Article
Engineering, Civil
Aline S. Falck, Javier Tomasella, Fabio L. R. Diniz, Viviana Maggioni
Summary: The study demonstrates the potential of a stochastic error model to generate precipitation ensemble fields from a regional numerical weather forecasting model, reducing both systematic and random errors. Compared to the more sophisticated ensemble techniques used by the ECMWF model, SREM2D is proven to be an efficient technique with low computational cost.
JOURNAL OF HYDROLOGY
(2021)
Article
Geosciences, Multidisciplinary
Manon Cassagnole, Maria-Helena Ramos, Ioanna Zalachori, Guillaume Thirel, Remy Garcon, Joel Gailhard, Thomas Ouillon
Summary: This study investigates the impact of 7-day streamflow forecasts of different qualities on the management of hydroelectric reservoirs and the economic gains generated from a linear programming optimization model. It shows that forecasts with recurrent positive bias and low accuracy result in the highest economic losses, while forecast systems with underdispersion reliability bias lead to the smallest losses. These losses, representing approximately 1% to 3% of revenue over the study period, are influenced not only by revenue but also spillage, stock evolution, production hours, and production rates.
HYDROLOGY AND EARTH SYSTEM SCIENCES
(2021)
Article
Engineering, Marine
R. Vettor, C. Guedes Soares
Summary: This study investigates different methodologies for predicting the uncertainties in ship fuel consumption, including ensemble weather forecasts, probabilistic approaches, and a classical first-order second-moment method. By comparing the results from different methods, it is found that the actual fuel consumption falls within the predicted range with reasonable agreement.
Article
Environmental Sciences
Zachary P. Brodeur, Scott Steinschneider
Summary: The study introduces a generalized error model for generating synthetic forecasts for water resources management, utilizing Skew Generalized Error Distribution and Copula method for simulation and validation. Two case studies conducted in Northern California demonstrate the flexibility and applicability of the model.
WATER RESOURCES RESEARCH
(2021)
Article
Geosciences, Multidisciplinary
Maryse Charpentier-Noyer, Daniela Peredo, Axelle Fleury, Hugo Marchal, Francois Bouttier, Eric Gaume, Pierre Nicolle, Olivier Payrastre, Maria-Helena Ramos
Summary: This paper presents a methodological framework for the event-based evaluation of short-range hydrometeorological ensemble forecasts in flash-flood events. The framework focuses on anticipating and accurately localizing discharge threshold exceedances. The proposed approach includes evaluating rainfall forecasts, analyzing the flood rising limb at ungauged sub-catchments, and evaluating forecast hydrographs at selected gauged sub-catchments. The framework is tested for a flash flood event in France and evaluated three ensemble rainfall nowcasting research products.
NATURAL HAZARDS AND EARTH SYSTEM SCIENCES
(2023)
Article
Water Resources
Samaneh Sohrabi, Francois P. Brissette
Summary: Resampling historical time series is a common method for generating long-term probabilistic streamflow forecasts, but there is a need for more flexible approaches considering non-stationarities. This study compared the performance of a stochastic weather generator with resampling historical meteorological time series for ensemble streamflow forecasts. The results indicated that both methods performed similarly, suggesting that weather generators can serve as substitutes for resampling historical data.
HYDROLOGICAL SCIENCES JOURNAL
(2021)
Article
Water Resources
James C. Bennett, Q. J. Wang, David E. Robertson, Robert Bridgart, Julien Lerat, Ming Li, Kelvin Michael
Summary: This study revised the error model for generating long-term forecasts for ephemeral rivers, showing that the Forecast Guided Stochastic Scenarios (FoGSS) can produce reliable ensemble forecasts even in highly ephemeral streams. The method improves the accuracy of forecasts at short lead times and transitions to climatology-like forecasts at long lead times, paving the way for operational long-range forecasts in ephemeral rivers.
ADVANCES IN WATER RESOURCES
(2021)
Article
Computer Science, Interdisciplinary Applications
Sanjib Sharma, Ganesh Raj Ghimire, Ridwan Siddique
Summary: Skillful streamflow forecasts using integrated numerical weather prediction ensembles, distributed hydrological models, and machine learning have been shown to improve forecast skill and reliability in various water policy and management areas. A case study in the Upper Susquehanna River basin demonstrated that the machine learning postprocessor can outperform low-complexity forecasts and standalone modeling approaches in improving streamflow forecasts, particularly at medium-range lead times, for high flows, and during the warm season. Overall, this study highlights the benefits of incorporating machine learning techniques in streamflow forecasting.
JOURNAL OF HYDROINFORMATICS
(2023)
Article
Environmental Sciences
Jiayuan Li, Xing Yuan
Summary: Medium-range streamflow forecasts are largely dependent on accurate meteorological forecasts, but due to errors in precipitation forecasts, most streamflow forecasts only rely on historical data. In this study, a cascade LSTM model is used to forecast daily streamflow over 49 watersheds in the Yangtze River basin up to 15 days. The results show that the cascade LSTM model provides skillful streamflow forecasts, with the performance improving with increasing drainage area. The implementation of the cascade LSTM model leads to increased streamflow Kling-Gupta efficiency in 61-88% of the watersheds, especially at longer lead times.
Article
Geosciences, Multidisciplinary
S. Vecherin, S. Ketcham, A. Meyer, K. Dunn, J. Desmond, M. Parker
Summary: This paper presents a methodology for probabilistic seismic ensemble prediction for unknown subsurface structures. Instead of specifying site properties, the methodology uses probability distribution functions to generate ensemble realizations of signal arrivals and estimate statistical properties of the signals. This approach can be used for risk analysis in remote or inaccessible locations.
JOURNAL OF APPLIED GEOPHYSICS
(2022)
Article
Meteorology & Atmospheric Sciences
Kirien Whan, Jakob Zscheischler, Alexander I. Jordan, Johanna F. Ziegel
Summary: Statistical post-processing plays a crucial role in providing accurate weather forecasts and early warnings. This study compared various methods and found that MBCn and OA are more effective in capturing dependence structures compared to ECC and the Schaake Shuffle.
WEATHER AND CLIMATE EXTREMES
(2021)
Article
Water Resources
Saswata Nandi, Manne Janga Reddy
Summary: This study evaluates the utility of the TIGGE multimodel ensemble meteorological forecasts over the Upper Bhima River basin and highlights the efficacy of the BMA approach in flood forecasting. Results show that precipitation and streamflow forecasts deteriorate with increasing lead time but can be improved with suitable techniques such as bias-correction and BMA-based post-processing. It is recommended to use an integrated system of improved precipitation prediction, calibrated VIC-RAPID model, and post-processing of streamflows for reliable flood warning system.
HYDROLOGICAL SCIENCES JOURNAL
(2023)
Article
Environmental Sciences
Yiheng Xiang, Tao Peng, Qi Gao, Tieyuan Shen, Haixia Qi
Summary: This study evaluated the reliabilities of the ECMWF and NCEP models in ensemble precipitation forecast and ensemble streamflow prediction. The GPP method was found to be more effective than the BMA method in improving the performances of NCEP. The results suggest that both ECMWF and NCEP have good potential for both EPF and ESP.
Article
Meteorology & Atmospheric Sciences
K. B. R. R. Hari Prasad, V. S. Prasad, M. Sateesh, K. Amar Jyothi
Summary: The study evaluates the consistency of combining 3D variational technique and nudging in the same modeling system for short-term forecasts of heavy rainfall events over the Indian subcontinent. It finds that assimilating radar and lightning data improves the accuracy of rainfall forecasts, with lightning data playing a significant role in forecast performance.
QUARTERLY JOURNAL OF THE ROYAL METEOROLOGICAL SOCIETY
(2023)
Article
Environmental Sciences
P. Ipsita, V. Rakesh, Randhir Singh, G. N. Mohapatra
Summary: This study analyzes the impact of land use changes on short range weather forecasts over the Indian region. The Weather Research and Forecasting (WRF) model is used to simulate experiments using land use data from MODIS and ISRO satellites. The results show that using recent land use data improves the model's skill in rainfall forecast and predicting extreme rare rainfall events, particularly during the monsoon season.
Article
Environmental Sciences
G. Piazzi, G. Thirel, C. Perrin, O. Delaigue
Summary: Skillful streamflow forecasts are crucial for water-related applications, with a growing emphasis on improving initial condition estimates through data assimilation. This study assesses the sensitivity of DA-based IC estimation to various uncertainties and model updates over 232 watersheds in France. The comparison of two ensemble-based techniques shows that accurate routing store estimates benefit the DA-based IC estimation, with the EnKF outperforming the PF in forecasting meteorological uncertainty.
WATER RESOURCES RESEARCH
(2021)
Article
Environmental Sciences
Ahmed Moucha, Lahoucine Hanich, Yves Tramblay, Amina Saaidi, Simon Gascoin, Eric Martin, Michel Le Page, Elhoussaine Bouras, Camille Szczypta, Lionel Jarlan
Summary: The research aims to evaluate and adapt the SAFRAN reanalysis system in order to map meteorological variables in the Tensift catchment in Morocco, as well as to project future temperature and precipitation based on the Euro-CORDEX database. Results show that an irregular grid up to 1 km resolution is better for reproducing meteorological variables, especially in mountainous areas, compared to the regular 8 km resolution version of SAFRAN.
Article
Water Resources
Thibault Lemaitre-Basset, Lila Collet, Guillaume Thirel, Juraj Parajka, Guillaume Evin, Benoit Hingray
Summary: The Mediterranean region is a climate change hotspot for water resources, but uncertainty analyses of hydrological projections are rarely quantified. The study found that high flows may increase by 30% on average by 2085, with the highest uncertainty contribution from RCPs and GCMs; while 50% of low-flow projections indicate a decrease of 7% or more by 2085, with the most important sources of uncertainty being HM structures, hydrological model parameters, and GCMs.
HYDROLOGICAL SCIENCES JOURNAL
(2021)
Article
Water Resources
Eric Sauquet, Aurelien Beaufort, Romain Sarremejane, Guillaume Thirel
Summary: Climate change is causing an increase in the probability of headwater drying, with future spatial patterns showing more contrast compared to current conditions. This may lead to losses of ecosystem functions in aquatic ecosystems, especially in regions with historically high probabilities of drying.
HYDROLOGICAL SCIENCES JOURNAL-JOURNAL DES SCIENCES HYDROLOGIQUES
(2021)
Article
Environmental Sciences
Thibault Lemaitre-Basset, Ludovic Oudin, Guillaume Thirel
Summary: This study investigates the impact of considering carbon dioxide (CO2) in the potential evapotranspiration (PE) formulation on hydrological projections. Results show that including CO2 in the formulation significantly decreases PE values and limits runoff decrease projections. The sensitivity of hydrological projections to the processes represented in the PE formulation is highlighted.
Article
Environmental Sciences
Alexis Jeantet, Guillaume Thirel, Alienor Jeliazkov, Philippe Martin, Julien Tournebize
Summary: This study evaluates the future of subsurface drainage in La Jailliere, France from a hydrological perspective and in the context of climate change. The findings suggest that the sustainability of the drainage system design is at risk, with potential consequences such as increased runoff and water quality issues.
FRONTIERS IN ENVIRONMENTAL SCIENCE
(2022)
Article
Agronomy
Myriam Soutif-Bellenger, Guillaume Thirel, Olivier Therond, Jean Villerd
Summary: This study evaluates the consequences of using simplified approaches for irrigation water requirement assessment at a catchment scale and the consequences of various modeling choices, providing information on the uncertainties. The results show that several simplified modeling approaches can reproduce the irrigation simulated by the high-accuracy model, but may not necessarily correspond to an optimal irrigation scheme.
IRRIGATION SCIENCE
(2023)
Article
Water Resources
Alexis Jeantet, Guillaume Thirel, Thibault Lemaitre-Basset, Julien Tournebize
Summary: To date, there have been few studies analyzing the propagation of uncertainty in a hydroclimatic modelling chain for subsurface drainage hydrology. This study conducted such an analysis in a representative French drainage site using 30 climate projections under three representative concentration pathways. Three hydrological models and parameter sets were used to quantify uncertainties in hydrological components. Results showed that the main source of uncertainty came from climate models, while the contribution of hydrological components to the uncertainty was negligible.
HYDROLOGICAL SCIENCES JOURNAL
(2023)
Article
Water Resources
Cyril Thebault, Charles Perrin, Vazken Andreassian, Guillaume Thirel, Sebastien Legrand, Olivier Delaigue
Summary: This study aimed to investigate the impact of inconsistencies in commonly available streamflow time series on the efficiency and parameter estimates of rainfall-runoff models. Data from 30 catchments in France from 1998 to 2018 were collected and used for hydrological modeling. The results suggest that common suspicious streamflow data have a limited impact on model efficiency and parameter estimates overall, but can lead to instability and lack of robustness in single catchment studies.
HYDROLOGICAL SCIENCES JOURNAL
(2023)
Article
Geosciences, Multidisciplinary
Antoine Sobaga, Bertrand Decharme, Florence Habets, Christine Delire, Noele Enjelvin, Paul-Olivier Redon, Pierre Faure-Catteloin, Patrick Le Moigne
Summary: This study evaluates the performance of the interactions between soil-biosphere-atmosphere (ISBA) land surface model in simulating soil hydrology and water drainage. The evaluation is done using data from seven lysimeters in two sites in northeastern France. The results show that ISBA performs well in terms of soil volumetric water content and water mass, but some weaknesses appear with the van Genuchten (1980) hydraulic conductivity function near saturation. The study also introduces a new hydraulic conductivity function that improves the simulation of drainage dynamics.
HYDROLOGY AND EARTH SYSTEM SCIENCES
(2023)
Article
Geosciences, Multidisciplinary
Eva Sebok, Hans Jorgen Henriksen, Ernesto Pasten-Zapata, Peter Berg, Guillaume Thirel, Anthony Lemoine, Andrea Lira-Loarca, Christiana Photiadou, Rafael Pimentel, Paul Royer-Gaspard, Erik Kjellstrom, Jens Hesselbjerg Christensen, Jean Philippe Vidal, Philippe Lucas-Picher, Markus G. Donat, Giovanni Besio, Maria Jose Polo, Simon Stisen, Yvan Caballero, Ilias G. Pechlivanidis, Lars Troldborg, Jens Christian Refsgaard
Summary: This study presents a method for assessing uncertainties in climate impact studies by using expert elicitation for model weighting. The results show that expert elicitation can effectively reduce uncertainties in climate impact.
HYDROLOGY AND EARTH SYSTEM SCIENCES
(2022)
Article
Geosciences, Multidisciplinary
Thibault Lemaitre-Basset, Ludovic Oudin, Guillaume Thirel, Lila Collet
Summary: In this study, we analyzed the sources of uncertainty in the potential evaporation (PE) modeling chain for hydrological studies. The results showed that the contributions of different factors, such as PE formulations, Representative Concentration Pathway (RCP) scenarios, GCMs, and RCMs, varied. All PE formulations showed similar future trends, but the Penman-Monteith formulation was found to be more representative in hydrological impact studies.
HYDROLOGY AND EARTH SYSTEM SCIENCES
(2022)
Article
Geosciences, Multidisciplinary
Paul Royer-Gaspard, Vazken Andreassian, Guillaume Thirel
Summary: The performance of hydrological models under different climatic conditions is crucial for assessing the impact of climate change on river regimes and water availability. A new performance metric, PMR, is proposed in this study to evaluate model robustness without using DSST, and can be performed with a single model calibration. The PMR metric demonstrates similar patterns to DSST biases and can be used to evaluate the temporal transferability of any hydrological model at a low computational cost.
HYDROLOGY AND EARTH SYSTEM SCIENCES
(2021)
Article
Geosciences, Multidisciplinary
Manon Cassagnole, Maria-Helena Ramos, Ioanna Zalachori, Guillaume Thirel, Remy Garcon, Joel Gailhard, Thomas Ouillon
Summary: This study investigates the impact of 7-day streamflow forecasts of different qualities on the management of hydroelectric reservoirs and the economic gains generated from a linear programming optimization model. It shows that forecasts with recurrent positive bias and low accuracy result in the highest economic losses, while forecast systems with underdispersion reliability bias lead to the smallest losses. These losses, representing approximately 1% to 3% of revenue over the study period, are influenced not only by revenue but also spillage, stock evolution, production hours, and production rates.
HYDROLOGY AND EARTH SYSTEM SCIENCES
(2021)
Article
Geosciences, Multidisciplinary
Laurene J. E. Bouaziz, Fabrizio Fenicia, Guillaume Thirel, Tanja de Boer-Euser, Joost Buitink, Claudia C. Brauer, Jan De Niel, Benjamin J. Dewals, Gilles Drogue, Benjamin Grelier, Lieke A. Melsen, Sotirios Moustakas, Jiri Nossent, Fernando Pereira, Eric Sprokkereef, Jasper Stam, Albrecht H. Weerts, Patrick Willems, Hubert H. G. Savenije, Markus Hrachowitz
Summary: This study quantified differences in performance among 12 hydrological models, finding substantial variations in internal process representation and a lack of systematic consistency with different data sources. Modeled annual evaporation rates were consistent with GLEAM estimates, but there were significant uncertainties in other aspects, indicating the complexity and challenges in accurately modeling hydrological processes.
HYDROLOGY AND EARTH SYSTEM SCIENCES
(2021)
