Articles | Volume 23, issue 1
https://doi.org/10.5194/hess-23-493-2019
© 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-23-493-2019
© Author(s) 2019. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
28 Jan 2019
Research article |
| 28 Jan 2019
| 28 Jan 2019
Subseasonal hydrometeorological ensemble predictions in small- and medium-sized mountainous catchments: benefits of the NWP approach
Swiss Federal Institute for Forest, Snow and Landscape Research
WSL, Mountain Hydrology and Mass Movements, Birmensdorf,
Switzerland
Federal Office of Meteorology and Climatology
MeteoSwiss, Climate Prediction, Zurich Airport, Switzerland
ETH
Zurich, Institute for Atmospheric and Climate Science, Zurich, Switzerland
Massimiliano Zappa
Swiss Federal Institute for Forest, Snow and Landscape Research
WSL, Mountain Hydrology and Mass Movements, Birmensdorf,
Switzerland
Christoph Spirig
Federal Office of Meteorology and Climatology
MeteoSwiss, Climate Prediction, Zurich Airport, Switzerland
Christoph Schär
ETH
Zurich, Institute for Atmospheric and Climate Science, Zurich, Switzerland
Konrad Bogner
Swiss Federal Institute for Forest, Snow and Landscape Research
WSL, Mountain Hydrology and Mass Movements, Birmensdorf,
Switzerland
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Responses of inland waters to climate change vary on global and regional scales. Shifts in river discharge regimes act as positive and negative feedbacks in influencing water temperature. The extent of this effect on warming is controlled by the change in river discharge and lake hydraulic residence time. A shift of deep penetrating river intrusions from summer towards winter can potentially counteract the otherwise negative climate effects on deep-water oxygen content.
Konrad Bogner, Katharina Liechti, and Massimiliano Zappa
Hydrol. Earth Syst. Sci., 21, 5493–5502, https://doi.org/10.5194/hess-21-5493-2017, https://doi.org/10.5194/hess-21-5493-2017, 2017
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The enhanced availability of many different weather prediction systems nowadays makes it very difficult for flood and water resource managers to choose the most reliable and accurate forecast. In order to circumvent this problem of choice, different approaches for combining this information have been applied at the Sihl River (CH) and the results have been verified. The outcome of this study highlights the importance of forecast combination in order to improve the quality of forecast systems.
Martin Wild, Atsumu Ohmura, Christoph Schär, Guido Müller, Doris Folini, Matthias Schwarz, Maria Zyta Hakuba, and Arturo Sanchez-Lorenzo
Earth Syst. Sci. Data, 9, 601–613, https://doi.org/10.5194/essd-9-601-2017, https://doi.org/10.5194/essd-9-601-2017, 2017
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The Global Energy Balance Archive (GEBA) is a database for the central storage of worldwide measured energy fluxes at the Earth's surface, maintained at ETH Zurich (Switzerland). This paper documents the status of the GEBA version 2017 database, presents the new web interface and user access, and reviews the scientific impact that GEBA data had in various applications. GEBA has continuously been expanded and updated and to date contains around 500 000 monthly mean entries from 2500 locations.
David Leutwyler, Oliver Fuhrer, Xavier Lapillonne, Daniel Lüthi, and Christoph Schär
Geosci. Model Dev., 9, 3393–3412, https://doi.org/10.5194/gmd-9-3393-2016, https://doi.org/10.5194/gmd-9-3393-2016, 2016
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The representation of moist convection (thunderstorms and rain showers) in climate models represents a major challenge, as this process is usually approximated due to the lack of appropriate computational resolution. Climate simulations using horizontal resolution of O(1 km) allow one to explicitly resolve deep convection and thus allow for an improved representation of the water cycle. We present a set of such simulations covering the European scale using a climate model enabled for GPUs.
Manuel Antonetti, Rahel Buss, Simon Scherrer, Michael Margreth, and Massimiliano Zappa
Hydrol. Earth Syst. Sci., 20, 2929–2945, https://doi.org/10.5194/hess-20-2929-2016, https://doi.org/10.5194/hess-20-2929-2016, 2016
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We evaluated three automatic mapping approaches of dominant runoff processes (DRPs) with different complexity using similarity measures and synthetic runoff simulations. The most complex DRP maps were the most similar to the reference maps. Runoff simulations derived from the simpler DRP maps were more uncertain due to inaccuracies in the input data and rather coarse simplifications in the mapping criteria. It would thus be worthwhile trying to obtain DRP maps that are as realistic as possible.
Lieke Melsen, Adriaan Teuling, Paul Torfs, Massimiliano Zappa, Naoki Mizukami, Martyn Clark, and Remko Uijlenhoet
Hydrol. Earth Syst. Sci., 20, 2207–2226, https://doi.org/10.5194/hess-20-2207-2016, https://doi.org/10.5194/hess-20-2207-2016, 2016
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In this study we investigated the sensitivity of a large-domain hydrological model for spatial and temporal resolution. We evaluated the results on a mesoscale catchment in Switzerland. Our results show that the model was hardly sensitive for the spatial resolution, which implies that spatial variability is likely underestimated. Our results provide a motivation to improve the representation of spatial variability in hydrological models in order to increase their credibility on a smaller scale.
Jon Olav Skøien, Konrad Bogner, Peter Salamon, Paul Smith, and Florian Pappenberger
Proc. IAHS, 373, 109–114, https://doi.org/10.5194/piahs-373-109-2016, https://doi.org/10.5194/piahs-373-109-2016, 2016
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. Zappa, N. Andres, P. Kienzler, D. Näf-Huber, C. Marti, and M. Oplatka
Proc. IAHS, 370, 235–242, https://doi.org/10.5194/piahs-370-235-2015, https://doi.org/10.5194/piahs-370-235-2015, 2015
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The most severe threat for the city of Zürich (Switzerland) are flash-floods from the small Sihl river. An assessment using a rainfall-runoff model evaluated more than 40000 extreme flood scenarios. These scenarios identified deficits for the safety of Zürich. The combination of different structural and flood management measures can lead to an optimal safety also in case of unfavorable initial conditions. Pending questions concern the costs, political decisions and the environmental matters.
M. Zappa, T. Vitvar, A. Rücker, G. Melikadze, L. Bernhard, V. David, M. Jans-Singh, N. Zhukova, and M. Sanda
Proc. IAHS, 369, 25–30, https://doi.org/10.5194/piahs-369-25-2015, https://doi.org/10.5194/piahs-369-25-2015, 2015
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A research effort involving Switzerland, Georgia and the Czech Republic has been launched to evaluate the relation between snowpack and summer low flows. Two rainfall-runoff models will simulate over 10 years of snow hydrology and runoff in nested streams. Processes involved will be also evaluated by mean by means of high frequency sampling of the environmental isotopes 18O and 2H. The paper presents first analysis of available datasets of 18O, 2H, discharge, snowpack and modelling experiments.
P. Ronco, M. Bullo, S. Torresan, A. Critto, R. Olschewski, M. Zappa, and A. Marcomini
Hydrol. Earth Syst. Sci., 19, 1561–1576, https://doi.org/10.5194/hess-19-1561-2015, https://doi.org/10.5194/hess-19-1561-2015, 2015
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The aim of the paper is the application of the KULTURisk regional risk assessment (KR-RRA) methodology, presented in the companion paper (Part 1), to the Sihl River basin, in northern Switzerland. Flood-related risks have been assessed for different receptors lying in the Sihl river valley including the city of Zurich, which represents a typical case of river flooding in an urban area, by means of a calibration process of the methodology to the site-specific context and features.
J. Grazioli, D. Tuia, S. Monhart, M. Schneebeli, T. Raupach, and A. Berne
Atmos. Meas. Tech., 7, 2869–2882, https://doi.org/10.5194/amt-7-2869-2014, https://doi.org/10.5194/amt-7-2869-2014, 2014
J. Hall, B. Arheimer, M. Borga, R. Brázdil, P. Claps, A. Kiss, T. R. Kjeldsen, J. Kriaučiūnienė, Z. W. Kundzewicz, M. Lang, M. C. Llasat, N. Macdonald, N. McIntyre, L. Mediero, B. Merz, R. Merz, P. Molnar, A. Montanari, C. Neuhold, J. Parajka, R. A. P. Perdigão, L. Plavcová, M. Rogger, J. L. Salinas, E. Sauquet, C. Schär, J. Szolgay, A. Viglione, and G. Blöschl
Hydrol. Earth Syst. Sci., 18, 2735–2772, https://doi.org/10.5194/hess-18-2735-2014, https://doi.org/10.5194/hess-18-2735-2014, 2014
S. Kotlarski, K. Keuler, O. B. Christensen, A. Colette, M. Déqué, A. Gobiet, K. Goergen, D. Jacob, D. Lüthi, E. van Meijgaard, G. Nikulin, C. Schär, C. Teichmann, R. Vautard, K. Warrach-Sagi, and V. Wulfmeyer
Geosci. Model Dev., 7, 1297–1333, https://doi.org/10.5194/gmd-7-1297-2014, https://doi.org/10.5194/gmd-7-1297-2014, 2014
S. Jörg-Hess, F. Fundel, T. Jonas, and M. Zappa
The Cryosphere, 8, 471–485, https://doi.org/10.5194/tc-8-471-2014, https://doi.org/10.5194/tc-8-471-2014, 2014
K. Liechti, L. Panziera, U. Germann, and M. Zappa
Hydrol. Earth Syst. Sci., 17, 3853–3869, https://doi.org/10.5194/hess-17-3853-2013, https://doi.org/10.5194/hess-17-3853-2013, 2013
F. Fundel, S. Jörg-Hess, and M. Zappa
Hydrol. Earth Syst. Sci., 17, 395–407, https://doi.org/10.5194/hess-17-395-2013, https://doi.org/10.5194/hess-17-395-2013, 2013
Related subject area
Subject: Hydrometeorology | Techniques and Approaches: Modelling approaches
The role of land–atmosphere coupling in subseasonal surface air temperature prediction across the contiguous United States
Barriers to urban hydrometeorological simulation: a review
Global catalog of soil moisture droughts over the past four decades
Probabilistic precipitation downscaling for ungauged mountain sites: a pilot study for the Hindu Kush Himalaya
Implementation of global soil databases in the Noah-MP model and the effects on simulated mean and extreme soil hydrothermal changes
Skilful probabilistic predictions of UK flood risk months ahead using a large-sample machine learning model trained on multimodel ensemble climate forecasts
Towards a robust hydrologic data assimilation system for hurricane-induced river flow forecasting
Enhanced evaluation of hourly and daily extreme precipitation in Norway from convection-permitting models at regional and local scales
Deep-learning-based sub-seasonal precipitation and streamflow ensemble forecasting over the source region of the Yangtze River
High-resolution land surface modelling over Africa: the role of uncertain soil properties in combination with forcing temporal resolution
Investigating the global and regional response of drought to idealized deforestation using multiple global climate models
Distribution, trends, and drivers of flash droughts in the United Kingdom
Are dependencies of extreme rainfall on humidity more reliable in convection-permitting climate models?
Leveraging a radar-based disdrometer network to develop a probabilistic precipitation phase model in eastern Canada
Assessment of seasonal soil moisture forecasts over the Central Mediterranean
Saudi Rainfall (SaRa): Hourly 0.1° Gridded Rainfall (1979–Present) for Saudi Arabia via Machine Learning Fusion of Satellite and Model Data
Do land models miss key soil hydrological processes controlling soil moisture memory?
Observation-driven model for calculating water-harvesting potential from advective fog in (semi-)arid coastal regions
Review of gridded climate products and their use in hydrological analyses reveals overlaps, gaps, and the need for a more objective approach to selecting model forcing datasets
Downscaling the probability of heavy rainfall over the Nordic countries
Modelling convective cell life cycles with a copula-based approach
Downscaling precipitation over High-mountain Asia using multi-fidelity Gaussian processes: improved estimates from ERA5
Mapping soil moisture across the UK: assimilating cosmic-ray neutron sensors, remotely sensed indices, rainfall radar and catchment water balance data in a Bayesian hierarchical model
Informativeness of teleconnections in local and regional frequency analysis of rainfall extremes
Assessing rainfall radar errors with an inverse stochastic modelling framework
Enhanced hydrological modelling with the WRF-Hydro lake/reservoir module at Convection-Permitting scale: a case study of the Tana River basin in East Africa
Multi-objective calibration and evaluation of the ORCHIDEE land surface model over France at high resolution
Spatiotemporal responses of runoff to climate change in the southern Tibetan Plateau
FROSTBYTE: a reproducible data-driven workflow for probabilistic seasonal streamflow forecasting in snow-fed river basins across North America
Storyline Analytical Framework for Understanding Future Severe Low-Water Episodes and Their Consequences
Assessing multivariate bias corrections of climate simulations on various impact models under climate change
On the combined use of rain gauges and GPM IMERG satellite rainfall products for hydrological modelling: impact assessment of the cellular-automata-based methodology in the Tanaro River basin in Italy
An increase in the spatial extent of European floods over the last 70 years
140-year daily ensemble streamflow reconstructions over 661 catchments in France
The agricultural expansion in South America's Dry Chaco: regional hydroclimate effects
Machine-learning-constrained projection of bivariate hydrological drought magnitudes and socioeconomic risks over China
Improving runoff simulation in the Western United States with Noah-MP and VIC models
Spatial variability in the seasonal precipitation lapse rates in complex topographical regions – application in France
Assessing downscaling methods to simulate hydrologically relevant weather scenarios from a global atmospheric reanalysis: case study of the upper Rhône River (1902–2009)
Global total precipitable water variations and trends over the period 1958–2021
Assessing decadal- to centennial-scale nonstationary variability in meteorological drought trends
Identification of compound drought and heatwave events on a daily scale and across four seasons
Potential for historically unprecedented Australian droughts from natural variability and climate change
Flood risk assessment for Indian sub-continental river basins
Key ingredients in regional climate modelling for improving the representation of typhoon tracks and intensities
Divergent future drought projections in UK river flows and groundwater levels
Predicting extreme sub-hourly precipitation intensification based on temperature shifts
Hydroclimatic processes as the primary drivers of the Early Khvalynian transgression of the Caspian Sea: new developments
Accounting for hydroclimatic properties in flood frequency analysis procedures
Understanding the influence of “hot” models in climate impact studies: a hydrological perspective
Yuna Lim, Andrea M. Molod, Randal D. Koster, and Joseph A. Santanello
Hydrol. Earth Syst. Sci., 29, 3435–3445, https://doi.org/10.5194/hess-29-3435-2025, https://doi.org/10.5194/hess-29-3435-2025, 2025
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To better utilize a given set of predictions, identifying “forecasts of opportunity” is valuable as this helps anticipate when prediction skill will be higher. This study shows that when strong land–atmosphere (L–A) coupling is detected 3–4 weeks into a forecast, the surface air temperature prediction skill at this lead time increases across the Midwest and northern Great Plains. Regions experiencing strong L–A coupling exhibit warm and dry anomalies, enhancing predictions of abnormally warm events.
Xuan Chen, Job Augustijn van der Werf, Arjan Droste, Miriam Coenders-Gerrits, and Remko Uijlenhoet
Hydrol. Earth Syst. Sci., 29, 3447–3480, https://doi.org/10.5194/hess-29-3447-2025, https://doi.org/10.5194/hess-29-3447-2025, 2025
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The review highlights the need to integrate urban land surface and hydrological models to better predict and manage compound climate events in cities. We find that inadequate representation of water surfaces, hydraulic systems and detailed building representations are key areas for improvement in future models. Coupled models show promise but face challenges at regional and neighbourhood scales. Interdisciplinary communication is crucial to enhance urban hydrometeorological simulations.
Jan Řehoř, Rudolf Brázdil, Oldřich Rakovec, Martin Hanel, Milan Fischer, Rohini Kumar, Jan Balek, Markéta Poděbradská, Vojtěch Moravec, Luis Samaniego, Yannis Markonis, and Miroslav Trnka
Hydrol. Earth Syst. Sci., 29, 3341–3358, https://doi.org/10.5194/hess-29-3341-2025, https://doi.org/10.5194/hess-29-3341-2025, 2025
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We present a robust method for identification and classification of global land drought events (GLDEs) based on soil moisture. Two models were used to calculate soil moisture and delimit soil drought over global land from 1980–2022, with clusters of 775 and 630 GLDEs. Using four spatiotemporal and three motion-related characteristics, we categorized GLDEs into seven severity and seven dynamic categories. The frequency of GLDEs has generally increased in recent decades.
Marc Girona-Mata, Andrew Orr, Martin Widmann, Daniel Bannister, Ghulam Hussain Dars, Scott Hosking, Jesse Norris, David Ocio, Tony Phillips, Jakob Steiner, and Richard E. Turner
Hydrol. Earth Syst. Sci., 29, 3073–3100, https://doi.org/10.5194/hess-29-3073-2025, https://doi.org/10.5194/hess-29-3073-2025, 2025
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We introduce a novel method for improving daily precipitation maps in mountain regions and pilot it across three basins in the Hindu Kush Himalaya (HKH). The approach leverages climate model and weather station data, along with statistical or machine learning techniques. Our results show that this approach outperforms traditional methods, especially in remote ungauged areas, suggesting that it could be used to improve precipitation maps across much of the HKH, as well as other mountain regions.
Kazeem Abiodun Ishola, Gerald Mills, Ankur Prabhat Sati, Benjamin Obe, Matthias Demuzere, Deepak Upreti, Gourav Misra, Paul Lewis, Daire Walsh, Tim McCarthy, and Rowan Fealy
Hydrol. Earth Syst. Sci., 29, 2551–2582, https://doi.org/10.5194/hess-29-2551-2025, https://doi.org/10.5194/hess-29-2551-2025, 2025
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Global soil information introduces uncertainty into models that simulate soil hydrothermal changes. Using the Noah with Multiparameterization (Noah-MP) model with two different global soil datasets, we find under-represented soil properties in wet loam, causing a dry bias in soil moisture. This bias is more pronounced and drought categories are more severe in the SoilGrids dataset. We conclude that models should incorporate detailed, region-specific soil information to minimize model uncertainties.
Simon Moulds, Louise Slater, Louise Arnal, and Andrew W. Wood
Hydrol. Earth Syst. Sci., 29, 2393–2406, https://doi.org/10.5194/hess-29-2393-2025, https://doi.org/10.5194/hess-29-2393-2025, 2025
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Seasonal streamflow forecasts are an important component of flood risk management. Here, we train and test a machine learning model to predict the monthly maximum daily streamflow up to 4 months ahead. We train the model on precipitation and temperature forecasts to produce probabilistic hindcasts for 579 stations across the UK for the period 2004–2016. We show skilful results up to 4 months ahead in many locations, although, in general, the skill declines with increasing lead time.
Peyman Abbaszadeh, Fatemeh Gholizadeh, Keyhan Gavahi, and Hamid Moradkhani
Hydrol. Earth Syst. Sci., 29, 2407–2427, https://doi.org/10.5194/hess-29-2407-2025, https://doi.org/10.5194/hess-29-2407-2025, 2025
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The Hybrid Ensemble and Variational Data Assimilation framework for Environmental Systems (HEAVEN) enhances flood predictions by refining hydrologic models through improved data integration and uncertainty management. Tested in three southeastern US watersheds during hurricanes, HEAVEN assimilates real-time United States Geological Survey (USGS) streamflow data, boosting forecast accuracy.
Kun Xie, Lu Li, Hua Chen, Stephanie Mayer, Andreas Dobler, Chong-Yu Xu, and Ozan Mert Göktürk
Hydrol. Earth Syst. Sci., 29, 2133–2152, https://doi.org/10.5194/hess-29-2133-2025, https://doi.org/10.5194/hess-29-2133-2025, 2025
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We compared hourly and daily extreme precipitation across Norway from HARMONIE Climate models at convection-permitting 3 km (HCLIM3) and 12 km (HCLIM12) resolutions. HCLIM3 more accurately captures the extremes in most regions and seasons (except in summer). Its advantages are more pronounced for hourly extremes than for daily extremes. The results highlight the value of convection-permitting models in improving extreme-precipitation predictions and in helping the local society brace for extreme weather.
Ningpeng Dong, Haoran Hao, Mingxiang Yang, Jianhui Wei, Shiqin Xu, and Harald Kunstmann
Hydrol. Earth Syst. Sci., 29, 2023–2042, https://doi.org/10.5194/hess-29-2023-2025, https://doi.org/10.5194/hess-29-2023-2025, 2025
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Hydrometeorological forecasting is crucial for managing water resources and mitigating extreme weather events, yet current long-term forecast products are often embedded with uncertainties. We develop a deep-learning-based modelling framework to improve 30 d rainfall and streamflow forecasts by combining advanced neural networks and physical models. With the flow forecast error reduced by up to 33 %, the framework has the potential to enhance water management and disaster prevention.
Bamidele Oloruntoba, Stefan Kollet, Carsten Montzka, Harry Vereecken, and Harrie-Jan Hendricks Franssen
Hydrol. Earth Syst. Sci., 29, 1659–1683, https://doi.org/10.5194/hess-29-1659-2025, https://doi.org/10.5194/hess-29-1659-2025, 2025
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We studied how soil and weather data affect land model simulations over Africa. By combining soil data processed in different ways with weather data of varying time intervals, we found that weather inputs had a greater impact on water processes than soil data type. However, the way soil data were processed became crucial when paired with high-frequency weather inputs, showing that detailed weather data can improve local and regional predictions of how water moves and interacts with the land.
Yan Li, Bo Huang, Chunping Tan, Xia Zhang, Francesco Cherubini, and Henning W. Rust
Hydrol. Earth Syst. Sci., 29, 1637–1658, https://doi.org/10.5194/hess-29-1637-2025, https://doi.org/10.5194/hess-29-1637-2025, 2025
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Deforestation has a significant impact on climate, yet its effects on drought remain less understood. This study investigates how deforestation affects drought across various climate zones and timescales. Findings indicate that deforestation leads to drier conditions in tropical regions and wetter conditions in arid areas, with minimal effects in temperate zones. Long-term drought is more affected than short-term drought, offering valuable insights into vegetation–climate interactions.
Iván Noguera, Jamie Hannaford, and Maliko Tanguy
Hydrol. Earth Syst. Sci., 29, 1295–1317, https://doi.org/10.5194/hess-29-1295-2025, https://doi.org/10.5194/hess-29-1295-2025, 2025
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The study provides a detailed characterisation of flash drought in the UK for 1969–2021. The spatio-temporal distribution and trends of flash droughts are highly variable, with important regional and seasonal contrasts. In the UK, flash drought development responds primarily to precipitation variability, while the atmospheric evaporative demand plays a secondary role. We also found that the North Atlantic Oscillation is the main circulation pattern controlling flash drought development.
Geert Lenderink, Nikolina Ban, Erwan Brisson, Ségolène Berthou, Virginia Edith Cortés-Hernández, Elizabeth Kendon, Hayley J. Fowler, and Hylke de Vries
Hydrol. Earth Syst. Sci., 29, 1201–1220, https://doi.org/10.5194/hess-29-1201-2025, https://doi.org/10.5194/hess-29-1201-2025, 2025
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Future extreme rainfall events are influenced by changes in both absolute and relative humidity. The impact of increasing absolute humidity is reasonably well understood, but the role of relative humidity decreases over land remains largely unknown. Using hourly observations from France and the Netherlands, we find that lower relative humidity generally leads to more intense rainfall extremes. This relation is only captured well in recently developed convection-permitting climate models.
Alexis Bédard-Therrien, François Anctil, Julie M. Thériault, Olivier Chalifour, Fanny Payette, Alexandre Vidal, and Daniel F. Nadeau
Hydrol. Earth Syst. Sci., 29, 1135–1158, https://doi.org/10.5194/hess-29-1135-2025, https://doi.org/10.5194/hess-29-1135-2025, 2025
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Precipitation data from an automated observational network in eastern Canada showed a temperature interval where rain and snow could coexist. Random forest models were developed to classify the precipitation phase using meteorological data to evaluate operational applications. The models demonstrated significantly improved phase classification and reduced error compared to benchmark operational models. However, accurate prediction of mixed-phase precipitation remains challenging.
Lorenzo Silvestri, Miriam Saraceni, Bruno Brunone, Silvia Meniconi, Giulia Passadore, and Paolina Bongioannini Cerlini
Hydrol. Earth Syst. Sci., 29, 925–946, https://doi.org/10.5194/hess-29-925-2025, https://doi.org/10.5194/hess-29-925-2025, 2025
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This work demonstrates that seasonal forecasts of soil moisture are a valuable resource for groundwater management in the areas of the Central Mediterranean where longer memory timescales are found. In particular, they show significant correlation coefficients and forecast skill for the deepest soil moisture at 289 cm depth. Wet and dry events can be predicted 6 months in advance, and, in general, dry events are better captured than wet events.
Xuetong Wang, Raied S. Alharbi, Oscar M. Baez-Villanueva, Amy Green, Matthew F. McCabe, Yoshihide Wada, Albert I. J. M. Van Dijk, Muhammad A. Abid, and Hylke Beck
EGUsphere, https://doi.org/10.5194/egusphere-2025-254, https://doi.org/10.5194/egusphere-2025-254, 2025
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Our paper introduces Saudi Rainfall (SaRa), a high-resolution, near real-time rainfall product for the Arabian Peninsula. Using machine learning, SaRa combines multiple satellite and (re)analysis datasets with static predictors, outperforming existing products in the region. With the fast development and continuing growth in water demand over this region, SaRa could help to address water challenges and support resource management.
Mohammad A. Farmani, Ali Behrangi, Aniket Gupta, Ahmad Tavakoly, Matthew Geheran, and Guo-Yue Niu
Hydrol. Earth Syst. Sci., 29, 547–566, https://doi.org/10.5194/hess-29-547-2025, https://doi.org/10.5194/hess-29-547-2025, 2025
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Soil moisture memory (SMM) shows how long soil stays moist after rain, impacting climate and ecosystems. Current models often overestimate SMM, causing inaccuracies in evaporation predictions. We enhanced a land model, Noah-MP, to include better water flow and ponding processes, and we tested it against satellite and field data. This improved model reduced overestimations and enhanced short-term predictions, helping create more accurate climate and weather forecasts.
Felipe Lobos-Roco, Jordi Vilà-Guerau de Arellano, and Camilo del Río
Hydrol. Earth Syst. Sci., 29, 109–125, https://doi.org/10.5194/hess-29-109-2025, https://doi.org/10.5194/hess-29-109-2025, 2025
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Water resources are fundamental for the social, economic, and natural development of (semi-)arid regions. Precipitation decreases due to climate change obligate us to find new water resources. Fog harvesting (FH) emerges as a complementary resource in regions where it is abundant but untapped. This research proposes a model to estimate FH potential in coastal (semi-)arid regions. This model could have broader applicability worldwide in regions where FH could be a viable water source.
Kyle R. Mankin, Sushant Mehan, Timothy R. Green, and David M. Barnard
Hydrol. Earth Syst. Sci., 29, 85–108, https://doi.org/10.5194/hess-29-85-2025, https://doi.org/10.5194/hess-29-85-2025, 2025
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We assess 63 gridded ground (G), satellite (S), and reanalysis (R) climate datasets. Higher-density station data and less-hilly terrain improved climate data. In mountainous and humid regions, dataset types performed similarly; however, R outperformed G when underlying data had low station density. G outperformed S or R datasets, although better streamflow modeling did not always follow. Hydrologic analyses need datasets that better represent climate variable dependencies and complex topography.
Rasmus E. Benestad, Kajsa M. Parding, and Andreas Dobler
Hydrol. Earth Syst. Sci., 29, 45–65, https://doi.org/10.5194/hess-29-45-2025, https://doi.org/10.5194/hess-29-45-2025, 2025
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We present a new method to calculate the chance of heavy downpour and the maximum rainfall expected over a 25-year period. It is designed to analyse global climate models' reproduction of past and future climates. For the Nordic countries, it projects a wetter climate in the future with increased intensity but not necessarily more wet days. The analysis also shows that rainfall intensity is sensitive to future greenhouse gas emissions, while the number of wet days appears to be less affected.
Chien-Yu Tseng, Li-Pen Wang, and Christian Onof
Hydrol. Earth Syst. Sci., 29, 1–25, https://doi.org/10.5194/hess-29-1-2025, https://doi.org/10.5194/hess-29-1-2025, 2025
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This study presents a new algorithm to model convective storms. We used advanced tracking methods to analyse 165 storm events in Birmingham (UK) and reconstruct storm cell life cycles. We found that cell properties like intensity and size are interrelated and vary over time. The new algorithm, based on vine copulas, accurately simulates these properties and their evolution. It also integrates an exponential shape function for realistic rainfall patterns, enhancing its hydrological applicability.
Kenza Tazi, Andrew Orr, Javier Hernandez-González, Scott Hosking, and Richard E. Turner
Hydrol. Earth Syst. Sci., 28, 4903–4925, https://doi.org/10.5194/hess-28-4903-2024, https://doi.org/10.5194/hess-28-4903-2024, 2024
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This work aims to improve the understanding of precipitation patterns in High-mountain Asia, a crucial water source for around 1.9 billion people. Through a novel machine learning method, we generate high-resolution precipitation predictions, including the likelihoods of floods and droughts. Compared to state-of-the-art methods, our method is simpler to implement and more suitable for small datasets. The method also shows accuracy comparable to or better than existing benchmark datasets.
Peter E. Levy and the COSMOS-UK team
Hydrol. Earth Syst. Sci., 28, 4819–4836, https://doi.org/10.5194/hess-28-4819-2024, https://doi.org/10.5194/hess-28-4819-2024, 2024
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Having accurate up-to-date maps of soil moisture is important for many purposes. However, current modelled and remotely sensed maps are rather coarse and not very accurate. Here, we demonstrate a simple but accurate approach that is closely linked to direct measurements of soil moisture at a network sites across the UK, to the water balance (precipitation minus drainage and evaporation) measured at a large number of catchments (1212) and to remotely sensed satellite estimates.
Andrea Magnini, Valentina Pavan, and Attilio Castellarin
EGUsphere, https://doi.org/10.5194/egusphere-2024-3261, https://doi.org/10.5194/egusphere-2024-3261, 2024
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This study describes a new methodology to identify regional structures in the dependence of extreme rainfall on global climate indexes. The study area is north-central Italy, but the methods are highly adaptable to other regions. We observe that the Western Mediterranean Oscillation Index has a strong influence, whose geographical pattern is in line with other studies. We show also that the use of the Index may improve the estimation of the extreme rainfall depth with a given probability.
Amy C. Green, Chris Kilsby, and András Bárdossy
Hydrol. Earth Syst. Sci., 28, 4539–4558, https://doi.org/10.5194/hess-28-4539-2024, https://doi.org/10.5194/hess-28-4539-2024, 2024
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Weather radar is a crucial tool in rainfall estimation, but radar rainfall estimates are subject to many error sources, with the true rainfall field unknown. A flexible model for simulating errors relating to the radar rainfall estimation process is implemented, inverting standard processing methods. This flexible and efficient model performs well in generating realistic weather radar images visually for a large range of event types.
Ling Zhang, Lu Li, Zhongshi Zhang, Joël Arnault, Stefan Sobolowski, Anthony Musili Mwanthi, Pratik Kad, Mohammed Abdullahi Hassan, Tanja Portele, and Harald Kunstmann
Hydrol. Earth Syst. Sci. Discuss., https://doi.org/10.5194/hess-2024-278, https://doi.org/10.5194/hess-2024-278, 2024
Revised manuscript accepted for HESS
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To address challenges related to unreliable hydrological simulations, we present an enhanced hydrological simulation with a refined climate model and a more comprehensive hydrological model. The model with the two parts outperforms that without, especially in migrating bias in peak flow and dry-season flow. Our findings highlight the enhanced hydrological simulation capability with the refined climate and lake module contributing 24 % and 76 % improvement, respectively.
Peng Huang, Agnès Ducharne, Lucia Rinchiuso, Jan Polcher, Laure Baratgin, Vladislav Bastrikov, and Eric Sauquet
Hydrol. Earth Syst. Sci., 28, 4455–4476, https://doi.org/10.5194/hess-28-4455-2024, https://doi.org/10.5194/hess-28-4455-2024, 2024
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We conducted a high-resolution hydrological simulation from 1959 to 2020 across France. We used a simple trial-and-error calibration to reduce the biases of the simulated water budget compared to observations. The selected simulation satisfactorily reproduces water fluxes, including their spatial contrasts and temporal trends. This work offers a reliable historical overview of water resources and a robust configuration for climate change impact analysis at the nationwide scale of France.
He Sun, Tandong Yao, Fengge Su, Wei Yang, and Deliang Chen
Hydrol. Earth Syst. Sci., 28, 4361–4381, https://doi.org/10.5194/hess-28-4361-2024, https://doi.org/10.5194/hess-28-4361-2024, 2024
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Our findings show that runoff in the Yarlung Zangbo (YZ) basin is primarily driven by rainfall, with the largest glacier runoff contribution in the downstream sub-basin. Annual runoff increased in the upper stream but decreased downstream due to varying precipitation patterns. It is expected to rise throughout the 21st century, mainly driven by increased rainfall.
Louise Arnal, Martyn P. Clark, Alain Pietroniro, Vincent Vionnet, David R. Casson, Paul H. Whitfield, Vincent Fortin, Andrew W. Wood, Wouter J. M. Knoben, Brandi W. Newton, and Colleen Walford
Hydrol. Earth Syst. Sci., 28, 4127–4155, https://doi.org/10.5194/hess-28-4127-2024, https://doi.org/10.5194/hess-28-4127-2024, 2024
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Forecasting river flow months in advance is crucial for water sectors and society. In North America, snowmelt is a key driver of flow. This study presents a statistical workflow using snow data to forecast flow months ahead in North American snow-fed rivers. Variations in the river flow predictability across the continent are evident, raising concerns about future predictability in a changing (snow) climate. The reproducible workflow hosted on GitHub supports collaborative and open science.
Gabriel Rondeau-Genesse, Louis-Philippe Caron, Kristelle Audet, Laurent Da Silva, Daniel Tarte, Rachel Parent, Élise Comeau, and Dominic Matte
EGUsphere, https://doi.org/10.5194/egusphere-2024-2595, https://doi.org/10.5194/egusphere-2024-2595, 2024
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The 2021 drought in Quebec showcased the province’s potential vulnerability. This study uses a storyline approach to explore impacts of future extreme droughts under +2 °C and +3 °C warming scenarios. By combining regional climate and hydrological simulations, it highlights the potential for severe water deficits. Collaboration with water management experts helped project the impacts of those future extreme droughts and their consequences for ecosystems and human activities.
Denis Allard, Mathieu Vrac, Bastien François, and Iñaki García de Cortázar-Atauri
Hydrol. Earth Syst. Sci. Discuss., https://doi.org/10.5194/hess-2024-102, https://doi.org/10.5194/hess-2024-102, 2024
Revised manuscript accepted for HESS
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Atmospheric variables from climate models often present biases relative to the past. In order to use these models to assess the impact of climate change on processes of interest, it is necessary to correct these biases. We tested several Multivariate Bias Correction Methods (MBCMs) for 5 physical variables that are input variables for 4 process models. We provide recommendations regarding the use of MBCMs when multivariate and time dependent processes are involved.
Annalina Lombardi, Barbara Tomassetti, Valentina Colaiuda, Ludovico Di Antonio, Paolo Tuccella, Mario Montopoli, Giovanni Ravazzani, Frank Silvio Marzano, Raffaele Lidori, and Giulia Panegrossi
Hydrol. Earth Syst. Sci., 28, 3777–3797, https://doi.org/10.5194/hess-28-3777-2024, https://doi.org/10.5194/hess-28-3777-2024, 2024
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The accurate estimation of precipitation and its spatial variability within a watershed is crucial for reliable discharge simulations. The study is the first detailed analysis of the potential usage of the cellular automata technique to merge different rainfall data inputs to hydrological models. This work shows an improvement in the performance of hydrological simulations when satellite and rain gauge data are merged.
Beijing Fang, Emanuele Bevacqua, Oldrich Rakovec, and Jakob Zscheischler
Hydrol. Earth Syst. Sci., 28, 3755–3775, https://doi.org/10.5194/hess-28-3755-2024, https://doi.org/10.5194/hess-28-3755-2024, 2024
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We use grid-based runoff from a hydrological model to identify large spatiotemporally connected flood events in Europe, assess extent trends over the last 70 years, and attribute the trends to different drivers. Our findings reveal a general increase in flood extent, with regional variations driven by diverse factors. The study not only enables a thorough examination of flood events across multiple basins but also highlights the potential challenges arising from changing flood extents.
Alexandre Devers, Jean-Philippe Vidal, Claire Lauvernet, Olivier Vannier, and Laurie Caillouet
Hydrol. Earth Syst. Sci., 28, 3457–3474, https://doi.org/10.5194/hess-28-3457-2024, https://doi.org/10.5194/hess-28-3457-2024, 2024
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Daily streamflow series for 661 near-natural French catchments are reconstructed over 1871–2012 using two ensemble datasets: HydRE and HydREM. They include uncertainties coming from climate forcings, streamflow measurement, and hydrological model error (for HydrREM). Comparisons with other hydrological reconstructions and independent/dependent observations show the added value of the two reconstructions in terms of quality, uncertainty estimation, and representation of extremes.
María Agostina Bracalenti, Omar V. Müller, Miguel A. Lovino, and Ernesto Hugo Berbery
Hydrol. Earth Syst. Sci., 28, 3281–3303, https://doi.org/10.5194/hess-28-3281-2024, https://doi.org/10.5194/hess-28-3281-2024, 2024
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The Gran Chaco is a large, dry forest in South America that has been heavily deforested, particularly in the dry Chaco subregion. This deforestation, mainly driven by the expansion of the agricultural frontier, has changed the land's characteristics, affecting the local and regional climate. The study reveals that deforestation has resulted in reduced precipitation, soil moisture, and runoff, and if intensive agriculture continues, it could make summers in this arid region even drier and hotter.
Rutong Liu, Jiabo Yin, Louise Slater, Shengyu Kang, Yuanhang Yang, Pan Liu, Jiali Guo, Xihui Gu, Xiang Zhang, and Aliaksandr Volchak
Hydrol. Earth Syst. Sci., 28, 3305–3326, https://doi.org/10.5194/hess-28-3305-2024, https://doi.org/10.5194/hess-28-3305-2024, 2024
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Climate change accelerates the water cycle and alters the spatiotemporal distribution of hydrological variables, thus complicating the projection of future streamflow and hydrological droughts. We develop a cascade modeling chain to project future bivariate hydrological drought characteristics over China, using five bias-corrected global climate model outputs under three shared socioeconomic pathways, five hydrological models, and a deep-learning model.
Lu Su, Dennis P. Lettenmaier, Ming Pan, and Benjamin Bass
Hydrol. Earth Syst. Sci., 28, 3079–3097, https://doi.org/10.5194/hess-28-3079-2024, https://doi.org/10.5194/hess-28-3079-2024, 2024
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We fine-tuned the variable infiltration capacity (VIC) and Noah-MP models across 263 river basins in the Western US. We developed transfer relationships to similar basins and extended the fine-tuned parameters to ungauged basins. Both models performed best in humid areas, and the skills improved post-calibration. VIC outperforms Noah-MP in all but interior dry basins following regionalization. VIC simulates annual mean streamflow and high flow well, while Noah-MP performs better for low flows.
Valentin Dura, Guillaume Evin, Anne-Catherine Favre, and David Penot
Hydrol. Earth Syst. Sci., 28, 2579–2601, https://doi.org/10.5194/hess-28-2579-2024, https://doi.org/10.5194/hess-28-2579-2024, 2024
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The increase in precipitation as a function of elevation is poorly understood in areas with complex topography. In this article, the reproduction of these orographic gradients is assessed with several precipitation products. The best product is a simulation from a convection-permitting regional climate model. The corresponding seasonal gradients vary significantly in space, with higher values for the first topographical barriers exposed to the dominant air mass circulations.
Caroline Legrand, Benoît Hingray, Bruno Wilhelm, and Martin Ménégoz
Hydrol. Earth Syst. Sci., 28, 2139–2166, https://doi.org/10.5194/hess-28-2139-2024, https://doi.org/10.5194/hess-28-2139-2024, 2024
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Climate change is expected to increase flood hazard worldwide. The evolution is typically estimated from multi-model chains, where regional hydrological scenarios are simulated from weather scenarios derived from coarse-resolution atmospheric outputs of climate models. We show that two such chains are able to reproduce, from an atmospheric reanalysis, the 1902–2009 discharge variations and floods of the upper Rhône alpine river, provided that the weather scenarios are bias-corrected.
Nenghan Wan, Xiaomao Lin, Roger A. Pielke Sr., Xubin Zeng, and Amanda M. Nelson
Hydrol. Earth Syst. Sci., 28, 2123–2137, https://doi.org/10.5194/hess-28-2123-2024, https://doi.org/10.5194/hess-28-2123-2024, 2024
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Global warming occurs at a rate of 0.21 K per decade, resulting in about 9.5 % K−1 of water vapor response to temperature from 1993 to 2021. Terrestrial areas experienced greater warming than the ocean, with a ratio of 2 : 1. The total precipitable water change in response to surface temperature changes showed a variation around 6 % K−1–8 % K−1 in the 15–55° N latitude band. Further studies are needed to identify the mechanisms leading to different water vapor responses.
Kyungmin Sung, Max C. A. Torbenson, and James H. Stagge
Hydrol. Earth Syst. Sci., 28, 2047–2063, https://doi.org/10.5194/hess-28-2047-2024, https://doi.org/10.5194/hess-28-2047-2024, 2024
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This study examines centuries of nonstationary trends in meteorological drought and pluvial climatology. A novel approach merges tree-ring proxy data (North American Seasonal Precipitation Atlas – NASPA) with instrumental precipitation datasets by temporally downscaling proxy data, correcting biases, and analyzing shared trends in normal and extreme precipitation anomalies. We identify regions experiencing recent unprecedented shifts towards drier or wetter conditions and shifts in seasonality.
Baoying Shan, Niko E. C. Verhoest, and Bernard De Baets
Hydrol. Earth Syst. Sci., 28, 2065–2080, https://doi.org/10.5194/hess-28-2065-2024, https://doi.org/10.5194/hess-28-2065-2024, 2024
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This study developed a convenient and new method to identify the occurrence of droughts, heatwaves, and co-occurring droughts and heatwaves (CDHW) across four seasons. Using this method, we could establish the start and/or end dates of drought (or heatwave) events. We found an increase in the frequency of heatwaves and CDHW events in Belgium caused by climate change. We also found that different months have different chances of CDHW events.
Georgina M. Falster, Nicky M. Wright, Nerilie J. Abram, Anna M. Ukkola, and Benjamin J. Henley
Hydrol. Earth Syst. Sci., 28, 1383–1401, https://doi.org/10.5194/hess-28-1383-2024, https://doi.org/10.5194/hess-28-1383-2024, 2024
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Multi-year droughts have severe environmental and economic impacts, but the instrumental record is too short to characterise multi-year drought variability. We assessed the nature of Australian multi-year droughts using simulations of the past millennium from 11 climate models. We show that multi-decadal
megadroughtsare a natural feature of the Australian hydroclimate. Human-caused climate change is also driving a tendency towards longer droughts in eastern and southwestern Australia.
Urmin Vegad, Yadu Pokhrel, and Vimal Mishra
Hydrol. Earth Syst. Sci., 28, 1107–1126, https://doi.org/10.5194/hess-28-1107-2024, https://doi.org/10.5194/hess-28-1107-2024, 2024
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A large population is affected by floods, which leave their footprints through human mortality, migration, and damage to agriculture and infrastructure, during almost every summer monsoon season in India. Despite the massive damage of floods, sub-basin level flood risk assessment is still in its infancy and needs to be improved. Using hydrological and hydrodynamic models, we reconstructed sub-basin level observed floods for the 1901–2020 period.
Qi Sun, Patrick Olschewski, Jianhui Wei, Zhan Tian, Laixiang Sun, Harald Kunstmann, and Patrick Laux
Hydrol. Earth Syst. Sci., 28, 761–780, https://doi.org/10.5194/hess-28-761-2024, https://doi.org/10.5194/hess-28-761-2024, 2024
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Tropical cyclones (TCs) often cause high economic loss due to heavy winds and rainfall, particularly in densely populated regions such as the Pearl River Delta (China). This study provides a reference to set up regional climate models for TC simulations. They contribute to a better TC process understanding and assess the potential changes and risks of TCs in the future. This lays the foundation for hydrodynamical modelling, from which the cities' disaster management and defence could benefit.
Simon Parry, Jonathan D. Mackay, Thomas Chitson, Jamie Hannaford, Eugene Magee, Maliko Tanguy, Victoria A. Bell, Katie Facer-Childs, Alison Kay, Rosanna Lane, Robert J. Moore, Stephen Turner, and John Wallbank
Hydrol. Earth Syst. Sci., 28, 417–440, https://doi.org/10.5194/hess-28-417-2024, https://doi.org/10.5194/hess-28-417-2024, 2024
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We studied drought in a dataset of possible future river flows and groundwater levels in the UK and found different outcomes for these two sources of water. Throughout the UK, river flows are likely to be lower in future, with droughts more prolonged and severe. However, whilst these changes are also found in some boreholes, in others, higher levels and less severe drought are indicated for the future. This has implications for the future balance between surface water and groundwater below.
Francesco Marra, Marika Koukoula, Antonio Canale, and Nadav Peleg
Hydrol. Earth Syst. Sci., 28, 375–389, https://doi.org/10.5194/hess-28-375-2024, https://doi.org/10.5194/hess-28-375-2024, 2024
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We present a new physical-based method for estimating extreme sub-hourly precipitation return levels (i.e., intensity–duration–frequency, IDF, curves), which are critical for the estimation of future floods. The proposed model, named TENAX, incorporates temperature as a covariate in a physically consistent manner. It has only a few parameters and can be easily set for any climate station given sub-hourly precipitation and temperature data are available.
Alexander Gelfan, Andrey Panin, Andrey Kalugin, Polina Morozova, Vladimir Semenov, Alexey Sidorchuk, Vadim Ukraintsev, and Konstantin Ushakov
Hydrol. Earth Syst. Sci., 28, 241–259, https://doi.org/10.5194/hess-28-241-2024, https://doi.org/10.5194/hess-28-241-2024, 2024
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Paleogeographical data show that 17–13 ka BP, the Caspian Sea level was 80 m above the current level. There are large disagreements on the genesis of this “Great” Khvalynian transgression of the sea, and we tried to shed light on this issue. Using climate and hydrological models as well as the paleo-reconstructions, we proved that the transgression could be initiated solely by hydroclimatic factors within the deglaciation period in the absence of the glacial meltwater effect.
Joeri B. Reinders and Samuel E. Munoz
Hydrol. Earth Syst. Sci., 28, 217–227, https://doi.org/10.5194/hess-28-217-2024, https://doi.org/10.5194/hess-28-217-2024, 2024
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Flooding presents a major hazard for people and infrastructure along waterways; however, it is challenging to study the likelihood of a flood magnitude occurring regionally due to a lack of long discharge records. We show that hydroclimatic variables like Köppen climate regions and precipitation intensity explain part of the variance in flood frequency distributions and thus reduce the uncertainty of flood probability estimates. This gives water managers a tool to locally improve flood analysis.
Mehrad Rahimpour Asenjan, Francois Brissette, Jean-Luc Martel, and Richard Arsenault
Hydrol. Earth Syst. Sci., 27, 4355–4367, https://doi.org/10.5194/hess-27-4355-2023, https://doi.org/10.5194/hess-27-4355-2023, 2023
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Climate models are central to climate change impact studies. Some models project a future deemed too hot by many. We looked at how including hot models may skew the result of impact studies. Applied to hydrology, this study shows that hot models do not systematically produce hydrological outliers.
Cited articles
Addor, N. and Fischer, E. M.: The influence of natural variability and
interpolation errors on bias characterization in RCM simulations, J.
Geophys. Res.-Atmos., 120, 10180–10195, https://doi.org/10.1002/2014JD022824,
2015.
Addor, N., Rohrer, M., Furrer, R., and Seibert, J.: Propagation of biases in
climate models from the synoptic to the regional scale: Implications for
bias adjustment, J. Geophys. Res.-Atmos., 121, 2075–2089,
https://doi.org/10.1002/2015JD024040, 2016.
Alfieri, L., Pappenberger, F., Wetterhall, F., Haiden, T., Richardson, D., and Salamon, P.: Evaluation of ensemble streamflow predictions in Europe, J.
Hydrol., 517, 913–922, https://doi.org/10.1016/j.jhydrol.2014.06.035, 2014.
Anderson, J. L.: A method for producing and evaluating probabilistic
forecasts from ensemble model integrations, J. Climate, 9, 1518–1530,
https://doi.org/10.1175/1520-0442(1996)009<1518:AMFPAE>2.0.CO;2,
1996.
Arnal, L., Cloke, H. L., Stephens, E., Wetterhall, F., Prudhomme, C.,
Neumann, J., Krzeminski, B., and Pappenberger, F.: Skilful seasonal forecasts
of streamflow over Europe?, Hydrol. Earth Syst. Sci., 22, 2057–2072,
https://doi.org/10.5194/hess-22-2057-2018, 2018.
Bauer, P., Thorpe, A., and Brunet, G.: The quiet revolution of numerical
weather prediction, Nature, 525, 47–55, https://doi.org/10.1038/nature14956, 2015.
Beerli, R., Wernli, H., and Grams, C. M.: Does the lower stratosphere provide
predictability for month-ahead wind electricity generation in Europe?, Q. J.
Roy. Meteor. Soc., 143, 3025–3036, https://doi.org/10.1002/qj.3158, 2017.
Begert, M. and Frei, C.: Long-term area-mean temperature series for
Switzerland – Combining homogenized station data and high resolution grid
data, Int. J. Climatol., 38, 2792–2807, https://doi.org/10.1002/joc.5460, 2018.
Bennett, J. C., Robertson, D. E., Lal, D., Wang, Q. J., Enever, D.,
Hapuarachchi, P., and Tuteja, N. K.: A System for Continuous Hydrological
Ensemble Forecasting (SCHEF) to lead times of 9 days, J. Hydrol., 519,
2832–2846, https://doi.org/10.1016/j.jhydrol.2014.08.010, 2014.
Bogner, K., Liechti, K., and Zappa, M.: Post-processing of stream flows in
Switzerland with an emphasis on low flows and floods, Water-SUI, 8, 115, https://doi.org/10.3390/w8040115, 2016.
Bogner, K., Liechti, K., Bernhard, L., Monhart, S., and Zappa, M.: Skill of
Hydrological Extended Range Forecasts for Water Resources Management in
Switzerland, Water Resour. Manag., 32, 969–984,
https://doi.org/10.1007/s11269-017-1849-5, 2018.
Bohn, T. J., Sonessa, M. Y., and Lettenmaier, D. P.: Seasonal Hydrologic
Forecasting: Do Multimodel Ensemble Averages Always Yield Improvements in
Forecast Skill?, J. Hydrometeorol., 11, 1358–1372,
https://doi.org/10.1175/2010JHM1267.1, 2010.
Brown, J. D., Demargne, J., Seo, D. J., and Liu, Y.: The Ensemble
Verification System (EVS): A software tool for verifying ensemble forecasts
of hydrometeorological and hydrologic variables at discrete locations,
Environ. Model. Softw., 25, 854–872, https://doi.org/10.1016/j.envsoft.2010.01.009,
2010.
Butt, M. J. and Bilal, M.: Application of snowmelt runoff model for water
resource management, Hydrol. Process., 25, 3735–3747, https://doi.org/10.1002/hyp.8099,
2011.
CH2018: CH2018 – Climate Scenarios for Switzerland, Technical Report,
National Center for Climate Services, Zurich, Chapter 5.7., 98–101,
available at:
https://www.nccs.admin.ch/nccs/de/home/klimawandel-und-auswirkungen/schweizer-klimaszenarien/technical-report.html, last access:
1 December 2018.
Cloke, H. L. and Pappenberger, F.: Ensemble flood forecasting: A review, J.
Hydrol., 375, 613–626, https://doi.org/10.1016/j.jhydrol.2009.06.005, 2009.
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.
Crochemore, L., Ramos, M.-H., Pappenberger, F., and Perrin, C.: Seasonal
streamflow forecasting by conditioning climatology with precipitation
indices, Hydrol. Earth Syst. Sci., 21, 1573–1591,
https://doi.org/10.5194/hess-21-1573-2017, 2017.
Davolio, S., Diomede, T., Marsigli, C., Miglietta, M. M., Montani, A., and
Morgillo, A.: Comparing different meteorological ensemble approaches:
hydrological predictions for a flood episode in Northern Italy, Adv. Sci.
Res., 8, 33–37, https://doi.org/10.5194/asr-8-33-2012, 2012.
Day, G. N.: Extended Streamflow Forecasting Using NWSRFS, J. Water Resour.
Plan. Manag., 111, 157–170, https://doi.org/10.1061/(ASCE)0733-9496(1985)111:2(157),
1985.
Demargne, J., Wu, L., Regonda, S. K., Brown, J. D., Lee, H., He, M., Seo, D.
J., Hartman, R., Herr, H. D., Fresch, M., Schaake, J., and Zhu, Y.: The
science of NOAA's operational hydrologic ensemble forecast service, B. Am.
Meteorol. Soc., 95, 79–98, https://doi.org/10.1175/BAMS-D-12-00081.1, 2014.
Díez, E., Primo, C., García-Moya, J. A., Gutiérrez, J. M., and
Orfila, B.: Statistical and dynamical downscaling of precipitation over Spain
from DEMETER seasonal forecasts, Tellus A, 57, 409–423,
https://doi.org/10.1111/j.1600-0870.2005.00130.x, 2005.
ECMWF, Part V: Ensemble Prediction System in IFS Documentation Cy40r1, ECMWF,
Reading, England, 1–25, 2014.
Ferro, C. A. T.: Fair scores for ensemble forecasts, Q. J. Roy. Meteor. Soc.,
140, 1917–1923, https://doi.org/10.1002/qj.2270, 2014.
Frei, C.: Interpolation of temperature in a mountainous region using
nonlinear profiles and non-Euclidean distances, Int. J. Climatol., 34,
1585–1605, https://doi.org/10.1002/joc.3786, 2014.
Frei, P.: Snowfall in the Alps: Evaluation and Projections based on the
EURO-CORDEX Regional Climate Models, Sci. Rep. Meteoswiss, 101, 122 pp., 2016.
Frei, P., Kotlarski, S., Liniger, M. A., and Schär, C.: Future snowfall in
the Alps: projections based on the EURO-CORDEX regional climate models, The
Cryosphere, 12, 1–24, https://doi.org/10.5194/tc-12-1-2018, 2018.
Freudiger, D., Frielingsdorf, B., Stahl, K., Steinbirch, A., Weiler, M.,
Griessinger, N., and Seibert, J.: The Potential of meteorological gridded
datasets for hydrological modeling in alpine basins, Hydrol. Wasserbewirts.,
60, 353–367, https://doi.org/10.5675/HyWa_2016,6_1, 2016.
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.
García-Morales, M. B. and Dubus, L.: Forecasting precipitation for
hydroelectric power management: how to exploit GCM's seasonal ensemble
forecasts, Int. J. Climatol., 27, 1691–1705, https://doi.org/10.1002/joc.1608, 2007.
Gurtz, J., Baltensweiler, A., and Lang, H.: Spatially distributed
hydrotope-based modelling of evapotranspiration and runoff in mountainous
basins, Hydrol. Process., 13, 2751–2768, 1999.
Hamill, T. M. and Colucci, S. J.: Verification of Eta – RSM Short-Range
Ensemble Forecasts, Mon. Weather Rev., 125, 1312–1328, 1997.
Hao, Z., Singh, V. P., and Xia, Y.: Seasonal Drought Prediction: Advances,
Challenges, and Future Prospects, Rev. Geophys., 56, 108–141,
https://doi.org/10.1002/2016RG000549, 2018.
Harrigan, S., Prudhomme, C., Parry, S., Smith, K., and Tanguy, M.:
Benchmarking ensemble streamflow prediction skill in the UK, Hydrol. Earth
Syst. Sci., 22, 2023–2039, https://doi.org/10.5194/hess-22-2023-2018,
2018.
Hersbach, H.: Decomposition of the Continuous Ranked Probability Score for
Ensemble Prediction Systems, Weather Forecast., 15, 559–570, 2000.
Hock, R.: Temperature index melt modelling in mountain areas, J. Hydrol.,
282, 104–115, https://doi.org/10.1016/S0022-1694(03)00257-9, 2003.
Hopson, T. M.: Assessing the Ensemble Spread – Error Relationship, Mon.
Weather Rev., 142, 1125–1142, https://doi.org/10.1175/MWR-D-12-00111.1, 2014.
Inman, R. H., Pedro, H. T. C., and Coimbra, C. F. M.: Solar forecasting
methods for renewable energy integration, Prog. Energy Combust. Sci., 39,
535–576, https://doi.org/10.1016/j.pecs.2013.06.002, 2013.
Isotta, F. A., Frei, C., Weilguni, V., Perčec Tadić, M.,
Lassègues, P., Rudolf, B., Pavan, V., Cacciamani, C., Antolini, G.,
Ratto, S. M., Munari, M., Micheletti, S., Bonati, V., Lussana, C., Ronchi,
C., Panettieri, E., Marigo, G., and Vertačnik, G.: The climate of daily
precipitation in the Alps: Development and analysis of a high-resolution grid
dataset from pan-Alpine rain-gauge data, Int. J. Climatol., 34, 1657–1675,
https://doi.org/10.1002/joc.3794, 2014.
Jaun, S., Ahrens, B., Walser, A., Ewen, T., and Schär, C.: A probabilistic
view on the August 2005 floods in the upper Rhine catchment, Nat. Hazards
Earth Syst. Sci., 8, 281–291, https://doi.org/10.5194/nhess-8-281-2008,
2008.
Jolliffe, I. T. and Stephenson, D. B.: Forecast Verification, edited by: Jolliffe, I. T. and Stephenson, D. B., John Wiley & Sons, Ltd, Chichester, UK.,
2012.
Jörg-Hess, S., Fundel, F., Jonas, T., and Zappa, M.: Homogenisation of a
gridded snow water equivalent climatology for Alpine terrain: methodology and
applications, The Cryosphere, 8, 471–485,
https://doi.org/10.5194/tc-8-471-2014, 2014.
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, 2015a.
Jörg-Hess, S., Kempf, S. B., Fundel, F., and Zappa, M.: The benefit of
climatological and calibrated reforecast data for simulating hydrological
droughts in Switzerland, Meteorol. Appl., 22, 444–458,
https://doi.org/10.1002/met.1474, 2015b.
Kang, T., Kim, Y., and Hong, I.: Comparison of pre- and post-processors for
ensemble streamflow prediction, Atmos. Sci. Lett., 159, 153–159,
https://doi.org/10.1002/asl.276, 2010.
Krause, P., Boyle, D. P., and Bäse, F.: Comparison of different efficiency
criteria for hydrological model assessment, Adv. Geosci., 5, 89–97,
https://doi.org/10.5194/adgeo-5-89-2005, 2005.
Kumar, S., Dirmeyer, P. A., and Kinter, J. L.: Usefulness of ensemble
forecasts from NCEP climate forecast system in sub-seasonal to intra-annual
forecasting, Geophys. Res. Lett., 41, 3586–3593, https://doi.org/10.1002/2014GL059586,
2014.
Lavers, D., Luo, L., and Wood, E. F.: A multiple model assessment of seasonal
climate forecast skill for applications, Geophys. Res. Lett., 36, L23711,
https://doi.org/10.1029/2009GL041365, 2009.
Liechti, K., Panziera, L., Germann, U., and Zappa, M.: The potential of
radar-based ensemble forecasts for flash-flood early warning in the southern
Swiss Alps, Hydrol. Earth Syst. Sci., 17, 3853–3869,
https://doi.org/10.5194/hess-17-3853-2013, 2013.
Liu, Y., Ren, G., Sun, X., and Li, X.: A new method to separate precipitation
phases, Hydrol. Earth Syst. Sci. Discuss.,
https://doi.org/10.5194/hess-2018-307, 2018.
Lucatero, D., Madsen, H., Refsgaard, J. C., Kidmose, J., and Jensen, K. H.:
On the skill of raw and post-processed ensemble seasonal meteorological
forecasts in Denmark, Hydrol. Earth Syst. Sci., 22, 6591–6609,
https://doi.org/10.5194/hess-22-6591-2018, 2018a.
Lucatero, D., Madsen, H., Refsgaard, J. C., Kidmose, J., and Jensen, K. H.:
Seasonal streamflow forecasts in the Ahlergaarde catchment, Denmark: the
effect of preprocessing and post-processing on skill and statistical
consistency, Hydrol. Earth Syst. Sci., 22, 3601–3617,
https://doi.org/10.5194/hess-22-3601-2018, 2018b.
Manzanas, R., Gutiérrez, J. M., Fernández, J., van Meijgaard, E.,
Calmanti, S., Magariño, M. E., Cofiño, A. S., and Herrera, S.:
Dynamical and statistical downscaling of seasonal temperature forecasts in
Europe: Added value for user applications, Clim. Serv., 9, 44–56,
https://doi.org/10.1016/j.cliser.2017.06.004, 2018.
Maraun, D.: Bias Correction, Quantile Mapping, and Downscaling: Revisiting
the Inflation Issue, J. Climate, 26, 2137–2143,
https://doi.org/10.1175/JCLI-D-12-00821.1, 2013.
Marsigli, C., Montani, A., and Paccagnella, T.: A spiatial verification
method applied to the evaluation of high-resolution ensemble forecasts,
Meteorol. Appl., 15, 125–143, https://doi.org/10.1002/met.65, 2008.
Meißner, D., Klein, B., and Ionita, M.: Development of a monthly to
seasonal forecast framework tailored to inland waterway transport in central
Europe, Hydrol. Earth Syst. Sci., 21, 6401–6423,
https://doi.org/10.5194/hess-21-6401-2017, 2017.
Melsen, L., Teuling, A., Torfs, P., Zappa, M., Mizukami, N., Clark, M., and
Uijlenhoet, R.: Representation of spatial and temporal variability in
large-domain hydrological models: case study for a mesoscale pre-Alpine
basin, Hydrol. Earth Syst. Sci., 20, 2207–2226,
https://doi.org/10.5194/hess-20-2207-2016, 2016.
Meteoswiss: Documentation of MeteoSwiss Grid-Data Products Daily Mean,
Minimum and Maximum Temperature: TabsD, TminD, TmaxD, Meteoschweiz Kundend.,
available at:
https://www.meteoswiss.admin.ch/home/services-and-publications/produkte.subpage.html/en/data/products/2014/raeumliche-daten-temperatur.html
(last access: 1 August 2018),
2016a.
MeteoSwiss: Documentation of MeteoSwiss grid-data products: Daily
precipitation (final analysis): RhiresD, Meteoschweiz Kundend., available at:
http://www.meteoswiss.admin.ch/home/services-and-publications/produkte.subpage.html/en/data/products/2014/raeumliche-daten-niederschlag.html
(last access: 1 August 2018), 2016b.
Monhart, S., Spirig, C., Bhend, J., Bogner, K., Schär, C., and Liniger,
M. A.: Skill of Subseasonal Forecasts in Europe: Effect of Bias Correction
and Downscaling Using Surface Observations, J. Geophys. Res.-Atmos., 123,
7999–8016, https://doi.org/10.1029/2017JD027923, 2018.
Montani, A., Marsigli, C., Nerozzi, F., Paccagnella, T., and Buizza, R.:
Nonlinear Processes in Geophysics Performance of the ARPA-SMR limited-area
ensemble prediction system?: two flood cases, Nonlinear Process. Geophys., 8,
387–399, https://doi.org/10.5194/npg-8-387-2001, 2001.
Montani, A., Marsigli, C., Nerozzi, F., Paccagnella, T., Tibaldi, S., and
Buizza, R.: The Soverato flood in Southern Italy: performance of global and
limited-area ensemble forecasts, Nonlinear Process. Geophys., 10, 261–274,
2003.
Montani, A., Cesari, D., Marsigli, C., and Paccagnella, T.: Seven years of
activity in the field of mesoscale ensemble forecasting by the COSMO-LEPS
system: Main achievements and open challenges, Tellus A, 63, 605–624,
https://doi.org/10.1111/j.1600-0870.2010.00499.x, 2011.
Müller, W. A., Appenzeller, C., Doblas-Reyes, F. J., and Liniger, M. A.:
A debiased ranked probability skill score to evaluate probabilistic ensemble
forecasts with small ensemble sizes, J. Climate, 18, 1513–1523,
https://doi.org/10.1175/JCLI3361.1, 2005.
Nash, E. and Sutcliffe, V.: River flow forecasting through conceptual models
Part 1 – A discussion of preinciples, J. Hydrol., 10, 282–290, 1970.
Ohmura, A.: Physical Basis for the Temperature-Based Melt-Index Method, J.
Appl. Meteorol., 40, 753–761,
https://doi.org/10.1175/1520-0450(2001)040<0753:PBFTTB>2.0.CO;2, 2001.
Orth, R. and Seneviratne, S. I.: Predictability of soil moisture and
streamflow on subseasonal timescales: A case study, J. Geophys. Res.-Atmos.,
118, 10963–10979, https://doi.org/10.1002/jgrd.50846, 2013a.
Orth, R. and Seneviratne, S. I.: Propagation of soil moisture memory to
streamflow and evapotranspiration in Europe, Hydrol. Earth Syst. Sci., 17,
3895–3911, https://doi.org/10.5194/hess-17-3895-2013, 2013b.
Orth, R., Staudinger, M., Seneviratne, S. I., Seibert, J., and Zappa, M.:
Does model performance improve with complexity? A case study with three
hydrological models, J. Hydrol., 523, 147–159,
https://doi.org/10.1016/j.jhydrol.2015.01.044, 2015.
Pappenberger, F., Ramos, M. H., Cloke, H. L., Wetterhall, F., Alfieri, L.,
Bogner, K., Mueller, A., and Salamon, P.: How do I know if my forecasts are
better? Using benchmarks in hydrological ensemble prediction, J. Hydrol.,
522, 697–713, https://doi.org/10.1016/j.jhydrol.2015.01.024, 2015.
Peleg, N., Fatichi, S., Paschalis, A., Molnar, P., and Burlando, P.: An
advanced stochastic weather generator for simulating 2-D high-resolution
climate variables, J. Adv. Model. Earth Sy., 9, 1595–1627,
https://doi.org/10.1002/2016MS000854, 2017.
Rahman, K., Etienne, C., Gago-Silva, A., Maringanti, C., Beniston, M., and
Lehmann, A.: Streamflow response to regional climate model output in the
mountainous watershed: a case study from the Swiss Alps, Environ. Earth Sci.,
72, 4357–4369, https://doi.org/10.1007/s12665-014-3336-0, 2014.
Rahman, M. M., Lu, M., and Kyi, K. H.: Seasonality of hydrological model
spin-up time: a case study using the Xinanjiang model, Hydrol. Earth Syst.
Sci. Discuss., https://doi.org/10.5194/hess-2016-316, in review, 2016.
Robertson, A. W., Kumar, A., Peña, M., and Vitart, F.: Improving and
Promoting Subseasonal to Seasonal Prediction, B. Am. Meteorol. Soc., 96,
ES49–ES53, https://doi.org/10.1175/BAMS-D-14-00139.1, 2015.
Schaake, J. C., Hamill, T. M., Buizza, R., and Clark, M.: HEPEX: The
hydrological ensemble prediction experiment, B. Am. Meteorol. Soc., 88,
1541–1547, https://doi.org/10.1175/BAMS-88-10-1541, 2007.
Schär, C., Vasilina, L., Pertziger, F., and Dirren, S.: Seasonal Runoff
Forecasting Using Precipitation from Meteorological Data Assimilation
Systems, J. Hydrometeorol., 5, 959–973,
https://doi.org/10.1175/1525-7541(2004)005<0959:SRFUPF>2.0.CO;2, 2004.
Schattan, P., Zappa, M., Lischke, H., Bernhard, L., Thurig, E., and
Diekkruger, B.: An approach for transient consideration of forest change in
hydrological impact studies, IAHS-AISH Proc. Reports, 359, 311–319, 2013.
Seck, A., Welty, C., and Maxwell, R. M.: Spin-up behavior and effects of
initial conditions for an integrated hydrologic model, Water Resour. Res.,
51, 2188–2210, https://doi.org/10.1002/2014WR016371, 2015.
Sharma, S., Siddique, R., Reed, S., Ahnert, P., Mendoza, P., and Mejia, A.:
Relative effects of statistical preprocessing and postprocessing on a
regional hydrological ensemble prediction system, Hydrol. Earth Syst. Sci.,
22, 1831–1849, https://doi.org/10.5194/hess-22-1831-2018, 2018.
Sinha, T. and Sankarasubramanian, A.: Role of climate forecasts and initial
conditions in developing streamflow and soil moisture forecasts in a
rainfall-runoff regime, Hydrol. Earth Syst. Sci., 17, 721–733,
https://doi.org/10.5194/hess-17-721-2013, 2013.
Speich, M. J. R., Bernhard, L., Teuling, A. J., and Zappa, M.: Application of
bivariate mapping for hydrological classification and analysis of temporal
change and scale effects in Switzerland, J. Hydrol., 523, 804–821,
https://doi.org/10.1016/j.jhydrol.2015.01.086, 2015.
Von Storch, H.: On the use of “inflation” in statistical downscaling, J.
Climate, 12, 3505–3506, https://doi.org/10.1175/1520-0442(1999)012<3505:OTUOII>2.0.CO;2, 1999.
Talagrand, O., Vautard, R., and Strauss, B.: Evaluation of probabilistic
prediction systems, in Proceedings of a Workshop held at ECMWF on
Predictability, 20–22 October 1997, Reading, UK, European Center
for Medium-Range Weather Forecasts, 1–25, 1997.
Thirel, G., Martin, E., Mahfouf, J.-F., Massart, S., Ricci, S., Regimbeau,
F., and Habets, F.: A past discharge assimilation system for ensemble
streamflow forecasts over France – Part 2: Impact on the ensemble streamflow
forecasts, Hydrol. Earth Syst. Sci., 14, 1639–1653,
https://doi.org/10.5194/hess-14-1639-2010, 2010.
Tobin, C., Nicotina, L., Parlange, M. B., Berne, A., and Rinaldo, A.:
Improved interpolation of meteorological forcings for hydrologic applications
in a Swiss Alpine region, J. Hydrol., 401, 77–89,
https://doi.org/10.1016/j.jhydrol.2011.02.010, 2011.
Van Dijk, A. I. J. M., Peña-Arancibia, J. L., Wood, E. F., Sheffield, J.,
and Beck, H. E.: Global analysis of seasonal streamflow predictability using
an ensemble prediction system and observations from 6192 small catchments
worldwide, Water Resour. Res., 49, 2729–2746, https://doi.org/10.1002/wrcr.20251,
2013.
Van Lanen, H. A. J., Laaha, G., Kingston, D. G., Gauster, T., Ionita, M.,
Vidal, J., 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., Blauhut, V., Caillouet, L., Chelcea,
S., Frovola, 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., 3104,
3097–3104, https://doi.org/10.1002/hyp.10838, 2016.
Verbunt, M., Walser, A., Grutz, J., Montani, A., and Schär, C.:
Probabilistic Flood Forecasting with a Limited-Area Ensemble Prediction
System: Selected Case Studies, J. Hydrometeorol., 8, 897–909,
https://doi.org/10.1175/JHM594.1, 2007.
Verkade, J. S., Brown, J. D., Reggiani, P., and Weerts, A. H.:
Post-processing ECMWF precipitation and temperature ensemble reforecasts for
operational hydrologic forecasting at various spatial, J. Hydrol., 501,
73–91, https://doi.org/10.1016/j.jhydrol.2013.07.039, 2013.
Vitart, F. and Robertson, A. W.: The sub-seasonal to seasonal prediction
project (S2S) and the prediction of extreme events, 85 npj Clim. Atmos. Sci.,
1, 1–3, https://doi.org/10.1038/s41612-018-0013-0, 2018.
Vitart, F., Ardilouze, C., Bonet, A., Brookshaw, A., Chen, M., Codorean, C.,
Déqué, M., Ferranti, L., Fucile, E., Fuentes, M., Hendon, H., Hodgson,
J., Kang, H. S., Kumar, A., Lin, H., Liu, G., Liu, X., Malguzzi, P., Mallas,
I., Manoussakis, M., Mastrangelo, D., MacLachlan, C., McLean, P., Minami, A.,
Mladek, R., Nakazawa, T., Najm, S., Nie, Y., Rixen, M., Robertson, A. W.,
Ruti, P., Sun, C., Takaya, Y., Tolstykh, M., Venuti, F., Waliser, D.,
Woolnough, S., Wu, T., Won, D. J., Xiao, H., Zaripov, R., and Zhang, L.: The
subseasonal to seasonal (S2S) prediction project database, B. Am. Meteorol.
Soc., 98, 163–173, https://doi.org/10.1175/BAMS-D-16-0017.1, 2017.
Viviroli, D., Zappa, M., Gurtz, J., and Weingartner, R.: An introduction to
the hydrological modelling system PREVAH and its pre- and
post-processing-tools, Environ. Model. Softw., 24, 1209–1222,
https://doi.org/10.1016/j.envsoft.2009.04.001, 2009a.
Viviroli, D., Zappa, M., Schwanbeck, J., Gurtz, J., and Weingartner, R.:
Continuous simulation for flood estimation in ungauged mesoscale catchments
of Switzerland – Part I: Modelling framework and calibration results, J.
Hydrol., 377, 191–207, https://doi.org/10.1016/j.jhydrol.2009.08.023, 2009b.
Voisin, N., Pappenberger, F., Lettenmaier, D. P., Buizza, R., and Schaake, J.
C.: Application of a Medium-Range Global Hydrologic Probabilistic Forecast
Scheme to the Ohio River Basin, Weather Forecast., 26, 425–446,
https://doi.org/10.1175/WAF-D-10-05032.1, 2011.
Volosciuk, C., Maraun, D., Vrac, M., and Widmann, M.: A combined statistical
bias correction and stochastic downscaling method for precipitation, Hydrol.
Earth Syst. Sci., 21, 1693–1719, https://doi.org/10.5194/hess-21-1693-2017,
2017.
Weingartner, R., Schädler, B., and Hänggi, P.: Auswirkungen der
Klimaänderung auf die schweizerische Wasserkraftnutzung, Geogr. Helv., 68,
239–248, https://doi.org/10.5194/gh-68-239-2013, 2013.
White, C. J., Carlsen, H., Robertson, A. W., Klein, R. J. T., Lazo, J. K.,
Kumar, A., Vitart, F., Coughlan de Perez, E., Ray, A. J., Murray, V.,
Bharwani, S., MacLeod, D., James, R., Fleming, L., Morse, A. P., Eggen, B.,
Graham, R., Kjellström, E., Becker, E., Pegion, K. V., Holbrook, N. J.,
McEvoy, D., Depledge, M., Perkins-Kirkpatrick, S., Brown, T. J., Street, R.,
Jones, L., Remenyi, T. A., Hodgson-Johnston, I., Buontempo, C., Lamb, R.,
Meinke, H., Arheimer, B., and Zebiak, S. E.: Potential applications of
subseasonal-to-seasonal (S2S) predictions, Meteorol. Appl., 24, 315–325,
https://doi.org/10.1002/met.1654, 2017.
Wilks, D. S.: Statistical Methods in the Atmospheric Sciences, 3rd ed.,
edited by: Wilks, D. S., International Geophysics Series, Vol. 100, Academic
Press Inc., London., 2011.
Wöhling, Th., Lennartz, F., and Zappa, M.: Technical Note: Updating
procedure for flood forecasting with conceptual HBV-type models, Hydrol.
Earth Syst. Sci., 10, 783–788, https://doi.org/10.5194/hess-10-783-2006,
2006.
Wood, A. W. and Lettenmaier, D. P.: An ensemble approach for attribution of
hydrologic prediction uncertainty, Geophys. Res. Lett., 35, 1–5,
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.
Zappa, M., Pos, F., Strassera, U., Warmerdam, P., and Gurtzl, J.: Seasonal
Water Balance of an Alpine Catchment as Evaluated by Different Methods for
Spatially Distributed Snowmelt Modelling, Nord. Hydrol., 34, 179–202, 2003.
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,
https://doi.org/10.1175/JCLI-D-16-0652.1, 2017.
Short summary
Subseasonal streamflow forecasts have received increasing attention during the past decade, but their performance in alpine catchments is still largely unknown. We analyse the effect of a statistical correction technique applied to the driving meteorological forecasts on the performance of the resulting streamflow forecasts. The study shows the benefits of such hydrometeorological ensemble prediction systems and highlights the importance of snow-related processes for subseasonal predictions.
Subseasonal streamflow forecasts have received increasing attention during the past decade, but...
