Articles | Volume 15, issue 4
https://doi.org/10.5194/essd-15-1555-2023
© Author(s) 2023. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/essd-15-1555-2023
© Author(s) 2023. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Data description paper
| 
05 Apr 2023
Data description paper |
| 05 Apr 2023
| 05 Apr 2023
Regional data sets of high-resolution (1 and 6 km) irrigation estimates from space
Department of Civil and Environmental Engineering, University of Perugia,
Perugia, Italy
Research Institute for Geo-Hydrological Protection, National Research
Council, Perugia, Italy
Luca Brocca
Research Institute for Geo-Hydrological Protection, National Research
Council, Perugia, Italy
Sara Modanesi
Research Institute for Geo-Hydrological Protection, National Research
Council, Perugia, Italy
Christian Massari
Research Institute for Geo-Hydrological Protection, National Research
Council, Perugia, Italy
Angelica Tarpanelli
Research Institute for Geo-Hydrological Protection, National Research
Council, Perugia, Italy
Silvia Barbetta
Research Institute for Geo-Hydrological Protection, National Research
Council, Perugia, Italy
Raphael Quast
Department of Geodesy and Geoinformation, Research Unit Remote
Sensing, Vienna University of Technology (TU Wien), Vienna, Austria
Mariette Vreugdenhil
Department of Geodesy and Geoinformation, Research Unit Remote
Sensing, Vienna University of Technology (TU Wien), Vienna, Austria
Vahid Freeman
Earth Intelligence, Spire Global, 2763 Luxembourg, Luxembourg
Anaïs Barella-Ortiz
Observatori de l'Ebre (OE), Ramon Llull University – CSIC, 43520
Roquetes, Spain
Pere Quintana-Seguí
Observatori de l'Ebre (OE), Ramon Llull University – CSIC, 43520
Roquetes, Spain
David Bretreger
School of Engineering, The University of Newcastle, Callaghan, New
South Wales 2308, Australia
Espen Volden
European Space Agency, ESRIN, Frascati, Italy
Related authors
Jacopo Dari, Paolo Filippucci, and Luca Brocca
Hydrol. Earth Syst. Sci., 28, 2651–2659, https://doi.org/10.5194/hess-28-2651-2024, https://doi.org/10.5194/hess-28-2651-2024, 2024
Short summary
Short summary
We have developed the first operational system (10 d latency) for estimating irrigation water use from accessible satellite and reanalysis data. As a proof of concept, the method has been implemented over an irrigated area fed by the Kakhovka Reservoir, in Ukraine, which collapsed on June 6, 2023. Estimates for the period 2015–2023 reveal that, as expected, the irrigation season of 2023 was characterized by the lowest amounts of irrigation.
Søren Julsgaard Kragh, Jacopo Dari, Sara Modanesi, Christian Massari, Luca Brocca, Rasmus Fensholt, Simon Stisen, and Julian Koch
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
Short summary
Short summary
This study provides a comparison of methodologies to quantify irrigation to enhance regional irrigation estimates. To evaluate the methodologies, we compared various approaches to quantify irrigation using soil moisture, evapotranspiration, or both within a novel baseline framework, together with irrigation estimates from other studies. We show that the synergy from using two equally important components in a joint approach within a baseline framework yields better irrigation estimates.
Jaime Gaona, Davide Bavera, Guido Fioravanti, Sebastian Hahn, Pietro Stradiotti, Paolo Filippucci, Stefania Camici, Luca Ciabatta, Hamidreza Mosaffa, Silvia Puca, Nicoletta Roberto, and Luca Brocca
Hydrol. Earth Syst. Sci., 29, 3865–3888, https://doi.org/10.5194/hess-29-3865-2025, https://doi.org/10.5194/hess-29-3865-2025, 2025
Short summary
Short summary
Soil moisture is crucial for the water cycle since it is at the front line of drought. Satellite, model and in situ data help identify soil moisture stress but are challenged by data uncertainties. This study evaluates trends and data coherence of common active/passive microwave sensors and model-based soil moisture data against in situ stations across Europe from 2007 to 2022. Data reliability is increasing, but combining data types improves soil moisture monitoring capabilities.
Louise Busschaert, Michel Bechtold, Sara Modanesi, Christian Massari, Dirk Raes, Sujay V. Kumar, and Gabriëlle J. M. De Lannoy
EGUsphere, https://doi.org/10.5194/egusphere-2025-2550, https://doi.org/10.5194/egusphere-2025-2550, 2025
This preprint is open for discussion and under review for Hydrology and Earth System Sciences (HESS).
Short summary
Short summary
This study estimates irrigation in the Po Valley using AquaCrop and Noah-MP models with sprinkler irrigation. Noah-MP shows higher annual rates than AquaCrop due to more water losses. After adjusting, both align with reported irrigation ranges (500–600 mm/yr). Soil moisture estimates from both models match satellite data, though both have limitations in vegetation and evapotranspiration modeling. The study emphasizes the need for observations to improve irrigation estimates.
Paolo Filippucci, Luca Brocca, Luca Ciabatta, Hamidreza Mosaffa, Francesco Avanzi, and Christian Massari
Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2025-156, https://doi.org/10.5194/essd-2025-156, 2025
Revised manuscript accepted for ESSD
Short summary
Short summary
Accurate rainfall data is essential, yet measuring daily precipitation worldwide is challenging. This research presents HYdroclimatic PERformance-enhanced Precipitation (HYPER-P), a dataset combining satellite, ground, and reanalysis data to estimate precipitation at a 1 km scale from 2000 to 2023. HYPER-P improves accuracy, especially in areas with few rain gauges. This dataset supports scientists and decision-makers in understanding and managing water resources more effectively.
Wolfgang Knorr, Matthew Williams, Tea Thum, Thomas Kaminski, Michael Voßbeck, Marko Scholze, Tristan Quaife, T. Luke Smallman, Susan C. Steele-Dunne, Mariette Vreugdenhil, Tim Green, Sönke Zaehle, Mika Aurela, Alexandre Bouvet, Emanuel Bueechi, Wouter Dorigo, Tarek S. El-Madany, Mirco Migliavacca, Marika Honkanen, Yann H. Kerr, Anna Kontu, Juha Lemmetyinen, Hannakaisa Lindqvist, Arnaud Mialon, Tuuli Miinalainen, Gaétan Pique, Amanda Ojasalo, Shaun Quegan, Peter J. Rayner, Pablo Reyes-Muñoz, Nemesio Rodríguez-Fernández, Mike Schwank, Jochem Verrelst, Songyan Zhu, Dirk Schüttemeyer, and Matthias Drusch
Geosci. Model Dev., 18, 2137–2159, https://doi.org/10.5194/gmd-18-2137-2025, https://doi.org/10.5194/gmd-18-2137-2025, 2025
Short summary
Short summary
When it comes to climate change, the land surface is where the vast majority of impacts happen. The task of monitoring those impacts across the globe is formidable and must necessarily rely on satellites – at a significant cost: the measurements are only indirect and require comprehensive physical understanding. We have created a comprehensive modelling system that we offer to the research community to explore how satellite data can be better exploited to help us capture the changes that happen on our lands.
Ather Abbas, Yuan Yang, Ming Pan, Yves Tramblay, Chaopeng Shen, Haoyu Ji, Solomon H. Gebrechorkos, Florian Pappenberger, Jong Cheol Pyo, Dapeng Feng, George Huffman, Phu Nguyen, Christian Massari, Luca Brocca, Tan Jackson, and Hylke E. Beck
EGUsphere, https://doi.org/10.5194/egusphere-2024-4194, https://doi.org/10.5194/egusphere-2024-4194, 2025
Short summary
Short summary
Our study evaluated 23 precipitation datasets using a hydrological model at global scale to assess their suitability and accuracy. We found that MSWEP V2.8 excels due to its ability to integrate data from multiple sources, while others, such as IMERG and JRA-3Q, demonstrated strong regional performances. This research assists in selecting the appropriate dataset for applications in water resource management, hazard assessment, agriculture, and environmental monitoring.
Ling Zhang, Yanhua Xie, Xiufang Zhu, Qimin Ma, and Luca Brocca
Earth Syst. Sci. Data, 16, 5207–5226, https://doi.org/10.5194/essd-16-5207-2024, https://doi.org/10.5194/essd-16-5207-2024, 2024
Short summary
Short summary
This study presented new annual maps of irrigated cropland in China from 2000 to 2020 (CIrrMap250). These maps were developed by integrating remote sensing data, irrigation statistics and surveys, and an irrigation suitability map. CIrrMap250 achieved high accuracy and outperformed currently available products. The new irrigation maps revealed a clear expansion of China’s irrigation area, with the majority (61%) occurring in the water-unsustainable regions facing severe to extreme water stress.
Louise Busschaert, Michel Bechtold, Sara Modanesi, Christian Massari, Dirk Raes, Sujay V. Kumar, and Gabrielle J. M. De Lannoy
EGUsphere, https://doi.org/10.2139/ssrn.4974019, https://doi.org/10.2139/ssrn.4974019, 2024
Preprint archived
Short summary
Short summary
This study estimates irrigation in the Po Valley using AquaCrop and Noah-MP models with sprinkler irrigation. Noah-MP shows higher annual rates than AquaCrop due to more water losses. After adjusting, both align with reported irrigation ranges (500–600 mm/yr). Soil moisture estimates from both models match satellite data, though both have limitations in vegetation and evapotranspiration modeling. The study emphasizes the need for observations to improve irrigation estimates.
Ruxandra-Maria Zotta, Leander Moesinger, Robin van der Schalie, Mariette Vreugdenhil, Wolfgang Preimesberger, Thomas Frederikse, Richard de Jeu, and Wouter Dorigo
Earth Syst. Sci. Data, 16, 4573–4617, https://doi.org/10.5194/essd-16-4573-2024, https://doi.org/10.5194/essd-16-4573-2024, 2024
Short summary
Short summary
VODCA v2 is a dataset providing vegetation indicators for long-term ecosystem monitoring. VODCA v2 comprises two products: VODCA CXKu, spanning 34 years of observations (1987–2021), suitable for monitoring upper canopy dynamics, and VODCA L (2010–2021), for above-ground biomass monitoring. VODCA v2 has lower noise levels than the previous product version and provides valuable insights into plant water dynamics and biomass changes, even in areas where optical data are limited.
Farhad Bahmanpouri, Tommaso Lazzarin, Silvia Barbetta, Tommaso Moramarco, and Daniele P. Viero
Hydrol. Earth Syst. Sci., 28, 3717–3737, https://doi.org/10.5194/hess-28-3717-2024, https://doi.org/10.5194/hess-28-3717-2024, 2024
Short summary
Short summary
The entropy model is a reliable tool to estimate flood discharge in rivers using observed level and surface velocity. Often, level and velocity sensors are placed on bridges, which may disturb the flow. Using accurate numerical models, we explored the entropy model reliability nearby a multi-arch bridge. We found that it is better to place sensors and to estimate the discharge upstream of bridges; downstream, the entropy model needs the river-wide distribution of surface velocity as input data.
Pierre Laluet, Luis Olivera-Guerra, Víctor Altés, Vincent Rivalland, Alexis Jeantet, Julien Tournebize, Omar Cenobio-Cruz, Anaïs Barella-Ortiz, Pere Quintana-Seguí, Josep Maria Villar, and Olivier Merlin
Hydrol. Earth Syst. Sci., 28, 3695–3716, https://doi.org/10.5194/hess-28-3695-2024, https://doi.org/10.5194/hess-28-3695-2024, 2024
Short summary
Short summary
Monitoring agricultural drainage flow in irrigated areas is key to water and soil management. In this paper, four simple drainage models are evaluated on two irrigated sub-basins where drainage flow is measured daily. The evaluation of their precision shows that they simulate drainage very well when calibrated with drainage data and that one of them is slightly better. The evaluation of their accuracy shows that only one model can provide rough drainage estimates without calibration data.
Jacopo Dari, Paolo Filippucci, and Luca Brocca
Hydrol. Earth Syst. Sci., 28, 2651–2659, https://doi.org/10.5194/hess-28-2651-2024, https://doi.org/10.5194/hess-28-2651-2024, 2024
Short summary
Short summary
We have developed the first operational system (10 d latency) for estimating irrigation water use from accessible satellite and reanalysis data. As a proof of concept, the method has been implemented over an irrigated area fed by the Kakhovka Reservoir, in Ukraine, which collapsed on June 6, 2023. Estimates for the period 2015–2023 reveal that, as expected, the irrigation season of 2023 was characterized by the lowest amounts of irrigation.
Søren Julsgaard Kragh, Jacopo Dari, Sara Modanesi, Christian Massari, Luca Brocca, Rasmus Fensholt, Simon Stisen, and Julian Koch
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
Short summary
Short summary
This study provides a comparison of methodologies to quantify irrigation to enhance regional irrigation estimates. To evaluate the methodologies, we compared various approaches to quantify irrigation using soil moisture, evapotranspiration, or both within a novel baseline framework, together with irrigation estimates from other studies. We show that the synergy from using two equally important components in a joint approach within a baseline framework yields better irrigation estimates.
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
Short summary
Short summary
We analyzed the water budget of nested karst catchments using simple methods and modeling. By utilizing the available data on precipitation and discharge, we were able to determine the response lag-time by adopting new techniques. Additionally, we modeled snow cover dynamics and evapotranspiration with the use of Earth observations, providing a concise overview of the water budget for the basin and its subbasins. We have made the data, models, and workflows accessible for further study.
Heidi Kreibich, Kai Schröter, Giuliano Di Baldassarre, Anne F. Van Loon, Maurizio Mazzoleni, Guta Wakbulcho Abeshu, Svetlana Agafonova, Amir AghaKouchak, Hafzullah Aksoy, Camila Alvarez-Garreton, Blanca Aznar, Laila Balkhi, Marlies H. Barendrecht, Sylvain Biancamaria, Liduin Bos-Burgering, Chris Bradley, Yus Budiyono, Wouter Buytaert, Lucinda Capewell, Hayley Carlson, Yonca Cavus, Anaïs Couasnon, Gemma Coxon, Ioannis Daliakopoulos, Marleen C. de Ruiter, Claire Delus, Mathilde Erfurt, Giuseppe Esposito, Didier François, Frédéric Frappart, Jim Freer, Natalia Frolova, Animesh K. Gain, Manolis Grillakis, Jordi Oriol Grima, Diego A. Guzmán, Laurie S. Huning, Monica Ionita, Maxim Kharlamov, Dao Nguyen Khoi, Natalie Kieboom, Maria Kireeva, Aristeidis Koutroulis, Waldo Lavado-Casimiro, Hong-Yi Li, Maria Carmen LLasat, David Macdonald, Johanna Mård, Hannah Mathew-Richards, Andrew McKenzie, Alfonso Mejia, Eduardo Mario Mendiondo, Marjolein Mens, Shifteh Mobini, Guilherme Samprogna Mohor, Viorica Nagavciuc, Thanh Ngo-Duc, Huynh Thi Thao Nguyen, Pham Thi Thao Nhi, Olga Petrucci, Nguyen Hong Quan, Pere Quintana-Seguí, Saman Razavi, Elena Ridolfi, Jannik Riegel, Md Shibly Sadik, Nivedita Sairam, Elisa Savelli, Alexey Sazonov, Sanjib Sharma, Johanna Sörensen, Felipe Augusto Arguello Souza, Kerstin Stahl, Max Steinhausen, Michael Stoelzle, Wiwiana Szalińska, Qiuhong Tang, Fuqiang Tian, Tamara Tokarczyk, Carolina Tovar, Thi Van Thu Tran, Marjolein H. J. van Huijgevoort, Michelle T. H. van Vliet, Sergiy Vorogushyn, Thorsten Wagener, Yueling Wang, Doris E. Wendt, Elliot Wickham, Long Yang, Mauricio Zambrano-Bigiarini, and Philip J. Ward
Earth Syst. Sci. Data, 15, 2009–2023, https://doi.org/10.5194/essd-15-2009-2023, https://doi.org/10.5194/essd-15-2009-2023, 2023
Short summary
Short summary
As the adverse impacts of hydrological extremes increase in many regions of the world, a better understanding of the drivers of changes in risk and impacts is essential for effective flood and drought risk management. We present a dataset containing data of paired events, i.e. two floods or two droughts that occurred in the same area. The dataset enables comparative analyses and allows detailed context-specific assessments. Additionally, it supports the testing of socio-hydrological models.
Kunlong He, Wei Zhao, Luca Brocca, and Pere Quintana-Seguí
Hydrol. Earth Syst. Sci., 27, 169–190, https://doi.org/10.5194/hess-27-169-2023, https://doi.org/10.5194/hess-27-169-2023, 2023
Short summary
Short summary
In this study, we developed a soil moisture-based precipitation downscaling (SMPD) method for spatially downscaling the GPM daily precipitation product by exploiting the connection between surface soil moisture and precipitation according to the soil water balance equation. Based on this physical method, the spatial resolution of the daily precipitation product was downscaled to 1 km and the SMPD method shows good potential for the development of the high-resolution precipitation product.
Jaime Gaona, Pere Quintana-Seguí, María José Escorihuela, Aaron Boone, and María Carmen Llasat
Nat. Hazards Earth Syst. Sci., 22, 3461–3485, https://doi.org/10.5194/nhess-22-3461-2022, https://doi.org/10.5194/nhess-22-3461-2022, 2022
Short summary
Short summary
Droughts represent a particularly complex natural hazard and require explorations of their multiple causes. Part of the complexity has roots in the interaction between the continuous changes in and deviation from normal conditions of the atmosphere and the land surface. The exchange between the atmospheric and surface conditions defines feedback towards dry or wet conditions. In semi-arid environments, energy seems to exceed water in its impact over the evolution of conditions, favoring drought.
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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.
Angelica Tarpanelli, Alessandro C. Mondini, and Stefania Camici
Nat. Hazards Earth Syst. Sci., 22, 2473–2489, https://doi.org/10.5194/nhess-22-2473-2022, https://doi.org/10.5194/nhess-22-2473-2022, 2022
Short summary
Short summary
We analysed 10 years of river discharge data from almost 2000 sites in Europe, and we extracted flood events, as proxies of flood inundations, based on the overpasses of Sentinel-1 and Sentinel-2 satellites to derive the percentage of potential inundation events that they were able to observe. Results show that on average 58 % of flood events are potentially observable by Sentinel-1 and only 28 % by Sentinel-2 due to the obstacle of cloud coverage.
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
Short summary
Short summary
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.
Ashwini Petchiappan, Susan C. Steele-Dunne, Mariette Vreugdenhil, Sebastian Hahn, Wolfgang Wagner, and Rafael Oliveira
Hydrol. Earth Syst. Sci., 26, 2997–3019, https://doi.org/10.5194/hess-26-2997-2022, https://doi.org/10.5194/hess-26-2997-2022, 2022
Short summary
Short summary
This study investigates spatial and temporal patterns in the incidence angle dependence of backscatter from the ASCAT C-band scatterometer and relates those to precipitation, humidity, and radiation data and GRACE equivalent water thickness in ecoregions in the Amazon. The results show that the ASCAT data record offers a unique perspective on vegetation water dynamics exhibiting sensitivity to moisture availability and demand and phenological change at interannual, seasonal, and diurnal scales.
Paolo Filippucci, Luca Brocca, Raphael Quast, Luca Ciabatta, Carla Saltalippi, Wolfgang Wagner, and Angelica Tarpanelli
Hydrol. Earth Syst. Sci., 26, 2481–2497, https://doi.org/10.5194/hess-26-2481-2022, https://doi.org/10.5194/hess-26-2481-2022, 2022
Short summary
Short summary
A high-resolution (1 km) rainfall product with 10–30 d temporal resolution was obtained starting from SM data from Sentinel-1. Good performances are achieved using observed data (gauge and radar) over the Po River Valley, Italy, as a benchmark. The comparison with a product characterized by lower spatial resolution (25 km) highlights areas where the high spatial resolution of Sentinel-1 has great benefits. Possible applications include water management, agriculture and index-based insurances.
Yves Tramblay and Pere Quintana Seguí
Nat. Hazards Earth Syst. Sci., 22, 1325–1334, https://doi.org/10.5194/nhess-22-1325-2022, https://doi.org/10.5194/nhess-22-1325-2022, 2022
Short summary
Short summary
Monitoring soil moisture is important during droughts, but very few measurements are available. Consequently, land-surface models are essential tools for reproducing soil moisture dynamics. In this study, a hybrid approach allowed for regionalizing soil water content using a machine learning method. This approach proved to be efficient, compared to the use of soil property maps, to run a simple soil moisture accounting model, and therefore it can be applied in various regions.
Rui Tong, Juraj Parajka, Borbála Széles, Isabella Greimeister-Pfeil, Mariette Vreugdenhil, Jürgen Komma, Peter Valent, and Günter Blöschl
Hydrol. Earth Syst. Sci., 26, 1779–1799, https://doi.org/10.5194/hess-26-1779-2022, https://doi.org/10.5194/hess-26-1779-2022, 2022
Short summary
Short summary
The role and impact of using additional data (other than runoff) for the prediction of daily hydrographs in ungauged basins are not well understood. In this study, we assessed the model performance in terms of runoff, soil moisture, and snow cover predictions with the existing regionalization approaches. Results show that the best transfer methods are the similarity and the kriging approaches. The performance of the transfer methods differs between lowland and alpine catchments.
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
Short summary
Short summary
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.
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
Short summary
Short summary
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.
Wouter Dorigo, Irene Himmelbauer, Daniel Aberer, Lukas Schremmer, Ivana Petrakovic, Luca Zappa, Wolfgang Preimesberger, Angelika Xaver, Frank Annor, Jonas Ardö, Dennis Baldocchi, Marco Bitelli, Günter Blöschl, Heye Bogena, Luca Brocca, Jean-Christophe Calvet, J. Julio Camarero, Giorgio Capello, Minha Choi, Michael C. Cosh, Nick van de Giesen, Istvan Hajdu, Jaakko Ikonen, Karsten H. Jensen, Kasturi Devi Kanniah, Ileen de Kat, Gottfried Kirchengast, Pankaj Kumar Rai, Jenni Kyrouac, Kristine Larson, Suxia Liu, Alexander Loew, Mahta Moghaddam, José Martínez Fernández, Cristian Mattar Bader, Renato Morbidelli, Jan P. Musial, Elise Osenga, Michael A. Palecki, Thierry Pellarin, George P. Petropoulos, Isabella Pfeil, Jarrett Powers, Alan Robock, Christoph Rüdiger, Udo Rummel, Michael Strobel, Zhongbo Su, Ryan Sullivan, Torbern Tagesson, Andrej Varlagin, Mariette Vreugdenhil, Jeffrey Walker, Jun Wen, Fred Wenger, Jean Pierre Wigneron, Mel Woods, Kun Yang, Yijian Zeng, Xiang Zhang, Marek Zreda, Stephan Dietrich, Alexander Gruber, Peter van Oevelen, Wolfgang Wagner, Klaus Scipal, Matthias Drusch, and Roberto Sabia
Hydrol. Earth Syst. Sci., 25, 5749–5804, https://doi.org/10.5194/hess-25-5749-2021, https://doi.org/10.5194/hess-25-5749-2021, 2021
Short summary
Short summary
The International Soil Moisture Network (ISMN) is a community-based open-access data portal for soil water measurements taken at the ground and is accessible at https://ismn.earth. Over 1000 scientific publications and thousands of users have made use of the ISMN. The scope of this paper is to inform readers about the data and functionality of the ISMN and to provide a review of the scientific progress facilitated through the ISMN with the scope to shape future research and operations.
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
Short summary
Short summary
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.
Maria Teresa Brunetti, Massimo Melillo, Stefano Luigi Gariano, Luca Ciabatta, Luca Brocca, Giriraj Amarnath, and Silvia Peruccacci
Hydrol. Earth Syst. Sci., 25, 3267–3279, https://doi.org/10.5194/hess-25-3267-2021, https://doi.org/10.5194/hess-25-3267-2021, 2021
Short summary
Short summary
Satellite and rain gauge data are tested to predict landslides in India, where the annual toll of human lives and loss of property urgently demands the implementation of strategies to prevent geo-hydrological instability. For this purpose, we calculated empirical rainfall thresholds for landslide initiation. The validation of thresholds showed that satellite-based rainfall data perform better than ground-based data, and the best performance is obtained with an hourly temporal resolution.
Rui Tong, Juraj Parajka, Andreas Salentinig, Isabella Pfeil, Jürgen Komma, Borbála Széles, Martin Kubáň, Peter Valent, Mariette Vreugdenhil, Wolfgang Wagner, and Günter Blöschl
Hydrol. Earth Syst. Sci., 25, 1389–1410, https://doi.org/10.5194/hess-25-1389-2021, https://doi.org/10.5194/hess-25-1389-2021, 2021
Short summary
Short summary
We used a new and experimental version of the Advanced Scatterometer (ASCAT) soil water index data set and Moderate Resolution Imaging Spectroradiometer (MODIS) C6 snow cover products for multiple objective calibrations of the TUWmodel in 213 catchments of Austria. Combined calibration to runoff, satellite soil moisture, and snow cover improves runoff (40 % catchments), soil moisture (80 % catchments), and snow (~ 100 % catchments) simulation compared to traditional calibration to runoff only.
Louise Mimeau, Yves Tramblay, Luca Brocca, Christian Massari, Stefania Camici, and Pascal Finaud-Guyot
Hydrol. Earth Syst. Sci., 25, 653–669, https://doi.org/10.5194/hess-25-653-2021, https://doi.org/10.5194/hess-25-653-2021, 2021
Short summary
Short summary
Soil moisture is a key variable related to droughts and flood genesis, but little is known about the evolution of soil moisture under climate change. Here, using a simulation approach, we show that changes in soil moisture are driven by changes in precipitation intermittence rather than changes in precipitation intensity or in temperature.
Stefania Camici, Christian Massari, Luca Ciabatta, Ivan Marchesini, and Luca Brocca
Hydrol. Earth Syst. Sci., 24, 4869–4885, https://doi.org/10.5194/hess-24-4869-2020, https://doi.org/10.5194/hess-24-4869-2020, 2020
Short summary
Short summary
The paper performs the most comprehensive European-scale evaluation to date of satellite rainfall products for river flow prediction. In doing so, how errors transfer from satellite-based rainfall products into flood simulation is investigated in depth and, for the first time, quantitative guidelines on the use of these products for hydrological applications are provided. This result can represent a keystone in the use of satellite rainfall products, especially in data-scarce regions.
El Mahdi El Khalki, Yves Tramblay, Christian Massari, Luca Brocca, Vincent Simonneaux, Simon Gascoin, and Mohamed El Mehdi Saidi
Nat. Hazards Earth Syst. Sci., 20, 2591–2607, https://doi.org/10.5194/nhess-20-2591-2020, https://doi.org/10.5194/nhess-20-2591-2020, 2020
Short summary
Short summary
In North Africa, the vulnerability to floods is high, and there is a need to improve the flood-forecasting systems. Remote-sensing and reanalysis data can palliate the lack of in situ measurements, in particular for soil moisture, which is a crucial parameter to consider when modeling floods. In this study we provide an evaluation of recent globally available soil moisture products for flood modeling in Morocco.
Cited articles
Abolafia-Rosenzweig, R., Livneh, B., Small, E. E., and Kumar, S. V.: Soil
moisture data assimilation to estimate irrigation water use, J. Adv. Model.
Earth Sy., 11, 3670–3690, https://doi.org/10.1029/2019MS001797, 2019.
Albergel, C., Rüdiger, C., Pellarin, T., Calvet, J.-C., Fritz, N., Froissard, F., Suquia, D., Petitpa, A., Piguet, B., and Martin, E.: From near-surface to root-zone soil moisture using an exponential filter: an assessment of the method based on in-situ observations and model simulations, Hydrol. Earth Syst. Sci., 12, 1323–1337, https://doi.org/10.5194/hess-12-1323-2008, 2008.
Allen, R. G., Pereira, L. S., Raes, D., and Smith, M.: Crop
Evapotranspiration: Guidelines for Computing Crop Requirements, Irrigation
and Drainage Paper, FAO, Rome, Italy, ISBN 92-5-104219-5, 1998.
Bauer-Marschallinger, B., Naeimi, V., Cao, S., Paulik, C., Schaufler, S.,
Stachl, T., Modanesi, S., Ciabatta, L., Massari, C., Brocca, L., and Wagner,
W.: Towards global soil moisture monitoring with Sentinel-1: harnessing
assets and overcoming obstacles, IEEE T. Geosci. Remote S., 57,
520–539, https://doi.org/10.1109/TGRS.2018.2858004, 2019.
Bazzi, H., Baghdadi, N., Ienco, D., El Hajj, M., Zribi, M., Belhouchette,
H., Escorihuela, M. J., and Demarez, V.: Mapping irrigated areas using
Sentinel-1 time series in Catalonia, Spain, Remote Sens.-Basel, 11, 1836,
https://doi.org/10.3390/rs11151836, 2019.
Beck, H. E., Zimmermann, N. E., McVicar, T. R., Vergopolan, N., Berg, A., and
Wood, E. F.: Present and future Köppen-Geiger climate classification maps
at 1-km resolution, Sci. Data, 5, 180214, https://doi.org/10.1038/sdata.2018.214,
2018.
Bretreger, D., Yeo, I.-Y., Hancock, G., and Willgoose, G.: Monitoring
irrigation using landsat observations and climate data over regional scales
in the Murray-Darling Basin, J. Hydrol., 590, 125356,
https://doi.org/10.1016/j.jhydrol.2020.125356, 2020.
Brocca, L., Ciabatta, L., Massari, C., Moramarco, T., Hahn, S., Hasenauer,
S., Kidd, R., Dorigo, W., Wagner, W., and Levizzani, V.: Soil as a natural
rain gauge: Estimating global rainfall from satellite soil moisture data, J.
Geophys. Res., 119, 5128–5141, https://doi.org/10.1002/2014JD021489, 2014.
Brocca, L., Massari, C., Ciabatta, L., Moramarco, T., Penna, D., Zuecco, G.,
Pianezzola, L., Borga, M., Matgen, P., and Martínez-Fernández, J.:
Rainfall estimation from in situ soil moisture observations at several sites
in Europe: an evaluation of the SM2RAIN algorithm, J. Hydrol.
Hydromech., 63, 201–209, https://doi.org/10.1515/johh-2015-0016, 2015.
Brocca, L., Tarpanelli, A., Filippucci, P., Dorigo, W., Zaussinger, F.,
Gruber, A., and Fernández-Prieto, D.: How much water is used for
irrigation? A new approach exploiting coarse resolution satellite soil
moisture products, Int. J. Appl. Earth Obs., 73, 752–766,
https://doi.org/10.1016/j.jag.2018.08.023, 2018.
Brombacher, J., de Oliveira Silva, I. R., Degen, J., and Pelgrum, H.: A novel
evapotranspiration based irrigation quantification method using the
hydrological similar pixels algorithm, Agr. Water Manage., 267, 107602,
https://doi.org/10.1016/j.agwat.2022.107602, 2022.
Ceppi, A., Ravazzani, G., Corbari, C., Salerno, R., Meucci, S., and Mancini, M.: Real-time drought forecasting system for irrigation management, Hydrol. Earth Syst. Sci., 18, 3353–3366, https://doi.org/10.5194/hess-18-3353-2014, 2014.
Dari, J., Brocca, L., Quintana-Seguí, P., Escorihuela, M. J., Stefan,
V., and Morbidelli, R.: Exploiting high-resolution remote sensing soil
moisture to estimate irrigation water amounts over a Mediterranean region,
Remote Sens.-Basel, 12, 2593, https://doi.org/10.3390/rs12162593, 2020.
Dari, J., Quintana-Seguí, P., Escorihuela, M.J., Stefan, V., Brocca,
L., and Morbidelli, R.: Detecting and mapping irrigated areas in a
Mediterranean environment by using remote sensing soil moisture and a land
surface model, J. Hydrol., 596, 126129,
https://doi.org/10.1016/j.jhydrol.2021.126129, 2021.
Dari, J., Brocca, L., Modanesi, S., Massari, C., Tarpanelli, A., Barbetta,
S., Quast, R., Vreugdenhil, M., Freeman, V., Barella-Ortiz, A.,
Quintana-Seguí, P., Bretreger, D., and Volden, E.: Regional data sets
of high-resolution (1 and 6 km) irrigation estimates from space (1.0), Zenodo [data
set], https://doi.org/10.5281/zenodo.7341284, 2022a.
Dari, J., Brocca, L., Quintana-Seguí, P., Casadei, S., Escorihuela,
M.J., Stefan, V., and Morbidelli, R.: Double-scale analysis on the
detectability of irrigation signals from remote sensing soil moisture over
an area with complex topography in central Italy, Adv. Water Res., 161,
104130, https://doi.org/10.1016/j.advwatres.2022.104130, 2022b.
Dari, J., Quintana-Seguí, P., Morbidelli, R., Saltalippi, C., Flammini,
A., Giugliarelli, E., Escorihuela, M. J., Stefan, V., and Brocca, L.:
Irrigation estimates from space: Implementation of different approaches to
model the evapotranspiration contribution within a soil-moisture-based
inversion algorithm, Agr. Water Manage., 265, 107537,
https://doi.org/10.1016/j.agwat.2022.107537, 2022c.
Das, N. N., Entekhabi, D., Dunbar, R. S., Chaubell, M. J., Colliander, A.,
Yueh, S., Jagdhuber, T., Chen, F., Crow, W., O'Neill, P. E., Walker, J. P.,
Berg, A., Bosch, D. D., Caldwell, T., Cosh, M. H., Collins, C. H., Lopez-Baeza,
E., and Thibeault, M.: The SMAP and Copernicus Sentinel 1A/B microwave
active-passive high resolution surface soil moisture product, Remote Sens.
Environ., 233, 111380, https://doi.org/10.1016/j.rse.2019.111380, 2019.
Deines, J. M., Kendall, A. D., Crowley, M. A., Rapp, J., Cardille, J. A.,
and Hyndman, D. W.: Mapping three decades of annual irrigation across the US
High Plains Aquifer using Landsat and Google Earth Engine, Remote Sens.
Environ., 233, 111400, https://doi.org/10.1016/j.rse.2019.111400, 2019.
De Lannoy, G. J. M. and Reichle, R. H.: Global assimilation of multiangle and
multipolarization SMOS brightness temperature observations into the GEOS-5
catchment land surface model for soil moisture estimation, J.
Hydrometeorol., 17, 669–691, https://doi.org/10.1175/JHM-D-15-0037.1,
2016a.
De Lannoy, G. J. M. and Reichle, R. H.: Assimilation of SMOS brightness temperatures or soil moisture retrievals into a land surface model, Hydrol. Earth Syst. Sci., 20, 4895–4911, https://doi.org/10.5194/hess-20-4895-2016, 2016b.
Dorigo, W., Dietrich, S., Aires, F., Brocca, L., Carter, S., Cretaux, J.-F.,
Dunkerley, D., Enomoto, H., Forsberg, R., Güntner, A., Hegglin, M. I.,
Hollmann, R., Hurst, D. F., Johannessen, J. A., Kummerow, C., Lee, T., Luojus,
K., Looser, U., Miralles, D. G., Pellet, V., Recknagel, T., Vargas, C. R.,
Schneider, U., Schoeneich, P., Schröder, M., Tapper, N., Vuglinsky, V.,
Wagner, W., Yu, L., Zappa, L., Zemp, M., and Aich, V.: Closing the water
cycle from observations across scales: where do we stand?, B. Am.
Meteorol. Soc., 102, E1897–E1935, https://doi.org/10.1175/BAMS-D-19-0316.1, 2021.
Elwan, E., Le Page, M., Jarlan, L., Baghdadi, N., Brocca, L., Modanesi, S.,
Dari, J., Quintana-Seguí, P., and Zribi, M.: Irrigation Mapping on Two
Contrasted Climatic Contexts Using Sentinel-1 and Sentinel-2 Data, Water,
14, 804, https://doi.org/10.3390/w14050804, 2022.
Famiglietti, J. S. and Wood, E. F.: Multiscale modeling of spatially variable
water and energy balance processes, Water Resour. Res., 30, 3061–3078,
https://doi.org/10.1029/94WR01498, 1994.
Ferguson, C. R., Pan, M., and Oki, T.: The effect of global warming on future
water availability: CMIP5 synthesis, Water Resour. Res., 54, 7791–7819,
https://doi.org/10.1029/2018WR022792, 2018.
Foley, J. A., Ramankutty, N., Brauman, K. A., Cassidy, E. S., Gerber, J. S., Johnston, M., Mueller, N. D., O’Connell, C., Ray, D. K., West, P. C., Balzer, C., Bennett, E. M., Carpenter, S. R., Hill, J., Monfreda, C., Polasky, S., Rockström, J., Sheehan, J., Siebert, S., Tilman, D., and Zaks, D. P. M.: Solutions for a cultivated planet, Nature, 478,
337–342, https://doi.org/10.1038/nature10452, 2011.
Formetta, G., Tootle, G., and Therrell, M.: Regional Reconstruction of Po
River Basin (Italy) Streamflow, Hydrology, 9, 163,
https://doi.org/10.3390/hydrology9100163, 2022.
Freeman, V., Esterhuizen, S., Jales, P., and Masters, D.: Spire's new GNSS-R
soil moisture products collected from small and innovative Earth observing
satellites, Proc. SPIE 11528, Remote Sensing for Agriculture, Ecosystems,
and Hydrology XXII, 115280F, 20 September 2020,
https://doi.org/10.1117/12.2574124, 2020.
Gao, Q., Zribi, M., Escorihela, M. J., Baghdadi, N., and Quintana-Seguí,
P.: Irrigation mapping using Sentinel-1 time series at field scale, Remote
Sens.-Basel, 10, 1495, https://doi.org/10.3390/rs10091495, 2018.
Hunter, M. C., Smith, R. G., Schipanski, M. E., Atwood, L. W., and Mortensen,
D. A.: Agriculture in 2050: Recalibrating targets for sustainable
intensification, BioScience, 67, 386–391,
https://doi.org/10.1093/biosci/bix010, 2017.
Jalilvand, E., Tajrishy, M., Hashemi, S. A. G., and Brocca, L.: Quantification
of irrigation water using remote sensing of soil moisture in a semi-arid
region, Remote Sens. Environ., 231, 111226,
https://doi.org/10.1016/j.rse.2019.111226, 2019.
Jalilvand, E., Abolafia-Rosenzweig, R., Tajrishy, M., and Das, N. N.:
Evaluation of SMAP-Sentinel1 High-Resolution Soil Moisture Data to Detect
Irrigation over Agricultural Domain, IEEE J. Sel. Top. Appl., 14, 10733–10747, https://doi.org/10.1109/JSTARS.2021.3119228, 2021.
Lawston, P. M., Santanello, J. A., Zaitchik, B. F., and Rodell, M.: Impact
of irrigation methods on land surface model spinup and initialization of WRF
forecasts, J. Hydrometeorol., 16, 1135–1154,
https://doi.org/10.1175/JHM-D-14-0203.1, 2015.
Lawston, P. M., Santanello, J. A., and Kumar, S. V.: Irrigation signals
detected from SMAP soil moisture retrievals, Geophys. Res. Lett.,
44, 11–860, https://doi.org/10.1002/2017GL075733, 2017.
Liang, X., Lettenmaier, D. P., Wood, E. F., and Burges, S. J.: A Simple
hydrologically Based Model of Land Surface Water and Energy Fluxes for GSMs,
J. Geophys. Res., 99, 14415–14428, 1994.
Lievens, H., Martens, B., Verhoest, N. E. C., Hahn, S., Reichle, R. H., and
Miralles, D. G.: Assimilation of global radar backscatter and radiometer
brightness temperature observations to improve soil moisture and land
evaporation estimates, Remote Sens. Environ., 189, 194–210,
https://doi.org/10.1016/j.rse.2016.11.022, 2017a.
Lievens, H., Reichle, R. H., Liu, Q., De Lannoy, G. J. M., Dunbar, R. S., Kim,
S. B., Das, N. N., Cosh, M., Walker, J. P., and Wagner, W.: Joint Sentinel-1
and SMAP data assimilation to improve soil moisture estimates, Geophys. Res.
Lett., 44, 6145–6153, https://doi.org/10.1002/2017GL073904, 2017b.
Martens, B., Miralles, D. G., Lievens, H., van der Schalie, R., de Jeu, R. A. M., Fernández-Prieto, D., Beck, H. E., Dorigo, W. A., and Verhoest, N. E. C.: GLEAM v3: satellite-based land evaporation and root-zone soil moisture, Geosci. Model Dev., 10, 1903–1925, https://doi.org/10.5194/gmd-10-1903-2017, 2017.
Massari, C., Modanesi, S., Dari, J., Gruber, A., De Lannoy, G. J. M., Girotto,
M., Quintana-Seguí, P., Le Page, M., Jarlan, L., Zribi, M., Ouaadi, N.,
Vreugdenhil, M., Zappa, L., Dorigo, W., Wagner, W., Brombacher, J., Pelgrum,
H., Jaquot, P., Freeman, V., Volden, E., Fernandez Prieto, D., Tarpanelli,
A., Barbetta, S., and Brocca, L.: A review of irrigation information
retrievals from space and their utility for users, Remote Sens.-Basel, 13,
4112, https://doi.org/10.3390/rs13204112, 2021.
Merlin, O., Escorihuela, M. J., Mayoral, M. A., Hagolle, O., AlBitar, A., and
Kerr, Y.: Self-calibrated evaporation-based disaggregation of SMOS soil
moisture: an evaluation study at 3 km and 100 m resolution in Catalunya,
Spain, Remote Sens. Environ., 130, 25–38,
https://doi.org/10.1016/j.rse.2012.11.008, 2013.
Miralles, D. G., Holmes, T. R. H., De Jeu, R. A. M., Gash, J. H., Meesters, A. G. C. A., and Dolman, A. J.: Global land-surface evaporation estimated from satellite-based observations, Hydrol. Earth Syst. Sci., 15, 453–469, https://doi.org/10.5194/hess-15-453-2011, 2011.
Modanesi, S., Dari, J., Massari, C., Tarpanelli, A., Barbetta, S., De
Lannoy, G., Gruber, A., Lievens, H., Bechtold, M., Quast, R., Vreugdenhil,
M., Zribi, M., Le Page, M., and Brocca, L.: A comparison between satellite-
and model-based approaches developed in the ESA Irrigation+ project
framework to estimate irrigation quantities, 2021 IEEE International
Workshop on Metrology for Agriculture and Forestry (MetroAgriFor), 268–272,
https://doi.org/10.1109/MetroAgriFor52389.2021.9628453, 2021a.
Modanesi, S., Massari, C., Gruber, A., Lievens, H., Tarpanelli, A., Morbidelli, R., and De Lannoy, G. J. M.: Optimizing a backscatter forward operator using Sentinel-1 data over irrigated land, Hydrol. Earth Syst. Sci., 25, 6283–6307, https://doi.org/10.5194/hess-25-6283-2021, 2021b.
Modanesi, S., Massari, C., Bechtold, M., Lievens, H., Tarpanelli, A., Brocca, L., Zappa, L., and De Lannoy, G. J. M.: Challenges and benefits of quantifying irrigation through the assimilation of Sentinel-1 backscatter observations into Noah-MP, Hydrol. Earth Syst. Sci., 26, 4685–4706, https://doi.org/10.5194/hess-26-4685-2022, 2022.
Muñoz-Sabater, J., Dutra, E., Agustí-Panareda, A., Albergel, C., Arduini, G., Balsamo, G., Boussetta, S., Choulga, M., Harrigan, S., Hersbach, H., Martens, B., Miralles, D. G., Piles, M., Rodríguez-Fernández, N. J., Zsoter, E., Buontempo, C., and Thépaut, J.-N.: ERA5-Land: a state-of-the-art global reanalysis dataset for land applications, Earth Syst. Sci. Data, 13, 4349–4383, https://doi.org/10.5194/essd-13-4349-2021, 2021.
Musolino, D., de Carli, A., and Massarutto, A.: Evaluation of socio-economic
impact of drought events: the case of Po river basin, European Countryside,
9, 163–176, https://doi.org/10.1515/euco-2017-0010, 2017.
Nagaraj, D., Proust, E., Todeschini, A., Rulli, M. C., and D'Odorico, P.: A
new dataset of global irrigation areas from 2001 to 2015, Adv. Water
Resour., 152, 103910, https://doi.org/10.1016/j.advwatres.2021.103910, 2021.
Nie, W., Zaitchik, B. F., Rodell, M., Kumar, S. V., Anderson, M. C., and
Hain, C.: Groundwater withdrawals under drought: Reconciling GRACE and Land
Surface Models in the United States High Plains Aquifer, Water Resour. Res.,
48, 317, https://doi.org/10.1029/2017WR022178, 2018.
Ozdogan, M., Rodell, M., Beaudoing, H. K., and Toll, D. L.: Simulating the
effects of irrigation over the United States in a land surface model based
on satellite derived agricultural data, J. Hydrometeorol., 11, 171–184,
https://doi.org/10.1175/2009JHM1116.1, 2010.
Peña-Arancibia, J. L., Mainuddin, M., Kirby, J. M., Chiew, F. H. S.,
McVicar, T. R., and Vaze, J.: Assessing irrigated agriculture's surface water
and groundwater consumption by combining satellite remote sensing and
hydrologic modelling, Sci. Total Environ., 542, 372–382, https://doi.org/10.1016/j.scitotenv.2015.10.086, 2016.
Peng, J., Albergel, C., Balenzano, A., Brocca, L., Cartus, O., Cosh, M. H., Crow, W. T., Dabrowska-Zielinska, K., Dadson, S., Davidson, M. W. J., de Rosnay, P., Dorigo, W., Gruber, A., Hagemann, S., Hirschi, M., Kerr, Y. H., Lovergine, F., Mahecha, M. D., Marzahn, P., Mattia, F., Musial, J. P., Preuschmann, S., Reichle, R. H., Satalino, G., Silgram, M., van Bodegom, P. M., Verhoest, N. E. C., Wagner, W., Walker, J. P., Wegmüller, U., and Loew, A.: A roadmap for high-resolution
satellite soil moisture applications – confronting product characteristics
with user requirements, Remote Sens. Environ., 252, 112162,
https://doi.org/10.1016/j.rse.2020.112162, 2021.
Portmann, F., Siebert, S., Bauer, C., and Döll, P.: Global data set of
monthly growing areas of 26 irrigated crops, Version 1.0, Frankfurt Hydrol.
Pap. 06, Inst. of Phys. Geogr., Univ. of Frankfurt, Frankfurt, Germany,
2008.
Quast, R.: “TUW-GEO/rt1: RT1 v1.5.1.”, Zenodo [data set], https://doi.org/10.5281/ZENODO.3745590, 2021.
Quast, R., Albergel, C., Calvet, J. C., and Wagner, W.: A Generic First-Order
Radiative Transfer Modelling Approach for the Inversion of Soil and
Vegetation Parameters from Scatterometer Observations, Remote Sens.-Basel, 11,
285, https://doi.org/10.3390/rs11030285, 2019.
Romaguera, M., Krol, M., Salama, M., Su, Z., and Hoekstra, A.: Application
of a remote sensing method for estimating monthly blue water
evapotranspiration in irrigated agriculture, Remote Sens.-Basel, 6, 10033–10050,
https://doi.org/10.3390/rs61010033, 2014.
Ruf, C., Gleason, S., Ridley, A., Rose, R., and Scherrer, J.: The Nasa
Cygnss Mission: Overview and Status Update, IEEE International Geoscience
and Remote Sensing Symposium (IGARSS), Fort Worth, TX, USA, 2641–2643, https://doi.org/10.1109/IGARSS.2017.8127537, 2017.
Salmon, J. M., Friedl, M. A, Frolking, S., Wisser, D., and Douglas, E. M.:
Global rain-fed, irrigated, and paddy croplands: a new high resolution map
derived from remote sensing, crop inventories and climate data, Int. J.
Appl. Earth Obs., 38, 321–334, https://doi.org/10.1016/j.jag.2015.01.014, 2015.
Siebert, S., Kummu, M., Porkka, M., Döll, P., Ramankutty, N., and Scanlon, B. R.: A global data set of the extent of irrigated land from 1900 to 2005, Hydrol. Earth Syst. Sci., 19, 1521–1545, https://doi.org/10.5194/hess-19-1521-2015, 2015.
Strosser, P., Dworak, T., Delvaux, P. A. G., Berglund, M., Schmidt, G.,
Mysiak, J., Kossida, M., Iacovides, I., and Ashton, V.: Gap analysis of the
water scarcity and droughts policy in the EU European Commission, European
Commission, Tender ENV.D.1/SER/2010/0049, 206, 2012.
van Dijk, A. I. J. M., Beck, H. E., Crosbie, R. S., de Jeu, R. A. M., Liu, Y. Y.,
Podger, G. M., Timbal, B., and Viney, N. R.: The Millennium Drought in
southeast Australia (2001-2009): Natural and human causes and implications
for water resources, ecosystems, economy, and society, Water Resour. Res.,
49, 1040–1057, https://doi.org/10.1002/wrcr.20123, 2013.
Van Eekelen, M. W., Bastiaanssen, W. G. M., Jarmain, C., Jackson, B., Ferreira, F., van der Zaag, P., Saraiva Okello, A., Bosch, J., Dye, P., Bastidas-Obando, E., Dost, R. J. J., and Luxemburg, W. M. J.: A novel approach to estimate direct and
indirect water withdrawals from satellite measurements: a case study from
the Incomati basin, Agric. Ecosyst. Environ., 200, 126–142,
https://doi.org/10.1016/j.agee.2014.10.023, 2015.
Zappa, L., Schlaffer, S., Bauer-Marschallinger, B., Nendel, C., Zimmerman,
B., and Dorigo, W.: Detection and Quantification of Irrigation Water Amounts
at 500 m Using Sentinel-1 Surface Soil Moisture, Remote Sens.-Basel, 13, 1727,
https://doi.org/10.3390/rs13091727, 2021.
Zappa, L., Schlaffer, S., Brocca, L., Vreugdenhil, M., Nendel, C., and
Dorigo, W.: How accurately can we retrieve irrigation timing and water
amounts from (satellite) soil moisture?, Int. J. Appl. Earth Obs.,
113, 102979, https://doi.org/10.1016/j.jag.2022.102979, 2022.
Zaussinger, F., Dorigo, W., Gruber, A., Tarpanelli, A., Filippucci, P., and Brocca, L.: Estimating irrigation water use over the contiguous United States by combining satellite and reanalysis soil moisture data, Hydrol. Earth Syst. Sci., 23, 897–923, https://doi.org/10.5194/hess-23-897-2019, 2019.
Zhang, K., Li, X., Zheng, D., Zhang, L., and Zhu, G.: Estimation of Global
Irrigation Water Use by the Integration of Multiple Satellite Observations,
Water Resour. Res., 58, e2021WR030031,
https://doi.org/10.1029/2021WR030031, 2022.
Short summary
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.
Irrigation is the main source of global freshwater consumption. Despite this, a detailed...
Altmetrics
Final-revised paper
Preprint