Articles | Volume 24, issue 11
https://doi.org/10.5194/hess-24-5519-2020
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/hess-24-5519-2020
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
23 Nov 2020
Research article |
| 23 Nov 2020
| 23 Nov 2020
On the potential of variational calibration for a fully distributed hydrological model: application on a Mediterranean catchment
Maxime Jay-Allemand
RECOVER, INRAE, Aix-Marseille Université, 3275 Route de Cézanne, 13182 Aix-en-Provence, France
INRAE, UMR G-EAU, 361 rue Jean-François Breton, 34196 Montpellier, France
RECOVER, INRAE, Aix-Marseille Université, 3275 Route de Cézanne, 13182 Aix-en-Provence, France
Igor Gejadze
INRAE, UMR G-EAU, 361 rue Jean-François Breton, 34196 Montpellier, France
Patrick Arnaud
RECOVER, INRAE, Aix-Marseille Université, 3275 Route de Cézanne, 13182 Aix-en-Provence, France
Pierre-Olivier Malaterre
INRAE, UMR G-EAU, 361 rue Jean-François Breton, 34196 Montpellier, France
Jean-Alain Fine
HYDRIS Hydrologie, Parc Scientifique Agropolis II, 2196 Boulevard de la Lironde, 34980 Montferrier-sur-Lez, France
Didier Organde
HYDRIS Hydrologie, Parc Scientifique Agropolis II, 2196 Boulevard de la Lironde, 34980 Montferrier-sur-Lez, France
Related authors
No articles found.
Eric Sauquet, Guillaume Evin, Sonia Siauve, Ryma Aissat, Patrick Arnaud, Maud Bérel, Jérémie Bonneau, Flora Branger, Yvan Caballero, François Colléoni, Agnès Ducharne, Joël Gailhard, Florence Habets, Frédéric Hendrickx, Louis Héraut, Benoît Hingray, Peng Huang, Tristan Jaouen, Alexis Jeantet, Sandra Lanini, Matthieu Le Lay, Claire Magand, Louise Mimeau, Céline Monteil, Simon Munier, Charles Perrin, Olivier Robelin, Fabienne Rousset, Jean-Michel Soubeyroux, Laurent Strohmenger, Guillaume Thirel, Flore Tocquer, Yves Tramblay, Jean-Pierre Vergnes, and Jean-Philippe Vidal
EGUsphere, https://doi.org/10.5194/egusphere-2025-1788, https://doi.org/10.5194/egusphere-2025-1788, 2025
This preprint is open for discussion and under review for Hydrology and Earth System Sciences (HESS).
Short summary
Short summary
The Explore2 project has provided an unprecedented set of hydrological projections in terms of the number of hydrological models used and the spatial and temporal resolution. The results have been made available through various media. Under the high-emission scenario, the hydrological models mostly agree on the decrease in seasonal flows in the south of France, confirming its hotspot status, and on the decrease in summer flows throughout France, with the exception of the northern part of France.
Juliette Godet, Eric Gaume, Pierre Javelle, Thomas Dias, Pierre Nicolle, and Olivier Payrastre
Abstr. Int. Cartogr. Assoc., 9, 16, https://doi.org/10.5194/ica-abs-9-16-2025, https://doi.org/10.5194/ica-abs-9-16-2025, 2025
François Colleoni, Ngo Nghi Truyen Huynh, Pierre-André Garambois, Maxime Jay-Allemand, Didier Organde, Benjamin Renard, Thomas De Fournas, Apolline El Baz, Julie Demargne, and Pierre Javelle
EGUsphere, https://doi.org/10.5194/egusphere-2025-690, https://doi.org/10.5194/egusphere-2025-690, 2025
Short summary
Short summary
We present smash, an open-source framework for high-resolution hydrological modeling and data assimilation. It combines process-based models with neural networks for regionalization, enabling accurate simulations from catchment to country scale. With an efficient, differentiable solver, smash supports large-scale calibration and parallel computing. Tested on open datasets, it shows strong performance in river flow prediction, making it a valuable tool for research and operational use.
Juliette Godet, Pierre Nicolle, Nabil Hocini, Eric Gaume, Philippe Davy, Frederic Pons, Pierre Javelle, Pierre-André Garambois, Dimitri Lague, and Olivier Payrastre
Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2024-472, https://doi.org/10.5194/essd-2024-472, 2024
Revised manuscript accepted for ESSD
Short summary
Short summary
This paper describes a dataset that includes input, output, and validation data for the simulation of flash flood hazards and three specific flash flood events in the French Mediterranean region. This dataset is particularly valuable as flood mapping methods often lack sufficient benchmark data. Additionally, we demonstrate how the hydraulic method we used, named Floodos, produces highly satisfactory results.
Maxime Jay-Allemand, Julie Demargne, Pierre-André Garambois, Pierre Javelle, Igor Gejadze, François Colleoni, Didier Organde, Patrick Arnaud, and Catherine Fouchier
Proc. IAHS, 385, 281–290, https://doi.org/10.5194/piahs-385-281-2024, https://doi.org/10.5194/piahs-385-281-2024, 2024
Short summary
Short summary
This work targets the improvement of a hydrologic model used for flash flood warnings. A gridded model is used to spatially describe the hydrological processes. We develop a method to estimate the best model setup based on scarce river flow observations. It uses a complex algorithm combined with geographical descriptors to generate gridded parameters that better capture catchment characteristics. Results are promising, improving the discharge estimations where no observations are available.
Juliette Godet, Eric Gaume, Pierre Javelle, Pierre Nicolle, and Olivier Payrastre
Hydrol. Earth Syst. Sci., 28, 1403–1413, https://doi.org/10.5194/hess-28-1403-2024, https://doi.org/10.5194/hess-28-1403-2024, 2024
Short summary
Short summary
This work was performed in order to precisely address a point that is often neglected by hydrologists: the allocation of points located on a river network to grid cells, which is often a mandatory step for hydrological modelling.
Reyhaneh Hashemi, Pierre Javelle, Olivier Delestre, and Saman Razavi
Hydrol. Earth Syst. Sci. Discuss., https://doi.org/10.5194/hess-2023-282, https://doi.org/10.5194/hess-2023-282, 2023
Manuscript not accepted for further review
Short summary
Short summary
Here, we have tackled the challenge of estimating water flow in areas without direct measurements, a crucial task in hydrology. We have applied deep learning techniques to a large sample of French catchments with various hydrological regimes. We have also compared our approach with traditional methods. We found that incorporating more data improves the accuracy of our deep learning predictions. Notably, our method outperforms traditional approaches in certain regimes, though not universally.
Juliette Godet, Olivier Payrastre, Pierre Javelle, and François Bouttier
Nat. Hazards Earth Syst. Sci., 23, 3355–3377, https://doi.org/10.5194/nhess-23-3355-2023, https://doi.org/10.5194/nhess-23-3355-2023, 2023
Short summary
Short summary
This article results from a master's research project which was part of a natural hazards programme developed by the French Ministry of Ecological Transition. The objective of this work was to investigate a possible way to improve the operational flash flood warning service by adding rainfall forecasts upstream of the forecasting chain. The results showed that the tested forecast product, which is new and experimental, has a real added value compared to other classical forecast products.
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.
Reyhaneh Hashemi, Pierre Brigode, Pierre-André Garambois, and Pierre Javelle
Hydrol. Earth Syst. Sci., 26, 5793–5816, https://doi.org/10.5194/hess-26-5793-2022, https://doi.org/10.5194/hess-26-5793-2022, 2022
Short summary
Short summary
Hydrologists have long dreamed of a tool that could adequately predict runoff in catchments. Data-driven long short-term memory (LSTM) models appear very promising to the hydrology community in this respect. Here, we have sought to benefit from traditional practices in hydrology to improve the effectiveness of LSTM models. We discovered that one LSTM parameter has a hydrologic interpretation and that there is a need to increase the data and to tune two parameters, thereby improving predictions.
François Colleoni, Pierre-André Garambois, Pierre Javelle, Maxime Jay-Allemand, and Patrick Arnaud
EGUsphere, https://doi.org/10.5194/egusphere-2022-506, https://doi.org/10.5194/egusphere-2022-506, 2022
Preprint archived
Short summary
Short summary
This contribution presents the first evaluation of Variational Data Assimilation successfully applied over a large sample to the spatially distributed calibration of a newly taylored grid-based parsimonious model structure and corresponding adjoint. High performances are obtained in spatio-temporal validation and at flood time scales, especially for mediterranenan and oceanic catchments. Regional sensitivity analysis revealed the importance of the non conservative and production components.
Abubakar Haruna, Pierre-Andre Garambois, Helene Roux, Pierre Javelle, and Maxime Jay-Allemand
Hydrol. Earth Syst. Sci. Discuss., https://doi.org/10.5194/hess-2021-414, https://doi.org/10.5194/hess-2021-414, 2021
Manuscript not accepted for further review
Short summary
Short summary
We compared three hydrological models in a flash flood modelling framework. We first identified the sensitive parameters of each model, then compared their performances in terms of outlet discharge and soil moisture simulation. We found out that resulting from the differences in their complexities/process representation, performance depends on the aspect/measure used. The study then highlights and proposed some future investigations/modifications to improve the models.
Nathalie Folton, Eric Martin, Patrick Arnaud, Pierre L'Hermite, and Mathieu Tolsa
Hydrol. Earth Syst. Sci., 23, 2699–2714, https://doi.org/10.5194/hess-23-2699-2019, https://doi.org/10.5194/hess-23-2699-2019, 2019
Short summary
Short summary
The long-term study of precipitation, flows, flood or drought mechanisms, in the Réal Collobrier research Watershed, located in South-East France, in the Mediterranean forest, improves knowledge of the water cycle and is unique tool for understanding of how catchments function. This study shows a small decrease in rainfall and a marked tendency towards a decrease in the water resources of the catchment in response to climate trends, with a consistent increase in drought severity and duration.
Clotilde Saint-Martin, Pierre Javelle, and Freddy Vinet
Earth Syst. Sci. Data, 10, 1019–1029, https://doi.org/10.5194/essd-10-1019-2018, https://doi.org/10.5194/essd-10-1019-2018, 2018
Short summary
Short summary
DamaGIS is a GIS database which aims to collect and assess the severity of flood-related damage. The reason for creating this database is the lack of precise damage data available to calibrate and validate flood risk assessment models. To this end, DamaGIS offers highly precise and easily accessible flood-related damage data. It uses multiple sources such as social networks. Since 2011, 729 damages caused by 23 flood events in the south of France have been reported within the database.
D. Defrance, P. Javelle, D. Organde, S. Ecrepont, V. Andréassian, and P. Arnaud
Hydrol. Earth Syst. Sci. Discuss., https://doi.org/10.5194/hessd-11-4365-2014, https://doi.org/10.5194/hessd-11-4365-2014, 2014
Revised manuscript has not been submitted
Related subject area
Subject: Hydrometeorology | Techniques and Approaches: Modelling approaches
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
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
Barriers of urban hydro-meteorological simulation: a review
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
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
Probabilistic precipitation downscaling for ungauged mountain sites: a pilot study for the Hindu Kush Karakoram Himalaya
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
The role of land-atmosphere coupling in subseasonal surface air temperature prediction
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
Global catalog of soil moisture droughts over the past four decades
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
A semi-parametric hourly space–time weather generator
A principal-component-based strategy for regionalisation of precipitation intensity–duration–frequency (IDF) statistics
Accounting for precipitation asymmetry in a multiplicative random cascade disaggregation model
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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.
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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.
Xuan Chen, Job Augustijn van der Werf, Arjan Droste, Miriam Coenders-Gerrits, and Remko Uijlenhoet
EGUsphere, https://doi.org/10.5194/egusphere-2024-3988, https://doi.org/10.5194/egusphere-2024-3988, 2025
Short summary
Short summary
Our research highlights the need to integrate urban land surface and hydrological models to better predict and manage compound climate disasters 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.
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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.
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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.
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
EGUsphere, https://doi.org/10.5194/egusphere-2024-2805, https://doi.org/10.5194/egusphere-2024-2805, 2024
Short summary
Short summary
We introduce a novel method for improving daily precipitation maps in mountain regions and pilot it across three basins in the Hindu Kush Karakoram Himalaya (HKH). The approach leverages climate model and weather station data, along with statistical / machine learning techniques. Our results show this approach outperforms traditional methods, especially in remote, ungauged areas, suggesting it could be used to improve precipitation maps across much of the HKH, as well as other mountain regions.
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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.
Yuna Lim, Andrea M. Molod, Randal D. Koster, and Joseph A. Santanello
EGUsphere, https://doi.org/10.5194/egusphere-2024-2312, https://doi.org/10.5194/egusphere-2024-2312, 2024
Short summary
Short summary
To better utilize a given set of predictions, identifying “forecasts of opportunity” has great value. It can help anticipate when prediction skill will be higher. This study reveals that when strong L-A coupling is detected 3–4 weeks into a forecast, the prediction skill for surface air temperature at this lead increases across the Midwest and northern Great Plains. Regions experiencing strong L-A coupling exhibit warm and dry anomalies, leading to improved predictions of abnormally warm events.
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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.
Jan Řehoř, Rudolf Brázdil, Oldřich Rakovec, Martin Hanel, Milan Fischer, Rohini Kumar, Jan Balek, Markéta Poděbradská, Vojtěch Moravec, Luis Samaniego, and Miroslav Trnka
EGUsphere, https://doi.org/10.5194/egusphere-2024-1434, https://doi.org/10.5194/egusphere-2024-1434, 2024
Short summary
Short summary
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, which was clustered into 775/630 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.
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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.
Ross Pidoto and Uwe Haberlandt
Hydrol. Earth Syst. Sci., 27, 3957–3975, https://doi.org/10.5194/hess-27-3957-2023, https://doi.org/10.5194/hess-27-3957-2023, 2023
Short summary
Short summary
Long continuous time series of meteorological variables (i.e. rainfall, temperature) are required for the modelling of floods. Observed time series are generally too short or not available. Weather generators are models that reproduce observed weather time series. This study extends an existing station-based rainfall model into space by enforcing observed spatial rainfall characteristics. To model other variables (i.e. temperature) the model is then coupled to a simple resampling approach.
Kajsa Maria Parding, Rasmus Emil Benestad, Anita Verpe Dyrrdal, and Julia Lutz
Hydrol. Earth Syst. Sci., 27, 3719–3732, https://doi.org/10.5194/hess-27-3719-2023, https://doi.org/10.5194/hess-27-3719-2023, 2023
Short summary
Short summary
Intensity–duration–frequency (IDF) curves describe the likelihood of extreme rainfall and are used in hydrology and engineering, for example, for flood forecasting and water management. We develop a model to estimate IDF curves from daily meteorological observations, which are more widely available than the observations on finer timescales (minutes to hours) that are needed for IDF calculations. The method is applied to all data at once, making it efficient and robust to individual errors.
Kaltrina Maloku, Benoit Hingray, and Guillaume Evin
Hydrol. Earth Syst. Sci., 27, 3643–3661, https://doi.org/10.5194/hess-27-3643-2023, https://doi.org/10.5194/hess-27-3643-2023, 2023
Short summary
Short summary
High-resolution precipitation data, needed for many applications in hydrology, are typically rare. Such data can be simulated from daily precipitation with stochastic disaggregation. In this work, multiplicative random cascades are used to disaggregate time series of 40 min precipitation from daily precipitation for 81 Swiss stations. We show that very relevant statistics of precipitation are obtained when precipitation asymmetry is accounted for in a continuous way in the cascade generator.
Cited articles
Abbaris, A., Dakhlaoui, H., Thiria, S., and Bargaoui, Z.:
Variational data assimilation with the YAO platform for hydrological forecasting, P. Int. Ass. Hydrol. Sci.,
364, 3–8, https://doi.org/10.5194/piahs-364-3-2014, 2014. a
Anderson, R. M., Koren, V. I., and Reed, S. M.:
Using SSURGO data to improve Sacramento Model a priori parameter estimates,
J. Hydrol.,
320, 103–116, https://doi.org/10.1016/j.jhydrol.2005.07.020, 2006. a
Arnaud, P., Lavabre, J., Fouchier, C., Diss, S., and Javelle, P.:
Sensitivity of hydrological models to uncertainty in rainfall input,
Hydrolog. Sci. J.,
56, 397–410, 2011. a
Artigue, G., Johannet, A., Borrell, V., and Pistre, S.: Flash flood forecasting in poorly gauged basins using neural networks: case study of the Gardon de Mialet basin (southern France), Nat. Hazards Earth Syst. Sci., 12, 3307–3324, https://doi.org/10.5194/nhess-12-3307-2012, 2012. a
Bell, V. A., Kay, A. L., Jones, R. G., and Moore, R. J.: Development of a high resolution grid-based river flow model for use with regional climate model output, Hydrol. Earth Syst. Sci., 11, 532–549, https://doi.org/10.5194/hess-11-532-2007, 2007. a
Beven, K.:
Changing ideas in hydrology – The case of physically-based models,
J. Hydrol.,
105, 157–172, https://doi.org/10.1016/0022-1694(89)90101-7, 1989. a
Beven, K.:
Prophecy, reality and uncertainty in distributed hydrological modelling,
Adv. Water Res.,
16, 41–51, 1993. a
Beven, K.: How far can we go in distributed hydrological modelling?, Hydrol. Earth Syst. Sci., 5, 1–12, https://doi.org/10.5194/hess-5-1-2001, 2001. a
Borga, M., Anagnostou, E. N., Blöschl, G., and Creutin, J. D.:
Flash flood forecasting, warning and risk management: the HYDRATE project,
Environ. Sci. Policy,
14, 834–844, https://doi.org/10.1016/j.envsci.2011.05.017, 2011. a
Bouvier, C. and DelClaux, F.:
ATHYS: a hydrological environment for spatial modelling and coupling with GIS,
IAHS Publications-Series of Proceedings and Reports-Intern Assoc Hydrological Sciences,
235, 19–28, 1996. a
Braud, I., Roux, H., Anquetin, S., Maubourguet, M.-M., Manus, C., Viallet, P., and Dartus, D.:
The use of distributed hydrological models for the Gard 2002 flash flood event: Analysis of associated hydrological processes,
J. Hydrol.,
394, 162–181, https://doi.org/10.1016/j.jhydrol.2010.03.033, 2010. a
Braud, I., Ayral, P.-A., Bouvier, C., Branger, F., Delrieu, G., Le Coz, J., Nord, G., Vandervaere, J.-P., Anquetin, S., Adamovic, M., Andrieu, J., Batiot, C., Boudevillain, B., Brunet, P., Carreau, J., Confoland, A., Didon-Lescot, J.-F., Domergue, J.-M., Douvinet, J., Dramais, G., Freydier, R., Gérard, S., Huza, J., Leblois, E., Le Bourgeois, O., Le Boursicaud, R., Marchand, P., Martin, P., Nottale, L., Patris, N., Renard, B., Seidel, J.-L., Taupin, J.-D., Vannier, O., Vincendon, B., and Wijbrans, A.: Multi-scale hydrometeorological observation and modelling for flash flood understanding, Hydrol. Earth Syst. Sci., 18, 3733–3761, https://doi.org/10.5194/hess-18-3733-2014, 2014. a
Braud, I., Borga, M., Gourley, J., Hurlimann Ziegler, M., Zappa, M., and Gallart, F.:
Flash floods, hydro-geomorphic response and risk management,
J. Hydrol.,
541, 1–5, 2016. a
Castaings, W., Dartus, D., Le Dimet, F.-X., and Saulnier, G.-M.: Sensitivity analysis and parameter estimation for distributed hydrological modeling: potential of variational methods, Hydrol. Earth Syst. Sci., 13, 503–517, https://doi.org/10.5194/hess-13-503-2009, 2009. a, b, c, d
Collier, C.:
Flash flood forecasting: What are the limits of predictability?,
Q. J. Roy. Meteor. Soc.,
133, 3–23, https://doi.org/10.1002/qj.29, 2007. a
De Lavenne, A., Andréassian, V., Thirel, G., Ramos, M.-H., and Perrin, C.:
A Regularization Approach to Improve the Sequential Calibration of a Semidistributed Hydrological Model,
Water Resour. Res.,
55, 8821–8839, https://doi.org/10.1029/2018WR024266, 2019. a, b
Douinot, A., Roux, H., Garambois, P.-A., Larnier, K., Labat, D., and Dartus, D.:
Accounting for rainfall systematic spatial variability in flash flood forecasting,
J. Hydrol.,
541, 359–370, 2016. a
Douinot, A., Roux, H., Garambois, P.-A., and Dartus, D.: Using a multi-hypothesis framework to improve the understanding of flow dynamics during flash floods, Hydrol. Earth Syst. Sci., 22, 5317–5340, https://doi.org/10.5194/hess-22-5317-2018, 2018. a
Drobinski, P., Ducrocq, V., Alpert, P., Anagnostou, E., Béranger, K., Borga, M., Braud, I., Chanzy, A., Davolio, S., Delrieu, G., Estournel, C., Boubrahmi, N. F., Font, J., Grubišić, V., Gualdi, S., Homar, V., Ivančan-Picek, B., Kottmeier, C., Kotroni, V., Lagouvardos, K., Lionello, P., Llasat, M. C., Ludwig, W., Lutoff, C., Mariotti, A., Richard, E., Romero, R., Rotunno, R., Roussot, O., Ruin, I., Somot, S., Taupier-Letage, I., Tintore, J., Uijlenhoet, R., and Wernli, H.:
HyMeX: A 10-Year Multidisciplinary Program on the Mediterranean Water Cycle,
B. Am. Meteorol. Soc.,
95, 1063–1082, https://doi.org/10.1175/BAMS-D-12-00242.1, 2014. a, b
Ducrocq, V., Davolio, S., Ferretti, R., Flamant, C., Santaner, V. H., Kalthoff, N., Richard, E., and Wernli, H.:
Introduction to the HyMeX Special Issue on “Advances in understanding and forecasting of heavy precipitation in the Mediterranean through the HyMeX SOP1 field campaign”,
Q. J. Roy. Meteor. Soc.,
142, 1–6, https://doi.org/10.1002/qj.2856, 2016. a
Errico, R. M.:
What is an adjoint model?,
B. Am. Meteorol. Soc.,
78, 2577–2591, 1997. a
Ficchì, A., Perrin, C., and Andréassian, V.:
Impact of temporal resolution of inputs on hydrological model performance: An analysis based on 2400 flood events,
J. Hydrol.,
538, 454–470, https://doi.org/10.1016/j.jhydrol.2016.04.016, 2016. a
Ficchì, A., Raso, L., Dorchies, D., Pianosi, F., Malaterre, P.-O., Overloop, P.-J. V., and Jay-Allemand, M.:
Optimal Operation of the Multireservoir System in the Seine River Basin Using Deterministic and Ensemble Forecasts,
J. Water Res. Pl.,
142, 05015005, https://doi.org/10.1061/(ASCE)WR.1943-5452.0000571, 2016. a
Garambois, P. A., Roux, H., Larnier, K., Castaings, W., and Dartus, D.: Characterization of process-oriented hydrologic model behavior with temporal sensitivity analysis for flash floods in Mediterranean catchments, Hydrol. Earth Syst. Sci., 17, 2305–2322, https://doi.org/10.5194/hess-17-2305-2013, 2013. a
Garambois, P.-A., Roux, H., Larnier, K., Labat, D., and Dartus, D.:
Parameter regionalization for a process-oriented distributed model dedicated to flash floods,
J. Hydrol.,
525, 383–399, 2015. a
Gourley, J., Flamig, Z., Vergara, H., Kirstetter, P.-E., Clark, R., Argyle, E., Arthur, A., Martinaitis, S., Terti, G., Erlingis, J., Hong, Y., and Howard, K.:
The flash project Improving the Tools for Flash Flood Monitoring and Prediction across the United States,
B. Am. Meteorol. Soc.,
98, 361–372, https://doi.org/10.1175/BAMS-D-15-00247.1, 2017. a
Gupta, H. V., Kling, H., Yilmaz, K. K., and Martinez, G. F.:
Decomposition of the mean squared error and NSE performance criteria: Implications for improving hydrological modelling,
J. Hydrol.,
377, 80–91, https://doi.org/10.1016/j.jhydrol.2009.08.003, 2009. a
Hapuarachchi, H., Wang, Q., and Pagano, T.:
A review of advances in flash flood forecasting,
Hydrol. Process.,
25, 2771–2784, https://doi.org/10.1002/hyp.8040, 2011. a
Hascoet, L. and Pascual, V.:
The Tapenade Automatic Differentiation tool: principles, model, and specification, ACM T. Math. Software,
39, 20, https://doi.org/10.1145/2450153.2450158, 2013. a
Javelle, P., Fouchier, C., Arnaud, P., and Lavabre, J.:
Flash flood warning at ungauged locations using radar rainfall and antecedent soil moisture estimations,
J. Hydrol.,
394, 267–274, 2010. a
Javelle, P., Demargne, J., Defrance, D., Pansu, J., and Arnaud, P.:
Evaluating flash-flood warnings at ungauged locations using post-event surveys: a case study with the AIGA warning system,
Hydrolog. Sci. J.,
59, 1390–1402, 2014. a
Javelle, P., Organde, D., Demargne, J., Saint-Martin, C., de Saint-Aubin, C., Garandeau, L., and Janet, B.:
Setting up a French national flash flood warning system for ungauged catchments based on the AIGA method,
in: 3rd European Conference on Flood Risk Management (FLOODrisk 2016), 17–21 October 2016, Lyon, France, Proceedings, https://doi.org/10.1051/e3sconf/20160718010, 2016. a
Javelle, P., Saint-Martin, C., Garandeau, L., and Janet, B.:
Flash flood warnings: Recent achievements in France with the national Vigicrues Flash system,
United Nations Office for Disaster Risk Reduction, Contributing Paper to the Global Assessment Report on Disaster Risk Reduction (GAR 2019),
available at:
https://www.undrr.org/publication/flash-flood-warnings-recent-achievements-france-national-vigicrues-flash-system (last access: 7 October 2020), 2019. a
Jay-Allemand, M., Gejadze, I., Javelle, P., Organde, D., Fine, J.-A., Patrick, A., and Malaterre, P.-O.:
Assimilation de données appliquée à un modèle pluie-débit distribué pour la prévision des crues,
in: De la prévision des crues à la gestion de crise,
Société hydaulique de France, Avignon, 2018. a
Klemes, V.:
Operational testing of hydrological simulation models,
Hydrolog. Sci. J.,
31, 13–24, https://doi.org/10.1080/02626668609491024, 1986. a
Laganier, O., Ayral, P. A., Salze, D., and Sauvagnargues, S.: A coupling of hydrologic and hydraulic models appropriate for the fast floods of the Gardon River basin (France), Nat. Hazards Earth Syst. Sci., 14, 2899–2920, https://doi.org/10.5194/nhess-14-2899-2014, 2014. a, b
Laurent, L., Le Riche, R., Soulier, B., and Boucard, P.-A.:
An Overview of Gradient-Enhanced Metamodels with Applications,
Arch. Comput. Method. E.,
26, 61–106, 2019. a
Ledimet, F. and Talagrand, O.:
Variational Algorithms For Analysis And Assimilation Of Meteorological Observations – Theoretical Aspects,
Tellus A,
38, 97–110, https://doi.org/10.3402/tellusa.v38i2.11706, 1986. a
Lee, H., Seo, D.-J., Liu, Y., Koren, V., McKee, P., and Corby, R.: Variational assimilation of streamflow into operational distributed hydrologic models: effect of spatiotemporal scale of adjustment, Hydrol. Earth Syst. Sci., 16, 2233–2251, https://doi.org/10.5194/hess-16-2233-2012, 2012. a
Liu, Y., Weerts, A. H., Clark, M., Hendricks Franssen, H.-J., Kumar, S., Moradkhani, H., Seo, D.-J., Schwanenberg, D., Smith, P., van Dijk, A. I. J. M., van Velzen, N., He, M., Lee, H., Noh, S. J., Rakovec, O., and Restrepo, P.: Advancing data assimilation in operational hydrologic forecasting: progresses, challenges, and emerging opportunities, Hydrol. Earth Syst. Sci., 16, 3863–3887, https://doi.org/10.5194/hess-16-3863-2012, 2012. a
Lobligeois, F., Andréassian, V., Perrin, C., Tabary, P., and Loumagne, C.: When does higher spatial resolution rainfall information improve streamflow simulation? An evaluation using 3620 flood events, Hydrol. Earth Syst. Sci., 18, 575–594, https://doi.org/10.5194/hess-18-575-2014, 2014. a
McLaughlin, D.:
Recent developments in hydrologic data assimilation,
Rev. Geophys.,
33, 977–984, 1995. a
Moradkhani, H. and Sorooshian, S.:
General review of rainfall-runoff modeling: model calibration, data assimilation, and uncertainty analysis,
in: Hydrological modelling and the water cycle,
edited by: Sorooshian, S., Hsu, K.-L., Coppola, E. Tomassetti, B. Verdecchia, M., and Visconti, G.,
Springer, Berlin, Heidelberg, 1–24, https://doi.org/10.1007/978-3-540-77843-1, 2009. a
Mouelhi, S., Michel, C., Perrin, C., and Andréassian, V.:
Linking stream flow to rainfall at the annual time step: the Manabe bucket model revisited,
J. Hydrol.,
328, 283–296, 2006. a
Munier, S., Litrico, X., Belaud, G., and Perrin, C.:
Assimilation of discharge data into semidistributed catchment models for short-term flow forecasting: Case study of the Seine River basin,
J. Hydrol. Eng.,
20, 05014021, https://doi.org/10.1061/(ASCE)HE.1943-5584.0001054, 2014. a
Nash, J. E. and Sutcliffe, J. V.:
River flow forecasting through conceptual models. Part I. A conceptual models discussion of principles.,
J. Hydrol.,
10, 282–290, 1970. a
Nguyen, V. T., Georges, D., Besançon, G., and Zin, I.:
Parameter estimation of a real hydrological system using an adjoint method,
IFAC Papersonline,
49, 300–305, https://doi.org/10.1016/j.ifacol.2016.07.978, 2016. a, b, c, d
Oudin, L., Hervieu, F., Michel, C., Perrin, C., Andréassian, V., Anctil, F., and Loumagne, C.:
Which potential evapotranspiration input for a lumped rainfall–runoff model?: Part 2 – Towards a simple and efficient potential evapotranspiration model for rainfall–runoff modelling,
J. Hydrol.,
303, 290–306, 2005. a
Perrin, C., Michel, C., and Andréassian, V.:
Improvement of a parsimonious model for streamflow simulation,
J. Hydrol.,
279, 275-289, https://doi.org/10.1016/S0022-1694(03)00225-7, 2003. a, b, c, d
Pokhrel, P. and Gupta, H. V.:
On the use of spatial regularization strategies to improve calibration of distributed watershed models,
Water Resour. Res.,
46, W01505, https://doi.org/10.1029/2009WR008066, 2010. a
Quesney, A., Francois, C., Ottle, C., Hegarat, S., Loumagne, C., Normand, M., et al.:
Sequential assimilation of SAR/ERS data in a lumped rainfall-runoff model with an extended Kalman filter,
IAHS Publ., 267, 495–497, 2000. a
Rakovec, O., Kumar, R., Attinger, S., and Samaniego, L.:
Improving the realism of hydrologic model functioning through multivariate parameter estimation,
Water Resour. Res.,
52, 7779–7792, https://www.scopus.com, 2016. a
Riboust, P., Thirel, G., Moine, N. L., and Ribstein, P.:
Revisiting a Simple Degree-Day Model for Integrating Satellite Data: Implementation of Swe-Sca Hystereses,
J. Hydrol. Hydromech.,
67, 70–81, 2019. a
Roux, H., Labat, D., Garambois, P.-A., Maubourguet, M.-M., Chorda, J., and Dartus, D.: A physically-based parsimonious hydrological model for flash floods in Mediterranean catchments, Nat. Hazards Earth Syst. Sci., 11, 2567–2582, https://doi.org/10.5194/nhess-11-2567-2011, 2011.
a
Samaniego, L., Kumar, R., and Attinger, S.:
Multiscale parameter regionalization of a grid-based hydrologic model at the mesoscale,
Water Resour. Res.,
46, W05523, https://doi.org/10.1029/2008WR007327, 2010. a
Santos, L., Thirel, G., and Perrin, C.: Continuous state-space representation of a bucket-type rainfall-runoff model: a case study with the GR4 model using state-space GR4 (version 1.0), Geosci. Model Dev., 11, 1591–1605, https://doi.org/10.5194/gmd-11-1591-2018, 2018. a
Seo, D.-J., Cajina, L., Corby, R., and Howieson, T.:
Automatic state updating for operational streamflow forecasting via variational data assimilation,
J. Hydrol.,
367, 255–275, https://doi.org/10.1016/j.jhydrol.2009.01.019, 2009. a
Sun, L., Nistor, I., and Seidou, O.:
Streamflow data assimilation in SWAT model using Extended Kalman Filter,
J. Hydrol.,
531, 671–684, 2015. a
Sun, L., Seidou, O., Nistor, I., and Liu, K.:
Review of the Kalman-type hydrological data assimilation,
Hydrolog. Sci. J.,
61, 2348–2366, 2016. a
Thirel, G., Martin, E., Mahfouf, J.-F., Massart, S., Ricci, S., and Habets, F.: A past discharges assimilation system for ensemble streamflow forecasts over France – Part 1: Description and validation of the assimilation system, Hydrol. Earth Syst. Sci., 14, 1623–1637, https://doi.org/10.5194/hess-14-1623-2010, 2010. a
Tramblay, Y., Bouvier, C., Crespy, A., and Marchandise, A.:
Improvement of flash flood modelling using spatial patterns of rainfall: A case study in southern France, in: Sixth World FRIEND Conference, the Global Change: Facing Risks and Threats to Water Resources, October 2010, Fez, Morocco, IAHS Publ. 340, 172–178, 2010. a, b
Vannier, O., Braud, I., and Anquetin, S.:
Regional estimation of catchment-scale soil properties by means of streamflow recession analysis for use in distributed hydrological models,
Hydrol. Process.,
28, 6276–6291, https://doi.org/10.1002/hyp.10101, 2014. a
Vannier, O., Anquetin, S., and Braud, I.:
Investigating the role of geology in the hydrological response of Mediterranean catchments prone to flash-floods: Regional modelling study and process understanding,
J. Hydrol.,
541, 158–172, https://doi.org/10.1016/j.jhydrol.2016.04.001, 2016. a
Vidal, J. P., Martin, E., Franchistéguy, L., Baillon, M., and Soubeyroux, J. M.:
A 50-year high-resolution atmospheric reanalysis over France with the Safran system,
Int. J. Climatol.,
30, 1627–1644, https://doi.org/10.1002/joc.2003, 2010. a
Wang, J., Hong, Y., Li, L., Gourley, J. J., Khan, S. I., Yilmaz, K. K., Adler, R. F., Policelli, F. S., Habib, S., Irwn, D., et al.:
The coupled routing and excess storage (CREST) distributed hydrological model,
Hydrolog. Sci. J.,
56, 84–98, 2011. a
Zhu, C., Byrd, R. H., Lu, P., and Nocedal, J.:
L-BFGS-B: a limited memory FORTRAN code for solving bound constrained optimization problems,
Technical Report No. NAM-11,
EECS Department, Northwestern University, Evanston, IL, 1994. a
Short summary
This study contributes to flash flood prediction using a hydrological model. The model describes the spatial properties of the watersheds with hundreds of unknown parameters. The Gardon d'Anduze watershed is chosen as the study benchmark. A sophisticated numerical algorithm and the downstream discharge measurements make the identification of the model parameters possible. Results provide better model predictions and relevant spatial variability of some parameters inside this watershed.
This study contributes to flash flood prediction using a hydrological model. The model describes...
