Articles | Volume 28, issue 16
https://doi.org/10.5194/hess-28-3777-2024
© Author(s) 2024. 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-28-3777-2024
© Author(s) 2024. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
22 Aug 2024
Research article |
| 22 Aug 2024
| 22 Aug 2024
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
Annalina Lombardi
CORRESPONDING AUTHOR
CETEMPS, Centre of Excellence University of L'Aquila, 67100 L'Aquila, Italy
Department of Physical and Chemical Sciences, University of L'Aquila, 67100 L'Aquila, Italy
Barbara Tomassetti
CORRESPONDING AUTHOR
CETEMPS, Centre of Excellence University of L'Aquila, 67100 L'Aquila, Italy
Valentina Colaiuda
CETEMPS, Centre of Excellence University of L'Aquila, 67100 L'Aquila, Italy
Ludovico Di Antonio
Univ Paris Est Creteil, Université Paris Cité, CNRS, LISA, F-94010 Créteil, France
Paolo Tuccella
CETEMPS, Centre of Excellence University of L'Aquila, 67100 L'Aquila, Italy
Department of Physical and Chemical Sciences, University of L'Aquila, 67100 L'Aquila, Italy
Mario Montopoli
CETEMPS, Centre of Excellence University of L'Aquila, 67100 L'Aquila, Italy
National Research Council of Italy, Institute of Atmospheric Sciences and Climate (CNR-ISAC), 00133 Rome, Italy
Giovanni Ravazzani
Department of Civil and Environmental Engineering, Politecnico di Milano, 20133 Milan, Italy
Frank Silvio Marzano
CETEMPS, Centre of Excellence University of L'Aquila, 67100 L'Aquila, Italy
Department of Information Engineering, Electronics and Telecommunications, Sapienza University of Rome, 00184 Rome, Italy
deceased, 8 May 2022
Raffaele Lidori
CETEMPS, Centre of Excellence University of L'Aquila, 67100 L'Aquila, Italy
Giulia Panegrossi
National Research Council of Italy, Institute of Atmospheric Sciences and Climate (CNR-ISAC), 00133 Rome, Italy
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Laurent Menut, Bertrand Bessagnet, Régis Briant, Arineh Cholakian, Florian Couvidat, Sylvain Mailler, Romain Pennel, Guillaume Siour, Paolo Tuccella, Solène Turquety, and Myrto Valari
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Paolo Tuccella, Giovanni Pitari, Valentina Colaiuda, Edoardo Raparelli, and Gabriele Curci
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Annalina Lombardi, Valentina Colaiuda, Marco Verdecchia, and Barbara Tomassetti
Hydrol. Earth Syst. Sci., 25, 1969–1992, https://doi.org/10.5194/hess-25-1969-2021, https://doi.org/10.5194/hess-25-1969-2021, 2021
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The paper presents a modelling approach for the assessment of extremes in the hydrological cycle at a multi-catchment scale. It describes two new hydrological stress indices, innovative instruments that could be used by Civil Protection operators, for flood mapping in early warning systems. The main advantage in using the proposed indices is the possibility of displaying hydrological-stress information over any geographical domain.
Rossella Ferretti, Annalina Lombardi, Barbara Tomassetti, Lorenzo Sangelantoni, Valentina Colaiuda, Vincenzo Mazzarella, Ida Maiello, Marco Verdecchia, and Gianluca Redaelli
Hydrol. Earth Syst. Sci., 24, 3135–3156, https://doi.org/10.5194/hess-24-3135-2020, https://doi.org/10.5194/hess-24-3135-2020, 2020
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Floods and severe rainfall are among the major natural hazards in the Mediterranean basin. Though precipitation weather forecasts have improved considerably, precipitation estimation is still affected by errors that can deteriorate the hydrological forecast. To improve hydrological forecasting, a regional-scale meteorological–hydrological ensemble is presented. This allows for predicting potential severe events days in advance and for characterizing the uncertainty of the hydrological forecast.
Laurent Menut, Paolo Tuccella, Cyrille Flamant, Adrien Deroubaix, and Marco Gaetani
Atmos. Chem. Phys., 19, 14657–14676, https://doi.org/10.5194/acp-19-14657-2019, https://doi.org/10.5194/acp-19-14657-2019, 2019
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Aerosol direct and indirect effects are studied over west Africa in the summer of 2016 using the coupled WRF-CHIMERE regional model including aerosol–cloud interaction parameterization. Sensitivity experiments are designed to gain insights into the impact of the aerosols dominating the atmospheric composition in southern west Africa. It is shown that the decrease of anthropogenic emissions along the coast has an impact on the mineral dust load over west Africa by increasing their emissions.
Laura Palacios-Peña, Pedro Jiménez-Guerrero, Rocío Baró, Alessandra Balzarini, Roberto Bianconi, Gabriele Curci, Tony Christian Landi, Guido Pirovano, Marje Prank, Angelo Riccio, Paolo Tuccella, and Stefano Galmarini
Atmos. Chem. Phys., 19, 2965–2990, https://doi.org/10.5194/acp-19-2965-2019, https://doi.org/10.5194/acp-19-2965-2019, 2019
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The main uncertainties regarding the estimation of changes in the Earth’s energy budget are related to the role of atmospheric aerosols. Our study evaluates the representation of aerosol optical properties by different atmospheric chemistry models against remote-sensing observations in order to reduce this uncertainty. Results show that the representation of aerosol optical properties is strongly dependent on the used model.
Gabriele Curci, Ummugulsum Alyuz, Rocio Barò, Roberto Bianconi, Johannes Bieser, Jesper H. Christensen, Augustin Colette, Aidan Farrow, Xavier Francis, Pedro Jiménez-Guerrero, Ulas Im, Peng Liu, Astrid Manders, Laura Palacios-Peña, Marje Prank, Luca Pozzoli, Ranjeet Sokhi, Efisio Solazzo, Paolo Tuccella, Alper Unal, Marta G. Vivanco, Christian Hogrefe, and Stefano Galmarini
Atmos. Chem. Phys., 19, 181–204, https://doi.org/10.5194/acp-19-181-2019, https://doi.org/10.5194/acp-19-181-2019, 2019
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Atmospheric carbonaceous aerosols are able to absorb solar radiation and they continue to contribute some of the largest uncertainties in projected climate change. One important detail is how the chemical species are arranged inside each particle, i.e. the knowledge of their mixing state. We use an ensemble of regional model simulations to test different mixing state assumptions and found that a combination of internal and external mixing may better reproduce sunphotometer observations.
Rocío Baró, Pedro Jiménez-Guerrero, Martin Stengel, Dominik Brunner, Gabriele Curci, Renate Forkel, Lucy Neal, Laura Palacios-Peña, Nicholas Savage, Martijn Schaap, Paolo Tuccella, Hugo Denier van der Gon, and Stefano Galmarini
Atmos. Chem. Phys., 18, 15183–15199, https://doi.org/10.5194/acp-18-15183-2018, https://doi.org/10.5194/acp-18-15183-2018, 2018
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Particles in the atmosphere, such as pollution, desert dust, and volcanic ash, have an impact on meteorology. They interact with incoming radiation resulting in a cooling effect of the atmosphere. Today, the use of meteorology and chemistry models help us to understand these processes, but there are a lot of uncertainties. The goal of this work is to evaluate how these interactions are represented in the models by comparing them to satellite data to see how close they are to reality.
Ulas Im, Jesper Heile Christensen, Camilla Geels, Kaj Mantzius Hansen, Jørgen Brandt, Efisio Solazzo, Ummugulsum Alyuz, Alessandra Balzarini, Rocio Baro, Roberto Bellasio, Roberto Bianconi, Johannes Bieser, Augustin Colette, Gabriele Curci, Aidan Farrow, Johannes Flemming, Andrea Fraser, Pedro Jimenez-Guerrero, Nutthida Kitwiroon, Peng Liu, Uarporn Nopmongcol, Laura Palacios-Peña, Guido Pirovano, Luca Pozzoli, Marje Prank, Rebecca Rose, Ranjeet Sokhi, Paolo Tuccella, Alper Unal, Marta G. Vivanco, Greg Yarwood, Christian Hogrefe, and Stefano Galmarini
Atmos. Chem. Phys., 18, 8929–8952, https://doi.org/10.5194/acp-18-8929-2018, https://doi.org/10.5194/acp-18-8929-2018, 2018
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We evaluate the impact of global and regional anthropogenic emission reductions on major air pollutant levels over Europe and North America, using a multi-model ensemble of regional chemistry and transport models. Results show that ozone levels are largely driven by long-range transport over both continents while other pollutants such as carbon monoxide or aerosols are mainly controlled by domestic sources. Use of multi-model ensembles can help to reduce the uncertainties in individual models.
Stefano Galmarini, Ioannis Kioutsioukis, Efisio Solazzo, Ummugulsum Alyuz, Alessandra Balzarini, Roberto Bellasio, Anna M. K. Benedictow, Roberto Bianconi, Johannes Bieser, Joergen Brandt, Jesper H. Christensen, Augustin Colette, Gabriele Curci, Yanko Davila, Xinyi Dong, Johannes Flemming, Xavier Francis, Andrea Fraser, Joshua Fu, Daven K. Henze, Christian Hogrefe, Ulas Im, Marta Garcia Vivanco, Pedro Jiménez-Guerrero, Jan Eiof Jonson, Nutthida Kitwiroon, Astrid Manders, Rohit Mathur, Laura Palacios-Peña, Guido Pirovano, Luca Pozzoli, Marie Prank, Martin Schultz, Rajeet S. Sokhi, Kengo Sudo, Paolo Tuccella, Toshihiko Takemura, Takashi Sekiya, and Alper Unal
Atmos. Chem. Phys., 18, 8727–8744, https://doi.org/10.5194/acp-18-8727-2018, https://doi.org/10.5194/acp-18-8727-2018, 2018
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An ensemble of model results relating to ozone concentrations in Europe in 2010 has been produced and studied. The novelty consists in the fact that the ensemble is made of results of models working at two different scales (regional and global), therefore contributing in detail two different parts of the atmospheric spectrum. The ensemble defined as a hybrid has been studied in detail and shown to bring additional value to the assessment of air quality.
Ulas Im, Jørgen Brandt, Camilla Geels, Kaj Mantzius Hansen, Jesper Heile Christensen, Mikael Skou Andersen, Efisio Solazzo, Ioannis Kioutsioukis, Ummugulsum Alyuz, Alessandra Balzarini, Rocio Baro, Roberto Bellasio, Roberto Bianconi, Johannes Bieser, Augustin Colette, Gabriele Curci, Aidan Farrow, Johannes Flemming, Andrea Fraser, Pedro Jimenez-Guerrero, Nutthida Kitwiroon, Ciao-Kai Liang, Uarporn Nopmongcol, Guido Pirovano, Luca Pozzoli, Marje Prank, Rebecca Rose, Ranjeet Sokhi, Paolo Tuccella, Alper Unal, Marta Garcia Vivanco, Jason West, Greg Yarwood, Christian Hogrefe, and Stefano Galmarini
Atmos. Chem. Phys., 18, 5967–5989, https://doi.org/10.5194/acp-18-5967-2018, https://doi.org/10.5194/acp-18-5967-2018, 2018
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The impacts of air pollution on human health and their costs in Europe and the United States for the year 2010 ared modeled by a multi-model ensemble. In Europe, the number of premature deaths is calculated to be 414 000, while in the US it is estimated to be 160 000. Health impacts estimated by individual models can vary up to a factor of 3. Results show that the domestic emissions have the largest impact on premature deaths, compared to foreign sources.
Daniele Visioni, Giovanni Pitari, Paolo Tuccella, and Gabriele Curci
Atmos. Chem. Phys., 18, 2787–2808, https://doi.org/10.5194/acp-18-2787-2018, https://doi.org/10.5194/acp-18-2787-2018, 2018
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Sulfate geoengineering is a proposed technique that would mimic explosive volcanic eruptions by injecting sulfur dioxide (SO2) into the stratosphere to counteract global warming produced by greenhouse gases by reflecting part of the incoming solar radiation. In this study we use two models to simulate how the injected aerosols would react to dynamical changes in the stratosphere (due to the quasi-biennial oscillation - QBO) and how this would affect the deposition of sulfate at the surface.
Stefano Federico, Marco Petracca, Giulia Panegrossi, Claudio Transerici, and Stefano Dietrich
Adv. Sci. Res., 14, 187–194, https://doi.org/10.5194/asr-14-187-2017, https://doi.org/10.5194/asr-14-187-2017, 2017
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This study investigates the impact of using lightning data on the precipitation forecast at different forecast ranges (3–24 h). Twenty case studies, occurred over Italy in fall 2012, are selected to show the impact.
Results show the important and positive impact of using lightning data to improve the precipitation forecast. The time range, however, is very important because the performance decreases steadily and substantially with forecasting time.
Efisio Solazzo, Roberto Bianconi, Christian Hogrefe, Gabriele Curci, Paolo Tuccella, Ummugulsum Alyuz, Alessandra Balzarini, Rocío Baró, Roberto Bellasio, Johannes Bieser, Jørgen Brandt, Jesper H. Christensen, Augistin Colette, Xavier Francis, Andrea Fraser, Marta Garcia Vivanco, Pedro Jiménez-Guerrero, Ulas Im, Astrid Manders, Uarporn Nopmongcol, Nutthida Kitwiroon, Guido Pirovano, Luca Pozzoli, Marje Prank, Ranjeet S. Sokhi, Alper Unal, Greg Yarwood, and Stefano Galmarini
Atmos. Chem. Phys., 17, 3001–3054, https://doi.org/10.5194/acp-17-3001-2017, https://doi.org/10.5194/acp-17-3001-2017, 2017
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As part of the third phase of AQMEII, this study uses timescale analysis to apportion error to the responsible processes, detect causes of model error, and identify the processes and scales that require dedicated investigations. The analysis tackles model performance gauging through measurement-to-model comparison, error decomposition, and time series analysis of model biases for ozone, CO, SO2, NO, NO2, PM10, PM2.5, wind speed, and temperature over Europe and North America.
Stefano Federico, Marco Petracca, Giulia Panegrossi, and Stefano Dietrich
Nat. Hazards Earth Syst. Sci., 17, 61–76, https://doi.org/10.5194/nhess-17-61-2017, https://doi.org/10.5194/nhess-17-61-2017, 2017
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The motivation of this study is to use lightning observations to improve the precipitation forecast at the short range (3 h). For this purpose 20 case studies, occurring in fall 2012, were analyzed using a meteorological model, whose set-up is applicable in real-time weather forecasting. Lightning observations were provided by the LINET network. Results show a systematic improvement of the 3 h precipitation forecast when lightning observations are used.
Eleonora Aruffo, Fabio Biancofiore, Piero Di Carlo, Marcella Busilacchio, Marco Verdecchia, Barbara Tomassetti, Cesare Dari-Salisburgo, Franco Giammaria, Stephane Bauguitte, James Lee, Sarah Moller, James Hopkins, Shalini Punjabi, Stephen J. Andrews, Alistair C. Lewis, Paul I. Palmer, Edward Hyer, Michael Le Breton, and Carl Percival
Atmos. Meas. Tech., 9, 5591–5606, https://doi.org/10.5194/amt-9-5591-2016, https://doi.org/10.5194/amt-9-5591-2016, 2016
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During the BORTAS aircraft campaign, we measured NO2 and their oxidtation products (as peroxy nitrates) with a custom laser-induced fluorescence instrument. Because of the high correlation between known pyrogenic tracers (i.e., carbon monoxide) and peroxy nitrates, we provide two methods to use these species for the identification of biomass burning (BB) plumes. Using an artifical neural network, we improved the BB identification taking into account of a meteorological parameter (pressure).
Paolo Sanò, Giulia Panegrossi, Daniele Casella, Anna C. Marra, Francesco Di Paola, and Stefano Dietrich
Atmos. Meas. Tech., 9, 5441–5460, https://doi.org/10.5194/amt-9-5441-2016, https://doi.org/10.5194/amt-9-5441-2016, 2016
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The objective of this paper is to describe the development and evaluate the performance of a totally new version of the Passive microwave Neural network Precipitation Retrieval (PNPR v2), an algorithm based on a neural network approach, designed to retrieve the instantaneous surface precipitation rate using the cross-track ATMS radiometer measurements.
N. Roberto, E. Adirosi, L. Baldini, D. Casella, S. Dietrich, P. Gatlin, G. Panegrossi, M. Petracca, P. Sanò, and A. Tokay
Atmos. Meas. Tech., 9, 535–552, https://doi.org/10.5194/amt-9-535-2016, https://doi.org/10.5194/amt-9-535-2016, 2016
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This study examines various microphysical properties of liquid and solid hydrometeors to investigate their relationship with lightning activity. Measurements were collected from the Polar 55C dual-polarization radar, a 2-DVD, and LINET. From the analysis of three significant case studies, linear relations between the total mass of graupel and the number of strokes were found. Results point out the key role of ice mass in determining the electrical charging of convective clouds.
D. Casella, G. Panegrossi, P. Sanò, L. Milani, M. Petracca, and S. Dietrich
Atmos. Meas. Tech., 8, 1217–1232, https://doi.org/10.5194/amt-8-1217-2015, https://doi.org/10.5194/amt-8-1217-2015, 2015
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The CCA algorithm is applicable to any modern passive microwave radiometer on board polar orbiting satellites; it has been developed using a data set of co-located SSMIS and TRMM-PR measurements and AMSU-MHS and TRMM-PR measurements. The algorithm shows a small rate of false alarms and superior detection capability and can efficiently detect (POD between 0.55 and 0.71) minimum rain rate varying from 0.14 mm/h (AMSU over ocean) to 0.41 (SSMIS over coast).
P. Sanò, G. Panegrossi, D. Casella, F. Di Paola, L. Milani, A. Mugnai, M. Petracca, and S. Dietrich
Atmos. Meas. Tech., 8, 837–857, https://doi.org/10.5194/amt-8-837-2015, https://doi.org/10.5194/amt-8-837-2015, 2015
L. Milani, F. Porcù, D. Casella, S. Dietrich, G. Panegrossi, M. Petracca, and P. Sanò
The Cryosphere Discuss., https://doi.org/10.5194/tcd-9-141-2015, https://doi.org/10.5194/tcd-9-141-2015, 2015
Revised manuscript not accepted
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The aim of this work is to show that the CloudSat Cloud Profiling Radar (CPR) can be a valuable source of snowfall rate data in Antarctica that can be used at different temporal scales. Two years of CloudSat data over Antarctica are analyzed and two different approaches for precipitation estimates are considered. The results show that CPR can provide valuable support to the sparse network of ground-based instruments both for numerical model validation and climatological studies.
S. Federico, E. Avolio, M. Petracca, G. Panegrossi, P. Sanò, D. Casella, and S. Dietrich
Nat. Hazards Earth Syst. Sci., 14, 2933–2950, https://doi.org/10.5194/nhess-14-2933-2014, https://doi.org/10.5194/nhess-14-2933-2014, 2014
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This paper shows the implementation of a simple model for simulating lightning into the RAMS model.
The methodology is applied to six case studies that occurred in central Italy and the results are verified against LINET observations.
Advantages and weaknesses of the methodology are discussed.
A. Ceppi, G. Ravazzani, C. Corbari, R. Salerno, S. Meucci, and M. Mancini
Hydrol. Earth Syst. Sci., 18, 3353–3366, https://doi.org/10.5194/hess-18-3353-2014, https://doi.org/10.5194/hess-18-3353-2014, 2014
R. Ferretti, E. Pichelli, S. Gentile, I. Maiello, D. Cimini, S. Davolio, M. M. Miglietta, G. Panegrossi, L. Baldini, F. Pasi, F. S. Marzano, A. Zinzi, S. Mariani, M. Casaioli, G. Bartolini, N. Loglisci, A. Montani, C. Marsigli, A. Manzato, A. Pucillo, M. E. Ferrario, V. Colaiuda, and R. Rotunno
Hydrol. Earth Syst. Sci., 18, 1953–1977, https://doi.org/10.5194/hess-18-1953-2014, https://doi.org/10.5194/hess-18-1953-2014, 2014
A. Mugnai, D. Casella, E. Cattani, S. Dietrich, S. Laviola, V. Levizzani, G. Panegrossi, M. Petracca, P. Sanò, F. Di Paola, D. Biron, L. De Leonibus, D. Melfi, P. Rosci, A. Vocino, F. Zauli, P. Pagliara, S. Puca, A. Rinollo, L. Milani, F. Porcù, and F. Gattari
Nat. Hazards Earth Syst. Sci., 13, 1959–1981, https://doi.org/10.5194/nhess-13-1959-2013, https://doi.org/10.5194/nhess-13-1959-2013, 2013
E. A. Smith, H. W.-Y. Leung, J. B. Elsner, A. V. Mehta, G. J. Tripoli, D. Casella, S. Dietrich, A. Mugnai, G. Panegrossi, and P. Sanò
Nat. Hazards Earth Syst. Sci., 13, 1185–1208, https://doi.org/10.5194/nhess-13-1185-2013, https://doi.org/10.5194/nhess-13-1185-2013, 2013
M. Formenton, G. Panegrossi, D. Casella, S. Dietrich, A. Mugnai, P. Sanò, F. Di Paola, H.-D. Betz, C. Price, and Y. Yair
Nat. Hazards Earth Syst. Sci., 13, 1085–1104, https://doi.org/10.5194/nhess-13-1085-2013, https://doi.org/10.5194/nhess-13-1085-2013, 2013
A. Ceppi, G. Ravazzani, A. Salandin, D. Rabuffetti, A. Montani, E. Borgonovo, and M. Mancini
Nat. Hazards Earth Syst. Sci., 13, 1051–1062, https://doi.org/10.5194/nhess-13-1051-2013, https://doi.org/10.5194/nhess-13-1051-2013, 2013
A. Mugnai, E. A. Smith, G. J. Tripoli, B. Bizzarri, D. Casella, S. Dietrich, F. Di Paola, G. Panegrossi, and P. Sanò
Nat. Hazards Earth Syst. Sci., 13, 887–912, https://doi.org/10.5194/nhess-13-887-2013, https://doi.org/10.5194/nhess-13-887-2013, 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
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
A semi-parametric hourly space–time weather generator
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.
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.
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
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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.
Cited articles
Andiego, G., Waseem, M., Usman, M., and Mani, N.:The Influence of Rain Gauge Network Density on the Performance of a Hydrological Model, Comput. Water Energ. Environ. Eng., 7, 27–50, https://doi.org/10.4236/cweee.2018.81002, 2018.
Benesty, J., Chen, J., and Huang, Y.: Time-delay estimation via linear interpolation and cross correlation, IEEE T. Speech Audio Process., 12, 509–519, https://doi.org/10.1109/TSA.2004.833008, 2004, 2004.
Berndt, D. J. and Clifford, J.: Using dynamic time warping to find patterns in time series. AAAIWS'94: Proceedings of the 3rd International Conference on Knowledge Discovery and Data Mining. AAAI Press, 359–370, Seattle WA 31 July–1 August, https://dl.acm.org/doi/proceedings/10.5555/3000850 (last access: 7 August 2024), 1994.
Bouttier, F. and Courtier, P.: Data Assimilation Concepts and Methods, https://www.ecmwf.int/en/elibrary/16928-data-assimilation-concepts-and-methods (last access: 6 August 2024), 1999.
Brocca, L., Massari, C., Pellarin, T., Filippucci, P., Ciabatta, L., Camici, S., Kerr, Y. H., and Fernández-Prieto, D.: River flow prediction in data scarce regions: soil moisture integrated satellite rainfall products outperform rain gauge observations in West Africa, Sci. Rep., 10, 12517, https://doi.org/10.1038/s41598-020-69343-x, 2020.
Camici, S., Massari, C., Ciabatta, L., Marchesini, I., and Brocca, L.: Which rainfall score is more informative about the performance in river discharge simulation? A comprehensive assessment on 1318 basins over Europe, Hydrol. Earth Syst. Sci., 24, 4869–4885, https://doi.org/10.5194/hess-24-4869-2020, 2020.
Camici, S., Giuliani, G., Brocca, L., Massari, C., Tarpanelli, A., Farahani, H. H., Sneeuw, N., Restano, M., and Benveniste, J.: Synergy between satellite observations of soil moisture and water storage anomalies for runoff estimation, Geosci. Model Dev., 15, 6935–6956, https://doi.org/10.5194/gmd-15-6935-2022, 2022.
Chacon-Hurtado, J. C., Alfonso, L., and Solomatine, D. P.: Rainfall and streamflow sensor network design: a review of applications, classification, and a proposed framework, Hydrol. Earth Syst. Sci., 21, 3071–3091, https://doi.org/10.5194/hess-21-3071-2017, 2017.
Colaiuda, V., Lombardi, A., Verdecchia, M., Mazzarella, V., Ricchi, A., Ferretti, R. and Tomassetti, B.: Flood Prediction: 770 Operational Hydrological Forecast with the Cetemps Hydrological Model (CHyM), Int. J. Environ. Sci. Nat. Res., 24, 556137, https://doi.org/10.19080/IJESNR.2020.24.556137, 2020.
Collischonn, B., Collischonn, W., and Morelli Tucci, C. E.: Daily hydrological modeling in the Amazon basin using TRMM rainfall estimates, J. Hydrol., 360, 207–216, https://doi.org/10.1016/j.jhydrol.2008.07.032, 2008.
Coppola, E., Tomassetti, B., Mariotti, L., Verdecchia, M., and Visconti, G.: Cellular automata algorithms for drainage network extraction and rainfall data assimilation, Hydrolog. Sci. J., 52, 579–592, https://doi.org/10.1623/hysj.52.3.579, 2007.
Coppola, E., Verdecchia, M., Giorgi, F., Colaiuda, V., Tomassetti, B., and Lombardi, A.: Changing hydrological conditions in the Po basin under global warming, Sci. Total Environ., 493, 1183–1196, https://doi.org/10.1016/j.scitotenv.2014.03.003, 2014.
Cressman, G. P.: An operational objective analysis system, Mon. Weather Rev., 87, 367–374, 1959.
Cristiano, E., ten Veldhuis, M.-C., and van de Giesen, N.: Spatial and temporal variability of rainfall and their effects on hydrological response in urban areas – a review, Hydrol. Earth Syst. Sci., 21, 3859–3878, https://doi.org/10.5194/hess-21-3859-2017, 2017.
Darko, S., Adjei, K.A., Gyamfi, C., Nii Odai, S., and Osei-Wusuansa, H.: Evaluation of RFE Satellite Precipitation and its Use in Streamflow Simulation in Poorly Gauged Basins, Environ. Process., 8, 691–712, https://doi.org/10.1007/s40710-021-00495-2, 2021.
Degiorgis, M., Gnecco, G., Gorni, S., Roth, G., Sanguineti, M. and Taramasso, A. C.: Flood hazard assessment via threshold binary classifiers: the case study of the Tanaro River Basin, Irrig. Drain., 62, 1–10, https://doi.org/10.1002/ird.1806, 2013.
Dembélé, M., Hrachowitz, M., Savenije, H. H. G., and Mariéthoz, G.: Improving the predictive skill of a distributed hydrological model by calibration on spatial patterns with multiple satellite datasets, Water Resour. Res., 56, e2019WR026085, https://doi.org/10.1029/2019WR026085, 2020.
Di Baldassarre, G. and Claps, P.: A hydraulic study on the applicability of flood rating curves, Hydrol. Res., 42, 10–19, https://doi.org/10.2166/nh.2010.098, 2011.
Di Baldassarre, G. and Montanari, A.: Uncertainty in river discharge observations: a quantitative analysis, Hydrol. Earth Syst. Sci., 13, 913–921, https://doi.org/10.5194/hess-13-913-2009, 2009.
Di Muzio, E., Riemer, M., Fink, A. H., and Maier-Gerber, M.: Assessing the predictability of Medicanes in ECMWF ensemble forecasts using an object-based approach, Q. J. Roy. Meteorol. Soc., 145, 1202–1217, 2019.
Dinku, T., Ceccato, P., Grover-Kopec, E., Lemma, M., Connor, S. J., and Ropelewski, C. F.: Validation of satellite rainfall products over East Africa's complex topography, Int. J. Remote Sens., 28, 1503–1526, 2007.
Duque-Gardeazábal, N., Zamora, D., and Erasmo Rodríguez, E.: Analysis of the kernel bandwidth influence in the double smoothing merging algorithm to improve rainfall fields in poorly gauged basins. HIC 2018: 13th Int. Conf. on Hydroinformatics, vol. 3., 635–626, https://doi.org/10.29007/2xp6, 2018.
Ebert, E. E., Janowiak, J. E., and Kidd, C.: Comparison of nearreal-time precipitation estimates from satellite observations and numerical models, B. Am. Meteorol. Soc., 88, 47–64, 2007.
European Space Agency: Copernicus Digital Elevation Model (DEM), AWS [data set], https://registry.opendata.aws/copernicus-dem (last access: 6 August 2024), 2021.
Falck, A. S., Tomasella, J., Diniz, F. L. R., and Maggioni, V.: Applying a precipitation error model to numerical weather predictions for probabilistic flood forecasts, J. Hydrol., 598, 126374, https://doi.org/10.1016/j.jhydrol.2021.126374, 2021.
Ferretti, R., Lombardi, A., Tomassetti, B., Sangelantoni, L., Colaiuda, V., Mazzarella, V., Maiello, I., Verdecchia, M., and Redaelli, G.: A meteorological–hydrological regional ensemble forecast for an early-warning system over small Apennine catchments in Central Italy, Hydrol. Earth Syst. Sci., 24, 3135–3156, https://doi.org/10.5194/hess-24-3135-2020, 2020.
French, M. N. and Krajewski, W. F.: A model for real-time quantitative rainfall forecasting using remote sensing: 1. Formulation, Water Resour. Res., 30, 1075–1083, 1994.
Gandin, L. S.: The Planning of Meteorological Station Networks, Technical Note No. 111, WMO No. 265, Geneva, 1970.
Gebremichael, M. and Krajewski, W. F.: Characterization of the temporal sampling error in space-time-averaged rainfall estimates from satellites, J. Geophys. Res., 109, D11110, https://doi.org/10.1029/2004JD004509, 2004.
Ghulami, M., Babel, M. S., and Shrestha, M. S.: Evaluation of gridded precipitation datasets for the Kabul Basin, Afghanistan, Int. J. Remote Sens., 38, 3317–3332, 2017.
Goodrich, D. C., Lane, L. J., Shillito, R. M., Miller, S. N., Syed, K. H., and Woolhiser, D. A.: Linearity of basin response as a function of scale in a semiarid watershed, Water Resour. Res., 33, 2951–2965, https://doi.org/10.1029/97WR01422, 1997.
Guetter, A. K., Georgakakos, K. P., and Tsonis, A. A.: Hydrologic applications of satellite data: 2. Flow simulation and soil water estimates, J. Geophys. Res.-Atmos., 101, 26527–26538, 1996.
Guo, J., Su, T., Li, Z., Miao, Y., Li, J., Liu, H., Xu, H., Cribb, M., and Zhai, P.: Declining frequency of summertime local-scale precipitation over eastern China from 1970–2010 and its potential link to aerosols, Geophys. Res. Lett., 44, 5700–5708, 2017.
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.
Hallouin, T.: HydroEval: Streamflow Simulations Evaluator (Version 0.0.3), Zenodo [code], https://doi.org/10.5281/zenodo.2591217, 2019.
Hersbach, H., Bell, B., Berrisford, P., Biavati, G., Horányi, A., Muñoz Sabater, J., Nicolas, J., Peubey, C., Radu, R., Rozum, I., Schepers, D., Simmons, A., Soci, C., Dee, D., and Thépaut, J.-N.: ERA5 hourly data on single levels from 1940 to present, Copernicus Climate Change Service (C3S) Climate Data Store (CDS) [data set], https://doi.org/10.24381/cds.adbb2d47, 2023.
Hirpa, F. A., Gebremichael, M., and Hopson, T.: Evaluation of high-resolution satellite precipitation products over very complex terrain in Ethiopia, J. Appl. Meteorol. Climatol., 49, 1044–1051, 2010.
Hong, Y., Hsu, K.-L., Moradkhani, H., and Sorooshian, S.: Uncertainty quantification of satellite precipitation estimation and Monte Carlo assessment of the error propagation into hydrologic response, Water Resour. Res., 42, W08421, https://doi.org/10.1029/2005WR004398, 2006.
Hong, Y., Gochis, D., Cheng, J., Hsu, K., and Sorooshian, S.: Evaluation of PERSIANN-CCS Rainfall Measurement Using the NAME Event Rain Gauge Network, J. Hydrometeorol., 8, 469–482, https://doi.org/10.1175/JHM574.1, 2007.
Hossain, F. and Anagnostou, E. N.: Numerical investigation of the impact of uncertainties in satellite rainfall estimation and land surface model parameters on simulation of soil moisture, Adv. Water Resour., 28, 1336–1350, 2005.
Hossain, F. and Anagnostou, E. N.: A two-dimensional satellite rainfall error model, IEEE T. Geosci. Remote, 44, 1511–1522, https://doi.org/10.1109/TGRS.2005.863866, 2006.
Huffman, G. J., Bolvin, D., Braithwaite, D., Hsu, K.-L., Joyce, R., Kidd, C., Nelkin, E., Sorooshian, S., Tan, J., and Xie, P.: Integrated Multi-Satellite Retrievals for GPM (IMERG) Technical Documentation, NASA/GSFC, Greenbelt, MD, USA, https://gpm.nasa.gov/sites/default/files/202307/IMERG_TechnicalDocumentation_final_230713.pdf (last access: 6 August 2024),, 2018.
Hughes, D. A.: Comparison of satellite rainfall data with observations from gauging station networks, J. Hydrol., 327, 399–410, 2006.
Italian Civil Protection Department, CIMA Research Foundation: The Dewetra Platform: A Multi-perspective Architecture for Risk Management during Emergencies, in: Information Systems for Crisis Response and Management in Mediterranean Countries, edited by: Hanachi, C., Bénaben, F., and Charoy, F., ISCRAM-med 2014, Lecture Notes in Business Information Processing, vol 196, Springer, Cham, https://doi.org/10.1007/978-3-319-11818-5_15, 2014.
Jiang, D. and Wang, K.: The Role of Satellite-Based Remote Sensing in Improving Simulated Streamflow: A Review, Water, 11, 1615, https://doi.org/10.3390/w11081615, 2019.
Keogh, E. J. and Pazzani, M.: Derivative Dynamic Time Warping, Proceedings of the 2001 SIAM International Conference on Data Mining (SDM), pp. 1–11, ISBN 978-0-89871-495-1, 2001, https://doi.org/10.1137/1.9781611972719.1, 2001.
Keogh, E. J. and Ratanamahatana, C. A.: Exact indexing of dynamic time warping, Knowl. Inform. Syst., 7, 358–386, https://doi.org/10.1007/s10115-004-0154-9, 2005.
Kidd, C. and Levizzani, V.: Status of satellite precipitation retrievals, Hydrol. Earth Syst. Sci., 15, 1109–1116, https://doi.org/10.5194/hess-15-1109-2011, 2011.
Kirstetter P. E., Viltard N., and Gosset M.: An error model for instantaneous satellite rainfall estimates: evaluation of BRAIN-TMI over West Africa, Q. J. Roy. Meteor. Soc., 139, 894–911, https://doi.org/10.1002/qj.1964, 2013.
Kling, H., Fuchs, M., and Paulin, M.: Runoff conditions in the upper Danube basin under an ensemble of climate change scenarios, J. Hydrol., 424–425, 264–277, https://doi.org/10.1016/j.jhydrol.2012.01.011, 2012.
Kubota, T., Ushio, T., Shige, S., Kida, S., Kachi, M., and Okamoto, K.: Verification of high-resolution satellite-based rainfall estimates around Japan using gauge-calibrated ground radar dataset, J. Meteor. Soc. Japan, 87A, 203–222, https://doi.org/10.2151/jmsj.87A.203, 2009.
Lehner, B., Verdin, K., and Jarvis, A.: New global hydrography derived from spaceborne elevation data, Eos, Transactions, American Geophysical Union, 89, 93–94, https://doi.org/10.1029/2008eo100001, 2008 (data available at: https://www.hydrosheds.org/, last access: 7 August 2024).
Li, M. and Shao, Q.: An improved statistical approach to merge satellite rainfall estimates and raingauge data, J. Hydrol., 385, 51–64, https://doi.org/10.1016/j.jhydrol.2010.01.023, 2010.
Li, X., Chen, Y., Deng, X., Zhang, Y., and Chen, L.: Evaluation and Hydrological Utility of the GPM IMERG Precipitation Products over the Xinfengjiang River Reservoir Basin, China, Remote Sens., 13, 866, https://doi.org/10.3390/rs13050866, 2021.
Liang, S., Li, X., and Wang, J.: Advanced Remote Sensing, Academic Press, 533–556, ISBN 9780123859549, https://doi.org/10.1016/B978-0-12-385954-9.00017-4, 2012.
Lombardi, A., Colaiuda, V., Verdecchia, M., and Tomassetti, B.: User-oriented hydrological indices for early warning systems with validation using post-event surveys: flood case studies in the Central Apennine District, Hydrol. Earth Syst. Sci., 25, 1969–1992, https://doi.org/10.5194/hess-25-1969-2021, 2021.
Luino, F.: Flooding vulnerability of a town in the Tanaro basin: the case of Ceva (Piedmont-northwest Italy), Workshop, Barcelona, vol. 16, no. 19, 2002.
Maggioni, V. and Massari, C.: On the performance of satellite precipitation products in riverine flood modeling: A review, J. Hydrol., 558, 214–224, https://doi.org/10.1016/j.jhydrol.2018.01.039, 2018.
Maggioni, V. and Massari, C. (Eds.): Extreme Hydroclimatic Events and Multivariate Hazards in a Changing Environment A Remote Sensing Approach, in: 1st Edn., Elsevier, Inc., Cambridge, MA, ISBN 9780128148990, 2019.
Maggioni, V., Reichle, R. H., and Anagnostou, E. N.: The Effect of Satellite Rainfall Error Modeling on Soil Moisture Prediction Uncertainty, J. Hydrometeorol., 12, 413–428, 2011.
Maggioni, V., Sapiano, M. R. P., Adler, R. F., Tian, Y., and Huffman, G. J.: An Error Model for Uncertainty Quantification in High-Time-Resolution Precipitation Products, J. Hydrometeorol., 15, 1274–1292, 2014.
Maggioni, V. and Massari, C. (Eds.): Extreme Hydroclimatic Events and Multivariate Hazards in a Changing Environment. A Remote Sensing Approach, 1st edn., Elsevier, Inc., Cambridge, MA, ISBN 9780128148990, 2019.
Maier-Gerber, M., Riemer, M., Fink, A. H., Knippertz, P., Di Muzio, E., and McTaggart-Cowan, R.: Tropical transition of Hurricane Chris (2012) over the North Atlantic Ocean: a multiscale investigation of predictability, Mon. Weather Rev., 147, 951–970, https://doi.org/10.1175/MWR-D-18-0188.1, 2019.
Marchi, E., Roth, G., and Siccardi, F.: The November 1994 flood event on the Po River: structural and non-structural measures against inundations, Workshop on hydrometeorology, impacts, and Management of Extreme Floods, Perugia, Italy, 1995.
Mathevet, T., Michel, C., Andreassian, V., and Perrin, C.: A bounded version of the Nash–Sutcliffe criterion for better model assessment on large sets of basins, in: Large Sample Basin Experiment for Hydrological Model Parameterization: Results of the Model Parameter Experiment – MOPEX, edited by: Andréassian, V., Hall, A., Chahinian, N., and Schaake, J., IAHS Publ., 30 p. 567, https://www.researchgate.net/profile/Thibault-Mathevet/publication/282319260_A_bounded_version_of_the_ Nash-Sutcliffe_criterion_for_better_model_assessment_on_large_ sets_of_basins/links/62de9581aa5823729ee0b9dd/A-bounded-version-of-the-Nash-Sutcliffe-criterion-for-better-model-assessment-on-large-sets-of-basins.pdf (last access: 7 August 2024), 2006.
McCollum, J. R., Krajewski, W. F., Ferraro, R. R., and Ba, M. B.: Evaluation of biases of satellite rainfall estimation algorithms over the continental United States, J. Appl. Meteorol., 41, 1065–1080. 2002.
Mei, Y., Nikolopoulos, E. I., Anagnostou, E. N., and Borga, M.: Evaluating Satellite Precipitation Error Propagation in Runoff Simulations of Mountainous Basins, J. Hydrometeorol., 17, 1407–1423, 2016.
Mei, Y., Anagnostou, E., Shen, X., and Nikolopoulos, E.: Decomposing the Satellite Precipitation Error Propagation through the Rainfall-Runoff Processes, Adv. Water Resour., 109, 253–266, https://doi.org/10.1016/j.advwatres.2017.09.012, 2017.
Nash, J. E. and Sutcliffe, J. V.: River flow forecasting through conceptual modelspart I – A discussion of principles, J. Hydrol., 10, 282–290, 1970.
Nemec, J.: Examples of design of HFS in WMO-assisted projects, in: Hydrological Forecasting, Water Science and Technology Library, 5, Springer, Dordrecht, https://doi.org/10.1007/978-94-009-4680-4_6, 1986.
Nijssen, B. and Lettenmaier, D. P.: Effect of precipitation sampling error on simulated hydrological fluxes and states: Anticipating the Global Precipitation Measurement satellites, J. Geophys. Res., 109, D02103, https://doi.org/10.1029/2003JD003497, 2004.
Nikolopoulos, E. I., Anagnostou, E. N., Hossain, F., Gebremichael, M., and Borga, M.: Understanding the scale relationships of uncertainty propagation of satellite rainfall through a distributed hydrologic model, J. Hydrometeorol., 11, 520–532, https://doi.org/10.1175/2009JHM1169.1, 2010.
O, S., Foelsche, U., Kirchengast, G., Fuchsberger, J., Tan, J., and Petersen, W. A.: Evaluation of GPM IMERG Early, Late, and Final rainfall estimates using WegenerNet gauge data in southeastern Austria, Hydrol. Earth Syst. Sci., 21, 6559–6572, https://doi.org/10.5194/hess-21-6559-2017, 2017.
Packard, N. H. and Wolfram, S.: Two-dimensional cellular automata, J. Stat. Phys., 38, 901–946, 1985.
Po River Basin Authority: Linee Generali Di Assetto Idrogeologico E Quadro Degli Interventi, Bacino del Tanaro, http://www.adbpo.it/PAI/3 - Linee generali di assetto idraulico e idrogeologico/3.3 - Elaborato Piemonte/Tanaro.pdf (last access: 14 June 2023), 2023.
Pool, S., Vis, M., and Seibert, J.: Evaluating model performance: towards a non-parametric variant of the Kling–Gupta efficiency, Hydrolog. Sci. J., 63, 1941–1953, https://doi.org/10.1080/02626667.2018.1552002, 2018.
Rabiner, L. R. and Gold, B.: Theory and Application of Digital Signal Processing, Prentice-Hall, Englewood Cliffs, NJ, p. 401, ISBN 0139141014, 1975.
Rabiner, L. R. and Schafer, R. W.: Digital Processing of Speech Signals, in: Signal Processing Series, Prentice Hall, Upper Saddle River, NJ, 147–148, ISBN 0132136031, 1978.
Sakoe, H. and Chiba, S.: Dynamic programming algorithm optimization for spoken word recognition. IEEE Transactions on Acoustics, Speech, and Signal Processing, 26, 43–49, https://doi.org/10.1109/TASSP.1978.1163055, 1978.
Sangelantoni, L., Tomassetti, B., Colaiuda, V., Lombardi, A., Verdecchia, M., Ferretti, R., and Redaelli, G.: On the Use of Original and Bias-Corrected Climate Simulations in Regional-Scale Hydrological Scenarios in the Mediterranean Basin, Atmosphere, 10, 799, https://doi.org/10.3390/atmos10120799, 2019.
Saouabe, T., El Khalki, E. M., Saidi, M. E. M., Najmi, A., Hadri, A., Rachidi, S., Jadoud, M., and Tramblay, Y.: Evaluation of the GPM-IMERG Precipitation Product for Flood Modeling in a Semi-Arid Mountainous Basin in Morocco, Water, 12, 2516, https://doi.org/10.3390/w12092516, 2020.
Sevruk, B.: Snow cover measurements and areal assessment of precipitation and soil moisture, Operational Hydrology Report, 35, Publ. 749, World Meteorological Organisation, Geneva, 91 pp., https://www.cabidigitallibrary.org/doi/full/10.5555/19941904049 (last access: 7 August 2024), 1992.
Shi, H., Chen, J., Li, T., and Wang, G.: A new method for estimation of spatially distributed rainfall through merging satellite observations, raingauge records, and terrain digital elevation model data, J. Hydro-Environ. Res., 28, 1–14, https://doi.org/10.1016/j.jher.2017.10.006; 2020.
Singh, P. and Kumar, N.: Impact assessment of climate change on the hydrological response of a snow and glacier melt runoff dominated Himalayan River, J. Hydrol., 193, 316–350, https://doi.org/10.1016/S0022-1694(96)03142-3, 1997.
Solakian, J., Maggioni, V., and Godrej, A.: Investigating the Error Propagation from Satellite-Based Input Precipitation to Output Water Quality Indicators Simulated by a Hydrologic Model, Remote Sens., 12, 3728, https://doi.org/10.3390/rs12223728, 2020.
Su, F., Hong, Y., and Lettenmaier, D. P.: Evaluation of TRMM multisatellite precipitation analysis (TMPA) and its utility in hydrologic prediction in the La Plata Basin, J. Hydrometeorol., 9, 622–640, 2008.
Thiemig, V., Rojas, R., Zambrano-Bigiarini, M., and De Roo, A.: Hydrological evaluation of satellite-based rainfall estimates over the Volta and Baro-Akobo Basin, J. Hydrol., 499, 324–338, https://doi.org/10.1016/j.jhydrol.2013.07.012, 2013.
Tian, Y. and Peters-Lidard, C. D.: A global map of uncertainties in satellite-based precipitation measurements, Geophys. Res. Lett., 37, L24407, https://doi.org/10.1029/2010GL046008, 2010.
Todini, E.: Influence of parameter estimation uncertainty in Kriging: Part 1 – Theoretical Development, Hydrol. Earth Syst. Sci., 5, 215–223, https://doi.org/10.5194/hess-5-215-2001, 2001.
Tomassetti, B., Coppola, E., Verdecchia, M., and Visconti, G.: Coupling a distributed grid based hydrological model and MM5 meteorological model for flooding alert mapping, Adv. Geosci., 2, 59–63, https://doi.org/10.5194/adgeo-2-59-2005, 2005.
Tramblay, Y., El Mahdi, E. K., Ciabatta, L., Camici, S., Hanich, L., El Mehdi Saidi, M., Ezzahouani, M., Benaabidate, L., Mahé, G., and Brocca, L.: River runoff estimation with satellite rainfall in Morocco, Hydrol. Sci. J., 68, 474–487, https://doi.org/10.1080/02626667.2023.2171295, 2023.
Tsintikidis, D., Georgakakos, K. P., Artan, G. A., Tsonis, A. A.: A feasibility study on mean areal rainfall estimation and hydrologic response in the Blue Nile region using METEOSAT images, J. Hydrol., 221, 97–116, https://doi.org/10.1016/S0022-1694(99)00071-2, 1999.
Verdecchia, M., Coppola, E., Tomassetti, B., and Visconti, G.: Cetemps Hydrological Model (CHyM), a Distributed Grid-Based Model Assimilating Different Rainfall Data Sources, in: Hydrological Modelling and the Water Cycle, edited by: Sorooshian, S., Hsu, K. L., Coppola, E., Tomassetti, B., Verdecchia, M., and Visconti, G., Water Sci. Technol. Library, vol 63, 165–201, Springer, Berlin, Heidelberg, https://doi.org/10.1007/978-3-540-77843-1_8, 2008
Wilk, J., Kniveton, D., Andersson, L., Layberry, R., Todd, M. C., Hughes, D., Ringrose, S., and Vanderpost, C.: Estimating rainfall and water balance over the Okavango River Basin for hydrological applications, J. Hydrol., 331, 18–29, https://doi.org/10.1016/j.jhydrol.2006.04.049, 2006.
WMO: Guide to Hydrological Practices, 5th edn., WMO no. 168, World Meteorological Organization, Geneva, Switzerland, ISBN 9789263151681, 1994.
Xu, H., Xu, C. Y., Chen, H., Zhang, Z., and Li, L.: Assessing theinfluence of rain gauge density and distribution on hydrologicalmodel performance in a humid region of China, J. Hydrol., 505, 1–12, 2013.
Yong, B., Ren, L. L., Hong, Y., Wang, J. H., Gourley, J. J.,Jiang, S. H., Chen, X., and Wang, W.: Hydrologic evaluation of Multisatellite Precipitation Analysis standard precipitation products in basins beyond its inclined latitude band: A case study in Laohahe basin, China, Water Resour. Res., 46, W07542, https://doi.org/10.1029/2009wr008965, 2010.
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.
The accurate estimation of precipitation and its spatial variability within a watershed is...
