Articles | Volume 23, issue 2
https://doi.org/10.5194/hess-23-897-2019
© Author(s) 2019. 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-23-897-2019
© Author(s) 2019. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
18 Feb 2019
Research article |
| 18 Feb 2019
Estimating irrigation water use over the contiguous United States by combining satellite and reanalysis soil moisture data
Felix Zaussinger
CORRESPONDING AUTHOR
CLIMERS – Research Group Climate and Environmental Remote Sensing, Department of Geodesy and Geoinformation, TU Wien, Vienna, Austria
Wouter Dorigo
CORRESPONDING AUTHOR
CLIMERS – Research Group Climate and Environmental Remote Sensing, Department of Geodesy and Geoinformation, TU Wien, Vienna, Austria
Alexander Gruber
CLIMERS – Research Group Climate and Environmental Remote Sensing, Department of Geodesy and Geoinformation, TU Wien, Vienna, Austria
Department of Earth and Environmental Sciences, KU Leuven, Heverlee, Belgium
Angelica Tarpanelli
Research Institute for Geo-Hydrological Protection, National Research Council, Perugia, Italy
Paolo Filippucci
Research Institute for Geo-Hydrological Protection, National Research Council, Perugia, Italy
Luca Brocca
Research Institute for Geo-Hydrological Protection, National Research Council, Perugia, Italy
Related authors
No articles found.
Remi Madelon, Nemesio J. Rodríguez-Fernández, Hassan Bazzi, Nicolas Baghdadi, Clement Albergel, Wouter Dorigo, and Mehrez Zribi
Hydrol. Earth Syst. Sci., 27, 1221–1242, https://doi.org/10.5194/hess-27-1221-2023, https://doi.org/10.5194/hess-27-1221-2023, 2023
Short summary
Short summary
We present an approach to estimate soil moisture (SM) at 1 km resolution using Sentinel-1 and Sentinel-3 satellites. The estimates were compared to other high-resolution (HR) datasets over Europe, northern Africa, Australia, and North America, showing good agreement. However, the discrepancies between the different HR datasets and their lower performances compared with in situ measurements and coarse-resolution datasets show the remaining challenges for large-scale HR SM mapping.
Luisa Schmidt, Matthias Forkel, Ruxandra-Maria Zotta, Samuel Scherrer, Wouter A. Dorigo, Alexander Kuhn-Régnier, Robin van der Schalie, and Marta Yebra
Biogeosciences, 20, 1027–1046, https://doi.org/10.5194/bg-20-1027-2023, https://doi.org/10.5194/bg-20-1027-2023, 2023
Short summary
Short summary
Vegetation attenuates natural microwave emissions from the land surface. The strength of this attenuation is quantified as the vegetation optical depth (VOD) parameter and is influenced by the vegetation mass, structure, water content, and observation wavelength. Here we model the VOD signal as a multi-variate function of several descriptive vegetation variables. The results help in understanding the effects of ecosystem properties on VOD.
Adam Pasik, Alexander Gruber, Wolfgang Preimesberger, Domenico De Santis, and Wouter Dorigo
EGUsphere, https://doi.org/10.5194/egusphere-2023-47, https://doi.org/10.5194/egusphere-2023-47, 2023
Short summary
Short summary
In this study, we apply the exponential filter (EF) method to satellite soil moisture retrievals to estimate the water content in the unobserved root-zone globally over 2002–2020. Quality assessment against an independent dataset shows satisfactory results. Error characterization is carried out using standard uncertainty propagation law and empirically estimated values of EF model structural uncertainty and parameter uncertainty. This is followed by analysis of temporal uncertainty variations.
Taylor Smith, Ruxandra-Maria Zotta, Chris A. Boulton, Timothy M. Lenton, Wouter Dorigo, and Niklas Boers
Earth Syst. Dynam., 14, 173–183, https://doi.org/10.5194/esd-14-173-2023, https://doi.org/10.5194/esd-14-173-2023, 2023
Short summary
Short summary
Multi-instrument records with varying signal-to-noise ratios are becoming increasingly common as legacy sensors are upgraded, and data sets are modernized. Induced changes in higher-order statistics such as the autocorrelation and variance are not always well captured by cross-calibration schemes. Here we investigate using synthetic examples how strong resulting biases can be and how they can be avoided in order to make reliable statements about changes in the resilience of a system.
Kunlong He, Wei Zhao, Luca Brocca, and Pere Quintana-Seguí
Hydrol. Earth Syst. Sci., 27, 169–190, https://doi.org/10.5194/hess-27-169-2023, https://doi.org/10.5194/hess-27-169-2023, 2023
Short summary
Short summary
In this study, we developed a soil moisture-based precipitation downscaling (SMPD) method for spatially downscaling the GPM daily precipitation product by exploiting the connection between surface soil moisture and precipitation according to the soil water balance equation. Based on this physical method, the spatial resolution of the daily precipitation product was downscaled to 1 km and the SMPD method shows good potential for the development of the high-resolution precipitation product.
Matthias Forkel, Luisa Schmidt, Ruxandra-Maria Zotta, Wouter Dorigo, and Marta Yebra
Hydrol. Earth Syst. Sci., 27, 39–68, https://doi.org/10.5194/hess-27-39-2023, https://doi.org/10.5194/hess-27-39-2023, 2023
Short summary
Short summary
The live fuel moisture content (LFMC) of vegetation canopies is a driver of wildfires. We investigate the relation between LFMC and passive microwave satellite observations of vegetation optical depth (VOD) and develop a method to estimate LFMC from VOD globally. Our global VOD-based estimates of LFMC can be used to investigate drought effects on vegetation and fire risks.
Samuel Scherrer, Gabriëlle De Lannoy, Zdenko Heyvaert, Michel Bechtold, Clement Albergel, Tarek S. El-Madany, and Wouter Dorigo
EGUsphere, https://doi.org/10.5194/egusphere-2022-1137, https://doi.org/10.5194/egusphere-2022-1137, 2022
Short summary
Short summary
We explored different options for data assimilation (DA) of remotely sensed leaf area index (LAI). We found strong biases between LAI predicted by Noah-MP and observations. LAI DA that does not take these biases into account can induce unphysical patterns in the resulting LAI and flux estimates, and leads to large changes in the climatology of root zone soil moisture. We tested two bias-correction approaches, which were successful at overcoming these problems, and explore alternative solutions.
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 Discuss., https://doi.org/10.5194/essd-2022-403, https://doi.org/10.5194/essd-2022-403, 2022
Revised manuscript accepted for ESSD
Short summary
Short summary
Irrigation is the main source of global freswhwater 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 signal are presented.
Leander Moesinger, Ruxandra-Maria Zotta, Robin van der Schalie, Tracy Scanlon, Richard de Jeu, and Wouter Dorigo
Biogeosciences, 19, 5107–5123, https://doi.org/10.5194/bg-19-5107-2022, https://doi.org/10.5194/bg-19-5107-2022, 2022
Short summary
Short summary
The standardized vegetation optical depth index (SVODI) can be used to monitor the vegetation condition, such as whether the vegetation is unusually dry or wet. SVODI has global coverage, spans the past 3 decades and is derived from multiple spaceborne passive microwave sensors of that period. SVODI is based on a new probabilistic merging method that allows the merging of normally distributed data even if the data are not gap-free.
Sara Modanesi, Christian Massari, Michel Bechtold, Hans Lievens, Angelica Tarpanelli, Luca Brocca, Luca Zappa, and Gabriëlle J. M. De Lannoy
Hydrol. Earth Syst. Sci., 26, 4685–4706, https://doi.org/10.5194/hess-26-4685-2022, https://doi.org/10.5194/hess-26-4685-2022, 2022
Short summary
Short summary
Given the crucial impact of irrigation practices on the water cycle, this study aims at estimating irrigation through the development of an innovative data assimilation system able to ingest high-resolution Sentinel-1 radar observations into the Noah-MP land surface model. The developed methodology has important implications for global water resource management and the comprehension of human impacts on the water cycle and identifies main challenges and outlooks for future research.
Stefania Camici, Gabriele Giuliani, Luca Brocca, Christian Massari, Angelica Tarpanelli, Hassan Hashemi Farahani, Nico Sneeuw, Marco Restano, and Jérôme Benveniste
Geosci. Model Dev., 15, 6935–6956, https://doi.org/10.5194/gmd-15-6935-2022, https://doi.org/10.5194/gmd-15-6935-2022, 2022
Short summary
Short summary
This paper presents an innovative approach, STREAM (SaTellite-based Runoff Evaluation And Mapping), to derive daily river discharge and runoff estimates from satellite observations of soil moisture, precipitation, and terrestrial total water storage anomalies. Potentially useful for multiple operational and scientific applications, the added value of the STREAM approach is the ability to increase knowledge on the natural processes, human activities, and their interactions on the land.
Lorenzo Alfieri, Francesco Avanzi, Fabio Delogu, Simone Gabellani, Giulia Bruno, Lorenzo Campo, Andrea Libertino, Christian Massari, Angelica Tarpanelli, Dominik Rains, Diego G. Miralles, Raphael Quast, Mariette Vreugdenhil, Huan Wu, and Luca Brocca
Hydrol. Earth Syst. Sci., 26, 3921–3939, https://doi.org/10.5194/hess-26-3921-2022, https://doi.org/10.5194/hess-26-3921-2022, 2022
Short summary
Short summary
This work shows advances in high-resolution satellite data for hydrology. We performed hydrological simulations for the Po River basin using various satellite products, including precipitation, evaporation, soil moisture, and snow depth. Evaporation and snow depth improved a simulation based on high-quality ground observations. Interestingly, a model calibration relying on satellite data skillfully reproduces observed discharges, paving the way to satellite-driven hydrological applications.
Robin van der Schalie, Mendy van der Vliet, Clément Albergel, Wouter Dorigo, Piotr Wolski, and Richard de Jeu
Hydrol. Earth Syst. Sci., 26, 3611–3627, https://doi.org/10.5194/hess-26-3611-2022, https://doi.org/10.5194/hess-26-3611-2022, 2022
Short summary
Short summary
Climate data records of surface soil moisture, vegetation optical depth, and land surface temperature can be derived from passive microwave observations. The ability of these datasets to properly detect anomalies and extremes is very valuable in climate research and can especially help to improve our insight in complex regions where the current climate reanalysis datasets reach their limitations. Here, we present a case study over the Okavango Delta, where we focus on inter-annual variability.
Paolo Filippucci, Luca Brocca, Raphael Quast, Luca Ciabatta, Carla Saltalippi, Wolfgang Wagner, and Angelica Tarpanelli
Hydrol. Earth Syst. Sci., 26, 2481–2497, https://doi.org/10.5194/hess-26-2481-2022, https://doi.org/10.5194/hess-26-2481-2022, 2022
Short summary
Short summary
A high-resolution (1 km) rainfall product with 10–30 d temporal resolution was obtained starting from SM data from Sentinel-1. Good performances are achieved using observed data (gauge and radar) over the Po River Valley, Italy, as a benchmark. The comparison with a product characterized by lower spatial resolution (25 km) highlights areas where the high spatial resolution of Sentinel-1 has great benefits. Possible applications include water management, agriculture and index-based insurances.
Benjamin Wild, Irene Teubner, Leander Moesinger, Ruxandra-Maria Zotta, Matthias Forkel, Robin van der Schalie, Stephen Sitch, and Wouter Dorigo
Earth Syst. Sci. Data, 14, 1063–1085, https://doi.org/10.5194/essd-14-1063-2022, https://doi.org/10.5194/essd-14-1063-2022, 2022
Short summary
Short summary
Gross primary production (GPP) describes the conversion of CO2 to carbohydrates and can be seen as a filter for our atmosphere of the primary greenhouse gas CO2. We developed VODCA2GPP, a GPP dataset that is based on vegetation optical depth from microwave remote sensing and temperature. Thus, it is mostly independent from existing GPP datasets and also available in regions with frequent cloud coverage. Analysis showed that VODCA2GPP is able to complement existing state-of-the-art GPP datasets.
Stefan Schlaffer, Marco Chini, Wouter Dorigo, and Simon Plank
Hydrol. Earth Syst. Sci., 26, 841–860, https://doi.org/10.5194/hess-26-841-2022, https://doi.org/10.5194/hess-26-841-2022, 2022
Short summary
Short summary
Prairie wetlands are important for biodiversity and water availability. Knowledge about their variability and spatial distribution is of great use in conservation and water resources management. In this study, we propose a novel approach for the classification of small water bodies from satellite radar images and apply it to our study area over 6 years. The retrieved dynamics show the different responses of small and large wetlands to dry and wet periods.
Sara Modanesi, Christian Massari, Alexander Gruber, Hans Lievens, Angelica Tarpanelli, Renato Morbidelli, and Gabrielle J. M. De Lannoy
Hydrol. Earth Syst. Sci., 25, 6283–6307, https://doi.org/10.5194/hess-25-6283-2021, https://doi.org/10.5194/hess-25-6283-2021, 2021
Short summary
Short summary
Worldwide, the amount of water used for agricultural purposes is rising and the quantification of irrigation is becoming a crucial topic. Land surface models are not able to correctly simulate irrigation. Remote sensing observations offer an opportunity to fill this gap as they are directly affected by irrigation. We equipped a land surface model with an observation operator able to transform Sentinel-1 backscatter observations into realistic vegetation and soil states via data assimilation.
Wouter Dorigo, Irene Himmelbauer, Daniel Aberer, Lukas Schremmer, Ivana Petrakovic, Luca Zappa, Wolfgang Preimesberger, Angelika Xaver, Frank Annor, Jonas Ardö, Dennis Baldocchi, Marco Bitelli, Günter Blöschl, Heye Bogena, Luca Brocca, Jean-Christophe Calvet, J. Julio Camarero, Giorgio Capello, Minha Choi, Michael C. Cosh, Nick van de Giesen, Istvan Hajdu, Jaakko Ikonen, Karsten H. Jensen, Kasturi Devi Kanniah, Ileen de Kat, Gottfried Kirchengast, Pankaj Kumar Rai, Jenni Kyrouac, Kristine Larson, Suxia Liu, Alexander Loew, Mahta Moghaddam, José Martínez Fernández, Cristian Mattar Bader, Renato Morbidelli, Jan P. Musial, Elise Osenga, Michael A. Palecki, Thierry Pellarin, George P. Petropoulos, Isabella Pfeil, Jarrett Powers, Alan Robock, Christoph Rüdiger, Udo Rummel, Michael Strobel, Zhongbo Su, Ryan Sullivan, Torbern Tagesson, Andrej Varlagin, Mariette Vreugdenhil, Jeffrey Walker, Jun Wen, Fred Wenger, Jean Pierre Wigneron, Mel Woods, Kun Yang, Yijian Zeng, Xiang Zhang, Marek Zreda, Stephan Dietrich, Alexander Gruber, Peter van Oevelen, Wolfgang Wagner, Klaus Scipal, Matthias Drusch, and Roberto Sabia
Hydrol. Earth Syst. Sci., 25, 5749–5804, https://doi.org/10.5194/hess-25-5749-2021, https://doi.org/10.5194/hess-25-5749-2021, 2021
Short summary
Short summary
The International Soil Moisture Network (ISMN) is a community-based open-access data portal for soil water measurements taken at the ground and is accessible at https://ismn.earth. Over 1000 scientific publications and thousands of users have made use of the ISMN. The scope of this paper is to inform readers about the data and functionality of the ISMN and to provide a review of the scientific progress facilitated through the ISMN with the scope to shape future research and operations.
Daniele Masseroni, Stefania Camici, Alessio Cislaghi, Giorgio Vacchiano, Christian Massari, and Luca Brocca
Hydrol. Earth Syst. Sci., 25, 5589–5601, https://doi.org/10.5194/hess-25-5589-2021, https://doi.org/10.5194/hess-25-5589-2021, 2021
Short summary
Short summary
We evaluate 63 years of changes in annual streamflow volume across Europe, using a data set of more than 3000 stations, with a special focus on the Mediterranean basin. The results show decreasing (increasing) volumes in the southern (northern) regions. These trends are strongly consistent with the changes in temperature and precipitation.
Maria Teresa Brunetti, Massimo Melillo, Stefano Luigi Gariano, Luca Ciabatta, Luca Brocca, Giriraj Amarnath, and Silvia Peruccacci
Hydrol. Earth Syst. Sci., 25, 3267–3279, https://doi.org/10.5194/hess-25-3267-2021, https://doi.org/10.5194/hess-25-3267-2021, 2021
Short summary
Short summary
Satellite and rain gauge data are tested to predict landslides in India, where the annual toll of human lives and loss of property urgently demands the implementation of strategies to prevent geo-hydrological instability. For this purpose, we calculated empirical rainfall thresholds for landslide initiation. The validation of thresholds showed that satellite-based rainfall data perform better than ground-based data, and the best performance is obtained with an hourly temporal resolution.
Irene E. Teubner, Matthias Forkel, Benjamin Wild, Leander Mösinger, and Wouter Dorigo
Biogeosciences, 18, 3285–3308, https://doi.org/10.5194/bg-18-3285-2021, https://doi.org/10.5194/bg-18-3285-2021, 2021
Short summary
Short summary
Vegetation optical depth (VOD), which contains information on vegetation water content and biomass, has been previously shown to be related to gross primary production (GPP). In this study, we analyzed the impact of adding temperature as model input and investigated if this can reduce the previously observed overestimation of VOD-derived GPP. In addition, we could show that the relationship between VOD and GPP largely holds true along a gradient of dry or wet conditions.
Louise Mimeau, Yves Tramblay, Luca Brocca, Christian Massari, Stefania Camici, and Pascal Finaud-Guyot
Hydrol. Earth Syst. Sci., 25, 653–669, https://doi.org/10.5194/hess-25-653-2021, https://doi.org/10.5194/hess-25-653-2021, 2021
Short summary
Short summary
Soil moisture is a key variable related to droughts and flood genesis, but little is known about the evolution of soil moisture under climate change. Here, using a simulation approach, we show that changes in soil moisture are driven by changes in precipitation intermittence rather than changes in precipitation intensity or in temperature.
Hylke E. Beck, Ming Pan, Diego G. Miralles, Rolf H. Reichle, Wouter A. Dorigo, Sebastian Hahn, Justin Sheffield, Lanka Karthikeyan, Gianpaolo Balsamo, Robert M. Parinussa, Albert I. J. M. van Dijk, Jinyang Du, John S. Kimball, Noemi Vergopolan, and Eric F. Wood
Hydrol. Earth Syst. Sci., 25, 17–40, https://doi.org/10.5194/hess-25-17-2021, https://doi.org/10.5194/hess-25-17-2021, 2021
Short summary
Short summary
We evaluated the largest and most diverse set of surface soil moisture products ever evaluated in a single study. We found pronounced differences in performance among individual products and product groups. Our results provide guidance to choose the most suitable product for a particular application.
Stefania Camici, Christian Massari, Luca Ciabatta, Ivan Marchesini, and Luca Brocca
Hydrol. Earth Syst. Sci., 24, 4869–4885, https://doi.org/10.5194/hess-24-4869-2020, https://doi.org/10.5194/hess-24-4869-2020, 2020
Short summary
Short summary
The paper performs the most comprehensive European-scale evaluation to date of satellite rainfall products for river flow prediction. In doing so, how errors transfer from satellite-based rainfall products into flood simulation is investigated in depth and, for the first time, quantitative guidelines on the use of these products for hydrological applications are provided. This result can represent a keystone in the use of satellite rainfall products, especially in data-scarce regions.
El Mahdi El Khalki, Yves Tramblay, Christian Massari, Luca Brocca, Vincent Simonneaux, Simon Gascoin, and Mohamed El Mehdi Saidi
Nat. Hazards Earth Syst. Sci., 20, 2591–2607, https://doi.org/10.5194/nhess-20-2591-2020, https://doi.org/10.5194/nhess-20-2591-2020, 2020
Short summary
Short summary
In North Africa, the vulnerability to floods is high, and there is a need to improve the flood-forecasting systems. Remote-sensing and reanalysis data can palliate the lack of in situ measurements, in particular for soil moisture, which is a crucial parameter to consider when modeling floods. In this study we provide an evaluation of recent globally available soil moisture products for flood modeling in Morocco.
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
Short summary
Short summary
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.
Kurt C. Solander, Brent D. Newman, Alessandro Carioca de Araujo, Holly R. Barnard, Z. Carter Berry, Damien Bonal, Mario Bretfeld, Benoit Burban, Luiz Antonio Candido, Rolando Célleri, Jeffery Q. Chambers, Bradley O. Christoffersen, Matteo Detto, Wouter A. Dorigo, Brent E. Ewers, Savio José Filgueiras Ferreira, Alexander Knohl, L. Ruby Leung, Nate G. McDowell, Gretchen R. Miller, Maria Terezinha Ferreira Monteiro, Georgianne W. Moore, Robinson Negron-Juarez, Scott R. Saleska, Christian Stiegler, Javier Tomasella, and Chonggang Xu
Hydrol. Earth Syst. Sci., 24, 2303–2322, https://doi.org/10.5194/hess-24-2303-2020, https://doi.org/10.5194/hess-24-2303-2020, 2020
Short summary
Short summary
We evaluate the soil moisture response in the humid tropics to El Niño during the three most recent super El Niño events. Our estimates are compared to in situ soil moisture estimates that span five continents. We find the strongest and most consistent soil moisture decreases in the Amazon and maritime southeastern Asia, while the most consistent increases occur over eastern Africa. Our results can be used to improve estimates of soil moisture in tropical ecohydrology models at multiple scales.
Angelika Xaver, Luca Zappa, Gerhard Rab, Isabella Pfeil, Mariette Vreugdenhil, Drew Hemment, and Wouter Arnoud Dorigo
Geosci. Instrum. Method. Data Syst., 9, 117–139, https://doi.org/10.5194/gi-9-117-2020, https://doi.org/10.5194/gi-9-117-2020, 2020
Short summary
Short summary
Soil moisture plays a key role in the hydrological cycle and the climate system. Although soil moisture can be observed by the means of satellites, ground observations are still crucial for evaluating and improving these satellite products. In this study, we investigate the performance of a consumer low-cost soil moisture sensor in the lab and in the field. We demonstrate that this sensor can be used for scientific applications, for example to create a dataset valuable for satellite validation.
Miguel D. Mahecha, Fabian Gans, Gunnar Brandt, Rune Christiansen, Sarah E. Cornell, Normann Fomferra, Guido Kraemer, Jonas Peters, Paul Bodesheim, Gustau Camps-Valls, Jonathan F. Donges, Wouter Dorigo, Lina M. Estupinan-Suarez, Victor H. Gutierrez-Velez, Martin Gutwin, Martin Jung, Maria C. Londoño, Diego G. Miralles, Phillip Papastefanou, and Markus Reichstein
Earth Syst. Dynam., 11, 201–234, https://doi.org/10.5194/esd-11-201-2020, https://doi.org/10.5194/esd-11-201-2020, 2020
Short summary
Short summary
The ever-growing availability of data streams on different subsystems of the Earth brings unprecedented scientific opportunities. However, researching a data-rich world brings novel challenges. We present the concept of
Earth system data cubesto study the complex dynamics of multiple climate and ecosystem variables across space and time. Using a series of example studies, we highlight the potential of effectively considering the full multivariate nature of processes in the Earth system.
Leander Moesinger, Wouter Dorigo, Richard de Jeu, Robin van der Schalie, Tracy Scanlon, Irene Teubner, and Matthias Forkel
Earth Syst. Sci. Data, 12, 177–196, https://doi.org/10.5194/essd-12-177-2020, https://doi.org/10.5194/essd-12-177-2020, 2020
Short summary
Short summary
Vegetation optical depth (VOD) is measured by satellites and is related to the density of vegetation and its water content. VOD has a wide range of uses, including drought, wildfire danger, biomass, and carbon stock monitoring. For the past 30 years there have been various VOD data sets derived from space-borne microwave sensors, but biases between them prohibit a combined use. We removed these biases and merged the data to create the global long-term VOD Climate Archive (VODCA).
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
Short summary
Short summary
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.
Alexander Gruber, Tracy Scanlon, Robin van der Schalie, Wolfgang Wagner, and Wouter Dorigo
Earth Syst. Sci. Data, 11, 717–739, https://doi.org/10.5194/essd-11-717-2019, https://doi.org/10.5194/essd-11-717-2019, 2019
Short summary
Short summary
Soil moisture is a key variable in our Earth system. Knowledge of soil moisture and its dynamics across scales is vital for many applications such as the prediction of agricultural yields or irrigation demands, flood and drought monitoring, weather forecasting and climate modelling. To date, the ESA CCI SM products are the only consistent long-term multi-satellite soil moisture data sets available. This paper reviews the evolution of these products and their underlying merging methodology.
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
Short summary
Short summary
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.
Matthias Forkel, Niels Andela, Sandy P. Harrison, Gitta Lasslop, Margreet van Marle, Emilio Chuvieco, Wouter Dorigo, Matthew Forrest, Stijn Hantson, Angelika Heil, Fang Li, Joe Melton, Stephen Sitch, Chao Yue, and Almut Arneth
Biogeosciences, 16, 57–76, https://doi.org/10.5194/bg-16-57-2019, https://doi.org/10.5194/bg-16-57-2019, 2019
Short summary
Short summary
Weather, humans, and vegetation control the occurrence of fires. In this study we find that global fire–vegetation models underestimate the strong increase of burned area with higher previous-season plant productivity in comparison to satellite-derived relationships.
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
Short summary
Short summary
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.
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
Short summary
Short summary
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.
Matthias Forkel, Wouter Dorigo, Gitta Lasslop, Irene Teubner, Emilio Chuvieco, and Kirsten Thonicke
Geosci. Model Dev., 10, 4443–4476, https://doi.org/10.5194/gmd-10-4443-2017, https://doi.org/10.5194/gmd-10-4443-2017, 2017
Short summary
Short summary
Wildfires affect infrastructures, vegetation, and the atmosphere. However, it is unclear how fires should be accurately represented in global vegetation models. We introduce here a new flexible data-driven fire modelling approach that allows us to explore sensitivities of burned areas to satellite and climate datasets. Our results suggest combining observations with data-driven and process-oriented fire models to better understand the role of fires in the Earth system.
Clément Albergel, Simon Munier, Delphine Jennifer Leroux, Hélène Dewaele, David Fairbairn, Alina Lavinia Barbu, Emiliano Gelati, Wouter Dorigo, Stéphanie Faroux, Catherine Meurey, Patrick Le Moigne, Bertrand Decharme, Jean-Francois Mahfouf, and Jean-Christophe Calvet
Geosci. Model Dev., 10, 3889–3912, https://doi.org/10.5194/gmd-10-3889-2017, https://doi.org/10.5194/gmd-10-3889-2017, 2017
Short summary
Short summary
LDAS-Monde, a global land data assimilation system, is applied over Europe and the Mediterranean basin to increase monitoring accuracy for land surface variables. It is able to ingest information from satellite-derived surface soil moisture (SSM) and leaf area index (LAI) observations to constrain the ISBA land surface model coupled with the CTRIP continental hydrological system. Assimilation of SSM and LAI leads to a better representation of evapotranspiration and gross primary production.
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
Short summary
Short summary
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
Marko Scholze, Michael Buchwitz, Wouter Dorigo, Luis Guanter, and Shaun Quegan
Biogeosciences, 14, 3401–3429, https://doi.org/10.5194/bg-14-3401-2017, https://doi.org/10.5194/bg-14-3401-2017, 2017
Short summary
Short summary
This paper briefly reviews data assimilation techniques in carbon cycle data assimilation and the requirements of data assimilation systems on observations. We provide a non-exhaustive overview of current observations and their uncertainties for use in terrestrial carbon cycle data assimilation, focussing on relevant space-based observations.
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
Short summary
Short summary
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.
Jaap Schellekens, Emanuel Dutra, Alberto Martínez-de la Torre, Gianpaolo Balsamo, Albert van Dijk, Frederiek Sperna Weiland, Marie Minvielle, Jean-Christophe Calvet, Bertrand Decharme, Stephanie Eisner, Gabriel Fink, Martina Flörke, Stefanie Peßenteiner, Rens van Beek, Jan Polcher, Hylke Beck, René Orth, Ben Calton, Sophia Burke, Wouter Dorigo, and Graham P. Weedon
Earth Syst. Sci. Data, 9, 389–413, https://doi.org/10.5194/essd-9-389-2017, https://doi.org/10.5194/essd-9-389-2017, 2017
Short summary
Short summary
The dataset combines the results of 10 global models that describe the global continental water cycle. The data can be used as input for water resources studies, flood frequency studies etc. at different scales from continental to medium-scale catchments. We compared the results with earth observation data and conclude that most uncertainties are found in snow-dominated regions and tropical rainforest and monsoon regions.
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
Short summary
Short summary
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.
Brecht Martens, Diego G. Miralles, Hans Lievens, Robin van der Schalie, Richard A. M. de Jeu, Diego Fernández-Prieto, Hylke E. Beck, Wouter A. Dorigo, and Niko E. C. Verhoest
Geosci. Model Dev., 10, 1903–1925, https://doi.org/10.5194/gmd-10-1903-2017, https://doi.org/10.5194/gmd-10-1903-2017, 2017
Short summary
Short summary
Terrestrial evaporation is a key component of the hydrological cycle and reliable data sets of this variable are of major importance. The Global Land Evaporation Amsterdam Model (GLEAM, www.GLEAM.eu) is a set of algorithms which estimates evaporation based on satellite observations. The third version of GLEAM, presented in this study, includes an improved parameterization of different model components. As a result, the accuracy of the GLEAM data sets has been improved upon previous versions.
Christina Papagiannopoulou, Diego G. Miralles, Stijn Decubber, Matthias Demuzere, Niko E. C. Verhoest, Wouter A. Dorigo, and Willem Waegeman
Geosci. Model Dev., 10, 1945–1960, https://doi.org/10.5194/gmd-10-1945-2017, https://doi.org/10.5194/gmd-10-1945-2017, 2017
Short summary
Short summary
Global satellite observations provide a means to unravel the influence of climate on vegetation. Common statistical methods used to study the relationships between climate and vegetation are often too simplistic to capture the complexity of these relationships. Here, we present a novel causality framework that includes data fusion from various databases, time series decomposition, and machine learning techniques. Results highlight the highly non-linear nature of climate–vegetation interactions.
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
Preprint retracted
Short summary
Short summary
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.
Markus Enenkel, Christoph Reimer, Wouter Dorigo, Wolfgang Wagner, Isabella Pfeil, Robert Parinussa, and Richard De Jeu
Hydrol. Earth Syst. Sci., 20, 4191–4208, https://doi.org/10.5194/hess-20-4191-2016, https://doi.org/10.5194/hess-20-4191-2016, 2016
Short summary
Short summary
Soil moisture is a crucial variable for a variety of applications, ranging from weather forecasting and agricultural production to the monitoring of floods and droughts. Satellite observations are particularly important in regions where no in situ measurements are available. Our study presents a method to integrate global near-real-time satellite observations from different sensors into one harmonized, daily data set. A first validation shows good results on a global scale.
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
Short summary
Short summary
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.
C. Szczypta, J.-C. Calvet, F. Maignan, W. Dorigo, F. Baret, and P. Ciais
Geosci. Model Dev., 7, 931–946, https://doi.org/10.5194/gmd-7-931-2014, https://doi.org/10.5194/gmd-7-931-2014, 2014
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
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
A. Loew, T. Stacke, W. Dorigo, R. de Jeu, and S. Hagemann
Hydrol. Earth Syst. Sci., 17, 3523–3542, https://doi.org/10.5194/hess-17-3523-2013, https://doi.org/10.5194/hess-17-3523-2013, 2013
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: Water Resources Management | Techniques and Approaches: Remote Sensing and GIS
Monitoring the combined effects of drought and salinity stress on crops using remote sensing in the Netherlands
A framework for irrigation performance assessment using WaPOR data: the case of a sugarcane estate in Mozambique
Satellite observations reveal 13 years of reservoir filling strategies, operating rules, and hydrological alterations in the Upper Mekong River basin
Satellite soil moisture data assimilation for improved operational continental water balance prediction
Mapping groundwater abstractions from irrigated agriculture: big data, inverse modeling, and a satellite–model fusion approach
Multi-constellation GNSS interferometric reflectometry with mass-market sensors as a solution for soil moisture monitoring
Can we trust remote sensing evapotranspiration products over Africa?
Influence of multi-decadal land use, irrigation practices and climate on riparian corridors across the Upper Missouri River headwaters basin, Montana
Developing GIS-based water poverty and rainwater harvesting suitability maps for domestic use in the Dead Sea region (West Bank, Palestine)
Estimating daily evapotranspiration based on a model of evaporative fraction (EF) for mixed pixels
A conceptual model of organochlorine fate from a combined analysis of spatial and mid- to long-term trends of surface and ground water contamination in tropical areas (FWI)
Spatio-temporal assessment of annual water balance models for upper Ganga Basin
Population growth, land use and land cover transformations, and water quality nexus in the Upper Ganga River basin
Wetlands inform how climate extremes influence surface water expansion and contraction
Participatory flood vulnerability assessment: a multi-criteria approach
Monitoring small reservoirs' storage with satellite remote sensing in inaccessible areas
Performance of the METRIC model in estimating evapotranspiration fluxes over an irrigated field in Saudi Arabia using Landsat-8 images
The predictability of reported drought events and impacts in the Ebro Basin using six different remote sensing data sets
A multi-sensor data-driven methodology for all-sky passive microwave inundation retrieval
Effect of the revisit interval and temporal upscaling methods on the accuracy of remotely sensed evapotranspiration estimates
Downstream ecosystem responses to middle reach regulation of river discharge in the Heihe River Basin, China
Combining satellite observations to develop a global soil moisture product for near-real-time applications
Supplemental irrigation potential and impact on downstream flow of Karkheh River basin in Iran
Mapping evapotranspiration with high-resolution aircraft imagery over vineyards using one- and two-source modeling schemes
Spatial evapotranspiration, rainfall and land use data in water accounting – Part 1: Review of the accuracy of the remote sensing data
Spatial evapotranspiration, rainfall and land use data in water accounting – Part 2: Reliability of water acounting results for policy decisions in the Awash Basin
Combining high-resolution satellite images and altimetry to estimate the volume of small lakes
Upscaling of evapotranspiration fluxes from instantaneous to daytime scales for thermal remote sensing applications
A new stream and nested catchment framework for Australia
GRACE water storage estimates for the Middle East and other regions with significant reservoir and lake storage
An original interpretation of the wet edge of the surface temperature–albedo space to estimate crop evapotranspiration (SEB-1S), and its validation over an irrigated area in northwestern Mexico
Using a thermal-based two source energy balance model with time-differencing to estimate surface energy fluxes with day–night MODIS observations
Regional effects of vegetation restoration on water yield across the Loess Plateau, China
Estimation of soil parameters over bare agriculture areas from C-band polarimetric SAR data using neural networks
Accounting for seasonality in a soil moisture change detection algorithm for ASAR Wide Swath time series
Evaluation and bias correction of satellite rainfall data for drought monitoring in Indonesia
Extension of the Hapke bidirectional reflectance model to retrieve soil water content
Estimating river discharge from earth observation measurements of river surface hydraulic variables
Combined use of optical and radar satellite data for the monitoring of irrigation and soil moisture of wheat crops
Mapping surface soil moisture over the Gourma mesoscale site (Mali) by using ENVISAT ASAR data
Soil surface moisture estimation over a semi-arid region using ENVISAT ASAR radar data for soil evaporation evaluation
Particular uncertainties encountered in using a pre-packaged SEBS model to derive evapotranspiration in a heterogeneous study area in South Africa
Effective roughness modelling as a tool for soil moisture retrieval from C- and L-band SAR
Combined use of FORMOSAT-2 images with a crop model for biomass and water monitoring of permanent grassland in Mediterranean region
Identification and mapping of soil erosion areas in the Blue Nile, Eastern Sudan using multispectral ASTER and MODIS satellite data and the SRTM elevation model
Wen Wen, Joris Timmermans, Qi Chen, and Peter M. van Bodegom
Hydrol. Earth Syst. Sci., 26, 4537–4552, https://doi.org/10.5194/hess-26-4537-2022, https://doi.org/10.5194/hess-26-4537-2022, 2022
Short summary
Short summary
A novel approach for evaluating individual and combined impacts of drought and salinity in real-life settings is proposed using Sentinel-2. We found that crop responses to drought and salinity differ between growth stages. Compared to salinity, crop growth is most strongly affected by drought stress and is, in general, further exacerbated when co-occurring with salinity stress. Our approach facilitates a way to monitor crop health under multiple stresses with potential large-scale applications.
Abebe D. Chukalla, Marloes L. Mul, Pieter van der Zaag, Gerardo van Halsema, Evaristo Mubaya, Esperança Muchanga, Nadja den Besten, and Poolad Karimi
Hydrol. Earth Syst. Sci., 26, 2759–2778, https://doi.org/10.5194/hess-26-2759-2022, https://doi.org/10.5194/hess-26-2759-2022, 2022
Short summary
Short summary
New techniques to monitor the performance of irrigation schemes are vital to improve land and water productivity. We developed a framework and applied the remotely sensed FAO WaPOR dataset to assess uniformity, equity, adequacy, and land and water productivity at the Xinavane sugarcane estate, segmented by three irrigation methods. The developed performance assessment framework and the Python script in Jupyter Notebooks can aid in such irrigation performance analysis in other regions.
Dung Trung Vu, Thanh Duc Dang, Stefano Galelli, and Faisal Hossain
Hydrol. Earth Syst. Sci., 26, 2345–2364, https://doi.org/10.5194/hess-26-2345-2022, https://doi.org/10.5194/hess-26-2345-2022, 2022
Short summary
Short summary
The lack of data on how big dams are operated in the Upper Mekong, or Lancang, largely contributes to the ongoing controversy between China and the other Mekong countries. Here, we rely on satellite observations to reconstruct monthly storage time series for the 10 largest reservoirs in the Lancang. Our analysis shows how quickly reservoirs were filled in, what decisions were made during recent droughts, and how these decisions impacted downstream discharge.
Siyuan Tian, Luigi J. Renzullo, Robert C. Pipunic, Julien Lerat, Wendy Sharples, and Chantal Donnelly
Hydrol. Earth Syst. Sci., 25, 4567–4584, https://doi.org/10.5194/hess-25-4567-2021, https://doi.org/10.5194/hess-25-4567-2021, 2021
Short summary
Short summary
Accurate daily continental water balance predictions are valuable in monitoring and forecasting water availability and land surface conditions. A simple and robust method was developed for an operational water balance model to constrain model predictions temporally and spatially with satellite soil moisture observations. The improved soil water storage prediction can provide constraints in model forecasts that persist for several weeks.
Oliver Miguel López Valencia, Kasper Johansen, Bruno José Luis Aragón Solorio, Ting Li, Rasmus Houborg, Yoann Malbeteau, Samer AlMashharawi, Muhammad Umer Altaf, Essam Mohammed Fallatah, Hari Prasad Dasari, Ibrahim Hoteit, and Matthew Francis McCabe
Hydrol. Earth Syst. Sci., 24, 5251–5277, https://doi.org/10.5194/hess-24-5251-2020, https://doi.org/10.5194/hess-24-5251-2020, 2020
Short summary
Short summary
The agricultural sector in Saudi Arabia has expanded rapidly over the last few decades, supported by non-renewable groundwater abstraction. This study describes a novel data–model fusion approach to compile national-scale groundwater abstractions and demonstrates its use over 5000 individual center-pivot fields. This method will allow both farmers and water management agencies to make informed water accounting decisions across multiple spatial and temporal scales.
Angel Martín, Sara Ibáñez, Carlos Baixauli, Sara Blanc, and Ana Belén Anquela
Hydrol. Earth Syst. Sci., 24, 3573–3582, https://doi.org/10.5194/hess-24-3573-2020, https://doi.org/10.5194/hess-24-3573-2020, 2020
Short summary
Short summary
In the case study presented in this paper, the GNSS-IR technique was used to monitor soil moisture during 66 d, from 3 December 2018 to 6 February 2019, in the installations of the Cajamar Centre of Experiences, Paiporta, Valencia, Spain. Two main objectives were pursued. The first was the extension of the technique to a multi-constellation solution using GPS, GLONASS, and GALILEO satellites, and the second was to test whether mass-market sensors could be used for this technique.
Imeshi Weerasinghe, Wim Bastiaanssen, Marloes Mul, Li Jia, and Ann van Griensven
Hydrol. Earth Syst. Sci., 24, 1565–1586, https://doi.org/10.5194/hess-24-1565-2020, https://doi.org/10.5194/hess-24-1565-2020, 2020
Short summary
Short summary
Water resource allocation to various sectors requires an understanding of the hydrological cycle, where evapotranspiration (ET) is a key component. Satellite-derived products estimate ET but are hard to evaluate at large scales. This work presents an alternate evaluation methodology to point-scale observations in Africa. The paper enables users to select an ET product based on their performance regarding selected criteria using a ranking system. The highest ranked products are WaPOR and CMRSET.
Melanie K. Vanderhoof, Jay R. Christensen, and Laurie C. Alexander
Hydrol. Earth Syst. Sci., 23, 4269–4292, https://doi.org/10.5194/hess-23-4269-2019, https://doi.org/10.5194/hess-23-4269-2019, 2019
Short summary
Short summary
We evaluated trends (1984–2016) in riparian wetness across the Upper Missouri River headwaters basin during peak irrigation months (June, July and August). We found that 8 of the 19 riparian reaches across the basin showed a significant drying trend from 1984 to 2016. The temporal drying trends persisted after removing variability attributable to climate. Instead, the drying trends co-occurred with a shift towards center-pivot irrigation across the basin.
Sameer M. Shadeed, Tariq G. Judeh, and Mohammad N. Almasri
Hydrol. Earth Syst. Sci., 23, 1581–1592, https://doi.org/10.5194/hess-23-1581-2019, https://doi.org/10.5194/hess-23-1581-2019, 2019
Short summary
Short summary
The paper aimed to develop DWP and DRWHS maps in the West Bank (Palestine) using an integrated GIS-based MCDA approach. The obtained maps will assist the decision makers to formulate proper strategies including the development of efficient and comprehensive water resource management strategies in trying to bridge the increasing water supply–demand gap for domestic purposes in the West Bank as a recognized area in the Dead Sea region which is facing a series water resource shortage challenges.
Fugen Li, Xiaozhou Xin, Zhiqing Peng, and Qinhuo Liu
Hydrol. Earth Syst. Sci., 23, 949–969, https://doi.org/10.5194/hess-23-949-2019, https://doi.org/10.5194/hess-23-949-2019, 2019
Short summary
Short summary
This study proposes a simple but efficient model for estimating daily evapotranspiration considering heterogeneity of mixed pixels. In order to do so, an equation to calculate evapotranspiration fraction (EF) of mixed pixels was derived based on two key hypotheses. The model is easy to apply and is independent and easy to be embedded in the traditional remote sensing algorithms of heat fluxes to get daily ET.
Philippe Cattan, Jean-Baptiste Charlier, Florence Clostre, Philippe Letourmy, Luc Arnaud, Julie Gresser, and Magalie Jannoyer
Hydrol. Earth Syst. Sci., 23, 691–709, https://doi.org/10.5194/hess-23-691-2019, https://doi.org/10.5194/hess-23-691-2019, 2019
Short summary
Short summary
We investigated the management of long-term environmental pollution by organochlorine pesticides. We selected the case of chlordecone on the island of Martinique. We propose a conceptual model of organochlorine fate accounting for physical conditions relative to soils and geology. This model explains pollution variability in water but also the dynamics of pollution trends. It helps to identify risky areas where pollution will last for a long time and where more attention is needed.
Anoop Kumar Shukla, Shray Pathak, Lalit Pal, Chandra Shekhar Prasad Ojha, Ana Mijic, and Rahul Dev Garg
Hydrol. Earth Syst. Sci., 22, 5357–5371, https://doi.org/10.5194/hess-22-5357-2018, https://doi.org/10.5194/hess-22-5357-2018, 2018
Short summary
Short summary
In this study, we carried out a comparative evaluation of water yield using two approaches, the Lumped Zhang model and the pixel-based approach. Even in pixel-level computations, experiments are made with existing models of some of the involved parameters. The study indicates not only the suitability of pixel-based computations but also clarifies the suitable model of some of the parameters to be used with pixel-based computations to obtain better results.
Anoop Kumar Shukla, Chandra Shekhar Prasad Ojha, Ana Mijic, Wouter Buytaert, Shray Pathak, Rahul Dev Garg, and Satyavati Shukla
Hydrol. Earth Syst. Sci., 22, 4745–4770, https://doi.org/10.5194/hess-22-4745-2018, https://doi.org/10.5194/hess-22-4745-2018, 2018
Short summary
Short summary
Geospatial technologies and OIP are promising tools to study the effect of demographic changes and LULC transformations on the spatiotemporal variations in the water quality (WQ) across a large river basin. Therefore, this study could help to assess and solve local and regional WQ-related problems over a river basin. It may help the policy makers and planners to understand the status of water pollution so that suitable strategies could be planned for sustainable development in a river basin.
Melanie K. Vanderhoof, Charles R. Lane, Michael G. McManus, Laurie C. Alexander, and Jay R. Christensen
Hydrol. Earth Syst. Sci., 22, 1851–1873, https://doi.org/10.5194/hess-22-1851-2018, https://doi.org/10.5194/hess-22-1851-2018, 2018
Short summary
Short summary
Effective monitoring and prediction of flood and drought events requires an improved understanding of surface water dynamics. We examined how the relationship between surface water extent, as mapped using Landsat imagery, and climate, is a function of landscape characteristics, using the Prairie Pothole Region and adjacent Northern Prairie in the United States as our study area. We found that at a landscape scale wetlands play a key role in informing how climate extremes influence surface water.
Mariana Madruga de Brito, Mariele Evers, and Adrian Delos Santos Almoradie
Hydrol. Earth Syst. Sci., 22, 373–390, https://doi.org/10.5194/hess-22-373-2018, https://doi.org/10.5194/hess-22-373-2018, 2018
Short summary
Short summary
This paper sheds light on the integration of interdisciplinary knowledge in the assessment of flood vulnerability in Taquari-Antas river basin, Brazil. It shows how stakeholder participation is crucial for increasing not only the acceptance of model results but also its quality.
Nicolas Avisse, Amaury Tilmant, Marc François Müller, and Hua Zhang
Hydrol. Earth Syst. Sci., 21, 6445–6459, https://doi.org/10.5194/hess-21-6445-2017, https://doi.org/10.5194/hess-21-6445-2017, 2017
Short summary
Short summary
Information on small reservoir storage is crucial for water management in a river basin. However, it is most of the time not freely available in remote, ungauged, or conflict-torn areas. We propose a novel approach using satellite imagery information only to quantitatively estimate storage variations in such inaccessible areas. We apply the method to southern Syria, where ground monitoring is impeded by the ongoing civil war, and validate it against in situ measurements in neighbouring Jordan.
Rangaswamy Madugundu, Khalid A. Al-Gaadi, ElKamil Tola, Abdalhaleem A. Hassaballa, and Virupakshagouda C. Patil
Hydrol. Earth Syst. Sci., 21, 6135–6151, https://doi.org/10.5194/hess-21-6135-2017, https://doi.org/10.5194/hess-21-6135-2017, 2017
Short summary
Short summary
In view of the pressing need to assess the productivity of agricultural fields in Saudi Arabia, this study was undertaken in an attempt to apply the METRIC model with Landsat-8 imagery for the determination of spatial and temporal variability in ET aiming at optimizing the quantification of crop water requirement and the formulation of efficient irrigation schedules. This paper will be of great interest to readers in the areas of agriculture (in general), water management and remote sensing.
Clara Linés, Micha Werner, and Wim Bastiaanssen
Hydrol. Earth Syst. Sci., 21, 4747–4765, https://doi.org/10.5194/hess-21-4747-2017, https://doi.org/10.5194/hess-21-4747-2017, 2017
Short summary
Short summary
This paper aims at identifying Earth observation data sets that can help river basin managers detect drought conditions that may lead to impacts early enough to take mitigation actions. Six remote sensing products were assessed using two types of impact data as a benchmark: media records from a regional newspaper and crop yields. Precipitation, vegetation condition and evapotranspiration products showed the best results, offering early signs of impacts up to 6 months before the reported damages.
Zeinab Takbiri, Ardeshir M. Ebtehaj, and Efi Foufoula-Georgiou
Hydrol. Earth Syst. Sci., 21, 2685–2700, https://doi.org/10.5194/hess-21-2685-2017, https://doi.org/10.5194/hess-21-2685-2017, 2017
Short summary
Short summary
We present a multi-sensor retrieval algorithm for flood extent mapping at high spatial and temporal resolution. While visible bands provide flood mapping at fine spatial resolution, their capability is very limited in a cloudy sky. Passive microwaves can penetrate through clouds but cannot detect small-scale flooded surfaces due to their coarse resolution. The proposed method takes advantage of these two observations to retrieve sub-pixel flooded surfaces in all-sky conditions.
Joseph G. Alfieri, Martha C. Anderson, William P. Kustas, and Carmelo Cammalleri
Hydrol. Earth Syst. Sci., 21, 83–98, https://doi.org/10.5194/hess-21-83-2017, https://doi.org/10.5194/hess-21-83-2017, 2017
Yan Zhao, Yongping Wei, Shoubo Li, and Bingfang Wu
Hydrol. Earth Syst. Sci., 20, 4469–4481, https://doi.org/10.5194/hess-20-4469-2016, https://doi.org/10.5194/hess-20-4469-2016, 2016
Short summary
Short summary
The paper finds that combined inflow from both current and previous years' discharge determines water availability in downstream regions. Temperature determines broad vegetation distribution while hydrological variables show significant effects only in near-river-channel regions. Agricultural development curtailed further vegetation recovery in the studied area. Enhancing current water allocation schemes and regulating regional agricultural activities are required for future restoration.
Markus Enenkel, Christoph Reimer, Wouter Dorigo, Wolfgang Wagner, Isabella Pfeil, Robert Parinussa, and Richard De Jeu
Hydrol. Earth Syst. Sci., 20, 4191–4208, https://doi.org/10.5194/hess-20-4191-2016, https://doi.org/10.5194/hess-20-4191-2016, 2016
Short summary
Short summary
Soil moisture is a crucial variable for a variety of applications, ranging from weather forecasting and agricultural production to the monitoring of floods and droughts. Satellite observations are particularly important in regions where no in situ measurements are available. Our study presents a method to integrate global near-real-time satellite observations from different sensors into one harmonized, daily data set. A first validation shows good results on a global scale.
Behzad Hessari, Adriana Bruggeman, Ali Mohammad Akhoond-Ali, Theib Oweis, and Fariborz Abbasi
Hydrol. Earth Syst. Sci., 20, 1903–1910, https://doi.org/10.5194/hess-20-1903-2016, https://doi.org/10.5194/hess-20-1903-2016, 2016
Short summary
Short summary
Yields of rainfed winter crops such as wheat can be substantially improved with limited supplemental irrigation. The upper Karkheh River basin in Iran has 15 840 km2 of rainfed crops. A GIS method was designed to identify suitable areas for irrigation and a routine was developed to allocate water uses and route the flows downstream. A maximum of 13 % of the rainfed cropland could be irrigated under normal flow, 9 % if environmental flow requirements are considered and 6 % under drought conditions.
Ting Xia, William P. Kustas, Martha C. Anderson, Joseph G. Alfieri, Feng Gao, Lynn McKee, John H. Prueger, Hatim M. E. Geli, Christopher M. U. Neale, Luis Sanchez, Maria Mar Alsina, and Zhongjing Wang
Hydrol. Earth Syst. Sci., 20, 1523–1545, https://doi.org/10.5194/hess-20-1523-2016, https://doi.org/10.5194/hess-20-1523-2016, 2016
Short summary
Short summary
This paper describes a model inter-comparison and validation study conducted using sub-meter resolution thermal data from an aircraft. The model inter-comparison is between a physically based model and a very simple empirical model. The strengths and weaknesses of both modeling approaches for high-resolution mapping of water use in vineyards is described. The findings provide significant insight into the utility of complex versus simple models for precise water resources management.
P. Karimi and W. G. M. Bastiaanssen
Hydrol. Earth Syst. Sci., 19, 507–532, https://doi.org/10.5194/hess-19-507-2015, https://doi.org/10.5194/hess-19-507-2015, 2015
P. Karimi, W. G. M. Bastiaanssen, A. Sood, J. Hoogeveen, L. Peiser, E. Bastidas-Obando, and R. J. Dost
Hydrol. Earth Syst. Sci., 19, 533–550, https://doi.org/10.5194/hess-19-533-2015, https://doi.org/10.5194/hess-19-533-2015, 2015
F. Baup, F. Frappart, and J. Maubant
Hydrol. Earth Syst. Sci., 18, 2007–2020, https://doi.org/10.5194/hess-18-2007-2014, https://doi.org/10.5194/hess-18-2007-2014, 2014
C. Cammalleri, M. C. Anderson, and W. P. Kustas
Hydrol. Earth Syst. Sci., 18, 1885–1894, https://doi.org/10.5194/hess-18-1885-2014, https://doi.org/10.5194/hess-18-1885-2014, 2014
J. L. Stein, M. F. Hutchinson, and J. A. Stein
Hydrol. Earth Syst. Sci., 18, 1917–1933, https://doi.org/10.5194/hess-18-1917-2014, https://doi.org/10.5194/hess-18-1917-2014, 2014
L. Longuevergne, C. R. Wilson, B. R. Scanlon, and J. F. Crétaux
Hydrol. Earth Syst. Sci., 17, 4817–4830, https://doi.org/10.5194/hess-17-4817-2013, https://doi.org/10.5194/hess-17-4817-2013, 2013
O. Merlin
Hydrol. Earth Syst. Sci., 17, 3623–3637, https://doi.org/10.5194/hess-17-3623-2013, https://doi.org/10.5194/hess-17-3623-2013, 2013
R. Guzinski, M. C. Anderson, W. P. Kustas, H. Nieto, and I. Sandholt
Hydrol. Earth Syst. Sci., 17, 2809–2825, https://doi.org/10.5194/hess-17-2809-2013, https://doi.org/10.5194/hess-17-2809-2013, 2013
X. M. Feng, G. Sun, B. J. Fu, C. H. Su, Y. Liu, and H. Lamparski
Hydrol. Earth Syst. Sci., 16, 2617–2628, https://doi.org/10.5194/hess-16-2617-2012, https://doi.org/10.5194/hess-16-2617-2012, 2012
N. Baghdadi, R. Cresson, M. El Hajj, R. Ludwig, and I. La Jeunesse
Hydrol. Earth Syst. Sci., 16, 1607–1621, https://doi.org/10.5194/hess-16-1607-2012, https://doi.org/10.5194/hess-16-1607-2012, 2012
J. Van doninck, J. Peters, H. Lievens, B. De Baets, and N. E. C. Verhoest
Hydrol. Earth Syst. Sci., 16, 773–786, https://doi.org/10.5194/hess-16-773-2012, https://doi.org/10.5194/hess-16-773-2012, 2012
R. R. E. Vernimmen, A. Hooijer, Mamenun, E. Aldrian, and A. I. J. M. van Dijk
Hydrol. Earth Syst. Sci., 16, 133–146, https://doi.org/10.5194/hess-16-133-2012, https://doi.org/10.5194/hess-16-133-2012, 2012
G.-J. Yang, C.-J. Zhao, W.-J. Huang, and J.-H. Wang
Hydrol. Earth Syst. Sci., 15, 2317–2326, https://doi.org/10.5194/hess-15-2317-2011, https://doi.org/10.5194/hess-15-2317-2011, 2011
J. Negrel, P. Kosuth, and N. Bercher
Hydrol. Earth Syst. Sci., 15, 2049–2058, https://doi.org/10.5194/hess-15-2049-2011, https://doi.org/10.5194/hess-15-2049-2011, 2011
R. Fieuzal, B. Duchemin, L. Jarlan, M. Zribi, F. Baup, O. Merlin, O. Hagolle, and J. Garatuza-Payan
Hydrol. Earth Syst. Sci., 15, 1117–1129, https://doi.org/10.5194/hess-15-1117-2011, https://doi.org/10.5194/hess-15-1117-2011, 2011
F. Baup, E. Mougin, P. de Rosnay, P. Hiernaux, F. Frappart, P. L. Frison, M. Zribi, and J. Viarre
Hydrol. Earth Syst. Sci., 15, 603–616, https://doi.org/10.5194/hess-15-603-2011, https://doi.org/10.5194/hess-15-603-2011, 2011
M. Zribi, A. Chahbi, M. Shabou, Z. Lili-Chabaane, B. Duchemin, N. Baghdadi, R. Amri, and A. Chehbouni
Hydrol. Earth Syst. Sci., 15, 345–358, https://doi.org/10.5194/hess-15-345-2011, https://doi.org/10.5194/hess-15-345-2011, 2011
L. A. Gibson, Z. Münch, and J. Engelbrecht
Hydrol. Earth Syst. Sci., 15, 295–310, https://doi.org/10.5194/hess-15-295-2011, https://doi.org/10.5194/hess-15-295-2011, 2011
H. Lievens, N. E. C. Verhoest, E. De Keyser, H. Vernieuwe, P. Matgen, J. Álvarez-Mozos, and B. De Baets
Hydrol. Earth Syst. Sci., 15, 151–162, https://doi.org/10.5194/hess-15-151-2011, https://doi.org/10.5194/hess-15-151-2011, 2011
D. Courault, R. Hadria, F. Ruget, A. Olioso, B. Duchemin, O. Hagolle, and G. Dedieu
Hydrol. Earth Syst. Sci., 14, 1731–1744, https://doi.org/10.5194/hess-14-1731-2010, https://doi.org/10.5194/hess-14-1731-2010, 2010
M. El Haj Tahir, A. Kääb, and C.-Y. Xu
Hydrol. Earth Syst. Sci., 14, 1167–1178, https://doi.org/10.5194/hess-14-1167-2010, https://doi.org/10.5194/hess-14-1167-2010, 2010
Cited articles
Allan, R. P. and Soden, B. J.: Atmospheric warming and the amplification of
precipitation extremes, Science, 321, 1481–1484, 2008. a
Ambika, A. K., Wardlow, B., and Mishra, V.: Remotely sensed high resolution
irrigated area mapping in India for 2000 to 2015, Scientific data, 3,
160118, https://doi.org/10.1038/sdata.2016.118, 2016. a, b
Bastiaanssen, W. G., Menenti, M., Feddes, R., and Holtslag, A.: A remote
sensing surface energy balance algorithm for land (SEBAL). 1. Formulation,
J. Hydrol., 212, 198–212, 1998. a
Bauer-Marschallinger, B., Paulik, C., Hochstöger, S., Mistelbauer, T.,
Modanesi, S., Ciabatta, L., Massari, C., Brocca, L., and Wagner, W.: Soil
Moisture from Fusion of Scatterometer and SAR: Closing the Scale Gap with
Temporal Filtering, Remote Sensing, 10, 1030, https://doi.org/10.3390/rs10071030,
2018. a
Bontemps, S., Defourny, P., Radoux, J., Van Bogaert, E., Lamarche, C., Achard,
F., Mayaux, P., Boettcher, M., Brockmann, C., Kirches, G., Bontemps, S., Defourny, P.,
Radoux, J., Van Bogaert, E., Lamarche, C., Achard, F., Mayaux, P., Boettcher, M.,
Brockmann, C., Kirches, G., Zulkhe, M., Kalogirou, V., Seifert, F. M., and Arino, O.: Consistent
global land cover maps for climate modelling communities: current
achievements of the ESA's land cover CCI, in: Proceedings of the ESA Living
Planet Symposium, Edimburgh, 9–13, 2013. a, b, c
Boucher, O., Myhre, G., and Myhre, A.: Direct human influence of irrigation on
atmospheric water vapour and climate, Clim. Dynam., 22, 597–603, 2004. a
Brocca, L., Melone, F., Moramarco, T., Wagner, W., and Albergel, C.: Scaling
and filtering approaches for the use of satellite soil moisture observations,
in: Remote Sensing of Energy Fluxes and Soil Moisture Content, 415–430,
CRC Press, Boca Raton, 2013. a
Chan, S. K., Bindlish, R., O'Neill, P., Jackson, T., Njoku, E., Dunbar, S.,
Chaubell, J., Piepmeier, J., Yueh, S., Entekhabi, D., Colliander, A., Chen,
F., Cosh, M. H., Caldwell, T., Walker, J., Berg, A., McNairn, H., Thibeault,
M., Martínez-Fernández, J., Uldall, F., Seyfried, M., Bosch, D.,
Starks, P., Holifield Collins, C., Prueger, J., van der Velde, R., Asanuma,
J., Palecki, M., Small, E. E., Zreda, M., Calvet, J., Crow, W. T., and Kerr,
Y.: Development and
assessment of the SMAP enhanced passive soil moisture product, Remote Sens.
Environ., 204, 931–941, 2018. a
Chen, M., Shi, W., Xie, P., Silva, V., Kousky, V. E., Wayne Higgins, R., and
Janowiak, J. E.: Assessing objective techniques for gauge-based analyses of
global daily precipitation, J. Geophys. Res.-Atmos.,
113, D04110, https://doi.org/10.1029/2007JD009132, 2008. a
Chew, C. and Small, E.: Soil moisture sensing using spaceborne GNSS
reflections: Comparison of CYGNSS reflectivity to SMAP soil moisture,
Geophys. Res. Lett., 45, 4049–4057, https://doi.org/10.1029/2018GL077905, 2018. a
Colliander, A., Jackson, T. J., Bindlish, R., Chan, S., Das, N., Kim, S. B.,
Cosh, M. H., Dunbar, R. S., Dang, L., Pashaian, L., Asanuma, J., Aida, K.,
Berg, A., Rowlandson, T., Bosch, D., Caldwell, T., Caylor, K., Goodrich, D.,
al Jassar, H., Lopez-Baeza, E., Martínez-Fernández, J.,
González-Zamora, A., Livingston, S., McNairn, H., Pacheco, A., Moghaddam,
M., Montzka, C., Notarnicola, C., Niedrist, G., Pellarin, T., Prueger, J.,
Pulliainen, J., Rautiainen, K., Ramos, J., Seyfried, M., Starks, P., Su, Z.,
Zeng, Y., van der Velde, R., Thibeault, M., Dorigo, W., Vreugdenhil, M.,
Walker, J. P., Wu, X., Monerris, A., O'Neill, P. E., Entekhabi, D., Njoku, E.
G., and Yueh, S.: Validation of SMAP surface
soil moisture products with core validation sites, Remote Sens.
Environ., 191, 215–231, 2017. a
Daughtry, C., Ranson, K., and Biehl, L.: C-band backscattering from corn
canopies, Int. J. Remote Sens., 12, 1097–1109, 1991. a
der Schalie, R., Kerr, Y., Wigneron, J., Rodríguez-Fernández, N.,
Al-Yaari, A., and Jeu, R.: Global SMOS Soil Moisture Retrievals from The Land
Parameter Retrieval Model, Int. J. Appl. Earth Obs., 45, 125–134,
https://doi.org/10.1016/j.jag.2015.08.005, 2016. a
Döll, P. and Siebert, S.: Global modeling of irrigation water requirements,
Water Resour. Res., 38, 8-1–8-10, https://doi.org/10.1029/2001WR000355, 2002. a
Dorigo, W., Xaver, A., Vreugdenhil, M., Gruber, A., Hegyiova, A.,
Sanchis-Dufau, A., Zamojski, D., Cordes, C., Wagner, W., and Drusch, M.:
Global automated quality control of in situ soil moisture data from the
International Soil Moisture Network, Vadose Zone J., 12, https://doi.org/10.2136/vzj2012.0097, 2013. a
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. a, b, c
Entekhabi, D., Njoku, E. G., O'Neill, P. E., Kellogg, K. H., Crow, W. T.,
Edelstein, W. N., Entin, J. K., Goodman, S. D., Jackson, T. J., Johnson, J.,
Kimball, J., Piepmeier, J. R., Koster, R. D., Martin, N., McDonald, K. C.,
Moghaddam, M., Moran, S., Reichle, R., Shi, J. C., Spencer, M. W., Thurman,
S. W., Tsang, L., and Van Zyl, J.: The soil moisture active
passive (SMAP) mission, P. IEEE, 98, 704–716, 2010. a, b, c
Foley, J. A., Ramankutty, N., Brauman, K. A., Cassidy, E. S., Gerber, J. S.,
Johnston, M., Mueller, N. D., O'Connell, C., Ray, D. K., West, P. C., Balzer,
C., Bennett, E. M., Carpenter, S. R., Hill, J., Monfreda, C., Polasky, S.,
Rockström, J., Sheehan, J., Siebert, S., Tilman, D., and Zaks, D. P. M.:
Solutions for a cultivated planet, Nature, 478, 337–342, 2011. a
Gruber, A., Dorigo, W. A., Crow, W., and Wagner, W.: Triple collocation-based
merging of satellite soil moisture retrievals, IEEE T.
Geosci. Remote, 55, 6780–6792, 2017. a
Hahn, S., Reimer, C., Vreugdenhil, M., Melzer, T., and Wagner, W.: Dynamic
characterization of the incidence angle dependence of backscatter using metop
ASCAT, IEEE J. Sel. Top. Appl., 10, 2348–2359, 2017. a
Hain, C. R., Crow, W. T., Anderson, M. C., and Yilmaz, M. T.: Diagnosing
neglected soil moisture source–sink processes via a thermal infrared–based
two-source energy balance model, J. Hydrometeorol., 16, 1070–1086,
2015. a
Howitt, R.: Preliminary Analysis: 2015 Drought Economic Impact Study, Tech.
rep., California Department of Food and Agriculture, 2015. a
Imaoka, K., Kachi, M., Fujii, H., Murakami, H., Hori, M., Ono, A., Igarashi,
T., Nakagawa, K., Oki, T., Honda, Y., and Shimoda, H.: Global Change
Observation
Mission (GCOM) for monitoring carbon, water cycles, and climate change,
P. IEEE, 98, 717–734, 2010. a
Jackson, T. E. A.: Soil Moisture Active Passive (SMAP) Project: Calibration and
Validation for the L2/3_SM_P Version 5 and L2/3_SM_P_E Version 5 Data
Products, NASA, 2018. a
Joseph, A., van der Velde, R., O'neill, P., Lang, R., and Gish, T.: Effects of
corn on C-and L-band radar backscatter: A correction method for soil moisture
retrieval, Remote Sens. Environ., 114, 2417–2430, 2010. a
Kebede, H., Fisher, D. K., Sui, R., Reddy, K. N.: Irrigation methods
and scheduling in the delta region of Mississippi: Current status and
strategies to improve irrigation efficiency, American Journal of Plant
Sciences, 5, 50005, https://doi.org/10.4236/ajps.2014.520307, 2014. a
Kueppers, L. M., Snyder, M. A., and Sloan, L. C.: Irrigation cooling effect:
Regional climate forcing by land-use change, Geophys. Res. Lett.,
34, L03703, https://doi.org/10.1029/2006GL028679, 2007. a, b, c
Kumar, S. V., Peters-Lidard, C. D., Santanello, J. A., Reichle, R. H.,
Draper, C. S., Koster, R. D., Nearing, G., and Jasinski, M. F.: Evaluating
the utility of satellite soil moisture retrievals over irrigated areas and
the ability of land data assimilation methods to correct for unmodeled
processes, Hydrol. Earth Syst. Sci., 19, 4463–4478,
https://doi.org/10.5194/hess-19-4463-2015, 2015. a, b, c
Kumar, S. V., Jasinski, M., Mocko, D., Rodell, M., Borak, J., Li, B.,
Kato Beaudoing, H., and Peters-Lidard, C. D.: NCA-LDAS land analysis:
Development and performance of a multisensor, multivariate land data
assimilation system for the National Climate Assessment, J.
Hydrometeorol., https://doi.org/10.1175/JHM-D-17-0125.1, 2018. a, b
Kummu, M., Guillaume, J., De Moel, H., Eisner, S., Flörke, M., Porkka, M.,
Siebert, S., Veldkamp, T., and Ward, P.: The world's road to water scarcity:
shortage and stress in the 20th century and pathways towards sustainability,
Sci. Rep.-UK, 6, 38495, https://doi.org/10.1038/srep38495, 2016. a
Le Toan, T., Ribbes, F., Wang, L.-F., Floury, N., Ding, K.-H., Kong, J. A.,
Fujita, M., and Kurosu, T.: Rice crop mapping and monitoring using ERS-1 data
based on experiment and modeling results, IEEE T. Geosci.
Remote, 35, 41–56, 1997. a
Linquist, B., Snyder, R., Anderson, F., Espino, L., Inglese, G., Marras, S.,
Moratiel, R., Mutters, R., Nicolosi, P., Rejmanek, H., Russo, A., Shapland,
T., Song, Z., Swelam, A., Tindula, G., and Hill, J.: Water balances
and evapotranspiration in water-and dry-seeded rice systems, Irrigation
Sci., 33, 375–385, 2015. a, b
Lobell, D. B., Bala, G., and Duffy, P. B.: Biogeophysical impacts of cropland
management changes on climate, Geophys. Res. Lett., 33, l06708,
https://doi.org/10.1029/2005GL025492, 2006. a, b, c
Loveland, T. R., Reed, B. C., Brown, J. F., Ohlen, D. O., Zhu, Z., Yang, L.,
and Merchant, J. W.: Development of a global land cover characteristics
database and IGBP DISCover from 1 km AVHRR data, Int. J.
Remote Sens., 21, 1303–1330, 2000. a
Masson, V., Le Moigne, P., Martin, E., Faroux, S., Alias, A., Alkama, R.,
Belamari, S., Barbu, A., Boone, A., Bouyssel, F., Brousseau, P., Brun, E.,
Calvet, J.-C., Carrer, D., Decharme, B., Delire, C., Donier, S., Essaouini,
K., Gibelin, A.-L., Giordani, H., Habets, F., Jidane, M., Kerdraon, G.,
Kourzeneva, E., Lafaysse, M., Lafont, S., Lebeaupin Brossier, C., Lemonsu,
A., Mahfouf, J.-F., Marguinaud, P., Mokhtari, M., Morin, S., Pigeon, G.,
Salgado, R., Seity, Y., Taillefer, F., Tanguy, G., Tulet, P., Vincendon, B.,
Vionnet, V., and Voldoire, A.: The SURFEXv7.2 land and ocean surface platform
for coupled or offline simulation of earth surface variables and fluxes,
Geosci. Model Dev., 6, 929–960, https://doi.org/10.5194/gmd-6-929-2013,
2013. a
McColl, K. A., Alemohammad, S. H., Akbar, R., Konings, A. G., Yueh, S., and
Entekhabi, D.: The global distribution and dynamics of surface soil moisture,
Nat. Geosci., 10, 100–104, https://doi.org/10.1038/ngeo2868,
2017. a
Meier, J., Zabel, F., and Mauser, W.: A global approach to estimate irrigated
areas – a comparison between different data and statistics, Hydrol. Earth
Syst. Sci., 22, 1119–1133, https://doi.org/10.5194/hess-22-1119-2018, 2018. a
Naeimi, V., Scipal, K., Bartalis, Z., Hasenauer, S.,
and Wagner, W.: An
improved soil moisture retrieval algorithm for ERS and METOP scatterometer
observations, IEEE T. Geosci. Remote, 47,
1999–2013, 2009. a
NASS, U.: Usual planting and harvesting dates for US field crops, Tech. rep.,
NASS, USDA, 2010. a
Nguyen, D. B., Clauss, K., Cao, S., Naeimi, V., Kuenzer, C., and Wagner, W.:
Mapping Rice Seasonality in the Mekong Delta with Multi-Year Envisat ASAR WSM
Data, Remote Sensing, 7, 15868–15893, https://doi.org/10.3390/rs71215808,
2015. a, b, c
Nguyen, D. B., Gruber, A., and Wagner, W.: Mapping rice extent and cropping
scheme in the Mekong Delta using Sentinel-1A data, Remote Sens. Lett., 7,
1209–1218, 2016. a
O'Neill, P. E., Chan, S., Njoku, E. G., Jackson, T., and Bindlish, R.: SMAP
L2 Radiometer Half-Orbit 36 km EASE-Grid Soil Moisture, Version 5, [Indicate
subset used], Boulder, Colorado USA, NASA National Snow and Ice Data Center
Distributed Active Archive Center, https://doi.org/10.5067/SODMLCE6LGLL, 2018. a
Owe, M., de Jeu, R., and Holmes, T.: Multisensor historical climatology of
satellite-derived global land surface moisture, J. Geophys.
Res.-Earth, 113, F01002, https://doi.org/10.1029/2007JF000769, 2008. a
Ozdogan, M. and Gutman, G.: A new methodology to map irrigated areas using
multi-temporal MODIS and ancillary data: An application example in the
continental US, Remote Sens. Environ., 112, 3520–3537,
https://doi.org/10.1016/j.rse.2008.04.010, 2008. a
Ozdogan, M., Rodell, M., Beaudoing, H. K., and Toll, D. L.: Simulating the
Effects of Irrigation over the United States in a Land Surface Model Based on
Satellite-Derived Agricultural Data, J. Hydrometeorol., 11,
171–184, https://doi.org/10.1175/2009jhm1116.1, 2010a. a
Ozdogan, M., Yang, Y., Allez, G., and Cervantes, C.: Remote Sensing of
Irrigated Agriculture: Opportunities and Challenges, Remote Sensing, 2,
2274–2304, https://doi.org/10.3390/rs2092274, 2010b. a
Pereira, L. S., Oweis, T., and Zairi, A.: Irrigation management under water
scarcity, Agr. Water Manage., 57, 175–206, 2002. a
Pervez, M. S. and Brown, J. F.: Mapping Irrigated Lands at 250-m Scale by
Merging MODIS Data and National Agricultural Statistics, Remote Sensing, 2,
2388–2412, https://doi.org/10.3390/rs2102388, 2010. a, b, c, d
Pervez, S., Brown, J. F., and Maxwell, S.: Evaluation of remote sensing-based
irrigated area map for the Conterminous United States, Proceedings of the
ASPRS Pecora, 17, https://www.asprs.org/a/publications/proceedings/pecora17/0027.pdf (last access: 10 May 2018), 2008. a
Portmann, F. T., Siebert, S., and Döll, P.: MIRCA2000 – Global monthly
irrigated and rainfed crop areas around the year 2000: A new high-resolution
data set for agricultural and hydrological modeling, Global Biogeochem.
Cy., 24, GB1011, https://doi.org/10.1029/2008GB003435, 2010. a, b
Pun, M., Mutiibwa, D., and Li, R.: Land Use Classification: A Surface Energy
Balance and Vegetation Index Application to Map and Monitor Irrigated Lands,
Remote Sensing, 9, 1256, https://doi.org/10.3390/rs9121256, 2017. a
Qiu, J., Gao, Q., Wang, S., and Su, Z.: Comparison of temporal trends from
multiple soil moisture data sets and precipitation: The implication of
irrigation on regional soil moisture trend, Int. J. Appl.
Earth Obs., 48, 17–27, 2016. a
Reichle, R. H., Draper, C. S., Liu, Q., Girotto, M., Mahanama, S. P., Koster,
R. D., and De Lannoy, G. J.: Assessment of MERRA-2 land surface hydrology
estimates, J. Climate, 30, 2937–2960,
https://doi.org/10.1175/JCLI-D-16-0720.1,
2017a. a
Reichle, R. H., Draper, C. S., Liu, Q., Girotto, M., Mahanama, S. P., Koster,
R. D., and De Lannoy, G. J.: Assessment of MERRA-2 land surface hydrology
estimates, J. Climate, 30, 2937–2960, 2017b. a
Reichle, R. H., Liu, Q., Koster, R. D., Draper, C. S., Mahanama, S. P., and
Partyka, G. S.: Land surface precipitation in MERRA-2, J. Climate,
30, 1643–1664, https://doi.org/10.1175/JCLI-D-16-0570.1,
2017c. a
Rockström, J., Falkenmark, M., Lannerstad, M., and Karlberg, L.: The
planetary water drama: Dual task of feeding humanity and curbing climate
change, Geophys. Res. Lett., 39, L15401, https://doi.org/10.1029/2012GL051688, 2012. a
Rosas, J., Houborg, R., and McCabe, M. F.: Sensitivity of Landsat 8 Surface
Temperature Estimates to Atmospheric Profile Data: A Study Using MODTRAN in
Dryland Irrigated Systems, Remote Sensing, 9, 988, https://doi.org/10.3390/rs9100988, 2017. a
Roseta-Palma, C., Iglesias, E., and Koppl-Turyna, M.: Illegal groundwater
pumping, in: 5th World Congress of Environmental and Resource Economists,
Istanbul, Turkey, paper, vol. 863, 2014. a
Sacks, W. J., Cook, B. I., Buenning, N., Levis, S., and Helkowski, J. H.:
Effects of global irrigation on the near-surface climate, Clim. Dynam.,
33, 159–175, https://doi.org/10.1007/s00382-008-0445-z, 2009. a, b, c
Saffi, M. and Cheddadi, A.: Identification of illegal groundwater pumping in
semi-confined aquifers, Hydrolog. Sci. J., 55, 1348–1356, 2010. a
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. a
Shiklomanov, I. A.: Appraisal and assessment of world water resources, Water
Int., 25, 11–32, 2000. a
Siebert, S., Döll, P., Hoogeveen, J., Faures, J.-M., Frenken, K., and
Feick, S.: Development and validation of the global map of irrigation areas,
Hydrol. Earth Syst. Sci., 9, 535–547,
https://doi.org/10.5194/hess-9-535-2005, 2005. a, b, c
Siebert, S., Döll, P., Feick, S., Hoogeveen, J., and Frenken, K.: Global
map of irrigation areas version 4.0. 1, Johann Wolfgang Goethe University,
Frankfurt am Main, Germany/Food and Agriculture Organization of the United
Nations, Rome, Italy, 2007. a
Siebert, S., Burke, J., Faures, J. M., Frenken, K., Hoogeveen, J., Döll,
P., and Portmann, F. T.: Groundwater use for irrigation – a global
inventory, Hydrol. Earth Syst. Sci., 14, 1863–1880,
https://doi.org/10.5194/hess-14-1863-2010, 2010. a, b
Siebert, S., Kummu, M., Porkka, M., Döll, P., Ramankutty, N., and
Scanlon, B. R.: A global data set of the extent of irrigated land from 1900
to 2005, Hydrol. Earth Syst. Sci., 19, 1521–1545,
https://doi.org/10.5194/hess-19-1521-2015, 2015. a
Taylor, R. G., Scanlon, B., Döll, P., Rodell, M., van Beek, R., Wada, Y.,
Longuevergne, L., Leblanc, M., Famiglietti, J. S., Edmunds, M., Konikow, L.,
Green, T. R., Chen, J., Taniguchi, M., Bierkens, M. F. P., MacDonald, A.,
Fan, Y., Maxwell, R. M., Yechieli, Y., Gurdak, J. J., Allen, D. M.,
Shamsudduha, M., Hiscock, K., Yeh, P. J. F., Holman, I., and Treidel, H.:
Ground water and climate change, Nat. Clim. Change, 3, 322–329,
https://doi.org/10.1038/nclimate1744, 2012. a
Teluguntla, P., Thenkabail, P. S., Xiong, J., Gumma, M. K., Congalton, R. G.,
Oliphant, A., Poehnelt, J., Yadav, K., Rao, M., and Massey, R.: Spectral
matching techniques (SMTs) and automated cropland classification algorithms
(ACCAs) for mapping croplands of Australia using MODIS 250-m time-series
(2000–2015) data, Int. J. Digit. Earth, 10, 944–977, 2017. a
Thenkabail, P. S., Biradar, C. M., Noojipady, P., Dheeravath, V., Li, Y.,
Velpuri, M., Gumma, M., Gangalakunta, O. R. P., Turral, H., Cai, X.,
Vithanage, J., Schull, M. A., and Dutta, R.:
Global irrigated area map (GIAM), derived from remote sensing, for the end of
the last millennium, Int. J. Remote Sens., 30, 3679–3733,
2009. a
Thiery, W., Davin, E. L., Lawrence, D. M., Hirsch, A. L., Hauser, M., and
Seneviratne, S. I.: Present-day irrigation mitigates heat extremes, J.
Geophys. Res.-Atmos., 122, 1403–1422, 2017. a
Tuinenburg, O. and Vries, J.: Irrigation Patterns Resemble ERA-Interim
Reanalysis Soil Moisture Additions, Geophys. Res. Lett., 44, 10341–10348,
https://doi.org/10.1002/2017GL074884, 2017. a, b
Vreugdenhil, M., Dorigo, W. A., Wagner, W., De Jeu, R. A., Hahn, S., and
Van Marle, M. J.: Analyzing the vegetation parameterization in the TU-Wien
ASCAT soil moisture retrieval, IEEE T. Geosci. Remote, 54, 3513–3531, 2016. a
Wagner, W., Lemoine, G., and Rott, H.: A method for estimating soil moisture
from ERS scatterometer and soil data, Remote Sens. Environ., 70,
191–207, 1999. a
Wagner, W., Hahn, S., Kidd, R., Melzer, T., Bartalis, Z., Hasenauer, S.,
Figa-Saldaña, J., de Rosnay, P., Jann, A., Schneider, S., Komma, J.,
Kubu, G., Brugger, K., Aubrecht, C., Züger, J., Gangkofner, U.,
Kienberger, S., Brocca, L., Wang, Y., Blöschl, G., Eitzinger, J., and
Steinnocher, K.: The
ASCAT soil moisture product: A review of its specifications, validation
results, and emerging applications, Meteorol. Z., 22, 5–33,
2013. a
Wei, J., Dirmeyer, P. A., Wisser, D., Bosilovich, M. G., and Mocko, D. M.:
Where Does the Irrigation Water Go? An Estimate of the Contribution of
Irrigation to Precipitation Using MERRA, J. Hydrometeorol., 14,
275–289, https://doi.org/10.1175/jhm-d-12-079.1, 2013. a, b
Xie, P., Chen, M., and Shi, W.: CPC unified gauge-based analysis of global
daily precipitation, in: Preprints, 24th Conf. on Hydrology, Atlanta, GA,
Amer. Meteor. Soc, vol. 2,
available at: https://ams.confex.com/ams/90annual/techprogram/paper_163676.htm (last access: 5 June 2018), 2010. a
Short summary
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.
About 70 % of global freshwater is consumed by irrigation. Yet, policy-relevant estimates of...
