Articles | Volume 13, issue 12
Data description paper 03 Dec 2021
Data description paper | 03 Dec 2021
CCAM: China Catchment Attributes and Meteorology dataset
Zhen Hao et al.
Related subject area
Hydrology and Soil Science – HydrologyA high-accuracy rainfall dataset by merging multiple satellites and dense gauges over the southern Tibetan Plateau for 2014–2019 warm seasonsBaseline data for monitoring geomorphological effects of glacier lake outburst flood: a very-high-resolution image and GIS datasets of the distal part of the Zackenberg River, northeast GreenlandMineral, thermal and deep groundwater of Hesse, GermanyLamaH-CE: LArge-SaMple DAta for Hydrology and Environmental Sciences for Central EuropeDevelopment of observation-based global multilayer soil moisture products for 1970 to 2016A year of attenuation data from a commercial dual-polarized duplex microwave link with concurrent disdrometer, rain gauge, and weather observationsRosalia: an experimental research site to study hydrological processes in a forest catchmentLong time series of daily evapotranspiration in China based on the SEBAL model and multisource images and validationCAMELS-AUS: hydrometeorological time series and landscape attributes for 222 catchments in AustraliaA multi-source 120-year US flood database with a unified common format and public accessC-band radar data and in situ measurements for the monitoring of wheat crops in a semi-arid area (center of Morocco)The three-dimensional groundwater salinity distribution and fresh groundwater volumes in the Mekong Delta, Vietnam, inferred from geostatistical analysesA national topographic dataset for hydrological modeling over the contiguous United StatesStatus of the Tibetan Plateau observatory (Tibet-Obs) and a 10-year (2009–2019) surface soil moisture datasetCLIGEN parameter regionalization for mainland ChinaYear-long, broad-band, microwave backscatter observations of an alpine meadow over the Tibetan Plateau with a ground-based scatterometerSTH-net: a soil monitoring network for process-based hydrological modelling from the pedon to the hillslope scaleComprehensive bathymetry and intertidal topography of the Amazon estuaryVirtual water trade and water footprint of agricultural goods: the 1961–2016 CWASI databaseHistorical cartographic and topo-bathymetric database on the French Rhône River (17th–20th century)COSMOS-UK: national soil moisture and hydrometeorology data for environmental science researchSoilKsatDB: global database of soil saturated hydraulic conductivity measurements for geoscience applicationsADHI: the African Database of Hydrometric Indices (1950–2018)Dynamics of shallow wakes on gravel-bed floodplains: dataset from field experimentsTwo decades of distributed global radiation time series across a mountainous semiarid area (Sierra Nevada, Spain)Inventory of dams in GermanyCountry-level and gridded estimates of wastewater production, collection, treatment and reuseDataset of Georeferenced Dams in South America (DDSA)The impact of landscape evolution on soil physics: evolution of soil physical and hydraulic properties along two chronosequences of proglacial morainesThe CH-IRP data set: a decade of fortnightly data on δ2H and δ18O in streamflow and precipitation in SwitzerlandCAMELS-GB: hydrometeorological time series and landscape attributes for 671 catchments in Great BritainA dense network of cosmic-ray neutron sensors for soil moisture observation in a highly instrumented pre-Alpine headwater catchment in GermanyCAMELS-BR: hydrometeorological time series and landscape attributes for 897 catchments in BrazilGloFAS-ERA5 operational global river discharge reanalysis 1979–presentA Canadian River Ice Database from the National Hydrometric Program ArchivesAn integration of gauge, satellite, and reanalysis precipitation datasets for the largest river basin of the Tibetan PlateauTowards harmonisation of image velocimetry techniques for river surface velocity observationsAIMERG: a new Asian precipitation dataset (0.1°/half-hourly, 2000–2015) by calibrating the GPM-era IMERG at a daily scale using APHRODITEVegetation, ground cover, soil, rainfall simulation, and overland-flow experiments before and after tree removal in woodland-encroached sagebrush steppe: the hydrology component of the Sagebrush Steppe Treatment Evaluation Project (SageSTEP)Satellite-based remote sensing data set of global surface water storage change from 1992 to 2018Data for wetlandscapes and their changes around the worldMeasurements of the water balance components of a large green roof in the greater Paris areaA distributed soil moisture, temperature and infiltrometer dataset for permeable pavements and green spacesA 439-year simulated daily discharge dataset (1861–2299) for the upper Yangtze River, ChinaRunoff reaction from extreme rainfall events on natural hillslopes: a data set from 132 large-scale sprinkling experiments in south-western GermanyPaleo-hydrologic reconstruction of 400 years of past flows at a weekly time step for major rivers of Western CanadaGlobal River Radar Altimetry Time Series (GRRATS): new river elevation earth science data records for the hydrologic communityAn Arctic watershed observatory at Lake Peters, Alaska: weather–glacier–river–lake system data for 2015–2018GRUN: an observation-based global gridded runoff dataset from 1902 to 2014SM2RAIN–ASCAT (2007–2018): global daily satellite rainfall data from ASCAT soil moisture observations
Kunbiao Li, Fuqiang Tian, Mohd Yawar Ali Khan, Ran Xu, Zhihua He, Long Yang, Hui Lu, and Yingzhao Ma
Earth Syst. Sci. Data, 13, 5455–5467,Short summary
Due to complex climate and topography, there is still a lack of a high-quality rainfall dataset for hydrological modeling over the Tibetan Plateau. This study aims to establish a high-accuracy daily rainfall product over the southern Tibetan Plateau through merging satellite rainfall estimates based on a high-density rainfall gauge network. Statistical and hydrological evaluation indicated that the new dataset outperforms the raw satellite estimates and several other products of similar types.
Aleksandra M. Tomczyk and Marek W. Ewertowski
Earth Syst. Sci. Data, 13, 5293–5309,Short summary
We collected detailed (cm-scale) topographical data to illustrate how a single flood event can modify river landscape in the high-Arctic setting of Zackenberg Valley, NE Greenland. The studied flood was a result of an outburst from a glacier-dammed lake. We used drones to capture images immediately before, during, and after the flood for the 2 km long section of the river. Data can be used for monitoring and modelling of flood events and assessment of geohazards for Zackenberg Research Station.
Rafael Schäffer, Kristian Bär, Sebastian Fischer, Johann-Gerhard Fritsche, and Ingo Sass
Earth Syst. Sci. Data, 13, 4847–4860,Short summary
Knowledge of groundwater properties is relevant, e.g. for drinking-water supply, spas or geothermal energy. We compiled 1035 groundwater datasets from 560 springs or wells sampled since 1810, using mainly publications, supplemented by personal communication and our own measurements. The data can help address spatial–temporal variation in groundwater composition, uncertainties in groundwater property prediction, deep groundwater movement, or groundwater characteristics like temperature and age.
Christoph Klingler, Karsten Schulz, and Mathew Herrnegger
Earth Syst. Sci. Data, 13, 4529–4565,Short summary
LamaH-CE is a large-sample catchment hydrology dataset for Central Europe. The dataset contains hydrometeorological time series (daily and hourly resolution) and various attributes for 859 gauged basins. Sticking closely to the CAMELS datasets, LamaH includes additional basin delineations and attributes for describing a large interconnected river network. LamaH further contains outputs of a conceptual hydrological baseline model for plausibility checking of the inputs and for benchmarking.
Yaoping Wang, Jiafu Mao, Mingzhou Jin, Forrest M. Hoffman, Xiaoying Shi, Stan D. Wullschleger, and Yongjiu Dai
Earth Syst. Sci. Data, 13, 4385–4405,Short summary
We developed seven global soil moisture datasets (1970–2016, monthly, half-degree, and multilayer) by merging a wide range of data sources, including in situ and satellite observations, reanalysis, offline land surface model simulations, and Earth system model simulations. Given the great value of long-term, multilayer, gap-free soil moisture products to climate research and applications, we believe this paper and the presented datasets would be of interest to many different communities.
Anna Špačková, Vojtěch Bareš, Martin Fencl, Marc Schleiss, Joël Jaffrain, Alexis Berne, and Jörg Rieckermann
Earth Syst. Sci. Data, 13, 4219–4240,Short summary
An original dataset of microwave signal attenuation and rainfall variables was collected during 1-year-long field campaign. The monitored 38 GHz dual-polarized commercial microwave link with a short sampling resolution (4 s) was accompanied by five disdrometers and three rain gauges along its path. Antenna radomes were temporarily shielded for approximately half of the campaign period to investigate antenna wetting impacts.
Josef Fürst, Hans Peter Nachtnebel, Josef Gasch, Reinhard Nolz, Michael Paul Stockinger, Christine Stumpp, and Karsten Schulz
Earth Syst. Sci. Data, 13, 4019–4034,Short summary
Rosalia is a 222 ha forested research watershed in eastern Austria to study water, energy and solute transport processes. The paper describes the site, monitoring network, instrumentation and the datasets: high-resolution (10 min interval) time series starting in 2015 of four discharge gauging stations, seven rain gauges, and observations of air and water temperature, relative humidity, and conductivity, as well as soil water content and temperature, at different depths at four profiles.
Minghan Cheng, Xiyun Jiao, Binbin Li, Xun Yu, Mingchao Shao, and Xiuliang Jin
Earth Syst. Sci. Data, 13, 3995–4017,Short summary
Evapotranspiration (ET) is a key node linking surface water and energy balance. Satellite observations of ET have been widely used for water resources management in China. In this study, an ET product with high spatiotemporal resolution was generated using a surface energy balance algorithm and multisource remote sensing data. The generated ET product can be used for geoscience studies, especially global change, water resources management, and agricultural drought monitoring, for example.
Keirnan J. A. Fowler, Suwash Chandra Acharya, Nans Addor, Chihchung Chou, and Murray C. Peel
Earth Syst. Sci. Data, 13, 3847–3867,Short summary
This paper presents the Australian edition of the Catchment Attributes and Meteorology for Large-sample Studies (CAMELS) series of datasets. CAMELS-AUS comprises data for 222 unregulated catchments with long-term monitoring, combining hydrometeorological time series (streamflow and 18 climatic variables) with 134 attributes related to geology, soil, topography, land cover, anthropogenic influence and hydroclimatology. It is freely downloadable from https://doi.pangaea.de/10.1594/PANGAEA.921850.
Zhi Li, Mengye Chen, Shang Gao, Jonathan J. Gourley, Tiantian Yang, Xinyi Shen, Randall Kolar, and Yang Hong
Earth Syst. Sci. Data, 13, 3755–3766,Short summary
This dataset is a compilation of multi-sourced flood records, retrieved from official reports, instruments, and crowdsourcing data since 1900. This study utilizes the flood database to analyze flood seasonality within major basins and socioeconomic impacts over time. It is anticipated that this dataset can support a variety of flood-related research, such as validation resources for hydrologic models, hydroclimatic studies, and flood vulnerability analysis across the United States.
Nadia Ouaadi, Jamal Ezzahar, Saïd Khabba, Salah Er-Raki, Adnane Chakir, Bouchra Ait Hssaine, Valérie Le Dantec, Zoubair Rafi, Antoine Beaumont, Mohamed Kasbani, and Lionel Jarlan
Earth Syst. Sci. Data, 13, 3707–3731,Short summary
In this paper, a radar remote sensing database composed of processed Sentinel-1 products and field measurements of soil and vegetation characteristics, weather data, and irrigation water inputs is described. The data set was collected over 3 years (2016–2019) in three drip-irrigated wheat fields in the center of Morocco. It is dedicated to radar data analysis over vegetated surface including the retrieval of soil and vegetation characteristics.
Jan L. Gunnink, Hung Van Pham, Gualbert H. P. Oude Essink, and Marc F. P. Bierkens
Earth Syst. Sci. Data, 13, 3297–3319,Short summary
In the Mekong Delta (Vietnam) groundwater is important for domestic, agricultural and industrial use. Increased pumping of groundwater has caused land subsidence and increased the risk of salinization, thereby endangering the livelihood of the population in the delta. We made a model of the salinity of the groundwater by integrating different sources of information and determined fresh groundwater volumes. The resulting model can be used by researchers and policymakers.
Jun Zhang, Laura E. Condon, Hoang Tran, and Reed M. Maxwell
Earth Syst. Sci. Data, 13, 3263–3279,Short summary
Existing national topographic datasets for the US may not be compatible with gridded hydrologic models. A national topographic dataset developed to support physically based hydrologic models at 1 km and 250 m over the contiguous US is provided. We used a Priority Flood algorithm to ensure hydrologically consistent drainage networks and evaluated the performance with an integrated hydrologic model. Datasets and scripts are available for direct data usage or modification of processing as desired.
Pei Zhang, Donghai Zheng, Rogier van der Velde, Jun Wen, Yijian Zeng, Xin Wang, Zuoliang Wang, Jiali Chen, and Zhongbo Su
Earth Syst. Sci. Data, 13, 3075–3102,Short summary
This paper reports on the status of the Tibet-Obs and presents a 10-year (2009–2019) surface soil moisture (SM) dataset produced based on in situ measurements taken at a depth of 5 cm collected from the Tibet-Obs. This surface SM dataset includes the original 15 min in situ measurements collected by multiple SM monitoring sites of three networks (i.e. the Maqu, Naqu, and Ngari networks) and the spatially upscaled SM records produced for the Maqu and Shiquanhe networks.
Wenting Wang, Shuiqing Yin, Bofu Yu, and Shaodong Wang
Earth Syst. Sci. Data, 13, 2945–2962,Short summary
A gridded input dataset at a 10 km resolution of a weather generator, CLIGEN, was established for mainland China. Based on this, CLIGEN can generate a series of daily temperature, solar radiation, precipitation data, and rainfall intensity information. In each grid, the input file contains 13 groups of parameters. All parameters were first calculated based on long-term observations and then interpolated by universal kriging. The accuracy of the gridded input dataset has been fully assessed.
Jan G. Hofste, Rogier van der Velde, Jun Wen, Xin Wang, Zuoliang Wang, Donghai Zheng, Christiaan van der Tol, and Zhongbo Su
Earth Syst. Sci. Data, 13, 2819–2856,Short summary
The dataset reported in this paper concerns the measurement of microwave reflections from an alpine meadow over the Tibetan Plateau. These microwave reflections were measured continuously over 1 year. With it, variations in soil water content due to evaporation, precipitation, drainage, and soil freezing/thawing can be seen. A better understanding of the effects aforementioned processes have on microwave reflections may improve methods for estimating soil water content used by satellites.
Edoardo Martini, Matteo Bauckholt, Simon Kögler, Manuel Kreck, Kurt Roth, Ulrike Werban, Ute Wollschläger, and Steffen Zacharias
Earth Syst. Sci. Data, 13, 2529–2539,Short summary
We present the in situ data available from the soil monitoring network
STH-net, recently implemented at the Schäfertal Hillslope site (Germany). The STH-net provides data (soil water content, soil temperature, water level, and meteorological variables – measured at a 10 min interval since 1 January 2019) for developing and testing modelling approaches in the context of vadose zone hydrology at spatial scales ranging from the pedon to the hillslope.
Alice César Fassoni-Andrade, Fabien Durand, Daniel Moreira, Alberto Azevedo, Valdenira Ferreira dos Santos, Claudia Funi, and Alain Laraque
Earth Syst. Sci. Data, 13, 2275–2291,Short summary
We present a seamless dataset of river, land, and ocean topography of the Amazon River estuary with a 30 m spatial resolution. An innovative remote sensing approach was used to estimate the topography of the intertidal flats, riverbanks, and adjacent floodplains. Amazon River bathymetry was generated from digitized nautical charts. The novel dataset opens up a broad range of opportunities, providing the poorly known underwater digital topography required for environmental sciences.
Stefania Tamea, Marta Tuninetti, Irene Soligno, and Francesco Laio
Earth Syst. Sci. Data, 13, 2025–2051,Short summary
The database includes water footprint and virtual water trade data for 370 agricultural goods in all countries, starting from 1961 and 1986, respectively. Data improve upon earlier datasets because of the annual variability of data and the tracing of goods’ origin within the international trade. The CWASI database aims at supporting national and global assessments of water use in agriculture and food production/consumption and welcomes contributions from the research community.
Fanny Arnaud, Lalandy Sehen Chanu, Jules Grillot, Jérémie Riquier, Hervé Piégay, Dad Roux-Michollet, Georges Carrel, and Jean-Michel Olivier
Earth Syst. Sci. Data, 13, 1939–1955,Short summary
This article provides a database of 350 cartographic and topographic resources on the 530-km-long French Rhône River, compiled from the 17th to mid-20th century in 14 national, regional, and departmental archive services. The database has several potential applications in geomorphology, retrospective hydraulic modelling, historical ecology, and sustainable river management and restoration, as well as permitting comparisons of channel changes with other human-impacted rivers worldwide.
Hollie M. Cooper, Emma Bennett, James Blake, Eleanor Blyth, David Boorman, Elizabeth Cooper, Jonathan Evans, Matthew Fry, Alan Jenkins, Ross Morrison, Daniel Rylett, Simon Stanley, Magdalena Szczykulska, Emily Trill, Vasileios Antoniou, Anne Askquith-Ellis, Lucy Ball, Milo Brooks, Michael A. Clarke, Nicholas Cowan, Alexander Cumming, Philip Farrand, Olivia Hitt, William Lord, Peter Scarlett, Oliver Swain, Jenna Thornton, Alan Warwick, and Ben Winterbourn
Earth Syst. Sci. Data, 13, 1737–1757,Short summary
COSMOS-UK is a UK network of environmental monitoring sites, with a focus on measuring field-scale soil moisture. Each site includes soil and hydrometeorological sensors providing data including air temperature, humidity, net radiation, neutron counts, snow water equivalent, and potential evaporation. These data can provide information for science, industry, and agriculture by improving existing understanding and data products in fields such as water resources, space sciences, and biodiversity.
Surya Gupta, Tomislav Hengl, Peter Lehmann, Sara Bonetti, and Dani Or
Earth Syst. Sci. Data, 13, 1593–1612,
Yves Tramblay, Nathalie Rouché, Jean-Emmanuel Paturel, Gil Mahé, Jean-François Boyer, Ernest Amoussou, Ansoumana Bodian, Honoré Dacosta, Hamouda Dakhlaoui, Alain Dezetter, Denis Hughes, Lahoucine Hanich, Christophe Peugeot, Raphael Tshimanga, and Patrick Lachassagne
Earth Syst. Sci. Data, 13, 1547–1560,Short summary
This dataset provides a set of hydrometric indices for about 1500 stations across Africa with daily discharge data. These indices represent mean flow characteristics and extremes (low flows and floods), allowing us to study the long-term evolution of hydrology in Africa and support the modeling efforts that aim at reducing the vulnerability of African countries to hydro-climatic variability.
Oleksandra O. Shumilova, Alexander N. Sukhodolov, George S. Constantinescu, and Bruce J. MacVicar
Earth Syst. Sci. Data, 13, 1519–1529,Short summary
Obstructions (vegetation and/or boulders) located on a riverbed alter flow structure and affect riverbed morphology and biodiversity. We studied flow dynamics around obstructions by carrying out experiments in a gravel-bed river. Flow rates, size, submergence and solid fractions of the obstructions were varied in a set of 30 experimental runs, in which high-resolution patterns of mean and turbulent flow were obtained. For an introduction to the experiments see: https://youtu.be/5wXjvzqxONI.
Cristina Aguilar, Rafael Pimentel, and María J. Polo
Earth Syst. Sci. Data, 13, 1335–1359,Short summary
This work presents the reconstruction of 19 years of daily, monthly, and annual global radiation maps in Sierra Nevada (Spain) derived using daily historical records from weather stations in the area and a modeling scheme that captures the topographic effects that constitute the main sources of the spatial and temporal variability of solar radiation. The generated datasets are valuable in different fields, such as hydrology, ecology, or energy production systems downstream.
Gustavo Andrei Speckhann, Heidi Kreibich, and Bruno Merz
Earth Syst. Sci. Data, 13, 731–740,Short summary
Dams are an important element of water resources management. Data about dams are crucial for practitioners, scientists, and policymakers. We present the most comprehensive open-access dam inventory for Germany to date. The inventory combines multiple sources of information. It comprises 530 dams with information on name, location, river, start year of construction and operation, crest length, dam height, lake area, lake volume, purpose, dam structure, and building characteristics.
Edward R. Jones, Michelle T. H. van Vliet, Manzoor Qadir, and Marc F. P. Bierkens
Earth Syst. Sci. Data, 13, 237–254,Short summary
Continually improving and affordable wastewater management provides opportunities for both pollution reduction and clean water supply augmentation. This study provides a global outlook on the state of domestic and industrial wastewater production, collection, treatment and reuse. Our results can serve as a baseline in evaluating progress towards policy goals (e.g. Sustainable Development Goals) and as input data in large-scale water resource assessments (e.g. water quality modelling).
Bolivar Paredes-Beltran, Alvaro Sordo-Ward, and Luis Garrote
Earth Syst. Sci. Data, 13, 213–229,Short summary
We present a dataset of 1010 entries of dams in South America describing several attributes such as the dams' names, characteristics, purposes, georeferenced locations and also relevant data on the dams' catchments. Information was obtained from extensive research through numerous sources and then validated individually. With this work we expect to contribute to the development of new research in the region, which to date has been limited to certain basins due to the absence of information.
Anne Hartmann, Markus Weiler, and Theresa Blume
Earth Syst. Sci. Data, 12, 3189–3204,Short summary
Our analysis of soil physical and hydraulic properties across two soil chronosequences of 10 millennia in the Swiss Alps provides important observation of the evolution of soil hydraulic behavior. A strong co-evolution of soil physical and hydraulic properties was revealed by the observed change of fast-draining coarse-textured soils to slow-draining soils with a high water-holding capacity in correlation with a distinct change in structural properties and organic matter content.
Maria Staudinger, Stefan Seeger, Barbara Herbstritt, Michael Stoelzle, Jan Seibert, Kerstin Stahl, and Markus Weiler
Earth Syst. Sci. Data, 12, 3057–3066,Short summary
The data set CH-IRP provides isotope composition in precipitation and streamflow from 23 Swiss catchments, being unique regarding its long-term multi-catchment coverage along an alpine–pre-alpine gradient. CH-IRP contains fortnightly time series of stable water isotopes from streamflow grab samples complemented by time series in precipitation. Sampling conditions, catchment and climate information, lab standards and errors are provided together with areal precipitation and catchment boundaries.
Gemma Coxon, Nans Addor, John P. Bloomfield, Jim Freer, Matt Fry, Jamie Hannaford, Nicholas J. K. Howden, Rosanna Lane, Melinda Lewis, Emma L. Robinson, Thorsten Wagener, and Ross Woods
Earth Syst. Sci. Data, 12, 2459–2483,Short summary
We present the first large-sample catchment hydrology dataset for Great Britain. The dataset collates river flows, catchment attributes, and catchment boundaries for 671 catchments across Great Britain. We characterise the topography, climate, streamflow, land cover, soils, hydrogeology, human influence, and discharge uncertainty of each catchment. The dataset is publicly available for the community to use in a wide range of environmental and modelling analyses.
Benjamin Fersch, Till Francke, Maik Heistermann, Martin Schrön, Veronika Döpper, Jannis Jakobi, Gabriele Baroni, Theresa Blume, Heye Bogena, Christian Budach, Tobias Gränzig, Michael Förster, Andreas Güntner, Harrie-Jan Hendricks Franssen, Mandy Kasner, Markus Köhli, Birgit Kleinschmit, Harald Kunstmann, Amol Patil, Daniel Rasche, Lena Scheiffele, Ulrich Schmidt, Sandra Szulc-Seyfried, Jannis Weimar, Steffen Zacharias, Marek Zreda, Bernd Heber, Ralf Kiese, Vladimir Mares, Hannes Mollenhauer, Ingo Völksch, and Sascha Oswald
Earth Syst. Sci. Data, 12, 2289–2309,
Vinícius B. P. Chagas, Pedro L. B. Chaffe, Nans Addor, Fernando M. Fan, Ayan S. Fleischmann, Rodrigo C. D. Paiva, and Vinícius A. Siqueira
Earth Syst. Sci. Data, 12, 2075–2096,Short summary
We present a new dataset for large-sample hydrological studies in Brazil. The dataset encompasses daily observed streamflow from 3679 gauges, as well as meteorological forcing for 897 selected catchments. It also includes 65 attributes covering topographic, climatic, hydrologic, land cover, geologic, soil, and human intervention variables. CAMELS-BR is publicly available and will enable new insights into the hydrological behavior of catchments in Brazil.
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,Short summary
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.
Laurent de Rham, Yonas Dibike, Spyros Beltaos, Daniel Peters, Barrie Bonsal, and Terry Prowse
Earth Syst. Sci. Data, 12, 1835–1860,Short summary
This paper describes the Canadian River Ice Database. Water level recordings at a network of 196 National Hydrometric Program gauging sites over the period 1894–2015 were reviewed. This database, of nearly 73 000 recorded variables and over 460 000 data entries, includes the timing and magnitude of fall freeze-up, midwinter break-up, winter minimum, ice thickness, spring break-up and maximum open-water levels. These data cover the range of river types and climate regions for Canada.
Yuanwei Wang, Lei Wang, Xiuping Li, Jing Zhou, and Zhidan Hu
Earth Syst. Sci. Data, 12, 1789–1803,Short summary
This article is to provide a better precipitation product for the largest river basin of the Tibetan Plateau, the upper Brahmaputra River basin, suitable for use in hydrological simulations and other climate change studies. We integrate gauge, satellite, and reanalysis precipitation datasets to generate a new dataset. The new product has been rigorously validated at various temporal and spatial scales with gauge precipitation observations as well as in cryosphere hydrological simulations.
Matthew T. Perks, Silvano Fortunato Dal Sasso, Alexandre Hauet, Elizabeth Jamieson, Jérôme Le Coz, Sophie Pearce, Salvador Peña-Haro, Alonso Pizarro, Dariia Strelnikova, Flavia Tauro, James Bomhof, Salvatore Grimaldi, Alain Goulet, Borbála Hortobágyi, Magali Jodeau, Sabine Käfer, Robert Ljubičić, Ian Maddock, Peter Mayr, Gernot Paulus, Lionel Pénard, Leigh Sinclair, and Salvatore Manfreda
Earth Syst. Sci. Data, 12, 1545–1559,Short summary
We present datasets acquired from seven countries across Europe and North America consisting of image sequences. These have been subjected to a range of pre-processing methods in preparation for image velocimetry analysis. These datasets and accompanying reference data are a resource that may be used for conducting benchmarking experiments, assessing algorithm performances, and focusing future software development.
Ziqiang Ma, Jintao Xu, Siyu Zhu, Jun Yang, Guoqiang Tang, Yuanjian Yang, Zhou Shi, and Yang Hong
Earth Syst. Sci. Data, 12, 1525–1544,Short summary
Focusing on the potential drawbacks in generating the state-of-the-art IMERG data in both the TRMM and GPM era, a new daily calibration algorithm on IMERG was proposed, as well as a new AIMERG precipitation dataset (0.1°/half-hourly, 2000–2015, Asia) with better quality than IMERG for Asian scientific research and applications. The proposed daily calibration algorithm for GPM is promising and applicable in generating the future IMERG in either an operational scheme or a retrospective manner.
C. Jason Williams, Frederick B. Pierson, Patrick R. Kormos, Osama Z. Al-Hamdan, and Justin C. Johnson
Earth Syst. Sci. Data, 12, 1347–1365,Short summary
Data were collected at three sites over 10 years to evaluate ecologic impacts of tree encroachment on rangelands and assess impacts of tree-removal practices on vegetation, surface conditions, and hydrologic/erosion processes. The dataset includes 1300 rainfall simulation and 838 overland-flow experiments paired with vegetation, surface cover, and soil data across point to hillslope scales. The data advance hydrology/erosion process understanding and are a source for model development/testing.
Riccardo Tortini, Nina Noujdina, Samantha Yeo, Martina Ricko, Charon M. Birkett, Ankush Khandelwal, Vipin Kumar, Miriam E. Marlier, and Dennis P. Lettenmaier
Earth Syst. Sci. Data, 12, 1141–1151,Short summary
We present a global collection of satellite-derived time series of surface water volume changes for 347 lakes and reservoirs for 1992–2018. These changes were estimated using a statistical relationship between water surface elevation and area measured from satellite, even during periods when either elevation or area was not available. These records represent the most complete global surface water time series, and they are of fundamental importance to baseline future satellite missions.
Navid Ghajarnia, Georgia Destouni, Josefin Thorslund, Zahra Kalantari, Imenne Åhlén, Jesús A. Anaya-Acevedo, Juan F. Blanco-Libreros, Sonia Borja, Sergey Chalov, Aleksandra Chalova, Kwok P. Chun, Nicola Clerici, Amanda Desormeaux, Bethany B. Garfield, Pierre Girard, Olga Gorelits, Amy Hansen, Fernando Jaramillo, Jerker Jarsjö, Adnane Labbaci, John Livsey, Giorgos Maneas, Kathryn McCurley Pisarello, Sebastián Palomino-Ángel, Jan Pietroń, René M. Price, Victor H. Rivera-Monroy, Jorge Salgado, A. Britta K. Sannel, Samaneh Seifollahi-Aghmiuni, Ylva Sjöberg, Pavel Terskii, Guillaume Vigouroux, Lucia Licero-Villanueva, and David Zamora
Earth Syst. Sci. Data, 12, 1083–1100,Short summary
Hydroclimate and land-use conditions determine the dynamics of wetlands and their ecosystem services. However, knowledge and data for conditions and changes over entire wetlandscapes are scarce. This paper presents a novel database for 27 wetlandscapes around the world, combining survey-based local information and hydroclimatic and land-use datasets. The developed database can enhance our capacity to understand and manage critical wetland ecosystems and their services under global change.
Pierre-Antoine Versini, Filip Stanic, Auguste Gires, Daniel Schertzer, and Ioulia Tchiguirinskaia
Earth Syst. Sci. Data, 12, 1025–1035,Short summary
The Blue Green Wave of Champs-sur-Marne (1 ha, France) has been converted into a full-scale monitoring site devoted to studying the uses of green infrastructure in storm-water management. For this purpose, the components of the water balance have been monitored: rainfall, water content in the substrate, and discharge. These measurements are useful to better understand the processes (infiltration and retention) in hydrological performance and spatial variability.
Axel Schaffitel, Tobias Schuetz, and Markus Weiler
Earth Syst. Sci. Data, 12, 501–517,Short summary
This paper contains detailed information about the instrumentation of permeable pavements with soil moisture sensors and the performance of infiltration experiments on these surfaces. The collected data are beneficial for studying urban water and energy cycles. They contain valuable information about the hydrological behavior of permeable pavements and urban subsurface heat anomalies. Due to the lack of similar data, we are convinced that the dataset is of great scientific value.
Chao Gao, Buda Su, Valentina Krysanova, Qianyu Zha, Cai Chen, Gang Luo, Xiaofan Zeng, Jinlong Huang, Ming Xiong, Liping Zhang, and Tong Jiang
Earth Syst. Sci. Data, 12, 387–402,Short summary
The study produced the daily discharge time series for the upper Yangtze River basin (Cuntan hydrological station) in the period 1861–2299 under scenarios with and without anthropogenic climate change. The daily discharge was simulated by using four hydrological models (HBV, SWAT, SWIM and VIC) driven by multiple GCM outputs. This dataset could be compared to assess changes in river discharge in the upper Yangtze River basin attributable to anthropogenic climate change.
Fabian Ries, Lara Kirn, and Markus Weiler
Earth Syst. Sci. Data, 12, 245–255,Short summary
Pluvial or flash floods generated by heavy precipitation events cause large economic damage and loss of life worldwide. As discharge observations from such extreme occurrences are rare, data from artificial sprinkling experiments offer valuable information on runoff generation processes, overland and subsurface flow rates, and response times. A extensive data set from 132 large-scale sprinkling experiments in Germany is described and presented in this paper.
Andrew R. Slaughter and Saman Razavi
Earth Syst. Sci. Data, 12, 231–243,Short summary
Water management faces the challenge of non-stationarity in future flows. To extend flow datasets beyond the gauging data, this study presents a method of generating an ensemble of weekly flows from tree-ring reconstructed flows to represent uncertainty that can overcome certain long-standing data challenges with paleo-reconstruction. An ensemble of 500 flow time series were generated for the four sub-basins of the Saskatchewan River basin, Canada, for the period 1600–2001.
Stephen Coss, Michael Durand, Yuchan Yi, Yuanyuan Jia, Qi Guo, Stephen Tuozzolo, C. K. Shum, George H. Allen, Stéphane Calmant, and Tamlin Pavelsky
Earth Syst. Sci. Data, 12, 137–150,Short summary
We present a new radar-altimeter-satellite-measured river surface height dataset. Our novel approach is broadly applicable rather than location specific. We were able to measure rivers that account for > 34 % of global drainage area with an accuracy comparable to much of the established literature. 389 of our 932 measurement locations include river gage validation. We have focused our efforts on creating a consistent, well-documented data product to encourage use by the broader science community.
Ellie Broadman, Lorna L. Thurston, Erik Schiefer, Nicholas P. McKay, David Fortin, Jason Geck, Michael G. Loso, Matt Nolan, Stéphanie H. Arcusa, Christopher W. Benson, Rebecca A. Ellerbroek, Michael P. Erb, Cody C. Routson, Charlotte Wiman, A. Jade Wong, and Darrell S. Kaufman
Earth Syst. Sci. Data, 11, 1957–1970,Short summary
Rapid climate warming is impacting physical processes in Arctic environments. Glacier–fed lakes are influenced by many of these processes, and they are impacted by the changing behavior of weather, glaciers, and rivers. We present data from weather stations, river gauging stations, lake moorings, and more, following 4 years of environmental monitoring in the watershed of Lake Peters, a glacier–fed lake in Arctic Alaska. These data can help us study the changing dynamics of this remote setting.
Gionata Ghiggi, Vincent Humphrey, Sonia I. Seneviratne, and Lukas Gudmundsson
Earth Syst. Sci. Data, 11, 1655–1674,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.
Luca Brocca, Paolo Filippucci, Sebastian Hahn, Luca Ciabatta, Christian Massari, Stefania Camici, Lothar Schüller, Bojan Bojkov, and Wolfgang Wagner
Earth Syst. Sci. Data, 11, 1583–1601,Short summary
SM2RAIN–ASCAT is a new 12-year (2007–2018) global-scale rainfall dataset obtained by applying the SM2RAIN algorithm to ASCAT soil moisture data. The dataset has a spatiotemporal sampling resolution of 12.5 km and 1 d. Results show that the new dataset performs particularly well in Africa and South America, i.e. in the continents in which ground observations are scarce and the need for satellite rainfall data is high. SM2RAIN–ASCAT is available at http://doi.org/10.5281/zenodo.340556.
Abrams, M., Crippen, R., and Fujisada, H.: ASTER global digital elevation model (GDEM) and ASTER global water body dataset (ASTWBD), Remote Sensing, 12, 1156, https://doi.org/10.3390/rs12071156, 2020.
Addor, N., Newman, A. J., Mizukami, N., and Clark, M. P.: The CAMELS data set: catchment attributes and meteorology for large-sample studies, Hydrol. Earth Syst. Sci., 21, 5293–5313, https://doi.org/10.5194/hess-21-5293-2017, 2017.
Addor, N., Do, H. X., Alvarez-Garreton, C., Coxon, G., Fowler, K., and Mendoza, P. A.: Large-sample hydrology: recent progress, guidelines for new datasets and grand challenges, Hydrolog. Sci. J., 65, 712–725, 2020.
Alvarez-Garreton, C., Mendoza, P. A., Boisier, J. P., Addor, N., Galleguillos, M., Zambrano-Bigiarini, M., Lara, A., Puelma, C., Cortes, G., Garreaud, R., McPhee, J., and Ayala, A.: The CAMELS-CL dataset: catchment attributes and meteorology for large sample studies – Chile dataset, Hydrol. Earth Syst. Sci., 22, 5817–5846, https://doi.org/10.5194/hess-22-5817-2018, 2018.
Belward, A. S., Estes, J. E., and Kline, K. D.: The IGBP-DIS global 1-km land-cover data set DISCover: A project overview, Photogramm. Eng. Rem. S., 65, 1013–1020, 1999.
Berghuijs, W. R., Aalbers, E. E., Larsen, J. R., Trancoso, R., and Woods, R. A.: Recent changes in extreme floods across multiple continents, Environ. Res. Lett., 12, 114035, https://doi.org/10.1088/1748-9326/aa8847, 2017.
Blume, T., van Meerveld, I., and Weiler, M.: Incentives for field hydrology and data sharing: collaboration and compensation: reply to “A need for incentivizing field hydrology, especially in an era of open data”, Hydrolog. Sci. J., 63, 1266–1268, 2018.
Brodeur, Z. P., Herman, J. D., and Steinschneider, S.: Bootstrap Aggregation and Cross-Validation Methods to Reduce Overfitting in Reservoir Control Policy Search, Water Resour. Res., 56, e2020WR027184, https://doi.org/10.1029/2020WR027184, 2020.
Bureau of Geology and Mineral Resources of Xinjiang (BGX): Geological map of Xinjiang Uygur, Autonomous Region, China, version 2, scale , Geol. Publ. House, Beijing, 1992.
Ceola, S., Arheimer, B., Baratti, E., Blöschl, G., Capell, R., Castellarin, A., Freer, J., Han, D., Hrachowitz, M., Hundecha, Y., Hutton, C., Lindström, G., Montanari, A., Nijzink, R., Parajka, J., Toth, E., Viglione, A., and Wagener, T.: Virtual laboratories: new opportunities for collaborative water science, Hydrol. Earth Syst. Sci., 19, 2101–2117, https://doi.org/10.5194/hess-19-2101-2015, 2015.
Chagas, V. B. P., Chaffe, P. L. B., Addor, N., Fan, F. M., Fleischmann, A. S., Paiva, R. C. D., and Siqueira, V. A.: CAMELS-BR: hydrometeorological time series and landscape attributes for 897 catchments in Brazil, Earth Syst. Sci. Data, 12, 2075–2096, https://doi.org/10.5194/essd-12-2075-2020, 2020.
China Geological Survey (CGS): -scale digital geological map database of China, Beijing, 2001.
Coron, L., Andreassian, V., Perrin, C., Lerat, J., Vaze, J., Bourqui, M., and Hendrickx, F.: Crash testing hydrological models in contrasted climate conditions: An experiment on 216 Australian catchments, Water Resour. Res., 48, W05552, https://doi.org/10.1029/2011WR011721, 2012.
Coxon, G., Addor, N., Bloomfield, J. P., Freer, J., Fry, M., Hannaford, J., Howden, N. J. K., Lane, R., Lewis, M., Robinson, E. L., Wagener, T., and Woods, R.: CAMELS-GB: hydrometeorological time series and landscape attributes for 671 catchments in Great Britain, Earth Syst. Sci. Data, 12, 2459–2483, https://doi.org/10.5194/essd-12-2459-2020, 2020.
Dai, Y., Xin, Q., Wei, N., Zhang, Y., Shangguan, W., Yuan, H., Zhang, S., Liu, S., and Lu, X.: A global high-resolution data set of soil hydraulic and thermal properties for land surface modeling, J. Adv. Model. Earth Sy., 11, 2996–3023, 2019.
de Araújo, J. C. and González Piedra, J. I.: Comparative hydrology: analysis of a semiarid and a humid tropical watershed, Hydrol. Process., 23, 1169–1178, 2009.
Desborough, C. E.: The impact of root weighting on the response of transpiration to moisture stress in land surface schemes, Mon. Weather Rev., 125, 1920–1930, 1997.
Didan, K.: MOD13A3 MODIS/Terra vegetation Indices Monthly L3 Global 1km SIN Grid V006, NASA EOSDIS Land Processes DAAC [Data set], https://doi.org/10.5067/MODIS/MOD13A3.006, 2015.
Feng, D., Fang, K., and Shen, C.: Enhancing streamflow forecast and extracting insights using long-short term memory networks with data integration at continental scales, Water Resour. Res., 56, e2019WR026793, https://doi.org/10.1029/2019WR026793, 2020.
Friedl, M. A., Sulla-Menashe, D., Tan, B., Schneider, A., Ramankutty, N., Sibley, A., and Huang, X.: MODIS Collection 5 global land cover: Algorithm refinements and characterization of new datasets, Remote Sens. Environ., 114, 168–182, 2010.
GDAL/OGR contributors: GDAL/OGR Geospatial Data Abstraction software Library, Open Source Geospatial Foundation [code], available at: https://gdal.org (last access: 26 November 2021), 2020.
Gleeson, T., Smith, L., Moosdorf, N., Hartmann, J., Dürr, H. H., Manning, A. H., van Beek, L. P., and Jellinek, A. M.: Mapping permeability over the surface of the Earth, Geophys. Res. Lett., 38, L02401, https://doi.org/10.1029/2010GL045565, 2011.
Gleeson, T., Moosdorf, N., Hartmann, J., and Van Beek, L.: A glimpse beneath earth's surface: GLobal HYdrogeology MaPS (GLHYMPS) of permeability and porosity, Geophys. Res. Lett., 41, 3891–3898, 2014.
Hartmann, J. and Moosdorf, N.: The new global lithological map database GLiM: A representation of rock properties at the Earth surface, Geochem. Geophy. Geosy., 13, Q12004, https://doi.org/10.1029/2012GC004370, 2012.
Hengl, T., Mendes de Jesus, J., Heuvelink, G. B., Ruiperez Gonzalez, M., Kilibarda, M., Blagotić, A., Shangguan, W., Wright, M. N., Geng, X., and Bauer-Marschallinger, B.: SoilGrids250m: Global gridded soil information based on machine learning, PLoS one, 12, e0169748, https://doi.org/10.1371/journal.pone.0169748, 2017.
Horn, B. K.: Hill shading and the reflectance map, Proc. IEEE, 69, 14–47, 1981.
Hoyer, S. and Hamman, J.: xarray: ND labeled arrays and datasets in Python, Journal of Open Research Software [code], 5, 2017.
Huang, H., Han, Y., Cao, M., Song, J., and Xiao, H.: Spatial-temporal variation of aridity index of China during 1960–2013, Adv. Meteorol., 2016, 1536135, https://doi.org/10.1155/2016/1536135, 2016.
Jenson, S. K. and Domingue, J. O.: Extracting topographic structure from digital elevation data for geographic information system analysis, Photogramm. Eng. Rem. S., 54, 1593–1600, 1988.
Kendall, M. G.: A new measure of rank correlation, Biometrika, 30, 81–93, 1938.
Knoben, W. J. M., Freer, J. E., and Woods, R. A.: Technical note: Inherent benchmark or not? Comparing Nash–Sutcliffe and Kling–Gupta efficiency scores, Hydrol. Earth Syst. Sci., 23, 4323–4331, https://doi.org/10.5194/hess-23-4323-2019, 2019.
Knyazikhin, Y.: MODIS leaf area index (LAI) and fraction of photosynthetically active radiation absorbed by vegetation (FPAR) product (MOD 15) algorithm theoretical basis document, available at: https://modis.gsfc.nasa.gov/data/atbd/atbd_mod15.pdf (last access: 26 November 2021), 1999.
Kollat, J., Reed, P., and Wagener, T.: When are multiobjective calibration trade-offs in hydrologic models meaningful?, Water Resour. Res., 48, W03520, https://doi.org/10.1029/2011WR011534, 2012.
Kratzert, F., Klotz, D., Shalev, G., Klambauer, G., Hochreiter, S., and Nearing, G.: Towards learning universal, regional, and local hydrological behaviors via machine learning applied to large-sample datasets, Hydrol. Earth Syst. Sci., 23, 5089–5110, https://doi.org/10.5194/hess-23-5089-2019, 2019.
Lane, R. A., Coxon, G., Freer, J. E., Wagener, T., Johnes, P. J., Bloomfield, J. P., Greene, S., Macleod, C. J. A., and Reaney, S. M.: Benchmarking the predictive capability of hydrological models for river flow and flood peak predictions across over 1000 catchments in Great Britain, Hydrol. Earth Syst. Sci., 23, 4011–4032, https://doi.org/10.5194/hess-23-4011-2019, 2019.
Legasa, M. and Gutiérrez, J. M.: Multisite Weather Generators using Bayesian Networks: An illustrative case study for precipitation occurrence, Water Resour. Res., 56, e2019WR026416, https://doi.org/10.1029/2019WR026416, 2020.
Lehner, B.: HydroBASINS: Global watershed boundaries and sub-basin delineations derived from HydroSHEDS data at 15 second resolution – Technical documentation version 1. c, 2014.
Lehner, B., Verdin, K., and Jarvis, A: New global hydrography derived from spaceborne elevation data, Eos, Transactions, AGU, 89, 93–94, 2008.
Linke, S., Lehner, B., Dallaire, C. O., Ariwi, J., Grill, G., Anand, M., Beames, P., Burchard-Levine, V., Maxwell, S., and Moidu, H.: Global hydro-environmental sub-basin and river reach characteristics at high spatial resolution, Sci. Data, 6, 1–15, 2019.
Liu, B., Xu, M., Henderson, M., and Gong, W.: A spatial analysis of pan evaporation trends in China, 1955–2000, J. Geophys. Res.-Atmos., 109, D15102, https://doi.org/10.1029/2004JD004511, 2004.
Liu, Q., Yang, Z., and Xia, X.: Trends for pan evaporation during 1959–2000 in China, Procedia Environ. Sci., 2, 1934–1941, 2010.
Liu, Y., Zheng, J., Hao, Z., and Zhang, X.: Unprecedented warming revealed from multi-proxy reconstruction of temperature in southern China for the past 160 years, Adv. Atmos. Sci., 34, 977–982, 2017.
Maidment, D. R.: GIS and hydrologic modeling-an assessment of progress, Third International Conference on GIS and Environmental Modeling, Santa Fe, New Mexico, 1996.
Maidment, D. R. and Morehouse, S.: Arc Hydro: GIS for water resources, ESRI Press, Redlands, CA, USA, 2002.
Masutomi, Y., Inui, Y., Takahashi, K., and Matsuoka, Y.: Development of highly accurate global polygonal drainage basin data, Hydrol. Process., 23, 572–584, 2009.
Mei, Y., Maggioni, V., Houser, P., Xue, Y., and Rouf, T.: A nonparametric statistical technique for spatial downscaling of precipitation over High Mountain Asia, Water Resour. Res., 56, e2020WR027472, https://doi.org/10.1029/2020WR027472, 2020.
Ministry of Geology and Mineral Resources of the People’s Republic of China (MGC): Geological map of Nei Mongol Autonomous Region, People’s Republic of China, scale , Geol. Publ. House, Beijing, 1991.
Myneni, R., Knyazikhin, Y., and Park, T.: MYD15A2H MODIS/Aqua Leaf Area Index/FPAR 8-Day L4 Global 500m SIN Grid, Boston University and MODAPS SIPS – NASA, NASA LP DAAC [dataset], https://doi.org/10.5067/MODIS/MYD15A2H.006 2015.
Nevo, S., Anisimov, V., Elidan, G., El-Yaniv, R., Giencke, P., Gigi, Y., Hassidim, A., Moshe, Z., Schlesinger, M., and Shalev, G.: ML for flood forecasting at scale, arXiv [preprint], arXiv:1901.09583, 2019.
Newman, A. J., Clark, M. P., Sampson, K., Wood, A., Hay, L. E., Bock, A., Viger, R. J., Blodgett, D., Brekke, L., Arnold, J. R., Hopson, T., and Duan, Q.: Development of a large-sample watershed-scale hydrometeorological data set for the contiguous USA: data set characteristics and assessment of regional variability in hydrologic model performance, Hydrol. Earth Syst. Sci., 19, 209–223, https://doi.org/10.5194/hess-19-209-2015, 2015.
Ni, H. and Benson, S. M.: Using Unsupervised Machine Learning to Characterize Capillary Flow and Residual Trapping, Water Resour. Res., 56, e2020WR027473, https://doi.org/10.1029/2020WR027473, 2020.
Oudin, L., Andréassian, V., Lerat, J., and Michel, C.: Has land cover a significant impact on mean annual streamflow? An international assessment using 1508 catchments, J. Hydrol., 357, 303–316, 2008.
Running, S. and Mu, Q.: MOD16A2 MODIS/Terra Evapotranspiration 8-day L4 Global 500m SIN Grid, University of Montana and MODAPS SIPS – NASA, NASA LP DAAC [data set], https://doi.org/10.5067/MODIS/MOD16A2.006, 2017.
Seybold, H., Rothman, D. H., and Kirchner, J. W.: Climate's watermark in the geometry of stream networks, Geophys. Res. Lett., 44, 2272–2280, 2017.
Shangguan, W., Dai, Y., Liu, B., Zhu, A., Duan, Q., Wu, L., Ji, D., Ye, A., Yuan, H., and Zhang, Q.: A China data set of soil properties for land surface modeling, J. Adv. Model. Earth Sy., 5, 212–224, 2013.
Shangguan, W., Dai, Y., Duan, Q., Liu, B., and Yuan, H.: A global soil data set for earth system modeling, J. Adv. Model. Earth Sy., 6, 249–263, 2014.
Shen, C., Laloy, E., Elshorbagy, A., Albert, A., Bales, J., Chang, F.-J., Ganguly, S., Hsu, K.-L., Kifer, D., Fang, Z., Fang, K., Li, D., Li, X., and Tsai, W.-P.: HESS Opinions: Incubating deep-learning-powered hydrologic science advances as a community, Hydrol. Earth Syst. Sci., 22, 5639–5656, https://doi.org/10.5194/hess-22-5639-2018, 2018.
Silberstein, R.: Hydrological models are so good, do we still need data?, Environ. Model. Softw., 21, 1340–1352, 2006.
Singh, R., Archfield, S., and Wagener, T.: Identifying dominant controls on hydrologic parameter transfer from gauged to ungauged catchments – A comparative hydrology approach, J. Hydrol., 517, 985–996, 2014a.
Singh, R., van Werkhoven, K., and Wagener, T.: Hydrological impacts of climate change in gauged and ungauged watersheds of the Olifants basin: a trading-space-for-time approach, Hydrolog. Sci. J., 59, 29–55, 2014b.
Subramanya, K.: Engineering Hydrology, 4e, McGraw Hill Education Private Limited P-24, Green Park Extension, New Delhi, India, 2013.
Sulla-Menashe, D. and Friedl, M. A.: User guide to collection 6 MODIS land cover (MCD12Q1 and MCD12C1) product, USGS, Reston, VA, USA, 1–18, 2018.
Tyralis, H., Papacharalampous, G., and Tantanee, S.: How to explain and predict the shape parameter of the generalized extreme value distribution of streamflow extremes using a big dataset, J. Hydrol., 574, 628–645, 2019.
van Werkhoven, K., Wagener, T., Reed, P., and Tang, Y.: Characterization of watershed model behavior across a hydroclimatic gradient, Water Resour. Res., 44, W01429, https://doi.org/10.1029/2007WR006271, 2008.
van Wijk, M. T. and Williams, M.: Optical instruments for measuring leaf area index in low vegetation: application in arctic ecosystems, Ecol. Appl., 15, 1462–1470, 2005.
Voepel, H., Ruddell, B., Schumer, R., Troch, P. A., Brooks, P. D., Neal, A., Durcik, M., and Sivapalan, M.: Quantifying the role of climate and landscape characteristics on hydrologic partitioning and vegetation response, Water Resour. Res., 47, W00J09, https://doi.org/10.1029/2010WR009944, 2011.
Wang, J., Chen, M., Lü, G., Yue, S., Wen, Y., Lan, Z., and Zhang, S.: A data sharing method in the open web environment: Data sharing in hydrology, J. Hydrol., 587, 124973, https://doi.org/10.1016/j.jhydrol.2020.124973, 2020.
Wongso, E., Nateghi, R., Zaitchik, B., Quiring, S., and Kumar, R.: A Data-Driven Framework to Characterize State-Level Water Use in the United States, Water Resour. Res., 56, e2019WR024894, https://doi.org/10.1029/2019WR024894, 2020.
Woods, R. A.: Analytical model of seasonal climate impacts on snow hydrology: Continuous snowpacks, Adv. Water Resour., 32, 1465–1481, 2009.
Xu, Y., Gao, X., Shen, Y., Xu, C., Shi, Y., and Giorgi, a.: A daily temperature dataset over China and its application in validating a RCM simulation, Adv. Atmos. Sci., 26, 763–772, 2009.
Yamazaki, D., Ikeshima, D., Sosa, J., Bates, P. D., Allen, G. H., and Pavelsky, T. M.: MERIT Hydro: a high-resolution global hydrography map based on latest topography dataset, Water Resour. Res., 55, 5053–5073, 2019.
Zeng, X.: Global vegetation root distribution for land modeling, J. Hydrometeorol., 2, 525–530, 2001.
Zhen, H.: CCAM: China Catchment Attributes and Meteorology dataset, Zenodo [code], https://doi.org/10.5281/zenodo.5749718, last access: 30 November 2021.
Zhen, H., Jin, J., Xia, R., Tian, S., Yang, W., Liu, Q., Zhu, M., Ma, T., and Chengran, J.: CCAM: China Catchment Attributes and Meteorology dataset, Zenodo [data set], https://doi.org/10.5281/zenodo.5729444, 2021.
CCAM is proposed to promote large-sample hydrological research in China. The first catchment attribute dataset and catchment-scale meteorological time series dataset in China are built. We also built HydroMLYR, a hydrological dataset with standardized streamflow observations supporting machine learning modeling. The open-source code producing CCAM supports the calculation of custom watersheds.
CCAM is proposed to promote large-sample hydrological research in China. The first catchment...