<2563::AID-HYP942>3.0.CO;2-D, 1999.
Quinton, W. L., Hayashi, M., and Chasmer, L. E.: Permafrost-thaw-induced
land-cover change in the Canadian subarctic: implications for water
resources, Hydrol. Process., 25, 152–158, https://doi.org/10.1002/hyp.7894, 2011.
Razavi, S., Elshorbagy, A., Wheater, H., and Sauchyn, D.: Toward
understanding nonstationarity in climate and hydrology through tree ring
proxy records, Water Resour. Res., 51, 1813–1830,
https://doi.org/10.1002/2014WR015696, 2015.
Riseborough, D., Shiklomanov, N., Etzelmüller, B., Gruber, S., and
Marchenko, S.: Recent advances in permafrost modelling, Permafrost Periglac., 19, 137–156, https://doi.org/10.1002/ppp.615, 2008.
Romanovsky, V. E. and Osterkamp, T. E.: Interannual variations of the
thermal regime of the active layer and near-surface permafrost in northern
Alaska, Permafrost Periglac., 6, 313–335,
https://doi.org/10.1002/ppp.3430060404, 1995.
Sapriza-Azuri, G., Gamazo, P., Razavi, S., and Wheater, H. S.: On the appropriate definition of soil profile configuration and initial conditions for land surface–hydrology models in cold regions, Hydrol. Earth Syst. Sci., 22, 3295–3309, https://doi.org/10.5194/hess-22-3295-2018, 2018.
Shangguan, W., Hengl, T., Mendes de Jesus, J., Yuan, H., and Dai, Y.: Mapping
the global depth to bedrock for land surface modeling, J. Adv. Model. Earth
Syst., 9, 65–88, https://doi.org/10.1002/2016MS000686, 2017.
Sheffield, J., Goteti, G., and Wood, E. F.: Development of a 50-year
high-resolution global dataset of meteorological forcings for land surface
modeling, J. Climate, 19, 3088–3111, https://doi.org/10.1175/JCLI3790.1, 2006.
Smith, S. L. and Burgess, M.: Ground Temperature Database for Northern
Canada, Geological Survey of Canada Open File Report 3954, October 2000, Ottawa, Canada, 2000.
Smith, S. L. and Burgess, M. M.: A digital database of permafrost thickness
in Canada, Geological Survey of Canada Open File 4173, Ottawa, Canada, 2002.
Smith, S. L., Burgess, M. M., Riseborough, D., Coultish, T., and Chartrand,
J.: Digital summary database of permafrost and thermal conditions - Norman
Wells pipeline study sites, Geol. Surv. Canada, Open File 4635, 4635,
1–104, https://doi.org/10.4095/215482, 2004.
Smith, S. L., Ye, S., and Ednie, M.: Enhancement of permafrost monitoring network and collection of baseline environmental data between Fort Good Hope and Norman Wells, Northwest Territories, Geological Survey of Canada, Current Research 2007-B7, 1–10, Ottawa, Canada, 2007.
Smith, S. L., Riseborough, D. W., Nixon, F. M., Chartrand, J., Duchesne, C.,
and Ednie, M.: Data for Geological Survey of Canada Active Layer Monitoring
Sites in the Mackenzie Valley, N.W.T., Geological Survey Of Canada Open File 6287, Ottawa, Canada, 2009.
Smith, S. L., Chartrand, J., Duchesne, C., and Ednie, M.: Report on 2015
field activities and collection of ground thermal and active layer data in
the Mackenzie corridor, Northwest Territories, Geol. Surv. Canada Open File
8125, https://doi.org/10.4095/292864, 2016.
Soil Classification Working Group: The Canadian system of soil classification, 3rd edn., NRC Research Press, Ottawa, Canada, available at: http://sis.agr.gc.ca/cansis/publications/manuals/1998-cssc-ed3/cssc3_manual.pdf (last access: 17 April 2019), 1998.
Soulis, E. D. E., Snelgrove, K. K. R., Kouwen, N., Seglenieks, F., and
Verseghy, D. L. D.: Towards closing the vertical water balance in Canadian
atmospheric models: Coupling of the land surface scheme class with the
distributed hydrological model watflood, Atmos.-Ocean, 38, 251–269,
https://doi.org/10.1080/07055900.2000.9649648, 2000.
St. Jacques, J. M. and Sauchyn, D. J.: Increasing winter baseflow and mean
annual streamflow from possible permafrost thawing in the Northwest
Territories, Canada, Geophys. Res. Lett., 36, L01401,
https://doi.org/10.1029/2008GL035822, 2009.
Swenson, S. C., Lawrence, D. M., and Lee, H.: Improved simulation of the
terrestrial hydrological cycle in permafrost regions by the Community Land
Model, J. Adv. Model. Earth Syst., 4, 1–15, https://doi.org/10.1029/2012MS000165,
2012.
Szeicz, J. M. and MacDonald, G. M.: Dendroclimatic Reconstruction of Summer
Temperatures in Northwestern Canada since A.D. 1638 Based on Age-Dependent
Modeling, Quaternary Res., 44, 257–266, https://doi.org/10.1006/qres.1995.1070, 1995.
University of Saskatchewan: MESH – A Community Hydrology – Land Surface Model (Releases), available at: https://wiki.usask.ca/display/MESH/Releases, last access: 21 January 2019.
van Everdingen, R. O.: Multi-language Glossary of Permafrost and Related Ground-Ice Terms, International Permafrost Association, The Arctic Institute of North America, University of Calgary, Calgary, Canada,
2005.
Verseghy, D.: CLASS – The Canadian land surface scheme (version 3.6) -
technical documentation, Intern. report, Clim. Res. Div. Sci. Technol.
Branch, Environ. Canada, 2012.
Verseghy, D. L.: Class—A Canadian land surface scheme for GCMS. I. Soil
model, Int. J. Climatol., 11, 111–133, https://doi.org/10.1002/joc.3370110202, 1991.
Walvoord, M. A. and Kurylyk, B. L.: Hydrologic Impacts of Thawing
Permafrost – A Review, Vadose Zone J., 15, https://doi.org/10.2136/vzj2016.01.0010,
2016.
Walvoord, M. A. and Striegl, R. G.: Increased groundwater to stream
discharge from permafrost thawing in the Yukon River basin: Potential
impacts on lateral export of carbon and nitrogen, Geophys. Res. Lett.,
34, L12402, https://doi.org/10.1029/2007GL030216, 2007.
Weedon, G. P., Gomes, S., Viterbo, P., Shuttleworth, W. J., Blyth, E.,
Österle, H., Adam, J. C., Bellouin, N., Boucher, O., and Best, M.:
Creation of the WATCH Forcing Data and Its Use to Assess Global and Regional
Reference Crop Evaporation over Land during the Twentieth Century, J.
Hydrometeorol., 12, 823–848, https://doi.org/10.1175/2011JHM1369.1, 2011.
Weedon, G. P., Balsamo, G., Bellouin, N., Gomes, S., Best, M. J., and
Viterbo, P.: The WFDEI meteorological forcing data set: WATCH Forcing Data
methodology applied to ERA-Interim reanalysis data, Water Resour. Res., 50,
7505–7514, https://doi.org/10.1002/2014WR015638, 2014.
Wong, J. S., Razavi, S., Bonsal, B. R., Wheater, H. S., and Asong, Z. E.: Inter-comparison of daily precipitation products for large-scale hydro-climatic applications over Canada, Hydrol. Earth Syst. Sci., 21, 2163–2185, https://doi.org/10.5194/hess-21-2163-2017, 2017.
Wright, J. F., Duchesne, C., and Côté, M. M.: Regional-scale
permafrost mapping using the TTOP ground temperature
model, in: Proceedings of the Eighth International Conference
on Permafrost, 21–25 July 2003, Zurich, Switzerland, 1241–1246,
2003.
Yassin, F., Razavi, S., Wheater, H., Sapriza-Azuri, G., Davison, B., and
Pietroniro, A.: Enhanced identification of a hydrologic model using
streamflow and satellite water storage data: A multicriteria sensitivity
analysis and optimization approach, Hydrol. Process., 31, 3320–3333,
https://doi.org/10.1002/hyp.11267, 2017.
Yassin, F., Razavi, S., Wong, J. S., Pietroniro, A., and Wheater, H.: Hydrologic-Land Surface Modelling of a Complex System under Precipitation Uncertainty: A Case Study of the Saskatchewan River Basin, Canada, Hydrol. Earth Syst. Sci. Discuss., https://doi.org/10.5194/hess-2019-207, 2019a.
Yassin, F., Razavi, S., Elshamy, M., Davison, B., Sapriza-Azuri, G., and Wheater, H.: Representation and improved parameterization of reservoir operation in hydrological and land-surface models, Hydrol. Earth Syst. Sci., 23, 3735–3764, https://doi.org/10.5194/hess-23-3735-2019, 2019b.
Yeh, K.-S., Côté, J., Gravel, S., Méthot, A., Patoine, A., Roch,
M., Staniforth, A., Yeh, K.-S., Côté, J., Gravel, S., Méthot,
A., Patoine, A., Roch, M., and Staniforth, A.: The CMC–MRB Global
Environmental Multiscale (GEM) Model. Part III: Nonhydrostatic Formulation,
Mon. Weather Rev., 130, 339–356, https://doi.org/10.1175/1520-0493(2002)130<0339:TCMGEM>2.0.CO;2, 2002.
Zhang, T., Barry, R. G., Knowles, K., Heginbottom, J. A., and Brown, J.:
Polar Geography Statistics and characteristics of permafrost and ground-ice
distribution in the Northern Hemisphere, Polar Geogr., 31, 47–68, https://doi.org/10.1080/10889370802175895,
2008.
Zhang, X., Flato, G., Kirchmeier-Young, M., Vincent, L., Wan, H., Wang, X., Rong, R., Fyfe, J., Li, G. and Kharin, V. V: Changes in Temperature and Precipitation Across Canada, in Canada's Changing Climate Report, 112–193, available at: https://changingclimate.ca/site/assets/uploads/sites/2/2018/12/CCCR-Chapter4-TemperatureAndPrecipitationAcrossCanada.pdf, last access: 22 April 2019.
Zhang, Y., Cheng, G., Li, X., Han, X., Wang, L., Li, H., Chang, X., and
Flerchinger, G. N.: Coupling of a simultaneous heat and water model with a
distributed hydrological model and evaluation of the combined model in a
cold region watershed, Hydrol. Process., 27, 3762–3776, https://doi.org/10.1002/hyp.9514, 2012.
Short summary
Permafrost is an important feature of cold-region hydrology and needs to be properly represented in hydrological and land surface models (H-LSMs), especially under the observed and expected climate warming trends. This study aims to devise a robust, yet computationally efficient, initialization and parameterization approach for permafrost. We used permafrost observations from three sites along the Mackenzie River valley spanning different permafrost classes to test the validity of the approach.
Permafrost is an important feature of cold-region hydrology and needs to be properly represented...
