Articles | Volume 16, issue 4
https://doi.org/10.5194/essd-16-1811-2024
© Author(s) 2024. 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-16-1811-2024
© Author(s) 2024. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
CAMELE: Collocation-Analyzed Multi-source Ensembled Land Evapotranspiration Data
Changming Li
State Key Laboratory of Hydroscience and Engineering, Department of Hydraulic Engineering, Tsinghua University, Beijing 100084, China
Ziwei Liu
State Key Laboratory of Hydroscience and Engineering, Department of Hydraulic Engineering, Tsinghua University, Beijing 100084, China
Wencong Yang
State Key Laboratory of Hydroscience and Engineering, Department of Hydraulic Engineering, Tsinghua University, Beijing 100084, China
Zhuoyi Tu
State Key Laboratory of Hydroscience and Engineering, Department of Hydraulic Engineering, Tsinghua University, Beijing 100084, China
Juntai Han
State Key Laboratory of Hydroscience and Engineering, Department of Hydraulic Engineering, Tsinghua University, Beijing 100084, China
Sien Li
Center for Agricultural Water Research in China, China Agricultural University, Beijing 100083, China
State Key Laboratory of Hydroscience and Engineering, Department of Hydraulic Engineering, Tsinghua University, Beijing 100084, China
Related authors
Yufen He, Changming Li, and Hanbo Yang
Hydrol. Earth Syst. Sci. Discuss., https://doi.org/10.5194/hess-2024-349, https://doi.org/10.5194/hess-2024-349, 2024
Preprint under review for HESS
Short summary
Short summary
Our research presents an improved method to enhance the understanding and prediction of water flows in rivers and streams, focusing on key runoff components: surface flow, baseflow, and total runoff. Using a streamlined model, the MPS model, we analyzed over 600 catchments in China and the U.S., demonstrating its accuracy in capturing the spatial and temporal variability of these components. This model offers a practical tool for water resource management.
Ziwei Liu, Hanbo Yang, Changming Li, and Taihua Wang
Hydrol. Earth Syst. Sci., 28, 4349–4360, https://doi.org/10.5194/hess-28-4349-2024, https://doi.org/10.5194/hess-28-4349-2024, 2024
Short summary
Short summary
The determination of the coefficient α in the Priestley–Taylor equation is empirical. Based on an atmospheric boundary layer model, we derived a physically clear and parameter-free expression to investigate the behavior of α. We showed that the temperature dominates changes in α and emphasized that the variation of α with temperature should be considered for long-term hydrological predictions. Our works advance and promote the most classical models in the field.
Wencong Yang, Hanbo Yang, Changming Li, Taihua Wang, Ziwei Liu, Qingfang Hu, and Dawen Yang
Hydrol. Earth Syst. Sci., 26, 6427–6441, https://doi.org/10.5194/hess-26-6427-2022, https://doi.org/10.5194/hess-26-6427-2022, 2022
Short summary
Short summary
We produced a daily 0.1° dataset of precipitation, soil moisture, and snow water equivalent in 1981–2017 across China via reconstructions. The dataset used global background data and local on-site data as forcing input and satellite-based data as reconstruction benchmarks. This long-term high-resolution national hydrological dataset is valuable for national investigations of hydrological processes.
Changming Li, Hanbo Yang, Wencong Yang, Ziwei Liu, Yao Jia, Sien Li, and Dawen Yang
Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2021-456, https://doi.org/10.5194/essd-2021-456, 2022
Revised manuscript not accepted
Short summary
Short summary
A long-term (1980–2020) global ET product is generated based on a collocation-based merging method. The produced Collocation-Analyzed Multi-source Ensembled Land Evapotranspiration Data (CAMELE) performed well over different vegetation coverage against in-situ data. For global comparison, the spatial distribution of multi-year average and annual variation were in consistent with inputs.The CAMELE products is freely available at https://doi.org/10.5281/zenodo.6283239 (Li et al., 2021).
Wangyipu Li, Zhaoyuan Yao, Yifan Qu, Hanbo Yang, Yang Song, Lisheng Song, Lifeng Wu, and Yaokui Cui
Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2024-460, https://doi.org/10.5194/essd-2024-460, 2024
Preprint under review for ESSD
Short summary
Short summary
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 time scales. This comprehensive dataset can strongly support ET modelling, water-carbon cycle monitoring, and long-term climate change analysis.
Yufen He, Changming Li, and Hanbo Yang
Hydrol. Earth Syst. Sci. Discuss., https://doi.org/10.5194/hess-2024-349, https://doi.org/10.5194/hess-2024-349, 2024
Preprint under review for HESS
Short summary
Short summary
Our research presents an improved method to enhance the understanding and prediction of water flows in rivers and streams, focusing on key runoff components: surface flow, baseflow, and total runoff. Using a streamlined model, the MPS model, we analyzed over 600 catchments in China and the U.S., demonstrating its accuracy in capturing the spatial and temporal variability of these components. This model offers a practical tool for water resource management.
Ziwei Liu, Hanbo Yang, Changming Li, and Taihua Wang
Hydrol. Earth Syst. Sci., 28, 4349–4360, https://doi.org/10.5194/hess-28-4349-2024, https://doi.org/10.5194/hess-28-4349-2024, 2024
Short summary
Short summary
The determination of the coefficient α in the Priestley–Taylor equation is empirical. Based on an atmospheric boundary layer model, we derived a physically clear and parameter-free expression to investigate the behavior of α. We showed that the temperature dominates changes in α and emphasized that the variation of α with temperature should be considered for long-term hydrological predictions. Our works advance and promote the most classical models in the field.
Wencong Yang, Hanbo Yang, Changming Li, Taihua Wang, Ziwei Liu, Qingfang Hu, and Dawen Yang
Hydrol. Earth Syst. Sci., 26, 6427–6441, https://doi.org/10.5194/hess-26-6427-2022, https://doi.org/10.5194/hess-26-6427-2022, 2022
Short summary
Short summary
We produced a daily 0.1° dataset of precipitation, soil moisture, and snow water equivalent in 1981–2017 across China via reconstructions. The dataset used global background data and local on-site data as forcing input and satellite-based data as reconstruction benchmarks. This long-term high-resolution national hydrological dataset is valuable for national investigations of hydrological processes.
Zhuoyi Tu, Yuting Yang, and Michael L. Roderick
Hydrol. Earth Syst. Sci., 26, 1745–1754, https://doi.org/10.5194/hess-26-1745-2022, https://doi.org/10.5194/hess-26-1745-2022, 2022
Short summary
Short summary
Here we test a maximum evaporation theory that acknowledges the interdependence between radiation, surface temperature, and evaporation over saturated land. We show that the maximum evaporation approach recovers observed evaporation and surface temperature under non-water-limited conditions across a broad range of bio-climates. The implication is that the maximum evaporation concept can be used to predict potential evaporation that has long been a major difficulty for the hydrological community.
Changming Li, Hanbo Yang, Wencong Yang, Ziwei Liu, Yao Jia, Sien Li, and Dawen Yang
Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2021-456, https://doi.org/10.5194/essd-2021-456, 2022
Revised manuscript not accepted
Short summary
Short summary
A long-term (1980–2020) global ET product is generated based on a collocation-based merging method. The produced Collocation-Analyzed Multi-source Ensembled Land Evapotranspiration Data (CAMELE) performed well over different vegetation coverage against in-situ data. For global comparison, the spatial distribution of multi-year average and annual variation were in consistent with inputs.The CAMELE products is freely available at https://doi.org/10.5281/zenodo.6283239 (Li et al., 2021).
Wencong Yang, Hanbo Yang, Dawen Yang, and Aizhong Hou
Hydrol. Earth Syst. Sci., 25, 2705–2720, https://doi.org/10.5194/hess-25-2705-2021, https://doi.org/10.5194/hess-25-2705-2021, 2021
Short summary
Short summary
This study quantified the causal effects of land cover changes and dams on the changes in annual maximum discharges (Q) in 757 catchments of China using panel regressions. We found that a 1 % point increase in urban areas causes a 3.9 % increase in Q, and a 1 unit increase in reservoir index causes a 21.4 % decrease in Q for catchments with no dam before. This study takes the first step to explain the human-caused flood changes on a national scale in China.
Xu Shan, Xingdong Li, and Hanbo Yang
Hydrol. Earth Syst. Sci. Discuss., https://doi.org/10.5194/hess-2019-283, https://doi.org/10.5194/hess-2019-283, 2019
Manuscript not accepted for further review
Short summary
Short summary
The Budyko hypothesis has been generally used to quantify how much precipitation transforms into evaporation in one catchment. To approach this hypothesis, previous studies proposed analytical formulas derived based on mathematic reasoning. Differently, this study drew a new derivation for this hypothesis based on fundamental physical principles. It clearly reveals the underlying assumptions in the previous mathematic reasoning and promotes hydrologic understanding on this hypothesis.
Xu Shan, Xindong Li, and Hanbo Yang
Hydrol. Earth Syst. Sci. Discuss., https://doi.org/10.5194/hess-2018-598, https://doi.org/10.5194/hess-2018-598, 2018
Manuscript not accepted for further review
Short summary
Short summary
The Budyko hypothesis has been generally used to quantify how much precipitation transforms into evaporation in one catchment. To approach this hypothesis, previous studies proposed analytical formulas derived based on mathematic reasoning. Differently, this study drew a new derivation for this hypothesis based on fundamental physical principles. It clearly reveals the underlying assumptions in the previous mathematic reasoning and promotes hydrologic understanding on this hypothesis.
Zhongwang Chen, Huimin Lei, Hanbo Yang, Dawen Yang, and Yongqiang Cao
Hydrol. Earth Syst. Sci., 21, 2233–2248, https://doi.org/10.5194/hess-21-2233-2017, https://doi.org/10.5194/hess-21-2233-2017, 2017
Short summary
Short summary
The significant climate changes remind us to characterize the hydrological response to it. Based on the long-term observed hydrological and meteorological data in 291 catchments across China, we find a pattern of the response stating that
drier regions are more likely to become drier, whereas wetter regions are more likely to become wetter. We also reveal that the precipitation changes play the most significant role in this process.
Tingting Gong, Huimin Lei, Dawen Yang, Yang Jiao, and Hanbo Yang
Hydrol. Earth Syst. Sci., 21, 863–877, https://doi.org/10.5194/hess-21-863-2017, https://doi.org/10.5194/hess-21-863-2017, 2017
Short summary
Short summary
Seasonal and inter-annual features of ET were analyzed over four periods. A normalization method was adopted to exclude the effects of potential evapotranspiration and soil water stress on ET. During the land degradation process, when natural vegetation (including leaves and branches), sand dunes, dry sand layers, and BSCs were all bulldozed, ET was observed to increase at a mild rate. In a vegetation rehabilitation process with sufficient groundwater, ET also increased at a faster rate.
Zhongwei Huang, Hanbo Yang, and Dawen Yang
Hydrol. Earth Syst. Sci., 20, 2573–2587, https://doi.org/10.5194/hess-20-2573-2016, https://doi.org/10.5194/hess-20-2573-2016, 2016
Short summary
Short summary
The hydrologic processes have been influenced by different climatic factors. However, the dominant climatic factor driving annual runoff change is still unknown in many catchments in China. By using the climate elasticity method proposed by Yang and Yang (2011), the elasticity of runoff to climatic factors was estimated, and the dominant climatic factors driving annual runoff change were detected at catchment scale over China.
T. T. Gong, H. M. Lei, D. W. Yang, Y. Jiao, and H. B. Yang
Hydrol. Earth Syst. Sci. Discuss., https://doi.org/10.5194/hessd-11-13571-2014, https://doi.org/10.5194/hessd-11-13571-2014, 2014
Revised manuscript not accepted
Related subject area
Domain: ESSD – Land | Subject: Hydrology
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
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
CAMELS-DE: hydro-meteorological time series and attributes for 1555 catchments in Germany
Lena River biogeochemistry captured by a 4.5-year high-frequency sampling program
Partitioning of water and CO2 fluxes at NEON sites into soil and plant components: a five-year dataset for spatial and temporal analysis
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
A hydrogeomorphic dataset for characterizing catchment hydrological behavior across the Tibetan Plateau
A synthesis of Global Streamflow Characteristics, Hydrometeorology, and Catchment Attributes (GSHA) for large sample river-centric studies
FOCA: a new quality-controlled database of floods and catchment descriptors in Italy
Dams in the Mekong: a comprehensive database, spatiotemporal distribution, and hydropower potentials
A global dataset of the shape of drainage systems
An extensive spatiotemporal water quality dataset covering four decades (1980–2022) in China
HERA: a high-resolution pan-European hydrological reanalysis (1950–2020)
Flood simulation with the RiverCure approach: the open dataset of the 2016 Águeda flood event
GloLakes: water storage dynamics for 27 000 lakes globally from 1984 to present derived from satellite altimetry and optical imaging
AltiMaP: altimetry mapping procedure for hydrography data
CAMELS-CH: hydro-meteorological time series and landscape attributes for 331 catchments in hydrologic Switzerland
The use of GRDC gauging stations for calibrating large-scale hydrological models
A long-term dataset of simulated epilimnion and hypolimnion temperatures in 401 French lakes (1959–2020)
GTWS-MLrec: global terrestrial water storage reconstruction by machine learning from 1940 to present
A global 5 km monthly potential evapotranspiration dataset (1982–2015) estimated by the Shuttleworth–Wallace model
A gridded dataset of consumptive water footprints, evaporation, transpiration, and associated benchmarks related to crop production in China during 2000–2018
Hydro-PE: gridded datasets of historical and future Penman–Monteith potential evaporation for the United Kingdom
A global streamflow indices time series dataset for large-sample hydrological analyses on streamflow regime (until 2022)
Soil water retention and hydraulic conductivity measured in a wide saturation range
A high-frequency, long-term data set of hydrology and sediment yield: the alpine badland catchments of Draix-Bléone Observatory
Geospatial dataset for hydrologic analyses in India (GHI): a quality-controlled dataset on river gauges, catchment boundaries and hydrometeorological time series
Lake-TopoCat: a global lake drainage topology and catchment database
Three years of soil moisture observations by a dense cosmic-ray neutron sensing cluster at an agricultural research site in north-east Germany
A long-term monthly surface water storage dataset for the Congo basin from 1992 to 2015
A global database of historic glacier lake outburst floods
Past and future discharge and stream temperature at high spatial resolution in a large European basin (Loire basin, France)
Res-CN (Reservoir dataset in China): hydrometeorological time series and landscape attributes across 3254 Chinese reservoirs
An ensemble of 48 physically perturbed model estimates of the 1∕8° terrestrial water budget over the conterminous United States, 1980–2015
The UKSCAPE-G2G river flow and soil moisture datasets: Grid-to-Grid model estimates for the UK for historical and potential future climates
The enhanced future Flows and Groundwater dataset: development and evaluation of nationally consistent hydrological projections based on UKCP18
RC4USCoast: a river chemistry dataset for regional ocean model applications in the US East Coast, Gulf of Mexico, and US West Coast
Generation of global 1 km daily soil moisture product from 2000 to 2020 using ensemble learning
Panta Rhei benchmark dataset: socio-hydrological data of paired events of floods and droughts
Twelve years of profile soil moisture and temperature measurements in Twente, the Netherlands
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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.
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
Short summary
Short summary
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
Short summary
Short summary
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.
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 Discuss., https://doi.org/10.5194/essd-2024-318, https://doi.org/10.5194/essd-2024-318, 2024
Revised manuscript accepted for ESSD
Short summary
Short summary
The CAMELS-DE dataset features data from 1555 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.
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 Discuss., https://doi.org/10.5194/essd-2024-290, https://doi.org/10.5194/essd-2024-290, 2024
Revised manuscript accepted for ESSD
Short summary
Short summary
The Siberian Arctic is warming fast: permafrost is thawing, river chemistry is changing, and coastal ecosystems are affected. We want to understand changes to 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/.
Einara Zahn and Elie Bou-Zeid
Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2024-272, https://doi.org/10.5194/essd-2024-272, 2024
Revised manuscript accepted for ESSD
Short summary
Short summary
Quantifying water and CO2 exchanges through transpiration, evaporation, photosynthesis, and soil respiration are essential to understand how ecosystems function. We implemented five methods to estimate these fluxes over a five-year period across 47 sites. This is the first dataset representing such a large spatial and temporal coverage of soil and plant exchanges, and it has many potentials applications such as to examine the response of ecosystem to weather extremes and climate change.
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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.
Yuhan Guo, Hongxing Zheng, Yuting Yang, Yanfang Sang, and Congcong Wen
Earth Syst. Sci. Data, 16, 1651–1665, https://doi.org/10.5194/essd-16-1651-2024, https://doi.org/10.5194/essd-16-1651-2024, 2024
Short summary
Short summary
We have provided an inaugural version of the hydrogeomorphic dataset for catchments over the Tibetan Plateau. We first provide the width-function-based instantaneous unit hydrograph (WFIUH) for each HydroBASINS catchment, which can be used to investigate the spatial heterogeneity of hydrological behavior across the Tibetan Plateau. It is expected to facilitate hydrological modeling across the Tibetan Plateau.
Ziyun Yin, Peirong Lin, Ryan Riggs, George H. Allen, Xiangyong Lei, Ziyan Zheng, and Siyu Cai
Earth Syst. Sci. Data, 16, 1559–1587, https://doi.org/10.5194/essd-16-1559-2024, https://doi.org/10.5194/essd-16-1559-2024, 2024
Short summary
Short summary
Large-sample hydrology (LSH) datasets have been the backbone of hydrological model parameter estimation and data-driven machine learning models for hydrological processes. This study complements existing LSH studies by creating a dataset with improved sample coverage, uncertainty estimates, and dynamic descriptions of human activities, which are all crucial to hydrological understanding and modeling.
Pierluigi Claps, Giulia Evangelista, Daniele Ganora, Paola Mazzoglio, and Irene Monforte
Earth Syst. Sci. Data, 16, 1503–1522, https://doi.org/10.5194/essd-16-1503-2024, https://doi.org/10.5194/essd-16-1503-2024, 2024
Short summary
Short summary
FOCA (Italian FlOod and Catchment Atlas) is the first systematic collection of data on Italian river catchments. It comprises geomorphological, soil, land cover, NDVI, climatological and extreme rainfall catchment attributes. FOCA also contains 631 peak and daily discharge time series covering the 1911–2016 period. Using this first nationwide data collection, a wide range of applications, in particular flood studies, can be undertaken within the Italian territory.
Wei Jing Ang, Edward Park, Yadu Pokhrel, Dung Duc Tran, and Ho Huu Loc
Earth Syst. Sci. Data, 16, 1209–1228, https://doi.org/10.5194/essd-16-1209-2024, https://doi.org/10.5194/essd-16-1209-2024, 2024
Short summary
Short summary
Dams have burgeoned in the Mekong, but information on dams is scattered and inconsistent. Up-to-date evaluation of dams is unavailable, and basin-wide hydropower potential has yet to be systematically assessed. We present a comprehensive database of 1055 dams, a spatiotemporal analysis of the dams, and a total hydropower potential of 1 334 683 MW. Considering projected dam development and hydropower potential, the vulnerability and the need for better dam management may be highest in Laos.
Chuanqi He, Ci-Jian Yang, Jens M. Turowski, Richard F. Ott, Jean Braun, Hui Tang, Shadi Ghantous, Xiaoping Yuan, and Gaia Stucky de Quay
Earth Syst. Sci. Data, 16, 1151–1166, https://doi.org/10.5194/essd-16-1151-2024, https://doi.org/10.5194/essd-16-1151-2024, 2024
Short summary
Short summary
The shape of drainage basins and rivers holds significant implications for landscape evolution processes and dynamics. We used a global 90 m resolution topography to obtain ~0.7 million drainage basins with sizes over 50 km2. Our dataset contains the spatial distribution of drainage systems and their morphological parameters, supporting fields such as geomorphology, climatology, biology, ecology, hydrology, and natural hazards.
Jingyu Lin, Peng Wang, Jinzhu Wang, Youping Zhou, Xudong Zhou, Pan Yang, Hao Zhang, Yanpeng Cai, and Zhifeng Yang
Earth Syst. Sci. Data, 16, 1137–1149, https://doi.org/10.5194/essd-16-1137-2024, https://doi.org/10.5194/essd-16-1137-2024, 2024
Short summary
Short summary
Our paper provides a repository comprising over 330 000 observations encompassing daily, weekly, and monthly records of surface water quality spanning the period 1980–2022. It included 18 distinct indicators, meticulously gathered at 2384 monitoring sites, ranging from inland locations to coastal and oceanic areas. This dataset will be very useful for researchers and decision-makers in the fields of hydrology, ecological studies, climate change, policy development, and oceanography.
Aloïs Tilloy, Dominik Paprotny, Stefania Grimaldi, Goncalo Gomes, Alessandra Bianchi, Stefan Lange, Hylke Beck, and Luc Feyen
Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2024-41, https://doi.org/10.5194/essd-2024-41, 2024
Revised manuscript accepted for ESSD
Short summary
Short summary
This article presents a reanalysis of Europe's rivers streamflow for the period 1950–2020, using a state-of-the-art hydrological simulation framework. The dataset, called HERA (Hydrological European ReAnalysis), uses detailed information about the landscape, climate, and human activities to estimate river flow. HERA can be a valuable tool for studying hydrological dynamics, including the impacts of climate change and human activities on European water resources, flood and drought risks.
Ana M. Ricardo, Rui M. L. Ferreira, Alberto Rodrigues da Silva, Jacinto Estima, Jorge Marques, Ivo Gamito, and Alexandre Serra
Earth Syst. Sci. Data, 16, 375–385, https://doi.org/10.5194/essd-16-375-2024, https://doi.org/10.5194/essd-16-375-2024, 2024
Short summary
Short summary
Floods are among the most common natural disasters responsible for severe damages and human losses. Agueda.2016Flood, a synthesis of locally sensed data and numerically produced data, allows complete characterization of the flood event that occurred in February 2016 in the Portuguese Águeda River. The dataset was managed through the RiverCure Portal, a collaborative web platform connected to a validated shallow-water model.
Jiawei Hou, Albert I. J. M. Van Dijk, Luigi J. Renzullo, and Pablo R. Larraondo
Earth Syst. Sci. Data, 16, 201–218, https://doi.org/10.5194/essd-16-201-2024, https://doi.org/10.5194/essd-16-201-2024, 2024
Short summary
Short summary
The GloLakes dataset provides historical and near-real-time time series of relative (i.e. storage change) and absolute (i.e. total stored volume) storage for more than 27 000 lakes worldwide using multiple sources of satellite data, including laser and radar altimetry and optical remote sensing. These data can help us understand the influence of climate variability and anthropogenic activities on water availability and system ecology over the last 4 decades.
Menaka Revel, Xudong Zhou, Prakat Modi, Jean-François Cretaux, Stephane Calmant, and Dai Yamazaki
Earth Syst. Sci. Data, 16, 75–88, https://doi.org/10.5194/essd-16-75-2024, https://doi.org/10.5194/essd-16-75-2024, 2024
Short summary
Short summary
As satellite technology advances, there is an incredible amount of remotely sensed data for observing terrestrial water. Satellite altimetry observations of water heights can be utilized to calibrate and validate large-scale hydrodynamic models. However, because large-scale models are discontinuous, comparing satellite altimetry to predicted water surface elevation is difficult. We developed a satellite altimetry mapping procedure for high-resolution river network data.
Marvin Höge, Martina Kauzlaric, Rosi Siber, Ursula Schönenberger, Pascal Horton, Jan Schwanbeck, Marius Günter Floriancic, Daniel Viviroli, Sibylle Wilhelm, Anna E. Sikorska-Senoner, Nans Addor, Manuela Brunner, Sandra Pool, Massimiliano Zappa, and Fabrizio Fenicia
Earth Syst. Sci. Data, 15, 5755–5784, https://doi.org/10.5194/essd-15-5755-2023, https://doi.org/10.5194/essd-15-5755-2023, 2023
Short summary
Short summary
CAMELS-CH is an open large-sample hydro-meteorological data set that covers 331 catchments in hydrologic Switzerland from 1 January 1981 to 31 December 2020. It comprises (a) daily data of river discharge and water level as well as meteorologic variables like precipitation and temperature; (b) yearly glacier and land cover data; (c) static attributes of, e.g, topography or human impact; and (d) catchment delineations. CAMELS-CH enables water and climate research and modeling at catchment level.
Peter Burek and Mikhail Smilovic
Earth Syst. Sci. Data, 15, 5617–5629, https://doi.org/10.5194/essd-15-5617-2023, https://doi.org/10.5194/essd-15-5617-2023, 2023
Short summary
Short summary
We address an annoying problem every grid-based hydrological model must solve to compare simulated and observed river discharge. First, station locations do not fit the high-resolution river network. We update the database with stations based on a new high-resolution network. Second, station locations do not work with a coarser grid-based network. We use a new basin shape similarity concept for station locations on a coarser grid, reducing the error of assigning stations to the wrong basin.
Najwa Sharaf, Jordi Prats, Nathalie Reynaud, Thierry Tormos, Rosalie Bruel, Tiphaine Peroux, and Pierre-Alain Danis
Earth Syst. Sci. Data, 15, 5631–5650, https://doi.org/10.5194/essd-15-5631-2023, https://doi.org/10.5194/essd-15-5631-2023, 2023
Short summary
Short summary
We present a regional long-term (1959–2020) dataset (LakeTSim) of daily epilimnion and hypolimnion water temperature simulations in 401 French lakes. Overall, less uncertainty is associated with the epilimnion compared to the hypolimnion. LakeTSim is valuable for providing new insights into lake water temperature for assessing the impact of climate change, which is often hindered by the lack of observations, and for decision-making by stakeholders.
Jiabo Yin, Louise J. Slater, Abdou Khouakhi, Le Yu, Pan Liu, Fupeng Li, Yadu Pokhrel, and Pierre Gentine
Earth Syst. Sci. Data, 15, 5597–5615, https://doi.org/10.5194/essd-15-5597-2023, https://doi.org/10.5194/essd-15-5597-2023, 2023
Short summary
Short summary
This study presents long-term (i.e., 1940–2022) and high-resolution (i.e., 0.25°) monthly time series of TWS anomalies over the global land surface. The reconstruction is achieved by using a set of machine learning models with a large number of predictors, including climatic and hydrological variables, land use/land cover data, and vegetation indicators (e.g., leaf area index). Our proposed GTWS-MLrec performs overall as well as, or is more reliable than, previous TWS datasets.
Shanlei Sun, Zaoying Bi, Jingfeng Xiao, Yi Liu, Ge Sun, Weimin Ju, Chunwei Liu, Mengyuan Mu, Jinjian Li, Yang Zhou, Xiaoyuan Li, Yibo Liu, and Haishan Chen
Earth Syst. Sci. Data, 15, 4849–4876, https://doi.org/10.5194/essd-15-4849-2023, https://doi.org/10.5194/essd-15-4849-2023, 2023
Short summary
Short summary
Based on various existing datasets, we comprehensively considered spatiotemporal differences in land surfaces and CO2 effects on plant stomatal resistance to parameterize the Shuttleworth–Wallace model, and we generated a global 5 km ensemble mean monthly potential evapotranspiration (PET) dataset (including potential transpiration PT and soil evaporation PE) during 1982–2015. The new dataset may be used by academic communities and various agencies to conduct various studies.
Wei Wang, La Zhuo, Xiangxiang Ji, Zhiwei Yue, Zhibin Li, Meng Li, Huimin Zhang, Rong Gao, Chenjian Yan, Ping Zhang, and Pute Wu
Earth Syst. Sci. Data, 15, 4803–4827, https://doi.org/10.5194/essd-15-4803-2023, https://doi.org/10.5194/essd-15-4803-2023, 2023
Short summary
Short summary
The consumptive water footprint of crop production (WFCP) measures blue and green evapotranspiration of either irrigated or rainfed crops in time and space. A gridded monthly WFCP dataset for China is established. There are four improvements from existing datasets: (i) distinguishing water supply modes and irrigation techniques, (ii) distinguishing evaporation and transpiration, (iii) consisting of both total and unit WFCP, and (iv) providing benchmarks for unit WFCP by climatic zones.
Emma L. Robinson, Matthew J. Brown, Alison L. Kay, Rosanna A. Lane, Rhian Chapman, Victoria A. Bell, and Eleanor M. Blyth
Earth Syst. Sci. Data, 15, 4433–4461, https://doi.org/10.5194/essd-15-4433-2023, https://doi.org/10.5194/essd-15-4433-2023, 2023
Short summary
Short summary
This work presents two new Penman–Monteith potential evaporation datasets for the UK, calculated with the same methodology applied to historical climate data (Hydro-PE HadUK-Grid) and an ensemble of future climate projections (Hydro-PE UKCP18 RCM). Both include an optional correction for evaporation of rain that lands on the surface of vegetation. The historical data are consistent with existing PE datasets, and the future projections include effects of rising atmospheric CO2 on vegetation.
Xinyu Chen, Liguang Jiang, Yuning Luo, and Junguo Liu
Earth Syst. Sci. Data, 15, 4463–4479, https://doi.org/10.5194/essd-15-4463-2023, https://doi.org/10.5194/essd-15-4463-2023, 2023
Short summary
Short summary
River flow is experiencing changes under the impacts of climate change and human activities. For example, flood events are occurring more often and are more destructive in many places worldwide. To deal with such issues, hydrologists endeavor to understand the features of extreme events as well as other hydrological changes. One key approach is analyzing flow characteristics, represented by hydrological indices. Building such a comprehensive global large-sample dataset is essential.
Tobias L. Hohenbrink, Conrad Jackisch, Wolfgang Durner, Kai Germer, Sascha C. Iden, Janis Kreiselmeier, Frederic Leuther, Johanna C. Metzger, Mahyar Naseri, and Andre Peters
Earth Syst. Sci. Data, 15, 4417–4432, https://doi.org/10.5194/essd-15-4417-2023, https://doi.org/10.5194/essd-15-4417-2023, 2023
Short summary
Short summary
The article describes a collection of 572 data sets of soil water retention and unsaturated hydraulic conductivity data measured with state-of-the-art laboratory methods. Furthermore, the data collection contains basic soil properties such as soil texture and organic carbon content. We expect that the data will be useful for various important purposes, for example, the development of soil hydraulic property models and related pedotransfer functions.
Sebastien Klotz, Caroline Le Bouteiller, Nicolle Mathys, Firmin Fontaine, Xavier Ravanat, Jean-Emmanuel Olivier, Frédéric Liébault, Hugo Jantzi, Patrick Coulmeau, Didier Richard, Jean-Pierre Cambon, and Maurice Meunier
Earth Syst. Sci. Data, 15, 4371–4388, https://doi.org/10.5194/essd-15-4371-2023, https://doi.org/10.5194/essd-15-4371-2023, 2023
Short summary
Short summary
Mountain badlands are places of intense erosion. They deliver large amounts of sediment to river systems, with consequences for hydropower sustainability, habitat quality and biodiversity, and flood hazard and river management. Draix-Bleone Observatory was created in 1983 to understand and quantify sediment delivery from such badland areas. Our paper describes how water and sediment fluxes have been monitored for almost 40 years in the small mountain catchments of this observatory.
Gopi Goteti
Earth Syst. Sci. Data, 15, 4389–4415, https://doi.org/10.5194/essd-15-4389-2023, https://doi.org/10.5194/essd-15-4389-2023, 2023
Short summary
Short summary
Data on river gauging stations, river basin boundaries and river flow paths are critical for hydrological analyses, but existing data for India's river basins have limited availability and reliability. This work fills the gap by building a new dataset. Data for 645 stations in 15 basins of India were compiled and checked against global data sources; data were supplemented with additional information where needed. This dataset will serve as a reliable building block in hydrological analyses.
Md Safat Sikder, Jida Wang, George H. Allen, Yongwei Sheng, Dai Yamazaki, Chunqiao Song, Meng Ding, Jean-François Crétaux, and Tamlin M. Pavelsky
Earth Syst. Sci. Data, 15, 3483–3511, https://doi.org/10.5194/essd-15-3483-2023, https://doi.org/10.5194/essd-15-3483-2023, 2023
Short summary
Short summary
We introduce Lake-TopoCat to reveal detailed lake hydrography information. It contains the location of lake outlets, the boundary of lake catchments, and a wide suite of attributes that depict detailed lake drainage relationships. It was constructed using lake boundaries from a global lake dataset, with the help of high-resolution hydrography data. This database may facilitate a variety of applications including water quality, agriculture and fisheries, and integrated lake–river modeling.
Maik Heistermann, Till Francke, Lena Scheiffele, Katya Dimitrova Petrova, Christian Budach, Martin Schrön, Benjamin Trost, Daniel Rasche, Andreas Güntner, Veronika Döpper, Michael Förster, Markus Köhli, Lisa Angermann, Nikolaos Antonoglou, Manuela Zude-Sasse, and Sascha E. Oswald
Earth Syst. Sci. Data, 15, 3243–3262, https://doi.org/10.5194/essd-15-3243-2023, https://doi.org/10.5194/essd-15-3243-2023, 2023
Short summary
Short summary
Cosmic-ray neutron sensing (CRNS) allows for the non-invasive estimation of root-zone soil water content (SWC). The signal observed by a single CRNS sensor is influenced by the SWC in a radius of around 150 m (the footprint). Here, we have put together a cluster of eight CRNS sensors with overlapping footprints at an agricultural research site in north-east Germany. That way, we hope to represent spatial SWC heterogeneity instead of retrieving just one average SWC estimate from a single sensor.
Benjamin M. Kitambo, Fabrice Papa, Adrien Paris, Raphael M. Tshimanga, Frederic Frappart, Stephane Calmant, Omid Elmi, Ayan Santos Fleischmann, Melanie Becker, Mohammad J. Tourian, Rômulo A. Jucá Oliveira, and Sly Wongchuig
Earth Syst. Sci. Data, 15, 2957–2982, https://doi.org/10.5194/essd-15-2957-2023, https://doi.org/10.5194/essd-15-2957-2023, 2023
Short summary
Short summary
The surface water storage (SWS) in the Congo River basin (CB) remains unknown. In this study, the multi-satellite and hypsometric curve approaches are used to estimate SWS in the CB over 1992–2015. The results provide monthly SWS characterized by strong variability with an annual mean amplitude of ~101 ± 23 km3. The evaluation of SWS against independent datasets performed well. This SWS dataset contributes to the better understanding of the Congo basin’s surface hydrology using remote sensing.
Natalie Lützow, Georg Veh, and Oliver Korup
Earth Syst. Sci. Data, 15, 2983–3000, https://doi.org/10.5194/essd-15-2983-2023, https://doi.org/10.5194/essd-15-2983-2023, 2023
Short summary
Short summary
Glacier lake outburst floods (GLOFs) are a prominent natural hazard, and climate change may change their magnitude, frequency, and impacts. A global, literature-based GLOF inventory is introduced, entailing 3151 reported GLOFs. The reporting density varies temporally and regionally, with most cases occurring in NW North America. Since 1900, the number of yearly documented GLOFs has increased 6-fold. However, many GLOFs have incomplete records, and we call for a systematic reporting protocol.
Hanieh Seyedhashemi, Florentina Moatar, Jean-Philippe Vidal, and Dominique Thiéry
Earth Syst. Sci. Data, 15, 2827–2839, https://doi.org/10.5194/essd-15-2827-2023, https://doi.org/10.5194/essd-15-2827-2023, 2023
Short summary
Short summary
This paper presents a past and future dataset of daily time series of discharge and stream temperature for 52 278 reaches over the Loire River basin (100 000 km2) in France, using thermal and hydrological models. Past data are provided over 1963–2019. Future data are available over the 1976–2100 period under different future climate change models (warm and wet, intermediate, and hot and dry) and scenarios (optimistic, intermediate, and pessimistic).
Youjiang Shen, Karina Nielsen, Menaka Revel, Dedi Liu, and Dai Yamazaki
Earth Syst. Sci. Data, 15, 2781–2808, https://doi.org/10.5194/essd-15-2781-2023, https://doi.org/10.5194/essd-15-2781-2023, 2023
Short summary
Short summary
Res-CN fills a gap in a comprehensive and extensive dataset of reservoir-catchment characteristics for 3254 Chinese reservoirs with 512 catchment-level attributes and significantly enhanced spatial and temporal coverage (e.g., 67 % increase in water level and 225 % in storage anomaly) of time series of reservoir water level (data available for 20 % of 3254 reservoirs), water area (99 %), storage anomaly (92 %), and evaporation (98 %), supporting a wide range of applications and disciplines.
Hui Zheng, Wenli Fei, Zong-Liang Yang, Jiangfeng Wei, Long Zhao, Lingcheng Li, and Shu Wang
Earth Syst. Sci. Data, 15, 2755–2780, https://doi.org/10.5194/essd-15-2755-2023, https://doi.org/10.5194/essd-15-2755-2023, 2023
Short summary
Short summary
An ensemble of evapotranspiration, runoff, and water storage is estimated here using the Noah-MP land surface model by perturbing model parameterization schemes. The data could be beneficial for monitoring and understanding the variability of water resources. Model developers could also gain insights by intercomparing the ensemble members.
Alison L. Kay, Victoria A. Bell, Helen N. Davies, Rosanna A. Lane, and Alison C. Rudd
Earth Syst. Sci. Data, 15, 2533–2546, https://doi.org/10.5194/essd-15-2533-2023, https://doi.org/10.5194/essd-15-2533-2023, 2023
Short summary
Short summary
Climate change will affect the water cycle, including river flows and soil moisture. We have used both observational data (1980–2011) and the latest UK climate projections (1980–2080) to drive a national-scale grid-based hydrological model. The data, covering Great Britain and Northern Ireland, suggest potential future decreases in summer flows, low flows, and summer/autumn soil moisture, and possible future increases in winter and high flows. Society must plan how to adapt to such impacts.
Jamie Hannaford, Jonathan D. Mackay, Matthew Ascott, Victoria A. Bell, Thomas Chitson, Steven Cole, Christian Counsell, Mason Durant, Christopher R. Jackson, Alison L. Kay, Rosanna A. Lane, Majdi Mansour, Robert Moore, Simon Parry, Alison C. Rudd, Michael Simpson, Katie Facer-Childs, Stephen Turner, John R. Wallbank, Steven Wells, and Amy Wilcox
Earth Syst. Sci. Data, 15, 2391–2415, https://doi.org/10.5194/essd-15-2391-2023, https://doi.org/10.5194/essd-15-2391-2023, 2023
Short summary
Short summary
The eFLaG dataset is a nationally consistent set of projections of future climate change impacts on hydrology. eFLaG uses the latest available UK climate projections (UKCP18) run through a series of computer simulation models which enable us to produce future projections of river flows, groundwater levels and groundwater recharge. These simulations are designed for use by water resource planners and managers but could also be used for a wide range of other purposes.
Fabian A. Gomez, Sang-Ki Lee, Charles A. Stock, Andrew C. Ross, Laure Resplandy, Samantha A. Siedlecki, Filippos Tagklis, and Joseph E. Salisbury
Earth Syst. Sci. Data, 15, 2223–2234, https://doi.org/10.5194/essd-15-2223-2023, https://doi.org/10.5194/essd-15-2223-2023, 2023
Short summary
Short summary
We present a river chemistry and discharge dataset for 140 rivers in the United States, which integrates information from the Water Quality Database of the US Geological Survey (USGS), the USGS’s Surface-Water Monthly Statistics for the Nation, and the U.S. Army Corps of Engineers. This dataset includes dissolved inorganic carbon and alkalinity, two key properties to characterize the carbonate system, as well as nutrient concentrations, such as nitrate, phosphate, and silica.
Yufang Zhang, Shunlin Liang, Han Ma, Tao He, Qian Wang, Bing Li, Jianglei Xu, Guodong Zhang, Xiaobang Liu, and Changhao Xiong
Earth Syst. Sci. Data, 15, 2055–2079, https://doi.org/10.5194/essd-15-2055-2023, https://doi.org/10.5194/essd-15-2055-2023, 2023
Short summary
Short summary
Soil moisture observations are important for a range of earth system applications. This study generated a long-term (2000–2020) global seamless soil moisture product with both high spatial and temporal resolutions (1 km, daily) using an XGBoost model and multisource datasets. Evaluation of this product against dense in situ soil moisture datasets and microwave soil moisture products showed that this product has reliable accuracy and more complete spatial coverage.
Heidi Kreibich, Kai Schröter, Giuliano Di Baldassarre, Anne F. Van Loon, Maurizio Mazzoleni, Guta Wakbulcho Abeshu, Svetlana Agafonova, Amir AghaKouchak, Hafzullah Aksoy, Camila Alvarez-Garreton, Blanca Aznar, Laila Balkhi, Marlies H. Barendrecht, Sylvain Biancamaria, Liduin Bos-Burgering, Chris Bradley, Yus Budiyono, Wouter Buytaert, Lucinda Capewell, Hayley Carlson, Yonca Cavus, Anaïs Couasnon, Gemma Coxon, Ioannis Daliakopoulos, Marleen C. de Ruiter, Claire Delus, Mathilde Erfurt, Giuseppe Esposito, Didier François, Frédéric Frappart, Jim Freer, Natalia Frolova, Animesh K. Gain, Manolis Grillakis, Jordi Oriol Grima, Diego A. Guzmán, Laurie S. Huning, Monica Ionita, Maxim Kharlamov, Dao Nguyen Khoi, Natalie Kieboom, Maria Kireeva, Aristeidis Koutroulis, Waldo Lavado-Casimiro, Hong-Yi Li, Maria Carmen LLasat, David Macdonald, Johanna Mård, Hannah Mathew-Richards, Andrew McKenzie, Alfonso Mejia, Eduardo Mario Mendiondo, Marjolein Mens, Shifteh Mobini, Guilherme Samprogna Mohor, Viorica Nagavciuc, Thanh Ngo-Duc, Huynh Thi Thao Nguyen, Pham Thi Thao Nhi, Olga Petrucci, Nguyen Hong Quan, Pere Quintana-Seguí, Saman Razavi, Elena Ridolfi, Jannik Riegel, Md Shibly Sadik, Nivedita Sairam, Elisa Savelli, Alexey Sazonov, Sanjib Sharma, Johanna Sörensen, Felipe Augusto Arguello Souza, Kerstin Stahl, Max Steinhausen, Michael Stoelzle, Wiwiana Szalińska, Qiuhong Tang, Fuqiang Tian, Tamara Tokarczyk, Carolina Tovar, Thi Van Thu Tran, Marjolein H. J. van Huijgevoort, Michelle T. H. van Vliet, Sergiy Vorogushyn, Thorsten Wagener, Yueling Wang, Doris E. Wendt, Elliot Wickham, Long Yang, Mauricio Zambrano-Bigiarini, and Philip J. Ward
Earth Syst. Sci. Data, 15, 2009–2023, https://doi.org/10.5194/essd-15-2009-2023, https://doi.org/10.5194/essd-15-2009-2023, 2023
Short summary
Short summary
As the adverse impacts of hydrological extremes increase in many regions of the world, a better understanding of the drivers of changes in risk and impacts is essential for effective flood and drought risk management. We present a dataset containing data of paired events, i.e. two floods or two droughts that occurred in the same area. The dataset enables comparative analyses and allows detailed context-specific assessments. Additionally, it supports the testing of socio-hydrological models.
Rogier van der Velde, Harm-Jan F. Benninga, Bas Retsios, Paul C. Vermunt, and M. Suhyb Salama
Earth Syst. Sci. Data, 15, 1889–1910, https://doi.org/10.5194/essd-15-1889-2023, https://doi.org/10.5194/essd-15-1889-2023, 2023
Short summary
Short summary
From 2009, a network of 20 profile soil moisture and temperature monitoring stations has been operational in the Twente region, east of the Netherlands. In addition, field campaigns have been conducted covering four growing seasons during which soil moisture was measured near 12 monitoring stations. We describe the monitoring network and field campaigns, and we provide an overview of open third-party datasets that may support the use of the Twente datasets.
Cited articles
Baker, J. C. A., Garcia-Carreras, L., Gloor, M., Marsham, J. H., Buermann, W., da Rocha, H. R., Nobre, A. D., de Araujo, A. C., and Spracklen, D. V.: Evapotranspiration in the Amazon: spatial patterns, seasonality, and recent trends in observations, reanalysis, and climate models, Hydrol. Earth Syst. Sci., 25, 2279–2300, https://doi.org/10.5194/hess-25-2279-2021, 2021.
Barraza Bernadas, V., Grings, F., Restrepo-Coupe, N., and Huete, A.: Comparison of the performance of latent heat flux products over southern hemisphere forest ecosystems: estimating latent heat flux error structure using in situ measurements and the triple collocation method, Int. J. Remote Sens., 39, 6300–6315, 2018.
Bates, J. M. and Granger, C. W.: The combination of forecasts, J. Oper. Res. Soc., 20, 451–468, 1969.
Chen, Z., Zhu, Z., Jiang, H., and Sun, S.: Estimating daily reference evapotranspiration based on limited meteorological data using deep learning and classical machine learning methods, J. Hydrol., 591, 125286, https://doi.org/10.1016/j.jhydrol.2020.125286, 2020.
De Lannoy, G. J., Houser, P. R., Verhoest, N. E., Pauwels, V. R., and Gish, T. J.: Upscaling of point soil moisture measurements to field averages at the OPE3 test site, J. Hydrol., 343, 1–11, 2007.
Deng, X., Zhu, L., Wang, H., Zhang, X., Tong, C., Li, S., and Wang, K.: Triple Collocation Analysis and In Situ Validation of the CYGNSS Soil Moisture Product, IEEE J. Sel. Top. Appl., 16, 1883–1899, https://doi.org/10.1109/jstars.2023.3235111, 2023.
Dong, J. and Crow, W. T.: An Improved Triple Collocation Analysis Algorithm for Decomposing Autocorrelated and White Soil Moisture Retrieval Errors, J. Geophys. Res.-Atmos., 122, 13081–13094, https://doi.org/10.1002/2017jd027387, 2017.
Dong, J., Crow, W. T., Duan, Z., Wei, L., and Lu, Y.: A double instrumental variable method for geophysical product error estimation, Remote Sens. Environ., 225, 217–228, https://doi.org/10.1016/j.rse.2019.03.003, 2019.
Dong, J., Wei, L., Chen, X., Duan, Z., and Lu, Y.: An instrument variable based algorithm for estimating cross-correlated hydrological remote sensing errors, J. Hydrol., 581, 124413, https://doi.org/10.1016/j.jhydrol.2019.124413, 2020a.
Dong, J., Lei, F., and Wei, L.: Triple Collocation Based Multi-Source Precipitation Merging, Front. Water, 2, 498793, https://doi.org/10.3389/frwa.2020.00001, 2020b.
Dong, J., Crow, W. T., Chen, X., Tangdamrongsub, N., Gao, M., Sun, S., Qiu, J., Wei, L., Gao, H., and Duan, Z.: Statistical uncertainty analysis-based precipitation merging (SUPER): A new framework for improved global precipitation estimation, Remote Sens. Environ., 283, 113299, https://doi.org/10.1016/j.rse.2022.113299, 2022.
Draper, C., Reichle, R., de Jeu, R., Naeimi, V., Parinussa, R., and Wagner, W.: Estimating root mean square errors in remotely sensed soil moisture over continental scale domains, Remote Sens. Environ., 137, 288–298, 2013.
Duan, Z., Duggan, E., Chen, C., Gao, H., Dong, J., and Liu, J.: Comparison of traditional method and triple collocation analysis for evaluation of multiple gridded precipitation products across Germany, J. Hydrometeorol., 22, 2983–2999, https://doi.org/10.1175/JHM-D-21-0049.1, 2021.
ECMWF: In IFS documentation CY40R1 Part IV: Physical Processes, ECMWF, Reading, UK, 111–113, https://doi.org/10.21957/f56vvey1x, 2014.
Ershadi, A., McCabe, M. F., Evans, J. P., Chaney, N. W., and Wood, E. F.: Multi-site evaluation of terrestrial evaporation models using FLUXNET data, Agr. Forest Meteorol., 187, 46–61, https://doi.org/10.1016/j.agrformet.2013.11.008, 2014.
Feng, Y., Cui, N., Zhao, L., Hu, X., and Gong, D.: Comparison of ELM, GANN, WNN and empirical models for estimating reference evapotranspiration in humid region of Southwest China, J. Hydrol., 536, 376–383, https://doi.org/10.1016/j.jhydrol.2016.02.053, 2016.
Gan, R., Zhang, Y., Shi, H., Yang, Y., Eamus, D., Cheng, L., Chiew, F. H., and Yu, Q.: Use of satellite leaf area index estimating evapotranspiration and gross assimilation for Australian ecosystems, Ecohydrology, 11, e1974, https://doi.org/10.1002/eco.1974, 2018.
Gentine, P., Massmann, A., Lintner, B. R., Hamed Alemohammad, S., Fu, R., Green, J. K., Kennedy, D., and Vilà-Guerau de Arellano, J.: Land–atmosphere interactions in the tropics – a review, Hydrol. Earth Syst. Sci., 23, 4171–4197, https://doi.org/10.5194/hess-23-4171-2019, 2019.
Gruber, A., Su, C., Crow, W. T., Zwieback, S., Dorigo, W., and Wagner, W.: Estimating error cross-correlations in soil moisture data sets using extended collocation analysis, J. Geophys. Res.-Atmos., 121, 1208–1219, 2016a.
Gruber, A., Su, C.-H., Zwieback, S., Crow, W., Dorigo, W., and Wagner, W.: Recent advances in (soil moisture) triple collocation analysis, Int. J. Appl. Earth Obs., 45, 200–211, https://doi.org/10.1016/j.jag.2015.09.002, 2016b.
Gruber, A., Dorigo, W. A., Crow, W., and Wagner, W.: Triple Collocation-Based Merging of Satellite Soil Moisture Retrievals, IEEE Ts. Geosci. Remote, 55, 6780–6792, https://doi.org/10.1109/TGRS.2017.2734070, 2017.
Gruber, A., Scanlon, T., van der Schalie, R., Wagner, W., and Dorigo, W.: Evolution of the ESA CCI Soil Moisture climate data records and their underlying merging methodology, Earth Syst. Sci. Data, 11, 717–739, https://doi.org/10.5194/essd-11-717-2019, 2019.
Gruber, A., De Lannoy, G., Albergel, C., Al-Yaari, A., Brocca, L., Calvet, J. C., Colliander, A., Cosh, M., Crow, W., Dorigo, W., Draper, C., Hirschi, M., Kerr, Y., Konings, A., Lahoz, W., McColl, K., Montzka, C., Muñoz-Sabater, J., Peng, J., Reichle, R., Richaume, P., Rüdiger, C., Scanlon, T., van der Schalie, R., Wigneron, J. P., and Wagner, W.: Validation practices for satellite soil moisture retrievals: What are (the) errors?, Remote Sens. Environ., 244, 111806, https://doi.org/10.1016/j.rse.2020.111806, 2020.
Gupta, H. V., Kling, H., Yilmaz, K. K., and Martinez, G. F.: Decomposition of the mean squared error and NSE performance criteria: Implications for improving hydrological modelling, J. Hydrol., 377, 80–91, 2009.
Han, S. and Tian, F.: A review of the complementary principle of evaporation: from the original linear relationship to generalized nonlinear functions, Hydrol. Earth Syst. Sci., 24, 2269–2285, https://doi.org/10.5194/hess-24-2269-2020, 2020.
Hao, Y., Baik, J., and Choi, M.: Combining generalized complementary relationship models with the Bayesian Model Averaging method to estimate actual evapotranspiration over China, Agr. Forest Meteorol., 279, 107759, https://doi.org/10.1016/j.agrformet.2019.107759, 2019.
Hersbach, H., Bell, B., Berrisford, P., Hirahara, S., Horányi, A., Muñoz-Sabater, J., Nicolas, J., Peubey, C., Radu, R., Schepers, D., Simmons, A., Soci, C., Abdalla, S., Abellan, X., Balsamo, G., Bechtold, P., Biavati, G., Bidlot, J., Bonavita, M., Chiara, G., Dahlgren, P., Dee, D., Diamantakis, M., Dragani, R., Flemming, J., Forbes, R., Fuentes, M., Geer, A., Haimberger, L., Healy, S., Hogan, R. J., Hólm, E., Janisková, M., Keeley, S., Laloyaux, P., Lopez, P., Lupu, C., Radnoti, G., Rosnay, P., Rozum, I., Vamborg, F., Villaume, S., and Thépaut, J.: The ERA5 global reanalysis, Q. J. Roy. Meteor. Soc., 146, 1999–2049, https://doi.org/10.1002/qj.3803, 2020.
Hoareau, N., Portabella, M., Lin, W., Ballabrera-Poy, J., and Turiel, A.: Error characterization of sea surface salinity products using triple collocation analysis, IEEE T. Geosci. Remote, 56, 5160–5168, 2018.
Jia, Y., Li, C., Yang, H., Yang, W., and Liu, Z.: Assessments of three evapotranspiration products over China using extended triple collocation and water balance methods, J. Hydrol., 614, 128594, https://doi.org/10.1016/j.jhydrol.2022.128594, 2022.
Jiang, C. and Ryu, Y.: Multi-scale evaluation of global gross primary productivity and evapotranspiration products derived from Breathing Earth System Simulator (BESS), Remote Sens. Environ., 186, 528–547, 2016.
Jiang, C., Ryu, Y., Fang, H., Myneni, R., Claverie, M., and Zhu, Z.: Inconsistencies of interannual variability and trends in long-term satellite leaf area index products, Glob. Chang Biol., 23, 4133–4146, https://doi.org/10.1111/gcb.13787, 2017.
Jiang, C., Guan, K., Pan, M., Ryu, Y., Peng, B., and Wang, S.: BESS-STAIR: a framework to estimate daily, 30 m, and all-weather crop evapotranspiration using multi-source satellite data for the US Corn Belt, Hydrol. Earth Syst. Sci., 24, 1251–1273, https://doi.org/10.5194/hess-24-1251-2020, 2020.
Jiménez, C., Prigent, C., Mueller, B., Seneviratne, S. I., McCabe, M. F., Wood, E. F., Rossow, W. B., Balsamo, G., Betts, A. K., Dirmeyer, P. A., Fisher, J. B., Jung, M., Kanamitsu, M., Reichle, R. H., Reichstein, M., Rodell, M., Sheffield, J., Tu, K., and Wang, K.: Global intercomparison of 12 land surface heat flux estimates, J. Geophys. Res., 116, d014545, https://doi.org/10.1029/2010jd014545, 2011.
Jung, M., Koirala, S., Weber, U., Ichii, K., Gans, F., Camps-Valls, G., Papale, D., Schwalm, C., Tramontana, G., and Reichstein, M.: The FLUXCOM ensemble of global land-atmosphere energy fluxes, Sci. Data, 6, 74, https://doi.org/10.1038/s41597-019-0076-8, 2019.
Khan, M. S., Liaqat, U. W., Baik, J., and Choi, M.: Stand-alone uncertainty characterization of GLEAM, GLDAS and MOD16 evapotranspiration products using an extended triple collocation approach, Agr. Forest Meteorol., 252, 256–268, https://doi.org/10.1016/j.agrformet.2018.01.022, 2018.
Kim, S., Pham, H. T., Liu, Y. Y., Marshall, L., and Sharma, A.: Improving the Combination of Satellite Soil Moisture Data Sets by Considering Error Cross Correlation: A Comparison Between Triple Collocation (TC) and Extended Double Instrumental Variable (EIVD) Alternatives, IEEE T. Geosci. Remote, 59, 7285–7295, https://doi.org/10.1109/tgrs.2020.3032418, 2021a.
Kim, S., Sharma, A., Liu, Y. Y., and Young, S. I.: Rethinking satellite data merging: from averaging to SNR optimization, IEEE T. Geosci. Remote, 60, 1–15, 2021b.
Kling, H., Fuchs, M., and Paulin, M.: Runoff conditions in the upper Danube basin under an ensemble of climate change scenarios, J. Hydrol., 424–425, 264–277, https://doi.org/10.1016/j.jhydrol.2012.01.011, 2012.
Knauer, J., Zaehle, S., Medlyn, B. E., Reichstein, M., Williams, C. A., Migliavacca, M., De Kauwe, M. G., Werner, C., Keitel, C., Kolari, P., Limousin, J. M., and Linderson, M. L.: Towards physiologically meaningful water-use efficiency estimates from eddy covariance data, Glob. Chang Biol., 24, 694–710, https://doi.org/10.1111/gcb.13893, 2018.
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.
Koster, R. D., Liu, Q., Reichle, R. H., and Huffman, G. J.: Improved Estimates of Pentad Precipitation Through the Merging of Independent Precipitation Data Sets, Water Resour. Res., 57, e2021WR030330, https://doi.org/10.1029/2021wr030330, 2021.
Leuning, R., Zhang, Y., Rajaud, A., Cleugh, H., and Tu, K.: A simple surface conductance model to estimate regional evaporation using MODIS leaf area index and the Penman-Monteith equation, Water Resour. Res., 44, W10419, https://doi.org/10.1029/2007WR006562, 2008.
Leuning, R., Zhang, Y. Q., Rajaud, A., Cleugh, H., and Tu, K.: Correction to “A simple surface conductance model to estimate regional evaporation using MODIS leaf area index and the Penman-Monteith equation,” Water Resour. Res., 45, W01701, https://doi.org/10.1029/2008wr007631, 2009.
Li, B., Rodell, M., Kumar, S., Beaudoing, H. K., Getirana, A., Zaitchik, B. F., Goncalves, L. G., Cossetin, C., Bhanja, S., Mukherjee, A., Tian, S., Tangdamrongsub, N., Long, D., Nanteza, J., Lee, J., Policelli, F., Goni, I. B., Daira, D., Bila, M., Lannoy, G., Mocko, D., Steele-Dunne, S. C., Save, H., and Bettadpur, S.: Global GRACE Data Assimilation for Groundwater and Drought Monitoring: Advances and Challenges, Water Resour. Res., 55, 7564–7586, https://doi.org/10.1029/2018WR024618, 2019.
Li, C., Tang, G., and Hong, Y.: Cross-evaluation of ground-based, multi-satellite and reanalysis precipitation products: Applicability of the Triple Collocation method across Mainland China, J. Hydrol., 562, 71–83, https://doi.org/10.1016/j.jhydrol.2018.04.039, 2018.
Li, C., Yang, H., Yang, W., Liu, Z., Jia, Y., Li, S., and Yang, D.: Error Characterization of Global Land Evapotranspiration Products: Collocation-based approach, J. Hydrol., 612, 128102, https://doi.org/10.1016/j.jhydrol.2022.128102, 2022.
Li, C., Liu, Z., Tu, Z., Shen, J., He, Y., and Yang, H.: Assessment of global gridded transpiration products using the extended instrumental variable technique (EIVD), J. Hydrol., 623, 129880, https://doi.org/10.1016/j.jhydrol.2023.129880, 2023a.
Li, C., Liu, Z., Yang, W., Tu, Z., Han, J., Sien, L., and Hanbo, Y.: CAMELE: Collocation-Analyzed Multi-source Ensembled Land Evapotranspiration Data, Zenodo [data set], https://doi.org/10.5281/zenodo.8047038, 2023b.
Li, X., Gentine, P., Lin, C., Zhou, S., Sun, Z., Zheng, Y., Liu, J., and Zheng, C.: A simple and objective method to partition evapotranspiration into transpiration and evaporation at eddy-covariance sites, Agr. Forest Meteorol., 265, 171–182, https://doi.org/10.1016/j.agrformet.2018.11.017, 2019.
Li, X., Zhang, W., Vermeulen, A., Dong, J., and Duan, Z.: Triple collocation-based merging of multi-source gridded evapotranspiration data in the Nordic Region, Agr. Forest Meteorol., 335, 109451, https://doi.org/10.1016/j.agrformet.2023.109451, 2023.
Lian, X., Piao, S., Huntingford, C., Li, Y., Zeng, Z., Wang, X., Ciais, P., McVicar, T. R., Peng, S., Ottlé, C., Yang, H., Yang, Y., Zhang, Y., and Wang, T.: Partitioning global land evapotranspiration using CMIP5 models constrained by observations, Nat. Clim. Change, 8, 640–646, https://doi.org/10.1038/s41558-018-0207-9, 2018.
Lin, C., Gentine, P., Huang, Y., Guan, K., Kimm, H., and Zhou, S.: Diel ecosystem conductance response to vapor pressure deficit is suboptimal and independent of soil moisture, Agr. Forest Meteorol., 250, 24–34, 2018.
Loveland, T. R., Zhu, Z., Ohlen, D. O., Brown, J. F., Reed, B. C., and Yang, L.: An analysis of the IGBP global land-cover characterization process, Photogramm. Eng. Remote S., 65, 1021–1032, 1999.
Lu, J., Wang, G., Chen, T., Li, S., Hagan, D. F. T., Kattel, G., Peng, J., Jiang, T., and Su, B.: A harmonized global land evaporation dataset from model-based products covering 1980–2017, Earth Syst. Sci. Data, 13, 5879–5898, https://doi.org/10.5194/essd-13-5879-2021, 2021.
Ma, N., Szilagyi, J., and Jozsa, J.: Benchmarking large-scale evapotranspiration estimates: A perspective from a calibration-free complementary relationship approach and FLUXCOM, J. Hydrol., 590, 125221, https://doi.org/10.1016/j.jhydrol.2020.125221, 2020.
Majozi, N. P., Mannaerts, C. M., Ramoelo, A., Mathieu, R., Nickless, A., and Verhoef, W.: Analysing surface energy balance closure and partitioning over a semi-arid savanna FLUXNET site in Skukuza, Kruger National Park, South Africa, Hydrol. Earth Syst. Sci., 21, 3401–3415, https://doi.org/10.5194/hess-21-3401-2017, 2017.
Martens, B., Miralles, D. G., Lievens, H., van der Schalie, R., de Jeu, R. A. M., Fernández-Prieto, D., Beck, H. E., Dorigo, W. A., and Verhoest, N. E. C.: GLEAM v3: satellite-based land evaporation and root-zone soil moisture, Geosci. Model Dev., 10, 1903–1925, https://doi.org/10.5194/gmd-10-1903-2017, 2017.
McColl, K. A., Vogelzang, J., Konings, A. G., Entekhabi, D., Piles, M., and Stoffelen, A.: Extended triple collocation: Estimating errors and correlation coefficients with respect to an unknown target, Geophys. Res. Lett., 41, 6229–6236, https://doi.org/10.1002/2014gl061322, 2014.
Medlyn, B. E., De Kauwe, M. G., Lin, Y. S., Knauer, J., Duursma, R. A., Williams, C. A., Arneth, A., Clement, R., Isaac, P., Limousin, J. M., Linderson, M. L., Meir, P., Martin-StPaul, N., and Wingate, L.: How do leaf and ecosystem measures of water-use efficiency compare?, New Phytol., 216, 758–770, https://doi.org/10.1111/nph.14626, 2017.
Ming, W., Ji, X., Zhang, M., Li, Y., Liu, C., Wang, Y., and Li, J.: A Hybrid Triple Collocation-Deep Learning Approach for Improving Soil Moisture Estimation from Satellite and Model-Based Data, Remote Sens., 14, 1744, https://doi.org/10.3390/rs14071744, 2022.
Miralles, D. G., De Jeu, R. A. M., Gash, J. H., Holmes, T. R. H., and Dolman, A. J.: Magnitude and variability of land evaporation and its components at the global scale, Hydrol. Earth Syst. Sci., 15, 967–981, https://doi.org/10.5194/hess-15-967-2011, 2011.
Miralles, D. G., Gentine, P., Seneviratne, S. I., and Teuling, A. J.: Land-atmospheric feedbacks during droughts and heatwaves: state of the science and current challenges, Ann. NY Acad. Sci., 1436, 19–35, https://doi.org/10.1111/nyas.13912, 2019.
Mu, Q., Zhao, M., and Running, S. W.: Improvements to a MODIS global terrestrial evapotranspiration algorithm, Remote Sens. Environ., 115, 1781–1800, 2011.
Muñoz-Sabater, J., Dutra, E., Agustí-Panareda, A., Albergel, C., Arduini, G., Balsamo, G., Boussetta, S., Choulga, M., Harrigan, S., Hersbach, H., Martens, B., Miralles, D. G., Piles, M., Rodríguez-Fernández, N. J., Zsoter, E., Buontempo, C., and Thépaut, J.-N.: ERA5-Land: a state-of-the-art global reanalysis dataset for land applications, Earth Syst. Sci. Data, 13, 4349–4383, https://doi.org/10.5194/essd-13-4349-2021, 2021.
Pan, S., Pan, N., Tian, H., Friedlingstein, P., Sitch, S., Shi, H., Arora, V. K., Haverd, V., Jain, A. K., Kato, E., Lienert, S., Lombardozzi, D., Nabel, J. E. M. S., Ottlé, C., Poulter, B., Zaehle, S., and Running, S. W.: Evaluation of global terrestrial evapotranspiration using state-of-the-art approaches in remote sensing, machine learning and land surface modeling, Hydrol. Earth Syst. Sci., 24, 1485–1509, https://doi.org/10.5194/hess-24-1485-2020, 2020.
Park, J., Baik, J., and Choi, M.: Triple collocation-based multi-source evaporation and transpiration merging, Agr. Forest Meteorol., 331, 109353, https://doi.org/10.1016/j.agrformet.2023.109353, 2023.
Pastorello, G., Trotta, C., Canfora, E., Chu, H., Christianson, D., Cheah, Y.-W., Poindexter, C., Chen, J., Elbashandy, A., and Humphrey, M.: The FLUXNET2015 dataset and the ONEFlux processing pipeline for eddy covariance data, Sci. Data, 7, 225, https://doi.org/10.1038/s41597-020-0534-3, 2020.
Priestley, C. H. B. and Taylor, R. J.: On the assessment of surface heat flux and evaporation using large-scale parameters, Mon. Weather Rev., 100, 81–92, 1972.
Qi, W., Liu, J., and Chen, D.: Evaluations and Improvements of GLDAS2.0 and GLDAS2.1 Forcing Data's Applicability for Basin Scale Hydrological Simulations in the Tibetan Plateau, J. Geophys. Res.-Atmos., 123, 13128–13148, https://doi.org/10.1029/2018JD029116, 2018.
Qi, W., Liu, J., Yang, H., Zhu, X., Tian, Y., Jiang, X., Huang, X., and Feng, L.: Large Uncertainties in Runoff Estimations of GLDAS Versions 2.0 and 2.1 in China, Earth Space Sci., 7, e2019EA000829, https://doi.org/10.1029/2019EA000829, 2020.
Restrepo-Coupe, N., Albert, L. P., Longo, M., Baker, I., Levine, N. M., Mercado, L. M., da Araujo, A. C., Christoffersen, B. O., Costa, M. H., Fitzjarrald, D. R., Galbraith, D., Imbuzeiro, H., Malhi, Y., von Randow, C., Zeng, X., Moorcroft, P., and Saleska, S. R.: Understanding water and energy fluxes in the Amazonia: Lessons from an observation-model intercomparison, Glob. Change Biol., 27, 1802–1819, https://doi.org/10.1111/gcb.15555, 2021.
Ribal, A. and Young, I. R.: Global Calibration and Error Estimation of Altimeter, Scatterometer, and Radiometer Wind Speed Using Triple Collocation, Remote Sens., 12, https://doi.org/10.3390/rs12121997, 2020.
Rodell, M., Houser, P., Jambor, U., Gottschalck, J., Mitchell, K., Meng, C.-J., Arsenault, K., Cosgrove, B., Radakovich, J., and Bosilovich, M.: The global land data assimilation system, B. Am. Meteorol. Soc., 85, 381–394, 2004.
Sheffield, J., Goteti, G., and Wood, E. F.: Development of a 50-Year High-Resolution Global Dataset of Meteorological Forcings for Land Surface Modeling, J. Climate, 19, 3088–3111, https://doi.org/10.1175/JCLI3790.1, 2006.
Stoffelen, A.: Toward the true near-surface wind speed: Error modeling and calibration using triple collocation, J. Geophys. Res.-Oceans, 103, 7755–7766, https://doi.org/10.1029/97jc03180, 1998.
Su, C.-H. and Ryu, D.: Multi-scale analysis of bias correction of soil moisture, Hydrol. Earth Syst. Sci., 19, 17–31, https://doi.org/10.5194/hess-19-17-2015, 2015.
Su, C.-H., Ryu, D., Crow, W. T., and Western, A. W.: Beyond triple collocation: Applications to soil moisture monitoring, J. Geophys. Res.-Atmos., 119, 6419–6439, https://doi.org/10.1002/2013jd021043, 2014.
Sun, J., McColl, K. A., Wang, Y., Rigden, A. J., Lu, H., Yang, K., Li, Y., and Santanello, J. A.: Global evaluation of terrestrial near-surface air temperature and specific humidity retrievals from the Atmospheric Infrared Sounder (AIRS), Remote Sens. Environ., 252, 112146, https://doi.org/10.1016/j.rse.2020.112146, 2021.
Towner, J., Cloke, H. L., Zsoter, E., Flamig, Z., Hoch, J. M., Bazo, J., Coughlan de Perez, E., and Stephens, E. M.: Assessing the performance of global hydrological models for capturing peak river flows in the Amazon basin, Hydrol. Earth Syst. Sci., 23, 3057–3080, https://doi.org/10.5194/hess-23-3057-2019, 2019.
Tsamalis, C.: Clarifications on the equations and the sample number in triple collocation analysis using SST observations, Remote Sens. Environ., 272, 112936, https://doi.org/10.1016/j.rse.2022.112936, 2022.
Twine, T. E., Kustas, W., Norman, J., Cook, D., Houser, Pr., Meyers, T., Prueger, J., Starks, P., and Wesely, M.: Correcting eddy-covariance flux underestimates over a grassland, Agr. Forest Meteorol., 103, 279–300, 2000.
Vogelzang, J., Stoffelen, A., and Verhoef, A.: The Effect of Error Non-Orthogonality on Triple Collocation Analyses, Remote Sens., 14, 4268, https://doi.org/10.3390/rs14174268, 2022.
Wu, K., Ryu, D., Nie, L., and Shu, H.: Time-variant error characterization of SMAP and ASCAT soil moisture using Triple Collocation Analysis, Remote Sens. Environ., 256, 112324, https://doi.org/10.1016/j.rse.2021.112324, 2021.
Yang, Y., Roderick, M. L., Guo, H., Miralles, D. G., Zhang, L., Fatichi, S., Luo, X., Zhang, Y., McVicar, T. R., and Tu, Z.: Evapotranspiration on a greening Earth, Nat. Rev. Earth Environ., 4, 626–641, 2023.
Yilmaz, M. T. and Crow, W. T.: The optimality of potential rescaling approaches in land data assimilation, J. Hydrometeorol., 14, 650–660, 2013.
Yilmaz, M. T. and Crow, W. T.: Evaluation of Assumptions in Soil Moisture Triple Collocation Analysis, J. Hydrometeorol., 15, 1293–1302, https://doi.org/10.1175/JHM-D-13-0158.1, 2014.
Yilmaz, M. T., Crow, W. T., Anderson, M. C., and Hain, C.: An objective methodology for merging satellite- and model-based soil moisture products, Water Resour. Res., 48, W11502, https://doi.org/10.1029/2011wr011682, 2012.
Yin, G. and Park, J.: The use of triple collocation approach to merge satellite- and model-based terrestrial water storage for flood potential analysis, J. Hydrol., 603, 127197, https://doi.org/10.1016/j.jhydrol.2021.127197, 2021.
Yin, L., Tao, F., Chen, Y., Liu, F., and Hu, J.: Improving terrestrial evapotranspiration estimation across China during 2000–2018 with machine learning methods, J. Hydrol., 600, 126538, https://doi.org/10.1016/j.jhydrol.2021.126538, 2021.
Zhang, Y., Leuning, R., Hutley, L. B., Beringer, J., McHugh, I., and Walker, J. P.: Using long-term water balances to parameterize surface conductances and calculate evaporation at 0.05 spatial resolution, Water Resour. Res., 46, W05512, https://doi.org/10.1029/2009WR008716, 2010.
Zhang, Y., Kong, D., Gan, R., Chiew, F. H. S., McVicar, T. R., Zhang, Q., and Yang, Y.: Coupled estimation of 500 m and 8-day resolution global evapotranspiration and gross primary production in 2002–2017, Remote Sens. Environ., 222, 165–182, https://doi.org/10.1016/j.rse.2018.12.031, 2019.
Zhao, M., Liu, Y., and Konings, A. G.: Evapotranspiration frequently increases during droughts, Nat. Clim. Change, 12, 1024–1030, https://doi.org/10.1038/s41558-022-01505-3, 2022.
Zhu, G., Li, X., Zhang, K., Ding, Z., Han, T., Ma, J., Huang, C., He, J., and Ma, T.: Multi-model ensemble prediction of terrestrial evapotranspiration across north China using Bayesian model averaging, Hydrol. Process., 30, 2861–2879, https://doi.org/10.1002/hyp.10832, 2016.
Zwieback, S., Su, C.-H., Gruber, A., Dorigo, W. A., and Wagner, W.: The impact of quadratic nonlinear relations between soil moisture products on uncertainty estimates from triple collocation analysis and two quadratic extensions, J. Hydrometeorol., 17, 1725–1743, 2016.
Short summary
Using a collocation-based approach, we developed a reliable global land evapotranspiration product (CAMELE) by merging multi-source datasets. The CAMELE product outperformed individual input datasets and showed satisfactory performance compared to reference data. It also demonstrated superiority for different plant functional types. Our study provides a promising solution for data fusion. The CAMELE dataset allows for detailed research and a better understanding of land–atmosphere interactions.
Using a collocation-based approach, we developed a reliable global land evapotranspiration...
Altmetrics
Final-revised paper
Preprint