Articles | Volume 21, issue 10
https://doi.org/10.5194/hess-21-5089-2017
© Author(s) 2017. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
https://doi.org/10.5194/hess-21-5089-2017
© Author(s) 2017. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
Research article
| 
09 Oct 2017
Research article |
| 09 Oct 2017
Using isotopes to constrain water flux and age estimates in snow-influenced catchments using the STARR (Spatially distributed Tracer-Aided Rainfall–Runoff) model
Northern Rivers Institute, School of Geosciences, University of
Aberdeen, AB24 3UF, UK
Doerthe Tetzlaff
Northern Rivers Institute, School of Geosciences, University of
Aberdeen, AB24 3UF, UK
James P. McNamara
Department of Geosciences, Boise State University, Boise, ID 83725,
USA
Hjalmar Laudon
Department of Forest, Ecology and Management, Swedish University of
Agricultural Sciences, 90183 Umeå, Sweden
Chris Soulsby
Northern Rivers Institute, School of Geosciences, University of
Aberdeen, AB24 3UF, UK
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Jari-Pekka Nousu, Matthieu Lafaysse, Giulia Mazzotti, Pertti Ala-aho, Hannu Marttila, Bertrand Cluzet, Mika Aurela, Annalea Lohila, Pasi Kolari, Aaron Boone, Mathieu Fructus, and Samuli Launiainen
The Cryosphere, 18, 231–263, https://doi.org/10.5194/tc-18-231-2024, https://doi.org/10.5194/tc-18-231-2024, 2024
Short summary
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The snowpack has a major impact on the land surface energy budget. Accurate simulation of the snowpack energy budget is difficult, and studies that evaluate models against energy budget observations are rare. We compared predictions from well-known models with observations of energy budgets, snow depths and soil temperatures in Finland. Our study identified contrasting strengths and limitations for the models. These results can be used for choosing the right models depending on the use cases.
Anssi Rauhala, Leo-Juhani Meriö, Anton Kuzmin, Pasi Korpelainen, Pertti Ala-aho, Timo Kumpula, Bjørn Kløve, and Hannu Marttila
The Cryosphere, 17, 4343–4362, https://doi.org/10.5194/tc-17-4343-2023, https://doi.org/10.5194/tc-17-4343-2023, 2023
Short summary
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Snow conditions in the Northern Hemisphere are rapidly changing, and information on snow depth is important for decision-making. We present snow depth measurements using different drones throughout the winter at a subarctic site. Generally, all drones produced good estimates of snow depth in open areas. However, differences were observed in the accuracies produced by the different drones, and a reduction in accuracy was observed when moving from an open mire area to forest-covered areas.
Leo-Juhani Meriö, Anssi Rauhala, Pertti Ala-aho, Anton Kuzmin, Pasi Korpelainen, Timo Kumpula, Bjørn Kløve, and Hannu Marttila
The Cryosphere, 17, 4363–4380, https://doi.org/10.5194/tc-17-4363-2023, https://doi.org/10.5194/tc-17-4363-2023, 2023
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Information on seasonal snow cover is essential in understanding snow processes and operational forecasting. We study the spatiotemporal variability in snow depth and snow processes in a subarctic, boreal landscape using drones. We identified multiple theoretically known snow processes and interactions between snow and vegetation. The results highlight the applicability of the drones to be used for a detailed study of snow depth in multiple land cover types and snow–vegetation interactions.
Filip Muhic, Pertti Ala-Aho, Matthias Sprenger, Björn Klöve, and Hannu Marttila
EGUsphere, https://doi.org/10.5194/egusphere-2023-884, https://doi.org/10.5194/egusphere-2023-884, 2023
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Doerthe Tetzlaff, Aaron Smith, Lukas Kleine, Hauke Daempfling, Jonas Freymueller, and Chris Soulsby
Earth Syst. Sci. Data, 15, 1543–1554, https://doi.org/10.5194/essd-15-1543-2023, https://doi.org/10.5194/essd-15-1543-2023, 2023
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We present a comprehensive set of ecohydrological hydrometric and stable water isotope data of 2 years of data. The data set is unique as the different compartments of the landscape were sampled and the effects of a prolonged drought (2018–2020) captured by a marked negative rainfall anomaly (the most severe regional drought of the 21st century). Thus, the data allow the drought effects on water storage, flux and age dynamics, and persistence of lowland landscapes to be investigated.
Anna Lupon, Stefan Willem Ploum, Jason Andrew Leach, Lenka Kuglerová, and Hjalmar Laudon
Hydrol. Earth Syst. Sci., 27, 613–625, https://doi.org/10.5194/hess-27-613-2023, https://doi.org/10.5194/hess-27-613-2023, 2023
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Xiaoqiang Yang, Doerthe Tetzlaff, Chris Soulsby, and Dietrich Borchardt
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2022-239, https://doi.org/10.5194/gmd-2022-239, 2022
Preprint retracted
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We develop the catchment water quality assessment platform HiWaQ v1.0, which is compatible with multiple hydrological model structures. The nitrogen module (HiWaQ-N) and its coupling tests with two contrasting grid-based hydrological models demonstrate the robustness of the platform in estimating catchment N dynamics. With the unique design of the coupling flexibility, HiWaQ can leverage advancements in hydrological modelling and advance integrated catchment water quantity-quality assessments.
Guangxuan Li, Xi Chen, Zhicai Zhang, Lichun Wang, and Chris Soulsby
Hydrol. Earth Syst. Sci., 26, 5515–5534, https://doi.org/10.5194/hess-26-5515-2022, https://doi.org/10.5194/hess-26-5515-2022, 2022
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Johannes Larson, William Lidberg, Anneli M. Ågren, and Hjalmar Laudon
Hydrol. Earth Syst. Sci., 26, 4837–4851, https://doi.org/10.5194/hess-26-4837-2022, https://doi.org/10.5194/hess-26-4837-2022, 2022
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Aaron Smith, Doerthe Tetzlaff, Jessica Landgraf, Maren Dubbert, and Chris Soulsby
Biogeosciences, 19, 2465–2485, https://doi.org/10.5194/bg-19-2465-2022, https://doi.org/10.5194/bg-19-2465-2022, 2022
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Jessica Landgraf, Dörthe Tetzlaff, Maren Dubbert, David Dubbert, Aaron Smith, and Chris Soulsby
Hydrol. Earth Syst. Sci., 26, 2073–2092, https://doi.org/10.5194/hess-26-2073-2022, https://doi.org/10.5194/hess-26-2073-2022, 2022
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Using water stable isotopes, we studied from which water source (lake water, stream water, groundwater, or soil water) two willows were taking their water. We monitored the environmental conditions (e.g. air temperature and soil moisture) and the behaviour of the trees (water flow in the stem). We found that the most likely water sources of the willows were the upper soil layers but that there were seasonal dynamics.
Conrad Jackisch, Sibylle K. Hassler, Tobias L. Hohenbrink, Theresa Blume, Hjalmar Laudon, Hilary McMillan, Patricia Saco, and Loes van Schaik
Hydrol. Earth Syst. Sci., 25, 5277–5285, https://doi.org/10.5194/hess-25-5277-2021, https://doi.org/10.5194/hess-25-5277-2021, 2021
Aaron J. Neill, Christian Birkel, Marco P. Maneta, Doerthe Tetzlaff, and Chris Soulsby
Hydrol. Earth Syst. Sci., 25, 4861–4886, https://doi.org/10.5194/hess-25-4861-2021, https://doi.org/10.5194/hess-25-4861-2021, 2021
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Structural changes (cover and height of vegetation plus tree canopy characteristics) to forests during regeneration on degraded land affect how water is partitioned between streamflow, groundwater recharge and evapotranspiration. Partitioning most strongly deviates from baseline conditions during earlier stages of regeneration with dense forest, while recovery may be possible as the forest matures and opens out. This has consequences for informing sustainable landscape restoration strategies.
Mikael Gillefalk, Dörthe Tetzlaff, Reinhard Hinkelmann, Lena-Marie Kuhlemann, Aaron Smith, Fred Meier, Marco P. Maneta, and Chris Soulsby
Hydrol. Earth Syst. Sci., 25, 3635–3652, https://doi.org/10.5194/hess-25-3635-2021, https://doi.org/10.5194/hess-25-3635-2021, 2021
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We used a tracer-aided ecohydrological model to quantify water flux–storage–age interactions for three urban vegetation types: trees, shrub and grass. The model results showed that evapotranspiration increased in the order shrub < grass < trees during one growing season. Additionally, we could show how
infiltration hotspotscreated by runoff from sealed onto vegetated surfaces can enhance both evapotranspiration and groundwater recharge.
Ahmad Hojatimalekshah, Zachary Uhlmann, Nancy F. Glenn, Christopher A. Hiemstra, Christopher J. Tennant, Jake D. Graham, Lucas Spaete, Arthur Gelvin, Hans-Peter Marshall, James P. McNamara, and Josh Enterkine
The Cryosphere, 15, 2187–2209, https://doi.org/10.5194/tc-15-2187-2021, https://doi.org/10.5194/tc-15-2187-2021, 2021
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We describe the relationships between snow depth, vegetation canopy, and local-scale processes during the snow accumulation period using terrestrial laser scanning (TLS). In addition to topography and wind, our findings suggest the importance of fine-scale tree structure, species type, and distributions on snow depth. Snow depth increases from the canopy edge toward the open areas, but wind and topographic controls may affect this trend. TLS data are complementary to wide-area lidar surveys.
Aaron Smith, Doerthe Tetzlaff, Lukas Kleine, Marco Maneta, and Chris Soulsby
Hydrol. Earth Syst. Sci., 25, 2239–2259, https://doi.org/10.5194/hess-25-2239-2021, https://doi.org/10.5194/hess-25-2239-2021, 2021
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We used a tracer-aided ecohydrological model on a mixed land use catchment in northeastern Germany to quantify water flux–storage–age interactions at four model grid resolutions. The model's ability to reproduce spatio-temporal flux–storage–age interactions decreases with increasing model grid sizes. Similarly, larger model grids showed vegetation-influenced changes in blue and green water partitioning. Simulations reveal the value of measured soil and stream isotopes for model calibration.
Jenna R. Snelgrove, James M. Buttle, Matthew J. Kohn, and Dörthe Tetzlaff
Hydrol. Earth Syst. Sci., 25, 2169–2186, https://doi.org/10.5194/hess-25-2169-2021, https://doi.org/10.5194/hess-25-2169-2021, 2021
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Elin Jutebring Sterte, Fredrik Lidman, Emma Lindborg, Ylva Sjöberg, and Hjalmar Laudon
Hydrol. Earth Syst. Sci., 25, 2133–2158, https://doi.org/10.5194/hess-25-2133-2021, https://doi.org/10.5194/hess-25-2133-2021, 2021
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A numerical model was used to estimate annual and seasonal mean travel times across 14 long-term nested monitored catchments in the boreal region. The estimated travel times and young water fractions were consistent with observed variations of base cation concentration and stable water isotopes, δ18O. Soil type was the most important factor regulating the variation in mean travel times among sub-catchments, while the areal coverage of mires increased the young water fraction.
Lena-Marie Kuhlemann, Doerthe Tetzlaff, Aaron Smith, Birgit Kleinschmit, and Chris Soulsby
Hydrol. Earth Syst. Sci., 25, 927–943, https://doi.org/10.5194/hess-25-927-2021, https://doi.org/10.5194/hess-25-927-2021, 2021
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We studied water partitioning under urban grassland, shrub and trees during a warm and dry growing season in Berlin, Germany. Soil evaporation was highest under grass, but total green water fluxes and turnover time of soil water were greater under trees. Lowest evapotranspiration losses under shrub indicate potential higher drought resilience. Knowledge of water partitioning and requirements of urban green will be essential for better adaptive management of urban water and irrigation strategies.
Miguel A. Aguayo, Alejandro N. Flores, James P. McNamara, Hans-Peter Marshall, and Jodi Mead
Hydrol. Earth Syst. Sci. Discuss., https://doi.org/10.5194/hess-2020-451, https://doi.org/10.5194/hess-2020-451, 2020
Manuscript not accepted for further review
Lukas Kleine, Doerthe Tetzlaff, Aaron Smith, Hailong Wang, and Chris Soulsby
Hydrol. Earth Syst. Sci., 24, 3737–3752, https://doi.org/10.5194/hess-24-3737-2020, https://doi.org/10.5194/hess-24-3737-2020, 2020
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We investigated the effects of the 2018 drought on water partitioning in a lowland catchment under grassland and forest in north-eastern Germany. Conditions resulted in drying up of streams, yield losses, and lower groundwater levels. Oak trees continued to transpire during the drought. We used stable isotopes to assess the fluxes and ages of water. Sustainable use of resource water requires such understanding of ecohydrological water partitioning.
Nataliia Kozii, Kersti Haahti, Pantana Tor-ngern, Jinshu Chi, Eliza Maher Hasselquist, Hjalmar Laudon, Samuli Launiainen, Ram Oren, Matthias Peichl, Jörgen Wallerman, and Niles J. Hasselquist
Hydrol. Earth Syst. Sci., 24, 2999–3014, https://doi.org/10.5194/hess-24-2999-2020, https://doi.org/10.5194/hess-24-2999-2020, 2020
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The hydrologic cycle is one of the greatest natural processes on Earth and strongly influences both regional and global climate as well as ecosystem functioning. Results from this study clearly show the central role trees play in regulating the water cycle of boreal catchments, implying that forest management impacts on stand structure as well as climate change effects on tree growth are likely to have large cascading effects on the way water moves through boreal forested landscapes.
Stefan W. Ploum, Hjalmar Laudon, Andrés Peralta-Tapia, and Lenka Kuglerová
Hydrol. Earth Syst. Sci., 24, 1709–1720, https://doi.org/10.5194/hess-24-1709-2020, https://doi.org/10.5194/hess-24-1709-2020, 2020
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Near-stream areas, or riparian zones, are important for the health of streams and rivers. If these areas are disturbed by forestry or other anthropogenic activity, the water quality and all life in streams may be at risk. We examined which riparian areas are particularly sensitive. We found that only a few wet areas bring most of the rainwater from the landscape to the stream, and they have a unique water quality. In order to maintain healthy streams and rivers, these areas should be protected.
Aaron Smith, Doerthe Tetzlaff, Hjalmar Laudon, Marco Maneta, and Chris Soulsby
Hydrol. Earth Syst. Sci., 23, 3319–3334, https://doi.org/10.5194/hess-23-3319-2019, https://doi.org/10.5194/hess-23-3319-2019, 2019
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We adapted and used a spatially distributed eco-hydrological model, EcH2O-iso, to temporally evaluate the influence of soil freeze–thaw dynamics on evaporation and transpiration fluxes in a northern Swedish catchment. We used multi-criterion calibration over multiple years and found an early-season influence of soil frost on transpiration water ages. This work provides a framework for quantifying the current and future interactions of soil water, evaporation, and transpiration.
Thea I. Piovano, Doerthe Tetzlaff, Sean K. Carey, Nadine J. Shatilla, Aaron Smith, and Chris Soulsby
Hydrol. Earth Syst. Sci., 23, 2507–2523, https://doi.org/10.5194/hess-23-2507-2019, https://doi.org/10.5194/hess-23-2507-2019, 2019
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We adapted the spatially distributed, tracer-aided model, STARR, to a permafrost-influenced catchment in the Yukon Territory, Canada, with a time-variable implementation of field capacity to capture thaw layer spatio-temporal dynamics. We applied a multi-criteria calibration with multi-year field data. This study demonstrates the value of the integration of isotope data in a spatially distributed model to quantify catchment water storage and age dynamics in a permafrost-influenced environment.
Hongkai Gao, Christian Birkel, Markus Hrachowitz, Doerthe Tetzlaff, Chris Soulsby, and Hubert H. G. Savenije
Hydrol. Earth Syst. Sci., 23, 787–809, https://doi.org/10.5194/hess-23-787-2019, https://doi.org/10.5194/hess-23-787-2019, 2019
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Supported by large-sample ecological observations, a novel, simple and topography-driven runoff generation module (HSC-MCT) was created. The HSC-MCT is calibration-free, and therefore it can be used to predict in ungauged basins, and has great potential to be generalized at the global scale. Also, it allows us to reproduce the variation of saturation areas, which has great potential to be used for broader hydrological, ecological, climatological, and biogeochemical studies.
Zhicai Zhang, Xi Chen, Qinbo Cheng, and Chris Soulsby
Hydrol. Earth Syst. Sci., 23, 51–71, https://doi.org/10.5194/hess-23-51-2019, https://doi.org/10.5194/hess-23-51-2019, 2019
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We developed a new tracer-aided hydrological model for karst catchments. This model captured the flow and tracer dynamics within each landscape unit quite well, and we could estimate the storage, fluxes and age of water within each. Such tracer-aided models enhance our understanding of the hydrological connectivity between different landscape units and the mixing processes between various flow sources. It is an encouraging step forward in tracer-aided modelling of karst catchments.
Marcus Klaus, Erik Geibrink, Anders Jonsson, Ann-Kristin Bergström, David Bastviken, Hjalmar Laudon, Jonatan Klaminder, and Jan Karlsson
Biogeosciences, 15, 5575–5594, https://doi.org/10.5194/bg-15-5575-2018, https://doi.org/10.5194/bg-15-5575-2018, 2018
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Forest management is widely used to mitigate climate change. However, forest greenhouse gas (GHG) budgets neglect to consider that clear-cuts often release carbon and nitrogen into streams and lakes and may affect aquatic GHG emissions. Here, we show that such emissions remain unaffected by experimental boreal forest clear-cutting despite increased groundwater carbon dioxide and methane concentrations, highlighting that riparian zones or in-stream processes may have buffered clear-cut leachates.
Sylvain Kuppel, Doerthe Tetzlaff, Marco P. Maneta, and Chris Soulsby
Geosci. Model Dev., 11, 3045–3069, https://doi.org/10.5194/gmd-11-3045-2018, https://doi.org/10.5194/gmd-11-3045-2018, 2018
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This paper presents a novel ecohydrological model in which both the fluxes of water and the relative concentration in stable isotopes (2H and 18O) can be simulated. Spatial heterogeneity, lateral transfers and plant-driven water use are incorporated. A thorough evaluation shows encouraging results using a wide range of in situ measurements from a Scottish catchment. The same modelling principles are then used to simulate how (and where) precipitation ages as water transits in the catchment.
Matthias Sprenger, Doerthe Tetzlaff, Jim Buttle, Hjalmar Laudon, and Chris Soulsby
Hydrol. Earth Syst. Sci., 22, 3965–3981, https://doi.org/10.5194/hess-22-3965-2018, https://doi.org/10.5194/hess-22-3965-2018, 2018
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We estimated water ages in the upper critical zone with a soil physical model (SWIS) and found that the age of water stored in the soil, as well as of water leaving the soil via evaporation, transpiration, or recharge, was younger the higher soil water storage (inverse storage effect). Travel times of transpiration and evaporation were different. We conceptualized the subsurface into fast and slow flow domains and the water was usually half as young in the fast as in the slow flow domain.
Sarah E. Godsey, Danny Marks, Patrick R. Kormos, Mark S. Seyfried, Clarissa L. Enslin, Adam H. Winstral, James P. McNamara, and Timothy E. Link
Earth Syst. Sci. Data, 10, 1207–1216, https://doi.org/10.5194/essd-10-1207-2018, https://doi.org/10.5194/essd-10-1207-2018, 2018
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Weather data in mountainous rain-to-snow transition zones are limited, but are vital for water resources. We present a 10-year dataset for this zone that includes hourly temperatures, relative humidity, streamflow, snow depth, precipitation, wind speed/direction, solar energy, and soil moisture at 11 stations. Average air temperatures are near freezing 8 months each year, so that slight warming may determine whether rain falls instead of snow, affecting water supplies and fire risk.
Aaron A. Smith, Doerthe Tetzlaff, and Chris Soulsby
Hydrol. Earth Syst. Sci. Discuss., https://doi.org/10.5194/hess-2018-57, https://doi.org/10.5194/hess-2018-57, 2018
Preprint withdrawn
Martin Berggren, Marcus Klaus, Balathandayuthabani Panneer Selvam, Lena Ström, Hjalmar Laudon, Mats Jansson, and Jan Karlsson
Biogeosciences, 15, 457–470, https://doi.org/10.5194/bg-15-457-2018, https://doi.org/10.5194/bg-15-457-2018, 2018
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The quality of dissolved organic carbon (DOC), especially its color, is a defining feature of freshwater ecosystems. We found that colored DOC fractions are surprisingly resistant to natural degradation during water transit through many brown-water lakes. This is explained by the dominance of microbial processes that appear to selectively remove noncolored DOC. However, in lakes where sunlight degradation plays a relatively larger role, significant DOC bleaching occurs.
Fernando Jaramillo, Neil Cory, Berit Arheimer, Hjalmar Laudon, Ype van der Velde, Thomas B. Hasper, Claudia Teutschbein, and Johan Uddling
Hydrol. Earth Syst. Sci., 22, 567–580, https://doi.org/10.5194/hess-22-567-2018, https://doi.org/10.5194/hess-22-567-2018, 2018
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Which is the dominant effect on evapotranspiration in northern forests, an increase by recent forests expansion or a decrease by the water use response due to increasing CO2 concentrations? We determined the dominant effect during the period 1961–2012 in 65 Swedish basins. We used the Budyko framework to study the hydroclimatic movements in Budyko space. Our findings suggest that forest expansion is the dominant driver of long-term and large-scale evapotranspiration changes.
Matthias Sprenger, Doerthe Tetzlaff, and Chris Soulsby
Hydrol. Earth Syst. Sci., 21, 3839–3858, https://doi.org/10.5194/hess-21-3839-2017, https://doi.org/10.5194/hess-21-3839-2017, 2017
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We sampled the isotopic composition in the top 20 cm at four different sites in the Scottish Highlands at 5 cm intervals over 1 year. The relationship between the soil water isotopic fractionation and evapotranspiration showed a hysteresis pattern due to a lag response to onset and offset of the evaporative losses. The isotope data revealed that vegetation had a significant influence on the soil evaporation with evaporation being double from soils beneath Scots pine compared to heather.
Fredrik Lidman, Åsa Boily, Hjalmar Laudon, and Stephan J. Köhler
Biogeosciences, 14, 3001–3014, https://doi.org/10.5194/bg-14-3001-2017, https://doi.org/10.5194/bg-14-3001-2017, 2017
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The riparian zone is the narrow strip of land that lines a watercourse. This is the last soil that the groundwater is in contact with before it enters the stream and it therefore has a high impact on the water quality. In this paper we show that many elements occur in elevated concentrations in the peat-like riparian zone of boreal headwaters and that this also leads to elevated concentrations in the streams. Hence, understanding riparian soils is crucial for a sustainable management of streams.
Adrian A. Harpold, Michael L. Kaplan, P. Zion Klos, Timothy Link, James P. McNamara, Seshadri Rajagopal, Rina Schumer, and Caitriana M. Steele
Hydrol. Earth Syst. Sci., 21, 1–22, https://doi.org/10.5194/hess-21-1-2017, https://doi.org/10.5194/hess-21-1-2017, 2017
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The phase of precipitation as rain or snow is fundamental to hydrological processes and water resources. Despite its importance, the methods used to predict precipitation phase are inconsistent and often overly simplified. We review these methods and underlying mechanisms that control phase. We present a vision to meet important research gaps needed to improve prediction, including new field-based and remote measurements, validating new and existing methods, and expanding regional prediction.
Tobias Lindborg, Johan Rydberg, Mats Tröjbom, Sten Berglund, Emma Johansson, Anders Löfgren, Peter Saetre, Sara Nordén, Gustav Sohlenius, Eva Andersson, Johannes Petrone, Micke Borgiel, Ulrik Kautsky, and Hjalmar Laudon
Earth Syst. Sci. Data, 8, 439–459, https://doi.org/10.5194/essd-8-439-2016, https://doi.org/10.5194/essd-8-439-2016, 2016
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This paper presents a biogeochemical and ecological data set from the Kangerlussuaq region, western Greenland. The data set is used to conceptualize and model terrestrial and limnic ecosystems as well as the land–lake linkage. Both biotic and abiotic data is presented and will be used for biogeochemical mass-balance and transport calculations. The data set constitutes an important source in order to understand and describe accumulation and flow of matter within periglacial landscapes.
Clarissa L. Enslin, Sarah E. Godsey, Danny Marks, Patrick R. Kormos, Mark S. Seyfried, James P. McNamara, and Timothy E. Link
Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2016-44, https://doi.org/10.5194/essd-2016-44, 2016
Preprint withdrawn
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Weather data in mountainous rain-to-snow transition zones are limited, but vital for water resources. We present a 10-year dataset for this zone that includes hourly temperatures, relative humidity, stream flow, snow depth, precipitation, wind speed/direction, solar energy, and soil moisture at 11 stations. Average air temperatures are near freezing eight months each year, so that slight warming may determine whether rain falls instead of snow, affecting water supplies, ecosystems and fire risk.
Stephen Oni, Martyn Futter, Jose Ledesma, Claudia Teutschbein, Jim Buttle, and Hjalmar Laudon
Hydrol. Earth Syst. Sci., 20, 2811–2825, https://doi.org/10.5194/hess-20-2811-2016, https://doi.org/10.5194/hess-20-2811-2016, 2016
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This paper presents an important framework to improve hydrologic projections in cold regions. Hydrologic modelling/projections are often based on model calibration to long-term data. Here we used dry and wet years as a proxy to quantify uncertainty in projecting hydrologic extremes. We showed that projections based on long-term data could underestimate runoff by up to 35% in boreal regions. We believe the hydrologic modelling community will benefit from new insights derived from this study.
J. Schelker, R. Sponseller, E. Ring, L. Högbom, S. Löfgren, and H. Laudon
Biogeosciences, 13, 1–12, https://doi.org/10.5194/bg-13-1-2016, https://doi.org/10.5194/bg-13-1-2016, 2016
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The scientific question that is addressed in this study is how forest disturbance affects organic and inorganic nitrogen export from a boreal landscape. The key findings are that the mobilization of inorganic nitrogen from the terrestrial environment to streams increased strongly as a response to harvesting, but the stream network removed a major fraction of this load before it reached the outlet, while organic nitrogen was not removed and transported downstream.
M. Haei and H. Laudon
Biogeosciences Discuss., https://doi.org/10.5194/bgd-12-15763-2015, https://doi.org/10.5194/bgd-12-15763-2015, 2015
Revised manuscript not accepted
P. Ala-aho, P. M. Rossi, and B. Kløve
Hydrol. Earth Syst. Sci., 19, 1961–1976, https://doi.org/10.5194/hess-19-1961-2015, https://doi.org/10.5194/hess-19-1961-2015, 2015
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We present a novel simulation method for estimating spatially distributed and transient groundwater recharge in unconfined sandy aquifers. The approach uses field data for the most important parameters affecting groundwater recharge and accounts for parameter uncertainty. The results show that tree canopy cover is the most important factor in controlling groundwater recharge at our study area. Tree canopy is thinned by forestry, which may lead to a significant increase of groundwater recharge.
J. R. Poulsen, E. Sebok, C. Duque, D. Tetzlaff, and P. K. Engesgaard
Hydrol. Earth Syst. Sci., 19, 1871–1886, https://doi.org/10.5194/hess-19-1871-2015, https://doi.org/10.5194/hess-19-1871-2015, 2015
F. I. Leith, K. J. Dinsmore, M. B. Wallin, M. F. Billett, K. V. Heal, H. Laudon, M. G. Öquist, and K. Bishop
Biogeosciences, 12, 1881–1892, https://doi.org/10.5194/bg-12-1881-2015, https://doi.org/10.5194/bg-12-1881-2015, 2015
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Carbon dioxide transport between the terrestrial and aquatic systems was dominated by export from the near-stream riparian zone. Over the year, riparian export was highest during autumn storms and the spring snowmelt event. This resulted in high downstream export during these periods with vertical evasion from the stream surface accounting for 60% of the total stream water export, highlighting the importance of evasion to carbon export via the aquatic conduit.
P. R. Kormos, D. Marks, C. J. Williams, H. P. Marshall, P. Aishlin, D. G. Chandler, and J. P. McNamara
Earth Syst. Sci. Data, 6, 165–173, https://doi.org/10.5194/essd-6-165-2014, https://doi.org/10.5194/essd-6-165-2014, 2014
H. Zarei, A. M. Akhondali, H. Mohammadzadeh, F. Radmanesh, and H. Laudon
Hydrol. Earth Syst. Sci. Discuss., https://doi.org/10.5194/hessd-11-3787-2014, https://doi.org/10.5194/hessd-11-3787-2014, 2014
Manuscript not accepted for further review
A. M. Ågren, I. Buffam, D. M. Cooper, T. Tiwari, C. D. Evans, and H. Laudon
Biogeosciences, 11, 1199–1213, https://doi.org/10.5194/bg-11-1199-2014, https://doi.org/10.5194/bg-11-1199-2014, 2014
T. P. Karjalainen, P. M. Rossi, P. Ala-aho, R. Eskelinen, K. Reinikainen, B. Kløve, M. Pulido-Velazquez, and H. Yang
Hydrol. Earth Syst. Sci., 17, 5141–5153, https://doi.org/10.5194/hess-17-5141-2013, https://doi.org/10.5194/hess-17-5141-2013, 2013
E. Bosson, T. Lindborg, S. Berglund, L.-G. Gustafsson, J.-O. Selroos, H. Laudon, L. L. Claesson, and G. Destouni
Hydrol. Earth Syst. Sci. Discuss., https://doi.org/10.5194/hessd-10-9271-2013, https://doi.org/10.5194/hessd-10-9271-2013, 2013
Revised manuscript not accepted
J. L. J. Ledesma, T. Grabs, M. N. Futter, K. H. Bishop, H. Laudon, and S. J. Köhler
Biogeosciences, 10, 3849–3868, https://doi.org/10.5194/bg-10-3849-2013, https://doi.org/10.5194/bg-10-3849-2013, 2013
S. K. Oni, M. N. Futter, K. Bishop, S. J. Köhler, M. Ottosson-Löfvenius, and H. Laudon
Biogeosciences, 10, 2315–2330, https://doi.org/10.5194/bg-10-2315-2013, https://doi.org/10.5194/bg-10-2315-2013, 2013
M. Hrachowitz, H. Savenije, T. A. Bogaard, D. Tetzlaff, and C. Soulsby
Hydrol. Earth Syst. Sci., 17, 533–564, https://doi.org/10.5194/hess-17-533-2013, https://doi.org/10.5194/hess-17-533-2013, 2013
Related subject area
Subject: Catchment hydrology | Techniques and Approaches: Modelling approaches
Multi-scale soil moisture data and process-based modeling reveal the importance of lateral groundwater flow in a subarctic catchment
Catchment response to climatic variability: implications for root zone storage and streamflow predictions
Hybrid hydrological modeling for large alpine basins: a semi-distributed approach
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
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
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
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
Spatio-temporal patterns and trends of streamflow in water-scarce Mediterranean basins
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
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., 28, 4643–4666, https://doi.org/10.5194/hess-28-4643-2024, https://doi.org/10.5194/hess-28-4643-2024, 2024
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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.
Nienke Tempel, Laurène Bouaziz, Riccardo Taormina, Ellis van Noppen, Jasper Stam, Eric Sprokkereef, and Markus Hrachowitz
Hydrol. Earth Syst. Sci., 28, 4577–4597, https://doi.org/10.5194/hess-28-4577-2024, https://doi.org/10.5194/hess-28-4577-2024, 2024
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This study explores the impact of climatic variability on root zone water storage capacities and, 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.
Bu Li, Ting Sun, Fuqiang Tian, Mahmut Tudaji, Li Qin, and Guangheng Ni
Hydrol. Earth Syst. Sci., 28, 4521–4538, https://doi.org/10.5194/hess-28-4521-2024, https://doi.org/10.5194/hess-28-4521-2024, 2024
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This paper developed hybrid semi-distributed hydrological models by employing a process-based 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 to improve understanding about the hydrological sensitivities to climate change in large alpine basins.
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.
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.
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.
Laia Estrada, Xavier Garcia, Joan Saló, Rafael Marcé, Antoni Munné, and Vicenç Acuña
EGUsphere, https://doi.org/10.5194/egusphere-2023-3007, https://doi.org/10.5194/egusphere-2023-3007, 2024
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Hydrological modelling is a powerful tool to support decision-making. We assessed spatio-temporal patterns and trends of streamflow for 2001–2022 with a hydrological modelling integrating stakeholder expert knowledge on management operations. The results provide insight into how climate change and anthropogenic pressures affect water resources availability in regions vulnerable to water scarcity, thus raising the need for sustainable management practices and integrated hydrological modelling.
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.
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Short summary
We used the Spatially Distributed Tracer-Aided Rainfall-Runoff model (STARR) to simulate streamflows, stable water isotope ratios, snowpack dynamics, and water ages in three snow-influenced experimental catchments with exceptionally long and rich datasets. Our simulations reproduced the hydrological observations in all three catchments, suggested contrasting stream water age distributions between catchments, and demonstrated the importance of snow isotope processes in tracer-aided modelling.
We used the Spatially Distributed Tracer-Aided Rainfall-Runoff model (STARR) to simulate...
