Articles | Volume 27, issue 1
https://doi.org/10.5194/hess-27-169-2023
© 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/hess-27-169-2023
© Author(s) 2023. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
10 Jan 2023
Research article |
| 10 Jan 2023
| 10 Jan 2023
SMPD: a soil moisture-based precipitation downscaling method for high-resolution daily satellite precipitation estimation
Kunlong He
Institute of Mountain Hazards and Environment, Chinese Academy of
Sciences, Chengdu 610299, China
School of Civil Engineering, Sun Yat-sen University, Guangzhou 510275, China
Institute of Mountain Hazards and Environment, Chinese Academy of
Sciences, Chengdu 610299, China
Luca Brocca
Research Institute for Geo-Hydrological Protection, National Research Council, Perugia, Italy
Pere Quintana-Seguí
Ebro Observatory (OE), Ramon Llull University – CSIC, Roquetes,
Spain
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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
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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.
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
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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
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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.
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
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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.
Jaime Gaona, Davide Bavera, Guido Fioravanti, Sebastian Hahn, Pietro Stradiotti, Paolo Filippucci, Stefania Camici, Luca Ciabatta, Hamidreza Mossaffa, Silvia Puca, Nicoletta Roberto, and Luca Brocca
Hydrol. Earth Syst. Sci. Discuss., https://doi.org/10.5194/hess-2024-182, https://doi.org/10.5194/hess-2024-182, 2024
Revised manuscript accepted for HESS
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Soil moisture is crucial for the water cycle since it is the frontline of drought. Satellite, model, and in-situ data help identify soil moisture stress but 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.
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
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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
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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.
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
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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.
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.
Haoxuan Yang, Qunming Wang, Wei Zhao, and Peter Atkinson
Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2022-426, https://doi.org/10.5194/essd-2022-426, 2023
Preprint withdrawn
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A random forest (RF) model was proposed to extend the superior SMAP dataset (named RF_SMAP) from 1979 to 2015, using the corresponding CCI time-series. The new long time-series RF_SMAP dataset, which will be available to download, will be of great value for a range of research in applications such as climate assessment, agricultural planning, food insecurity monitoring and drought assessment and monitoring.
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
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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.
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.
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.
Haoxuan Yang, Qunming Wang, Wei Zhao, and Peter M. Atkinson
Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2022-137, https://doi.org/10.5194/essd-2022-137, 2022
Preprint withdrawn
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A random forest (RF) model was proposed to extend the superior SMAP dataset (named RF_SMAP) from 1979 to 2015, using the corresponding CCI time-series. The new long time-series RF_SMAP dataset, which will be available to download, will be of great value for a range of research in applications such as climate assessment, agricultural planning, food insecurity monitoring and drought assessment and monitoring.
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
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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
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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.
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
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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
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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.
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
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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.
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
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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
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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
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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.
Christian Massari, Luca Brocca, Thierry Pellarin, Gab Abramowitz, Paolo Filippucci, Luca Ciabatta, Viviana Maggioni, Yann Kerr, and Diego Fernandez Prieto
Hydrol. Earth Syst. Sci., 24, 2687–2710, https://doi.org/10.5194/hess-24-2687-2020, https://doi.org/10.5194/hess-24-2687-2020, 2020
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Rain gauges are unevenly spaced around the world with extremely low gauge density over places like Africa and South America. Here, water-related problems like floods, drought and famine are particularly severe and able to cause fatalities, migration and diseases. We have developed a rainfall dataset that exploits the synergies between rainfall and soil moisture to provide accurate rainfall observations which can be used to face these problems.
Anaïs Barella-Ortiz and Pere Quintana-Seguí
Hydrol. Earth Syst. Sci., 23, 5111–5131, https://doi.org/10.5194/hess-23-5111-2019, https://doi.org/10.5194/hess-23-5111-2019, 2019
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Drought is an important climatic risk. This study analyses drought representation and propagation by regional climate models from Med-CORDEX simulations using standardized indices. Results show that these models improve meteorological drought representation, but uncertainties are identified in its propagation and the way soil moisture and hydrological droughts are characterized. These are mainly due to model structure, making further improvements in land surface modelling necessary.
Luca Brocca, Paolo Filippucci, Sebastian Hahn, Luca Ciabatta, Christian Massari, Stefania Camici, Lothar Schüller, Bojan Bojkov, and Wolfgang Wagner
Earth Syst. Sci. Data, 11, 1583–1601, https://doi.org/10.5194/essd-11-1583-2019, https://doi.org/10.5194/essd-11-1583-2019, 2019
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SM2RAIN–ASCAT is a new 12-year (2007–2018) global-scale rainfall dataset obtained by applying the SM2RAIN algorithm to ASCAT soil moisture data. The dataset has a spatiotemporal sampling resolution of 12.5 km and 1 d. Results show that the new dataset performs particularly well in Africa and South America, i.e. in the continents in which ground observations are scarce and the need for satellite rainfall data is high. SM2RAIN–ASCAT is available at http://doi.org/10.5281/zenodo.340556.
Felix Zaussinger, Wouter Dorigo, Alexander Gruber, Angelica Tarpanelli, Paolo Filippucci, and Luca Brocca
Hydrol. Earth Syst. Sci., 23, 897–923, https://doi.org/10.5194/hess-23-897-2019, https://doi.org/10.5194/hess-23-897-2019, 2019
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About 70 % of global freshwater is consumed by irrigation. Yet, policy-relevant estimates of irrigation water use (IWU) are virtually lacking at regional to global scales. To bridge this gap, we develop a method for quantifying IWU from a combination of state-of-the-art remotely sensed and modeled soil moisture products and apply it over the United States for the period 2013–2016. Overall, our estimates agree well with reference data on irrigated area and irrigation water withdrawals.
Victor Pellet, Filipe Aires, Simon Munier, Diego Fernández Prieto, Gabriel Jordá, Wouter Arnoud Dorigo, Jan Polcher, and Luca Brocca
Hydrol. Earth Syst. Sci., 23, 465–491, https://doi.org/10.5194/hess-23-465-2019, https://doi.org/10.5194/hess-23-465-2019, 2019
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This study is an effort for a better understanding and quantification of the water cycle and related processes in the Mediterranean region, by dealing with satellite products and their uncertainties. The aims of the paper are 3-fold: (1) developing methods with hydrological constraints to integrate all the datasets, (2) giving the full picture of the Mediterranean WC, and (3) building a model-independent database that can evaluate the numerous regional climate models (RCMs) for this region.
Md Abul Ehsan Bhuiyan, Efthymios I. Nikolopoulos, Emmanouil N. Anagnostou, Pere Quintana-Seguí, and Anaïs Barella-Ortiz
Hydrol. Earth Syst. Sci., 22, 1371–1389, https://doi.org/10.5194/hess-22-1371-2018, https://doi.org/10.5194/hess-22-1371-2018, 2018
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This study investigates the use of a nonparametric model for combining multiple global precipitation datasets and characterizing estimation uncertainty. Inputs to the model included three satellite precipitation products, an atmospheric reanalysis precipitation dataset, satellite-derived near-surface daily soil moisture data, and terrain elevation. We evaluated the technique based on high-resolution reference precipitation data and further used generated ensembles to force a hydrological model.
Luca Ciabatta, Christian Massari, Luca Brocca, Alexander Gruber, Christoph Reimer, Sebastian Hahn, Christoph Paulik, Wouter Dorigo, Richard Kidd, and Wolfgang Wagner
Earth Syst. Sci. Data, 10, 267–280, https://doi.org/10.5194/essd-10-267-2018, https://doi.org/10.5194/essd-10-267-2018, 2018
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In this study, rainfall is estimated starting from satellite soil moisture observation on a global scale, using the ESA CCI soil moisture datasets. The new obtained rainfall product has proven to correctly identify rainfall events, showing performance sometimes higher than those obtained by using classical rainfall estimation approaches.
Antoine Colmet-Daage, Emilia Sanchez-Gomez, Sophie Ricci, Cécile Llovel, Valérie Borrell Estupina, Pere Quintana-Seguí, Maria Carmen Llasat, and Eric Servat
Hydrol. Earth Syst. Sci., 22, 673–687, https://doi.org/10.5194/hess-22-673-2018, https://doi.org/10.5194/hess-22-673-2018, 2018
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Here, the first assessment of future changes in extreme precipitation in small Mediterranean watersheds is done through three watersheds frequently subjected to flash floods. Collaboration between Spanish and French laboratories enabled us to conclude that the intensity of high precipitation will increase at the end of the century. A high degree of confidence results from the multi-model approach used here with eight regional climate models (RCMs) developed in the Med and Euro-CORDEX project.
Hylke E. Beck, Noemi Vergopolan, Ming Pan, Vincenzo Levizzani, Albert I. J. M. van Dijk, Graham P. Weedon, Luca Brocca, Florian Pappenberger, George J. Huffman, and Eric F. Wood
Hydrol. Earth Syst. Sci., 21, 6201–6217, https://doi.org/10.5194/hess-21-6201-2017, https://doi.org/10.5194/hess-21-6201-2017, 2017
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This study represents the most comprehensive global-scale precipitation dataset evaluation to date. We evaluated 13 uncorrected precipitation datasets using precipitation observations from 76 086 gauges, and 9 gauge-corrected ones using hydrological modeling for 9053 catchments. Our results highlight large differences in estimation accuracy, and hence, the importance of precipitation dataset selection in both research and operational applications.
Christian Massari, Wade Crow, and Luca Brocca
Hydrol. Earth Syst. Sci., 21, 4347–4361, https://doi.org/10.5194/hess-21-4347-2017, https://doi.org/10.5194/hess-21-4347-2017, 2017
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The paper explores a method for the assessment of the performance of global rainfall estimates without relying on ground-based observations. Thanks to this method, different global correlation maps are obtained (for the first time without relying on a benchmark dataset) for some of the most used globally available rainfall products. This is central for hydroclimatic studies within data-scarce regions, where ground observations are scarce to evaluate the relative quality of a rainfall product
Xiaodong Gao, Xining Zhao, Luca Brocca, Gaopeng Huo, Ting Lv, and Pute Wu
Hydrol. Earth Syst. Sci. Discuss., https://doi.org/10.5194/hess-2017-292, https://doi.org/10.5194/hess-2017-292, 2017
Preprint retracted
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Profile soil moisture is key state variable in the Critical Zone ecology and hydrology. This paper sucessfully used a simple statistical method, the cumulative distribution frequency (CDF) matching method for the first time, to predict profile soil moisture (0–100 cm) from surface measurement (5 cm). The findings here can provide insights into profile soil moisture estimation from remote sensing moisture products.
Wuletawu Abera, Giuseppe Formetta, Luca Brocca, and Riccardo Rigon
Hydrol. Earth Syst. Sci., 21, 3145–3165, https://doi.org/10.5194/hess-21-3145-2017, https://doi.org/10.5194/hess-21-3145-2017, 2017
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This study documents a state-of-the-art estimation of the water budget (rainfall, evapotranspiration, discharge, and soil and groundwater storage) components for the Upper Blue Nile river. The budget uses various JGrass-NewAGE components, satellite data and all ground measurements available. The analysis shows that precipitation of the basin is 1360 ± 230 mm per year. Evapotranspiration accounts for 56 %, runoff is 33 %, and storage varies from minus 10 % to plus 17 % of the annual water budget.
Pere Quintana-Seguí, Marco Turco, Sixto Herrera, and Gonzalo Miguez-Macho
Hydrol. Earth Syst. Sci., 21, 2187–2201, https://doi.org/10.5194/hess-21-2187-2017, https://doi.org/10.5194/hess-21-2187-2017, 2017
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The quality of two high-resolution precipitation datasets for Spain at the daily time scale is reported: the new SAFRAN-based dataset and Spain02. ERA-Interim is also included. The precipitation products are compared with observations. SAFRAN and Spain02 have very similar scores, and they perform better than ERA-Interim. The high-resolution gridded products overestimate the number of precipitation days. Both SAFRAN and Spain02 underestimate high precipitation events.
Xiaodong Gao, Xining Zhao, Luca Brocca, Ting Lv, Gaopeng Huo, and Pute Wu
Hydrol. Earth Syst. Sci. Discuss., https://doi.org/10.5194/hess-2016-617, https://doi.org/10.5194/hess-2016-617, 2016
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We built observation operators by the CDF matching method. Two-year duration was identified as the optimal data length in prediction accuracy. Application in different climates in USA showed these operators are a robust statistical tool for upscaling soil moisture from surface to profile by using exponential filter as a reference method. The findings here may be applied in the prediction of profile soil moisture from surface measurements via remote sensing techniques.
F. Todisco, L. Brocca, L. F. Termite, and W. Wagner
Hydrol. Earth Syst. Sci., 19, 3845–3856, https://doi.org/10.5194/hess-19-3845-2015, https://doi.org/10.5194/hess-19-3845-2015, 2015
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We developed a new formulation of USLE, named Soil Moisture for Erosion (SM4E), that directly incorporates soil moisture information. SM4E is applied here by using modeled data and satellite observations obtained from the Advanced SCATterometer (ASCAT). SM4E is found to outperform USLE and USLE-MM models in silty–clay soil in central Italy. Through satellite data, there is the potential of applying SM4E for large-scale monitoring and quantification of the soil erosion process.
S. Manfreda, L. Brocca, T. Moramarco, F. Melone, and J. Sheffield
Hydrol. Earth Syst. Sci., 18, 1199–1212, https://doi.org/10.5194/hess-18-1199-2014, https://doi.org/10.5194/hess-18-1199-2014, 2014
M. C. Llasat, M. Turco, P. Quintana-Seguí, and M. Llasat-Botija
Nat. Hazards Earth Syst. Sci., 14, 427–441, https://doi.org/10.5194/nhess-14-427-2014, https://doi.org/10.5194/nhess-14-427-2014, 2014
C. Massari, L. Brocca, S. Barbetta, C. Papathanasiou, M. Mimikou, and T. Moramarco
Hydrol. Earth Syst. Sci., 18, 839–853, https://doi.org/10.5194/hess-18-839-2014, https://doi.org/10.5194/hess-18-839-2014, 2014
L. Brocca, S. Liersch, F. Melone, T. Moramarco, and M. Volk
Hydrol. Earth Syst. Sci., 17, 3159–3169, https://doi.org/10.5194/hess-17-3159-2013, https://doi.org/10.5194/hess-17-3159-2013, 2013
Related subject area
Subject: Hydrometeorology | Techniques and Approaches: Remote Sensing and GIS
Historical trends of seasonal droughts in Australia
Evaluation of remote sensing and reanalysis based precipitation products for agro-hydrological studies in semi-arid tropics of Tamil Nadu
Extent of gross underestimation of precipitation in India
A D-vine copula-based quantile regression towards merging satellite precipitation products over rugged topography: a case study in the upper Tekeze–Atbara Basin
Improved soil evaporation remote sensing retrieval algorithms and associated uncertainty analysis on the Tibetan Plateau
Evaluating the accuracy of gridded water resources reanalysis and evapotranspiration products for assessing water security in poorly gauged basins
Attribution of global evapotranspiration trends based on the Budyko framework
The influence of vegetation water dynamics on the ASCAT backscatter–incidence angle relationship in the Amazon
Extrapolating continuous vegetation water content to understand sub-daily backscatter variations
Comprehensive evaluation of satellite-based and reanalysis soil moisture products using in situ observations over China
Variations in surface roughness of heterogeneous surfaces in the Nagqu area of the Tibetan Plateau
Evapotranspiration in the Amazon: spatial patterns, seasonality, and recent trends in observations, reanalysis, and climate models
The benefit of brightness temperature assimilation for the SMAP Level-4 surface and root-zone soil moisture analysis
Evaluation of the dual-polarization weather radar quantitative precipitation estimation using long-term datasets
Validation of SMAP L2 passive-only soil moisture products using upscaled in situ measurements collected in Twente, the Netherlands
Suitability of 17 gridded rainfall and temperature datasets for large-scale hydrological modelling in West Africa
Data-driven estimates of evapotranspiration and its controls in the Congo Basin
Ability of an Australian reanalysis dataset to characterise sub-daily precipitation
A daily 25 km short-latency rainfall product for data-scarce regions based on the integration of the Global Precipitation Measurement mission rainfall and multiple-satellite soil moisture products
Evaluation of soil moisture from CCAM-CABLE simulation, satellite-based models estimates and satellite observations: a case study of Skukuza and Malopeni flux towers
Statistical characteristics of raindrop size distribution during rainy seasons in the Beijing urban area and implications for radar rainfall estimation
An evaluation of daily precipitation from a regional atmospheric reanalysis over Australia
Performance of bias-correction schemes for CMORPH rainfall estimates in the Zambezi River basin
The El Niño event of 2015–2016: climate anomalies and their impact on groundwater resources in East and Southern Africa
Consistency of satellite-based precipitation products in space and over time compared with gauge observations and snow- hydrological modelling in the Lake Titicaca region
Using phase lags to evaluate model biases in simulating the diurnal cycle of evapotranspiration: a case study in Luxembourg
Integrating multiple satellite observations into a coherent dataset to monitor the full water cycle – application to the Mediterranean region
An improved perspective in the spatial representation of soil moisture: potential added value of SMOS disaggregated 1 km resolution “all weather” product
Temporal- and spatial-scale and positional effects on rain erosivity derived from point-scale and contiguous rain data
The PERSIANN family of global satellite precipitation data: a review and evaluation of products
Exploring seasonal and regional relationships between the Evaporative Stress Index and surface weather and soil moisture anomalies across the United States
Development of soil moisture profiles through coupled microwave–thermal infrared observations in the southeastern United States
Evaluation of multiple climate data sources for managing environmental resources in East Africa
Precipitation downscaling using a probability-matching approach and geostationary infrared data: an evaluation over six climate regions
Regional co-variability of spatial and temporal soil moisture–precipitation coupling in North Africa: an observational perspective
Regional evapotranspiration from an image-based implementation of the Surface Temperature Initiated Closure (STIC1.2) model and its validation across an aridity gradient in the conterminous US
Regional frequency analysis of extreme rainfall in Belgium based on radar estimates
An assessment of the performance of global rainfall estimates without ground-based observations
Water–food–energy nexus with changing agricultural scenarios in India during recent decades
Intensity–duration–frequency curves from remote sensing rainfall estimates: comparing satellite and weather radar over the eastern Mediterranean
The effect of satellite-derived surface soil moisture and leaf area index land data assimilation on streamflow simulations over France
Reservoir storage and hydrologic responses to droughts in the Paraná River basin, south-eastern Brazil
Remote sensing algorithm for surface evapotranspiration considering landscape and statistical effects on mixed pixels
Comparison of satellite-based evapotranspiration estimates over the Tibetan Plateau
Evaluation of soil moisture downscaling using a simple thermal-based proxy – the REMEDHUS network (Spain) example
The SPARSE model for the prediction of water stress and evapotranspiration components from thermal infra-red data and its evaluation over irrigated and rainfed wheat
Evaluation of precipitation estimates over CONUS derived from satellite, radar, and rain gauge data sets at daily to annual scales (2002–2012)
Scoping a field experiment: error diagnostics of TRMM precipitation radar estimates in complex terrain as a basis for IPHEx2014
Comparison of rainfall estimations by TRMM 3B42, MPEG and CFSR with ground-observed data for the Lake Tana basin in Ethiopia
Downscaling of seasonal soil moisture forecasts using satellite data
Matthew O. Grant, Anna M. Ukkola, Elisabeth Vogel, Sanaa Hobeichi, Andy J. Pitman, Alex Raymond Borowiak, and Keirnan Fowler
EGUsphere, https://doi.org/10.5194/egusphere-2024-4024, https://doi.org/10.5194/egusphere-2024-4024, 2025
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Australia is regularly subjected to severe and widespread drought. By using multiple drought indicators, we show that while there have been widespread decreases in droughts since the beginning of the 20th century. However, many regions have seen an increase in droughts in more recent decades. Despite these changes, our analysis shows that they remain within the range of observed variability and are not unprecedented in the context of past droughts.
Aatralarasi Saravanan, Daniel Karthe, Selvaprakash Ramalingam, and Niels Schütze
EGUsphere, https://doi.org/10.5194/egusphere-2024-2369, https://doi.org/10.5194/egusphere-2024-2369, 2024
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In water-scarce regions, precipitation is a highly variable and essential resource for crop production. Developing countries like India have an uneven distribution of rain gauges, so reliance on satellite and reanalysis-based precipitation products is critical for their prudent management. Hence, the study statistically evaluated different precipitation products against the station data for water-scarce regions in Tamil Nadu and found that ERA5-Land performed the best, followed by MSWEP.
Gopi Goteti and James Famiglietti
Hydrol. Earth Syst. Sci., 28, 3435–3455, https://doi.org/10.5194/hess-28-3435-2024, https://doi.org/10.5194/hess-28-3435-2024, 2024
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Underestimation of precipitation (UoP) in India is a substantial issue not just within gauge-based precipitation datasets but also within state-of-the-art satellite and reanalysis-based datasets. UoP is prevalent across most river basins of India, including those that have experienced catastrophic flooding in the recent past. This paper highlights not only a major limitation of existing precipitation products for India but also other data-related obstacles faced by the research community.
Mohammed Abdallah, Ke Zhang, Lijun Chao, Abubaker Omer, Khalid Hassaballah, Kidane Welde Reda, Linxin Liu, Tolossa Lemma Tola, and Omar M. Nour
Hydrol. Earth Syst. Sci., 28, 1147–1172, https://doi.org/10.5194/hess-28-1147-2024, https://doi.org/10.5194/hess-28-1147-2024, 2024
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A D-vine copula-based quantile regression (DVQR) model is used to merge satellite precipitation products. The performance of the DVQR model is compared with the simple model average and one-outlier-removed average methods. The nonlinear DVQR model outperforms the quantile-regression-based multivariate linear and Bayesian model averaging methods.
Jin Feng, Ke Zhang, Huijie Zhan, and Lijun Chao
Hydrol. Earth Syst. Sci., 27, 363–383, https://doi.org/10.5194/hess-27-363-2023, https://doi.org/10.5194/hess-27-363-2023, 2023
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Here we improved a satellite-driven evaporation algorithm by introducing the modified versions of the two constraint schemes. The two moisture constraint schemes largely improved the evaporation estimation on two barren-dominated basins of the Tibetan Plateau. Investigation of moisture constraint uncertainty showed that high-quality soil moisture can optimally represent moisture, and more accessible precipitation data generally help improve the estimation of barren evaporation.
Elias Nkiaka, Robert G. Bryant, Joshua Ntajal, and Eliézer I. Biao
Hydrol. Earth Syst. Sci., 26, 5899–5916, https://doi.org/10.5194/hess-26-5899-2022, https://doi.org/10.5194/hess-26-5899-2022, 2022
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Achieving water security in poorly gauged regions is hindered by a lack of in situ hydrometeorological data. In this study, we validated nine existing gridded water resource reanalyses and eight evapotranspiration products in eight representative gauged basins in Central–West Africa. Our results show the strengths and and weaknesses of the existing products and that these products can be used to assess water security in ungauged basins. However, it is imperative to validate these products.
Shijie Li, Guojie Wang, Chenxia Zhu, Jiao Lu, Waheed Ullah, Daniel Fiifi Tawia Hagan, Giri Kattel, and Jian Peng
Hydrol. Earth Syst. Sci., 26, 3691–3707, https://doi.org/10.5194/hess-26-3691-2022, https://doi.org/10.5194/hess-26-3691-2022, 2022
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We found that the precipitation variability dominantly controls global evapotranspiration (ET) in dry climates, while the net radiation has substantial control over ET in the tropical regions, and vapor pressure deficit (VPD) impacts ET trends in boreal mid-latitude climate. The critical role of VPD in controlling ET trends is particularly emphasized due to its influence in controlling the carbon–water–energy cycle.
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
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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.
Paul C. Vermunt, Susan C. Steele-Dunne, Saeed Khabbazan, Jasmeet Judge, and Nick C. van de Giesen
Hydrol. Earth Syst. Sci., 26, 1223–1241, https://doi.org/10.5194/hess-26-1223-2022, https://doi.org/10.5194/hess-26-1223-2022, 2022
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This study investigates the use of hydrometeorological sensors to reconstruct variations in internal vegetation water content of corn and relates these variations to the sub-daily behaviour of polarimetric L-band backscatter. The results show significant sensitivity of backscatter to the daily cycles of vegetation water content and dew, particularly on dry days and for vertical and cross-polarizations, which demonstrates the potential for using radar for studies on vegetation water dynamics.
Xiaolu Ling, Ying Huang, Weidong Guo, Yixin Wang, Chaorong Chen, Bo Qiu, Jun Ge, Kai Qin, Yong Xue, and Jian Peng
Hydrol. Earth Syst. Sci., 25, 4209–4229, https://doi.org/10.5194/hess-25-4209-2021, https://doi.org/10.5194/hess-25-4209-2021, 2021
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Soil moisture (SM) plays a critical role in the water and energy cycles of the Earth system, for which a long-term SM product with high quality is urgently needed. In situ observations are generally treated as the true value to systematically evaluate five SM products, including one remote sensing product and four reanalysis data sets during 1981–2013. This long-term intercomparison study provides clues for SM product enhancement and further hydrological applications.
Maoshan Li, Xiaoran Liu, Lei Shu, Shucheng Yin, Lingzhi Wang, Wei Fu, Yaoming Ma, Yaoxian Yang, and Fanglin Sun
Hydrol. Earth Syst. Sci., 25, 2915–2930, https://doi.org/10.5194/hess-25-2915-2021, https://doi.org/10.5194/hess-25-2915-2021, 2021
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In this study, using MODIS satellite data and site atmospheric turbulence observation data in the Nagqu area of the northern Tibetan Plateau, with the Massman-retrieved model and a single height observation to determine aerodynamic surface roughness, temporal and spatial variation characteristics of the surface roughness were analyzed. The result is feasible, and it can be applied to improve the model parameters of the land surface model and the accuracy of model simulation in future work.
Jessica C. A. Baker, Luis Garcia-Carreras, Manuel Gloor, John H. Marsham, Wolfgang Buermann, Humberto R. da Rocha, Antonio D. Nobre, Alessandro Carioca de Araujo, and Dominick V. Spracklen
Hydrol. Earth Syst. Sci., 25, 2279–2300, https://doi.org/10.5194/hess-25-2279-2021, https://doi.org/10.5194/hess-25-2279-2021, 2021
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Evapotranspiration (ET) is a vital part of the Amazon water cycle, but it is difficult to measure over large areas. In this study, we compare spatial patterns, seasonality, and recent trends in Amazon ET from a water-budget analysis with estimates from satellites, reanalysis, and global climate models. We find large differences between products, showing that many widely used datasets and climate models may not provide a reliable representation of this crucial variable over the Amazon.
Jianxiu Qiu, Jianzhi Dong, Wade T. Crow, Xiaohu Zhang, Rolf H. Reichle, and Gabrielle J. M. De Lannoy
Hydrol. Earth Syst. Sci., 25, 1569–1586, https://doi.org/10.5194/hess-25-1569-2021, https://doi.org/10.5194/hess-25-1569-2021, 2021
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The SMAP L4 dataset has been extensively used in hydrological applications. We innovatively use a machine learning method to analyze how the efficiency of the L4 data assimilation (DA) system is determined. It shows that DA efficiency is mainly related to Tb innovation, followed by error in precipitation forcing and microwave soil roughness. Since the L4 system can effectively filter out precipitation error, future development should focus on correctly specifying the SSM–RZSM coupling strength.
Tanel Voormansik, Roberto Cremonini, Piia Post, and Dmitri Moisseev
Hydrol. Earth Syst. Sci., 25, 1245–1258, https://doi.org/10.5194/hess-25-1245-2021, https://doi.org/10.5194/hess-25-1245-2021, 2021
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A long set of operational polarimetric weather radar rainfall accumulations from Estonia and Italy are generated and investigated. Results show that the combined product of specific differential phase and horizontal reflectivity yields the best results when compared to rain gauge measurements. The specific differential-phase-based product overestimates weak precipitation, and the horizontal-reflectivity-based product underestimates heavy rainfall in all analysed accumulation periods.
Rogier van der Velde, Andreas Colliander, Michiel Pezij, Harm-Jan F. Benninga, Rajat Bindlish, Steven K. Chan, Thomas J. Jackson, Dimmie M. D. Hendriks, Denie C. M. Augustijn, and Zhongbo Su
Hydrol. Earth Syst. Sci., 25, 473–495, https://doi.org/10.5194/hess-25-473-2021, https://doi.org/10.5194/hess-25-473-2021, 2021
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NASA’s SMAP satellite provides estimates of the amount of water in the soil. With measurements from a network of 20 monitoring stations, the accuracy of these estimates has been studied for a 4-year period. We found an agreement between satellite and in situ estimates in line with the mission requirements once the large mismatches associated with rapidly changing water contents, e.g. soil freezing and rainfall, are excluded.
Moctar Dembélé, Bettina Schaefli, Nick van de Giesen, and Grégoire Mariéthoz
Hydrol. Earth Syst. Sci., 24, 5379–5406, https://doi.org/10.5194/hess-24-5379-2020, https://doi.org/10.5194/hess-24-5379-2020, 2020
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This study evaluates 102 combinations of rainfall and temperature datasets from satellite and reanalysis sources as input to a fully distributed hydrological model. The model is recalibrated for each input dataset, and the outputs are evaluated with streamflow, evaporation, soil moisture and terrestrial water storage data. Results show that no single rainfall or temperature dataset consistently ranks first in reproducing the spatio-temporal variability of all hydrological processes.
Michael W. Burnett, Gregory R. Quetin, and Alexandra G. Konings
Hydrol. Earth Syst. Sci., 24, 4189–4211, https://doi.org/10.5194/hess-24-4189-2020, https://doi.org/10.5194/hess-24-4189-2020, 2020
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Water that evaporates from Africa's tropical forests provides rainfall throughout the continent. However, there are few sources of meteorological data in central Africa, so we use observations from satellites to estimate evaporation from the Congo Basin at different times of the year. We find that existing evaporation estimates in tropical Africa do not accurately capture seasonal variations in evaporation and that fluctuations in soil moisture and solar radiation drive evaporation rates.
Suwash Chandra Acharya, Rory Nathan, Quan J. Wang, Chun-Hsu Su, and Nathan Eizenberg
Hydrol. Earth Syst. Sci., 24, 2951–2962, https://doi.org/10.5194/hess-24-2951-2020, https://doi.org/10.5194/hess-24-2951-2020, 2020
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BARRA is a high-resolution reanalysis dataset over the Oceania region. This study evaluates the performance of sub-daily BARRA precipitation at point and spatial scales over Australia. We find that the dataset reproduces some of the sub-daily characteristics of precipitation well, although it exhibits some spatial displacement errors, and it performs better in temperate than in tropical regions. The product is well suited to complement other estimates derived from remote sensing and rain gauges.
Christian Massari, Luca Brocca, Thierry Pellarin, Gab Abramowitz, Paolo Filippucci, Luca Ciabatta, Viviana Maggioni, Yann Kerr, and Diego Fernandez Prieto
Hydrol. Earth Syst. Sci., 24, 2687–2710, https://doi.org/10.5194/hess-24-2687-2020, https://doi.org/10.5194/hess-24-2687-2020, 2020
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Rain gauges are unevenly spaced around the world with extremely low gauge density over places like Africa and South America. Here, water-related problems like floods, drought and famine are particularly severe and able to cause fatalities, migration and diseases. We have developed a rainfall dataset that exploits the synergies between rainfall and soil moisture to provide accurate rainfall observations which can be used to face these problems.
Floyd Vukosi Khosa, Mohau Jacob Mateyisi, Martina Reynita van der Merwe, Gregor Timothy Feig, Francois Alwyn Engelbrecht, and Michael John Savage
Hydrol. Earth Syst. Sci., 24, 1587–1609, https://doi.org/10.5194/hess-24-1587-2020, https://doi.org/10.5194/hess-24-1587-2020, 2020
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The paper evaluates soil moisture outputs from three structurally distinct models against in situ data. Our goal is to find how representative the model outputs are for site and region. This is a question of interest as some of the models have a specific regional focus on their inceptions. Much focus is placed on how the models capture the soil moisture signal. We find that there is agreement on seasonal patterns between the models and observations with a tolerable level of model uncertainty.
Yu Ma, Guangheng Ni, Chandrasekar V. Chandra, Fuqiang Tian, and Haonan Chen
Hydrol. Earth Syst. Sci., 23, 4153–4170, https://doi.org/10.5194/hess-23-4153-2019, https://doi.org/10.5194/hess-23-4153-2019, 2019
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Raindrop size distribution (DSD) information is fundamental in understanding the precipitation microphysics and quantitative precipitation estimation. This study extensively investigates the DSD characteristics during rainy seasons in the Beijing urban area using 5-year DSD observations from a Parsivel2 disdrometer. The statistical distributions of DSD parameters are examined and the polarimetric radar rainfall algorithms are derived to support the ongoing development of an X-band radar network.
Suwash Chandra Acharya, Rory Nathan, Quan J. Wang, Chun-Hsu Su, and Nathan Eizenberg
Hydrol. Earth Syst. Sci., 23, 3387–3403, https://doi.org/10.5194/hess-23-3387-2019, https://doi.org/10.5194/hess-23-3387-2019, 2019
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BARRA is a novel regional reanalysis for Australia. Our research demonstrates that it is able to characterize a rich spatial variation in daily precipitation behaviour. In addition, its ability to represent large rainfalls is valuable for the analysis of extremes. It is a useful complement to existing precipitation datasets for Australia, especially in sparsely gauged regions.
Webster Gumindoga, Tom H. M. Rientjes, Alemseged Tamiru Haile, Hodson Makurira, and Paolo Reggiani
Hydrol. Earth Syst. Sci., 23, 2915–2938, https://doi.org/10.5194/hess-23-2915-2019, https://doi.org/10.5194/hess-23-2915-2019, 2019
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We evaluate the influence of elevation and distance from large-scale open water bodies on bias for CMORPH satellite rainfall in the Zambezi basin. Effects of distance > 10 km from water bodies are minimal, whereas the effects at shorter distances are indicated but are not conclusive for lack of rain gauges. Taylor diagrams show station elevation influencing CMORPH performance. The
spatio-temporaland newly developed
elevation zonebias schemes proved more effective in removing CMORPH bias.
Seshagiri Rao Kolusu, Mohammad Shamsudduha, Martin C. Todd, Richard G. Taylor, David Seddon, Japhet J. Kashaigili, Girma Y. Ebrahim, Mark O. Cuthbert, James P. R. Sorensen, Karen G. Villholth, Alan M. MacDonald, and Dave A. MacLeod
Hydrol. Earth Syst. Sci., 23, 1751–1762, https://doi.org/10.5194/hess-23-1751-2019, https://doi.org/10.5194/hess-23-1751-2019, 2019
Frédéric Satgé, Denis Ruelland, Marie-Paule Bonnet, Jorge Molina, and Ramiro Pillco
Hydrol. Earth Syst. Sci., 23, 595–619, https://doi.org/10.5194/hess-23-595-2019, https://doi.org/10.5194/hess-23-595-2019, 2019
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This paper assesses the potential of satellite precipitation estimates (SPEs) for precipitation measurement and hydrological and snow modelling. A total of 12 SPEs is considered to provide a global overview of available SPE accuracy for users interested in such datasets. Results show that, over poorly monitored regions, SPEs represent a very efficient alternative to traditional precipitation gauges to follow precipitation in time and space and for hydrological and snow modelling.
Maik Renner, Claire Brenner, Kaniska Mallick, Hans-Dieter Wizemann, Luigi Conte, Ivonne Trebs, Jianhui Wei, Volker Wulfmeyer, Karsten Schulz, and Axel Kleidon
Hydrol. Earth Syst. Sci., 23, 515–535, https://doi.org/10.5194/hess-23-515-2019, https://doi.org/10.5194/hess-23-515-2019, 2019
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We estimate the phase lag of surface states and heat fluxes to incoming solar radiation at the sub-daily timescale. While evapotranspiration reveals a minor phase lag, the vapor pressure deficit used as input by Penman–Monteith approaches shows a large phase lag. The surface-to-air temperature gradient used by energy balance residual approaches shows a small phase shift in agreement with the sensible heat flux and thus explains the better correlation of these models at the sub-daily timescale.
Victor Pellet, Filipe Aires, Simon Munier, Diego Fernández Prieto, Gabriel Jordá, Wouter Arnoud Dorigo, Jan Polcher, and Luca Brocca
Hydrol. Earth Syst. Sci., 23, 465–491, https://doi.org/10.5194/hess-23-465-2019, https://doi.org/10.5194/hess-23-465-2019, 2019
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This study is an effort for a better understanding and quantification of the water cycle and related processes in the Mediterranean region, by dealing with satellite products and their uncertainties. The aims of the paper are 3-fold: (1) developing methods with hydrological constraints to integrate all the datasets, (2) giving the full picture of the Mediterranean WC, and (3) building a model-independent database that can evaluate the numerous regional climate models (RCMs) for this region.
Samiro Khodayar, Amparo Coll, and Ernesto Lopez-Baeza
Hydrol. Earth Syst. Sci., 23, 255–275, https://doi.org/10.5194/hess-23-255-2019, https://doi.org/10.5194/hess-23-255-2019, 2019
Franziska K. Fischer, Tanja Winterrath, and Karl Auerswald
Hydrol. Earth Syst. Sci., 22, 6505–6518, https://doi.org/10.5194/hess-22-6505-2018, https://doi.org/10.5194/hess-22-6505-2018, 2018
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The potential of rain to cause soil erosion by runoff is called rain erosivity. Rain erosivity is highly variable in space and time even over distances of less than 1 km. Contiguously measured radar rain data depict for the first time this spatio-temporal variation, but scaling factors are required to account for differences in spatial and temporal resolution compared to rain gauge data. These scaling factors were obtained from more than 2 million erosive events.
Phu Nguyen, Mohammed Ombadi, Soroosh Sorooshian, Kuolin Hsu, Amir AghaKouchak, Dan Braithwaite, Hamed Ashouri, and Andrea Rose Thorstensen
Hydrol. Earth Syst. Sci., 22, 5801–5816, https://doi.org/10.5194/hess-22-5801-2018, https://doi.org/10.5194/hess-22-5801-2018, 2018
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The goal of this article is to first provide an overview of the available PERSIANN precipitation retrieval algorithms and their differences. We evaluate the products over CONUS at different spatial and temporal scales using CPC data. Daily scale is the finest temporal scale used for the evaluation over CONUS. We provide a comparison of the available products at a quasi-global scale. We highlight the strengths and limitations of the PERSIANN products.
Jason A. Otkin, Yafang Zhong, David Lorenz, Martha C. Anderson, and Christopher Hain
Hydrol. Earth Syst. Sci., 22, 5373–5386, https://doi.org/10.5194/hess-22-5373-2018, https://doi.org/10.5194/hess-22-5373-2018, 2018
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Correlation analyses were used to explore relationships between the Evaporative Stress Index (ESI) – which depicts anomalies in evapotranspiration (ET) – and various land and atmospheric variables that impact ET. The results revealed that the ESI is more strongly correlated to anomalies in soil moisture and near-surface vapor pressure deficit than to precipitation and temperature anomalies. Large regional and seasonal dependencies in the strengths of the correlations were also observed.
Vikalp Mishra, James F. Cruise, Christopher R. Hain, John R. Mecikalski, and Martha C. Anderson
Hydrol. Earth Syst. Sci., 22, 4935–4957, https://doi.org/10.5194/hess-22-4935-2018, https://doi.org/10.5194/hess-22-4935-2018, 2018
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Multiple satellite observations can be used for surface and subsurface soil moisture estimations. In this study, satellite observations along with a mathematical model were used to distribute and develop multiyear soil moisture profiles over the southeastern US. Such remotely sensed profiles become particularly useful at large spatiotemporal scales, can be a significant tool in data-scarce regions of the world, can complement various land and crop models, and can act as drought indicators etc.
Solomon Hailu Gebrechorkos, Stephan Hülsmann, and Christian Bernhofer
Hydrol. Earth Syst. Sci., 22, 4547–4564, https://doi.org/10.5194/hess-22-4547-2018, https://doi.org/10.5194/hess-22-4547-2018, 2018
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In Africa field-based meteorological data are scarce; therefore global data sources based on remote sensing and climate models are often used as alternatives. To assess their suitability for a large and topographically complex area in East Africa, we evaluated multiple climate data products with available ground station data at multiple timescales over 21 regions. The comprehensive evaluation resulted in identification of preferential data sources to be used for climate and hydrological studies.
Ruifang Guo, Yuanbo Liu, Han Zhou, and Yaqiao Zhu
Hydrol. Earth Syst. Sci., 22, 3685–3699, https://doi.org/10.5194/hess-22-3685-2018, https://doi.org/10.5194/hess-22-3685-2018, 2018
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Existing satellite products are often insufficient for use in small-scale (< 10 km) hydrological and meteorological studies. We propose a new approach based on the cumulative distribution of frequency to downscale satellite precipitation products with geostationary (GEO) data. This paper uses CMORPH and FY2-E GEO data to examine the approach in six different climate regions. The downscaled precipitation performed better for convective systems.
Irina Y. Petrova, Chiel C. van Heerwaarden, Cathy Hohenegger, and Françoise Guichard
Hydrol. Earth Syst. Sci., 22, 3275–3294, https://doi.org/10.5194/hess-22-3275-2018, https://doi.org/10.5194/hess-22-3275-2018, 2018
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In North Africa rain storms can be as vital as they are devastating. The present study uses multi-year satellite data to better understand how and where soil moisture conditions affect development of rainfall in the area. Our results reveal two major regions in the southwest and southeast, where drier soils show higher potential to cause rainfall development. This knowledge is essential for the hydrological sector, and can be further used by models to improve prediction of rainfall and droughts.
Nishan Bhattarai, Kaniska Mallick, Nathaniel A. Brunsell, Ge Sun, and Meha Jain
Hydrol. Earth Syst. Sci., 22, 2311–2341, https://doi.org/10.5194/hess-22-2311-2018, https://doi.org/10.5194/hess-22-2311-2018, 2018
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We report the first ever regional-scale implementation of the Surface Temperature Initiated Closure (STIC1.2) model for mapping evapotranspiration (ET) using MODIS land surface and gridded climate datasets to overcome the existing uncertainties in aerodynamic temperature and conductance estimation in global ET models. Validation and intercomparison with SEBS and MOD16 products across an aridity gradient in the US manifested better ET mapping potential of STIC1.2 in different climates and biomes.
Edouard Goudenhoofdt, Laurent Delobbe, and Patrick Willems
Hydrol. Earth Syst. Sci., 21, 5385–5399, https://doi.org/10.5194/hess-21-5385-2017, https://doi.org/10.5194/hess-21-5385-2017, 2017
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Knowing the characteristics of extreme precipitation is useful for flood management applications like sewer system design. The potential of a 12-year high-quality weather radar precipitation dataset is investigated by comparison with rain gauges. Despite known limitations, a good agreement is found between the radar and the rain gauges. Using the radar data allow us to reduce the uncertainty of the extreme value analysis, especially for short duration extremes related to thunderstorms.
Christian Massari, Wade Crow, and Luca Brocca
Hydrol. Earth Syst. Sci., 21, 4347–4361, https://doi.org/10.5194/hess-21-4347-2017, https://doi.org/10.5194/hess-21-4347-2017, 2017
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The paper explores a method for the assessment of the performance of global rainfall estimates without relying on ground-based observations. Thanks to this method, different global correlation maps are obtained (for the first time without relying on a benchmark dataset) for some of the most used globally available rainfall products. This is central for hydroclimatic studies within data-scarce regions, where ground observations are scarce to evaluate the relative quality of a rainfall product
Beas Barik, Subimal Ghosh, A. Saheer Sahana, Amey Pathak, and Muddu Sekhar
Hydrol. Earth Syst. Sci., 21, 3041–3060, https://doi.org/10.5194/hess-21-3041-2017, https://doi.org/10.5194/hess-21-3041-2017, 2017
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The article summarises changing patterns of the water-food-energy nexus in India during recent decades. The work first analyses satellite data of water storage with a validation using the observed well data. Northern India shows a declining trend of water storage and western-central India shows an increasing trend of the same. Major droughts result in a drop in water storage which is not recovered due to uncontrolled ground water irrigation for agricultural activities even in good monsoon years.
Francesco Marra, Efrat Morin, Nadav Peleg, Yiwen Mei, and Emmanouil N. Anagnostou
Hydrol. Earth Syst. Sci., 21, 2389–2404, https://doi.org/10.5194/hess-21-2389-2017, https://doi.org/10.5194/hess-21-2389-2017, 2017
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Rainfall frequency analyses from radar and satellite estimates over the eastern Mediterranean are compared examining different climatic conditions. Correlation between radar and satellite results is high for frequent events and decreases with return period. The uncertainty related to record length is larger for drier climates. The agreement between different sensors instills confidence on their use for rainfall frequency analysis in ungauged areas of the Earth.
David Fairbairn, Alina Lavinia Barbu, Adrien Napoly, Clément Albergel, Jean-François Mahfouf, and Jean-Christophe Calvet
Hydrol. Earth Syst. Sci., 21, 2015–2033, https://doi.org/10.5194/hess-21-2015-2017, https://doi.org/10.5194/hess-21-2015-2017, 2017
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This study assesses the impact on river discharge simulations over France of assimilating ASCAT-derived surface soil moisture (SSM) and leaf area index (LAI) observations into the ISBA land surface model. Wintertime LAI has a notable impact on river discharge. SSM assimilation degrades river discharge simulations. This is caused by limitations in the simplified versions of the Kalman filter and ISBA model used in this study. Implementing an observation operator for ASCAT is needed.
Davi de C. D. Melo, Bridget R. Scanlon, Zizhan Zhang, Edson Wendland, and Lei Yin
Hydrol. Earth Syst. Sci., 20, 4673–4688, https://doi.org/10.5194/hess-20-4673-2016, https://doi.org/10.5194/hess-20-4673-2016, 2016
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Drought propagation from rainfall deficits to reservoir depletion was studied based on remote sensing, monitoring and modelling data. Regional droughts were shown by widespread depletion in total water storage that reduced soil moisture storage and runoff, greatly reducing reservoir storage. The multidisciplinary approach to drought assessment shows the linkages between meteorological and hydrological droughts that are essential for managing water resources subjected to climate extremes.
Zhi Qing Peng, Xiaozhou Xin, Jin Jun Jiao, Ti Zhou, and Qinhuo Liu
Hydrol. Earth Syst. Sci., 20, 4409–4438, https://doi.org/10.5194/hess-20-4409-2016, https://doi.org/10.5194/hess-20-4409-2016, 2016
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A remote sensing algorithm named temperature sharpening and flux aggregation (TSFA) was applied to HJ-1B satellite data to estimate evapotranspiration over heterogeneous surface considering landscape and statistical effects on mixed pixels. Footprint validation results showed TSFA was more accurate and less uncertain than other two upscaling methods. Additional analysis and comparison showed TSFA can capture land surface heterogeneities and integrate the effect of landscapes within mixed pixels.
Jian Peng, Alexander Loew, Xuelong Chen, Yaoming Ma, and Zhongbo Su
Hydrol. Earth Syst. Sci., 20, 3167–3182, https://doi.org/10.5194/hess-20-3167-2016, https://doi.org/10.5194/hess-20-3167-2016, 2016
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The Tibetan Plateau plays a major role in regional and global climate. The knowledge of latent heat flux can help to better describe the complex interactions between land and atmosphere. The purpose of this paper is to provide a detailed cross-comparison of existing latent heat flux products over the TP. The results highlight the recently developed latent heat product – High Resolution Land Surface Parameters from Space (HOLAPS).
J. Peng, J. Niesel, and A. Loew
Hydrol. Earth Syst. Sci., 19, 4765–4782, https://doi.org/10.5194/hess-19-4765-2015, https://doi.org/10.5194/hess-19-4765-2015, 2015
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This paper gives a comprehensive evaluation of a simple newly developed downscaling scheme using in situ measurements from REMEDHUS network, a first cross-comparison of the performance of the downscaled soil moisture from MODIS and MSG SEVIRI, an evaluation of the performance of the downscaled soil moisture at different spatial resolutions, and an exploration of the influence of LST, vegetation index, terrain, clouds, and land cover heterogeneity on the performance of VTCI.
G. Boulet, B. Mougenot, J.-P. Lhomme, P. Fanise, Z. Lili-Chabaane, A. Olioso, M. Bahir, V. Rivalland, L. Jarlan, O. Merlin, B. Coudert, S. Er-Raki, and J.-P. Lagouarde
Hydrol. Earth Syst. Sci., 19, 4653–4672, https://doi.org/10.5194/hess-19-4653-2015, https://doi.org/10.5194/hess-19-4653-2015, 2015
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The paper presents a new model (SPARSE) to estimate total evapotranspiration as well as its components (evaporation and transpiration) from remote-sensing data in the thermal infra-red domain. The limits of computing two unknowns (evaporation and transpiration) out of one piece of information (one surface temperature) are assessed theoretically. The model performance in retrieving the components as well as the water stress is assessed for two wheat crops (one irrigated and one rainfed).
O. P. Prat and B. R. Nelson
Hydrol. Earth Syst. Sci., 19, 2037–2056, https://doi.org/10.5194/hess-19-2037-2015, https://doi.org/10.5194/hess-19-2037-2015, 2015
Y. Duan, A. M. Wilson, and A. P. Barros
Hydrol. Earth Syst. Sci., 19, 1501–1520, https://doi.org/10.5194/hess-19-1501-2015, https://doi.org/10.5194/hess-19-1501-2015, 2015
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A diagnostic analysis of the space-time structure of error in quantitative precipitation estimates (QPEs) from the precipitation radar on the Tropical Rainfall Measurement Mission satellite is presented here in preparation for the Integrated Precipitation and Hydrology Experiment (IPHEx) in 2014. A high-density raingauge network over the southern Appalachians allows for direct comparison between ground-based measurements and satellite-based QPE (PR 2A25 Version 7 with 5 years of data 2008-2013).
A. W. Worqlul, B. Maathuis, A. A. Adem, S. S. Demissie, S. Langan, and T. S. Steenhuis
Hydrol. Earth Syst. Sci., 18, 4871–4881, https://doi.org/10.5194/hess-18-4871-2014, https://doi.org/10.5194/hess-18-4871-2014, 2014
S. Schneider, A. Jann, and T. Schellander-Gorgas
Hydrol. Earth Syst. Sci., 18, 2899–2905, https://doi.org/10.5194/hess-18-2899-2014, https://doi.org/10.5194/hess-18-2899-2014, 2014
Cited articles
Abdollahipour, A., Ahmadi, H., and Aminnejad, B.: A review of downscaling
methods of satellite-based precipitation estimates, Earth. Sci. Inform., 15, 1–20, https://doi.org/10.1007/s12145-021-00669-4, 2021.
Baez-Villanueva, O. M., Zambrano-Bigiarini, M., Beck, H. E., McNamara, I.,
Ribbe, L., Nauditt, A., Birkel, C., Verbist, K., Giraldo-Osorio, J. D., and
Thinh, N. X.: RF-MEP: A novel Random Forest method for merging gridded
precipitation products and ground-based measurements, Remote Sens. Environ.,
239, 111606, https://doi.org/10.1016/j.rse.2019.111606, 2020.
Bezak, N., Borrelli, P., and Panagos, P.: Exploring the possible role of
satellite-based rainfall data in estimating inter- and intra-annual global
rainfall erosivity, Hydrol. Earth Syst. Sci., 26, 1907–1924, https://doi.org/10.5194/hess-26-1907-2022, 2022.
Birtwistle, A. N., Laituri, M., Bledsoe, B., and Friedman, J. M.: Using NDVI
to measure precipitation in semi-arid landscapes, J. Arid Environ., 131, 15–24, https://doi.org/10.1016/j.jaridenv.2016.04.004, 2016.
Brocca, L., Moramarco, T., Melone, F., and Wagner, W.: A new method for
rainfall estimation through soil moisture observations, Geophys. Res. Lett.,
40, 853–858, https://doi.org/10.1002/grl.50173, 2013.
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.-Atmos., 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., Pellarin, T., Crow, W. T., Ciabatta, L., Massari, C., Ryu, D.,
Su, C. H., Rüdiger, C., and Kerr, Y.: Rainfall estimation by inverting
SMOS soil moisture estimates: A comparison of different methods over Australia, J. Geophys. Res.-Atmos., 121, 12062–12079, https://doi.org/10.1002/2016JD025382, 2016.
Brocca, L., Filippucci, P., Hahn, S., Ciabatta, L., Massari, C., Camici, S.,
Schüller, L., Bojkov, B., and Wagner, W.: SM2RAIN–ASCAT (2007–2018):
global daily satellite rainfall data from ASCAT soil moisture observations,
Earth Syst. Sci. Data., 11, 1583–1601, https://doi.org/10.5194/essd-11-1583-2019, 2019.
Carpintero, E., Mateos, L., Andreu, A., and González-Dugo, M. P.: Effect
of the differences in spectral response of Mediterranean tree canopies on
the estimation of evapotranspiration using vegetation index-based crop
coefficients, Agr. Water Manage., 238, 106201, https://doi.org/10.1016/j.agwat.2020.106201, 2020.
Chao, L., Zhang, K., Li, Z., Zhu, Y., Wang, J., and Yu, Z.: Geographically
weighted regression based methods for merging satellite and gauge
precipitation, J. Hydrol., 558, 275–289, https://doi.org/10.1016/j.jhydrol.2018.01.042, 2018.
Chen, F., Crow, W., and Holmes, T. R.: Improving long-term, retrospective
precipitation datasets using satellite-based surface soil moisture retrievals and the soil moisture analysis rainfall tool, J. Appl. Remote Sens., 6, 063604, https://doi.org/10.1117/1.JRS.6.063604, 2012.
Chen, S., Xiong, L., Ma, Q., Kim, J.-S., Chen, J., and Xu, C.-Y.: Improving
daily spatial precipitation estimates by merging gauge observation with
multiple satellite-based precipitation products based on the geographically
weighted ridge regression method, J. Hydrol., 589, 125156, https://doi.org/10.1016/j.jhydrol.2020.125156, 2020.
Chen, Y., Huang, J., Sheng, S., Mansaray, L. R., Liu, Z., Wu, H., and Wang,
X.: A new downscaling-integration framework for high-resolution monthly
precipitation estimates: Combining rain gauge observations, satellite-derived precipitation data and geographical ancillary data, Remote Sens. Environ., 214, 154–172, https://doi.org/10.1016/j.rse.2018.05.021, 2018.
Ciabatta, L., Marra, A. C., Panegrossi, G., Casella, D., Sanò, P., Dietrich, S., Massari, C., and Brocca, L.: Daily precipitation estimation
through different microwave sensors: Verification study over Italy, J. Hydrol., 545, 436–450, https://doi.org/10.1016/j.jhydrol.2016.12.057, 2017.
Ciabatta, L., Massari, C., Brocca, L., Gruber, A., Reimer, C., Hahn, S.,
Paulik, C., Dorigo, W., Kidd, R., and Wagner, W.: SM2RAIN-CCI: a new global
long-term rainfall data set derived from ESA CCI soil moisture, Earth Syst.
Sci. Data., 10, 267–280, https://doi.org/10.5194/essd-10-267-2018, 2018.
Colliander, A., Jackson, T. J., Bindlish, R., Chan, S., Das, N., Kim, S.,
Cosh, M., Dunbar, R., Dang, L., and Pashaian, L.: Validation of SMAP surface
soil moisture products with core validation sites, Remote Sens. Environ., 191, 215–231, https://doi.org/10.1016/j.rse.2017.01.021, 2017.
Dorigo, W., Wagner, W., Albergel, C., Albrecht, F., Balsamo, G., Brocca, L.,
Chung, D., Ertl, M., Forkel, M., Gruber, A., Haas, E., Hamer, P. D., Hirschi, M., Ikonen, J., de Jeu, R., Kidd, R., Lahoz, W., Liu, Y. Y., Miralles, D., Mistelbauer, T., Nicolai-Shaw, N., Parinussa, R., Pratola, C., Reimer, C., van der Schalie, R., Seneviratne, S. I., Smolander, T., and Lecomte, P.: ESA CCI Soil Moisture for improved Earth system understanding: State-of-the art and future directions, Remote Sens. Environ., 203, 185–215,
https://doi.org/10.1016/j.rse.2017.07.001, 2017.
Duan, Z. and Bastiaanssen, W.: First results from Version 7 TRMM 3B43
precipitation product in combination with a new downscaling–calibration
procedure, Remote Sens. Environ., 131, 1–13, https://doi.org/10.1016/j.rse.2012.12.002, 2013.
Ebrahimy, H. and Azadbakht, M.: Downscaling MODIS land surface temperature
over a heterogeneous area: An investigation of machine learning techniques,
feature selection, and impacts of mixed pixels, Comput. Geosci.-UK, 124,
93–102, https://doi.org/10.1016/j.cageo.2019.01.004, 2019.
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.
Fan, Y., Ma, Z., Ma, Y., Ma, W., Xie, Z., Ding, L., Han, Y., Hu, W., and Su,
R.: Respective Advantages of “Top-Down” Based GPM IMERG and “Bottom-Up”
Based SM2RAIN-ASCAT Precipitation Products Over the Tibetan Plateau, J.
Geophys. Res.-Atmos., 126, e2020JD033946, https://doi.org/10.1029/2020JD033946, 2021.
Gruber, A., Scanlon, T., van der Schalie, R., Wagner, W., and Dorigo, W.:
Evolution of the ESA CCI Soil Moisture climate data records and their
underlying merging methodology, Earth Syst. Sci. Data, 11, 717–739,
https://doi.org/10.5194/essd-11-717-2019, 2019.
Guo, X., Guo, Cui, P., Chen, X., Li, Y., Zhang, J., and Sun, Y.: Spatial
uncertainty of rainfall and its impact on hydrological hazard forecasting in
a small semiarid mountainous watershed, J. Hydrol., 595, 126049, https://doi.org/10.1016/j.jhydrol.2021.126049, 2021.
Haylock, M. R., Cawley, G. C., Harpham, C., Wilby, R. L., and Goodess, C. M.: Downscaling heavy precipitation over the United Kingdom: a comparison of dynamical and statistical methods and their future scenarios, Int. J. Climatol., 26, 1397–1415, https://doi.org/10.1002/joc.1318, 2006.
He, K.: High-resolution soil moisture data (1 km) [Data set]. In Hydrology and Earth System Sciences (Version 1), Zenodo [data set], https://doi.org/10.5281/zenodo.7451422, 2022.
He, X., Chaney, N. W., Schleiss, M., and Sheffield, J.: Spatial downscaling
of precipitation using adaptable random forests, Water Resour. Res., 52,
8217–8237, https://doi.org/10.1002/2016WR019034, 2016.
Hong, Z., Han, Z., Li, X., Long, D., Tang, G., and Wang, J.: Generation of
an improved precipitation dataset from multisource information over the
Tibetan Plateau, J. Hydrometeorol., 22, 1275–1295, https://doi.org/10.1175/JHM-D-20-0252.1, 2021.
Hou, A. Y., Kakar, R. K., Neeck, S., Azarbarzin, A. A., Kummerow, C. D.,
Kojima, M., Oki, R., Nakamura, K., and Iguchi, T.: The Global Precipitation
Measurement Mission, B. Am. Meteorol. Soc., 95, 701–722, https://doi.org/10.1175/BAMS-D-13-00164.1, 2014.
Huffman, G. J., Adler, R. F., Arkin, P., Chang, A., Ferraro, R., Gruber, A.,
Janowiak, J., McNab, A., Rudolf, B., and Schneider, U.: The global precipitation climatology project (GPCP) combined precipitation dataset, B.
Am. Meteorol. Soc., 78, 5–20, https://doi.org/10.1175/1520-0477(1997)078<0005:TGPCPG>2.0.CO;2, 1997.
Huffman, G. J., Bolvin, D. T., Nelkin, E. J., Wolff, D. B., Adler, R. F.,
Gu, G., Hong, Y., Bowman, K. P., and Stocker, E. F.: The TRMM Multisatellite
Precipitation Analysis (TMPA): Quasi-global, multiyear, combined-sensor
precipitation estimates at fine scales, J. Hydrometeorol., 8, 38–55,
https://doi.org/10.1175/JHM560.1, 2007.
Huffman, G. J., Bolvin, D. T., Braithwaite, D., Hsu, K., Joyce, R., Xie, P.,
and Yoo, S.-H.: NASA global precipitation measurement (GPM) integrated
multi-satellite retrievals for GPM (IMERG), Algorithm Theoretical Basis
Document (ATBD) Version 4, National Aeronautics and Space Administration, 26 pp., https://gpm.nasa.gov/resources/documents/algorithm-information/IMERG-V06-ATBD (last access: 9 January 2023), 2020a.
Huffman, G. J., Bolvin, D. T., Braithwaite, D., Hsu, K.-L., Joyce, R. J.,
Kidd, C., Nelkin, E. J., Sorooshian, S., Stocker, E. F., and Tan, J.:
Integrated multi-satellite retrievals for the Global Precipitation
Measurement (GPM) mission (IMERG), in: Satellite precipitation measurement,
Springer, Cham, 343–353, https://doi.org/10.1007/978-3-030-24568-9_19, 2020b.
Hutengs, C. and Vohland, M.: Downscaling land surface temperatures at regional scales with random forest regression, Remote Sens. Environ., 178,
127–141, https://doi.org/10.1016/j.rse.2016.03.006, 2016.
Immerzeel, W. W., Rutten, M. M., and Droogers, P.: Spatial downscaling of
TRMM precipitation using vegetative response on the Iberian Peninsula, Remote Sens. Environ., 113, 362–370, https://doi.org/10.1016/j.rse.2008.10.004, 2009.
Jadidoleslam, N., Mantilla, R., Krajewski, W. F., and Goska, R.: Investigating the role of antecedent SMAP satellite soil moisture, radar rainfall and MODIS vegetation on runoff production in an agricultural
region, J. Hydrol., 579, 124210, https://doi.org/10.1016/j.jhydrol.2019.124210, 2019.
Jia, S., Zhu, W., Lű, A., and Yan, T.: A statistical spatial downscaling
algorithm of TRMM precipitation based on NDVI and DEM in the Qaidam Basin of
China, Remote Sens. Environ., 115, 3069–3079, https://doi.org/10.1016/j.rse.2011.06.009, 2011.
Jing, W., Yang, Y., Yue, X., and Zhao, X.: A Spatial Downscaling Algorithm
for Satellite-Based Precipitation over the Tibetan Plateau Based on NDVI,
DEM, and Land Surface Temperature, Remote Sens., 8, 655, https://doi.org/10.3390/rs8080655, 2016a.
Jing, W., Yang, Y., Yue, X., and Zhao, X.: A Comparison of Different
Regression Algorithms for Downscaling Monthly Satellite-Based Precipitation
over North China, Remote Sens., 8, 1–17, https://doi.org/10.3390/rs8100835, 2016b.
Jing, Y., Lin, L., Li, X., Li, T., and Shen, H.: An attention mechanism
based convolutional network for satellite precipitation downscaling over China, J. Hydrol., 613, 128388, https://doi.org/10.1016/j.jhydrol.2022.128388, 2022.
Joiner, J., Yoshida, Y., Anderson, M., Holmes, T., Hain, C., Reichle, R.,
Koster, R., Middleton, E., and Zeng, F.-W.: Global relationships among
traditional reflectance vegetation indices (NDVI and NDII),
evapotranspiration (ET), and soil moisture variability on weekly timescales,
Remote Sens. Environ., 219, 339–352, https://doi.org/10.1016/j.rse.2018.10.020, 2018.
Joyce, R. J., Janowiak, J. E., Arkin, P. A., and Xie, P.: CMORPH: A method
that produces global precipitation estimates from passive microwave and
infrared data at high spatial and temporal resolution, J. Hydrometeorol., 5,
487–503, https://doi.org/10.1175/1525-7541(2004)005<0487:CAMTPG>2.0.CO;2, 2004.
Kubota, T., Shige, S., Hashizume, H., Aonashi, K., Takahashi, N., Seto, S.,
Hirose, M., Takayabu, Y. N., Ushio, T., and Nakagawa, K.: Global
precipitation map using satellite-borne microwave radiometers by the GSMaP
project: Production and validation, IEEE T. Geosci. Remote, 45, 2259–2275, https://doi.org/10.1109/TGRS.2007.895337, 2007.
Li, X. and Long, D.: An improvement in accuracy and spatiotemporal continuity of the MODIS precipitable water vapor product based on a data fusion approach, Remote Sens. Environ., 248, 111966, https://doi.org/10.1016/j.rse.2020.111966, 2020.
Lin, A. and Wang, X. L.: An algorithm for blending multiple satellite precipitation estimates with in situ precipitation measurements in Canada,
J. Geophys. Res.-Atmos., 116, D21111, https://doi.org/10.1029/2011JD016359, 2011.
Long, D., Bai, L., Yan, L., Zhang, C., Yang, W., Lei, H., Quan, J., Meng,
X., and Shi, C.: Generation of spatially complete and daily continuous surface soil moisture of high spatial resolution, Remote Sens. Environ., 233, 111364, https://doi.org/10.1016/j.rse.2019.111364, 2019.
Long, Y., Zhang, Y., and Ma, Q.: A Merging Framework for Rainfall Estimation
at High Spatiotemporal Resolution for Distributed Hydrological Modeling in a
Data-Scarce Area, Remote Sens., 8, 599, https://doi.org/10.3390/rs8070599, 2016.
Lu, X., Tang, G., Wang, X., Liu, Y., Jia, L., Xie, G., Li, S., and Zhang, Y.: Correcting GPM IMERG precipitation data over the Tianshan Mountains in China, J. Hydrol., 575, 1239–1252, https://doi.org/10.1016/j.jhydrol.2019.06.019, 2019.
Lu, X., Chen, Y., Tang, G., Wang, X., Liu, Y., and Wei, M.: Quantitative
estimation of hourly precipitation in the Tianshan Mountains based on area-to-point kriging downscaling and satellite-gauge data merging, J. Mt.
Sci., 19, 58–72, https://doi.org/10.1007/s11629-021-6901-5, 2022.
Ma, Y., Sun, X., Chen, H., Hong, Y., and Zhang, Y.: A two-stage blending
approach for merging multiple satellite precipitation estimates and rain gauge observations: an experiment in the northeastern Tibetan Plateau, Hydrol. Earth Syst. Sci., 25, 359–374, https://doi.org/10.5194/hess-25-359-2021, 2021.
Ma, Z., Zhou, Y., Hu, B., Liang, Z., and Shi, Z.: Downscaling annual
precipitation with TMPA and land surface characteristics in China, Int. J.
Climatol., 37, 5107–5119, https://doi.org/10.1002/joc.5148, 2017a.
Ma, Z., Shi, Z., Zhou, Y., Xu, J., Yu, W., and Yang, Y.: A spatial data mining algorithm for downscaling TMPA 3B43 V7 data over the Qinghai–Tibet
Plateau with the effects of systematic anomalies removed, Remote Sens. Environ., 200, 378–395, https://doi.org/10.1016/j.rse.2017.08.023, 2017b.
Ma, Z., He, K., Tan, X., Liu, Y., Lu, H., and Shi, Z.: A new approach for
obtaining precipitation estimates with a finer spatial resolution on a daily
scale based on TMPA V7 data over the Tibetan Plateau, Int. J. Remote Sens.,
40, 8465–8483, https://doi.org/10.1080/01431161.2019.1612118, 2019a.
Ma, Z., Ghent, D., Tan, X., He, K., Li, H., Han, X., Huang, Q., and Peng, J.: Long-Term Precipitation Estimates Generated by a Downscaling-Calibration Procedure Over the Tibetan Plateau From 1983 to 2015, Earth Space Sci., 6,
2180–2199, https://doi.org/10.1029/2019EA000657, 2019b.
Ma, Z., Xu, J., He, K., Han, X., Ji, Q., Wang, T., Xiong, W., and Hong, Y.:
An updated moving window algorithm for hourly-scale satellite precipitation
downscaling: A case study in the Southeast Coast of China, J. Hydrol., 581,
124378, https://doi.org/10.1016/j.jhydrol.2019.124378, 2020a.
Ma, Z., Xu, J., Zhu, S., Yang, J., Tang, G., Yang, Y., Shi, Z., and Hong, Y.: AIMERG: a new Asian precipitation dataset (0.1∘/half-hourly, 2000–2015) by calibrating the GPM-era IMERG at a daily scale using APHRODITE, Earth Syst. Sci. Data, 12, 1525–1544, https://doi.org/10.5194/essd-12-1525-2020, 2020b.
Ma, Z., Xu, J., Ma, Y., Zhu, S., He, K., Zhang, S., Ma, W., and Xu, X.:
AERA5-Asia: A Long-Term Asian Precipitation Dataset (0.1∘, 1-hourly, 1951–2015, Asia) Anchoring the ERA5-Land under the Total Volume Control by APHRODITE, B. Am. Meteorol. Soc., 103, E1146–E1171, https://doi.org/10.1175/BAMS-D-20-0328.1, 2022.
Mao, Y., Crow, W. T., and Nijssen, B.: A Framework for Diagnosing Factors
Degrading the Streamflow Performance of a Soil Moisture Data Assimilation
System, J. Hydrometeorol., 20, 79–97, https://doi.org/10.1175/JHM-D-18-0115.1, 2019.
Maraun, D., Wetterhall, F., Ireson, A., Chandler, R., Kendon, E., Widmann, M., Brienen, S., Rust, H., Sauter, T., and Themeßl, M.: Precipitation
downscaling under climate change: Recent developments to bridge the gap
between dynamical models and the end user, Rev. Geophys., 48, RG3003, https://doi.org/10.1029/2009RG000314, 2010.
Maselli, F., Chiesi, M., Angeli, L., Fibbi, L., Rapi, B., Romani, M., Sabatini, F., and Battista, P.: An improved NDVI-based method to predict
actual evapotranspiration of irrigated grasses and crops, Agr. Water
Manage., 233, 106077, https://doi.org/10.1016/j.agwat.2020.106077, 2020.
Massari, C., Brocca, L., Moramarco, T., Tramblay, Y., and Didon Lescot, J.-F.: Potential of soil moisture observations in flood modelling: Estimating initial conditions and correcting rainfall, Adv. Water Resour., 74, 44–53, https://doi.org/10.1016/j.advwatres.2014.08.004, 2014.
McNally, A., Shukla, S., Arsenault, K. R., Wang, S., Peters-Lidard, C. D.,
and Verdin, J. P.: Evaluating ESA CCI soil moisture in East Africa, Int. J.
Appl. Earth Obs. Geoinf., 48, 96–109, https://doi.org/10.1016/j.jag.2016.01.001, 2016.
Mei, Y., Maggioni, V., Houser, P., Xue, Y., and Rouf, T.: A nonparametric
statistical technique for spatial downscaling of precipitation over High
Mountain Asia, Water Resour. Res., 56, e2020WR027472, https://doi.org/10.1029/2020WR027472, 2020.
Merlin, O., Walker, J. P., Chehbouni, A., and Kerr, Y.: Towards deterministic downscaling of SMOS soil moisture using MODIS derived soil evaporative efficiency, Remote Sens. Environ., 112, 3935–3946, https://doi.org/10.1016/j.rse.2008.06.012, 2008.
Min, X., Ma, Z., Xu, J., He, K., Wang, Z., Huang, Q., and Li, J.: Spatially
Downscaling IMERG at Daily Scale Using Machine Learning Approaches Over Zhejiang, Southeastern China, Front. Earth Sci., 8, 146, https://doi.org/10.3389/feart.2020.00146, 2020.
Mishra, V., Ellenburg, W. L., Griffin, R. E., Mecikalski, J. R., Cruise, J.
F., Hain, C. R., and Anderson, M. C.: An initial assessment of a SMAP soil
moisture disaggregation scheme using TIR surface evaporation data over the
continental United States, Int. J. Appl. Earth Obs. Geoinf., 68, 92–104,
https://doi.org/10.1016/j.jag.2018.02.005, 2018.
Mu, Q., Jones, L. A., Kimball, J. S., McDonald, K. C., and Running, S. W.:
Satellite assessment of land surface evapotranspiration for the pan-Arctic
domain, Water Resour. Res., 45, W09420, https://doi.org/10.1029/2008WR007189, 2009.
Muelchi, R., Rssler, O., Schwanbeck, J., Weingartner, R., and Martius, O.:
An ensemble of daily simulated runoff data (1981–2099) under climate change
conditions for 93 catchments in Switzerland (Hydro-CH2018-Runoff ensemble),
Geosci. Data. J., 9, 46–57, https://doi.org/10.1002/gdj3.117, 2022.
Munsi, A., Kesarkar, A., Bhate, J., Panchal, A., Singh, K., Kutty, G., and
Giri, R.: Rapidly intensified, long duration North Indian Ocean tropical
cyclones: Mesoscale downscaling and validation, Atmos. Res., 259, 105678,
https://doi.org/10.1016/j.atmosres.2021.105678, 2021.
Nagler, P. L., Cleverly, J., Glenn, E., Lampkin, D., Huete, A., and Wan, Z.:
Predicting riparian evapotranspiration from MODIS vegetation indices and
meteorological data, Remote Sens. Environ., 94, 17–30, https://doi.org/10.1016/j.rse.2004.08.009, 2005a.
Nagler, P. L., Scott, R. L., Westenburg, C., Cleverly, J. R., Glenn, E. P.,
and Huete, A. R.: Evapotranspiration on western U.S. rivers estimated using
the Enhanced Vegetation Index from MODIS and data from eddy covariance and
Bowen ratio flux towers, Remote Sens. Environ., 97, 337–351, https://doi.org/10.1016/j.rse.2005.05.011, 2005b.
Neinavaz, E., Skidmore, A. K., and Darvishzadeh, R.: Effects of prediction
accuracy of the proportion of vegetation cover on land surface emissivity
and temperature using the NDVI threshold method, Int. J. Appl. Earth Obs.
Geoinf., 85, 101984, https://doi.org/10.1016/j.jag.2019.101984, 2020.
NOAA: Global Surface Summary of the Day – GSOD, https://www.ncei.noaa.gov/access/search/data-search/global-summary-of-the-day, last access: 6 January 2023.
Pan, L., Xia, H., Zhao, X., Guo, Y., and Qin, Y.: Mapping Winter Crops Using
a Phenology Algorithm, Time-Series Sentinel-2 and Landsat-7/8 Images, and
Google Earth Engine, Remote Sens., 13, 2510, https://doi.org/10.3390/rs13132510, 2021.
Peng, J., Loew, A., Zhang, S., Wang, J., and Niesel, J.: Spatial Downscaling
of Satellite Soil Moisture Data Using a Vegetation Temperature Condition
Index, IEEE T. Geosci. Remote, 54, 558–566, https://doi.org/10.1109/TGRS.2015.2462074, 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.
Piles, M., Sanchez, N., Vall-llossera, M., Camps, A., Martinez-Fernandez, J., Martinez, J., and Gonzalez-Gambau, V.: A Downscaling Approach for SMOS Land Observations: Evaluation of High-Resolution Soil Moisture Maps Over the Iberian Peninsula, IEEE J. Select. Top. Appl. Earth Obs. Remote Sens., 7, 3845–3857, https://doi.org/10.1109/JSTARS.2014.2325398, 2014.
Prakash, S., Mitra, A. K., Pai, D. S., and AghaKouchak, A.: From TRMM to GPM: How well can heavy rainfall be detected from space?, Adv. Water Resour., 88, 1–7, https://doi.org/10.1016/j.advwatres.2015.11.008, 2016.
Quiroz, R., Yarlequé, C., Posadas, A., Mares, V., and Immerzeel, W. W.:
Improving daily rainfall estimation from NDVI using a wavelet transform,
Environ. Model. Softw., 26, 201–209, https://doi.org/10.1016/j.envsoft.2010.07.006, 2011.
Rockel, B.: The regional downscaling approach: a brief history and recent
advances, Curr. Clim. Change. Rep., 1, 22–29, https://doi.org/10.1007/s40641-014-0001-3, 2015.
Rozante, J. R., Gutierrez, E. R., Fernandes, A. d. A., and Vila, D. A.:
Performance of precipitation products obtained from combinations of satellite and surface observations, Int. J. Remote Sens., 41, 7585–7604,
https://doi.org/10.1080/01431161.2020.1763504, 2020.
Sabaghy, S., Walker, J. P., Renzullo, L. J., Akbar, R., Chan, S., Chaubell,
J., Das, N., Dunbar, R. S., Entekhabi, D., Gevaert, A., Jackson, T. J., Loew, A., Merlin, O., Moghaddam, M., Peng, J., Peng, J., Piepmeier, J., Rüdiger, C., Stefan, V., Wu, X., Ye, N., and Yueh, S.: Comprehensive analysis of alternative downscaled soil moisture products, Remote Sens.
Environ., 239, 111586, https://doi.org/10.1016/j.rse.2019.111586, 2020.
Salzmann, M.: Global warming without global mean precipitation increase?, Sci. Adv., 2, e1501572, https://doi.org/10.1126/sciadv.1501572, 2016.
Senanayake, I. P., Yeo, I. Y., Willgoose, G. R., and Hancock, G. R.:
Disaggregating satellite soil moisture products based on soil thermal inertia: A comparison of a downscaling model built at two spatial scales, J.
Hydrol., 594, 125894, https://doi.org/10.1016/j.jhydrol.2020.125894, 2021.
Seneviratne, S. I., Corti, T., Davin, E. L., Hirschi, M., Jaeger, E. B.,
Lehner, I., Orlowsky, B., and Teuling, A. J.: Investigating soil moisture–climate interactions in a changing climate: A review, Earth Sci.
Rev., 99, 125–161, https://doi.org/10.1016/j.earscirev.2010.02.004, 2010.
Sheffield, J., Ferguson, C. R., Troy, T. J., Wood, E. F., and McCabe, M. F.:
Closing the terrestrial water budget from satellite remote sensing, Geophys.
Res. Lett., 36, L07403, https://doi.org/10.1029/2009GL037338, 2009.
Shen, Y., Xiong, A., Hong, Y., Yu, J., Pan, Y., Chen, Z., and Saharia, M.:
Uncertainty analysis of five satellite-based precipitation products and
evaluation of three optimally merged multi-algorithm products over the
Tibetan Plateau, Int. J. Climatol., 35, 6843–6858, https://doi.org/10.1080/01431161.2014.960612, 2014.
Song, S., Brocca, L., Wang, W., and Cui, W.: Testing the potential of soil
moisture observations to estimate rainfall in a soil tank experiment, J.
Hydrol., 581, 124368, https://doi.org/10.1016/j.jhydrol.2019.124368, 2020.
Sorooshian, S., Hsu, K.-L., Gao, X., Gupta, H. V., Imam, B., and Braithwaite, D.: Evaluation of PERSIANN system satellite-based estimates of tropical rainfall, B. Am. Meteorol. Soc., 81, 2035–2046, https://doi.org/10.1175/1520-0477(2000)081<2035:EOPSSE>2.3.CO;2, 2000.
Spötl, C., Koltai, G., Jarosch, A., and Cheng, H.: Increased autumn and
winter precipitation during the Last Glacial Maximum in the European Alps,
Nat. Commun., 12, 1–9, https://doi.org/10.1038/s41467-021-22090-7, 2021.
Tagesson, T., Horion, S., Nieto, H., Zaldo Fornies, V., Mendiguren González, G., Bulgin, C. E., Ghent, D., and Fensholt, R.: Disaggregation of SMOS soil moisture over West Africa using the Temperature and Vegetation Dryness Index based on SEVIRI land surface parameters, Remote Sens. Environ., 206, 424–441, https://doi.org/10.1016/j.rse.2017.12.036, 2018.
Tang, G., Behrangi, A., Long, D., Li, C., and Hong, Y.: Accounting for spatiotemporal errors of gauges: A critical step to evaluate gridded
precipitation products, J. Hydrol., 559, 294–306, https://doi.org/10.1016/j.jhydrol.2018.02.057, 2018.
Tang, J., Niu, X., Wang, S., Gao, H., Wang, X., and Wu, J.: Statistical
downscaling and dynamical downscaling of regional climate in China: Present
climate evaluations and future climate projections, J. Geophys. Res.-Atmos., 121, 2110–2129, https://doi.org/10.1002/2015JD023977, 2016.
Wackernagel, H.: Ordinary kriging, in: Multivariate geostatistics, Springer,
79–88, https://doi.org/10.1007/978-3-662-03098-1_11, 2003.
Wehbe, Y., Ghebreyesus, D., Temimi, M., Milewski, A., and Al Mandous, A.:
Assessment of the consistency among global precipitation products over the
United Arab Emirates, Hydrol. Reg. Stud., 12, 122–135, https://doi.org/10.1016/j.ejrh.2017.05.002, 2017.
Wehbe, Y., Temimi, M., and Adler, R. F.: Enhancing precipitation estimates
through the fusion of weather radar, satellite retrievals, and surface parameters, Remote Sens., 12, 1342, https://doi.org/10.3390/rs12081342, 2020.
Wei, K., Ouyang, C., Duan, H., Li, Y., Chen, M., Ma, J., An, H., and Zhou, S.: Reflections on the Catastrophic 2020 Yangtze River Basin Flooding in
Southern China, Innovation, 1, 100038, https://doi.org/10.1016/j.xinn.2020.100038, 2020.
Wen, F., Zhao, W., Wang, Q., and Sánchez, N.: A Value-Consistent Method
for Downscaling SMAP Passive Soil Moisture With MODIS Products Using Self-Adaptive Window, IEEE T. Geosci. Remote, 58, 913–924,
https://doi.org/10.1109/TGRS.2019.2941696, 2020.
Xia, T., Wang, Z.-J., and Zheng, H.: Topography and Data Mining Based Methods for Improving Satellite Precipitation in Mountainous Areas of China, Atmosphere, 6, 983–1005, https://doi.org/10.3390/atmos6080983, 2015.
Xu, J., Ma, Z., Yan, S., and Peng, J.: Do ERA5 and ERA5-land precipitation
estimates outperform satellite-based precipitation products? A comprehensive
comparison between state-of-the-art model-based and satellite-based
precipitation products over mainland China, J. Hydrol., 605, 127353,
https://doi.org/10.1016/j.jhydrol.2021.127353, 2022.
Xu, S., Wu, C., Wang, L., Gonsamo, A., Shen, Y., and Niu, Z.: A new satellite-based monthly precipitation downscaling algorithm with non-stationary relationship between precipitation and land surface characteristics, Remote Sens. Environ., 162, 119–140, https://doi.org/10.1016/j.rse.2015.02.024, 2015.
Yan, X., Chen, H., Tian, B., Sheng, S., and Kim, J. S.: A Downscaling–Merging Scheme for Improving Daily Spatial Precipitation
Estimates Based on Random Forest and Cokriging, Remote Sens., 13, 2040,
https://doi.org/10.3390/rs13112040, 2021.
Yang, X. and Huang, P.: Restored relationship between ENSO and Indian summer
monsoon rainfall around 1999/2000, Innovation, 2, 100102, https://doi.org/10.1016/j.xinn.2021.100102, 2021.
Zambrano-Bigiarini, M., Nauditt, A., Birkel, C., Verbist, K., and Ribbe, L.:
Temporal and spatial evaluation of satellite-based rainfall estimates across
the complex topographical and climatic gradients of Chile, Hydrol. Earth
Syst. Sci., 21, 1295–1320, https://doi.org/10.5194/hess-21-1295-2017, 2017.
Zeng, Z., Chen, H., Shi, Q., and Li, J.: Spatial Downscaling of IMERG
Considering Vegetation Index Based on Adaptive Lag Phase, IEEE T. Geosci. Remote, 60, 4201415, https://doi.org/10.1109/TGRS.2021.3070417, 2021.
Zhan, C., Han, J., Hu, S., Liu, L., and Dong, Y.: Spatial Downscaling of GPM
Annual and Monthly Precipitation Using Regression-Based Algorithms in a
Mountainous Area, Adv. Meteorol., 2018, 1506017, https://doi.org/10.1155/2018/1506017, 2018.
Zhang, H., Ma, J., Chen, C., and Tian, X.: NDVI-Net: A fusion network for
generating high-resolution normalized difference vegetation index in remote
sensing, ISPRS J. Photogram. Remote Sens., 168, 182–196, https://doi.org/10.1016/j.isprsjprs.2020.08.010, 2020.
Zhang, L., Ren, D., Nan, Z., Wang, W., Zhao, Y., Zhao, Y., Ma, Q., and Wu,
X.: Interpolated or satellite-based precipitation? Implications for hydrological modeling in a meso-scale mountainous watershed on the Qinghai-Tibet Plateau, J. Hydrol., 583, 124629, https://doi.org/10.1016/j.jhydrol.2020.124629, 2020.
Zhao, W., Sánchez, N., Lu, H., and Li, A.: A spatial downscaling approach for the SMAP passive surface soil moisture product using random forest regression, J. Hydrol., 563, 1009–1024, https://doi.org/10.1016/j.jhydrol.2018.06.081, 2018.
Zhao, W., Wen, F., Wang, Q., Sanchez, N., and Piles, M.: Seamless downscaling of the ESA CCI soil moisture data at the daily scale with MODIS land products, J. Hydrol., 603, 126930, https://doi.org/10.1016/j.jhydrol.2021.126930, 2021.
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.
In this study, we developed a soil moisture-based precipitation downscaling (SMPD) method for...
