Articles | Volume 11, issue 4
https://doi.org/10.5194/essd-11-1655-2019
© 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/essd-11-1655-2019
© Author(s) 2019. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Data description paper
| 
13 Nov 2019
Data description paper |
| 13 Nov 2019
| 13 Nov 2019
GRUN: an observation-based global gridded runoff dataset from 1902 to 2014
Institute for Atmospheric and Climate Science, ETH Zurich,
Universitaetstrasse 16, 8092 Zurich, Switzerland
Environmental Remote Sensing Laboratory (LTE), EPFL, 1005 Lausanne,
Switzerland
Vincent Humphrey
Institute for Atmospheric and Climate Science, ETH Zurich,
Universitaetstrasse 16, 8092 Zurich, Switzerland
Division of Geological and Planetary Sciences, California Institute
of Technology, Pasadena, CA, USA
Sonia I. Seneviratne
Institute for Atmospheric and Climate Science, ETH Zurich,
Universitaetstrasse 16, 8092 Zurich, Switzerland
Lukas Gudmundsson
Institute for Atmospheric and Climate Science, ETH Zurich,
Universitaetstrasse 16, 8092 Zurich, Switzerland
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Lea Beusch, Lukas Gudmundsson, and Sonia I. Seneviratne
Earth Syst. Dynam., 11, 139–159, https://doi.org/10.5194/esd-11-139-2020, https://doi.org/10.5194/esd-11-139-2020, 2020
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Inne Vanderkelen, Jakob Zschleischler, Lukas Gudmundsson, Klaus Keuler, Francois Rineau, Natalie Beenaerts, Jaco Vangronsveld, and Wim Thiery
Biogeosciences Discuss., https://doi.org/10.5194/bg-2019-267, https://doi.org/10.5194/bg-2019-267, 2019
Manuscript not accepted for further review
Vincent Humphrey and Lukas Gudmundsson
Earth Syst. Sci. Data, 11, 1153–1170, https://doi.org/10.5194/essd-11-1153-2019, https://doi.org/10.5194/essd-11-1153-2019, 2019
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Because changes in freshwater availability can impact many natural ecosystems and human activities, it is crucial to better understand long-term changes in the water cycle. This dataset is a reconstruction of past changes in land water storage over the last century, obtained by combining satellite observations with historical weather data. It can be used to investigate both regional changes in freshwater availability or drought frequency and long-term changes in the global water cycle.
Mathias Hauser, Wim Thiery, and Sonia Isabelle Seneviratne
Earth Syst. Dynam., 10, 157–169, https://doi.org/10.5194/esd-10-157-2019, https://doi.org/10.5194/esd-10-157-2019, 2019
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We develop a method to keep the amount of water in the soil at the present-day level, using only local water sources in a global climate model. This leads to less drying over many land areas, but also decreases river runoff. We find that temperature extremes in the 21st century decrease substantially using our method. This provides a new perspective on how land water can influence regional climate and introduces land water management as potential tool for local mitigation of climate change.
Clemens Schwingshackl, Martin Hirschi, and Sonia I. Seneviratne
Earth Syst. Dynam., 9, 1217–1234, https://doi.org/10.5194/esd-9-1217-2018, https://doi.org/10.5194/esd-9-1217-2018, 2018
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Changing amounts of water in the soil can have a strong impact on atmospheric temperatures. We present a theoretical approach that can be used to quantify the effect that soil moisture has on temperature and validate it using climate model simulations in which soil moisture is prescribed. This theoretical approach also allows us to study the soil moisture effect on temperature in standard climate models, even if they do not provide dedicated soil moisture simulations.
Martha M. Vogel, Jakob Zscheischler, and Sonia I. Seneviratne
Earth Syst. Dynam., 9, 1107–1125, https://doi.org/10.5194/esd-9-1107-2018, https://doi.org/10.5194/esd-9-1107-2018, 2018
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Climate change projections of temperature extremes are particularly uncertain in central Europe. We demonstrate that varying soil moisture–atmosphere feedbacks in current climate models leads to an enhancement of model differences; thus, they can explain the large uncertainties in extreme temperature projections. Using an observation-based constraint, we show that the strong drying and large increase in temperatures exhibited by models on the hottest day in central Europe are highly unlikely.
Hong Xuan Do, Lukas Gudmundsson, Michael Leonard, and Seth Westra
Earth Syst. Sci. Data, 10, 765–785, https://doi.org/10.5194/essd-10-765-2018, https://doi.org/10.5194/essd-10-765-2018, 2018
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The production of 30 959 daily streamflow time series in the Global Streamflow and Metadata Archive (GSIM) project is presented. The paper also describes the development of three metadata products that are freely available. Having collated an unprecedented number of stations and associated metadata, GSIM can be used to advance large-scale hydrological research and improve understanding of the global water cycle.
Lukas Gudmundsson, Hong Xuan Do, Michael Leonard, and Seth Westra
Earth Syst. Sci. Data, 10, 787–804, https://doi.org/10.5194/essd-10-787-2018, https://doi.org/10.5194/essd-10-787-2018, 2018
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Time-series indices characterizing streamflow at annual, seasonal and monthly resolution at more than 30 000 stations around the world are presented. The data belong to the Global Streamflow and Metadata Archive (GSIM) and allow for an assessment of water balance components, hydrological extremes and the seasonality of water availability. The quality of the data is tested using automated methods to aid potential users to gauge the suitability of the data for specific applications.
Peter Greve, Lukas Gudmundsson, and Sonia I. Seneviratne
Earth Syst. Dynam., 9, 227–240, https://doi.org/10.5194/esd-9-227-2018, https://doi.org/10.5194/esd-9-227-2018, 2018
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Assessing projected hydroclimatological changes is crucial, but associated with large uncertainties. We statistically assess here the response of precipitation and water availability to global temperature change, enabling us to estimate the significance of drying/wetting tendencies under anthropogenic climate change. We further show that opting for a 1.5 K warming target just slightly influences the mean response but could substantially reduce the risk of experiencing extreme changes.
Richard Wartenburger, Martin Hirschi, Markus G. Donat, Peter Greve, Andy J. Pitman, and Sonia I. Seneviratne
Geosci. Model Dev., 10, 3609–3634, https://doi.org/10.5194/gmd-10-3609-2017, https://doi.org/10.5194/gmd-10-3609-2017, 2017
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This article analyses regional changes in climate extremes as a function of projected changes in global mean temperature. We introduce the DROUGHT-HEAT Regional Climate Atlas, an interactive tool to analyse and display a range of well-established climate extremes and water-cycle indices and their changes as a function of global warming. Readers are encouraged to use the online tool for visualization of specific indices of interest, e.g. to assess their response to 1.5 or 2 °C global warming.
Sebastian Sippel, Jakob Zscheischler, Miguel D. Mahecha, Rene Orth, Markus Reichstein, Martha Vogel, and Sonia I. Seneviratne
Earth Syst. Dynam., 8, 387–403, https://doi.org/10.5194/esd-8-387-2017, https://doi.org/10.5194/esd-8-387-2017, 2017
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The present study (1) evaluates land–atmosphere coupling in the CMIP5 multi-model ensemble against an ensemble of benchmarking datasets and (2) refines the model ensemble using a land–atmosphere coupling diagnostic as constraint. Our study demonstrates that a considerable fraction of coupled climate models overemphasize warm-season
moisture-limitedclimate regimes in midlatitude regions. This leads to biases in daily-scale temperature extremes, which are alleviated in a constrained ensemble.
Mathias Hauser, René Orth, and Sonia I. Seneviratne
Geosci. Model Dev., 10, 1665–1677, https://doi.org/10.5194/gmd-10-1665-2017, https://doi.org/10.5194/gmd-10-1665-2017, 2017
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Water in the soil can influence temperature and precipitation of the atmosphere. However, the atmosphere also alters the soil moisture content. Climate model simulations prescribing soil moisture are a means to decouple these relationships. We find that the atmospheric response depends strongly on the method used to fix the soil moisture, as well as on the employed soil moisture data set.
Martin Hirschi and Sonia I. Seneviratne
Earth Syst. Sci. Data, 9, 251–258, https://doi.org/10.5194/essd-9-251-2017, https://doi.org/10.5194/essd-9-251-2017, 2017
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Terrestrial water storage comprises all forms of water storage on land surfaces, and its seasonal and inter-annual variations are mostly determined by soil moisture, groundwater, snow cover, and surface water. Soil moisture, especially, contributes to land--atmosphere coupling in an essential way. This paper presents an update of a basin-scale diagnostic dataset of monthly variations in terrestrial water storage for large river basins worldwide.
Lukas Gudmundsson and Sonia I. Seneviratne
Earth Syst. Sci. Data, 8, 279–295, https://doi.org/10.5194/essd-8-279-2016, https://doi.org/10.5194/essd-8-279-2016, 2016
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Despite the scientific and societal relevance of freshwater, there are to date no observation-based pan-European runoff estimates available. Here we employ state-of-the-art techniques to estimate monthly runoff rates in Europe. The new data product is based on an unprecedented collection of river flow observations which are combined with atmospheric variables using machine learning. Potential applications of the presented product include climatological assessments and drought monitoring.
Peter Greve, Lukas Gudmundsson, Boris Orlowsky, and Sonia I. Seneviratne
Hydrol. Earth Syst. Sci., 20, 2195–2205, https://doi.org/10.5194/hess-20-2195-2016, https://doi.org/10.5194/hess-20-2195-2016, 2016
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The widely used Budyko framework is by definition limited to steady-state conditions. In this study we analytically derive a new, two-parameter formulation of the Budyko framework that represents conditions under which evapotranspiration exceeds precipitation. This is technically achieved by rotating the water supply limit within the Budyko space. The new formulation is shown to be capable to represent first-order seasonal dynamics within the hydroclimatological system.
L. Gudmundsson and S. I. Seneviratne
Hydrol. Earth Syst. Sci., 19, 2859–2879, https://doi.org/10.5194/hess-19-2859-2015, https://doi.org/10.5194/hess-19-2859-2015, 2015
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Water storages and fluxes on land are key variables in the Earth system. To provide context for local investigations and to understand phenomena that emerge at large spatial scales, information on continental freshwater dynamics is needed. This paper presents a methodology to estimate continental-scale runoff on a 0.5° spatial grid, which combines the advantages of in situ observations with the power of machine learning regression. The resulting runoff estimates compare well with observations.
L. Gudmundsson and S. I. Seneviratne
Proc. IAHS, 369, 75–79, https://doi.org/10.5194/piahs-369-75-2015, https://doi.org/10.5194/piahs-369-75-2015, 2015
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Recent climate projections suggest changes in European drought frequency, indicating increased drought risk in the south and less droughts in the north. Here we show that a similar change pattern can be identified in the observed record. The results raise the question whether observed changes in European drought frequency are a consequence of anthropogenic climate change.
L. Gudmundsson and S. I. Seneviratne
Hydrol. Earth Syst. Sci. Discuss., https://doi.org/10.5194/hessd-10-13191-2013, https://doi.org/10.5194/hessd-10-13191-2013, 2013
Manuscript not accepted for further review
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Benchmark dataset for hydraulic simulations of flash floods in the French Mediterranean region
Transformation rate maps of dissolved organic carbon in the contiguous US
A 1985–2023 time series dataset of absolute reservoir storage in Mainland Southeast Asia (MSEA-Res)
Machine-learning-based reconstruction of long-term global terrestrial water storage anomalies from observed, satellite and land-surface model data
Mapping the world's inland surface waters: an upgrade to the Global Lakes and Wetlands Database (GLWD v2)
One year of high-frequency monitoring of groundwater physico-chemical parameters in the Weierbach experimental catchment, Luxembourg
Discrete global grid system-based flow routing datasets in the Amazon and Yukon basins
GRILSS: opening the gateway to global reservoir sedimentation data curation
An operational SMOS soil freeze-thaw product
A worldwide event-based debris flow barrier dam dataset from 1800 to 2023
CAMELS-DK: hydrometeorological time series and landscape attributes for 3330 Danish catchments with streamflow observations from 304 gauged stations
An in situ daily dataset for benchmarking temporal variability of groundwater recharge
CAMELS-FR dataset: a large-sample hydroclimatic dataset for France to explore hydrological diversity and support model benchmarking
Development of HYPER-P: HYdroclimatic PERformance-enhanced Precipitation at 1 km/daily over the Europe-Mediterranean region from 2007 to 2022
Features of Italian large dams and their upstream catchments
P-LSHv2: a multi-decadal global daily land surface actual evapotranspiration dataset enhanced with explicit soil moisture constraints in remote sensing retrieval
Gridded rainfall erosivity (2014–2022) in mainland China using 1 min precipitation data from densely distributed weather stations
Multi-tool dataset on Northern Eurasian Riverbank Migration (NERM)
High-resolution hydrometeorological and snow data for the Dischma catchment in Switzerland
CAMELS-IND: hydrometeorological time series and catchment attributes for 228 catchments in Peninsular India
HERA: a high-resolution pan-European hydrological reanalysis (1951–2020)
BCUB – a large-sample ungauged basin attribute dataset for British Columbia, Canada
A 1 km soil moisture data over eastern CONUS generated through assimilating SMAP data into the Noah-MP land surface model
A seamless global daily 5 km soil moisture product from 1982 to 2021 using AVHRR satellite data and an attention-based deep learning model
ESA CCI Soil Moisture GAPFILLED: An independent global gap-free satellite climate data record with uncertainty estimates
Lena River biogeochemistry captured by a 4.5-year high-frequency sampling program
CAMELS-DE: hydro-meteorological time series and attributes for 1582 catchments in Germany
Observational partitioning of water and CO2 fluxes at National Ecological Observatory Network (NEON) sites: a 5-year dataset of soil and plant components for spatial and temporal analysis
GRDC-Caravan: extending Caravan with data from the Global Runoff Data Centre
CIrrMap250: annual maps of China's irrigated cropland from 2000 to 2020 developed through multisource data integration
HANZE v2.1: an improved database of flood impacts in Europe from 1870 to 2020
A Copernicus-based evapotranspiration dataset at 100 m spatial resolution over four Mediterranean basins
Gridded dataset of nitrogen and phosphorus point sources from wastewater in Germany (1950–2019)
A globally sampled high-resolution hand-labeled validation dataset for evaluating surface water extent maps
Satellite-based near-real-time global daily terrestrial evapotranspiration estimates
Multivariate characterisation of a blackberry–alder agroforestry system in South Africa: hydrological, pedological, dendrological and meteorological measurements
CAMELS-AUS v2: updated hydrometeorological timeseries and landscape attributes for an enlarged set of catchments in Australia
SHIFT: a spatial-heterogeneity improvement in DEM-based mapping of global geomorphic floodplains
First comprehensive stable isotope dataset of diverse water units in a permafrost-dominated catchment on the Qinghai–Tibet Plateau
LamaH-Ice: LArge-SaMple DAta for Hydrology and Environmental Sciences for Iceland
High-resolution mapping of monthly industrial water withdrawal in China from 1965 to 2020
Evapotranspiration evaluation using three different protocols on a large green roof in the greater Paris area
Simbi: historical hydro-meteorological time series and signatures for 24 catchments in Haiti
Wangyipu Li, Zhaoyuan Yao, Yifan Qu, Hanbo Yang, Yang Song, Lisheng Song, Lifeng Wu, and Yaokui Cui
Earth Syst. Sci. Data, 17, 3835–3855, https://doi.org/10.5194/essd-17-3835-2025, https://doi.org/10.5194/essd-17-3835-2025, 2025
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Due to shortcomings such as extensive data gaps and limited observation durations in current ground-based latent heat flux (LE) datasets, we developed a novel gap-filling and prolongation framework for ground-based LE observations, establishing a benchmark dataset for global evapotranspiration (ET) estimation from 2000 to 2022 across 64 sites at various timescales. This comprehensive dataset can strongly support ET modeling, water–carbon cycle monitoring, and long-term climate change analysis.
Colleen Mortimer and Vincent Vionnet
Earth Syst. Sci. Data, 17, 3619–3640, https://doi.org/10.5194/essd-17-3619-2025, https://doi.org/10.5194/essd-17-3619-2025, 2025
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In situ observations of snow water equivalent (SWE) are critical for climate applications and resource management. NorSWE is a dataset of in situ SWE observations covering North America, Norway, Finland, Switzerland, Russia, and Nepal over the period 1979–2021. It includes more than 11.5 million observations from more than 10 000 different locations compiled from nine different sources. Snow depth and derived bulk snow density are included when available.
Camille Minaudo, Andras Abonyi, Carles Alcaraz, Jacob Diamond, Nicholas J. K. Howden, Michael Rode, Estela Romero, Vincent Thieu, Fred Worrall, Qian Zhang, and Xavier Benito
Earth Syst. Sci. Data, 17, 3411–3430, https://doi.org/10.5194/essd-17-3411-2025, https://doi.org/10.5194/essd-17-3411-2025, 2025
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Many waterbodies undergo nutrient decline, called oligotrophication, globally, but a comprehensive dataset to understand ecosystem responses is lacking. The OLIGOTREND database comprises multi-decadal chlorophyll a and nutrient time series from rivers, lakes, and estuaries with 4.3 million observations from 1894 unique measurement locations. The database provides empirical evidence for oligotrophication responses with a spatial and temporal coverage that exceeds previous efforts.
Haoxuan Yang, Jia Yang, Tyson E. Ochsner, Erik S. Krueger, Mengyuan Xu, and Chris B. Zou
Earth Syst. Sci. Data, 17, 3391–3409, https://doi.org/10.5194/essd-17-3391-2025, https://doi.org/10.5194/essd-17-3391-2025, 2025
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We developed a 3 h, 1 km surface soil moisture dataset for the contiguous United States from 2015 to 2023 using the spatio-temporal fusion method. This dataset effectively combines the distinct advantages of two long-term surface soil moisture datasets, which is also the first hourly-level 1 km soil moisture dataset at the continental US scale. The new dataset could provide new insight into the fast changes in soil moisture along with drought and wet spell occurrences.
Andrea Galletti, Soroush Zarghami Dastjerdi, and Bruno Majone
Earth Syst. Sci. Data, 17, 3353–3373, https://doi.org/10.5194/essd-17-3353-2025, https://doi.org/10.5194/essd-17-3353-2025, 2025
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IAR-HP (Italian Alpine Region HydroPower) is a detailed inventory of large hydropower systems in Italy's Alpine Region, aimed at improving their inclusion in hydrological modeling by providing relevant information with a consistent level of detail. It includes structural, geographic, and operational data for over 300 hydropower plants and their related reservoirs and water intakes. Validated through modeling, IAR-HP accurately reproduces observed hydropower, capturing 96.2 % of actual production.
Lauranne Alaerts, Jonathan Lambrechts, Ny Riana Randresihaja, Luc Vandenbulcke, Olivier Gourgue, Emmanuel Hanert, and Marilaure Grégoire
Earth Syst. Sci. Data, 17, 3125–3140, https://doi.org/10.5194/essd-17-3125-2025, https://doi.org/10.5194/essd-17-3125-2025, 2025
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We created the first comprehensive, high-resolution, and easily accessible bathymetry dataset for the three main branches of the Danube Delta. By combining four data sources, we obtained a detailed representation of the riverbed, with resolutions ranging from 2 to 100 m. This dataset will support future studies on water and nutrient exchanges between the Danube and the Black Sea and provide insights into the delta's buffer role within the understudied Danube–Black Sea continuum.
Bennett J. McAfee, Aanish Pradhan, Abhilash Neog, Sepideh Fatemi, Robert T. Hensley, Mary E. Lofton, Anuj Karpatne, Cayelan C. Carey, and Paul C. Hanson
Earth Syst. Sci. Data, 17, 3141–3165, https://doi.org/10.5194/essd-17-3141-2025, https://doi.org/10.5194/essd-17-3141-2025, 2025
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LakeBeD-US is a dataset of lake water quality data collected by multiple long-term monitoring programs around the United States. This dataset is designed to foster collaboration between lake scientists and computer scientists to improve predictions of water quality. By offering a way for computer models to be tested against real-world lake data, LakeBeD-US offers opportunities for both sciences to grow and to give new insights into the causes of water quality changes.
Juliette Godet, Pierre Nicolle, Nabil Hocini, Eric Gaume, Philippe Davy, Frederic Pons, Pierre Javelle, Pierre-André Garambois, Dimitri Lague, and Olivier Payrastre
Earth Syst. Sci. Data, 17, 2963–2983, https://doi.org/10.5194/essd-17-2963-2025, https://doi.org/10.5194/essd-17-2963-2025, 2025
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This paper describes a dataset that includes input, output, and validation data for the simulation of flash flood hazards and three specific flash flood events in the French Mediterranean region. This dataset is particularly valuable as flood mapping methods often lack sufficient benchmark data. Additionally, we demonstrate how the hydraulic method we used, named Floodos, produces highly satisfactory results.
Lingbo Li, Hong-Yi Li, Guta Abeshu, Jinyun Tang, L. Ruby Leung, Chang Liao, Zeli Tan, Hanqin Tian, Peter Thornton, and Xiaojuan Yang
Earth Syst. Sci. Data, 17, 2713–2733, https://doi.org/10.5194/essd-17-2713-2025, https://doi.org/10.5194/essd-17-2713-2025, 2025
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We have developed new maps that reveal how organic carbon from soil leaches into headwater streams over the contiguous United States. We use advanced artificial intelligence techniques and a massive amount of data, including observations at over 2500 gauges and a wealth of climate and environmental information. The maps are a critical step in understanding and predicting how carbon moves through our environment, hence making them a useful tool for tackling climate challenges.
Shanti Shwarup Mahto, Simone Fatichi, and Stefano Galelli
Earth Syst. Sci. Data, 17, 2693–2712, https://doi.org/10.5194/essd-17-2693-2025, https://doi.org/10.5194/essd-17-2693-2025, 2025
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The MSEA-Res database offers an open-access dataset tracking absolute water storage for 186 large reservoirs across Mainland Southeast Asia from 1985 to 2023. It provides valuable insights into how reservoir storage grew by 130 % between 2008 and 2017, driven by dams in key river basins. Our data also reveal how droughts, like the 2019–2020 event, significantly impacted water reservoirs. This resource can aid water management, drought planning, and research globally.
Nehar Mandal, Prabal Das, and Kironmala Chanda
Earth Syst. Sci. Data, 17, 2575–2604, https://doi.org/10.5194/essd-17-2575-2025, https://doi.org/10.5194/essd-17-2575-2025, 2025
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Optimal features among hydroclimatic variables and land surface model (LSM) outputs are selected using a novel Bayesian network (BN) approach for simulating terrestrial water storage anomalies (TWSAs). TWSAs are reconstructed (BNML_TWSA) with grid-specific leader models (among four machine learning models) from January 1960 to December 2022 to generate a continuous global gridded dataset. The uncertainty in the reconstructed BNML_TWSA product is also assessed in terms of standard error.
Bernhard Lehner, Mira Anand, Etienne Fluet-Chouinard, Florence Tan, Filipe Aires, George H. Allen, Philippe Bousquet, Josep G. Canadell, Nick Davidson, Meng Ding, C. Max Finlayson, Thomas Gumbricht, Lammert Hilarides, Gustaf Hugelius, Robert B. Jackson, Maartje C. Korver, Liangyun Liu, Peter B. McIntyre, Szabolcs Nagy, David Olefeldt, Tamlin M. Pavelsky, Jean-Francois Pekel, Benjamin Poulter, Catherine Prigent, Jida Wang, Thomas A. Worthington, Dai Yamazaki, Xiao Zhang, and Michele Thieme
Earth Syst. Sci. Data, 17, 2277–2329, https://doi.org/10.5194/essd-17-2277-2025, https://doi.org/10.5194/essd-17-2277-2025, 2025
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The Global Lakes and Wetlands Database (GLWD) version 2 distinguishes a total of 33 non-overlapping wetland classes, providing a static map of the world’s inland surface waters. It contains cell fractions of wetland extents per class at a grid cell resolution of ~500 m. The total combined extent of all classes including all inland and coastal waterbodies and wetlands of all inundation frequencies – that is, the maximum extent – covers 18.2 × 106 km2, equivalent to 13.4 % of total global land area.
Karl Nicolaus van Zweel, Laurent Gourdol, Jean François Iffly, Loïc Léonard, François Barnich, Laurent Pfister, Erwin Zehe, and Christophe Hissler
Earth Syst. Sci. Data, 17, 2217–2229, https://doi.org/10.5194/essd-17-2217-2025, https://doi.org/10.5194/essd-17-2217-2025, 2025
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Our study monitored groundwater in a Luxembourg forest over a year to understand water and chemical changes. We found seasonal variations in water chemistry, influenced by rainfall and soil interactions. These data help predict environmental responses and manage water resources better. By measuring key parameters like pH and dissolved oxygen, our research provides valuable insights into groundwater behaviour and serves as a resource for future environmental studies.
Chang Liao, Darren Engwirda, Matthew G. Cooper, Mingke Li, and Yilin Fang
Earth Syst. Sci. Data, 17, 2035–2062, https://doi.org/10.5194/essd-17-2035-2025, https://doi.org/10.5194/essd-17-2035-2025, 2025
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Discrete global grid systems, or DGGS, are digital frameworks that help us organize information about our planet. Although scientists have used DGGS in areas like weather and nature, using them in the water cycle has been challenging because some core datasets are missing. We created a way to generate these datasets. We then developed the datasets in the Amazon and Yukon basins, which play important roles in our planet's climate. These datasets may help us improve our water cycle models.
Sanchit Minocha and Faisal Hossain
Earth Syst. Sci. Data, 17, 1743–1759, https://doi.org/10.5194/essd-17-1743-2025, https://doi.org/10.5194/essd-17-1743-2025, 2025
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Trustworthy and independently verifiable information on declining storage capacity or sedimentation rates worldwide is sparse and suffers from inconsistent metadata and curation to allow global-scale archiving and analyses. The Global Reservoir Inventory of Lost Storage by Sedimentation (GRILSS) dataset addresses this challenge by providing organized, well-curated, and open-source data on sedimentation rates and capacity loss for 1013 reservoirs in 75 major river basins across 54 countries.
Kimmo Rautiainen, Manu Holmberg, Juval Cohen, Arnaud Mialon, Mike Schwank, Juha Lemmetyinen, Antonio de la Fuente, and Yann Kerr
Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2025-68, https://doi.org/10.5194/essd-2025-68, 2025
Revised manuscript accepted for ESSD
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The SMOS Soil Freeze Thaw State product uses satellite data to monitor seasonal soil freezing and thawing globally, with a focus on high latitude regions. This is important for understanding greenhouse gas emissions, as frozen soil is associated with methane release. The product provides accurate data on key events such as the first day of soil freezing in autumn, helping scientists to study climate change, ecosystem dynamics and its impact on our planet.
Haiguang Cheng, Kaiheng Hu, Shuang Liu, Xiaopeng Zhang, Hao Li, Qiyuan Zhang, Lan Ning, Manish Raj Gouli, Pu Li, Anna Yang, Peng Zhao, Junyu Liu, and Li Wei
Earth Syst. Sci. Data, 17, 1573–1593, https://doi.org/10.5194/essd-17-1573-2025, https://doi.org/10.5194/essd-17-1573-2025, 2025
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After reviewing 2519 literature and media reports, we compiled the first comprehensive global dataset of 555 debris flow barrier dams (DFBDs) from 1800 to 2023. Our dataset meticulously documents 38 attributes of DFBDs, and we have utilized Google Earth for validation. Additionally, we discussed the applicability of landslide dam stability and peak-discharge models to DFBDs. This dataset offers a rich foundation of data for future studies on DFBDs.
Jun Liu, Julian Koch, Simon Stisen, Lars Troldborg, Anker Lajer Højberg, Hans Thodsen, Mark F. T. Hansen, and Raphael J. M. Schneider
Earth Syst. Sci. Data, 17, 1551–1572, https://doi.org/10.5194/essd-17-1551-2025, https://doi.org/10.5194/essd-17-1551-2025, 2025
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We developed a CAMELS-style dataset in Denmark, which contains hydrometeorological time series and landscape attributes for 3330 catchments (304 gauged). Many catchments in CAMELS-DK are small and at low elevations. The dataset provides information on groundwater characteristics and dynamics, as well as quantities related to the human impact on the hydrological system in Denmark. The dataset is especially relevant for developing data-driven and hybrid physically informed modeling frameworks.
Pragnaditya Malakar, Aatish Anshuman, Mukesh Kumar, Georgios Boumis, T. Prabhakar Clement, Arik Tashie, Hitesh Thakur, Nagaraj Bhat, and Lokendra Rathore
Earth Syst. Sci. Data, 17, 1515–1528, https://doi.org/10.5194/essd-17-1515-2025, https://doi.org/10.5194/essd-17-1515-2025, 2025
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Groundwater dynamics depend on groundwater recharge, but daily benchmark data of recharge are scarce. Here we present a daily groundwater recharge per unit specified yield (RpSy) data at 485 US groundwater monitoring wells. RpSy can be used to validate the temporal consistency of recharge products from land surface and hydrologic models and facilitate assessment of recharge-driver functional relationships in them.
Olivier Delaigue, Guilherme Mendoza Guimarães, Pierre Brigode, Benoît Génot, Charles Perrin, Jean-Michel Soubeyroux, Bruno Janet, Nans Addor, and Vazken Andréassian
Earth Syst. Sci. Data, 17, 1461–1479, https://doi.org/10.5194/essd-17-1461-2025, https://doi.org/10.5194/essd-17-1461-2025, 2025
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This dataset covers 654 rivers all flowing in France. The provided time series and catchment attributes will be of interest to those modelers wishing to analyze hydrological behavior and perform model assessments.
Paolo Filippucci, Luca Brocca, Luca Ciabatta, Hamidreza Mosaffa, Francesco Avanzi, and Christian Massari
Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2025-156, https://doi.org/10.5194/essd-2025-156, 2025
Revised manuscript accepted for ESSD
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Accurate rainfall data is essential, yet measuring daily precipitation worldwide is challenging. This research presents HYdroclimatic PERformance-enhanced Precipitation (HYPER-P), a dataset combining satellite, ground, and reanalysis data to estimate precipitation at a 1 km scale from 2000 to 2023. HYPER-P improves accuracy, especially in areas with few rain gauges. This dataset supports scientists and decision-makers in understanding and managing water resources more effectively.
Giulia Evangelista, Paola Mazzoglio, Daniele Ganora, Francesca Pianigiani, and Pierluigi Claps
Earth Syst. Sci. Data, 17, 1407–1426, https://doi.org/10.5194/essd-17-1407-2025, https://doi.org/10.5194/essd-17-1407-2025, 2025
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This paper presents the first comprehensive dataset of 528 large dams in Italy. It contains structural characteristics of the dams, such as coordinates, reservoir surface areas and volumes, together with a range of geomorphological, climatological, extreme rainfall, land cover and soil-related attributes of their upstream catchments.
Jin Feng, Ke Zhang, Lijun Chao, Huijie Zhan, and Yunping Li
Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2025-137, https://doi.org/10.5194/essd-2025-137, 2025
Revised manuscript accepted for ESSD
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Understanding how soil moisture affects evapotranspiration (ET) is essential for improving ET estimates. However, many global ET datasets overlook soil moisture constraints, causing large uncertainties. In this study, we developed an improved model that better captures the influence of soil moisture on vegetation and soil evaporation. Our model significantly improves ET estimation accuracy and provides a new long-term global ET dataset to support water cycle and climate research.
Yueli Chen, Yun Xie, Xingwu Duan, and Minghu Ding
Earth Syst. Sci. Data, 17, 1265–1274, https://doi.org/10.5194/essd-17-1265-2025, https://doi.org/10.5194/essd-17-1265-2025, 2025
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Rainfall erosivity maps are crucial for identifying key areas of water erosion. Due to the limited historical precipitation data, there are certain biases in rainfall erosivity estimates in China. This study develops a new rainfall erosivity map for mainland China using 1 min precipitation data from 60 129 weather stations, revealing that areas exceeding 4000 MJ mm ha−1 h−1yr−1 of annual rainfall erosivity are mainly concentrated in southern China and on the southern Tibetan Plateau.
Sergey R. Chalov, Victor Ivanov, Danila Shkolnyi, Ekaterina Pavlyukevich, Michal Habel, Dmitry Botavin, Aleksandra Chalova, Pavel Golovlev, Arseny Kamyshev, Roman Kolesnikov, Uliana Koneva, Anna Kurakova, Nadezda Mikhailova, Elizaveta Tuzova, Kristina Prokopeva, Aleksandr Zavadsky, Rituparna Acharyya, Roman S. Chalov, Aleksandr Varenov, Leonid Turykin, Anna Tarbeeva, and Daidu Fan
Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2025-150, https://doi.org/10.5194/essd-2025-150, 2025
Revised manuscript accepted for ESSD
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This study presents a unique multi-tool dataset on riverbank migration across Northern Eurasia, covering 140,000 km of river channels over a period of up to 70 years. Using satellite imagery and field observations, we identify key drivers of bank erosion in large spatial scale and highlight role of river discharge and permafrost. The dataset enhances understanding of river channel dynamics and supports the development of predictive models for river channel evolution and erosion risk assessment.
Jan Magnusson, Yves Bühler, Louis Quéno, Bertrand Cluzet, Giulia Mazzotti, Clare Webster, Rebecca Mott, and Tobias Jonas
Earth Syst. Sci. Data, 17, 703–717, https://doi.org/10.5194/essd-17-703-2025, https://doi.org/10.5194/essd-17-703-2025, 2025
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In this study, we present a dataset for the Dischma catchment in eastern Switzerland, which represents a typical high-alpine watershed in the European Alps. Accurate monitoring and reliable forecasting of snow and water resources in such basins are crucial for a wide range of applications. Our dataset is valuable for improving physics-based snow, land surface, and hydrological models, with potential applications in similar high-alpine catchments.
Nikunj K. Mangukiya, Kanneganti Bhargav Kumar, Pankaj Dey, Shailza Sharma, Vijaykumar Bejagam, Pradeep P. Mujumdar, and Ashutosh Sharma
Earth Syst. Sci. Data, 17, 461–491, https://doi.org/10.5194/essd-17-461-2025, https://doi.org/10.5194/essd-17-461-2025, 2025
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We introduce CAMELS-IND (Catchment Attributes and MEteorology for Large-sample Studies – India), which provides daily hydrometeorological time series and static catchment attributes representing the location, topography, climate, hydrological signatures, land use, land cover, soil, geology, and anthropogenic influences for 472 catchments in Peninsular India to foster large-sample hydrological studies in India and promote the inclusion of Indian catchments in global hydrological research.
Aloïs Tilloy, Dominik Paprotny, Stefania Grimaldi, Goncalo Gomes, Alessandra Bianchi, Stefan Lange, Hylke Beck, Cinzia Mazzetti, and Luc Feyen
Earth Syst. Sci. Data, 17, 293–316, https://doi.org/10.5194/essd-17-293-2025, https://doi.org/10.5194/essd-17-293-2025, 2025
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This article presents a reanalysis of Europe's river streamflow for the period 1951–2020. Streamflow is estimated through a state-of-the-art hydrological simulation framework benefitting from detailed information about the landscape, climate, and human activities. The resulting Hydrological European ReAnalysis (HERA) can be a valuable tool for studying hydrological dynamics, including the impacts of climate change and human activities on European water resources and flood and drought risks.
Daniel Kovacek and Steven Weijs
Earth Syst. Sci. Data, 17, 259–275, https://doi.org/10.5194/essd-17-259-2025, https://doi.org/10.5194/essd-17-259-2025, 2025
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We made a dataset for British Columbia describing the terrain, soil, land cover, and climate of over 1 million watersheds. The attributes are often used in hydrology because they are related to the water cycle. The data are meant to be used for water resources problems that can benefit from lots of watersheds and their attributes. The data and instructions needed to build the dataset from scratch are freely available. The permanent home for the data is https://doi.org/10.5683/SP3/JNKZVT.
Sheng-Lun Tai, Zhao Yang, Brian Gaudet, Koichi Sakaguchi, Larry Berg, Colleen Kaul, Yun Qian, Ye Liu, and Jerome Fast
Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2024-599, https://doi.org/10.5194/essd-2024-599, 2025
Revised manuscript accepted for ESSD
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Our study created a high-resolution soil moisture dataset for the eastern U.S. by integrating satellite data with a land surface model and advanced algorithms, achieving 1-km scale analyses. Validated against multiple networks and datasets, it demonstrated superior accuracy. This dataset is vital for understanding soil moisture dynamics, especially during droughts, and highlights the need for improved modeling of clay soils to refine future predictions.
Yufang Zhang, Shunlin Liang, Han Ma, Tao He, Feng Tian, Guodong Zhang, and Jianglei Xu
Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2024-553, https://doi.org/10.5194/essd-2024-553, 2025
Revised manuscript accepted for ESSD
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Soil moisture (SM) plays a vital role in climate, agriculture, and hydrology, yet reliable long-term seamless global datasets remain scarce. To fill this gap, we developed a four-decade seamless global daily 5 km SM product using multi-source datasets and deep learning techniques. This product has long-term coverage, spatial and temporal integrity, and high accuracy, making it a valuable tool for applications like SM trend analysis, drought monitoring, and assessing vegetation responses.
Wolfgang Preimesberger, Pietro Stradiotti, and Wouter Dorigo
Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2024-610, https://doi.org/10.5194/essd-2024-610, 2025
Revised manuscript accepted for ESSD
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We introduce the official ESA CCI Soil Moisture GAPFILLED climate data record. A univariate interpolation algorithm is applied to predict missing data points without relying on ancillary variables. The dataset includes gap-free uncertainty estimates for all predictions and was validated with independent in situ reference measurements. The data are recommended for applications, which require global long-term gap-free satellite soil moisture data.
Bennet Juhls, Anne Morgenstern, Jens Hölemann, Antje Eulenburg, Birgit Heim, Frederieke Miesner, Hendrik Grotheer, Gesine Mollenhauer, Hanno Meyer, Ephraim Erkens, Felica Yara Gehde, Sofia Antonova, Sergey Chalov, Maria Tereshina, Oxana Erina, Evgeniya Fingert, Ekaterina Abramova, Tina Sanders, Liudmila Lebedeva, Nikolai Torgovkin, Georgii Maksimov, Vasily Povazhnyi, Rafael Gonçalves-Araujo, Urban Wünsch, Antonina Chetverova, Sophie Opfergelt, and Pier Paul Overduin
Earth Syst. Sci. Data, 17, 1–28, https://doi.org/10.5194/essd-17-1-2025, https://doi.org/10.5194/essd-17-1-2025, 2025
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The Siberian Arctic is warming fast: permafrost is thawing, river chemistry is changing, and coastal ecosystems are affected. We aimed to understand changes in the Lena River, a major Arctic river flowing to the Arctic Ocean, by collecting 4.5 years of detailed water data, including temperature and carbon and nutrient contents. This dataset records current conditions and helps us to detect future changes. Explore it at https://doi.org/10.1594/PANGAEA.913197 and https://lena-monitoring.awi.de/.
Ralf Loritz, Alexander Dolich, Eduardo Acuña Espinoza, Pia Ebeling, Björn Guse, Jonas Götte, Sibylle K. Hassler, Corina Hauffe, Ingo Heidbüchel, Jens Kiesel, Mirko Mälicke, Hannes Müller-Thomy, Michael Stölzle, and Larisa Tarasova
Earth Syst. Sci. Data, 16, 5625–5642, https://doi.org/10.5194/essd-16-5625-2024, https://doi.org/10.5194/essd-16-5625-2024, 2024
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The CAMELS-DE dataset features data from 1582 streamflow gauges across Germany, with records spanning from 1951 to 2020. This comprehensive dataset, which includes time series of up to 70 years (median 46 years), enables advanced research on water flow and environmental trends and supports the development of hydrological models.
Einara Zahn and Elie Bou-Zeid
Earth Syst. Sci. Data, 16, 5603–5624, https://doi.org/10.5194/essd-16-5603-2024, https://doi.org/10.5194/essd-16-5603-2024, 2024
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Quantifying water and CO2 exchanges through transpiration, evaporation, net photosynthesis, and soil respiration is essential for understanding how ecosystems function. We implemented five methods to estimate these fluxes over a 5-year period across 47 sites. This is the first dataset representing such large spatial and temporal coverage of soil and plant exchanges, and it has many potential applications, such as examining the response of ecosystems to weather extremes and climate change.
Claudia Färber, Henning Plessow, Simon Mischel, Frederik Kratzert, Nans Addor, Guy Shalev, and Ulrich Looser
Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2024-427, https://doi.org/10.5194/essd-2024-427, 2024
Revised manuscript accepted for ESSD
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Large-sample datasets are essential in hydrological science to support modelling studies and advance process understanding. Caravan is a community initiative to create a large-sample hydrology dataset of meteorological forcing data, catchment attributes, and discharge data for catchments around the world. This dataset is a subset of hydrological discharge data and station-based watersheds from the Global Runoff Data Centre (GRDC), which are covered by an open data policy.
Ling Zhang, Yanhua Xie, Xiufang Zhu, Qimin Ma, and Luca Brocca
Earth Syst. Sci. Data, 16, 5207–5226, https://doi.org/10.5194/essd-16-5207-2024, https://doi.org/10.5194/essd-16-5207-2024, 2024
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This study presented new annual maps of irrigated cropland in China from 2000 to 2020 (CIrrMap250). These maps were developed by integrating remote sensing data, irrigation statistics and surveys, and an irrigation suitability map. CIrrMap250 achieved high accuracy and outperformed currently available products. The new irrigation maps revealed a clear expansion of China’s irrigation area, with the majority (61%) occurring in the water-unsustainable regions facing severe to extreme water stress.
Dominik Paprotny, Paweł Terefenko, and Jakub Śledziowski
Earth Syst. Sci. Data, 16, 5145–5170, https://doi.org/10.5194/essd-16-5145-2024, https://doi.org/10.5194/essd-16-5145-2024, 2024
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Knowledge about past natural disasters can help adaptation to their future occurrences. Here, we present a dataset of 2521 riverine, pluvial, coastal, and compound floods that have occurred in 42 European countries between 1870 and 2020. The dataset contains available information on the inundated area, fatalities, persons affected, or economic loss and was obtained by extensive data collection from more than 800 sources ranging from news reports through government databases to scientific papers.
Paulina Bartkowiak, Bartolomeo Ventura, Alexander Jacob, and Mariapina Castelli
Earth Syst. Sci. Data, 16, 4709–4734, https://doi.org/10.5194/essd-16-4709-2024, https://doi.org/10.5194/essd-16-4709-2024, 2024
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This paper presents the Two-Source Energy Balance evapotranspiration (ET) product driven by Copernicus Sentinel-2 and Sentinel-3 imagery together with ERA5 climate reanalysis data. Daily ET maps are available at 100 m spatial resolution for the period 2017–2021 across four Mediterranean basins: Ebro (Spain), Hérault (France), Medjerda (Tunisia), and Po (Italy). The product is highly beneficial for supporting vegetation monitoring and sustainable water management at the river basin scale.
Fanny J. Sarrazin, Sabine Attinger, and Rohini Kumar
Earth Syst. Sci. Data, 16, 4673–4708, https://doi.org/10.5194/essd-16-4673-2024, https://doi.org/10.5194/essd-16-4673-2024, 2024
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Nitrogen (N) and phosphorus (P) contamination of water bodies is a long-term issue due to the long history of N and P inputs to the environment and their persistence. Here, we introduce a long-term and high-resolution dataset of N and P inputs from wastewater (point sources) for Germany, combining data from different sources and conceptual understanding. We also account for uncertainties in modelling choices, thus facilitating robust long-term and large-scale water quality studies.
Rohit Mukherjee, Frederick Policelli, Ruixue Wang, Elise Arellano-Thompson, Beth Tellman, Prashanti Sharma, Zhijie Zhang, and Jonathan Giezendanner
Earth Syst. Sci. Data, 16, 4311–4323, https://doi.org/10.5194/essd-16-4311-2024, https://doi.org/10.5194/essd-16-4311-2024, 2024
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Global water resource monitoring is crucial due to climate change and population growth. This study presents a hand-labeled dataset of 100 PlanetScope images for surface water detection, spanning diverse biomes. We use this dataset to evaluate two state-of-the-art mapping methods. Results highlight performance variations across biomes, emphasizing the need for diverse, independent validation datasets to enhance the accuracy and reliability of satellite-based surface water monitoring techniques.
Lei Huang, Yong Luo, Jing M. Chen, Qiuhong Tang, Tammo Steenhuis, Wei Cheng, and Wen Shi
Earth Syst. Sci. Data, 16, 3993–4019, https://doi.org/10.5194/essd-16-3993-2024, https://doi.org/10.5194/essd-16-3993-2024, 2024
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Timely global terrestrial evapotranspiration (ET) data are crucial for water resource management and drought forecasting. This study introduces the VISEA algorithm, which integrates satellite data and shortwave radiation to provide daily 0.05° gridded near-real-time ET estimates. By employing a vegetation index–temperature method, this algorithm can estimate ET without requiring additional data. Evaluation results demonstrate VISEA's comparable accuracy with accelerated data availability.
Sibylle Kathrin Hassler, Rafael Bohn Reckziegel, Ben du Toit, Svenja Hoffmeister, Florian Kestel, Anton Kunneke, Rebekka Maier, and Jonathan Paul Sheppard
Earth Syst. Sci. Data, 16, 3935–3948, https://doi.org/10.5194/essd-16-3935-2024, https://doi.org/10.5194/essd-16-3935-2024, 2024
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Agroforestry systems (AFSs) combine trees and crops within the same land unit, providing a sustainable land use option which protects natural resources and biodiversity. Introducing trees into agricultural systems can positively affect water resources, soil characteristics, biomass and microclimate. We studied an AFS in South Africa in a multidisciplinary approach to assess the different influences and present the resulting dataset consisting of water, soil, tree and meteorological variables.
Keirnan J. A. Fowler, Ziqi Zhang, and Xue Hou
Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2024-263, https://doi.org/10.5194/essd-2024-263, 2024
Revised manuscript accepted for ESSD
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This paper presents Version 2 of the Australian edition of the Catchment Attributes and Meteorology for Large-sample Studies (CAMELS) series of datasets. CAMELS-AUS v2 comprises data for an increased number (561) of catchments, each with with long-term monitoring, combining hydrometeorological time series with attributes related to geology, soil, topography, land cover, anthropogenic influence and hydroclimatology. It is freely downloadable from https://zenodo.org/doi/10.5281/zenodo.12575680.
Kaihao Zheng, Peirong Lin, and Ziyun Yin
Earth Syst. Sci. Data, 16, 3873–3891, https://doi.org/10.5194/essd-16-3873-2024, https://doi.org/10.5194/essd-16-3873-2024, 2024
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We develop a globally applicable thresholding scheme for DEM-based floodplain delineation to improve the representation of spatial heterogeneity. It involves a stepwise approach to estimate the basin-level floodplain hydraulic geometry parameters that best respect the scaling law while approximating the global hydrodynamic flood maps. A ~90 m resolution global floodplain map, the Spatial Heterogeneity Improved Floodplain by Terrain analysis (SHIFT), is delineated with demonstrated superiority.
Yuzhong Yang, Qingbai Wu, Xiaoyan Guo, Lu Zhou, Helin Yao, Dandan Zhang, Zhongqiong Zhang, Ji Chen, and Guojun Liu
Earth Syst. Sci. Data, 16, 3755–3770, https://doi.org/10.5194/essd-16-3755-2024, https://doi.org/10.5194/essd-16-3755-2024, 2024
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We present the temporal data of stable isotopes in different waterbodies in the Beiluhe Basin in the hinterland of the Qinghai–Tibet Plateau (QTP) produced between 2017 and 2022. In this article, the first detailed stable isotope data of 359 ground ice samples are presented. This first data set provides a new basis for understanding the hydrological effects of permafrost degradation on the QTP.
Hordur Bragi Helgason and Bart Nijssen
Earth Syst. Sci. Data, 16, 2741–2771, https://doi.org/10.5194/essd-16-2741-2024, https://doi.org/10.5194/essd-16-2741-2024, 2024
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LamaH-Ice is a large-sample hydrology (LSH) dataset for Iceland. The dataset includes daily and hourly hydro-meteorological time series, including observed streamflow and basin characteristics, for 107 basins. LamaH-Ice offers most variables that are included in existing LSH datasets and additional information relevant to cold-region hydrology such as annual time series of glacier extent and mass balance. A large majority of the basins in LamaH-Ice are unaffected by human activities.
Chengcheng Hou, Yan Li, Shan Sang, Xu Zhao, Yanxu Liu, Yinglu Liu, and Fang Zhao
Earth Syst. Sci. Data, 16, 2449–2464, https://doi.org/10.5194/essd-16-2449-2024, https://doi.org/10.5194/essd-16-2449-2024, 2024
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To fill the gap in the gridded industrial water withdrawal (IWW) data in China, we developed the China Industrial Water Withdrawal (CIWW) dataset, which provides monthly IWWs from 1965 to 2020 at a spatial resolution of 0.1°/0.25° and auxiliary data including subsectoral IWW and industrial output value in 2008. This dataset can help understand the human water use dynamics and support studies in hydrology, geography, sustainability sciences, and water resource management and allocation in China.
Pierre-Antoine Versini, Leydy Alejandra Castellanos-Diaz, David Ramier, and Ioulia Tchiguirinskaia
Earth Syst. Sci. Data, 16, 2351–2366, https://doi.org/10.5194/essd-16-2351-2024, https://doi.org/10.5194/essd-16-2351-2024, 2024
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Nature-based solutions (NBSs), such as green roofs, have appeared as relevant solutions to mitigate urban heat islands. The evapotranspiration (ET) process allows NBSs to cool the air. To improve our knowledge about ET assessment, this paper presents some experimental measurement campaigns carried out during three consecutive summers. Data are available for three different (large, small, and point-based) spatial scales.
Ralph Bathelemy, Pierre Brigode, Vazken Andréassian, Charles Perrin, Vincent Moron, Cédric Gaucherel, Emmanuel Tric, and Dominique Boisson
Earth Syst. Sci. Data, 16, 2073–2098, https://doi.org/10.5194/essd-16-2073-2024, https://doi.org/10.5194/essd-16-2073-2024, 2024
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The aim of this work is to provide the first hydroclimatic database for Haiti, a Caribbean country particularly vulnerable to meteorological and hydrological hazards. The resulting database, named Simbi, provides hydroclimatic time series for around 150 stations and 24 catchment areas.
Cited articles
Alter, R. E., Fan, Y., Lintner, B. R., and Weaver, C. P.: Observational
Evidence that Great Plains Irrigation Has Enhanced Summer Precipitation
Intensity and Totals in the Midwestern United States, J. Hydrometeorol.,
16, 1717–1735, https://doi.org/10.1175/jhm-d-14-0115.1, 2015.
Arheimer, B., Donnelly, C., and Lindström, G.: Regulation of snow-fed
rivers affects flow regimes more than climate change, Nat. Commun., 8, 62,
https://doi.org/10.1038/s41467-017-00092-8, 2017.
Bierkens, M. F. P. and van Beek, L. P. H.: Seasonal Predictability of
European Discharge: NAO and Hydrological Response Time, J. Hydrometeorol.,
10, 953–968, https://doi.org/10.1175/2009JHM1034.1, 2009.
Blöschl, G., Sivapalan, M., Wagener, T., Viglione, A., and Savenije, H.:
Runoff Prediction in Ungauged Basins: Synthesis Across Processes, Places and
Scales, Cambridge University Press, 2013.
Blöschl, G., Hall, J., Parajka, J., Perdigão, R. A. P., Merz, B.,
Arheimer, B., Aronica, G. T., Bilibashi, A., Bonacci, O., Borga, M.,
Čanjevac, I., Castellarin, A., Chirico, G. B., Claps, P., Fiala, K.,
Frolova, N., Gorbachova, L., Gül, A., Hannaford, J., Harrigan, S.,
Kireeva, M., Kiss, A., Kjeldsen, T. R., Kohnová, S., Koskela, J. J.,
Ledvinka, O., Macdonald, N., Mavrova-Guirguinova, M., Mediero, L., Merz, R.,
Molnar, P., Montanari, A., Murphy, C., Osuch, M., Ovcharuk, V., Radevski,
I., Rogger, M., Salinas, J. L., Sauquet, E., Šraj, M., Szolgay, J.,
Viglione, A., Volpi, E., Wilson, D., Zaimi, K., and Živković, N.:
Changing climate shifts timing of European floods, Science, 357,
588–590, https://doi.org/10.1126/science.aan2506, 2017.
Bouwer, L. M., Vermaat, J. E., and Aerts, J. C. J. H.: Winter atmospheric
circulation and river discharge in northwest Europe, Geophys. Res. Lett.,
33, 2–5, https://doi.org/10.1029/2005GL025548, 2006.
Breiman, L.: Random forests, Mach. Learn., 45, 5–32,
https://doi.org/10.1023/A:1010933404324, 2001.
Breiman, L., Friedman, J., Stone, C. J., and Olshen, R. A.: Classification
and regression trees, Chapman and Hall, 1984.
Caillouet, L., Vidal, J.-P., Sauquet, E., Devers, A., and Graff, B.: Ensemble reconstruction of spatio-temporal extreme low-flow events in France since 1871, Hydrol. Earth Syst. Sci., 21, 2923–2951, https://doi.org/10.5194/hess-21-2923-2017, 2017.
Castello, L. and Macedo, M. N.: Large-scale degradation of Amazonian
freshwater ecosystems, Glob. Change Biol., 22, 990–1007,
https://doi.org/10.1111/gcb.13173, 2016.
Chen, J. and Gupta, A. K.: Parametric statistical change point analysis,
Birkhäuser Boston, 2012.
Clark, E. A., Sheffield, J., van Vliet, M. T. H., Nijssen, B., and
Lettenmaier, D. P.: Continental Runoff into the Oceans (1950–2008), J.
Hydrometeorol., 16, 1502–1520, https://doi.org/10.1175/JHM-D-14-0183.1, 2015.
Compo, G. P., Whitaker, J. S., Sardeshmukh, P. D., Matsui, N., Allan, R. J.,
Yin, X., Gleason, B. E., Vose, R. S., Rutledge, G., Bessemoulin, P.,
BroNnimann, S., Brunet, M., Crouthamel, R. I., Grant, A. N., Groisman, P.
Y., Jones, P. D., Kruk, M. C., Kruger, A. C., Marshall, G. J., Maugeri, M.,
Mok, H. Y., Nordli, O., Ross, T. F., Trigo, R. M., Wang, X. L., Woodruff, S.
D., and Worley, S. J.: The Twentieth Century Reanalysis Project, Q. J. Roy.
Meteor. Soc., 137, 1–28, https://doi.org/10.1002/qj.776, 2011.
Cook, B. I., Miller, R. L., and Seager, R.: Amplification of the North
American “Dust Bowl” drought through human-induced land degradation, P.
Natl. Acad. Sci. USA, 106, 4997–5001, https://doi.org/10.1073/pnas.0810200106, 2009.
Cook, B. I., Seager, R., and Smerdon, J. E.: The worst North American drought
year of the last millennium: 1934, Geophys. Res. Lett., 41, 7298–7305,
https://doi.org/10.1002/2014GL061661, 2014.
Cook, E. R., Anchukaitis, K. J., Jacoby, G. C., Wright, W. E., Buckley, B.
M., and D'Arrigo, R. D.: Asian Monsoon Failure and Megadrought During the
Last Millennium, Science, 328, 486–489, https://doi.org/10.1126/science.1185188,
2010a.
Cook, E. R., Seager, R., Heim, R. R., Vose, R. S., Herweijer, C., and
Woodhouse, C.: Megadroughts in North America: Placing IPCC projections of
hydroclimatic change in a long-term palaeoclimate context, J. Quaternary Sci.,
25, 48–61, https://doi.org/10.1002/jqs.1303, 2010b.
Cook, E. R., Seager, R., Kushnir, Y., Briffa, K. R., Büntgen, U., Frank,
D., Krusic, P. J., Tegel, W., van der Schrier, G., Andreu-Hayles, L.,
Baillie, M., Baittinger, C., Bleicher, N., Bonde, N., Brown, D., Carrer, M.,
Cooper, R., Čufar, K., Dittmar, C., Esper, J., Griggs, C., Gunnarson,
B., Günther, B., Gutierrez, E., Haneca, K., Helama, S., Herzig, F.,
Heussner, K.-U., Hofmann, J., Janda, P., Kontic, R., Köse, N., Kyncl,
T., Levanič, T., Linderholm, H., Manning, S., Melvin, T. M., Miles, D.,
Neuwirth, B., Nicolussi, K., Nola, P., Panayotov, M., Popa, I., Rothe, A.,
Seftigen, K., Seim, A., Svarva, H., Svoboda, M., Thun, T., Timonen, M.,
Touchan, R., Trotsiuk, V., Trouet, V., Walder, F., Wazny, T.,
Wilson, R., and Zang, C.: Old World megadroughts and pluvials during the
Common Era, Sci. Adv., 1, e1500561, https://doi.org/10.1126/sciadv.1500561, 2015.
Dai, A. and Trenberth, K. E.: Estimates of Freshwater Discharge from
Continents: Latitudinal and Seasonal Variations, J. Hydrometeorol., 3,
660–687, https://doi.org/10.1175/1525-7541(2002)003<0660:EOFDFC>2.0.CO;2, 2002.
D'Almeida, C., Vörösmarty, C. J., Hurtt, G. C., Marengo, J. A.,
Dingman, S. L., and Keim, B. D.: The effects of deforestation on the
hydrological cycle in Amazonia: A review on scale and resolution, Int. J.
Climatol., 27, 633–647, https://doi.org/10.1002/joc.1475, 2007.
Davin, E. L., de Noblet-Ducoudré, N., and Friedlingstein, P.: Impact of
land cover change on surface climate: Relevance of the radiative forcing
concept, Geophys. Res. Lett., 34, 1–5, https://doi.org/10.1029/2007GL029678, 2007.
DeAngelis, A., Dominguez, F., Fan, Y., Robock, A., Kustu, M. D., and
Robinson, D.: Evidence of enhanced precipitation due to irrigation over the
Great Plains of the United States, J. Geophys. Res.-Atmos., 115,
1–14, https://doi.org/10.1029/2010JD013892, 2010.
Dirmeyer, P. A.: A History and Review of the Global Soil Wetness Project
(GSWP), J. Hydrometeorol., 12, 729–749, https://doi.org/10.1175/JHM-D-10-05010.1,
2011.
Dirmeyer, P. A., Gao, X., Zhao, M., Guo, Z., Oki, T., and Hanasaki, N.:
GSWP-2: Multimodel analysis and implications for our perception of the land
surface, B. Am. Meteorol. Soc., 87, 1381–1397,
https://doi.org/10.1175/BAMS-87-10-1381, 2006.
Do, H. X., Gudmundsson, L., Leonard, M., and Westra, S.: The Global Streamflow Indices and Metadata Archive (GSIM) – Part 1: The production of a daily streamflow archive and metadata, Earth Syst. Sci. Data, 10, 765–785, https://doi.org/10.5194/essd-10-765-2018, 2018.
Döll, P., Kaspar, F., and Lehner, B.: A global hydrological model for
deriving water availability indicators: Model tuning and validation, J.
Hydrol., 270, 105–134, https://doi.org/10.1016/S0022-1694(02)00283-4, 2003.
Fekete, B. M. and Vörösmarty, C. J.: The current status of global
river discharge monitoring and potential new technologies complementing
traditional discharge measurements, IAHS Publ., 309, 129–136, 2007.
Fekete, B. M., Vörösmarty, C. J., and Grabs, W.: High-resolution
fields of global runoff combining observed river discharge and simulated
water balances, Global Biogeochem. Cy., 16, 15–1–15–10,
https://doi.org/10.1029/1999GB001254, 2002.
Fekete, B. M., Looser, U., Pietroniro, A., and Robarts, R. D.: Rationale for
Monitoring Discharge on the Ground, J. Hydrometeorol., 13, 1977–1986,
https://doi.org/10.1175/JHM-D-11-0126.1, 2012.
Fekete, B. M., Robarts, R. D., Kumagai, M., Nachtnebel, H. P., Odada, E., and
Zhulidov, A. V.: Time for in situ renaissance, Science, 349, 685–686,
https://doi.org/10.1126/science.aac7358, 2015.
Ghiggi, G.: Reconstruction of European monthly runoff and river flow from
1951 to 2015 using machine learning algorithms, Master Thesis, ETHZ, 2018.
Ghiggi, G., Seneviratne, S. I., Humphrey, V., and Gudmundsson, L.: GRUN:
Global Runoff Reconstruction, figshare, https://doi.org/10.6084/m9.figshare.9228176,
2019.
Gosling, S. N., Müller Schmied, H., Betts, R., Chang, J., Ciais, P.,
Dankers, R., Döll, P., Eisner, S., Flörke, M., Gerten, D.,
Grillakis, M., Hanasaki, N., Hagemann, S., Huang, M., Huang, Z., Jerez, S.,
Kim, H., Koutroulis, A., Leng, G., Liu, X., Masaki, Y., Montavez, P.,
Morfopoulos, C., Oki, T., Papadimitriou, L., Pokhrel, Y., Portmann, F. T.,
Orth, R., Ostberg, S., Satoh, Y., Seneviratne, S., Sommer, P., Stacke, T.,
Tang, Q., Tsanis, I., Wada, Y., Zhou, T., Büchner, M., Schewe, J., and
Zhao, F.: ISIMIP2a Simulation Data from Water (global) Sector, GFZ Data
Serv., https://doi.org/10.5880/PIK.2017.010, 2017.
Greve, P., Orlowsky, B., Mueller, B., Sheffield, J., Reichstein, M., and
Seneviratne, S. I.: Global assessment of trends in wetting and drying over
land, Nat. Geosci., 7, 716–721, https://doi.org/10.1038/NGEO2247, 2014.
Gudmundsson, L. and Seneviratne, S. I.: Towards observation-based gridded runoff estimates for Europe, Hydrol. Earth Syst. Sci., 19, 2859–2879, https://doi.org/10.5194/hess-19-2859-2015, 2015.
Gudmundsson, L. and Seneviratne, S. I.: Observation-based gridded runoff estimates for Europe (E-RUN version 1.1), Earth Syst. Sci. Data, 8, 279–295, https://doi.org/10.5194/essd-8-279-2016, 2016.
Gudmundsson, L., Tallaksen, L. M., Stahl, K., Clark, D. B., Dumont, E.,
Hagemann, S., Bertrand, N., Gerten, D., Heinke, J., Hanasaki, N., Voss, F.,
and Koirala, S.: Comparing Large-Scale Hydrological Model Simulations to
Observed Runoff Percentiles in Europe, J. Hydrometeorol., 13, 604–620,
https://doi.org/10.1175/JHM-D-11-083.1, 2012.
Gudmundsson, L., Seneviratne, S. I., and Zhang, X.: Anthropogenic climate
change detected in European renewable freshwater resources, Nat. Clim.
Change, 7, 813–816, https://doi.org/10.1038/nclimate3416, 2017.
Gudmundsson, L., Leonard, M., Do, H. X., Westra, S., and Seneviratne, S. I.:
Observed Trends in Global Indicators of Mean and Extreme Streamflow,
Geophys. Res. Lett., 46, 756–766, https://doi.org/10.1029/2018GL079725, 2018a.
Gudmundsson, L., Do, H. X., Leonard, M., and Westra, S.: The Global Streamflow Indices and Metadata Archive (GSIM) – Part 2: Quality control, time-series indices and homogeneity assessment, Earth Syst. Sci. Data, 10, 787–804, https://doi.org/10.5194/essd-10-787-2018, 2018b.
Haddeland, I., Clark, D. B., Franssen, W., Ludwig, F., Vöss,
F., Arnell, N. W., Bertrand, N., Best, M., Folwell, S., Gerten, D., Gomes,
S., Gosling, S. N., Hagemann, S., Hanasaki, N., Harding, R., Heinke, J.,
Kabat, P., Koirala, S., Oki, T., Polcher, J., Stacke, T., Viterbo, P.,
Weedon, G. P., and Yeh, P.: Multimodel Estimate of the Global Terrestrial
Water Balance: Setup and First Results, J. Hydrometeorol., 12, 869–884,
https://doi.org/10.1175/2011JHM1324.1, 2011.
Hall, J. and Blöschl, G.: Spatial patterns and characteristics of flood seasonality in Europe, Hydrol. Earth Syst. Sci., 22, 3883–3901, https://doi.org/10.5194/hess-22-3883-2018, 2018.
Harding, R., Best, M., Blyth, E., Hagemann, S., Kabat, P., Tallaksen, L. M.,
Warnaars, T., Wiberg, D., Weedon, G. P., van Lanen, H., Ludwig, F., and
Haddeland, I.: WATCH: Current Knowledge of the Terrestrial Global Water
Cycle, J. Hydrometeorol., 12, 1149–1156, https://doi.org/10.1175/JHM-D-11-024.1,
2011.
Hastie, T., Tibsharani, R., and Friedman, J. H.: The Elements of Statistical
Learning, 2nd Edn., Springer, New York, 2009.
Hegerl, G. C., Black, E., Allan, R. P., Ingram, W. J., Polson, D.,
Trenberth, K. E., Chadwick, R. S., Arkin, P. A., Sarojini, B. B., Becker,
A., Dai, A., Durack, P. J., Easterling, D., Fowler, H. J., Kendon, E. J.,
Huffman, G. J., Liu, C., Marsh, R., New, M., Osborn, T. J., Skliris, N.,
Stott, P. A., Vidale, P.-L., Wijffels, S. E., Wilcox, L. J., Willett, K. M.,
and Zhang, X.: Challenges in Quantifying Changes in the Global Water Cycle,
B. Am. Meteorol. Soc., 96, 1097–1115, https://doi.org/10.1175/BAMS-D-13-00212.1,
2015.
Hrachowitz, M., Savenije, H. H. G., Blöschl, G., McDonnell, J. J.,
Sivapalan, M., Pomeroy, J. W., Arheimer, B., Blume, T., Clark, M. P., Ehret,
U., Fenicia, F., Freer, J. E., Gelfan, A., Gupta, H. V., Hughes, D. A., Hut,
R. W., Montanari, A., Pande, S., Tetzlaff, D., Troch, P. A., Uhlenbrook, S.,
Wagener, T., Winsemius, H. C., Woods, R. A., Zehe, E., and Cudennec, C.: A
decade of Predictions in Ungauged Basins (PUB) – a review, Hydrolog. Sci. J.,
58, 1198–1255, https://doi.org/10.1080/02626667.2013.803183, 2013.
Humphrey, V., Gudmundsson, L., and Seneviratne, S. I.: Assessing Global Water
Storage Variability from GRACE: Trends, Seasonal Cycle, Subseasonal
Anomalies and Extremes, Surv. Geophys., 37, 357–395,
https://doi.org/10.1007/s10712-016-9367-1, 2016.
Humphrey, V., Zscheischler, J., Ciais, P., Gudmundsson, L., Sitch, S., and
Seneviratne, S. I.: Sensitivity of atmospheric CO2 growth rate to observed
changes in terrestrial water storage, Nature, 560, 628–631,
https://doi.org/10.1038/s41586-018-0424-4, 2018.
Ionita, M., Tallaksen, L. M., Kingston, D. G., Stagge, J. H., Laaha, G., Van Lanen, H. A. J., Scholz, P., Chelcea, S. M., and Haslinger, K.: The European 2015 drought from a climatological perspective, Hydrol. Earth Syst. Sci., 21, 1397–1419, https://doi.org/10.5194/hess-21-1397-2017, 2017.
Jahfer, S., Vinayachandran, P. N., and Nanjundiah, R. S.: Long-Term impact of
Amazon river runoff on northern hemispheric climate, Nat. Sci. Rep., 7, 10989, https://doi.org/10.1038/s41598-017-10750-y, 2017.
Jaramillo, F. and Destouni, G.: Local flow regulation and irrigation raise
global human water consumption and footprint, Science, 350,
1248–1251, https://doi.org/10.1126/science.aad1010, 2015.
Kidane, A.: Mortality estimates of the 1984-85 Ethiopian famine, Scand. J.
Soc. Med., 18, 281–286, https://doi.org/10.1177/140349489001800409, 1990.
Kim, H., Watanabe, S., Chang, E. C., Yoshimura, K., Hirabayashi, J.,
Famiglietti, J., and Oki, T.: Global Soil Wetness Project Phase 3 Atmospheric
Boundary Conditions (Experiment 1) [Data set], Data Integration and Analysis
System (DIAS), https://doi.org/10.20783/DIAS.501, 2017.
Kummu, M., Guillaume, J. H. A., de Moel, H., Eisner, S., Flörke, M.,
Porkka, M., Siebert, S., Veldkamp, T. I. E., and Ward, P. J.: The world's
road to water scarcity: shortage and stress in the 20th century and pathways
towards sustainability, Nat. Sci. Rep., 6, 38495, https://doi.org/10.1038/srep38495,
2016.
Lanckriet, S., Frankl, A., Adgo, E., Termonia, P., and Nyssen, J.: Droughts
related to quasi-global oscillations: A diagnostic teleconnection analysis
in North Ethiopia, Int. J. Climatol., 35, 1534–1542,
https://doi.org/10.1002/joc.4074, 2015.
Latrubesse, E. M., Arima, E. Y., Dunne, T., Park, E., Baker, V. R., D'Horta,
F. M., Wight, C., Wittmann, F., Zuanon, J., Baker, P. A., Ribas, C. C.,
Norgaard, R. B., Filizola, N., Ansar, A., Flyvbjerg, B., and Stevaux, J. C.:
Damming the rivers of the Amazon basin, Nature, 546, 363–369,
https://doi.org/10.1038/nature22333, 2017.
Laudon, H., Spence, C., Buttle, J., Carey, S. K., McDonnell, J. J.,
McNamara, J. P., Soulsby, C., and Tetzlaff, D.: Save northern high-latitude
catchments, Nat. Geosci., 10, 324–325, https://doi.org/10.1038/ngeo2947, 2017.
Lawrence, D. and Vandecar, K.: Effects of tropical deforestation on climate
and agriculture, Nat. Clim. Change, 5, 27–36, https://doi.org/10.1038/nclimate2430,
2015.
Lorenzo-Lacruz, J., Vicente-Serrano, S. M., López-Moreno, J. I., González-Hidalgo, J. C., and Morán-Tejeda, E.: The response of Iberian rivers to the North Atlantic Oscillation, Hydrol. Earth Syst. Sci., 15, 2581–2597, https://doi.org/10.5194/hess-15-2581-2011, 2011.
Luyssaert, S., Jammet, M., Stoy, P. C., Estel, S., Pongratz, J., Ceschia,
E., Churkina, G., Don, A., Erb, K., Ferlicoq, M., Gielen, B., Grünwald,
T., Houghton, R. A., Klumpp, K., Knohl, A., Kolb, T., Kuemmerle, T.,
Laurila, T., Lohila, A., Loustau, D., McGrath, M. J., Meyfroidt, P., Moors,
E. J., Naudts, K., Novick, K., Otto, J., Pilegaard, K., Pio, C. A., Rambal,
S., Rebmann, C., Ryder, J., Suyker, A. E., Varlagin, A., Wattenbach, M., and
Dolman, A. J.: Land management and land-cover change have impacts of similar
magnitude on surface temperature, Nat. Clim. Change, 4, 389–393,
https://doi.org/10.1038/nclimate2196, 2014.
Materia, S., Gualdi, S., Navarra, A., and Terray, L.: The effect of Congo
River freshwater discharge on Eastern Equatorial Atlantic climate
variability, Clim. Dynam., 39, 2109–2125,
https://doi.org/10.1007/s00382-012-1514-x, 2012.
Meko, D. M., Woodhouse, C. A., and Morino, K.: Dendrochronology and links to
streamflow, J. Hydrol., 412–413, 200–209,
https://doi.org/10.1016/j.jhydrol.2010.11.041, 2012.
Mekonnen, M. and Hoekstra, Y. A.: Four Billion People Experience Water
Scarcity, Sci. Adv., 2, 1–7, https://doi.org/10.1126/sciadv.1500323, 2016.
Meyer, H., Reudenbach, C., Hengl, T., Katurji, M., and Nauss, T.: Improving
performance of spatio-temporal machine learning models using forward feature
selection and target-oriented validation, Environ. Model. Softw., 101, 1–9,
https://doi.org/10.1016/j.envsoft.2017.12.001, 2018.
Mishra, V., Shah, R., Azhar, S., Shah, H., Modi, P., and Kumar, R.: Reconstruction of droughts in India using multiple land-surface models (1951–2015), Hydrol. Earth Syst. Sci., 22, 2269–2284, https://doi.org/10.5194/hess-22-2269-2018, 2018.
Montanari, A., Young, G., Savenije, H. H. G., Hughes, D., Wagener, T., Ren,
L. L., Koutsoyiannis, D., Cudennec, C., Toth, E., Grimaldi, S., Blöschl,
G., Sivapalan, M., Beven, K., Gupta, H., Hipsey, M., Schaefli, B., Arheimer,
B., Boegh, E., Schymanski, S. J., Di Baldassarre, G., Yu, B., Hubert, P.,
Huang, Y., Schumann, A., Post, D. A., Srinivasan, V., Harman, C., Thompson,
S., Rogger, M., Viglione, A., McMillan, H., Characklis, G., Pang, Z., and
Belyaev, V.: “Panta Rhei-Everything Flows”: Change in hydrology and
society-The IAHS Scientific Decade 2013–2022, Hydrolog. Sci. J., 58,
1256–1275, https://doi.org/10.1080/02626667.2013.809088, 2013.
Moravec, V., Markonis, Y., Rakovec, O., Kumar, R., and Hanel, M.: A 250-year
European drought inventory derived from ensemble hydrologic modelling,
Geophys. Res. Lett., 46, 5909–5917, https://doi.org/10.1029/2019gl082783, 2019.
Müller Schmied, H., Adam, L., Eisner, S., Fink, G., Flörke, M., Kim, H., Oki, T., Portmann, F. T., Reinecke, R., Riedel, C., Song, Q., Zhang, J., and Döll, P.: Variations of global and continental water balance components as impacted by climate forcing uncertainty and human water use, Hydrol. Earth Syst. Sci., 20, 2877–2898, https://doi.org/10.5194/hess-20-2877-2016, 2016.
Munia, H. A., Guillaume, J. H. A., Mirumachi, N., Wada, Y., and Kummu, M.: How downstream sub-basins depend on upstream inflows to avoid scarcity: typology and global analysis of transboundary rivers, Hydrol. Earth Syst. Sci., 22, 2795–2809, https://doi.org/10.5194/hess-22-2795-2018, 2018.
Nash, J. E. and Sutcliffe, J. V.: River flow forecasting through conceptual
models part I – A discussion of principles, J. Hydrol., 10, 282–290,
https://doi.org/10.1016/0022-1694(70)90255-6, 1970.
Nicault, A., Alleaume, S., Brewer, S., Carrer, M., Nola, P., and Guiot, J.:
Mediterranean drought fluctuation during the last 500 years based on
tree-ring data, Clim. Dynam., 31, 227–245,
https://doi.org/10.1007/s00382-007-0349-3, 2008.
Oki, T. and Kanae, S.: Global Hydrological Cycles and Word Water Resources,
Science, 313, 1068–1072, https://doi.org/10.1126/science.1128845, 2006.
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.
Rodell, M., Beaudoing, H. K., L'Ecuyer, T. S., Olson, W. S., Famiglietti, J.
S., Houser, P. R., Adler, R., Bosilovich, M. G., Clayson, C. A., Chambers,
D., Clark, E., Fetzer, E. J., Gao, X., Gu, G., Hilburn, K., Huffman, G. J.,
Lettenmaier, D. P., Liu, W. T., Robertson, F. R., Schlosser, C. A.,
Sheffield, J., and Wood, E. F.: The observed state of the water cycle in the
early twenty-first century, J. Climate, 28, 8289–8318,
https://doi.org/10.1175/JCLI-D-14-00555.1, 2015.
Samaniego, L., Kumar, R., and Attinger, S.: Multiscale parameter
regionalization of a grid-based hydrologic model at the mesoscale, Water Resour. Res., 46, W05523, https://doi.org/10.1029/2008WR007327, 2010.
Samaniego, L., Kumar, R., Thober, S., Rakovec, O., Zink, M., Wanders, N., Eisner, S., Müller Schmied, H., Sutanudjaja, E. H., Warrach-Sagi, K., and Attinger, S.: Toward seamless hydrologic predictions across spatial scales, Hydrol. Earth Syst. Sci., 21, 4323–4346, https://doi.org/10.5194/hess-21-4323-2017, 2017.
Schellekens, J., Dutra, E., Martínez-de la Torre, A., Balsamo, G., van Dijk, A., Sperna Weiland, F., Minvielle, M., Calvet, J.-C., Decharme, B., Eisner, S., Fink, G., Flörke, M., Peßenteiner, S., van Beek, R., Polcher, J., Beck, H., Orth, R., Calton, B., Burke, S., Dorigo, W., and Weedon, G. P.: A global water resources ensemble of hydrological models: the eartH2Observe Tier-1 dataset, Earth Syst. Sci. Data, 9, 389–413, https://doi.org/10.5194/essd-9-389-2017, 2017.
Schneider, T., Bischoff, T., and Haug, G. H.: Migrations and dynamics of the
intertropical convergence zone, Nature, 513, 45–53,
https://doi.org/10.1038/nature13636, 2014.
Schubert, S. D., Suarez, M. J., Pegion, P. J., Koster, R. D., and Bacmeister,
T.: On the Cause of the 1930s Dust Bowl, Science, 303, 1855–1859,
https://doi.org/10.1126/science.1095048, 2004.
Sen, P. K.: Estimates of the Regression Coefficient Based on Kendall's Tau,
J. Am. Stat. Assoc., 63, 1379–1389,
https://doi.org/10.1080/01621459.1968.10480934, 1968.
Seneviratne, S. I., Nicholls, N., Easterling, D., Goodess, C. M., Kanae, S.,
Kossin, J., Luo, Y., Marengo, J., Mc Innes, K., Rahimi, M., Reichstein, M.,
Sorteberg, A., Vera, C., Zhang, X., Rusticucci, M., Semenov, V., Alexander,
L. V., Allen, S., Benito, G., Cavazos, T., Clague, J., Conway, D.,
Della-Marta, P. M., Gerber, M., Gong, S., Goswami, B. N., Hemer, M., Huggel,
C., Van den Hurk, B., Kharin, V. V., Kitoh, A., Klein Tank, A. M. G., Li,
G., Mason, S., Mc Guire, W., Van Oldenborgh, G. J., Orlowsky, B., Smith, S.,
Thiaw, W., Velegrakis, A., Yiou, P., Zhang, T., Zhou, T., and Zwiers, F. W.:
Changes in climate extremes and their impacts on the natural physical
environment, in Managing the Risks of Extreme Events and Disasters to
Advance Climate Change Adaptation: Special Report of the Intergovernmental
Panel on Climate Change, Cambridge University
Press, 109–230, 2012.
Shiklomanov, A. I., Lammers, R. B., and Vörösmarty, C. J.: Widespread
decline in hydrological monitoring threatens Pan-Arctic research, Eos,
83, 13–17, https://doi.org/10.1029/2002EO000007, 2002.
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.
Sivapalan, M.: Prediction in ungauged basins: a grand challenge for
theoretical hydrology, Hydrol. Process., 17, 3163–3170,
https://doi.org/10.1002/hyp.5155, 2003.
Smith, K. A., Barker, L. J., Tanguy, M., Parry, S., Harrigan, S., Legg, T. P., Prudhomme, C., and Hannaford, J.: A multi-objective ensemble approach to hydrological modelling in the UK: an application to historic drought reconstruction, Hydrol. Earth Syst. Sci., 23, 3247–3268, https://doi.org/10.5194/hess-23-3247-2019, 2019.
Spinoni, J., Naumann, G., Vogt, J. V., and Barbosa, P.: The biggest drought
events in Europe from 1950 to 2012, J. Hydrol. Reg. Stud., 3, 509–524,
https://doi.org/10.1016/j.ejrh.2015.01.001, 2015.
Spracklen, D. V. and Garcia-Carreras, L.: The impact of Amazonian
deforestation on Amazon basin rainfall, Geophys. Res. Lett., 42,
9546–9552, https://doi.org/10.1002/2015GL066063, 2015.
Spracklen, D. V., Arnold, S. R., and Taylor, C. M.: Observations of increased
tropical rainfall preceded by air passage over forests, Nature, 489,
282–285, https://doi.org/10.1038/nature11390, 2012.
Stahl, K., Hisdal, H., Hannaford, J., Tallaksen, L. M., van Lanen, H. A. J., Sauquet, E., Demuth, S., Fendekova, M., and Jódar, J.: Streamflow trends in Europe: evidence from a dataset of near-natural catchments, Hydrol. Earth Syst. Sci., 14, 2367–2382, https://doi.org/10.5194/hess-14-2367-2010, 2010.
Stahl, K., Tallaksen, L. M., Hannaford, J., and van Lanen, H. A. J.: Filling the white space on maps of European runoff trends: estimates from a multi-model ensemble, Hydrol. Earth Syst. Sci., 16, 2035–2047, https://doi.org/10.5194/hess-16-2035-2012, 2012.
Steirou, E., Gerlitz, L., Apel, H., and Merz, B.: Links between large-scale
circulation patterns and streamflow in Central Europe: A review, J. Hydrolog.,
549, 484–500, https://doi.org/10.1016/j.jhydrol.2017.04.003, 2017.
Syed, T. H., Famiglietti, J. S., and Chambers, D. P.: GRACE-Based Estimates
of Terrestrial Freshwater Discharge from Basin to Continental Scales, J.
Hydrometeorol., 10, 22–40, https://doi.org/10.1175/2008JHM993.1, 2009.
Tang, T., Li, W., and Sun, G.: Impact of two different types of El Niño events on runoff over the conterminous United States, Hydrol. Earth Syst. Sci., 20, 27–37, https://doi.org/10.5194/hess-20-27-2016, 2016.
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., 122, 1403–1422, https://doi.org/10.1002/2016JD025740, 2017.
Trenberth, K. E. and Asrar, G. R.: Challenges and Opportunities in Water
Cycle Research: WCRP Contributions, Surv. Geophys., 35, 515–532,
https://doi.org/10.1007/s10712-012-9214-y, 2014.
Van Den Hurk, B., Best, M., Dirmeyer, P., Pitman, A., Polcher, J., and
Santanello, J.: Acceleration of land surface model development over a decade
of glass, B. Am. Meteorol. Soc., 92, 1593–1600,
https://doi.org/10.1175/BAMS-D-11-00007.1, 2011.
van den Hurk, B., Kim, H., Krinner, G., Seneviratne, S. I., Derksen, C., Oki, T., Douville, H., Colin, J., Ducharne, A., Cheruy, F., Viovy, N., Puma, M. J., Wada, Y., Li, W., Jia, B., Alessandri, A., Lawrence, D. M., Weedon, G. P., Ellis, R., Hagemann, S., Mao, J., Flanner, M. G., Zampieri, M., Materia, S., Law, R. M., and Sheffield, J.: LS3MIP (v1.0) contribution to CMIP6: the Land Surface, Snow and Soil moisture Model Intercomparison Project – aims, setup and expected outcome, Geosci. Model Dev., 9, 2809–2832, https://doi.org/10.5194/gmd-9-2809-2016, 2016.
Veldkamp, T. I. E., Wada, Y., Aerts, J. C. J. H., Döll, P., Gosling, S.
N., Liu, J., Masaki, Y., Oki, T., Ostberg, S., Pokhrel, Y., Satoh, Y., Kim,
H., and Ward, P. J.: Water scarcity hotspots travel downstream due to human
interventions in the 20th and 21st century, Nat. Commun., 8, 15697,
https://doi.org/10.1038/ncomms15697, 2017.
Viste, E., Korecha, D., and Sorteberg, A.: Recent drought and precipitation
tendencies in Ethiopia, Theor. Appl. Climatol., 112, 535–551,
https://doi.org/10.1007/s00704-012-0746-3, 2013.
Vizy, E. K. and Cook, K. H.: Influence of the Amazon/Orinoco Plume on the
summertime Atlantic climate, J. Geophys. Res.-Atmos., 115, 1–18,
https://doi.org/10.1029/2010JD014049, 2010.
Vörösmarty, C. J., Green, P., Salisbury, J., and Lammers, R.: Global
water resources: vulnerability from climate change and population growth,
Science, 289, 284–288, https://doi.org/10.1126/science.289.5477.284, 2000.
Vörösmarty, C. J., Lettenmaier, D., Levêque, C., Meybeck, M.,
Pahl-Wostl, C., Alcamo, J., Cosgrove, W., Grassl, H., Hoff, H., Kabat, P.,
Lansigan, F., Lawford, R., and Naiman, R.: Human transforming the Global
Water System, Eos, 85, 509–520, https://doi.org/10.1029/2004EO480001, 2004.
Vörösmarty, C. J., McIntyre, P. B., Gessner, M. O., Dudgeon, D.,
Prusevich, A., Green, P., Glidden, S., Bunn, S. E., Sullivan, C. A.,
Liermann, C. R., and Davies, P. M.: Global threats to human water security
and river biodiversity, Nature, 467, 555–561,
https://doi.org/10.1038/nature09440, 2010.
Wagener, T., Sivapalan, M., Troch, P. A., McGlynn, B. L., Harman, C. J.,
Gupta, H. V., Kumar, P., Rao, P. S. C., Basu, N. B., and Wilson, J. S.: The
future of hydrology: An evolving science for a changing world, Water Resour.
Res., 46, 1–10, https://doi.org/10.1029/2009WR008906, 2010.
Wanders, N. and Wada, Y.: Decadal predictability of river discharge with
climate oscillations over the 20th and early 21st century, Geophys. Res.
Lett., 42, 10689–10695, https://doi.org/10.1002/2015GL066929, 2015.
Wang, A., Bohn, T. J., Mahanama, S. P., Koster, R. D., and Lettenmaier, D.
P.: Multimodel ensemble reconstruction of drought over the continental
United States, J. Climate, 22, 2694–2712, https://doi.org/10.1175/2008JCLI2586.1,
2009.
Ward, P. J., Beets, W., Bouwer, L. M., Aerts, J. C. J. H., and Renssen, H.:
Sensitivity of river discharge to ENSO, Geophys. Res. Lett., 37, L12402,
https://doi.org/10.1029/2010GL043215, 2010.
Warszawski, L., Frieler, K., Huber, V., Piontek, F., Serdeczny, O., and
Schewe, J.: The Inter-Sectoral Impact Model Intercomparison Project
(ISI–MIP): Project framework, P. Natl. Acad. Sci. USA, 111, 3228–3232,
https://doi.org/10.1073/pnas.1312330110, 2014.
WEF: The Global Risks Report 2018, available at:
http://reports.weforum.org/global-risks-2018/, last access: 25 November 2018.
Wisser, D., Fekete, B. M., Vörösmarty, C. J., and Schumann, A. H.: Reconstructing 20th century global hydrography: a contribution to the Global Terrestrial Network- Hydrology (GTN-H), Hydrol. Earth Syst. Sci., 14, 1–24, https://doi.org/10.5194/hess-14-1-2010, 2010.
Wolter, K. and Timlin, M. S.: El Niño/Southern Oscillation behaviour
since 1871 as diagnosed in an extended multivariate ENSO index (MEI.ext),
Int. J. Climatol., 31, 1074–1087, https://doi.org/10.1002/joc.2336, 2011.
Wriedt, G., van der Velde, M., Aloe, A., and Bouraoui, F.: A European
irrigation map for spatially distributed agricultural modelling, Agr.
Water Manage., 96, 771–789, https://doi.org/10.1016/j.agwat.2008.10.012, 2009.
Wu, Z. Y., Lu, G. H., Wen, L., and Lin, C. A.: Reconstructing and analyzing China's fifty-nine year (1951–2009) drought history using hydrological model simulation, Hydrol. Earth Syst. Sci., 15, 2881–2894, https://doi.org/10.5194/hess-15-2881-2011, 2011.
Zaidman, M. D., Rees, H. G., and Young, A. R.: Spatio-temporal development of streamflow droughts in north-west Europe, Hydrol. Earth Syst. Sci., 6, 733–751, https://doi.org/10.5194/hess-6-733-2002, 2002.
Short summary
Freshwater resources are of high societal relevance and understanding their past variability is vital to water management in the context of current and future climatic change. This study introduces GRUN: the first global gridded monthly reconstruction of runoff covering the period from 1902 to 2014. The dataset agrees on average much better with the streamflow observations than an ensemble of 13 state-of-the-art global hydrological models and will foster the understanding of freshwater dynamics.
Freshwater resources are of high societal relevance and understanding their past variability is...
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