Articles | Volume 23, issue 3
https://doi.org/10.5194/hess-23-1339-2019
© Author(s) 2019. 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-23-1339-2019
© Author(s) 2019. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| Highlight paper
| 
11 Mar 2019
Research article | Highlight paper |
| 11 Mar 2019
| 11 Mar 2019
Effects of univariate and multivariate bias correction on hydrological impact projections in alpine catchments
Judith Meyer
Faculty of Environment and Natural Resources, University of Freiburg, 79098 Freiburg, Germany
now at: Catchment and Eco-Hydrology Research Group, Luxembourg Institute of Science and Technology, 4362 Esch-sur-Alzette, Luxembourg
Irene Kohn
CORRESPONDING AUTHOR
Faculty of Environment and Natural Resources, University of Freiburg, 79098 Freiburg, Germany
Kerstin Stahl
Faculty of Environment and Natural Resources, University of Freiburg, 79098 Freiburg, Germany
Kirsti Hakala
Department of Geography, University of Zurich, 8057 Zurich, Switzerland
Jan Seibert
Department of Geography, University of Zurich, 8057 Zurich, Switzerland
Department of Aquatic Sciences and Assessment, Swedish University of Agricultural Sciences, Uppsala, Sweden
Alex J. Cannon
Climate Research Division, Environment and Climate Change Canada, BC V8W 2Y2, Victoria, Canada
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Hydrol. Earth Syst. Sci., 25, 3245–3265, https://doi.org/10.5194/hess-25-3245-2021, https://doi.org/10.5194/hess-25-3245-2021, 2021
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Biogeosciences, 18, 3263–3283, https://doi.org/10.5194/bg-18-3263-2021, https://doi.org/10.5194/bg-18-3263-2021, 2021
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Shrub and sedge plant functional types (PFTs) were incorporated in the land surface component of the Canadian Earth System Model to improve representation of Arctic tundra ecosystems. Evaluated against 14 years of non-winter measurements, the magnitude and seasonality of carbon dioxide and energy fluxes at a Canadian dwarf-shrub tundra site were better captured by the shrub PFTs than by previously used grass and tree PFTs. Model simulations showed the tundra site to be an annual net CO2 source.
Jost Hellwig, Michael Stoelzle, and Kerstin Stahl
Hydrol. Earth Syst. Sci., 25, 1053–1068, https://doi.org/10.5194/hess-25-1053-2021, https://doi.org/10.5194/hess-25-1053-2021, 2021
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Camila Alvarez-Garreton, Juan Pablo Boisier, René Garreaud, Jan Seibert, and Marc Vis
Hydrol. Earth Syst. Sci., 25, 429–446, https://doi.org/10.5194/hess-25-429-2021, https://doi.org/10.5194/hess-25-429-2021, 2021
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The megadrought experienced in Chile (2010–2020) has led to larger than expected water deficits. By analysing 106 basins with snow-/rainfall regimes, we relate such intensification with the hydrological memory of the basins, explained by snow and groundwater. Snow-dominated basins have larger memory and thus accumulate the effect of persistent precipitation deficits more strongly than pluvial basins. This notably affects central Chile, a water-limited region where most of the population lives.
Anna E. Sikorska-Senoner, Bettina Schaefli, and Jan Seibert
Nat. Hazards Earth Syst. Sci., 20, 3521–3549, https://doi.org/10.5194/nhess-20-3521-2020, https://doi.org/10.5194/nhess-20-3521-2020, 2020
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This work proposes methods for reducing the computational requirements of hydrological simulations for the estimation of very rare floods that occur on average less than once in 1000 years. These methods enable the analysis of long streamflow time series (here for example 10 000 years) at low computational costs and with modelling uncertainty. They are to be used within continuous simulation frameworks with long input time series and are readily transferable to similar simulation tasks.
Maria Staudinger, Stefan Seeger, Barbara Herbstritt, Michael Stoelzle, Jan Seibert, Kerstin Stahl, and Markus Weiler
Earth Syst. Sci. Data, 12, 3057–3066, https://doi.org/10.5194/essd-12-3057-2020, https://doi.org/10.5194/essd-12-3057-2020, 2020
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The data set CH-IRP provides isotope composition in precipitation and streamflow from 23 Swiss catchments, being unique regarding its long-term multi-catchment coverage along an alpine–pre-alpine gradient. CH-IRP contains fortnightly time series of stable water isotopes from streamflow grab samples complemented by time series in precipitation. Sampling conditions, catchment and climate information, lab standards and errors are provided together with areal precipitation and catchment boundaries.
Alexandra Nauditt, Kerstin Stahl, Erasmo Rodríguez, Christian Birkel, Rosa Maria Formiga-Johnsson, Kallio Marko, Hamish Hann, Lars Ribbe, Oscar M. Baez-Villanueva, and Joschka Thurner
Nat. Hazards Earth Syst. Sci. Discuss., https://doi.org/10.5194/nhess-2020-360, https://doi.org/10.5194/nhess-2020-360, 2020
Manuscript not accepted for further review
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Recurrent droughts are causing severe damages to tropical countries. We used gridded drought hazard and vulnerability data sets to map drought risk in four mesoscale rural tropical study regions in Latin America and Vietnam/Cambodia. Our risk maps clearly identified drought risk hotspots and displayed spatial and sector-wise distribution of hazard and vulnerability. As results were confirmed by local stakeholders our approach provides relevant information for drought managers in the Tropics.
Mathilde Erfurt, Georgios Skiadaresis, Erik Tijdeman, Veit Blauhut, Jürgen Bauhus, Rüdiger Glaser, Julia Schwarz, Willy Tegel, and Kerstin Stahl
Nat. Hazards Earth Syst. Sci., 20, 2979–2995, https://doi.org/10.5194/nhess-20-2979-2020, https://doi.org/10.5194/nhess-20-2979-2020, 2020
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Droughts are multifaceted hazards with widespread negative consequences for the environment and society. This study explores different perspectives on drought and determines the added value of multidisciplinary datasets for a comprehensive understanding of past drought events in southwestern Germany. A long-term evaluation of drought frequency since 1801 revealed that events occurred in all decades, but a particular clustering was found in the mid-19th century and the most recent decade.
Michael Stoelzle, Maria Staudinger, Kerstin Stahl, and Markus Weiler
Proc. IAHS, 383, 43–50, https://doi.org/10.5194/piahs-383-43-2020, https://doi.org/10.5194/piahs-383-43-2020, 2020
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The role of recharge and catchment storage is crucial to understand streamflow drought sensitivity. Here we introduce a model experiment with recharge stress tests as complement to climate scenarios to quantify the streamflow drought sensitivities of catchments in Switzerland. We identified a pre-drought period of 12 months as maximum storage-memory for the study catchments. From stress testing, we found up to 200 days longer summer streamflow droughts and minimum flow reductions of 50 %–80 %.
Kerstin Stahl, Jean-Philippe Vidal, Jamie Hannaford, Erik Tijdeman, Gregor Laaha, Tobias Gauster, and Lena M. Tallaksen
Proc. IAHS, 383, 291–295, https://doi.org/10.5194/piahs-383-291-2020, https://doi.org/10.5194/piahs-383-291-2020, 2020
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Numerous indices exist for the description of hydrological drought, some are based on absolute thresholds of overall streamflows or water levels and some are based on relative anomalies with respect to the season. This article discusses paradigms and experiences with such index uses in drought monitoring and drought analysis to raise awareness of the different interpretations of drought severity.
Marc Girons Lopez, Marc J. P. Vis, Michal Jenicek, Nena Griessinger, and Jan Seibert
Hydrol. Earth Syst. Sci., 24, 4441–4461, https://doi.org/10.5194/hess-24-4441-2020, https://doi.org/10.5194/hess-24-4441-2020, 2020
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Snow processes are crucial for runoff in mountainous areas, but their complexity makes water management difficult. Temperature models are widely used as they are simple and do not require much data, but not much thought is usually given to which model to use, which may lead to bad predictions. We studied the impact of many model alternatives and found that a more complex model does not necessarily perform better. Finding which processes are most important in each area is a much better strategy.
Kirsti Hakala, Nans Addor, Thibault Gobbe, Johann Ruffieux, and Jan Seibert
Hydrol. Earth Syst. Sci., 24, 3815–3833, https://doi.org/10.5194/hess-24-3815-2020, https://doi.org/10.5194/hess-24-3815-2020, 2020
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Under a changing climate, reliable information on future hydrological conditions is necessary to inform water resource management. Here, we collaborated with a hydropower company that selected streamflow and energy demand indices. Using these indices, we identified stakeholder needs and used this to tailor the production of our climate change impact projections. We show that opportunities and risks for a hydropower company depend on a range of factors beyond those covered by traditional studies.
Leonie Kiewiet, Ilja van Meerveld, Manfred Stähli, and Jan Seibert
Hydrol. Earth Syst. Sci., 24, 3381–3398, https://doi.org/10.5194/hess-24-3381-2020, https://doi.org/10.5194/hess-24-3381-2020, 2020
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The sources of stream water are important, for instance, for predicting floods. The connectivity between streams and different (ground-)water sources can change during rain events, which affects the stream water composition. We investigated this for stream water sampled during four events and found that stream water came from different sources. The stream water composition changed gradually, and we showed that changes in solute concentrations could be partly linked to changes in connectivity.
Bastien François, Mathieu Vrac, Alex J. Cannon, Yoann Robin, and Denis Allard
Earth Syst. Dynam., 11, 537–562, https://doi.org/10.5194/esd-11-537-2020, https://doi.org/10.5194/esd-11-537-2020, 2020
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Recently, multivariate bias correction (MBC) methods designed to adjust climate simulations have been proposed. However, they use different approaches, leading potentially to different results. Therefore, this study intends to intercompare four existing MBC methods to provide end users with aid in choosing such methods for their applications. To do so, a wide range of evaluation criteria have been used to assess the ability of MBC methods to correct statistical properties of climate models.
Barbara Strobl, Simon Etter, H. J. Ilja van Meerveld, and Jan Seibert
Geosci. Commun., 3, 109–126, https://doi.org/10.5194/gc-3-109-2020, https://doi.org/10.5194/gc-3-109-2020, 2020
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Training can deter people from joining a citizen science project but may be needed to ensure good data quality. In this study, we found that an online game that was originally developed for data quality control in a citizen science project can be used for training as well. These findings are useful for the development of training strategies for other citizen science projects because they indicate that gamified approaches might be valuable scalable training methods.
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.
Michael Stoelzle, Tobias Schuetz, Markus Weiler, Kerstin Stahl, and Lena M. Tallaksen
Hydrol. Earth Syst. Sci., 24, 849–867, https://doi.org/10.5194/hess-24-849-2020, https://doi.org/10.5194/hess-24-849-2020, 2020
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During dry weather, different delayed sources of runoff (e.g. from groundwater, wetlands or snowmelt) modulate the magnitude and variability of streamflow. Hydrograph separation methods often do not distinguish these delayed contributions and mostly pool them into only two components (i.e. quickflow and baseflow). We propose a method that uncovers multiple components and demonstrates how they better reflect streamflow generation processes of different flow regimes.
H. J. Ilja van Meerveld, James W. Kirchner, Marc J. P. Vis, Rick S. Assendelft, and Jan Seibert
Hydrol. Earth Syst. Sci., 23, 4825–4834, https://doi.org/10.5194/hess-23-4825-2019, https://doi.org/10.5194/hess-23-4825-2019, 2019
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Flowing stream networks extend and retract seasonally and in response to precipitation. This affects the distances and thus the time that it takes a water molecule to reach the flowing stream and the stream outlet. When the network is fully extended, the travel times are short, but when the network retracts, the travel times become longer and more uniform. These dynamics should be included when modeling solute or pollutant transport.
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
Dae Il Jeong, Alex J. Cannon, and Xuebin Zhang
Nat. Hazards Earth Syst. Sci., 19, 857–872, https://doi.org/10.5194/nhess-19-857-2019, https://doi.org/10.5194/nhess-19-857-2019, 2019
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Atmospheric ice accretion caused by freezing precipitation leads to severe damage and failure of buildings and infrastructure. This study investigates projected changes to extreme ice loads used to design infrastructure over North America for future periods of specified global mean temperature change using a Canadian regional climate model. Increases in ice accretion for latitudes higher than 40° N are substantial and would have clear implications for future building and infrastructure design.
Alex J. Cannon and Silvia Innocenti
Nat. Hazards Earth Syst. Sci., 19, 421–440, https://doi.org/10.5194/nhess-19-421-2019, https://doi.org/10.5194/nhess-19-421-2019, 2019
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Rainfall intensity–duration–frequency (IDF) curves are used as the basis for water resource infrastructure design. Given intensification of the hydrological cycle with global warming, quantitative information on the future extreme rainfall hazard is needed by practitioners. Projected changes in annual maximum rainfall in high-resolution regional climate model simulations result in IDF curves that shift upward and steepen, with greater intensification at short durations and long return periods.
Jost Hellwig and Kerstin Stahl
Hydrol. Earth Syst. Sci., 22, 6209–6224, https://doi.org/10.5194/hess-22-6209-2018, https://doi.org/10.5194/hess-22-6209-2018, 2018
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Due to the lack of long-term observations, insights into changes of groundwater resources are obscured. In this paper we assess past and potential future changes in groundwater drought in headwater catchments using a baseflow approach. There are a few past trends which are highly dependent on the period of analysis. Catchments with short response times are found to have a higher sensitivity to projected seasonal precipitation shifts, urging for a local management based on response times.
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.
Simon Etter, Barbara Strobl, Jan Seibert, and H. J. Ilja van Meerveld
Hydrol. Earth Syst. Sci., 22, 5243–5257, https://doi.org/10.5194/hess-22-5243-2018, https://doi.org/10.5194/hess-22-5243-2018, 2018
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To evaluate the potential value of streamflow estimates for hydrological model calibration, we created synthetic streamflow datasets in various temporal resolutions based on the errors in streamflow estimates of 136 citizens. Our results show that streamflow estimates of untrained citizens are too inaccurate to be useful for model calibration. If, however, the errors can be reduced by training or filtering, the estimates become useful if also a sufficient number of estimates are available.
Hui-Min Wang, Jie Chen, Alex J. Cannon, Chong-Yu Xu, and Hua Chen
Hydrol. Earth Syst. Sci., 22, 3739–3759, https://doi.org/10.5194/hess-22-3739-2018, https://doi.org/10.5194/hess-22-3739-2018, 2018
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Facing a growing number of climate models, many selection methods were proposed to select subsets in the field of climate simulation, but the transferability of their performances to hydrological impacts remains doubtful. We investigate the transferability of climate simulation uncertainty to hydrological impacts using two selection methods, and conclude that envelope-based selection of about 10 climate simulations based on properly chosen climate variables is suggested for impact studies.
Daphné Freudiger, David Mennekes, Jan Seibert, and Markus Weiler
Earth Syst. Sci. Data, 10, 805–814, https://doi.org/10.5194/essd-10-805-2018, https://doi.org/10.5194/essd-10-805-2018, 2018
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To understand glacier changes in the Swiss Alps at the large scale, long-term datasets are needed. To fill the gap between the existing glacier inventories of the Swiss Alps between 1850 and 1973, we digitized glacier outlines from topographic historical maps of Switzerland for the time periods ca. 1900 and ca. 1935. We found that > 88 % of the digitized glacier area was plausible compared to four inventories. The presented dataset is therefore valuable information for long-term glacier studies.
Jan Seibert, Marc J. P. Vis, Irene Kohn, Markus Weiler, and Kerstin Stahl
Hydrol. Earth Syst. Sci., 22, 2211–2224, https://doi.org/10.5194/hess-22-2211-2018, https://doi.org/10.5194/hess-22-2211-2018, 2018
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In many glacio-hydrological models glacier areas are assumed to be constant over time, which is a crucial limitation. Here we describe a novel approach to translate mass balances as simulated by the (glacio)hydrological model into glacier area changes. We combined the Δh approach of Huss et al. (2010) with the bucket-type model HBV and introduced a lookup table approach, which also allows periods with advancing glaciers to be represented, which is not possible with the original Huss method.
Andrew M. Snauffer, William W. Hsieh, Alex J. Cannon, and Markus A. Schnorbus
The Cryosphere, 12, 891–905, https://doi.org/10.5194/tc-12-891-2018, https://doi.org/10.5194/tc-12-891-2018, 2018
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Estimating winter snowpack throughout British Columbia is challenging due to the complex terrain, thick forests, and high snow accumulations present. This paper describes a way to make better snow estimates by combining publicly available data using machine learning, a branch of artificial intelligence research. These improved estimates will help water resources managers better plan for changes in rivers and lakes fed by spring snowmelt and will aid other research that supports such planning.
Erik Tijdeman, Jamie Hannaford, and Kerstin Stahl
Hydrol. Earth Syst. Sci., 22, 1051–1064, https://doi.org/10.5194/hess-22-1051-2018, https://doi.org/10.5194/hess-22-1051-2018, 2018
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In this study, a screening approach was applied on a set of streamflow records for which various human influences are indicated to identify streamflow records that have drought characteristics that deviate from those expected under pristine conditions. Prolonged streamflow drought duration, a weaker correlation between streamflow and precipitation, and changes in streamflow drought occurrence over time were related to human influences such as groundwater abstractions or reservoir operations.
Marit Van Tiel, Adriaan J. Teuling, Niko Wanders, Marc J. P. Vis, Kerstin Stahl, and Anne F. Van Loon
Hydrol. Earth Syst. Sci., 22, 463–485, https://doi.org/10.5194/hess-22-463-2018, https://doi.org/10.5194/hess-22-463-2018, 2018
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Glaciers are important hydrological reservoirs. Short-term variability in glacier melt and also glacier retreat can cause droughts in streamflow. In this study, we analyse the effect of glacier changes and different drought threshold approaches on future projections of streamflow droughts in glacierised catchments. We show that these different methodological options result in different drought projections and that these options can be used to study different aspects of streamflow droughts.
Sophie Bachmair, Cecilia Svensson, Ilaria Prosdocimi, Jamie Hannaford, and Kerstin Stahl
Nat. Hazards Earth Syst. Sci., 17, 1947–1960, https://doi.org/10.5194/nhess-17-1947-2017, https://doi.org/10.5194/nhess-17-1947-2017, 2017
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This study tests the potential for developing empirical
drought impact functionsbased on hydro-meteorological drought indicators as predictors and text-based reports on drought impacts as a surrogate variable for drought damage. We showcase three data-driven modeling approaches and assess the effect of impact report quantification method.
Sandra Pool, Marc J. P. Vis, Rodney R. Knight, and Jan Seibert
Hydrol. Earth Syst. Sci., 21, 5443–5457, https://doi.org/10.5194/hess-21-5443-2017, https://doi.org/10.5194/hess-21-5443-2017, 2017
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This modeling study explores the effect of different model calibration criteria on the accuracy of simulated streamflow characteristics (SFCs). The results imply that one has to consider significant uncertainties when simulated time series are used to derive SFCs that were not included in the calibration. Thus, we strongly recommend calibrating the runoff model explicitly for the SFCs of interest. Our study helps improve the estimation of SFCs for ungauged catchments based on runoff models.
H. J. Ilja van Meerveld, Marc J. P. Vis, and Jan Seibert
Hydrol. Earth Syst. Sci., 21, 4895–4905, https://doi.org/10.5194/hess-21-4895-2017, https://doi.org/10.5194/hess-21-4895-2017, 2017
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We tested the usefulness of stream level class data for hydrological model calibration. Only two stream level classes, e.g. above or below a rock in the stream, were already informative, particularly when the boundary was chosen at a high stream level. There was hardly any improvement in model performance when using more than five stream level classes. These results suggest that model based streamflow time series can be obtained from citizen science based water level class data.
Gregor Laaha, Tobias Gauster, Lena M. Tallaksen, Jean-Philippe Vidal, Kerstin Stahl, Christel Prudhomme, Benedikt Heudorfer, Radek Vlnas, Monica Ionita, Henny A. J. Van Lanen, Mary-Jeanne Adler, Laurie Caillouet, Claire Delus, Miriam Fendekova, Sebastien Gailliez, Jamie Hannaford, Daniel Kingston, Anne F. Van Loon, Luis Mediero, Marzena Osuch, Renata Romanowicz, Eric Sauquet, James H. Stagge, and Wai K. Wong
Hydrol. Earth Syst. Sci., 21, 3001–3024, https://doi.org/10.5194/hess-21-3001-2017, https://doi.org/10.5194/hess-21-3001-2017, 2017
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In 2015 large parts of Europe were affected by a drought. In terms of low flow magnitude, a region around the Czech Republic was most affected, with return periods > 100 yr. In terms of deficit volumes, the drought was particularly severe around S. Germany where the event lasted notably long. Meteorological and hydrological events developed differently in space and time. For an assessment of drought impacts on water resources, hydrological data are required in addition to meteorological indices.
Erik Tijdeman, Sophie Bachmair, and Kerstin Stahl
Hydrol. Earth Syst. Sci., 20, 4043–4059, https://doi.org/10.5194/hess-20-4043-2016, https://doi.org/10.5194/hess-20-4043-2016, 2016
Tracy Ewen and Jan Seibert
Hydrol. Earth Syst. Sci., 20, 4079–4091, https://doi.org/10.5194/hess-20-4079-2016, https://doi.org/10.5194/hess-20-4079-2016, 2016
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Games are an optimal way to teach about water resource sharing, as they allow real-world scenarios to be explored. We look at how games can be used to teach about water resource sharing, by both playing and developing water games. An evaluation of the web-based game Irrigania found Irrigania to be an effective and easy tool to incorporate into curriculum, and a course on developing water games encouraged students to think about water resource sharing in a more critical and insightful way.
Nena Griessinger, Jan Seibert, Jan Magnusson, and Tobias Jonas
Hydrol. Earth Syst. Sci., 20, 3895–3905, https://doi.org/10.5194/hess-20-3895-2016, https://doi.org/10.5194/hess-20-3895-2016, 2016
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In Alpine catchments, snowmelt is a major contribution to runoff. In this study, we address the question of whether the performance of a hydrological model can be enhanced by integrating data from an external snow monitoring system. To this end, a hydrological model was driven with snowmelt input from snow models of different complexities. Best performance was obtained with a snow model, which utilized data assimilation, in particular for catchments at higher elevations and for snow-rich years.
Anne F. Van Loon, Kerstin Stahl, Giuliano Di Baldassarre, Julian Clark, Sally Rangecroft, Niko Wanders, Tom Gleeson, Albert I. J. M. Van Dijk, Lena M. Tallaksen, Jamie Hannaford, Remko Uijlenhoet, Adriaan J. Teuling, David M. Hannah, Justin Sheffield, Mark Svoboda, Boud Verbeiren, Thorsten Wagener, and Henny A. J. Van Lanen
Hydrol. Earth Syst. Sci., 20, 3631–3650, https://doi.org/10.5194/hess-20-3631-2016, https://doi.org/10.5194/hess-20-3631-2016, 2016
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In the Anthropocene, drought cannot be viewed as a natural hazard independent of people. Drought can be alleviated or made worse by human activities and drought impacts are dependent on a myriad of factors. In this paper, we identify research gaps and suggest a framework that will allow us to adequately analyse and manage drought in the Anthropocene. We need to focus on attribution of drought to different drivers, linking drought to its impacts, and feedbacks between drought and society.
Veit Blauhut, Kerstin Stahl, James Howard Stagge, Lena M. Tallaksen, Lucia De Stefano, and Jürgen Vogt
Hydrol. Earth Syst. Sci., 20, 2779–2800, https://doi.org/10.5194/hess-20-2779-2016, https://doi.org/10.5194/hess-20-2779-2016, 2016
S. Bachmair, C. Svensson, J. Hannaford, L. J. Barker, and K. Stahl
Hydrol. Earth Syst. Sci., 20, 2589–2609, https://doi.org/10.5194/hess-20-2589-2016, https://doi.org/10.5194/hess-20-2589-2016, 2016
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To date, there is little empirical evidence as to which indicator best represents drought impact occurrence for any given region and/or sector. We therefore exploited text-based data from the European Drought Impact report Inventory (EDII) to evaluate drought indicators, empirically determine indicator thresholds, and model drought impacts. A quantitative analysis using Germany and the UK as a testbed proved to be a useful tool for objectively appraising drought indicators.
Kerstin Stahl, Irene Kohn, Veit Blauhut, Julia Urquijo, Lucia De Stefano, Vanda Acácio, Susana Dias, James H. Stagge, Lena M. Tallaksen, Eleni Kampragou, Anne F. Van Loon, Lucy J. Barker, Lieke A. Melsen, Carlo Bifulco, Dario Musolino, Alessandro de Carli, Antonio Massarutto, Dionysis Assimacopoulos, and Henny A. J. Van Lanen
Nat. Hazards Earth Syst. Sci., 16, 801–819, https://doi.org/10.5194/nhess-16-801-2016, https://doi.org/10.5194/nhess-16-801-2016, 2016
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Based on the European Drought Impact report Inventory (EDII), the study presents an assessment of the occurrence and diversity of drought impacts across Europe. A unique research database has collected close to 5000 textual drought impact reports from 33 European countries. Consistently, reported impacts have been dominated in number by agriculture and water supply, but were very diverse across other sectors. Data and assessment may help drought policy planning at the international level.
Michal Jenicek, Jan Seibert, Massimiliano Zappa, Maria Staudinger, and Tobias Jonas
Hydrol. Earth Syst. Sci., 20, 859–874, https://doi.org/10.5194/hess-20-859-2016, https://doi.org/10.5194/hess-20-859-2016, 2016
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We quantified how long snowmelt affects runoff, and we estimated the sensitivity of catchments to changes in snowpack. This is relevant as the increase of air temperature might cause decreased snow storage. We used time series from 14 catchments in Switzerland. On average, a decrease of maximum snow storage by 10 % caused a decrease of minimum discharge in July by 2 to 9 %. The results showed a higher sensitivity of summer low flow to snow in alpine catchments compared to pre-alpine catchments.
M. Rinderer, H. C. Komakech, D. Müller, G. L. B. Wiesenberg, and J. Seibert
Hydrol. Earth Syst. Sci., 19, 3505–3516, https://doi.org/10.5194/hess-19-3505-2015, https://doi.org/10.5194/hess-19-3505-2015, 2015
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A field method for assessing soil moisture in semi-arid conditions is proposed and tested in terms of inter-rater reliability with 40 Tanzanian farmers, students and experts. The seven wetness classes are based on qualitative indicators that one can see, feel or hear. It could be shown that the qualitative wetness classes reflect differences in volumetric water content and neither experience nor a certain level of education was a prerequisite to gain high agreement among raters.
J. E. Reynolds, S. Halldin, C. Y. Xu, J. Seibert, and A. Kauffeldt
Hydrol. Earth Syst. Sci. Discuss., https://doi.org/10.5194/hessd-12-7437-2015, https://doi.org/10.5194/hessd-12-7437-2015, 2015
Revised manuscript not accepted
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In this study it was found that time-scale dependencies of hydrological model parameters are a result of the numerical method used in the model rather than a real time-scale-data dependence. This study further indicates that as soon as sub-daily driving data can be secured, flood forecasting in watersheds with sub-daily concentration times is possible with model parameter values inferred from long time series of daily data, as long as an appropriate numerical method is used.
A. K. Fleig, L. M. Tallaksen, P. James, H. Hisdal, and K. Stahl
Hydrol. Earth Syst. Sci., 19, 3093–3107, https://doi.org/10.5194/hess-19-3093-2015, https://doi.org/10.5194/hess-19-3093-2015, 2015
S. Bachmair, I. Kohn, and K. Stahl
Nat. Hazards Earth Syst. Sci., 15, 1381–1397, https://doi.org/10.5194/nhess-15-1381-2015, https://doi.org/10.5194/nhess-15-1381-2015, 2015
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There is little knowledge on the meaning of different hydro-meteorologic drought indicators for drought impact occurrence on the ground. This study investigates the link between commonly used drought indicators and text-based information on drought impacts through data visualization, extraction of indicator values concurrent with impact onset, and correlation analysis for the case study area Germany. The results demonstrate the feasibility of evaluating drought indicators with impacts.
M. Staudinger, M. Weiler, and J. Seibert
Hydrol. Earth Syst. Sci., 19, 1371–1384, https://doi.org/10.5194/hess-19-1371-2015, https://doi.org/10.5194/hess-19-1371-2015, 2015
I. K. Westerberg, L. Gong, K. J. Beven, J. Seibert, A. Semedo, C.-Y. Xu, and S. Halldin
Hydrol. Earth Syst. Sci., 18, 2993–3013, https://doi.org/10.5194/hess-18-2993-2014, https://doi.org/10.5194/hess-18-2993-2014, 2014
D. Freudiger, I. Kohn, K. Stahl, and M. Weiler
Hydrol. Earth Syst. Sci., 18, 2695–2709, https://doi.org/10.5194/hess-18-2695-2014, https://doi.org/10.5194/hess-18-2695-2014, 2014
P. Schneider, S. Pool, L. Strouhal, and J. Seibert
Hydrol. Earth Syst. Sci., 18, 875–892, https://doi.org/10.5194/hess-18-875-2014, https://doi.org/10.5194/hess-18-875-2014, 2014
C. Teutschbein and J. Seibert
Hydrol. Earth Syst. Sci., 17, 5061–5077, https://doi.org/10.5194/hess-17-5061-2013, https://doi.org/10.5194/hess-17-5061-2013, 2013
J. Hannaford, G. Buys, K. Stahl, and L. M. Tallaksen
Hydrol. Earth Syst. Sci., 17, 2717–2733, https://doi.org/10.5194/hess-17-2717-2013, https://doi.org/10.5194/hess-17-2717-2013, 2013
M. Stoelzle, K. Stahl, and M. Weiler
Hydrol. Earth Syst. Sci., 17, 817–828, https://doi.org/10.5194/hess-17-817-2013, https://doi.org/10.5194/hess-17-817-2013, 2013
Related subject area
Subject: Catchment hydrology | Techniques and Approaches: Modelling approaches
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?
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
Impacts of climate and land-surface change on catchment evapotranspiration and runoff from 1951–2020 in Saxony, Germany
Projecting sediment export from two highly glacierized alpine catchments under climate change: exploring non-parametric regression as an analysis tool
Evolution of river regime in the Mekong River basin over eight decades and role of dams in recent hydrologic extremes
A framework for parameter estimation, sensitivity analysis, and uncertainty analysis for holistic hydrologic modeling using SWAT+
On understanding mountainous carbonate basins of the Mediterranean using parsimonious modeling solutions
Comparing quantile regression forest and mixture density long short-term memory models for probabilistic post-processing of satellite precipitation-driven streamflow simulations
Recent ground thermo-hydrological changes in a southern Tibetan endorheic catchment and implications for lake level changes
Towards robust seasonal streamflow forecasts in mountainous catchments: impact of calibration metric selection in hydrological modeling
Modelling flood frequency and magnitude in a glacially conditioned, heterogeneous landscape: testing the importance of land cover and land use
When ancient numerical demons meet physics-informed machine learning: adjoint-based gradients for implicit differentiable modeling
Direct integration of reservoirs' operations in a hydrological model for streamflow estimation: coupling a CLSTM model with MOHID-Land
Skill of seasonal flow forecasts at catchment-scale: an assessment across South Korea
Modelling the regional sensitivity of snowmelt, soil moisture, and streamflow generation to climate over the Canadian Prairies using a basin classification approach
To what extent does river routing matter in hydrological modeling?
Calibrating macroscale hydrological models in poorly gauged and heavily regulated basins
An advanced tool integrating failure and sensitivity analysis into novel modeling of the stormwater flood volume
To Bucket or not to Bucket? Analyzing the performance and interpretability of hybrid hydrological models with dynamic parameterization
airGRteaching: an open-source tool for teaching hydrological modeling with R
Assessing the impact of climate change on high return levels of peak flows in Bavaria applying the CRCM5 Large Ensemble
To What Extent Do Extreme Storm Events Change Future Flood Hazards?
Stable water isotopes and tritium tracers tell the same tale: no evidence for underestimation of catchment transit times inferred by stable isotopes in StorAge Selection (SAS)-function models
Regionalization of GR4J model parameters for river flow prediction in Paraná, Brazil
Uncertainty in water transit time estimation with StorAge Selection functions and tracer data interpolation
Changes in Mediterranean flood processes and seasonality
Can the combining of wetlands with reservoir operation reduce the risk of future floods and droughts?
Knowledge-informed deep learning for hydrological model calibration: an application to Coal Creek Watershed in Colorado
When best is the enemy of good – critical evaluation of performance criteria in hydrological models
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.
Eduardo Acuña Espinoza, Ralf Loritz, Manuel Álvarez Chaves, Nicole Bäuerle, and Uwe Ehret
EGUsphere, https://doi.org/10.5194/egusphere-2023-1980, https://doi.org/10.5194/egusphere-2023-1980, 2023
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Hydrological hybrid models 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 LSTM networks. We explored this method to evaluate if the flexibility given by LSTM overwrites the interpretability of the process-based part. We showed that if a well-tested model architecture is combined with an LSTM, the latter can learn to operate the process-based model consistently.
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.
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Short summary
Several multivariate bias correction methods have been developed recently, but only a few studies have tested the effect of multivariate bias correction on hydrological impact projections. This study shows that incorporating or ignoring inter-variable relations between air temperature and precipitation can have a notable effect on the projected snowfall fraction. The effect translated to considerable consequences for the glacio-hydrological responses and streamflow components of the catchments.
Several multivariate bias correction methods have been developed recently, but only a few...
