Articles | Volume 21, issue 12
https://doi.org/10.5194/hess-21-6401-2017
© Author(s) 2017. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
Special issue:
https://doi.org/10.5194/hess-21-6401-2017
© Author(s) 2017. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
Research article
| 
15 Dec 2017
Research article |
| 15 Dec 2017
Development of a monthly to seasonal forecast framework tailored to inland waterway transport in central Europe
Dennis Meißner
CORRESPONDING AUTHOR
Federal Institute of Hydrology, 56068 Koblenz, Germany
Bastian Klein
Federal Institute of Hydrology, 56068 Koblenz, Germany
Monica Ionita
Alfred-Wegener-Institute, 27568 Bremerhaven, Germany
MARUM, Bremen University, Bremen, Germany
Related authors
No articles found.
Monica Ionita, Petru Vaideanu, Bogdan Antonescu, Catalin Roibu, Qiyun Ma, and Viorica Nagavciuc
EGUsphere, https://doi.org/10.5194/egusphere-2024-1207, https://doi.org/10.5194/egusphere-2024-1207, 2024
Short summary
Short summary
Eastern Europe's heatwave history is explored from 1885 to 2023, with a focus on pre-1960 events. The study reveals two periods with more frequent and intense heatwaves (HW): 1920s–1960s and 1980s–present. The research highlights the importance of a long-term perspective, revealing that extreme heat events have occurred throughout the entire study period and it emphasizes the combined influence of climate change and natural variations on increasing HW severity.
Viorica Nagavciuc, Simon L. L. Michel, Daniel F. Balting, Gerhard Helle, Mandy Freund, Gerhard H. Schleser, David N. Steger, Gerrit Lohmann, and Monica Ionita
Clim. Past, 20, 573–595, https://doi.org/10.5194/cp-20-573-2024, https://doi.org/10.5194/cp-20-573-2024, 2024
Short summary
Short summary
The main aim of this paper is to present the summer vapor pressure deficit (VPD) reconstruction dataset for the last 400 years over Europe based on δ18O records by using a random forest approach. We provide both a spatial and a temporal long-term perspective on the past summer VPD and new insights into the relationship between summer VPD and large-scale atmospheric circulation. This is the first gridded reconstruction of the European summer VPD over the past 400 years.
Anne F. Van Loon, Sarra Kchouk, Alessia Matanó, Faranak Tootoonchi, Camila Alvarez-Garreton, Khalid E. A. Hassaballah, Minchao Wu, Marthe L. K. Wens, Anastasiya Shyrokaya, Elena Ridolfi, Riccardo Biella, Viorica Nagavciuc, Marlies H. Barendrecht, Ana Bastos, Louise Cavalcante, Franciska T. de Vries, Margaret Garcia, Johanna Mård, Ileen N. Streefkerk, Claudia Teutschbein, Roshanak Tootoonchi, Ruben Weesie, Valentin Aich, Juan P. Boisier, Giuliano Di Baldassarre, Yiheng Du, Mauricio Galleguillos, René Garreaud, Monica Ionita, Sina Khatami, Johanna K. L. Koehler, Charles H. Luce, Shreedhar Maskey, Heidi D. Mendoza, Moses N. Mwangi, Ilias G. Pechlivanidis, Germano G. Ribeiro Neto, Tirthankar Roy, Robert Stefanski, Patricia Trambauer, Elizabeth A. Koebele, Giulia Vico, and Micha Werner
EGUsphere, https://doi.org/10.5194/egusphere-2024-421, https://doi.org/10.5194/egusphere-2024-421, 2024
Short summary
Short summary
Drought is a creeping phenomenon, but it is often still analysed and managed like an event without taking into consideration what happened before and after. In this paper we review the literature and discuss five cases, where drought, its impacts and responses develop differently over time. We look at the hydrological, ecological and social system and their connections. And we provide suggestions for further research and for monitoring, modelling and management.
Di Cai, Gerrit Lohmann, Xianyao Chen, and Monica Ionita
EGUsphere, https://doi.org/10.5194/egusphere-2023-1646, https://doi.org/10.5194/egusphere-2023-1646, 2023
Preprint archived
Short summary
Short summary
Our study reveals how a decline in autumn sea ice in the Barents-Kara Seas leads to severe winters in Europe. Using observational data, we illustrate that Arctic sea ice loss isn't just a local issue – it impacts harsh winter conditions globally. Current climate models struggle to reflect these effects accurately, indicating a need for more research. Gaining a more nuanced understanding of this relationship will enhance our climate predictions and preparation for future extremes.
Heidi Kreibich, Kai Schröter, Giuliano Di Baldassarre, Anne F. Van Loon, Maurizio Mazzoleni, Guta Wakbulcho Abeshu, Svetlana Agafonova, Amir AghaKouchak, Hafzullah Aksoy, Camila Alvarez-Garreton, Blanca Aznar, Laila Balkhi, Marlies H. Barendrecht, Sylvain Biancamaria, Liduin Bos-Burgering, Chris Bradley, Yus Budiyono, Wouter Buytaert, Lucinda Capewell, Hayley Carlson, Yonca Cavus, Anaïs Couasnon, Gemma Coxon, Ioannis Daliakopoulos, Marleen C. de Ruiter, Claire Delus, Mathilde Erfurt, Giuseppe Esposito, Didier François, Frédéric Frappart, Jim Freer, Natalia Frolova, Animesh K. Gain, Manolis Grillakis, Jordi Oriol Grima, Diego A. Guzmán, Laurie S. Huning, Monica Ionita, Maxim Kharlamov, Dao Nguyen Khoi, Natalie Kieboom, Maria Kireeva, Aristeidis Koutroulis, Waldo Lavado-Casimiro, Hong-Yi Li, Maria Carmen LLasat, David Macdonald, Johanna Mård, Hannah Mathew-Richards, Andrew McKenzie, Alfonso Mejia, Eduardo Mario Mendiondo, Marjolein Mens, Shifteh Mobini, Guilherme Samprogna Mohor, Viorica Nagavciuc, Thanh Ngo-Duc, Huynh Thi Thao Nguyen, Pham Thi Thao Nhi, Olga Petrucci, Nguyen Hong Quan, Pere Quintana-Seguí, Saman Razavi, Elena Ridolfi, Jannik Riegel, Md Shibly Sadik, Nivedita Sairam, Elisa Savelli, Alexey Sazonov, Sanjib Sharma, Johanna Sörensen, Felipe Augusto Arguello Souza, Kerstin Stahl, Max Steinhausen, Michael Stoelzle, Wiwiana Szalińska, Qiuhong Tang, Fuqiang Tian, Tamara Tokarczyk, Carolina Tovar, Thi Van Thu Tran, Marjolein H. J. van Huijgevoort, Michelle T. H. van Vliet, Sergiy Vorogushyn, Thorsten Wagener, Yueling Wang, Doris E. Wendt, Elliot Wickham, Long Yang, Mauricio Zambrano-Bigiarini, and Philip J. Ward
Earth Syst. Sci. Data, 15, 2009–2023, https://doi.org/10.5194/essd-15-2009-2023, https://doi.org/10.5194/essd-15-2009-2023, 2023
Short summary
Short summary
As the adverse impacts of hydrological extremes increase in many regions of the world, a better understanding of the drivers of changes in risk and impacts is essential for effective flood and drought risk management. We present a dataset containing data of paired events, i.e. two floods or two droughts that occurred in the same area. The dataset enables comparative analyses and allows detailed context-specific assessments. Additionally, it supports the testing of socio-hydrological models.
Viorica Nagavciuc, Patrick Scholz, and Monica Ionita
Nat. Hazards Earth Syst. Sci., 22, 1347–1369, https://doi.org/10.5194/nhess-22-1347-2022, https://doi.org/10.5194/nhess-22-1347-2022, 2022
Short summary
Short summary
Here we have assessed the variability and trends of hot and dry summers in Romania. The length, spatial extent, and frequency of heat waves in Romania have increased significantly over the last 70 years, while no significant changes have been observed in the drought conditions. The increased frequency of heat waves, especially after the 1990s, could be partially explained by an increase in the geopotential height over the eastern part of Europe.
Daniel Balting, Simon Michel, Viorica Nagavciuc, Gerhard Helle, Mandy Freund, Gerhard H. Schleser, David Steger, Gerrit Lohmann, and Monica Ionita
Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2022-47, https://doi.org/10.5194/essd-2022-47, 2022
Preprint withdrawn
Short summary
Short summary
Vapor pressure deficit is a key component of vegetation dynamics, soil science, meteorology, and soil science. In this study, we reconstruct the variability of the vapor pressure deficit in the past and examine the changes in future scenarios using climate models. In this way, past, present and future changes of the vapor pressure deficit can be detected locally, regionally, and continentally with higher statistical significance.
Petru Cosmin Vaideanu, Mihai Dima, Monica Ionita, and Mirela Voiculescu
Earth Syst. Dynam. Discuss., https://doi.org/10.5194/esd-2021-75, https://doi.org/10.5194/esd-2021-75, 2021
Revised manuscript not accepted
Short summary
Short summary
Observing clouds and their properties is not straightforward, however, these are important for reducing climate models uncertainties. Ground-based observations are spatially limited while satellite data are accompanied by various artefacts. In this paper, we use corrected observational and state-of-the-art reanalysis cloud data to show that the recent evolution of total cloud cover on a global scale is linked to the Eastern Pacific and the Central Pacific El Niño–Southern Oscillation.
Monica Ionita and Viorica Nagavciuc
Nat. Hazards Earth Syst. Sci., 21, 1685–1701, https://doi.org/10.5194/nhess-21-1685-2021, https://doi.org/10.5194/nhess-21-1685-2021, 2021
Short summary
Short summary
By analyzing the joint frequency of compound events (e.g., high temperatures and droughts), we show that the potential evapotranspiration and mean air temperature are becoming essential components for drought occurrence over Central Europe and the Mediterranean region. This, together with the projected increase in potential evapotranspiration under a warming climate, has significant implications concerning the future occurrence of drought events over these regions.
Aurel Perşoiu, Nenad Buzjak, Alexandru Onaca, Christos Pennos, Yorgos Sotiriadis, Monica Ionita, Stavros Zachariadis, Michael Styllas, Jure Kosutnik, Alexandru Hegyi, and Valerija Butorac
The Cryosphere, 15, 2383–2399, https://doi.org/10.5194/tc-15-2383-2021, https://doi.org/10.5194/tc-15-2383-2021, 2021
Short summary
Short summary
Extreme precipitation events in summer 2019 led to catastrophic loss of cave and surface ice in SE Europe at levels unprecedented during the last century. The projected continuous warming and increase in precipitation extremes could pose an additional threat to glaciers in southern Europe, resulting in a potentially ice-free SE Europe by the middle of the next decade (2035 CE).
Daniel F. Balting, Monica Ionita, Martin Wegmann, Gerhard Helle, Gerhard H. Schleser, Norel Rimbu, Mandy B. Freund, Ingo Heinrich, Diana Caldarescu, and Gerrit Lohmann
Clim. Past, 17, 1005–1023, https://doi.org/10.5194/cp-17-1005-2021, https://doi.org/10.5194/cp-17-1005-2021, 2021
Short summary
Short summary
To extend climate information back in time, we investigate the climate sensitivity of a δ18O network from tree rings, consisting of 26 European sites and covering the last 400 years. Our results suggest that the δ18O variability is associated with large-scale anomaly patterns that resemble those observed for the El Niño–Southern Oscillation. We conclude that the investigation of large-scale climate signals far beyond instrumental records can be done with a δ18O network derived from tree rings.
Carmen-Andreea Bădăluţă, Aurel Perșoiu, Monica Ionita, and Natalia Piotrowska
Clim. Past, 16, 2445–2458, https://doi.org/10.5194/cp-16-2445-2020, https://doi.org/10.5194/cp-16-2445-2020, 2020
Short summary
Short summary
We present a reconstruction of summer temperature for the last millennium in east-central Europe that shows little summer temperature differences between the Medieval Warm Period and the Little Ice Age on centennial scales as well as the fact that well-expressed minima and maxima occurred synchronously with periods of low and high solar activity, respectively. Furthermore, summer temperatures fluctuated with a periodicity similar to that of the Atlantic Multidecadal Oscillation.
Sigrid J. Bakke, Monica Ionita, and Lena M. Tallaksen
Hydrol. Earth Syst. Sci., 24, 5621–5653, https://doi.org/10.5194/hess-24-5621-2020, https://doi.org/10.5194/hess-24-5621-2020, 2020
Short summary
Short summary
This study provides an in-depth analysis of the 2018 northern European drought. Large parts of the region experienced 60-year record-breaking temperatures, linked to high-pressure systems and warm surrounding seas. Meteorological drought developed from May and, depending on local conditions, led to extreme low flows and groundwater drought in the following months. The 2018 event was unique in that it affected most of Fennoscandia as compared to previous droughts.
Monica Ionita, Viorica Nagavciuc, and Bin Guan
Hydrol. Earth Syst. Sci., 24, 5125–5147, https://doi.org/10.5194/hess-24-5125-2020, https://doi.org/10.5194/hess-24-5125-2020, 2020
Short summary
Short summary
Analysis of the largest 10 floods in the lower Rhine, between 1817 and 2015, shows that all these extreme flood peaks have been preceded, up to 7 d in advance, by intense moisture transport from the tropical North Atlantic basin in the form of narrow bands also known as atmospheric rivers. The results presented in this study offer new insights regarding the importance of moisture transport as the driver of extreme flooding in the lower part of the Rhine catchment area.
Aurel Perşoiu, Monica Ionita, and Harvey Weiss
Clim. Past, 15, 781–793, https://doi.org/10.5194/cp-15-781-2019, https://doi.org/10.5194/cp-15-781-2019, 2019
Short summary
Short summary
We present a reconstruction of winter climate around 4.2 ka cal BP in Europe, west Asia, and northern Africa that shows generally low temperatures and heterogeneously distributed precipitation. We hypothesize that in the extratropical Northern Hemisphere the 4.2 ka BP event was caused by the strengthening and expansion of the Siberian High, which effectively blocked the moisture-carrying westerlies from reaching west Asia and also resulted in outbreaks of northerly cold and dry winds.
Monica Ionita, Klaus Grosfeld, Patrick Scholz, Renate Treffeisen, and Gerrit Lohmann
Earth Syst. Dynam., 10, 189–203, https://doi.org/10.5194/esd-10-189-2019, https://doi.org/10.5194/esd-10-189-2019, 2019
Short summary
Short summary
Based on a simple statistical model we show that the September sea ice extent has a high predictive skill, up to 4 months ahead, based on previous months' oceanic and atmospheric conditions. Our statistical model skillfully captures the interannual variability of the September sea ice extent and could provide a valuable tool for identifying relevant regions and oceanic and atmospheric parameters that are important for the sea ice development in the Arctic.
Monica Ionita, Patrick Scholz, Klaus Grosfeld, and Renate Treffeisen
Earth Syst. Dynam., 9, 939–954, https://doi.org/10.5194/esd-9-939-2018, https://doi.org/10.5194/esd-9-939-2018, 2018
Short summary
Short summary
In austral spring 2016 the Antarctic region experienced anomalous sea ice retreat in all sectors, with sea ice extent in October and November 2016 being the lowest in the Southern Hemisphere over the observational record (1979–present). The extreme sea ice retreat was accompanied by the wettest and warmest spring on record, over large areas covering the Indian ocean, the Ross Sea, and the Weddell Sea.
Carmen-Andreea Bădăluță, Aurel Perșoiu, Monica Ionita, Viorica Nagavciuc, and Petruț-Ionel Bistricean
Hydrol. Earth Syst. Sci. Discuss., https://doi.org/10.5194/hess-2018-6, https://doi.org/10.5194/hess-2018-6, 2018
Manuscript not accepted for further review
Norel Rimbu, Monica Ionita, Markus Czymzik, Achim Brauer, and Gerrit Lohmann
Clim. Past Discuss., https://doi.org/10.5194/cp-2017-137, https://doi.org/10.5194/cp-2017-137, 2017
Manuscript not accepted for further review
Short summary
Short summary
Multi-decadal to millennial flood frequency variations in the Mid- to Late Holocene in a flood layer record from Lake Ammersee is strongly related to the occurrence of extreme precipitation and temperatures in the northeastern Europe.
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
Short summary
Short summary
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.
Monica Ionita, Lena M. Tallaksen, Daniel G. Kingston, James H. Stagge, Gregor Laaha, Henny A. J. Van Lanen, Patrick Scholz, Silvia M. Chelcea, and Klaus Haslinger
Hydrol. Earth Syst. Sci., 21, 1397–1419, https://doi.org/10.5194/hess-21-1397-2017, https://doi.org/10.5194/hess-21-1397-2017, 2017
Short summary
Short summary
This paper analyses the European summer drought of 2015 from a climatological perspective, including its origin and spatial and temporal development, and how it compares with the 2003 event. It discusses the main contributing factors controlling the occurrence and persistence of the event: temperature and precipitation anomalies, blocking episodes and sea surface temperatures. The results represent the outcome of a collaborative initiative of members of UNESCO’s FRIEND-Water program.
Norel Rimbu, Markus Czymzik, Monica Ionita, Gerrit Lohmann, and Achim Brauer
Clim. Past, 12, 377–385, https://doi.org/10.5194/cp-12-377-2016, https://doi.org/10.5194/cp-12-377-2016, 2016
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
The Kling–Gupta Efficiency (KGE) is a performance criterion extensively used to evaluate hydrological models. We conduct a critical study on the KGE and its variant to examine counterbalancing errors. Results show that, when assessing a simulation, concurrent over- and underestimation of discharge can lead to an overall higher criterion score without an associated increase in model relevance. We suggest that one carefully choose performance criteria and use scaling factors.
Cited articles
Alverado Montero, R., Schwanenberg, D., Krahe, P., Lisniak, D., Sensoy, A., Sorman, A. A., and Akkol, B.: Moving horizon estimation for assimilating H-SAF remote sensing data into the HBV hydrological model, Adv. Water Resour., 92, 248–257, https://doi.org/10.1016/j.advwatres.2016.04.011, 2016.
Bell, V. A., Davies, H. N., Kay, A. L., Brookshaw, A., and Scaife, A. A.: A national-scale seasonal hydrological forecast system: development and evaluation over Britain, Hydrol. Earth Syst. Sci., 21, 4681–4691, https://doi.org/10.5194/hess-21-4681-2017, 2017.
Beven, K. J.: Equifinality and Uncertainty in Geomorphological Modelling, in: The Scientific Nature of Geomorphology, edited by: Rhoads, B. L. and Thorn, C. E., Wiley, Chichester, UK, 289–313, 1996.
CCNR: Annual Report 2016 – Inland Navigation in Europe – Market Observation, Central Commission for the Navigation of the Rhine, Strasbourg, France, 2016.
Crochemore, L., Ramos, M.-H., and Pappenberger, F.: Bias correcting precipitation forecasts to improve the skill of seasonal streamflow forecasts, Hydrol. Earth Syst. Sci., 20, 3601–3618, https://doi.org/10.5194/hess-20-3601-2016, 2016.
Day, G. N.: Extended streamflow forecasting using NWSRFS, J. Water Resour. Plan. Man., 111, 157–170, 1985.
Dee, D. P., Uppala, S. M., Simmons, A. J., Berrisford, P., Poli, P., Kobayashi, S., Andrae, U., Balmaseda, M. A., Balsamo, G., Bauer, P., Bechtold, P., Beljaars, A. C. M., van de Berg, L., Bidlot, J., Bormann, N., Delsol, C., Dragani, R., Fuentes, M., Geer, A. J., Haimberger, L., Healy, S. B., Hersbach, H., Holm, E. V., Isaksen, L., Kallberg, P., Kohler, M., Matricardi, M., McNally, A. P., Monge-Sanz, B. M., Morcrette, J. J., Park, B. K., Peubey, C., de Rosnay, P., Tavolato, C., Thepaut, J. N., and Vitart, F.: The ERA-Interim reanalysis: configuration and performance of the data assimilation system, Q. J. Roy. Meteorol. Soc., 137, 553–597, 2011.
Demirel, M. C., Booij, M. J., and Hoekstra, A. Y.: Identification of appropriate lags and temporal resolutions for low flow indicators in the River Rhine to forecast low flows with different lead times, Hydrol. Proc., 27, 2742–2758, https://doi.org/10.1002/hyp.9402, 2012.
Demirel, M. C., Booij, M. J., and Hoekstra, A. Y.: Effect of different uncertainty sources on the skill of 10 day ensemble low flow forecasts for two hydrological models, Water Resour. Res., 49, 4035–4053, https://doi.org/10.1002/wrcr.20294, 2013.
Demirel, M. C., Booij, M. J., and Hoekstra, A. Y.: The skill of seasonal ensemble low-flow forecasts in the Moselle River for three different hydrological models, Hydrol. Earth Syst. Sci., 19, 275–291, https://doi.org/10.5194/hess-19-275-2015, 2015.
Domeisen, D. I. V., Butler, A. H., Fröhlich, K., Bittner, M., Müller, W. A., and Baehr, J.: Seasonal Predictability over Europe Arising from El Niño and Stratospheric Variability in the MPI-ESM Seasonal Prediction System, J. Climate, 28, 256–271, https://doi.org/10.1175/JCLI-D-14-00207.1, 2015.
DWD: Deliverable D.1.7 Gridded 20 yr dataset of surface solar radiation, cloud albedo, cloud fraction and surface albedo derived from MVIRI (SEVIRI) using the Heliosat method (0.05°), EU funded project EURO4M, EURO4M project report, available at http://www.euro4m.eu/downloads/D1.7_Gridded-20yr-dataset-of-SIS-SAL-CFC-CAL-derived-from-MVIRI-SEVIRI.pdf (last access: 11 December 2017), 2013.
European Commission: White paper – European transport policy for 2010: time to decide, COM(2001)370, Brussels, available at: https://ec.europa.eu/transport/sites/transport/files/themes/strategies/doc/2001_white_paper/lb_com_2001_0370_en.pdf (last access: 11 December 2017), 2001.
Fundel, F. and Zappa, M.: Hydrological Ensemble Forecasting in Mesoscale Catchments: Sensitivity to Initial Conditions and Value of Reforecasts, Water Resour. Res., 47, W09520, https://doi.org/10.1029/2010WR009996, 2011.
Fundel, F., Jörg-Hess, S., and Zappa, M.: Monthly hydrometeorological ensemble prediction of streamflow droughts and corresponding drought indices, Hydrol. Earth Syst. Sci., 17, 395–407, https://doi.org/10.5194/hess-17-395-2013, 2013.
Funk, D., Pouget, L., Dubus, L., Falloon, P., Meißner, D., Klein, B., Palin, E., Viel, C., Foster, K., Lootvoet, M., Bosi, L., Creswick, J., Davis, M., and Jimenez, I.: White paper on sector specific vulnerabilities, Deliverable 11.2, EUPORIAS – European Provision Of Regional Impacts Assessments on Seasonal and Decadal Timescales, Grant Agreement 308291, EUPORIAS project report, available at: http://www.euporias.eu/system/files/D11.2_Final.pdf (last access: 11 December 2017), 2015.
Gámiz-Fortis, S., Pozo-Vázquez, D., Trigo, R. M., and Castro-Díez, Y.: Quantifying the predictability of winter river flow in Iberia, Part II: seasonal predictability, J. Climate, 21, 2503–2518, 2008.
Gelfan, A. N., Motovilov, Yu. G., and Moreido, V. M.: Ensemble seasonal forecast of extreme water inflow into a large reservoir, Proc. IAHS, 369, 115–120, https://doi.org/10.5194/piahs-369-115-2015, 2015.
Haag, I., Johst, M., Sieber, A., and Bremicker, M.: Guideline for the Calibration of LARSIM Water Balance Models for operational Application in Flood Forecasting–Calibration Guide, available at: http://hmdblog.rlp.de/luwg/larsim/, last access: 3 March 2016.
Haylock, M. R., Hofstra, N., Klein Tank, A. M. G., Klok, E. J., Jones, P. D., and New, M. A.: European daily high-resolution gridded dataset of surface temperature and precipitation, J. Geophys. Res.-Atmos., 113, D20119, https://doi.org/10.1029/2008JD010201, 2008.
Hersbach, H.: Decomposition of the continuous ranked probability score for ensemble prediction systems, Weather Forecast., 15, 559–570, 2000.
Huang, B., Banzon, V. F., Freeman, E., Lawrimore, J., Liu, W., Peterson, T. C., Smith, T. M., Thorne, P. W., Woodruff, S. D., and Zhang, H.-M.: Extended Reconstructed Sea Surface Temperature version 4 (ERSST.v4): Part I, Upgrades and intercomparisons, J. Climate, 28, 911–930, https://doi.org/10.1175/JCLI-D-14-00006.1, 2014.
Leander, R. and Buishand, T.: Resampling of regional climate model output forthe simulation of extreme river flows, J. Hydrol., 332, 487–496, 2007.
Ionita, M., Lohmann, G., and Rimbu, N.: Prediction of Elbe discharge based on stable teleconnections with winter global temperature and precipitation, J. Climate, 21, 6215–6226, 2008.
Ionita, M., Lohmann, G., Rimbu, N., and Chelcea, S.: Interannual Variability of Rhine River Streamflow and Its Relationship with Large-Scale Anomaly Patterns in Spring and Autumn, J. Hydrometeorol., 13, 172–188, 2012.
Ionita, M., Dima, M., Lohmann, G., Scholz, P., and Rimbu, N.: Predicting the June 2013 European Flooding based on Precipitation, Soil Moisture and Sea Level Pressure, J. Hydrometeorol., 16, 598–614, https://doi.org/10.1175/JHM-D-14-0156.1, 2014.
Ionita, M., Tallaksen, L. M., Kingston, D. G., Stagge, J. H., Laaha, G., Van Lanen, H. A. J., Scholz, P., Chelcea, S. M., and Haslinger, K.: The European 2015 drought from a climatological perspective, Hydrol. Earth Syst. Sci., 21, 1397–1419, https://doi.org/10.5194/hess-21-1397-2017, 2017.
Jörg-Hess, S., Griessinger, N., and Zappa, M.: Probabilistic Forecasts of Snow Water Equivalent and Runoff in Mountainous Areas, J. Hydrometeorol., 16, 2169–2186, https://doi.org/10.1175/JHM-D-14-0193.1, 2015.
Kalnay, E., Kanamitsu, M., Kistler, R., Collins, W., Deaven, D., Gandin, L., Iredell, M., Saha, S., White, G., Woollen, J., Zhu, Y., Leetmaa, A., Reynolds, R., Chelliah, M., Ebisuzaki, W., Higgins, W., Janowiak, J., Mo, K. C., Ropelewski, C., Wang, J., Jenne, R., and Joseph, D.: The NCEP/NCAR 40-year reanalysis project, B. Am. Meteorol. Soc., 77, 437–470, 1996.
Kistler, R., Collins, W., Saha, S., White, G., Woollen, J., Kalnay, E., Chelliah, M., Ebisuzaki, W., Kanamitsu, M., Kousky, V., van den Dool, H., Jenne, R., and Fiorino, M.: The NCEP-NCAR 50-Year Reanalysis: Monthly Means CD-ROM and Documentation, B. Am. Meteorol. Soc., 82, 247–267, https://doi.org/10.1175/1520-0477(2001)082<0247:TNNYRM>2.3.CO;2, 2001.
Klein, B. and Meißner, D.: Vulnerability of Inland Waterway Transport and Waterway Management on Hydro-meteorological Extremes, Deliverable 9.1, IMPREX (Improving Predictions of Hydrological Extremes), Grant Agreement Number 641811, IMPREX project report, available at: http://www.imprex.eu/system/files/generated/files/resource/d9-1-imprex-v2-0.pdf (last access: 11 December 2017), 2016.
Laaha, G., Gauster, T., Tallaksen, L. M., Vidal, J.-P., Stahl, K., Prudhomme, C., Heudorfer, B., Vlnas, R., Ionita, M., Van Lanen, H. A. J., Adler, M.-J., Caillouet, L., Delus, C., Fendekova, M., Gailliez, S., Hannaford, J., Kingston, D., Van Loon, A. F., Mediero, L., Osuch, M., Romanowicz, R., Sauquet, E., Stagge, J. H., and Wong, W. K.: The European 2015 drought from a hydrological perspective, Hydrol. Earth Syst. Sci., 21, 3001–3024, https://doi.org/10.5194/hess-21-3001-2017, 2017.
Lenderink, G., Buishand, A., and van Deursen, W.: Estimates of future discharges of the river Rhine using two scenario methodologies: direct versus delta approach, Hydrol. Earth Syst. Sci., 11, 1145–1159, https://doi.org/10.5194/hess-11-1145-2007, 2007.
Lohmann, G., Rimbu, N., and Dima, M.: Where can the Arctic oscillation be reconstructed? Towards a reconstruction of climate modes based on stable teleconnections, Clim. Past Discuss., https://doi.org/10.5194/cpd-1-17-2005, 2005.
Ludwig, K. and Bremicker, M.: The Water Balance Model LARSIM, Design, Content and Applications, edited by: Leibundgut, C., Demuth, S., and Lange, J., Freiburger Schriften zur Hydrologie, Institut für Hydrologie, Universität Freiburg im Breisgau, Freiburg, 141 pp., 2006.
Marke, T.: Development and Application of a Model Interface to couple Land Surface Models with Regional Climate Models for Climate Change Risk Assessment in the Upper Danube Watershed, Dissertation, LMU München, Fakultät für Geowissenschaften, 2008.
Maurer, E. P. and Lettenmaier, D. P.: Predictability of seasonal runoff in the Mississippi river basin, J. Geophys. Res., 108, 8607, https://doi.org/10.1029/2002JD002555, 2003.
Meißner, D. and Klein, B.: Probabilistic Shipping Forecast, in: “Handbook of Hydrometeorological Ensemble Forecasting”, edited by: Duan, Q., Pappenberger, F., Thielen, J., Wood, A., Cloke, H. L., and Schaake, J. C., Springer, https://doi.org/10.1007/978-3-642-40457-3_58-1, 2016.
Molteni, F., Stockdale, T., Balmaseda, M., Balsamo, G., Buizza, R., Ferranti, L., Magnusson, L., Mogensen, K., Palmer, T., and Vitart, F.: The new ECMWF seasonal forecast system (System 4), ECMWF Tech. Memo., 656, 49 pp., available at: http://www.ecmwf.int/sites/default/files/elibrary/2011/11209-new-ecmwf-seasonal-forecast-system-system-4.pdf (last access: 29 August 2016), 2011.
Murphy, A. H.: What Is a Good Forecast? An Essay on the Nature of Goodness in Weather Forecasting, Weather Forecast., 8, 281–293, 1993.
Nilson, E., Lingemann, I., Klein, B., and Krahe, P.: Impact of hydrological change on navigation conditions, Deliverable 1.4 ECCONET – Effects of climate change on the inland waterway transport network, ECCONET project report, available at: http://www.tmleuven.be/project/ecconet/ECCONET_D1.4_final.pdf (last access: 11 December 2017), 2012.
Olsson, J., Uvo, C. B., Foster, K., and Yang, W.: Technical Note: Initial assessment of a multi-method approach to spring-flood forecasting in Sweden, Hydrol. Earth Syst. Sci., 20, 659–667, https://doi.org/10.5194/hess-20-659-2016, 2016.
Piani, C., Haerter, J., and Coppola, E.: Statistical bias correction for daily precipitation in regional climate models over Europe, Theor. Appl. Climatol., 2010, 187–192, https://doi.org/10.1007/s00704-009-0134-9, 2010.
Rauthe, M., Steiner, H., Riediger, U., Mazurkiewicz, A., and Gratzki, A.: A Central European precipitation climatology – Part I: Generation and validation of a high-resolution gridded daily data set (HYRAS), Meteorol. Z., 22, 235–256, 2013.
Richardson, D. S.: Skill and relative economic value of ECMWF ensemble prediction system, Q. J. Roy. Meteorol. Soc., 126, 649–667, 2000.
Richardson, D. S.: Economic Value and Skill, in: Forecast Verification: A Practitioner's Guide in Atmospheric Science, edited by: Joliffe, S. B., 2nd edn., John Wiley & Sons, Ltd., 167–184, 2012.
Richter, B. D., Baumgartner, J. V., Braun, D. P., and Powell, J.: A spatial assessment of hydrologic alteration within a river network, River Res. Appl., 14, 329–340, 1998.
Rimbu, N., Dima, M., Lohmann, G., and Stefan, S.: Impacts on the North Atlantic Oscillation and the El Niño–Southern Oscillation on Danube river flow variability, Geophys. Res. Lett., 31, L23203, https://doi.org/10.1029/2004GL020559, 2004.
Rimbu, N., Dima, M., Lohmann, G., and Musat, I.: Seasonal prediction of Danube flow variability based on stable teleconnection with sea surface temperature, Geophys. Res. Lett., 32, L21704, https://doi.org/10.1029/2005GL024241, 2005.
Robertson, D. E., Pokhrel, P., and Wang, Q. J.: Improving statistical forecasts of seasonal streamflows using hydrological model output, Hydrol. Earth Syst. Sci., 17, 579–593, https://doi.org/10.5194/hess-17-579-2013, 2013.
Roulin, E.: Skill and relative economic value of medium-range hydrological ensemble predictions, Hydrol. Earth Syst. Sci., 11, 725–737, https://doi.org/10.5194/hess-11-725-2007, 2007.
Shukla, S. and Lettenmaier, D. P.: Seasonal hydrologic prediction in the United States: understanding the role of initial hydrologic conditions and seasonal climate forecast skill, Hydrol. Earth Syst. Sci., 15, 3529–3538, https://doi.org/10.5194/hess-15-3529-2011, 2011.
Svensson, C.: Seasonal river flow forecasts for the United Kingdom using persistence and historical analogues, Hydrol. Sci. J., 61, 19–35, https://doi.org/10.1080/02626667.2014.992788, 2016.
Trigo, R. M., Pozo-Vázquez, D., Osborn, T. J., Castro-Diez, Y., Gamiz-Fortis, S., and Esteban-Parra, M. J.: North Atlantic Oscillation influence on precipitation, river flow and water resources in the Iberian Peninsula, Int. J. Climatol., 24, 925–944, 2004.
Tucci, C. E. M., Clarke, R. T., Collischonn, W., da Silva Dias, P. L., and de Oliveira, G. S.: Long-term flow forecasts based on climate and hydrologic modeling: Uruguay River basin, Water Resour. Res., 39, 1181, https://doi.org/10.1029/2003WR002074, 2003.
Van Lanen, H. A. J., Laaha, G., Kingston, D. G., Gauster, T., Ionita, M., Vidal, J.-P., Vlnas, R., Tallaksen, L. M., Stahl, K., Hannaford, J., Delus, C., Fendekova, M., Mediero, L., Prudhomme, C., Rets, E., Romanowicz, R. J., Gailliez, S., Wong, W. K., Adler, M.-J., Blauhut, V., Caillouet, L., Chelcea, S., Frolova, N., Gudmundsson, L., Hanel, M., Haslinger, K., Kireeva, M., Osuch, M., Sauquet, E., Stagge, J. H., and Van Loon, A. F.: Hydrology needed to manage droughts: the 2015 European case, Hydrol. Process., 16, 1373–1381, https://doi.org/10.1002/hyp.10838, 2016.
Wang, E., Zhang, Y., Luo, J., Chiew, F. H. S., and Wang, Q. J.: Monthly and Seasonal Streamflow Forecasts Using Rainfall-Runoff Modeling and Historical Weather Data, Water Resour. Res., 47, W05516, https://doi.org/10.1029/2010WR009922, 2011.
Wilby, R. L., Wedgbrow, C. S., and Fox, H. R.: Seasonal predictability of the summer hydrometeorology of the River Thames, UK, J. Hydrol., 295, 1–16, 2004.
Wilks, D. S.: A skill score based on economic value for probability forecasts, Meteorol. Appl., 8, 209–219, 2001.
Wood, A. W., Maurer, E. P., Kumar, A., and Lettenmaier, D. P.: Long-range experimental hydrologic forecasting for the eastern United States, J. Geophys. Res.-Atmos., 107, 4429, https://doi.org/10.1029/2001JD000659, 2002.
Wood, A. W. and Lettenmaier, D. P.: An ensemble approach for attribution of hydro-logic prediction uncertainty, Geophys. Res. Lett., 35, L14401, https://doi.org/10.1029/2008GL034648, 2008.
Wood, A. W., Hopson, T., Newman, A., Brekke, L., Arnold, J., and Clark, M.: Quantifying Streamflow Forecast Skill Elasticity to Initial Condition and Climate Prediction Skill, J. Hydrometeorol., 17, 651–668, https://doi.org/10.1175/JHM-D-14-0213.1, 2016.
Yossef, N. C., Winsemius, H., Weerts, A., van Beek, R., and Bierkens, M. F. P.: Skill of a global seasonal streamflow forecasting system, relative roles of initial conditions and meteorological forcing, Water Resour. Res., 49, 4687–4699, https://doi.org/10.1002/wrcr.20350, 2013.
Zappa, M., Bernhard, L., Spirig, C., Pfaundler, M., Stahl, K., Kruse, S., Seidl, I., and Stähli, M.: A prototype platform for water resources monitoring and early recognition of critical droughts in Switzerland, Proc. IAHS, 364, 492–498, https://doi.org/10.5194/piahs-364-492-2014, 2014.
Zhao, T., Bennett, J. C., Wang, Q. J., Schepen, A., Wood, A. W., Robertson, D. E., and Ramos, M. H.: How Suitable is Quantile Mapping For Postprocessing GCM Precipitation Forecasts? J. Climate, 30, 3185–3196, 2017.
Zink, M., Samaniego, L., Kumar, R., Thober, S., Mai, J., Scäfer, D., and Marx, A.: The German drought monitor, Environ. Res. Lett., 11, 074002, https://doi.org/10.1088/1748-9326/11/7/074002, 2016.
Short summary
Inland waterway transport is a commercial sector relying on hydrological forecasts on different timescales. This paper describes the set-up of a monthly to seasonal forecasting system for the German waterways. Multiple approaches are tested, compared and combined. Despite the predictive limitations on longer lead times, this study reveals the existence of a valuable predictability on monthly up to seasonal timescales. Forecast quality depends on forecast location, lead time and season.
Inland waterway transport is a commercial sector relying on hydrological forecasts on different...
Special issue