Articles | Volume 18, issue 11
https://doi.org/10.5194/hess-18-4467-2014
© Author(s) 2014. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
https://doi.org/10.5194/hess-18-4467-2014
© Author(s) 2014. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
Research article
| 
07 Nov 2014
Research article |
| 07 Nov 2014
Evaluation of the satellite-based Global Flood Detection System for measuring river discharge: influence of local factors
B. Revilla-Romero
CORRESPONDING AUTHOR
European Commission Joint Research Centre, Ispra, Italy
Utrecht University, Faculty of Geosciences, Utrecht, the Netherlands
J. Thielen
European Commission Joint Research Centre, Ispra, Italy
P. Salamon
European Commission Joint Research Centre, Ispra, Italy
T. De Groeve
European Commission Joint Research Centre, Ispra, Italy
G. R. Brakenridge
University of Colorado Boulder, Boulder, USA
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Andrea Betterle and Peter Salamon
Nat. Hazards Earth Syst. Sci., 24, 2817–2836, https://doi.org/10.5194/nhess-24-2817-2024, https://doi.org/10.5194/nhess-24-2817-2024, 2024
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The study proposes a new framework, named FLEXTH, to estimate flood water depth and improve satellite-based flood monitoring using topographical data. FLEXTH is readily available as a computer code, offering a practical and scalable solution for estimating flood depth quickly and systematically over large areas. The methodology can reduce the impacts of floods and enhance emergency response efforts, particularly where resources are limited.
Margarita Choulga, Francesca Moschini, Cinzia Mazzetti, Stefania Grimaldi, Juliana Disperati, Hylke Beck, Peter Salamon, and Christel Prudhomme
Hydrol. Earth Syst. Sci., 28, 2991–3036, https://doi.org/10.5194/hess-28-2991-2024, https://doi.org/10.5194/hess-28-2991-2024, 2024
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CEMS_SurfaceFields_2022 dataset is a new set of high-resolution maps for land type (e.g. lake, forest), soil properties and population water needs at approximately 2 and 6 km at the Equator, covering Europe and the globe (excluding Antarctica). We describe what and how new high-resolution information can be used to create the dataset. The paper suggests that the dataset can be used as input for river, weather or other models, as well as for statistical descriptions of the region of interest.
Florian Roth, Bernhard Bauer-Marschallinger, Mark Edwin Tupas, Christoph Reimer, Peter Salamon, and Wolfgang Wagner
Nat. Hazards Earth Syst. Sci., 23, 3305–3317, https://doi.org/10.5194/nhess-23-3305-2023, https://doi.org/10.5194/nhess-23-3305-2023, 2023
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In August and September 2022, millions of people were impacted by a severe flood event in Pakistan. Since many roads and other infrastructure were destroyed, satellite data were the only way of providing large-scale information on the flood's impact. Based on the flood mapping algorithm developed at Technische Universität Wien (TU Wien), we mapped an area of 30 492 km2 that was flooded at least once during the study's time period. This affected area matches about the total area of Belgium.
Shaun Harrigan, Ervin Zsoter, Hannah Cloke, Peter Salamon, and Christel Prudhomme
Hydrol. Earth Syst. Sci., 27, 1–19, https://doi.org/10.5194/hess-27-1-2023, https://doi.org/10.5194/hess-27-1-2023, 2023
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Real-time river discharge forecasts and reforecasts from the Global Flood Awareness System (GloFAS) have been made publicly available, together with an evaluation of forecast skill at the global scale. Results show that GloFAS is skillful in over 93 % of catchments in the short (1–3 d) and medium range (5–15 d) and skillful in over 80 % of catchments in the extended lead time (16–30 d). Skill is summarised in a new layer on the GloFAS Web Map Viewer to aid decision-making.
Vera Thiemig, Goncalo N. Gomes, Jon O. Skøien, Markus Ziese, Armin Rauthe-Schöch, Elke Rustemeier, Kira Rehfeldt, Jakub P. Walawender, Christine Kolbe, Damien Pichon, Christoph Schweim, and Peter Salamon
Earth Syst. Sci. Data, 14, 3249–3272, https://doi.org/10.5194/essd-14-3249-2022, https://doi.org/10.5194/essd-14-3249-2022, 2022
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EMO-5 is a free and open European high-resolution (5 km), sub-daily, multi-variable (precipitation, temperatures, wind speed, solar radiation, vapour pressure), multi-decadal meteorological dataset based on quality-controlled observations coming from almost 30 000 stations across Europe, and is produced in near real-time. EMO-5 (v1) covers the time period from 1990 to 2019. In this paper, we have provided insight into the source data, the applied methods, and the quality assessment of EMO-5.
Francesco Dottori, Lorenzo Alfieri, Alessandra Bianchi, Jon Skoien, and Peter Salamon
Earth Syst. Sci. Data, 14, 1549–1569, https://doi.org/10.5194/essd-14-1549-2022, https://doi.org/10.5194/essd-14-1549-2022, 2022
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We present a set of hazard maps for river flooding for Europe and the Mediterranean basin. The maps depict inundation extent and depth for flood probabilities for up to 1-in-500-year flood hazards and are based on hydrological and hydrodynamic models driven by observed climatology. The maps can identify two-thirds of the flood extent reported by official flood maps, with increasing skill for higher-magnitude floods. The maps are used for evaluating present and future impacts of river floods.
Shaun Harrigan, Ervin Zsoter, Lorenzo Alfieri, Christel Prudhomme, Peter Salamon, Fredrik Wetterhall, Christopher Barnard, Hannah Cloke, and Florian Pappenberger
Earth Syst. Sci. Data, 12, 2043–2060, https://doi.org/10.5194/essd-12-2043-2020, https://doi.org/10.5194/essd-12-2043-2020, 2020
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A new river discharge reanalysis dataset is produced operationally by coupling ECMWF's latest global atmospheric reanalysis, ERA5, with the hydrological modelling component of the Global Flood Awareness System (GloFAS). The GloFAS-ERA5 reanalysis is a global gridded dataset with a horizontal resolution of 0.1° at a daily time step and is freely available from 1979 until near real time. The evaluation against observations shows that the GloFAS-ERA5 reanalysis was skilful in 86 % of catchments.
W. Wagner, V. Freeman, S. Cao, P. Matgen, M. Chini, P. Salamon, N. McCormick, S. Martinis, B. Bauer-Marschallinger, C. Navacchi, M. Schramm, C. Reimer, and C. Briese
ISPRS Ann. Photogramm. Remote Sens. Spatial Inf. Sci., V-3-2020, 641–648, https://doi.org/10.5194/isprs-annals-V-3-2020-641-2020, https://doi.org/10.5194/isprs-annals-V-3-2020-641-2020, 2020
Rebecca Emerton, Ervin Zsoter, Louise Arnal, Hannah L. Cloke, Davide Muraro, Christel Prudhomme, Elisabeth M. Stephens, Peter Salamon, and Florian Pappenberger
Geosci. Model Dev., 11, 3327–3346, https://doi.org/10.5194/gmd-11-3327-2018, https://doi.org/10.5194/gmd-11-3327-2018, 2018
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Global overviews of upcoming flood and drought events are key for many applications from agriculture to disaster risk reduction. Seasonal forecasts are designed to provide early indications of such events weeks or even months in advance. This paper introduces GloFAS-Seasonal, the first operational global-scale seasonal hydro-meteorological forecasting system producing openly available forecasts of high and low river flow out to 4 months ahead.
Francesco Dottori, Milan Kalas, Peter Salamon, Alessandra Bianchi, Lorenzo Alfieri, and Luc Feyen
Nat. Hazards Earth Syst. Sci., 17, 1111–1126, https://doi.org/10.5194/nhess-17-1111-2017, https://doi.org/10.5194/nhess-17-1111-2017, 2017
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We present a method to use river flow forecasts to estimate the impacts of flood events in terms of flood-prone areas, economic damage, cities and population at risk. We tested our method by simulating the catastrophic floods occurred in May 2014 in Southern Europe. Comparison with observed data shows that our simulations can predict flooded areas and flood impacts well in advance. The method is now being used for real-time risk forecasts to help emergency response and management.
Michalis I. Vousdoukas, Evangelos Voukouvalas, Lorenzo Mentaschi, Francesco Dottori, Alessio Giardino, Dimitrios Bouziotas, Alessandra Bianchi, Peter Salamon, and Luc Feyen
Nat. Hazards Earth Syst. Sci., 16, 1841–1853, https://doi.org/10.5194/nhess-16-1841-2016, https://doi.org/10.5194/nhess-16-1841-2016, 2016
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Coastal flooding has severe socioeconomic impacts that are projected to increase under the changing climate. The present contribution reports on efforts towards a new methodology for mapping coastal flood hazard at European scale, combining the contribution of waves, improved inundation modeling and an open, physics-based framework which can be constantly upgraded whenever new and more accurate data become available.
Lorenzo Alfieri, Luc Feyen, Peter Salamon, Jutta Thielen, Alessandra Bianchi, Francesco Dottori, and Peter Burek
Nat. Hazards Earth Syst. Sci., 16, 1401–1411, https://doi.org/10.5194/nhess-16-1401-2016, https://doi.org/10.5194/nhess-16-1401-2016, 2016
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This work couples recent advances in large scale flood hazard mapping into a pan-European flood risk model to estimate the impact of river floods in a seamless simulation, covering more than two decades.
Results of this research are an important contribution in the reconstruction of a complete dataset of flood impact data. Also, it has direct implications in the area of flood early warning with regard to the rapid risk assessment of flood impacts.
Jon Olav Skøien, Konrad Bogner, Peter Salamon, Paul Smith, and Florian Pappenberger
Proc. IAHS, 373, 109–114, https://doi.org/10.5194/piahs-373-109-2016, https://doi.org/10.5194/piahs-373-109-2016, 2016
V. Thiemig, B. Bisselink, F. Pappenberger, and J. Thielen
Hydrol. Earth Syst. Sci., 19, 3365–3385, https://doi.org/10.5194/hess-19-3365-2015, https://doi.org/10.5194/hess-19-3365-2015, 2015
F. Wetterhall, F. Pappenberger, L. Alfieri, H. L. Cloke, J. Thielen-del Pozo, S. Balabanova, J. Daňhelka, A. Vogelbacher, P. Salamon, I. Carrasco, A. J. Cabrera-Tordera, M. Corzo-Toscano, M. Garcia-Padilla, R. J. Garcia-Sanchez, C. Ardilouze, S. Jurela, B. Terek, A. Csik, J. Casey, G. Stankūnavičius, V. Ceres, E. Sprokkereef, J. Stam, E. Anghel, D. Vladikovic, C. Alionte Eklund, N. Hjerdt, H. Djerv, F. Holmberg, J. Nilsson, K. Nyström, M. Sušnik, M. Hazlinger, and M. Holubecka
Hydrol. Earth Syst. Sci., 17, 4389–4399, https://doi.org/10.5194/hess-17-4389-2013, https://doi.org/10.5194/hess-17-4389-2013, 2013
L. Alfieri, P. Burek, E. Dutra, B. Krzeminski, D. Muraro, J. Thielen, and F. Pappenberger
Hydrol. Earth Syst. Sci., 17, 1161–1175, https://doi.org/10.5194/hess-17-1161-2013, https://doi.org/10.5194/hess-17-1161-2013, 2013
R. S. Westerhoff, M. P. H. Kleuskens, H. C. Winsemius, H. J. Huizinga, G. R. Brakenridge, and C. Bishop
Hydrol. Earth Syst. Sci., 17, 651–663, https://doi.org/10.5194/hess-17-651-2013, https://doi.org/10.5194/hess-17-651-2013, 2013
Related subject area
Subject: Global hydrology | Techniques and Approaches: Remote Sensing and GIS
Technical note: Surface fields for global environmental modelling
Benchmarking multimodel terrestrial water storage seasonal cycle against Gravity Recovery and Climate Experiment (GRACE) observations over major global river basins
Increasing seasonal variation in the extent of rivers and lakes from 1984 to 2022
Interannual Variations of Terrestrial Water Storage in the East African Rift Region
Investigating sources of variability in closing the terrestrial water balance with remote sensing
Dynamic rainfall erosivity estimates derived from IMERG data
A global analysis of water storage variations from remotely sensed soil moisture and daily satellite gravimetry
Soil moisture estimates at 1 km resolution making a synergistic use of Sentinel data
Global evaluation of the “dry gets drier, and wet gets wetter” paradigm from a terrestrial water storage change perspective
Global assessment of subnational drought impact based on the Geocoded Disasters dataset and land reanalysis
Scaling methods of leakage correction in GRACE mass change estimates revisited for the complex hydro-climatic setting of the Indus Basin
Remotely sensed reservoir water storage dynamics (1984–2015) and the influence of climate variability and management at a global scale
Characterizing natural variability in complex hydrological systems using passive microwave-based climate data records: a case study for the Okavango Delta
High-resolution (1 km) satellite rainfall estimation from SM2RAIN applied to Sentinel-1: Po River basin as a case study
The accuracy of temporal upscaling of instantaneous evapotranspiration to daily values with seven upscaling methods
Global component analysis of errors in three satellite-only global precipitation estimates
Estimation of hydrological drought recovery based on precipitation and Gravity Recovery and Climate Experiment (GRACE) water storage deficit
Intercomparison of freshwater fluxes over ocean and investigations into water budget closure
Widespread decline in terrestrial water storage and its link to teleconnections across Asia and eastern Europe
Assimilation of vegetation optical depth retrievals from passive microwave radiometry
Long-term total water storage change from a Satellite Water Cycle reconstruction over large southern Asian basins
Global partitioning of runoff generation mechanisms using remote sensing data
Land–atmosphere interactions in the tropics – a review
Global-scale human pressure evolution imprints on sustainability of river systems
Using GRACE in a streamflow recession to determine drainable water storage in the Mississippi River basin
A new dense 18-year time series of surface water fraction estimates from MODIS for the Mediterranean region
Global joint assimilation of GRACE and SMOS for improved estimation of root-zone soil moisture and vegetation response
Using modelled discharge to develop satellite-based river gauging: a case study for the Amazon Basin
Global downscaling of remotely sensed soil moisture using neural networks
Global 5 km resolution estimates of secondary evaporation including irrigation through satellite data assimilation
Exploring the merging of the global land evaporation WACMOS-ET products based on local tower measurements
Estimating time-dependent vegetation biases in the SMAP soil moisture product
Daily GRACE gravity field solutions track major flood events in the Ganges–Brahmaputra Delta
Controls on surface soil drying rates observed by SMAP and simulated by the Noah land surface model
Quantification of surface water volume changes in the Mackenzie Delta using satellite multi-mission data
Microwave implementation of two-source energy balance approach for estimating evapotranspiration
A global approach to estimate irrigated areas – a comparison between different data and statistics
The future of Earth observation in hydrology
Validation of terrestrial water storage variations as simulated by different global numerical models with GRACE satellite observations
MSWEP: 3-hourly 0.25° global gridded precipitation (1979–2015) by merging gauge, satellite, and reanalysis data
Evaluating the hydrological consistency of evaporation products using satellite-based gravity and rainfall data
Evaluating the strength of the land–atmosphere moisture feedback in Earth system models using satellite observations
Cloud tolerance of remote-sensing technologies to measure land surface temperature
Dynamic changes in terrestrial net primary production and their effects on evapotranspiration
Assessing changes in urban flood vulnerability through mapping land use from historical information
SACRA – a method for the estimation of global high-resolution crop calendars from a satellite-sensed NDVI
A global data set of the extent of irrigated land from 1900 to 2005
Spatial patterns in timing of the diurnal temperature cycle
Potential and limitations of multidecadal satellite soil moisture observations for selected climate model evaluation studies
Global multi-scale segmentation of continental and coastal waters from the watersheds to the continental margins
Margarita Choulga, Francesca Moschini, Cinzia Mazzetti, Stefania Grimaldi, Juliana Disperati, Hylke Beck, Peter Salamon, and Christel Prudhomme
Hydrol. Earth Syst. Sci., 28, 2991–3036, https://doi.org/10.5194/hess-28-2991-2024, https://doi.org/10.5194/hess-28-2991-2024, 2024
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CEMS_SurfaceFields_2022 dataset is a new set of high-resolution maps for land type (e.g. lake, forest), soil properties and population water needs at approximately 2 and 6 km at the Equator, covering Europe and the globe (excluding Antarctica). We describe what and how new high-resolution information can be used to create the dataset. The paper suggests that the dataset can be used as input for river, weather or other models, as well as for statistical descriptions of the region of interest.
Sadia Bibi, Tingju Zhu, Ashraf Rateb, Bridget R. Scanlon, Muhammad Aqeel Kamran, Abdelrazek Elnashar, Ali Bennour, and Ci Li
Hydrol. Earth Syst. Sci., 28, 1725–1750, https://doi.org/10.5194/hess-28-1725-2024, https://doi.org/10.5194/hess-28-1725-2024, 2024
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We assessed 13 global models using GRACE satellite data over 29 river basins. Simulated seasonal water storage cycles showed discrepancies compared to GRACE. The models overestimated seasonal amplitude in boreal basins and showed underestimation in tropical, arid, and temperate zones, with phase differences of 2–3 months compared to GRACE in cold basins and of 1 month in temperate, arid, and semi-arid basins. Seasonal amplitude and phase differences provide insights for model improvement.
Björn Nyberg, Roger Sayre, and Elco Luijendijk
Hydrol. Earth Syst. Sci., 28, 1653–1663, https://doi.org/10.5194/hess-28-1653-2024, https://doi.org/10.5194/hess-28-1653-2024, 2024
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Understanding the spatial and temporal distribution of surface water is crucial for effective water resource management, maintaining ecosystem health and assessing flood risks. This study examined permanent and seasonal rivers and lakes globally over 38 years, uncovering a statistically significant expansion in seasonal extent captured in the new SARL database. The findings offer valuable resources for assessing the impact of changing river and lake extents on ecosystems and human livelihoods.
Eva Boergens, Andreas Güntner, Mike Sips, Christian Schwatke, and Henryk Dobslaw
EGUsphere, https://doi.org/10.5194/egusphere-2024-641, https://doi.org/10.5194/egusphere-2024-641, 2024
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The satellites GRACE and GRACE-FO observe continental terrestrial water storage changes. With over 20 years of data, we can look into long-term variations in the East Africa Rift region. We focus on whether the observed changes are due to natural variations or man-made. We found, both strong influences due to natural variability but also for Lake Victoria the influence of human actions. That is caused by the Nalubaale Dam, which regulates the outflow of Lake Victoria.
Claire I. Michailovsky, Bert Coerver, Marloes Mul, and Graham Jewitt
Hydrol. Earth Syst. Sci., 27, 4335–4354, https://doi.org/10.5194/hess-27-4335-2023, https://doi.org/10.5194/hess-27-4335-2023, 2023
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Many remote sensing products for precipitation, evapotranspiration, and water storage variations exist. However, when these are used with in situ runoff data in water balance closure studies, no single combination of products consistently outperforms others. We analyzed the water balance closure using different products in catchments worldwide and related the results to catchment characteristics. Our results can help identify the dataset combinations best suited for use in different catchments.
Robert A. Emberson
Hydrol. Earth Syst. Sci., 27, 3547–3563, https://doi.org/10.5194/hess-27-3547-2023, https://doi.org/10.5194/hess-27-3547-2023, 2023
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Soil can be eroded by rainfall, and this is a major threat to agricultural sustainability. Estimating the erosivity of rainfall is essential as a first step to determine how much soil might be lost. Until recently, satellite data have not been used to estimate rainfall erosivity, but the data quality is now sufficient to do so. In this study, I test several methods to calculate rainfall erosivity using satellite rainfall data and contrast this with ground-based estimates.
Daniel Blank, Annette Eicker, Laura Jensen, and Andreas Güntner
Hydrol. Earth Syst. Sci., 27, 2413–2435, https://doi.org/10.5194/hess-27-2413-2023, https://doi.org/10.5194/hess-27-2413-2023, 2023
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Soil moisture (SM), a key variable of the global water cycle, is analyzed using two types of satellite observations; microwave sensors measure the top few centimeters and satellite gravimetry (GRACE) the full vertical water column. As SM can change very fast, non-standard daily GRACE data are applied for the first time for this analysis. Jointly analyzing these data gives insight into the SM dynamics at different soil depths, and time shifts indicate the infiltration time into deeper layers.
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
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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.
Jinghua Xiong, Shenglian Guo, Abhishek, Jie Chen, and Jiabo Yin
Hydrol. Earth Syst. Sci., 26, 6457–6476, https://doi.org/10.5194/hess-26-6457-2022, https://doi.org/10.5194/hess-26-6457-2022, 2022
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Although the "dry gets drier, and wet gets wetter (DDWW)" paradigm is prevalent in summarizing wetting and drying trends, we show that only 11.01 %–40.84 % of the global land confirms and 10.21 %–35.43 % contradicts the paradigm during 1985–2014 from a terrestrial water storage change perspective. Similar proportions that intensify with the increasing emission scenarios persist until the end of the 21st century. Findings benefit understanding of global hydrological responses to climate change.
Yuya Kageyama and Yohei Sawada
Hydrol. Earth Syst. Sci., 26, 4707–4720, https://doi.org/10.5194/hess-26-4707-2022, https://doi.org/10.5194/hess-26-4707-2022, 2022
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This study explores the link between hydrometeorological droughts and their socioeconomic impact at a subnational scale based on the newly developed disaster dataset with subnational location information. Hydrometeorological drought-prone areas were generally consistent with socioeconomic drought-prone areas in the disaster dataset. Our analysis clarifies the importance of the use of subnational disaster information.
Vasaw Tripathi, Andreas Groh, Martin Horwath, and Raaj Ramsankaran
Hydrol. Earth Syst. Sci., 26, 4515–4535, https://doi.org/10.5194/hess-26-4515-2022, https://doi.org/10.5194/hess-26-4515-2022, 2022
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GRACE/GRACE-FO provided global observations of water storage change since 2002. Scaling is a common approach to compensate for the spatial filtering inherent to the results. However, for complex hydrological basins, the compatibility of scaling with the characteristics of regional hydrology has been rarely assessed. We assess traditional scaling approaches and a new scaling approach for the Indus Basin. Our results will help users with regional focus understand implications of scaling choices.
Jiawei Hou, Albert I. J. M. van Dijk, Hylke E. Beck, Luigi J. Renzullo, and Yoshihide Wada
Hydrol. Earth Syst. Sci., 26, 3785–3803, https://doi.org/10.5194/hess-26-3785-2022, https://doi.org/10.5194/hess-26-3785-2022, 2022
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We used satellite imagery to measure monthly reservoir water volumes for 6695 reservoirs worldwide for 1984–2015. We investigated how changing precipitation, streamflow, evaporation, and human activity affected reservoir water storage. Almost half of the reservoirs showed significant increasing or decreasing trends over the past three decades. These changes are caused, first and foremost, by changes in precipitation rather than by changes in net evaporation or dam release patterns.
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
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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
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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.
Zhaofei Liu
Hydrol. Earth Syst. Sci., 25, 4417–4433, https://doi.org/10.5194/hess-25-4417-2021, https://doi.org/10.5194/hess-25-4417-2021, 2021
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Instantaneous evapotranspiration (ET), which is detected by the remote sensing technique, needs to be upscaled to daily values in order to practical applications. The accuracy of seven upscaling methods is evaluated by using global observations. The sine function and the evaporative fraction method using extraterrestrial solar irradiance are recommended. Although every upscaling scheme has high accuracy at most sites, it is less accurate at tropical rainforest and tropical monsoon sites.
Hanqing Chen, Bin Yong, Pierre-Emmanuel Kirstetter, Leyang Wang, and Yang Hong
Hydrol. Earth Syst. Sci., 25, 3087–3104, https://doi.org/10.5194/hess-25-3087-2021, https://doi.org/10.5194/hess-25-3087-2021, 2021
Alka Singh, John Thomas Reager, and Ali Behrangi
Hydrol. Earth Syst. Sci., 25, 511–526, https://doi.org/10.5194/hess-25-511-2021, https://doi.org/10.5194/hess-25-511-2021, 2021
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The study demonstrates the utility of Gravity Recovery and Climate Experiment (GRACE) terrestrial water storage anomalies (TWSAs) for obtaining statistics of hydrological droughts, i.e., recovery periods and required precipitation in different precipitation scenarios. The findings of this study are that the GRACE-based drought index is valid for estimating the required precipitation for drought recovery, and the period of drought recovery depends on the intensity of the precipitation.
Marloes Gutenstein, Karsten Fennig, Marc Schröder, Tim Trent, Stephan Bakan, J. Brent Roberts, and Franklin R. Robertson
Hydrol. Earth Syst. Sci., 25, 121–146, https://doi.org/10.5194/hess-25-121-2021, https://doi.org/10.5194/hess-25-121-2021, 2021
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The net exchange of water between the surface and atmosphere is mainly determined by the freshwater flux: the difference between evaporation (E) and precipitation (P), or E−P. Although there is consensus among modelers that with a warming climate E−P will increase, evidence from satellite data is still not conclusive, mainly due to sensor calibration issues. We here investigate the degree of correspondence among six recent
satellite-based climate data records and ERA5 reanalysis E−P data.
Xianfeng Liu, Xiaoming Feng, Philippe Ciais, and Bojie Fu
Hydrol. Earth Syst. Sci., 24, 3663–3676, https://doi.org/10.5194/hess-24-3663-2020, https://doi.org/10.5194/hess-24-3663-2020, 2020
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Freshwater availability is crucial for sustainable development across the Asian and eastern European regions. Our results indicate widespread decline in terrestrial water storage (TWS) over the region during 2002–2017, primarily due to the intensive over-extraction of groundwater and warmth-induced surface water loss. The findings provide insights into changes in TWS and its components over the Asian and eastern European regions, where there is growing demand for food grains and water supplies.
Sujay V. Kumar, Thomas R. Holmes, Rajat Bindlish, Richard de Jeu, and Christa Peters-Lidard
Hydrol. Earth Syst. Sci., 24, 3431–3450, https://doi.org/10.5194/hess-24-3431-2020, https://doi.org/10.5194/hess-24-3431-2020, 2020
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Vegetation optical depth (VOD) is a byproduct of the soil moisture retrieval from passive microwave instruments. This study demonstrates that VOD information can be utilized for improving land surface water budget and carbon conditions through data assimilation.
Victor Pellet, Filipe Aires, Fabrice Papa, Simon Munier, and Bertrand Decharme
Hydrol. Earth Syst. Sci., 24, 3033–3055, https://doi.org/10.5194/hess-24-3033-2020, https://doi.org/10.5194/hess-24-3033-2020, 2020
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The water mass variation at and below the land surface is a major component of the water cycle that was first estimated using GRACE observations (2002–2017). Our analysis shows the advantages of the use of satellite observation for precipitation and evapotranspiration along with river discharge measurement to perform an indirect and coherent reconstruction of this water component estimate over longer time periods.
Joseph T. D. Lucey, John T. Reager, and Sonya R. Lopez
Hydrol. Earth Syst. Sci., 24, 1415–1427, https://doi.org/10.5194/hess-24-1415-2020, https://doi.org/10.5194/hess-24-1415-2020, 2020
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This work relates total water storage (TWS) and rainfall to surface water inundation (SWI) using NASA satellite data. We determine whether TWS and/or rainfall control global SWI developments. Regression methods and cross-correlations were used to relate the measurements and correct for time differences among peaks. Results show TWS and rainfall control most global SWI developments. To our knowledge, this is the first global study on SWI controls and validates previous findings.
Pierre Gentine, Adam Massmann, Benjamin R. Lintner, Sayed Hamed Alemohammad, Rong Fu, Julia K. Green, Daniel Kennedy, and Jordi Vilà-Guerau de Arellano
Hydrol. Earth Syst. Sci., 23, 4171–4197, https://doi.org/10.5194/hess-23-4171-2019, https://doi.org/10.5194/hess-23-4171-2019, 2019
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Land–atmosphere interactions are key for the exchange of water, energy, and carbon dioxide, especially in the tropics. We here review some of the recent findings on land–atmosphere interactions in the tropics and where we see potential challenges and paths forward.
Serena Ceola, Francesco Laio, and Alberto Montanari
Hydrol. Earth Syst. Sci., 23, 3933–3944, https://doi.org/10.5194/hess-23-3933-2019, https://doi.org/10.5194/hess-23-3933-2019, 2019
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A simple and effective index for the quantitative estimation of the evolution of human pressure on rivers at global scale is proposed. This index, based on nightlights and river discharge data, shows a significant increase from 1992 to 2013 worldwide. The most notable changes are found in river basins across Africa and Asia, where human pressure on rivers is growing markedly. This index identifies priority areas that can be targeted for the implementation of mitigation strategies and plans.
Heloisa Ehalt Macedo, Ralph Edward Beighley, Cédric H. David, and John T. Reager
Hydrol. Earth Syst. Sci., 23, 3269–3277, https://doi.org/10.5194/hess-23-3269-2019, https://doi.org/10.5194/hess-23-3269-2019, 2019
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The water stored under the surface is very important for defining the amount of water available for human and environmental applications; however, it is still a challenge to obtain such measurements. NASA's GRACE satellites provide information on total terrestrial water storage based on observations of gravity changes. Here, we relate GRACE data to streamflow measurements, providing estimations of the fraction of baseflow and total drainable storage for the Mississippi River basin.
Linlin Li, Andrew Skidmore, Anton Vrieling, and Tiejun Wang
Hydrol. Earth Syst. Sci., 23, 3037–3056, https://doi.org/10.5194/hess-23-3037-2019, https://doi.org/10.5194/hess-23-3037-2019, 2019
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We derived an 8 d, 500 m resolution surface water fraction product over the Mediterranean region for 2000–2017 based on MODIS data. This dataset complements existing surface water/wetland datasets by adding more temporal detail. It allows for the seasonal, inter-annual, and long-term dynamics of the surface water extent to be monitored, inclusive of small-sized and highly dynamic water bodies; it can also contribute to biodiversity and climate change assessment.
Siyuan Tian, Luigi J. Renzullo, Albert I. J. M. van Dijk, Paul Tregoning, and Jeffrey P. Walker
Hydrol. Earth Syst. Sci., 23, 1067–1081, https://doi.org/10.5194/hess-23-1067-2019, https://doi.org/10.5194/hess-23-1067-2019, 2019
Jiawei Hou, Albert I. J. M. van Dijk, Luigi J. Renzullo, and Robert A. Vertessy
Hydrol. Earth Syst. Sci., 22, 6435–6448, https://doi.org/10.5194/hess-22-6435-2018, https://doi.org/10.5194/hess-22-6435-2018, 2018
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Satellite-based river gauging can be constructed based on remote-sensing-derived surface water extent and modelled discharge, and used to estimate river discharges with satellite observations only. This provides opportunities for monitoring river discharge in the absence of a real-time hydrological model or gauging stations.
Seyed Hamed Alemohammad, Jana Kolassa, Catherine Prigent, Filipe Aires, and Pierre Gentine
Hydrol. Earth Syst. Sci., 22, 5341–5356, https://doi.org/10.5194/hess-22-5341-2018, https://doi.org/10.5194/hess-22-5341-2018, 2018
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A new machine learning algorithm is developed to downscale satellite-based soil moisture estimates from their native spatial scale of 9 km to 2.25 km.
Albert I. J. M. van Dijk, Jaap Schellekens, Marta Yebra, Hylke E. Beck, Luigi J. Renzullo, Albrecht Weerts, and Gennadii Donchyts
Hydrol. Earth Syst. Sci., 22, 4959–4980, https://doi.org/10.5194/hess-22-4959-2018, https://doi.org/10.5194/hess-22-4959-2018, 2018
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Evaporation from wetlands, lakes and irrigation areas needs to be measured to understand water scarcity. So far, this has only been possible for small regions. Here, we develop a solution that can be applied at a very high resolution globally by making use of satellite observations. Our results show that 16% of global water resources evaporate before reaching the ocean, mostly from surface water. Irrigation water use is less than 1% globally but is a very large water user in several dry basins.
Carlos Jiménez, Brecht Martens, Diego M. Miralles, Joshua B. Fisher, Hylke E. Beck, and Diego Fernández-Prieto
Hydrol. Earth Syst. Sci., 22, 4513–4533, https://doi.org/10.5194/hess-22-4513-2018, https://doi.org/10.5194/hess-22-4513-2018, 2018
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Observing the amount of water evaporated in nature is not easy, and we need to combine accurate local measurements with estimates from satellites, more uncertain but covering larger areas. This is the main topic of our paper, in which local observations are compared with global land evaporation estimates, followed by a weighting of the global observations based on this comparison to attempt derive a more accurate evaporation product.
Simon Zwieback, Andreas Colliander, Michael H. Cosh, José Martínez-Fernández, Heather McNairn, Patrick J. Starks, Marc Thibeault, and Aaron Berg
Hydrol. Earth Syst. Sci., 22, 4473–4489, https://doi.org/10.5194/hess-22-4473-2018, https://doi.org/10.5194/hess-22-4473-2018, 2018
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Satellite soil moisture products can provide critical information on incipient droughts and the interplay between vegetation and water availability. However, time-variant systematic errors in the soil moisture products may impede their usefulness. Using a novel statistical approach, we detect such errors (associated with changing vegetation) in the SMAP soil moisture product. The vegetation-associated biases impede drought detection and the quantification of vegetation–water interactions.
Ben T. Gouweleeuw, Andreas Kvas, Christian Gruber, Animesh K. Gain, Thorsten Mayer-Gürr, Frank Flechtner, and Andreas Güntner
Hydrol. Earth Syst. Sci., 22, 2867–2880, https://doi.org/10.5194/hess-22-2867-2018, https://doi.org/10.5194/hess-22-2867-2018, 2018
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Daily GRACE gravity field solutions have been evaluated against daily river runoff data for major flood events in the Ganges–Brahmaputra Delta in 2004 and 2007. Compared to the monthly gravity field solutions, the trends over periods of a few days in the daily gravity field solutions are able to reflect temporal variations in river runoff during major flood events. This implies that daily gravity field solutions released in near-real time may support flood monitoring for large events.
Peter J. Shellito, Eric E. Small, and Ben Livneh
Hydrol. Earth Syst. Sci., 22, 1649–1663, https://doi.org/10.5194/hess-22-1649-2018, https://doi.org/10.5194/hess-22-1649-2018, 2018
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After soil gets wet, much of the surface moisture evaporates directly back into the air. Recent satellite data show that this process is enhanced when there is more water in the soil, less humidity in the air, and less vegetation covering the ground. A widely used model shows similar effects of soil water and humidity, but it largely misses the role of vegetation and assigns outsized importance to soil type. These results are encouraging evidence that the satellite can be used to improve models.
Cassandra Normandin, Frédéric Frappart, Bertrand Lubac, Simon Bélanger, Vincent Marieu, Fabien Blarel, Arthur Robinet, and Léa Guiastrennec-Faugas
Hydrol. Earth Syst. Sci., 22, 1543–1561, https://doi.org/10.5194/hess-22-1543-2018, https://doi.org/10.5194/hess-22-1543-2018, 2018
Thomas R. H. Holmes, Christopher R. Hain, Wade T. Crow, Martha C. Anderson, and William P. Kustas
Hydrol. Earth Syst. Sci., 22, 1351–1369, https://doi.org/10.5194/hess-22-1351-2018, https://doi.org/10.5194/hess-22-1351-2018, 2018
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In an effort to apply cloud-tolerant microwave data to satellite-based monitoring of evapotranspiration (ET), this study reports on an experiment where microwave-based land surface temperature is used as the key diagnostic input to a two-source energy balance method for the estimation of ET. Comparisons of this microwave ET with the conventional thermal infrared estimates show widespread agreement in spatial and temporal patterns from seasonal to inter-annual timescales over Africa and Europe.
Jonas Meier, Florian Zabel, and Wolfram Mauser
Hydrol. Earth Syst. Sci., 22, 1119–1133, https://doi.org/10.5194/hess-22-1119-2018, https://doi.org/10.5194/hess-22-1119-2018, 2018
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The following study extends existing irrigation maps based on official reports. The main idea was to extend the reported irrigated areas using agricultural suitability data and compare them with remote sensing information about plant conditions. The analysis indicates an increase in irrigated land by 18 % compared to the reported statistics. The additional areas are mainly identified within already known irrigated regions where irrigation is more dense than previously estimated.
Matthew F. McCabe, Matthew Rodell, Douglas E. Alsdorf, Diego G. Miralles, Remko Uijlenhoet, Wolfgang Wagner, Arko Lucieer, Rasmus Houborg, Niko E. C. Verhoest, Trenton E. Franz, Jiancheng Shi, Huilin Gao, and Eric F. Wood
Hydrol. Earth Syst. Sci., 21, 3879–3914, https://doi.org/10.5194/hess-21-3879-2017, https://doi.org/10.5194/hess-21-3879-2017, 2017
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We examine the opportunities and challenges that technological advances in Earth observation will present to the hydrological community. From advanced space-based sensors to unmanned aerial vehicles and ground-based distributed networks, these emergent systems are set to revolutionize our understanding and interpretation of hydrological and related processes.
Liangjing Zhang, Henryk Dobslaw, Tobias Stacke, Andreas Güntner, Robert Dill, and Maik Thomas
Hydrol. Earth Syst. Sci., 21, 821–837, https://doi.org/10.5194/hess-21-821-2017, https://doi.org/10.5194/hess-21-821-2017, 2017
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Global numerical models perform differently, as has been found in some model intercomparison studies, which mainly focused on components like evapotranspiration, soil moisture or runoff. We have applied terrestrial water storage that is estimated from a GRACE-based state-of-art post-processing method to validate four global numerical models and try to identify the advantages and deficiencies of a certain model. GRACE-based TWS demonstrates its additional benefits to improve the models in future.
Hylke E. Beck, Albert I. J. M. van Dijk, Vincenzo Levizzani, Jaap Schellekens, Diego G. Miralles, Brecht Martens, and Ad de Roo
Hydrol. Earth Syst. Sci., 21, 589–615, https://doi.org/10.5194/hess-21-589-2017, https://doi.org/10.5194/hess-21-589-2017, 2017
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MSWEP (Multi-Source Weighted-Ensemble Precipitation) is a new global terrestrial precipitation dataset with a high 3-hourly temporal and 0.25° spatial resolution. The dataset is unique in that it takes advantage of a wide range of data sources, including gauge, satellite, and reanalysis data, to obtain the best possible precipitation estimates at global scale. The dataset outperforms existing gauge-adjusted precipitation datasets.
Oliver López, Rasmus Houborg, and Matthew Francis McCabe
Hydrol. Earth Syst. Sci., 21, 323–343, https://doi.org/10.5194/hess-21-323-2017, https://doi.org/10.5194/hess-21-323-2017, 2017
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The study evaluated the spatial and temporal consistency of satellite-based hydrological products based on the water budget equation, including three global evaporation products. The products were spatially matched using spherical harmonics analysis. The results highlighted the difficulty in obtaining agreement between independent satellite products, even over regions with simple water budgets. However, imposing a time lag on water storage data improved results considerably.
Paul A. Levine, James T. Randerson, Sean C. Swenson, and David M. Lawrence
Hydrol. Earth Syst. Sci., 20, 4837–4856, https://doi.org/10.5194/hess-20-4837-2016, https://doi.org/10.5194/hess-20-4837-2016, 2016
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We demonstrate a new approach to assess the strength of feedbacks resulting from land–atmosphere coupling on decadal timescales. Our approach was tailored to enable evaluation of Earth system models (ESMs) using data from Earth observation satellites that measure terrestrial water storage anomalies and relevant atmospheric variables. Our results are consistent with previous work demonstrating that ESMs may be overestimating the strength of land surface feedbacks compared with observations.
Thomas R. H. Holmes, Christopher R. Hain, Martha C. Anderson, and Wade T. Crow
Hydrol. Earth Syst. Sci., 20, 3263–3275, https://doi.org/10.5194/hess-20-3263-2016, https://doi.org/10.5194/hess-20-3263-2016, 2016
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We test the cloud tolerance of two technologies to estimate land surface temperature (LST) from space: microwave (MW) and thermal infrared (TIR). Although TIR has slightly lower errors than MW with ground data under clear-sky conditions, it suffers increasing negative bias as cloud cover increases. In contrast, we find no direct impact of clouds on the accuracy and bias of MW-LST. MW-LST can therefore be used to improve TIR cloud screening and increase sampling in clouded regions.
Zhi Li, Yaning Chen, Yang Wang, and Gonghuan Fang
Hydrol. Earth Syst. Sci., 20, 2169–2178, https://doi.org/10.5194/hess-20-2169-2016, https://doi.org/10.5194/hess-20-2169-2016, 2016
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Global net primary production (NPP) slightly increased in 2000–2014. More than 64 % of vegetated land in the Northern Hemisphere (NH) showed increased NPP, while 60.3 % in Southern Hemisphere (SH) showed a decreasing trend. Vegetation greening and climate change promote rises of global evapotranspiration (ET). The increased rate of ET in the NH is faster than that in the SH. Meanwhile, global warming and vegetation greening accelerate evaporation in soil moisture. Continuation of these trends will likely exacerbate the risk of ecological drought.
M. Boudou, B. Danière, and M. Lang
Hydrol. Earth Syst. Sci., 20, 161–173, https://doi.org/10.5194/hess-20-161-2016, https://doi.org/10.5194/hess-20-161-2016, 2016
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This paper presents an appraisal of flood vulnerability of two French cities, Besançon and Moissac, which have been largely impacted by two ancient major floods (resp. in January 1910 and March 1930). An analysis of historical sources allows the mapping of land use and occupation within the flood extent of the two historical floods, both in past and present contexts. It gives an insight into the complexity of flood risk evolution, at a local scale.
S. Kotsuki and K. Tanaka
Hydrol. Earth Syst. Sci., 19, 4441–4461, https://doi.org/10.5194/hess-19-4441-2015, https://doi.org/10.5194/hess-19-4441-2015, 2015
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This study aims to develop a new global data set of a satellite-derived crop calendar (SACRA) and to reveal its advantages and disadvantages compared to other global products. The cultivation period of SACRA is identified from the time series of NDVI; therefore, SACRA considers current effects of human decisions and natural disasters. The difference between the estimated sowing dates and other existing products is less than 2 months (< 62 days) in most areas.
S. Siebert, M. Kummu, M. Porkka, P. Döll, N. Ramankutty, and B. R. Scanlon
Hydrol. Earth Syst. Sci., 19, 1521–1545, https://doi.org/10.5194/hess-19-1521-2015, https://doi.org/10.5194/hess-19-1521-2015, 2015
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We developed the historical irrigation data set (HID) depicting the spatio-temporal development of the area equipped for irrigation (AEI) between 1900 and 2005 at 5arcmin resolution.
The HID reflects very well the spatial patterns of irrigated land as shown on two historical maps for 1910 and 1960.
Global AEI increased from 63 million ha (Mha) in 1900 to 111 Mha in 1950 and 306 Mha in 2005. Mean aridity on irrigated land increased and mean natural river discharge decreased from 1900 to 1950.
T. R. H. Holmes, W. T. Crow, and C. Hain
Hydrol. Earth Syst. Sci., 17, 3695–3706, https://doi.org/10.5194/hess-17-3695-2013, https://doi.org/10.5194/hess-17-3695-2013, 2013
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
G. G. Laruelle, H. H. Dürr, R. Lauerwald, J. Hartmann, C. P. Slomp, N. Goossens, and P. A. G. Regnier
Hydrol. Earth Syst. Sci., 17, 2029–2051, https://doi.org/10.5194/hess-17-2029-2013, https://doi.org/10.5194/hess-17-2029-2013, 2013
Cited articles
Alfieri, L., Burek, P., Dutra, E., Krzeminski, B., Muraro, D., Thielen, J., and Pappenberger, F.: GloFAS –global ensemble streamflow forecasting and flood early warning, Hydrol. Earth Syst. Sci., 17, 1161–1175, https://doi.org/10.5194/hess-17-1161-2013, 2013.
Archer, K. J. and Kimes, R. V.: Empirical characterization of random forest variable importance measures, Comput. Stat. Data Anal., 52, 2249–2260, https://doi.org/10.1016/j.csda.2007.08.015, 2008.
Auret, L. and Aldrich, C.: Empirical comparison of tree ensemble variable importance measures, Chemomet. Intelligent Labor. Syst., 105, 157–170, https://doi.org/10.1016/j.chemolab.2010.12.004, 2011.
Bartholmes, J. C., Thielen, J., Ramos, M. H., and Gentilini, S.: The european flood alert system EFAS –Part 2: Statistical skill assessment of probabilistic and deterministic operational forecasts, Hydrol. Earth Syst. Sci., 13, 141–153, https://doi.org/10.5194/hess-13-141-2009, 2009.
Bontemps, S., Defourny, P., Bogaert, E. V., Arino, O., Kalogirou, V., and Perez, J.R.: GLOBCOVER 2009 – Products Description and Validation Report, available at: http://due.esrin.esa.int/globcover/ (last access: 15 February 2014), 2010.
Brakenridge, G. R., Nghiem, S. V., Anderson, E., and Chien, S.: Space-based measurement of river runoff, Eos Trans. AGU, 86, 185–188, https://doi.org/10.1029/2005EO190001, 2005.
Brakenridge, G. R., Nghiem, S. V., Anderson, E., and Mic, R.: Orbital microwave measurement of river discharge and ice status, Water Resour. Res., 43, W04405, https://doi.org/10.1029/2006WR005238, 2007.
Brakenridge, G. R., Cohen, S., Kettner, A. J., De Groeve, T., Nghiem, S. V., Syvitski, J. P. M., and Fekete, B. M.: Calibration of satellite measurements of river discharge using a global hydrology model, J. Hydrol., 475, 123–136, 2012.
Brakenridge, G. R., De Groeve, T., Cohen, S., and Nghiem, S. V.: River Watch, Version 2: Satellite River Discharge and Runoff Measurements: Technical Summary, University of Colorado, Boulder, CO, USA, available at: http://floodobservatory.colorado.edu/SatelliteGaugingSites/technical.html, last access: 1 December 2013.
Breiman, L.: Random Forests, Machine Learning, 45, 5–32, 2001.
Brown, J., Ferrians Jr., O. J., Heginbottom, J. A., and Melnikov, E. S.: Circum-Arctic Map of Permafrost and Ground-Ice Conditions. Version 2. [Permafrost], Boulder, Colorado USA: National Snow and Ice Data Center, 2002.
Committee on Earth Observation Satellites (CEOS) Flood Pilot, available at: http://www.ceos.org/, last access: 1 September 2014.
Chan, J. C.-W. and Paelinckx, D.: Evaluation of Random Forest and Adaboost tree-based ensemble classification and spectral band selection for ecotope mapping using airborne hyperspectral imagery, Remote Sens. Environ., 112, 2999–3011, 2008.
Chukhlantsev, A. A.: Modeling of microwave emission from vegetation canopies, Microwave Radiometry of Vegetation Canopies, Springer Netherlands, Chap. 6, 147–175, 2006.
De Groeve, T., Brakenridge, G. R., and Kugler, Z.: Near Real Time Flood Alerting for the Global Disaster Alert and Coordination System, edited by: Van de Walle, B., Burghardt, P., and Nieuwenhuis, C., Proceedings of the 4th International ISCRAM Conference, 33–40, 2006.
De Groeve, T. and Riva, P.: Global Real-time Detection of Major Floods Using Passive Microwave Remote Sensing, Proceedings of the 33rd International Symposium on Remote Sensing of Environment Stresa, Italy, May 2009.
De Groeve, T.: Flood monitoring and mapping using passive microwave remote sensing in Namibia, Geomatics, Nat. Hazards Risk, 1:1, 19–35, 2010.
Di Baldassarre, G. and Montanari, A.: Uncertainty in river discharge observations: a quantitative analysis, Hydrol. Earth Syst. Sci., 13, 913–921, https://doi.org/10.5194/hess-13-913-2009, 2009.
Disaster Charter: Space and Major Disasters, available at: http://www.disasterscharter.org/ (last access: 1 September 2014), 2013.
EM-DAT: The OFDA/CRED International Disaster Database, Université Catholique de Louvain, Brussels, Belgium, available at: http://www.emdat.be, last access: 1 December 2013.
Fekete, B. M., Vorosmarty, C. J., and Grabs, W.: Global, composite runoff fields based on observed river discharge and simulated water balances, GRDC Report 22, Global Runoff Data Center, Koblenz, Germany, 1999.
GDACS: Global Disaster Alert and Coordination System, Global Floods Detection System available at: http://www.gdacs.org/, last access: 1 December 2013.
Global Runoff Data Centre: Major River Basins of the World, 56068 Koblenz, Germany: Federal Institute of Hydrology (BfG), available at: http://grdc.bafg.de/ (last access: 20 January, 2013), 2007.
Global Runoff Data Centre: The. River Discharge Time Series, 56068 Koblenz, Germany: Federal Institute of Hydrology (BfG), available at: http://grdc.bafg.de/, last access: 20 January 2013.
Golnaraghi, M., Douris, J., and Migraine, J.-B.: Saving Lives Through Early Warning Systems and Emergency Preparedness, Risk Wise, Tudor Rose, 137–141, 2009.
Gonzalez, L., Velasco Morente, F., Gavilan Ruiz, J. M., Sanchez-Reyes and Fernandez, J. M.: The Similarity between the Square of the Coefficient of Variation and the Gini Index of a General Random Variable, J. Quant. Methods Econom. Business Admin., 10, 5–18, ISSN 1886-516X, 2010.
Gregorutti, B., Michel, B., and Saint-Pierre, P.: Correlation and variable importance in random forests,. Cornell University Library, arXiv: 1310.5726 [stat], 2013.
Grömping, U.: Variable Importance Assessment in Regression: Linear Regression versus Random Forest, The American Statistician, 11/2009; 63, 308–319, https://doi.org/10.1198/tast.2009.08199, 2009.
Hirpa, F. A., Hopson, T. M., De Groeve, T., Brakenridge, G. R., Gebremichael, M., and Restrepo, P. J.: Upstream satellite remote sensing for river discharge forecasting: Application to major rivers in South Asia, Remote Sens. Environ., 131, 140–151, 2013.
Hirsch R. M. and Costa J. E.: U.S. Stream Flow Measurement and Data Dissemination Improve EOS, Transactions, American Geophysical Union, 18 May 2004, 85, 197–203, 2004.
Khan, S. I., Hong, Y., Vergara, H. J., Gourley, J. J., Robert Brakenridge, G., De Groeve, T., Flamig, Z. L., Policelli, F., andYong, B.: Microwave satellite data for hydrologic modeling in ungauged basins, IEEE Geosci. Remote Sens. Lett., 9, 663–667, 2012.
Kugler, Z. and De Groeve, T.: The Global Flood Detection System, Office for Official Publications of the European Communities, Luxembourg, 2007.
Kugler, Z.: Remote sensing for natural hazard mitigation and climate change impact assessment, Quaterly J. Hungarian Meteorol. Serv., January–March 116, 21–38, 2012.
Kundzewicz, Z. W.: Changes in Flood Risk in Europe, Wallingford: IAHS Press. p. 516, IAHS special publication; 10, United Nations: Report of the United Nations Conference on Sustainable, Development Rio de Janeiro, Brazil, 20–22 June 2012, A/CONF.216/16, 2012.
Le Coz, J., Renard, B., Bonnifait, L., Branger, F., and Le Boursicaud, R.: Combining hydraulic knowledge and uncertain gaugings in the estimation of hydrometric rating curves: A Bayesian approach, J. Hydrol., 509, 573–587, 2014.
Lehner, B. and Döll, P.: Development and validation of a global database of lakes, reservoirs and wetlands, J. Hydrol., 296, 1–22, https://doi.org/10.1016/j.jhydrol.2004.03.028, 2004.
Lehner, B., Reidy Liermann, C., Revenga, C., Vörösmarty, C., Fekete, B., Crouzet, P., Döll, P., Endejan, M., Frenken, K., Magome, J., Nilsson, C., Robertson, J., Rödel, R., Sindorf, N., and Wisser, D.: High resolution mapping of the world's reservoirs and dams for sustainable river flow management, Frontiers in Ecology and the Environment. Source: GWSP Digital Water Atlas. Map 81: GRanD Database (V1.0), available at: http://atlas.gwsp.org/index.php?option=com_content&task=view&id=209&Itemid=1 (last access: 11 March 2014), 2008.
Moffitt, C. B., Hossain, F., Adler, R. F., Yilmaz, K. K., and Pierce, H. F.: Validation of a TRMM-Based Global Flood Detection System in Bangladesh, Int. J. Appl. Earth Observ. Geoinform., 13, 165–177, https://doi.org/10.1016/j.jag.2010.11.003, 2011.
MunichRe: Munich Reinsurance: January 2014 press release, Münchener Rückversicherungs-Gesellschaft, Geo Risks Research, NatCatSERVICE, available at: http://www.munichre.com/en/media_relations/press_releases/2014/2014_01_07_press_release.aspx, last access: 20 January 2014.
Nash, J. E. and Sutcliffe, J. V.: River flow forecasting through conceptual models part I – A discussion of principles, J. Hydrol., 10, 282–290, 1970.
Nicodemus, K. K.: Letter to the editor: On the stability and ranking of predictors from random forest variable importance measures, Briefings in Bioinform., 12, 369–373, https://doi.org/10.1093/bib/bbr016, 2011
Nicodemus, K. K. and Malley, J. D.: Predictor correlation impacts machine learning algorithms: implications for genomic studies, BCM Bioinform., 25, 1884–1890, https://doi.org/10.1093/bioinformatics/btp331, 2009.
Palczewska, A., Palczewski, J., Robinson, R. M., and Neagu, D.: Interpreting random forest models using a feature contribution method, Proceedings of the 2013 IEEE 14th International Conference on Information Reuse and Integration, IEEE IRI 2013, 112 pp., 2013.
Pappenberger, F., Matgen, P., Beven, K. J., Henry, J. B., Pfister, L., and de Fraipont, P.: Influence of uncertain boundary conditions and model structure on flood inundation predictions, Adv. Water Resour., 29, 1430–1449, https://doi.org/10.1016/j.advwatres.2005.11.012, 2006.
Pappenberger, F., Dutra, E., Wetterhall, F., and Cloke, H. L.: Deriving global flood hazard maps of fluvial floods through a physical model cascade, Hydrol. Earth Syst. Sci., 16, 4143–4156, https://doi.org/10.5194/hess-16-4143-2012, 2012.
Peel, M. C., Finlayson, B. L., and McMahon, T. A.: Updated world map of the Köppen-Geiger climate classification, Hydrol. Earth Syst. Sci., 11, 1633–1644, https://doi.org/10.5194/hess-11-1633-2007, 2007.
Pelletier, P. M.: Uncertainties in the single determination of river discharge: a literature review, Can. J. Civil Eng., 15, 834–850, 1988.
Rosso, R. A.: linear approach to the influence of discharge measurement error on flood estimates, Hydrol. Sci. J., 30, 137–149, https://doi.org/10.1080/02626668509490975, 1998.
Sandri, M. and Zuccolotto, P.: A bias correlation algorithm for the Gini variable importance measure in classification trees, J. Comput. Graphical Stat., 17, 611-628, https://doi.org/10.1198/106186008X344522, 2008.
Schumann, G., Bates, P. D., Horritt, M. S., Matgen, P., and Pappenberger, F.: Progress in Integration of Remote Sensing–derived Flood Extent and Stage Data and Hydraulic Models, Rev. Geophys., 47, RG4001, https://doi.org/10.1029/2008RG000274, 2009.
South African Water Affairs (DWA) database, available at: http://www.dwa.gov.za/Hydrology/, last access: 10 July 2013.
Strobl, C., Malley, J., and Tutz, G.: An Introduction to Recursive Partitioning: Rationale, Application, and Characteristics of Classification and Regression Trees, Bagging, and Random Forests, Psychol. Methods, 14, 323–348, https://doi.org/10.1186/1471-2105-9-307, 2009.
Thielen, J., Bartholmes, J., Ramos, M.-H., and de Roo, A.: The European Flood Alert System –Part 1: Concept and development, Hydrol. Earth Syst. Sci., 13, 125–140, https://doi.org/10.5194/hess-13-125-2009, 2009.
Thiemig, V., Bisselink, B., Pappenberger, F., and Thielen, J.: A pan-African Flood Forecasting System, Hydrol. Earth Syst. Sci. Discuss., 11, 5559–5597, https://doi.org/10.5194/hessd-11-5559-2014, 2014.
Tolosi, L. and Lengauer, T.: Classification with correlated features: unreliability of feature ranking and solutions, Bioinform., 27, 1986–1994, https://doi.org/10.1093/bioinformatics/btr300, 2011.
Tomkins, K. M.: Uncertainty in streamflow rating curves: Methods, controls and consequences, Hydrol. Process., 28, 464–481, 2014.
UNISDR: Global Assessment Report: Revealing Risk, Redefining Development, Chap. 2.2, Global disaster risk trends, United Nations, printed in the UK, ISBN 978-92-1-132030-5, 22–27, 2011.
UNOSAT, UNITAR Operational Satellite Applications Programme, available at: http://www.unitar.org/unosat/maps, last access: 1 December 2013.
Van Westen, C. J.: Remote sensing and GIS for natural hazards assessment and disaster risk management, in: Treatise on Geomorphology, edited by: Shroder, J. and Bishop, M. P., Academic Press, San Diego, CA, Vol. 3, Remote Sensing and GIScience in Geomorphology, 259–298, 2013.
Yamazaki, D., O'Loughlin, F., Trigg, M. A., Miller, Z. F., Pavelsky, T. M., and Bates, P. D.: Development of the global width database for large river, Water Resour. Res., 50, 3467–3480, https://doi.org/10.1002/2013WR014664, 2014.
Yitzhaki, S. and Schechtman, E.: The Gini Methodology. A Primer on a Statistical Methodology, Springer Series in Statistics, Vol. 272, ISBN: 978-1-4614-4720-7, 2013.
Zaraj, Z., Zambrano-Bigiarini, M., Salamon, P., Burek, P., Gentile, A., and Bianchi, A.: Calibration of the LISFLOOD hydrological model for Europe. Calibration Round 2013JRC Technical Report, European Commission, Joint Research Centre, Ispra, Italy, 2013.
Zhang, Y., Hong, Y., Wang, X., Gourley, J. J., Gao, J., Vergara, H. J., and Yong, B.: Assimilation of passive microwave streamflow signals for improving flood forecasting: A first study in Cubango River Basin, Africa, IEEE J. Selected Topics. Appl. Earth Observ. Remote Sens., 6, 2375–2390, 2013.
Zhu, Z., Bi, J., Pan, Y., Ganguly, S., Anav, A., Xu, L., Samanta, A., Piao, S., Nemani, R. R., and Myneni, R. B.: Global data sets of vegetation leaf area index (LAI)3g and fraction of photosynthetically active radiation (FPAR)3g derived from global inventory modeling and mapping studies (GIMMS) normalized difference vegetation index (NDVI3G) for the period 1981 to 2011, Remote Sens., 5, 927–948, 2013.
Short summary
One of the main challenges in global hydrological modelling is the limited availability of observational data for calibration and model verification. The aim of this study is to test the potentials and constraints of the remote sensing signal of the Global Flood Detection System (GFDS) for converting the flood detection signal into river discharge values. This work also provides a first analysis of the local factors influencing the accuracy of discharge measurement as provided by this system.
One of the main challenges in global hydrological modelling is the limited availability of...
