Articles | Volume 26, issue 3
https://doi.org/10.5194/nhess-26-1075-2026
© Author(s) 2026. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/nhess-26-1075-2026
© Author(s) 2026. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
04 Mar 2026
Research article |
| 04 Mar 2026
| 04 Mar 2026
Harnessing multi-source hydro-meteorological data for high flows modelling in a partially glacierized Himalayan basin
Domenico De Santis
CORRESPONDING AUTHOR
Research Institute for Geo-Hydrological Protection, National Research Council, Rende, 87036, Italy
Silvia Barbetta
Research Institute for Geo-Hydrological Protection, National Research Council, Perugia, 06128, Italy
Sumit Sen
Department of Hydrology, Indian Institute of Technology Roorkee, Roorkee-247667, Uttarakhand, India
Viviana Maggioni
Department of Civil, Environmental & Infrastructure Engineering, George Mason University, Fairfax, VA 22030, USA
Farhad Bahmanpouri
Research Institute for Geo-Hydrological Protection, National Research Council, Perugia, 06128, Italy
Ashutosh Sharma
Department of Hydrology, Indian Institute of Technology Roorkee, Roorkee-247667, Uttarakhand, India
Ankit Agarwal
Department of Hydrology, Indian Institute of Technology Roorkee, Roorkee-247667, Uttarakhand, India
GFZ Helmholtz Centre for Geosciences, Section Hydrology, Potsdam, 14473, Germany
Sagar Gupta
Department of Hydrology, Indian Institute of Technology Roorkee, Roorkee-247667, Uttarakhand, India
Francesco Avanzi
CIMA Research Foundation, Savona, 17100, Italy
Christian Massari
Research Institute for Geo-Hydrological Protection, National Research Council, Perugia, 06128, Italy
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Louise Busschaert, Michel Bechtold, Sara Modanesi, Christian Massari, Dirk Raes, Sujay V. Kumar, and Gabrielle J. M. De Lannoy
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Wolfgang Schwanghart, Ankit Agarwal, Kristen Cook, Ugur Ozturk, Roopam Shukla, and Sven Fuchs
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Hydrol. Earth Syst. Sci., 28, 441–457, https://doi.org/10.5194/hess-28-441-2024, https://doi.org/10.5194/hess-28-441-2024, 2024
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Francesca Munerol, Francesco Avanzi, Eleonora Panizza, Marco Altamura, Simone Gabellani, Lara Polo, Marina Mantini, Barbara Alessandri, and Luca Ferraris
Geosci. Commun., 7, 1–15, https://doi.org/10.5194/gc-7-1-2024, https://doi.org/10.5194/gc-7-1-2024, 2024
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Shima Azimi, Christian Massari, Giuseppe Formetta, Silvia Barbetta, Alberto Tazioli, Davide Fronzi, Sara Modanesi, Angelica Tarpanelli, and Riccardo Rigon
Hydrol. Earth Syst. Sci., 27, 4485–4503, https://doi.org/10.5194/hess-27-4485-2023, https://doi.org/10.5194/hess-27-4485-2023, 2023
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Giulia Blandini, Francesco Avanzi, Simone Gabellani, Denise Ponziani, Hervé Stevenin, Sara Ratto, Luca Ferraris, and Alberto Viglione
The Cryosphere, 17, 5317–5333, https://doi.org/10.5194/tc-17-5317-2023, https://doi.org/10.5194/tc-17-5317-2023, 2023
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Automatic snow depth data are a valuable source of information for hydrologists, but they also tend to be noisy. To maximize the value of these measurements for real-world applications, we developed an automatic procedure to differentiate snow cover from grass or bare ground data, as well as to detect random errors. This procedure can enhance snow data quality, thus providing more reliable data for snow models.
Adam Pasik, Alexander Gruber, Wolfgang Preimesberger, Domenico De Santis, and Wouter Dorigo
Geosci. Model Dev., 16, 4957–4976, https://doi.org/10.5194/gmd-16-4957-2023, https://doi.org/10.5194/gmd-16-4957-2023, 2023
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We apply the exponential filter (EF) method to satellite soil moisture retrievals to estimate the water content in the unobserved root zone globally from 2002–2020. Quality assessment against an independent dataset shows satisfactory results. Error characterization is carried out using the standard uncertainty propagation law and empirically estimated values of EF model structural uncertainty and parameter uncertainty. This is followed by analysis of temporal uncertainty variations.
Joel Z. Harms, Julien J. Malard-Adam, Jan F. Adamowski, Ashutosh Sharma, and Albert Nkwasa
Hydrol. Earth Syst. Sci., 27, 1683–1693, https://doi.org/10.5194/hess-27-1683-2023, https://doi.org/10.5194/hess-27-1683-2023, 2023
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Jacopo Dari, Luca Brocca, Sara Modanesi, Christian Massari, Angelica Tarpanelli, Silvia Barbetta, Raphael Quast, Mariette Vreugdenhil, Vahid Freeman, Anaïs Barella-Ortiz, Pere Quintana-Seguí, David Bretreger, and Espen Volden
Earth Syst. Sci. Data, 15, 1555–1575, https://doi.org/10.5194/essd-15-1555-2023, https://doi.org/10.5194/essd-15-1555-2023, 2023
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Irrigation is the main source of global freshwater consumption. Despite this, a detailed knowledge of irrigation dynamics (i.e., timing, extent of irrigated areas, and amounts of water used) are generally lacking worldwide. Satellites represent a useful tool to fill this knowledge gap and monitor irrigation water from space. In this study, three regional-scale and high-resolution (1 and 6 km) products of irrigation amounts estimated by inverting the satellite soil moisture signals are presented.
Tahmina Yasmin, Kieran Khamis, Anthony Ross, Subir Sen, Anita Sharma, Debashish Sen, Sumit Sen, Wouter Buytaert, and David M. Hannah
Nat. Hazards Earth Syst. Sci., 23, 667–674, https://doi.org/10.5194/nhess-23-667-2023, https://doi.org/10.5194/nhess-23-667-2023, 2023
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Floods continue to be a wicked problem that require developing early warning systems with plausible assumptions of risk behaviour, with more targeted conversations with the community at risk. Through this paper we advocate the use of a SMART approach to encourage bottom-up initiatives to develop inclusive and purposeful early warning systems that benefit the community at risk by engaging them at every step of the way along with including other stakeholders at multiple scales of operations.
Francesco Avanzi, Simone Gabellani, Fabio Delogu, Francesco Silvestro, Flavio Pignone, Giulia Bruno, Luca Pulvirenti, Giuseppe Squicciarino, Elisabetta Fiori, Lauro Rossi, Silvia Puca, Alexander Toniazzo, Pietro Giordano, Marco Falzacappa, Sara Ratto, Hervè Stevenin, Antonio Cardillo, Matteo Fioletti, Orietta Cazzuli, Edoardo Cremonese, Umberto Morra di Cella, and Luca Ferraris
Earth Syst. Sci. Data, 15, 639–660, https://doi.org/10.5194/essd-15-639-2023, https://doi.org/10.5194/essd-15-639-2023, 2023
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Snow cover has profound implications for worldwide water supply and security, but knowledge of its amount and distribution across the landscape is still elusive. We present IT-SNOW, a reanalysis comprising daily maps of snow amount and distribution across Italy for 11 snow seasons from September 2010 to August 2021. The reanalysis was validated using satellite images and snow measurements and will provide highly needed data to manage snow water resources in a warming climate.
Giulia Bruno, Doris Duethmann, Francesco Avanzi, Lorenzo Alfieri, Andrea Libertino, and Simone Gabellani
Hydrol. Earth Syst. Sci. Discuss., https://doi.org/10.5194/hess-2022-416, https://doi.org/10.5194/hess-2022-416, 2022
Manuscript not accepted for further review
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Hydrological models often have issues during droughts. We used the distributed Continuum model over the Po river basin and independent datasets of streamflow (Q), evapotranspiration (ET), and storage. Continuum simulated Q well during wet years and moderate droughts. Performances declined for a severe drought and we explained this drop with an increased uncertainty in ET anomalies in human-affected croplands. These findings provide guidelines for assessments of model robustness during droughts.
Riccardo Rigon, Giuseppe Formetta, Marialaura Bancheri, Niccolò Tubini, Concetta D'Amato, Olaf David, and Christian Massari
Hydrol. Earth Syst. Sci., 26, 4773–4800, https://doi.org/10.5194/hess-26-4773-2022, https://doi.org/10.5194/hess-26-4773-2022, 2022
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The
Digital Earth(DE) metaphor is very useful for both end users and hydrological modelers. We analyse different categories of models, with the view of making them part of a Digital eARth Twin Hydrology system (called DARTH). We also stress the idea that DARTHs are not models in and of themselves, rather they need to be built on an appropriate information technology infrastructure. It is remarked that DARTHs have to, by construction, support the open-science movement and its ideas.
Sara Modanesi, Christian Massari, Michel Bechtold, Hans Lievens, Angelica Tarpanelli, Luca Brocca, Luca Zappa, and Gabriëlle J. M. De Lannoy
Hydrol. Earth Syst. Sci., 26, 4685–4706, https://doi.org/10.5194/hess-26-4685-2022, https://doi.org/10.5194/hess-26-4685-2022, 2022
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Given the crucial impact of irrigation practices on the water cycle, this study aims at estimating irrigation through the development of an innovative data assimilation system able to ingest high-resolution Sentinel-1 radar observations into the Noah-MP land surface model. The developed methodology has important implications for global water resource management and the comprehension of human impacts on the water cycle and identifies main challenges and outlooks for future research.
Stefania Camici, Gabriele Giuliani, Luca Brocca, Christian Massari, Angelica Tarpanelli, Hassan Hashemi Farahani, Nico Sneeuw, Marco Restano, and Jérôme Benveniste
Geosci. Model Dev., 15, 6935–6956, https://doi.org/10.5194/gmd-15-6935-2022, https://doi.org/10.5194/gmd-15-6935-2022, 2022
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This paper presents an innovative approach, STREAM (SaTellite-based Runoff Evaluation And Mapping), to derive daily river discharge and runoff estimates from satellite observations of soil moisture, precipitation, and terrestrial total water storage anomalies. Potentially useful for multiple operational and scientific applications, the added value of the STREAM approach is the ability to increase knowledge on the natural processes, human activities, and their interactions on the land.
Ravi Kumar Meena, Sumit Sen, Aliva Nanda, Bhargabnanda Dass, and Anurag Mishra
Hydrol. Earth Syst. Sci., 26, 4379–4390, https://doi.org/10.5194/hess-26-4379-2022, https://doi.org/10.5194/hess-26-4379-2022, 2022
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We developed a mobile operated programmable rainfall simulator (RS) to simulate the near-natural moving storm rainfall condition and to study its impact on runoff, soil erosion, and nutrient transport. The designed RS can be used for variable velocity and slope conditions along with the three different soil types at a time. Moreover, the soil flume of the RS is associated with the surface, subsurface, and base flow components.
Lorenzo Alfieri, Francesco Avanzi, Fabio Delogu, Simone Gabellani, Giulia Bruno, Lorenzo Campo, Andrea Libertino, Christian Massari, Angelica Tarpanelli, Dominik Rains, Diego G. Miralles, Raphael Quast, Mariette Vreugdenhil, Huan Wu, and Luca Brocca
Hydrol. Earth Syst. Sci., 26, 3921–3939, https://doi.org/10.5194/hess-26-3921-2022, https://doi.org/10.5194/hess-26-3921-2022, 2022
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This work shows advances in high-resolution satellite data for hydrology. We performed hydrological simulations for the Po River basin using various satellite products, including precipitation, evaporation, soil moisture, and snow depth. Evaporation and snow depth improved a simulation based on high-quality ground observations. Interestingly, a model calibration relying on satellite data skillfully reproduces observed discharges, paving the way to satellite-driven hydrological applications.
Abhishek Kashyap, Mukunda Dev Behera, Anand Kumar Pandey, and Ankit Agarwal
EGUsphere, https://doi.org/10.5194/egusphere-2022-533, https://doi.org/10.5194/egusphere-2022-533, 2022
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Bedrock landslides are currently spatially dispersed over a process of landscape evolution in the NW Himalayan river catchments. Our analysis indicates that the zones with slope range between 24–32°, topographic relief ranges between 800–1200 m, and elevation range between 1200–2400 m, are compatible with precipitation intensity ranges between 1500–3000 mm/year in the NW Himalayan river catchments, have the highest probability of frequently occurring landslides.
Francesco Avanzi, Simone Gabellani, Fabio Delogu, Francesco Silvestro, Edoardo Cremonese, Umberto Morra di Cella, Sara Ratto, and Hervé Stevenin
Geosci. Model Dev., 15, 4853–4879, https://doi.org/10.5194/gmd-15-4853-2022, https://doi.org/10.5194/gmd-15-4853-2022, 2022
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Knowing in real time how much snow and glacier ice has accumulated across the landscape has significant implications for water-resource management and flood control. This paper presents a computer model – S3M – allowing scientists and decision makers to predict snow and ice accumulation during winter and the subsequent melt during spring and summer. S3M has been employed for real-world flood forecasting since the early 2000s but is here being made open source for the first time.
Pankaj R. Dhote, Joshal K. Bansal, Vaibhav Garg, Praveen K. Thakur, and Ankit Agarwal
Nat. Hazards Earth Syst. Sci. Discuss., https://doi.org/10.5194/nhess-2022-101, https://doi.org/10.5194/nhess-2022-101, 2022
Preprint withdrawn
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In the present paper, we have developed framework to establish virtual stage-discharge gauging network in sparsely gauged basin using hydrodynamic modelling and satellite altimetry data. The publication of the work will provide more insights to hydraulic community dealing with flood hazard in sparsely gauged basins, on how to monitor extreme river flow events using remote sensing data at ungauged locations.
Christian Massari, Francesco Avanzi, Giulia Bruno, Simone Gabellani, Daniele Penna, and Stefania Camici
Hydrol. Earth Syst. Sci., 26, 1527–1543, https://doi.org/10.5194/hess-26-1527-2022, https://doi.org/10.5194/hess-26-1527-2022, 2022
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Droughts are a creeping disaster, meaning that their onset, duration and recovery are challenging to monitor and forecast. Here, we provide further evidence of an additional challenge of droughts, i.e. the fact that the deficit in water supply during droughts is generally much more than expected based on the observed decline in precipitation. At a European scale we explain this with enhanced evapotranspiration, sustained by higher atmospheric demand for moisture during such dry periods.
Tessa Maurer, Francesco Avanzi, Steven D. Glaser, and Roger C. Bales
Hydrol. Earth Syst. Sci., 26, 589–607, https://doi.org/10.5194/hess-26-589-2022, https://doi.org/10.5194/hess-26-589-2022, 2022
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Predicting how much water will end up in rivers is more difficult during droughts because the relationship between precipitation and streamflow can change in unexpected ways. We differentiate between changes that are predictable based on the weather patterns and those harder to predict because they depend on the land and vegetation of a particular region. This work helps clarify why models are less accurate during droughts and helps predict how much water will be available for human use.
Sara Modanesi, Christian Massari, Alexander Gruber, Hans Lievens, Angelica Tarpanelli, Renato Morbidelli, and Gabrielle J. M. De Lannoy
Hydrol. Earth Syst. Sci., 25, 6283–6307, https://doi.org/10.5194/hess-25-6283-2021, https://doi.org/10.5194/hess-25-6283-2021, 2021
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Worldwide, the amount of water used for agricultural purposes is rising and the quantification of irrigation is becoming a crucial topic. Land surface models are not able to correctly simulate irrigation. Remote sensing observations offer an opportunity to fill this gap as they are directly affected by irrigation. We equipped a land surface model with an observation operator able to transform Sentinel-1 backscatter observations into realistic vegetation and soil states via data assimilation.
Daniele Masseroni, Stefania Camici, Alessio Cislaghi, Giorgio Vacchiano, Christian Massari, and Luca Brocca
Hydrol. Earth Syst. Sci., 25, 5589–5601, https://doi.org/10.5194/hess-25-5589-2021, https://doi.org/10.5194/hess-25-5589-2021, 2021
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We evaluate 63 years of changes in annual streamflow volume across Europe, using a data set of more than 3000 stations, with a special focus on the Mediterranean basin. The results show decreasing (increasing) volumes in the southern (northern) regions. These trends are strongly consistent with the changes in temperature and precipitation.
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Short summary
A conceptual, semi-distributed hydrological model was tailored to simulate high flows in monsoon-dominated, glacier-influenced and flood-prone Himalayan basins. Multi-data calibration using satellite-based glacier mass loss and evapotranspiration estimates improved process realism in data-scarce environments. The proposed modelling approach captured key streamflow features despite significant input uncertainties, proving to be a useful tool for exploring the local hydrological response dynamics.
A conceptual, semi-distributed hydrological model was tailored to simulate high flows in...
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