Articles | Volume 15, issue 11
https://doi.org/10.5194/essd-15-4849-2023
© Author(s) 2023. 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-15-4849-2023
© Author(s) 2023. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Data description paper
| 
31 Oct 2023
Data description paper |
| 31 Oct 2023
| 31 Oct 2023
A global 5 km monthly potential evapotranspiration dataset (1982–2015) estimated by the Shuttleworth–Wallace model
Shanlei Sun
CORRESPONDING AUTHOR
Collaborative Innovation Center on Forecast and Evaluation of Meteorological Disasters/Key Laboratory of Meteorological Disaster, Ministry of Education/International Joint Research Laboratory on Climate and Environment Change, Nanjing University of Information Science and Technology, Nanjing, China
Zaoying Bi
Collaborative Innovation Center on Forecast and Evaluation of Meteorological Disasters/Key Laboratory of Meteorological Disaster, Ministry of Education/International Joint Research Laboratory on Climate and Environment Change, Nanjing University of Information Science and Technology, Nanjing, China
Jingfeng Xiao
Earth Systems Research Center, Institute for the Study of Earth, Oceans, and Space, University of New Hampshire, Durham, USA
Yi Liu
School of Civil and Environmental Engineering, University of New South Wales, Sydney, Australia
Ge Sun
Eastern Forest Environmental Threat Assessment Center, Southern Research Station, USDA Forest Service, Raleigh, USA
Weimin Ju
International Institute for Earth System Science, Nanjing University, Nanjing, China
Chunwei Liu
Jiangsu Key Laboratory of Agricultural Meteorology, School of Applied Meteorology, Nanjing University of Information Science and Technology, Nanjing, China
Mengyuan Mu
ARC Centre of Excellence for Climate Extremes and Climate Change Research Centre, University of New South Wales, Sydney, Australia
Jinjian Li
School of Atmospheric Sciences/Plateau Atmosphere and Environment Key Laboratory of Sichuan Province, Chengdu University of Information Technology, Chengdu, China
Yang Zhou
Collaborative Innovation Center on Forecast and Evaluation of Meteorological Disasters/Key Laboratory of Meteorological Disaster, Ministry of Education/International Joint Research Laboratory on Climate and Environment Change, Nanjing University of Information Science and Technology, Nanjing, China
Xiaoyuan Li
Collaborative Innovation Center on Forecast and Evaluation of Meteorological Disasters/Key Laboratory of Meteorological Disaster, Ministry of Education/International Joint Research Laboratory on Climate and Environment Change, Nanjing University of Information Science and Technology, Nanjing, China
Jiangsu Key Laboratory of Agricultural Meteorology, School of Applied Meteorology, Nanjing University of Information Science and Technology, Nanjing, China
Haishan Chen
Collaborative Innovation Center on Forecast and Evaluation of Meteorological Disasters/Key Laboratory of Meteorological Disaster, Ministry of Education/International Joint Research Laboratory on Climate and Environment Change, Nanjing University of Information Science and Technology, Nanjing, China
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Geosci. Model Dev., 17, 6337–6363, https://doi.org/10.5194/gmd-17-6337-2024, https://doi.org/10.5194/gmd-17-6337-2024, 2024
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Jing M. Chen, Rong Wang, Yihong Liu, Liming He, Holly Croft, Xiangzhong Luo, Han Wang, Nicholas G. Smith, Trevor F. Keenan, I. Colin Prentice, Yongguang Zhang, Weimin Ju, and Ning Dong
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Rui Ma, Jingfeng Xiao, Shunlin Liang, Han Ma, Tao He, Da Guo, Xiaobang Liu, and Haibo Lu
Geosci. Model Dev., 15, 6637–6657, https://doi.org/10.5194/gmd-15-6637-2022, https://doi.org/10.5194/gmd-15-6637-2022, 2022
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Parameter optimization can improve the accuracy of modeled carbon fluxes. Few studies conducted pixel-level parameterization because it requires a high computational cost. Our paper used high-quality spatial products to optimize parameters at the pixel level, and also used the machine learning method to improve the speed of optimization. The results showed that there was significant spatial variability of parameters and we also improved the spatial pattern of carbon fluxes.
Fei Jiang, Weimin Ju, Wei He, Mousong Wu, Hengmao Wang, Jun Wang, Mengwei Jia, Shuzhuang Feng, Lingyu Zhang, and Jing M. Chen
Earth Syst. Sci. Data, 14, 3013–3037, https://doi.org/10.5194/essd-14-3013-2022, https://doi.org/10.5194/essd-14-3013-2022, 2022
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A 10-year (2010–2019) global monthly terrestrial NEE dataset (GCAS2021) was inferred from the GOSAT ACOS v9 XCO2 product. It shows strong carbon sinks over eastern N. America, the Amazon, the Congo Basin, Europe, boreal forests, southern China, and Southeast Asia. It has good quality and can reflect the impacts of extreme climates and large-scale climate anomalies on carbon fluxes well. We believe that this dataset can contribute to regional carbon budget assessment and carbon dynamics research.
Jing Fang, Xing Li, Jingfeng Xiao, Xiaodong Yan, Bolun Li, and Feng Liu
Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2021-452, https://doi.org/10.5194/essd-2021-452, 2022
Revised manuscript not accepted
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The dataset provided the vegetation photosynthetic phenology instead of traditional phenology to represent plant seasonal activities. This dataset had the latest period (2001–2020) and a fine spatial resolution (0.05 degree). Our phenology metrics revealed the spatial-temporal patterns of the multiple growing seasons in the Northern Hemisphere. The dataset will facilitate various research such as developing models, evaluating phenology shifts, and monitoring climate change worldwide.
Jiehao Zhang, Yulong Zhang, Ge Sun, Conghe Song, Matthew P. Dannenberg, Jiangfeng Li, Ning Liu, Kerong Zhang, Quanfa Zhang, and Lu Hao
Hydrol. Earth Syst. Sci., 25, 5623–5640, https://doi.org/10.5194/hess-25-5623-2021, https://doi.org/10.5194/hess-25-5623-2021, 2021
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To quantify how vegetation greening impacts the capacity of water supply, we built a hybrid model and conducted a case study using the upper Han River basin (UHRB) that serves as the water source area to the world’s largest water diversion project. Vegetation greening in the UHRB during 2001–2018 induced annual water yield (WY) greatly decreased. Vegetation greening also increased the possibility of drought and reduced a quarter of WY on average during drought periods.
Mengyuan Mu, Martin G. De Kauwe, Anna M. Ukkola, Andy J. Pitman, Weidong Guo, Sanaa Hobeichi, and Peter R. Briggs
Earth Syst. Dynam., 12, 919–938, https://doi.org/10.5194/esd-12-919-2021, https://doi.org/10.5194/esd-12-919-2021, 2021
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Groundwater can buffer the impacts of drought and heatwaves on ecosystems, which is often neglected in model studies. Using a land surface model with groundwater, we explained how groundwater sustains transpiration and eases heat pressure on plants in heatwaves during multi-year droughts. Our results showed the groundwater’s influences diminish as drought extends and are regulated by plant physiology. We suggest neglecting groundwater in models may overstate projected future heatwave intensity.
Rafael Poyatos, Víctor Granda, Víctor Flo, Mark A. Adams, Balázs Adorján, David Aguadé, Marcos P. M. Aidar, Scott Allen, M. Susana Alvarado-Barrientos, Kristina J. Anderson-Teixeira, Luiza Maria Aparecido, M. Altaf Arain, Ismael Aranda, Heidi Asbjornsen, Robert Baxter, Eric Beamesderfer, Z. Carter Berry, Daniel Berveiller, Bethany Blakely, Johnny Boggs, Gil Bohrer, Paul V. Bolstad, Damien Bonal, Rosvel Bracho, Patricia Brito, Jason Brodeur, Fernando Casanoves, Jérôme Chave, Hui Chen, Cesar Cisneros, Kenneth Clark, Edoardo Cremonese, Hongzhong Dang, Jorge S. David, Teresa S. David, Nicolas Delpierre, Ankur R. Desai, Frederic C. Do, Michal Dohnal, Jean-Christophe Domec, Sebinasi Dzikiti, Colin Edgar, Rebekka Eichstaedt, Tarek S. El-Madany, Jan Elbers, Cleiton B. Eller, Eugénie S. Euskirchen, Brent Ewers, Patrick Fonti, Alicia Forner, David I. Forrester, Helber C. Freitas, Marta Galvagno, Omar Garcia-Tejera, Chandra Prasad Ghimire, Teresa E. Gimeno, John Grace, André Granier, Anne Griebel, Yan Guangyu, Mark B. Gush, Paul J. Hanson, Niles J. Hasselquist, Ingo Heinrich, Virginia Hernandez-Santana, Valentine Herrmann, Teemu Hölttä, Friso Holwerda, James Irvine, Supat Isarangkool Na Ayutthaya, Paul G. Jarvis, Hubert Jochheim, Carlos A. Joly, Julia Kaplick, Hyun Seok Kim, Leif Klemedtsson, Heather Kropp, Fredrik Lagergren, Patrick Lane, Petra Lang, Andrei Lapenas, Víctor Lechuga, Minsu Lee, Christoph Leuschner, Jean-Marc Limousin, Juan Carlos Linares, Maj-Lena Linderson, Anders Lindroth, Pilar Llorens, Álvaro López-Bernal, Michael M. Loranty, Dietmar Lüttschwager, Cate Macinnis-Ng, Isabelle Maréchaux, Timothy A. Martin, Ashley Matheny, Nate McDowell, Sean McMahon, Patrick Meir, Ilona Mészáros, Mirco Migliavacca, Patrick Mitchell, Meelis Mölder, Leonardo Montagnani, Georgianne W. Moore, Ryogo Nakada, Furong Niu, Rachael H. Nolan, Richard Norby, Kimberly Novick, Walter Oberhuber, Nikolaus Obojes, A. Christopher Oishi, Rafael S. Oliveira, Ram Oren, Jean-Marc Ourcival, Teemu Paljakka, Oscar Perez-Priego, Pablo L. Peri, Richard L. Peters, Sebastian Pfautsch, William T. Pockman, Yakir Preisler, Katherine Rascher, George Robinson, Humberto Rocha, Alain Rocheteau, Alexander Röll, Bruno H. P. Rosado, Lucy Rowland, Alexey V. Rubtsov, Santiago Sabaté, Yann Salmon, Roberto L. Salomón, Elisenda Sánchez-Costa, Karina V. R. Schäfer, Bernhard Schuldt, Alexandr Shashkin, Clément Stahl, Marko Stojanović, Juan Carlos Suárez, Ge Sun, Justyna Szatniewska, Fyodor Tatarinov, Miroslav Tesař, Frank M. Thomas, Pantana Tor-ngern, Josef Urban, Fernando Valladares, Christiaan van der Tol, Ilja van Meerveld, Andrej Varlagin, Holm Voigt, Jeffrey Warren, Christiane Werner, Willy Werner, Gerhard Wieser, Lisa Wingate, Stan Wullschleger, Koong Yi, Roman Zweifel, Kathy Steppe, Maurizio Mencuccini, and Jordi Martínez-Vilalta
Earth Syst. Sci. Data, 13, 2607–2649, https://doi.org/10.5194/essd-13-2607-2021, https://doi.org/10.5194/essd-13-2607-2021, 2021
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Transpiration is a key component of global water balance, but it is poorly constrained from available observations. We present SAPFLUXNET, the first global database of tree-level transpiration from sap flow measurements, containing 202 datasets and covering a wide range of ecological conditions. SAPFLUXNET and its accompanying R software package
sapfluxnetrwill facilitate new data syntheses on the ecological factors driving water use and drought responses of trees and forests.
Fei Jiang, Hengmao Wang, Jing M. Chen, Weimin Ju, Xiangjun Tian, Shuzhuang Feng, Guicai Li, Zhuoqi Chen, Shupeng Zhang, Xuehe Lu, Jane Liu, Haikun Wang, Jun Wang, Wei He, and Mousong Wu
Atmos. Chem. Phys., 21, 1963–1985, https://doi.org/10.5194/acp-21-1963-2021, https://doi.org/10.5194/acp-21-1963-2021, 2021
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We present a 6-year inversion from 2010 to 2015 for the global and regional carbon fluxes using only the GOSAT XCO2 retrievals. We find that the XCO2 retrievals could significantly improve the modeling of atmospheric CO2 concentrations and that the inferred interannual variations in the terrestrial carbon fluxes in most land regions have a better relationship with the changes in severe drought area or leaf area index, or are more consistent with the previous estimates about drought impact.
Mengyuan Mu, Martin G. De Kauwe, Anna M. Ukkola, Andy J. Pitman, Teresa E. Gimeno, Belinda E. Medlyn, Dani Or, Jinyan Yang, and David S. Ellsworth
Hydrol. Earth Syst. Sci., 25, 447–471, https://doi.org/10.5194/hess-25-447-2021, https://doi.org/10.5194/hess-25-447-2021, 2021
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Land surface model (LSM) is a critical tool to study land responses to droughts and heatwaves, but lacking comprehensive observations limited past model evaluations. Here we use a novel dataset at a water-limited site, evaluate a typical LSM with a range of competing model hypotheses widely used in LSMs and identify marked uncertainty due to the differing process assumptions. We show the extensive observations constrain model processes and allow better simulated land responses to these extremes.
Yi Zheng, Ruoque Shen, Yawen Wang, Xiangqian Li, Shuguang Liu, Shunlin Liang, Jing M. Chen, Weimin Ju, Li Zhang, and Wenping Yuan
Earth Syst. Sci. Data, 12, 2725–2746, https://doi.org/10.5194/essd-12-2725-2020, https://doi.org/10.5194/essd-12-2725-2020, 2020
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Accurately reproducing the interannual variations in vegetation gross primary production (GPP) is a major challenge. A global GPP dataset was generated by integrating the regulations of several major environmental variables with long-term changes. The dataset can effectively reproduce the spatial, seasonal, and particularly interannual variations in global GPP. Our study will contribute to accurate carbon flux estimates at long timescales.
Hengmao Wang, Fei Jiang, Jun Wang, Weimin Ju, and Jing M. Chen
Atmos. Chem. Phys., 19, 12067–12082, https://doi.org/10.5194/acp-19-12067-2019, https://doi.org/10.5194/acp-19-12067-2019, 2019
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The differences in inverted global and regional carbon fluxes from GOSAT and OCO-2 XCO2 from 1 January to 31 December 2015 are studied. We find significant differences for inverted terrestrial carbon fluxes on both global and regional scales. Overall, GOSAT XCO2 has a better performance than OCO-2, and GOSAT data can effectively improve carbon flux estimates in the Northern Hemisphere, while OCO-2 data, with the specific version used in this study, show only slight improvement.
Wei He, Ivar R. van der Velde, Arlyn E. Andrews, Colm Sweeney, John Miller, Pieter Tans, Ingrid T. van der Laan-Luijkx, Thomas Nehrkorn, Marikate Mountain, Weimin Ju, Wouter Peters, and Huilin Chen
Geosci. Model Dev., 11, 3515–3536, https://doi.org/10.5194/gmd-11-3515-2018, https://doi.org/10.5194/gmd-11-3515-2018, 2018
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We have implemented a regional, high-resolution, and computationally attractive carbon dioxide data assimilation system. This system, named CTDAS-Lagrange, is capable of simultaneously optimizing terrestrial biosphere fluxes and the lateral boundary conditions. The CTDAS-Lagrange system can be easily extended to assimilate an additional tracer, e.g., carbonyl sulfide (COS or OCS), for regional estimates of both net and gross carbon fluxes.
Jun Wang, Ning Zeng, Meirong Wang, Fei Jiang, Jingming Chen, Pierre Friedlingstein, Atul K. Jain, Ziqiang Jiang, Weimin Ju, Sebastian Lienert, Julia Nabel, Stephen Sitch, Nicolas Viovy, Hengmao Wang, and Andrew J. Wiltshire
Atmos. Chem. Phys., 18, 10333–10345, https://doi.org/10.5194/acp-18-10333-2018, https://doi.org/10.5194/acp-18-10333-2018, 2018
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Based on the Mauna Loa CO2 records and TRENDY multi-model historical simulations, we investigate the different impacts of EP and CP El Niños on interannual carbon cycle variability. Composite analysis indicates that the evolutions of CO2 growth rate anomalies have three clear differences in terms of precursors (negative and neutral), amplitudes (strong and weak), and durations of peak (Dec–Apr and Oct–Jan) during EP and CP El Niños, respectively. We further discuss their terrestrial mechanisms.
Wei Li, Philippe Ciais, Shushi Peng, Chao Yue, Yilong Wang, Martin Thurner, Sassan S. Saatchi, Almut Arneth, Valerio Avitabile, Nuno Carvalhais, Anna B. Harper, Etsushi Kato, Charles Koven, Yi Y. Liu, Julia E.M.S. Nabel, Yude Pan, Julia Pongratz, Benjamin Poulter, Thomas A. M. Pugh, Maurizio Santoro, Stephen Sitch, Benjamin D. Stocker, Nicolas Viovy, Andy Wiltshire, Rasoul Yousefpour, and Sönke Zaehle
Biogeosciences, 14, 5053–5067, https://doi.org/10.5194/bg-14-5053-2017, https://doi.org/10.5194/bg-14-5053-2017, 2017
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We used several observation-based biomass datasets to constrain the historical land-use change carbon emissions simulated by models. Compared to the range of the original modeled emissions (from 94 to 273 Pg C), the observationally constrained global cumulative emission estimate is 155 ± 50 Pg C (1σ Gaussian error) from 1901 to 2012. Our approach can also be applied to evaluate the LULCC impact of land-based climate mitigation policies.
Xu Yue, Nadine Unger, Kandice Harper, Xiangao Xia, Hong Liao, Tong Zhu, Jingfeng Xiao, Zhaozhong Feng, and Jing Li
Atmos. Chem. Phys., 17, 6073–6089, https://doi.org/10.5194/acp-17-6073-2017, https://doi.org/10.5194/acp-17-6073-2017, 2017
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While it is widely recognized that air pollutants adversely affect human health and climate change, their impacts on the regional carbon balance are less well understood. We apply an Earth system model to quantify the combined effects of ozone and aerosol particles on net primary production in China. Ozone vegetation damage dominates over the aerosol effects, leading to a substantial net suppression of land carbon uptake in the present and future worlds.
Yu-Hao Mao, Hong Liao, and Hai-Shan Chen
Atmos. Chem. Phys., 17, 4799–4816, https://doi.org/10.5194/acp-17-4799-2017, https://doi.org/10.5194/acp-17-4799-2017, 2017
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We applied a global 3-D CTM to examine the impacts of the East Asian summer and winter monsoons on the interannual variations of surface concentrations, vertical distributions, and direct radiative forcing of black carbon (BC) over eastern China and the mechanisms through which the monsoon influences the variations of BC. Model results from our study have important implications for guiding measures to reduce BC emissions to mitigate near-term climate warming and to improve air quality in China.
Jingfeng Xiao, Shuguang Liu, and Paul C. Stoy
Biogeosciences, 13, 3665–3675, https://doi.org/10.5194/bg-13-3665-2016, https://doi.org/10.5194/bg-13-3665-2016, 2016
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This special issue showcases recent advancements on the impacts of disturbances and extreme events on the carbon (C) cycle. Notable advancements include quantifying harvest impacts on forest structure, recovery, and carbon stocks; observed dissolved organic C and methane increases in thermokarst lakes following summer warming; disentangling the roles of herbivores and fire on forest carbon dioxide flux; and improved atmospheric inversion of regional C flux by incorporating disturbances.
M. J. E. van Marle, G. R. van der Werf, R. A. M. de Jeu, and Y. Y. Liu
Biogeosciences, 13, 609–624, https://doi.org/10.5194/bg-13-609-2016, https://doi.org/10.5194/bg-13-609-2016, 2016
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We have quantified large-scale forest loss over a 21-year period (1990–2010) in the tropical biomes of South America using a new satellite-based data set. We found that South American forest exhibited interannual variability without a clear trend during the 1990s, but increased from 2000 to 2004. After 2004, forest loss decreased again, mainly as a result of a decrease in the Brazilian Amazon, whereas at the same time regions south of the arc of deforestation showed an increase in forest loss.
W. Wang, J. Xiao, S. V. Ollinger, A. R. Desai, J. Chen, and A. Noormets
Biogeosciences, 11, 6667–6682, https://doi.org/10.5194/bg-11-6667-2014, https://doi.org/10.5194/bg-11-6667-2014, 2014
F. Jiang, H. M. Wang, J. M. Chen, T. Machida, L. X. Zhou, W. M. Ju, H. Matsueda, and Y. Sawa
Atmos. Chem. Phys., 14, 10133–10144, https://doi.org/10.5194/acp-14-10133-2014, https://doi.org/10.5194/acp-14-10133-2014, 2014
Y. Liu, Y. Zhou, W. Ju, S. Wang, X. Wu, M. He, and G. Zhu
Biogeosciences, 11, 2583–2599, https://doi.org/10.5194/bg-11-2583-2014, https://doi.org/10.5194/bg-11-2583-2014, 2014
Y. Liu, Y. Zhou, W. Ju, J. Chen, S. Wang, H. He, H. Wang, D. Guan, F. Zhao, Y. Li, and Y. Hao
Hydrol. Earth Syst. Sci., 17, 4957–4980, https://doi.org/10.5194/hess-17-4957-2013, https://doi.org/10.5194/hess-17-4957-2013, 2013
N. Andela, Y. Y. Liu, A. I. J. M. van Dijk, R. A. M. de Jeu, and T. R. McVicar
Biogeosciences, 10, 6657–6676, https://doi.org/10.5194/bg-10-6657-2013, https://doi.org/10.5194/bg-10-6657-2013, 2013
F. Deng, J. M. Chen, Y. Pan, W. Peters, R. Birdsey, K. McCullough, and J. Xiao
Biogeosciences, 10, 5335–5348, https://doi.org/10.5194/bg-10-5335-2013, https://doi.org/10.5194/bg-10-5335-2013, 2013
F. Jiang, H. W. Wang, J. M. Chen, L. X. Zhou, W. M. Ju, A. J. Ding, L. X. Liu, and W. Peters
Biogeosciences, 10, 5311–5324, https://doi.org/10.5194/bg-10-5311-2013, https://doi.org/10.5194/bg-10-5311-2013, 2013
Related subject area
Domain: ESSD – Land | Subject: Hydrology
HERA: a high-resolution pan-European hydrological reanalysis (1951–2020)
BCUB – a large-sample ungauged basin attribute dataset for British Columbia, Canada
Lena River biogeochemistry captured by a 4.5-year high-frequency sampling program
CAMELS-DE: hydro-meteorological time series and attributes for 1582 catchments in Germany
Observational partitioning of water and CO2 fluxes at National Ecological Observatory Network (NEON) sites: a 5-year dataset of soil and plant components for spatial and temporal analysis
CAMELS-FR dataset: A large-sample hydroclimatic dataset for France to explore hydrological diversity and support model benchmarking
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)
High-resolution hydrometeorological and snow data for the Dischma catchment in Switzerland
A globally sampled high-resolution hand-labeled validation dataset for evaluating surface water extent maps
Features of the Italian Large Dams and their upstream catchments
CAMELS-INDIA: hydrometeorological time series and catchment attributes for 472 catchments in Peninsular India
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
An in-situ daily dataset for benchmarking temporal variability of groundwater recharge
Rainfall erosivity mapping in mainland China using 1-minute precipitation data from densely distributed weather stations
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
CAMELE: Collocation-Analyzed Multi-source Ensembled Land Evapotranspiration Data
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
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 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
Aloïs Tilloy, Dominik Paprotny, Stefania Grimaldi, Goncalo Gomes, Alessandra Bianchi, Stefan Lange, Hylke Beck, Cinzia Mazzetti, and Luc Feyen
Earth Syst. Sci. Data, 17, 293–316, https://doi.org/10.5194/essd-17-293-2025, https://doi.org/10.5194/essd-17-293-2025, 2025
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This article presents a reanalysis of Europe's river streamflow for the period 1951–2020. Streamflow is estimated through a state-of-the-art hydrological simulation framework benefitting from detailed information about the landscape, climate, and human activities. The resulting Hydrological European ReAnalysis (HERA) can be a valuable tool for studying hydrological dynamics, including the impacts of climate change and human activities on European water resources and flood and drought risks.
Daniel Kovacek and Steven Weijs
Earth Syst. Sci. Data, 17, 259–275, https://doi.org/10.5194/essd-17-259-2025, https://doi.org/10.5194/essd-17-259-2025, 2025
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We made a dataset for British Columbia describing the terrain, soil, land cover, and climate of over 1 million watersheds. The attributes are often used in hydrology because they are related to the water cycle. The data are meant to be used for water resources problems that can benefit from lots of watersheds and their attributes. The data and instructions needed to build the dataset from scratch are freely available. The permanent home for the data is https://doi.org/10.5683/SP3/JNKZVT.
Bennet Juhls, Anne Morgenstern, Jens Hölemann, Antje Eulenburg, Birgit Heim, Frederieke Miesner, Hendrik Grotheer, Gesine Mollenhauer, Hanno Meyer, Ephraim Erkens, Felica Yara Gehde, Sofia Antonova, Sergey Chalov, Maria Tereshina, Oxana Erina, Evgeniya Fingert, Ekaterina Abramova, Tina Sanders, Liudmila Lebedeva, Nikolai Torgovkin, Georgii Maksimov, Vasily Povazhnyi, Rafael Gonçalves-Araujo, Urban Wünsch, Antonina Chetverova, Sophie Opfergelt, and Pier Paul Overduin
Earth Syst. Sci. Data, 17, 1–28, https://doi.org/10.5194/essd-17-1-2025, https://doi.org/10.5194/essd-17-1-2025, 2025
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The Siberian Arctic is warming fast: permafrost is thawing, river chemistry is changing, and coastal ecosystems are affected. We aimed to understand changes in the Lena River, a major Arctic river flowing to the Arctic Ocean, by collecting 4.5 years of detailed water data, including temperature and carbon and nutrient contents. This dataset records current conditions and helps us to detect future changes. Explore it at https://doi.org/10.1594/PANGAEA.913197 and https://lena-monitoring.awi.de/.
Ralf Loritz, Alexander Dolich, Eduardo Acuña Espinoza, Pia Ebeling, Björn Guse, Jonas Götte, Sibylle K. Hassler, Corina Hauffe, Ingo Heidbüchel, Jens Kiesel, Mirko Mälicke, Hannes Müller-Thomy, Michael Stölzle, and Larisa Tarasova
Earth Syst. Sci. Data, 16, 5625–5642, https://doi.org/10.5194/essd-16-5625-2024, https://doi.org/10.5194/essd-16-5625-2024, 2024
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The CAMELS-DE dataset features data from 1582 streamflow gauges across Germany, with records spanning from 1951 to 2020. This comprehensive dataset, which includes time series of up to 70 years (median 46 years), enables advanced research on water flow and environmental trends and supports the development of hydrological models.
Einara Zahn and Elie Bou-Zeid
Earth Syst. Sci. Data, 16, 5603–5624, https://doi.org/10.5194/essd-16-5603-2024, https://doi.org/10.5194/essd-16-5603-2024, 2024
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Quantifying water and CO2 exchanges through transpiration, evaporation, net photosynthesis, and soil respiration is essential for understanding how ecosystems function. We implemented five methods to estimate these fluxes over a 5-year period across 47 sites. This is the first dataset representing such large spatial and temporal coverage of soil and plant exchanges, and it has many potential applications, such as examining the response of ecosystems to weather extremes and climate change.
Olivier Delaigue, Guilherme Mendoza Guimarães, Pierre Brigode, Benoît Génot, Charles Perrin, Jean-Michel Soubeyroux, Bruno Janet, Nans Addor, and Vazken Andréassian
Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2024-415, https://doi.org/10.5194/essd-2024-415, 2024
Revised manuscript accepted for ESSD
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This dataset covers 654 rivers all flowing in France. The provided time series and catchment attributes will be of interest to those modelers wishing to analyse hydrological behavior, perform model assessments.
Ling Zhang, Yanhua Xie, Xiufang Zhu, Qimin Ma, and Luca Brocca
Earth Syst. Sci. Data, 16, 5207–5226, https://doi.org/10.5194/essd-16-5207-2024, https://doi.org/10.5194/essd-16-5207-2024, 2024
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This study presented new annual maps of irrigated cropland in China from 2000 to 2020 (CIrrMap250). These maps were developed by integrating remote sensing data, irrigation statistics and surveys, and an irrigation suitability map. CIrrMap250 achieved high accuracy and outperformed currently available products. The new irrigation maps revealed a clear expansion of China’s irrigation area, with the majority (61%) occurring in the water-unsustainable regions facing severe to extreme water stress.
Dominik Paprotny, Paweł Terefenko, and Jakub Śledziowski
Earth Syst. Sci. Data, 16, 5145–5170, https://doi.org/10.5194/essd-16-5145-2024, https://doi.org/10.5194/essd-16-5145-2024, 2024
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Knowledge about past natural disasters can help adaptation to their future occurrences. Here, we present a dataset of 2521 riverine, pluvial, coastal, and compound floods that have occurred in 42 European countries between 1870 and 2020. The dataset contains available information on the inundated area, fatalities, persons affected, or economic loss and was obtained by extensive data collection from more than 800 sources ranging from news reports through government databases to scientific papers.
Paulina Bartkowiak, Bartolomeo Ventura, Alexander Jacob, and Mariapina Castelli
Earth Syst. Sci. Data, 16, 4709–4734, https://doi.org/10.5194/essd-16-4709-2024, https://doi.org/10.5194/essd-16-4709-2024, 2024
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This paper presents the Two-Source Energy Balance evapotranspiration (ET) product driven by Copernicus Sentinel-2 and Sentinel-3 imagery together with ERA5 climate reanalysis data. Daily ET maps are available at 100 m spatial resolution for the period 2017–2021 across four Mediterranean basins: Ebro (Spain), Hérault (France), Medjerda (Tunisia), and Po (Italy). The product is highly beneficial for supporting vegetation monitoring and sustainable water management at the river basin scale.
Fanny J. Sarrazin, Sabine Attinger, and Rohini Kumar
Earth Syst. Sci. Data, 16, 4673–4708, https://doi.org/10.5194/essd-16-4673-2024, https://doi.org/10.5194/essd-16-4673-2024, 2024
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Nitrogen (N) and phosphorus (P) contamination of water bodies is a long-term issue due to the long history of N and P inputs to the environment and their persistence. Here, we introduce a long-term and high-resolution dataset of N and P inputs from wastewater (point sources) for Germany, combining data from different sources and conceptual understanding. We also account for uncertainties in modelling choices, thus facilitating robust long-term and large-scale water quality studies.
Jan Magnusson, Yves Bühler, Louis Quéno, Bertrand Cluzet, Giulia Mazzotti, Clare Webster, Rebecca Mott, and Tobias Jonas
Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2024-374, https://doi.org/10.5194/essd-2024-374, 2024
Revised manuscript accepted for ESSD
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In this study, we present a dataset for the Dischma catchment in eastern Switzerland, which represents a typical high-alpine watershed in the European Alps. Accurate monitoring and reliable forecasting of snow and water resources in such basins are crucial for a wide range of applications. Our dataset is valuable for improving physics-based snow, land-surface, and hydrological models, with potential applications in similar high-alpine catchments.
Rohit Mukherjee, Frederick Policelli, Ruixue Wang, Elise Arellano-Thompson, Beth Tellman, Prashanti Sharma, Zhijie Zhang, and Jonathan Giezendanner
Earth Syst. Sci. Data, 16, 4311–4323, https://doi.org/10.5194/essd-16-4311-2024, https://doi.org/10.5194/essd-16-4311-2024, 2024
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Global water resource monitoring is crucial due to climate change and population growth. This study presents a hand-labeled dataset of 100 PlanetScope images for surface water detection, spanning diverse biomes. We use this dataset to evaluate two state-of-the-art mapping methods. Results highlight performance variations across biomes, emphasizing the need for diverse, independent validation datasets to enhance the accuracy and reliability of satellite-based surface water monitoring techniques.
Giulia Evangelista, Paola Mazzoglio, Daniele Ganora, Francesca Pianigiani, and Pierluigi Claps
Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2024-387, https://doi.org/10.5194/essd-2024-387, 2024
Revised manuscript accepted for ESSD
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This paper presents the first comprehensive dataset of 528 Large Dams in Italy. It contains structural characteristics of the dams, such as coordinates, reservoir surface area and volume, together with a range of geomorphological, climatological, extreme rainfall, land cover and soil-related attributes of their upstream catchments.
Nikunj K. Mangukiya, Kanneganti Bhargav Kumar, Pankaj Dey, Shailza Sharma, Vijaykumar Bejagam, Pradeep P. Mujumdar, and Ashutosh Sharma
Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2024-379, https://doi.org/10.5194/essd-2024-379, 2024
Revised manuscript accepted for ESSD
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We introduce CAMELS-INDIA (Catchment Attributes and MEteorology for Large-sample Studies – India), which provides daily hydrometeorological time series and static catchment attributes representing location, topography, climate, hydrological signatures, land-use, land cover, soil, geology, and anthropogenic influences for 472 catchments in peninsular India, to foster large-sample hydrological studies in India and promote the inclusion of Indian catchments in global hydrological research.
Lei Huang, Yong Luo, Jing M. Chen, Qiuhong Tang, Tammo Steenhuis, Wei Cheng, and Wen Shi
Earth Syst. Sci. Data, 16, 3993–4019, https://doi.org/10.5194/essd-16-3993-2024, https://doi.org/10.5194/essd-16-3993-2024, 2024
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Timely global terrestrial evapotranspiration (ET) data are crucial for water resource management and drought forecasting. This study introduces the VISEA algorithm, which integrates satellite data and shortwave radiation to provide daily 0.05° gridded near-real-time ET estimates. By employing a vegetation index–temperature method, this algorithm can estimate ET without requiring additional data. Evaluation results demonstrate VISEA's comparable accuracy with accelerated data availability.
Sibylle Kathrin Hassler, Rafael Bohn Reckziegel, Ben du Toit, Svenja Hoffmeister, Florian Kestel, Anton Kunneke, Rebekka Maier, and Jonathan Paul Sheppard
Earth Syst. Sci. Data, 16, 3935–3948, https://doi.org/10.5194/essd-16-3935-2024, https://doi.org/10.5194/essd-16-3935-2024, 2024
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Agroforestry systems (AFSs) combine trees and crops within the same land unit, providing a sustainable land use option which protects natural resources and biodiversity. Introducing trees into agricultural systems can positively affect water resources, soil characteristics, biomass and microclimate. We studied an AFS in South Africa in a multidisciplinary approach to assess the different influences and present the resulting dataset consisting of water, soil, tree and meteorological variables.
Kaihao Zheng, Peirong Lin, and Ziyun Yin
Earth Syst. Sci. Data, 16, 3873–3891, https://doi.org/10.5194/essd-16-3873-2024, https://doi.org/10.5194/essd-16-3873-2024, 2024
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We develop a globally applicable thresholding scheme for DEM-based floodplain delineation to improve the representation of spatial heterogeneity. It involves a stepwise approach to estimate the basin-level floodplain hydraulic geometry parameters that best respect the scaling law while approximating the global hydrodynamic flood maps. A ~90 m resolution global floodplain map, the Spatial Heterogeneity Improved Floodplain by Terrain analysis (SHIFT), is delineated with demonstrated superiority.
Yuzhong Yang, Qingbai Wu, Xiaoyan Guo, Lu Zhou, Helin Yao, Dandan Zhang, Zhongqiong Zhang, Ji Chen, and Guojun Liu
Earth Syst. Sci. Data, 16, 3755–3770, https://doi.org/10.5194/essd-16-3755-2024, https://doi.org/10.5194/essd-16-3755-2024, 2024
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We present the temporal data of stable isotopes in different waterbodies in the Beiluhe Basin in the hinterland of the Qinghai–Tibet Plateau (QTP) produced between 2017 and 2022. In this article, the first detailed stable isotope data of 359 ground ice samples are presented. This first data set provides a new basis for understanding the hydrological effects of permafrost degradation on the QTP.
Pragnaditya Malakar, Aatish Anshuman, Mukesh Kumar, Georgios Boumis, T. Prabhakar Clement, Arik Tashie, Hitesh Thakur, Nagaraj Bhat, and Lokendra Rathore
Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2024-324, https://doi.org/10.5194/essd-2024-324, 2024
Revised manuscript accepted for ESSD
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Groundwater dynamics depend on groundwater recharge, but daily benchmark data of recharge is scarce. Here we present a daily groundwater recharge per unit specified yield (RpSy) data at 485 US groundwater monitoring wells. RpSy can be used to validate temporal consistency of recharge products from land surface and hydrologic models and facilitate assessment of recharge-driver functional relationships in them.
Yueli Chen, Yun Xie, Xingwu Duan, and Minghu Ding
Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2024-195, https://doi.org/10.5194/essd-2024-195, 2024
Revised manuscript accepted for ESSD
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Rainfall erosivity map is crucial for identifying key areas of water erosion. Due to the limited historical precipitation data, there are certain biases in rainfall erosivity estimates in China. This study develops a new rainfall erosivity map for mainland China using 1-minute precipitation data from 60,129 weather stations, revealing that areas exceeding 4000 MJ·mm·ha−1·h−1·yr−1 of annual rainfall erosivity mainly concentrated in the southern China and southern Tibetan Plateau.
Hordur Bragi Helgason and Bart Nijssen
Earth Syst. Sci. Data, 16, 2741–2771, https://doi.org/10.5194/essd-16-2741-2024, https://doi.org/10.5194/essd-16-2741-2024, 2024
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LamaH-Ice is a large-sample hydrology (LSH) dataset for Iceland. The dataset includes daily and hourly hydro-meteorological time series, including observed streamflow and basin characteristics, for 107 basins. LamaH-Ice offers most variables that are included in existing LSH datasets and additional information relevant to cold-region hydrology such as annual time series of glacier extent and mass balance. A large majority of the basins in LamaH-Ice are unaffected by human activities.
Chengcheng Hou, Yan Li, Shan Sang, Xu Zhao, Yanxu Liu, Yinglu Liu, and Fang Zhao
Earth Syst. Sci. Data, 16, 2449–2464, https://doi.org/10.5194/essd-16-2449-2024, https://doi.org/10.5194/essd-16-2449-2024, 2024
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To fill the gap in the gridded industrial water withdrawal (IWW) data in China, we developed the China Industrial Water Withdrawal (CIWW) dataset, which provides monthly IWWs from 1965 to 2020 at a spatial resolution of 0.1°/0.25° and auxiliary data including subsectoral IWW and industrial output value in 2008. This dataset can help understand the human water use dynamics and support studies in hydrology, geography, sustainability sciences, and water resource management and allocation in China.
Pierre-Antoine Versini, Leydy Alejandra Castellanos-Diaz, David Ramier, and Ioulia Tchiguirinskaia
Earth Syst. Sci. Data, 16, 2351–2366, https://doi.org/10.5194/essd-16-2351-2024, https://doi.org/10.5194/essd-16-2351-2024, 2024
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Nature-based solutions (NBSs), such as green roofs, have appeared as relevant solutions to mitigate urban heat islands. The evapotranspiration (ET) process allows NBSs to cool the air. To improve our knowledge about ET assessment, this paper presents some experimental measurement campaigns carried out during three consecutive summers. Data are available for three different (large, small, and point-based) spatial scales.
Ralph Bathelemy, Pierre Brigode, Vazken Andréassian, Charles Perrin, Vincent Moron, Cédric Gaucherel, Emmanuel Tric, and Dominique Boisson
Earth Syst. Sci. Data, 16, 2073–2098, https://doi.org/10.5194/essd-16-2073-2024, https://doi.org/10.5194/essd-16-2073-2024, 2024
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The aim of this work is to provide the first hydroclimatic database for Haiti, a Caribbean country particularly vulnerable to meteorological and hydrological hazards. The resulting database, named Simbi, provides hydroclimatic time series for around 150 stations and 24 catchment areas.
Changming Li, Ziwei Liu, Wencong Yang, Zhuoyi Tu, Juntai Han, Sien Li, and Hanbo Yang
Earth Syst. Sci. Data, 16, 1811–1846, https://doi.org/10.5194/essd-16-1811-2024, https://doi.org/10.5194/essd-16-1811-2024, 2024
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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.
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
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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
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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
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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
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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
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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
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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.
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
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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
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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
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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
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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
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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
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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
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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.
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
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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
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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
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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
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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
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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
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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
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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
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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
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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
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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
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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
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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.
Cited articles
Allen, R. G., Pereira, L. S., Raes, D., and Smith, M.: Crop Evapotranspiration: Guidelines for computing crop water requirements, Irrigation and Drainage Paper 56, Food and Agriculture Organization of the United Nations, Rome, https://www.fao.org/3/X0490E/x0490e00.htm#Contents (last access: 18 July 2021), 1998.
Aminzadeh, M., Roderick, M. L., and Or, D.: A generalized complementary relationship between actual and potential evaporation defined by a reference surface temperature, Water Resour. Res., 52, 385–406, 2016.
Aouissi, J., Benabdallah, S., Chabaâne, Z. L., and Cudennec, C.: Evaluation of potential evapotranspiration assessment methods for hydrological modelling with SWAT – Application in data-scarce rural Tunisia, Agr. Water Manage., 174, 39–51, 2016.
Aschonitis, V. G., Demertzi, K., Papamichail, D., Colombani, N., and Mastrocicco, M.: Revisiting the Priestley-Taylor method for the assessment of reference crop evapotranspiration in Italy, Ital. J. Agrometeorol., 20, 5–18, 2015.
Aschonitis, V. G., Papamichail, D., Demertzi, K., Colombani, N., Mastrocicco, M., Ghirardini, A., Castaldelli, G., and Fano, E.-A.: High-resolution global grids of revised Priestley–Taylor and Hargreaves–Samani coefficients for assessing ASCE-standardized reference crop evapotranspiration and solar radiation, Earth Syst. Sci. Data, 9, 615–638, https://doi.org/10.5194/essd-9-615-2017, 2017.
Aubin, I., Beaudet, M., and Messier, C.: Light extinction coefficients specific to the understory vegetation of the southern boreal forest, Quebec, Can. J. Forest Res., 30, 168–177, 2000.
Barbero, R., Fowler, H. J., Lenderink, G., and Blenkinsop, S.: Is the intensification of precipitation extremes with global warming better detected at hourly than daily resolutions?, Geophys. Res. Lett., 44, 974–983, 2017.
Barbour, M. M. and Buckley, T. N.: The stomatal response to evaporative demand persists at night in Ricinus communis plants with high nocturnal conductance, Plant Cell Environ., 30, 711–721, 2007.
Beck, H. E., Zimmermann, N. E., McVicar, T. R., Vergopolan, N., Berg, A., and Wood, E. F.: Present and future Köppen-Geiger climate classification maps at 1-km resolution, Scientific Data, 5, 180214, https://doi.org/10.1038/sdata.2018.214, 2018.
Beck, H. E., Van Dijk, A. I. J. M., Larraondo, P. R., McVicar, T. R., Pan, M., Dutra, E., and Miralles, D. G.: MSWX: Global 3-hourly 0.1 bias-corrected meteorological data including near-real-time updates and forecast ensembles, B. Am. Meteorol. Soc., 103, E710–E732, 2022.
Berengena, J. and Gavilán, P.: Reference evapotranspiration estimation in a highly advective semiarid environment, J. Irrig. Drain. E., 131, 147–163, 2005.
Beven, K.: Rainfall-Runoff Modelling: The Primer, 2nd edn., John Wiley & Sons Ltd, Oxford (UK), 457 pp., ISBN 978-0-470-71459-1, 2012.
Brisson, N., Itier, B., L'Hotel, J. C., and Lorendeau, J. Y.: Parameterisation of the Shuttleworth-Wallace model to estimate daily maximum transpiration for use in crop models, Ecol. Model., 107, 159–169, 1998.
Cavalcante, R. B. L., Pontes, P. R. M., Souza, P. W. M., and de Souza, E. B.: Opposite effects of climate and land use changes on the annual water balance in the Amazon arc of deforestation, Water Resour. Res., 55, 3092–3106, 2019.
Chen, C., Park, T., Wang, X., Piao, S., Xu, B., Chaturved, R. K., Fuchs, R., Brovkin, V., Ciacis, P., Fensholt, R., Tømmervik, H., Bala, G., Zhu, Z., Nemani, R. R., and Myneni, R. B.: China and India lead in greening of the world through land-use management, Nature Sustainability, 2, 122–129, 2019.
Chen, H., Jiang, A. Z., Huang, J. J., Li, H., McBean, E., Singh, V. P., Zhang, J., Lan, Z., Gao, J., and Zhou, Z.: An enhanced Shuttleworth-Wallace model for simulation of evapotranspiration and its components, Agr. Forest Meteorol., 313, 108769, https://doi.org/10.1016/j.agrformet.2021.108769, 2022.
Cheng, W., Dan, L.i., Deng, X., Feng, J., Wang, Y., Peng, J., Tian, J., Qi, W., Liu, Z., Zheng, X., Zhou, D., Jiang, S., Zhao, H., and Wang, X.: Global monthly gridded atmospheric carbon dioxide concentrations under the historical and future scenarios, Scientific Data, 9, 83, https://doi.org/10.1038/s41597-022-01196-7, 2022.
Crago, R. and Crowley, R.: Complementary relationships for near-instantaneous evaporation, J. Hydrol., 300, 199–211, 2005.
Crow, W. T. and Kustas, W. P.: Monitoring root-zone soil moisture through the assimilation of a thermal remote sensing-based soil moisture proxy into a water balance model, Remote Sens. Environ., 112, 1268–1281, 2008.
Dai, Y., Wei, N., Yuan, H., Zhang, S., Shangguan, W., Liu, S., Lu, X., and Xin, Y.: Evaluation of soil thermal conductivity schemes for use in land surface modelling, J. Adv. Model. Earth Sy., 11, 3454–3473, 2019a.
Dai, Y., Xin, Q., Wei, N., Zhang, Y., Shangguan, W., Yuan, H., Zhang, S., Liu, S., and Lu, X.: A global high-resolution dataset of soil hydraulic and thermal properties for land surface modeling, J. Adv. Model. Earth Sy., 11, 2996–3023, 2019b.
Dallaire, G., Poulin, A., Arsenault, R., and Brissette, F.: Uncertainty of potential evapotranspiration modelling in climate change impact studies on low flows in North America, Hydrolog. Sci. J., 66, 689–702, 2021.
Damour, G., Simonneau, T., Cochard, H., and Urban, L.: An overview of models of stomatal conductance at the leaf level, Plant Cell Environ., 33, 1419–1438, 2010.
Dawson, T. E., Burgess, S. S., Tu, K. P., Oliveira, R. S., Santiago, L. S., Fisher, J. B., Simonin, K. A., and Ambrose A. R.: Nighttime transpiration in woody plants from contrasting ecosystems, Tree Physiol., 27, 561–575, 2007.
De Dios, V. R., Roy, J., Ferrio, J. P., Alday, J. G., Landais, D., Milcu, A., and Gessler, A.: Processes driving nocturnal transpiration and implications for estimating land evapotranspiration, Scientific Reports, 5, 10975, https://doi.org/10.1038/srep10975, 2015.
Douglas, E. M., Jacobs, J. M., Sumner, D. M., and Ray, R. L.: A comparison of models for estimating potential evapotranspiration for Florida land cover types, J. Hydrol., 373, 366–376, 2009.
Duursma, R. A., Blackman, C. J., Lopéz, R., Martin-StPaul, K., Cochard, H., and Medlyn, B. E.: On the minimum leaf conductance: Its role in models of plant water use, and ecological and environmental controls, New Phytol., 221, 693–705, 2019.
Eckhardt, K. and Ulbrich, U.: Potential impacts of climate change on groundwater recharge and streamflow in a central European low mountain range. J. Hydrol., 284, 244–252, 2003.
ECMWF: IFS Documentation-Cy31r1 Part IV: Physical Processes, http://www.ecmwf.int/sites/default/files/elibrary/2007/9221-part-iv-physical-processes.pdf (last access: 12 December 2022), 2007.
Elfarkh, J., Er-Raki, S., Ezzahar, J., Chehbouni, A., Aithssaine, B., Amazirh, A., Khabba, S., and Jarlan, L.: Integrating thermal stress indexes within Shuttleworth-Wallace model for evapotranspiration mapping over a complex surface, Irrigation Sci., 39, 45–61, 2021.
Emami-Bistghani, Z., Siadat, S. A., Torabi, M., Bakhshande, A., Alami, S. K., and Shiresmaeili, H.: Influence of plant density on light absorption and light extinction coefficient in sunflower cultivars, Res. Crop., 13, 174–179, 2012.
Espadafor, M., Lorite, I. J., Gavilán, P., and Berengena, J.: An analysis of the tendency of reference evapotranspiration estimates and other climate variables during the last 45 years in Southern Spain, Agr. Water Manage., 98, 1045–1061, 2011.
Fang, H., Jiang, C., Li, W., Wei, S., Baret, F., Chen, J. M., Garcia-Haro, J., Liang, S., Liu, R., Myneni, R. B., Pinty, B., Xiao, Z., and Zhu, Z.: Characterization and intercomparison of Global Moderate Resolution Leaf Area Index (LAI) products: Analysis of climatologies and theoretical uncertainties, J. Geophys. Res.-Biogeo., 118, 529–548, 2013.
Fauset, S., Gloor, M. U., Aidar, M. P. M., Freitas, H. C., Fyllas, N. M., Marabesi, M. A., Rochelle, A. L. C. A., Shenkin, Vieira, S. A., and Joly, C. A.: Tropical forest light regimes in a human-modified landscape, Ecosphere, 8, e02002, https://doi.org/10.1002/ecs2.2002, 2017.
Field, C. B., Jackson, R. B., and Mooney, H. A.: Stomatal responses to increased CO2: implications from the plant to the global scale, Plant Cell Environ., 18, 1214–1225, 1995.
Fisher, J. B., DeBiase, T. A., Qi, Y., Xu, M., and Goldstein, A. H.: Evapotranspiration models compared on a Sierra Nevada forest ecosystem, Environ. Modell. Softw., 20, 783–796, 2005.
Fisher, J. B., Whittaker, R. J., and Malhi, Y.: ET come home: potential evapotranspiration in geographical ecology, Global Ecol. Biogeogr., 20, 1–18, https://doi.org/10.1111/j.1466-8238.2010.00578.x, 2011.
Foken, T.: The energy balance closure problem: an overview, Ecol. Appl., 18, 1351–1367, 2008.
Franks, P. J. and Beerling, D. J.: Maximum leaf conductance driven by CO2 effects on stomatal size and density over geologic time, P. Natl. Acad. Sci. USA, 106, 10343–10347, 2008.
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, 68–182, 2010.
Gang, C.-C, Wang, Z.-Q, Yang, Y., Chen, Y.-Z., Zhang, Y.-Z., Li, J.-L., and Cheng, J.-M.: The NPP spatiotemporal variation of global grassland ecosystems in response to climate change over the past 100 years, Acta Prataculturae Sinica, 25, 1–14, https://doi.org/10.11686/cyxb2016148, 2016 (in Chinese with English Abstract).
Gardiol, J. M., Serio, L. A., and Maggiora, A. I. D.: Modeling evapotranspiration of corn (Zea mays) under different plant densities, J. Hydrol., 217, 188–196, 2003.
Gardner, A., Jiang, M., Ellsworth, D., MacKenzie, A. R., Pritchard, J., Bader, M. K.-F., Barton, C., Bernacchi, C., Calfapietra, C., Crous, K. Y., Dusenge, M. E., Gimeno, T. E., Hall, M., Lamba, S., Leuzinger, S., Uddling, J., Warren, J., Wallin, G., and Medlyn, B.: Optimal stomatal theory predicts CO2 responses of stomatal conductance in both gymnosperm and angiosperm trees, New Phytol., 153, 477–484, 2022.
Gash, J. H. C., Lloyd, C. R., and Lachaud, G.: Estimating sparse forest rainfall interception with an analytical model, J. Hydrol., 170, 79–86, 1995.
Gedney, N., Cox, P. M., Betts, R. A., Boucher, O., Huntingford, C., and Stott, P. A.: Detection of a direct carbon dioxide effect in continental river runoff records, Nature, 439, 835–838, 2006.
Gentine, P., Entekhabi, D., Chehbouni, A., Boulet, G., and Duchemin, B.: Analysis of evaporative fraction diurnal behavior, Agr. Forest Meteorol., 143, 13–29, 2007.
Gentine, P., Entekhabi, D., and Polcher, J.: The diurnal behavior of evaporative fraction in the soil-vegetation-atmospheric boundary layer continuum, J. Hydrometeorol., 12, 1530–1546, 2011.
Gong, X., Liu, H., Sun, J., Gao, Y., Zhang, X., Jha, S. K., Zhang, H., Ma, X., and Wang, W.: A proposed surface resistance model for the Penman-Monteith formula to estimate evapotranspiration in a solar greenhouse, J. Arid Land, 9, 530–546, 2017.
Groh, J., Pütz, T., Gerke, H., Vanderborght, J., and Vereecken, H.: Quantification and prediction of nighttime evapotranspiration for two distinct grassland ecosystems, Water Resour. Res., 55, 2961–2975, 2019.
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, 2012.
Han, Q., Wang, T., Wang, L., Smettem, K., Mai, M., and Chen X.: Comparison of nighttime with daytime evapotranspiration responses to environmental controls across temporal scales along a climate gradient, Water Resour. Res., 57, e2021WR029638, https://doi.org/10.1029/2021WR029638, 2021.
Hargreaves, G. H. and Samani, Z. A.: Estimating potential evapotranspiration. Journal of the Irrigation and Drainage Division, Proceedings of the American Society of Civils Engineers, 108, 225–230, 1983.
Harris, I., Osborn, T. J., Jones, P., and Lister, D.: Version 4 of the CRU TS monthly high-resolution gridded multivariate climate dataset, Scientific Data, 7, 109, https://doi.org/10.1038/s41597-020-0453-3, 2020.
Hawkins, B. A, Field, R., Cornell, H. V., Currie, D. J., Guégan, J. F., Kaufman, D. M., Kerr, J. T., Mittelbach, G. G., Oberdorff, T., and O'Brien, E. M.: Energy, water, and broad-scale geographic patterns of species richness, Ecology, 84, 3105–3117, 2003.
Hersbach, H., Bell, B., Berrisford, P., Biavati, G., Horányi, A., Muñoz Sabater, J., Nicolas, J., Peubey, C., Radu, R., Rozum, I., Schepers, D., Simmons, A., Soci, C., Dee, D., and Thépaut, J.-N.: ERA5 monthly averaged data on single levels from 1979 to present, Copernicus Climate Change Service (C3S) Climate Data Store (CDS) [data set], https://doi.org/10.24381/cds.f17050d7, 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., De 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.-N.: The ERA5 global reanalysis, Q. J. Roy. Meteor. Soc., 146, 1999–2049, 2020.
Hinkelman, L. M.: The Global Radiative Energy Budget in MERRA and MERRA-2: Evaluation with Respect to CERES EBAF Data, J. Climate, 32, 1973–1994, 2019.
Hu, Z., Yu, G., Zhou, Y., Sun, X., Li, Y., Shi, P., Wang, Y., Song, X., Zheng, Z., Zhang, L., and Li, S.: Partitioning of evapotranspiration and its controls in four grassland ecosystems: Application of a two-source model, Agr. Forest Meteorol., 149, 1410–1420, 2009.
Hu, Z., Li, S., Yu, G., Sun, X., Zhang, L., and Han, S.: Modeling evapotranspiration by combing a two-source model, a leaf stomatal model, and a light-use efficiency model, J. Hydrol., 501, 186–192, 2013.
Huang, H., Liu, C., Wang, X., Biging, G. S., Chen, Y., Yang, J., and Gong, P.: Mapping vegetation heights in China using slope correction ICESat data, SRTM, MODIS-derived and climate data, ISPRS J. Photogramm., 129, 189–199, https://doi.org/10.1016/j.isprsjprs.2017.04.020, 2017.
Huang, S., Yan, H., Zhang, C., Wang, G., Acquah, S. J., Yu, J., Li, L., Ma, J., and Darko, R. O.: Modeling evapotranspiration for cucumber plants based on the Shuttleworth-Wallace model in a Venlo-type greenhouse, Agr. Water Manage., 228, 105861, https://doi.org/10.1016/j.agwat.2019.105861, 2020.
International Food Policy Research Institute: Global spatially-disaggregated crop production statistics data for 2010 version 2.0, Harvard Dataverse [data set], https://doi.org/10.7910/DVN/PRFF8V, 2019.
IPCC: Summary for policymakers, in: Climate change 2014: impacts, adaptation, and vulnerability. part a: global and sectoral aspects, edited by: Field, C. B., Barros, V. R., Dokken, D. J., Mach, K. J., Mastrandrea, M. D., Bilir, T. E., Chatterjee, M., Ebi, K. L., Estrada, Y. O., Genova, R. C., Girma, B., Kissel, E. S., Levy, A. N., MacCracken, S., Mastrandrea, P. R., and White, L. L., contribution of working group ii to the fifth assessment report of the intergovernmental panel on climate change, Cambridge University Press, Cambridge, 1–32, https://www.ipcc.ch/site/assets/uploads/2018/02/ar5_wgII_spm_en.pdf (last access: 29 July 2021), 2014.
Iritz, Z., Lindroth, A., Heikinheimo, M., Grelle, A., and Kellner, E.: Test of a modified Shuttleworth-Wallace estimate of boreal forest evaporation, Agr. Forest Meteorol., 98–99, 605–619, 1999.
Itenfisu, D., Elliot, R., Allen, R., and Walter, I.: Comparison of reference evapotranspiration calculations across a range of climates, in: Proceedings of the 4th National Irrigation Symposium, Phoenix, Arizona, USA, 14–16 November, 2000, St. Joseph, ASAE Edn., 216–227, https://www.cabdirect.org/cabdirect/abstract/20003037387 (last access: 1 May 2022), 2000.
Jarvis, P. G.: Interpretation of variations in leaf water potential and stomatal conductance found in canopies in field, Philos. T. Roy. Soc. B, 273, 593–610, 1976.
Jensen, M., Burman, R., and Allen, R.: Evapotranspiration and irrigation water requirements, in: ASCE manual No. 70, ASCE Edn., New York, 332 pp., ISBN 0872627632, 1990.
Jiang, Y., Tang, R., and Li, Z. L.: A physical full-factorial scheme for gap-filling of eddy covariance measurements of daytime evapotranspiration, Agr. Forest Meteorol., 323, 109087, https://doi.org/10.1016/j.agrformet.2022.109087, 2022.
Jourdier, B.: Evaluation of ERA5, MERRA-2, COSMO-REA6, NEWA and AROME to simulate wind power production over France, Adv. Sci. Res., 17, 63–77, 2020.
Kadeba, A., Nacoulma, B. M. I., Ouédraogo, A., Bachmann, Y., Thiombiano, A., Schmidt, M., and Boussim, J. I.: Land cover change and plants diversity in the Sahel: a case study from northern Burkina Faso, Ann. For. Res., 58, 109–123, 2015.
Kahler, D. M. and Brutsaert, W.: Complementary relationship between daily evaporation in the environment and pan evaporation, Water Resour. Res., 42, W05413, https://doi.org/10.1029/2005WR004541, 2006.
Kerr, J.: Butterfly species richness patterns in Canada: energy, heterogeneity, and the potential consequences of climate change, Conserv. Ecol., 5, 10, https://doi.org/10.5751/ES-00246-050110, 2001.
Kool, D., Agam, N., Lazarovitch, N., Heitman, J. L., Sauer, T. J., and Ben-Gal, A.: A review of approaches for evapotranspiration partitioning, Agr. Forest Meteorol., 184, 56–70, 2014.
Lagos, L. O., Martin, D. L., Verma, S. B., Irmak, S., Irmak, A., Eisenhauer, D., and Suyker, A.: Surface energy balance model of transpiration from variable canopy cover and evaporation from residue-covered or bare soil systems: model evaluation, Irrigation Sci., 31, 135–150, 2013.
Lang, N., Kalischek, N., Armston, J., Schindler, K., Dubayah, R., and Wegner, J. D.: Global canopy top height estimates from GEDI LIDAR waveforms for 2019, Zenodo [data set], https://doi.org/10.5281/zenodo.5112903, 2021.
Lang, N., Kalischek, N., Armston, J., Schindler, K., Dubayah, R., and Wegner, J. D.: Global canopy height regression and uncertainty estimation from GEDI LIDAR waveforms with deep ensembles, Remote Sens. Environ., 268, 112760, https://doi.org/10.1016/j.rse.2021.112760, 2022.
Lawrence, D. M., Thornton, P. E., Oleson, K. W., and Bonan, G. B.: The partitioning of evapotranspiration into transpiration, soil evaporation, and canopy evaporation in a GCM: impacts on land-atmosphere interaction, J. Hydrometeorol., 8, 862–880, 2007.
Lhomme, J. P.: Stomatal control of transpiration: Examination of the Jarvis-type representation of canopy resistance in relation to humidity, Water Resour. Res., 37, 689–699, 2001.
Li, H. and Ma, Y.: Application on classification of Qinghai grassland by advanced comprehensive and sequential classification, Acta Prataculturae Sinica, 18, 76–82, 2009 (in Chinese with English Abstract).
Liang, S., Zhao, X., Liu, S., Yuan, W., Cheng, X., Xiao, Z., Zhang, X., Liu, Q., Cheng, J., Tang, H., Qu, Y., Bo, Y., Qu, Y., Ren, H., Yu, K., and Twonshend, J.: A long-term Global Land Surface Satellite (GLASS) data-set for environmental studies, Int. J. Digit. Earth, 6, 5–33, 2013.
Liang, T. G., Feng, Q. S., Huang, X. D., and Ren, J. D.: Review in the study of comprehensive sequential classification system of grassland, Acta Prataculturae Sinica, 20, 252–258, 2011 (in Chinese with English Abstract).
Lindroth, A. and Perttu, K.: Simple calculation of extinction coefficient of forest stands, Agr. Meteorol., 25, 97–110, 1981.
Liu, C., Sun G., McNulty, S. G., and Kang, S.: An improved evapotranspiration model for an apple orchard in northwestern China, Transactions of the American Society of Agricultural and Biological Engineers, 58, 1253–1264, 2015.
Liu, C., Sun, G., McNulty, S. G., Noormets, A., and Fang, Y.: Environmental controls on seasonal ecosystem evapotranspiration/potential evapotranspiration ratio as determined by the global eddy flux measurements, Hydrol. Earth Syst. Sci., 21, 311–322, https://doi.org/10.5194/hess-21-311-2017, 2017.
Liu, H., Gong, P., Wang, J., Clinton, N., Bai, Y., and Liang, S.: Annual dynamics of global land cover and its long-term changes from 1982 to 2015, Earth Syst. Sci. Data, 12, 1217–1243, https://doi.org/10.5194/essd-12-1217-2020, 2020a.
Liu, H., Gong, P., Wang, J., Nicholas, C., Bai, Y., and Liang, S.: Annual dynamics of global land cover and its long-term changes from 1982 to 2015, PANGAEA [data set], https://doi.org/10.1594/PANGAEA.913496, 2020b.
Liu, J., Chen, J. M., and Cihlar, J.: Mapping evapotranspiration based on remote sensing: an application to Canada's landmass, Water Resour. Res., 39, 1189, https://doi.org/10.1029/2002WR001680, 2003.
Liu, Q., McVicar, T. R., Yang, Z., Donohue, R. J., Liang, L., and Yang, Y.: The hydrological effects of varying vegetation characteristics in a temperate water-limited basin: development of the dynamic Budyko-Choudhury-Porporato (dBCP) model, J. Hydrol., 543, 595–611, 2016.
Liu, X., Xu, C., Zhong, X., Li, Y., Yuan, X., and Cao, J.: Comparison of 16 models for reference crop evapotranspiration against weighing lysimeter measurement, Agr. Water Manage., 184, 145–155, 2017.
Liu, Y., Liu, R., and Chen, J. M.: Retrospective retrieval of long-term consistent global leaf area index (1981–2011) from combined AVHRR and MODIS data, J. Geophys. Res.-Biogeo., 117, G04003, https://doi.org/10.1029/2012JG002084, 2012.
Liu, Y., Xiao, J., Ju, W., Xu, K., Zhou, Y., and Zhao, Y.: Recent trends in vegetation greenness in China significantly altered annual evapotranspiration and water yield, Environ. Res. Lett., 11, 094010, https://doi.org/10.1088/1748-9326/11/9/094010, 2016.
Liu, Y., Xiao, J., Ju, W., Zhu, G., Wu, X., Fan, W., Li, D., and Zhou, Y.: Satellite-derived LAI products exhibit large discrepancies and can lead to substantial uncertainty in simulated carbon and water fluxes, Remote Sens. Environ., 206, 174–188, 2018.
Lo Seen, D., Chehbouni, A., Njoku, E., Saatchi, S., Mougin, E., and Monteny, B.: An approach to couple vegetation functioning and soil-vegetation-atmosphere-transfer models for semiarid grasslands during the HAPEX-Sahel experiment, Agr. Forest Meteorol., 83, 49–74, 1997.
Lu, J., Sun, G., McNulty, S. G., and Amatya, D. M.: Modeling actual evapotranspiration from forested watersheds across the southeastern United States, J. Am. Water Resour. As., 39, 886–896, 2003.
Lu, J., Sun, G., McNulty, S. G., and Amatya, D. M.: A comparison of six potential evapotranspiration methods for regional use in the southeastern United States, J. Am. Water Resour. As., 41, 621–633, 2005.
Maddoni, G. A., Otegui, M. E., and Cirilo. A. G.: Plant population density, row spacing and hybrid effects on maize canopy architecture and light attenuation, Field Crop. Res., 71, 183–193, 2001.
Maes, W. H. and Steppe, K.: Estimating evapotranspiration and drought stress with ground-based thermal remote sensing in agriculture: a review, J. Exp. Bot., 63, 4671–4712, 2012.
Maes, W. H., Pashuysen, T., Trabucco, A., Veroustraete, F., and Muys, B.: Does energy dissipation increase with ecosystem succession? Testing the ecosystem exergy theory combining theoretical simulations and thermal remote sensing observations, Ecol. Model., 23–24, 3917–3941, 2011.
Maes, W. H., Gentine, P., Verhoest, N. E. C., and Miralles, D. G.: Potential evaporation at eddy-covariance sites across the globe, Hydrol. Earth Syst. Sci., 23, 925–948, https://doi.org/10.5194/hess-23-925-2019, 2019.
Maki, T., Ikegami, M., Fujita, T., Hirahara, T., Yamada, K., Mori, K., Takeuchi, A., Tsutsumi, Y., Suda, K., and Conway, T. J.: New technique to analyse global distributions of CO2 concentration and fluxes from non-processed observational data, Tellus B, 62, 797–809, https://doi.org/10.1111/j.1600-0889.2010.00488.x, 2010.
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.
Martínez-Vilalta, J., Poyatos, R., Aguadé, D., Retana, J., and Mencuccini, M.: A new look at water transport regulation in plants, New Phytol., 204, 105–115, 2014.
McVicar, T. R., Van Niel, T. G., Li, L. T., Hutchinson, M. F., Mu, X. M., and Liu, Z. H.: Spatially distributing monthly reference evapotranspiration and pan evaporation considering topographic influences, J. Hydrol., 338, 196–220, 2007.
Medlyn, B. E., Barton, C. V. M., Broadmeadow, M. S. J., Ceulemans, R., De Angelis, P., Forstreuter, M., Freeman, M., Jackson, S. B., Kellomäki, S., Laitat, E., Rey, A., Roberntz, P., Sigurdsson, B. D., Strassemeyer, J., Wang, K., Curtis, P. S., and Jarvis, P. G.: Stomatal conductance of forest species after long-term exposure to elevated CO2 concentrations: a synthesis, New Phytol., 149, 247–264, 2001.
Milly, P. C. and Dunne, K. A.: Potential evapotranspiration and continental drying, Nat. Clim. Change, 6, 946–951, 2016.
Miralles, D. G., Holmes, T. R. H., De Jeu, R. A. M., Gash, J. H., Meesters, A. G. C. A., and Dolman, A. J.: Global land-surface evaporation estimated from satellite-based observations, Hydrol. Earth Syst. Sci., 15, 453–469, https://doi.org/10.5194/hess-15-453-2011, 2011.
Mizutani, K., Yamanoi, K., Ikeda, T., and Watanabe, T.: Applicability of the eddy correlation method to measure sensible heat transfer to forest under rainfall conditions, Agr. Forest Meteorol., 86, 193–203, 1997.
Mo, X., Liu, S., Lin, Z., and Zhao, W.: Simulating temporal and spatial variation of evapotranspiration over the Lushi basin, J. Hydrol., 285, 125–142, 2004.
Molod, A., Takacs, L., Suarez, M., and Bacmeister, J.: Development of the GEOS-5 atmospheric general circulation model: evolution from MERRA to MERRA2, Geosci. Model Dev., 8, 1339–1356, https://doi.org/10.5194/gmd-8-1339-2015, 2015.
Monteith, J. L.: Evaporation and environment, Sym. Soc. Exp. Biol., 19, 205–234, 1965.
Moore, G. W., Cleverly, J., and Owens, M. K.: Nocturnal transpiration in riparian Tamarix thickets authenticated by sap flux, eddy covariance and leaf gas exchange measurements, Tree Physiol., 28, 521–528, 2008.
Morison, J. I. L. and Gifford, R. M.: Plant growth and water use with limited water supply in high CO2 concentrations. I. Leaf area, water use and transpiration, Funct. Plant Biol., 11, 361–374, 1984.
Mu, Q., Zhao, M., and Running, S. W.: MODIS Global Terrestrial Evapotranspiration (ET), Product (NASA MOD16A2/A3), Algorithm Theoretical Basis Document, Collection 5, NASA Headquarters, https://lpdaac.usgs.gov/documents/93/MOD16_ATBD.pdf (last access: 30 June 2022), 2013.
Mu, Q. Z., Zhao, M. S., and Running, S.W.: Improvements to a MODIS global terrestrial evapotranspiration algorithm, Remote Sens. Environ., 115, 1781–1800, 2011.
Nakamura, T., Maki, T., Machida, T., Matsueda, H., Sawa, Y., and Niwa, Y.: Improvement of atmospheric CO2 inversion analysis at JMA, A31B-0033, in: Proceedings of the AGU Fall Meeting, San Francisco, CA, USA, 14–18 December 2015, 2015AGUFM.A31B0033N, https://agu.confex.com/agu/fm15/webprogram/Paper64173.html (last access: 28 May 2022), 2015.
Neitsch, S. L, Arnold, J. G., Kiniry, J. R., Williams, J. R., and King, K. W.: Soil and Water Assessment Tool Theoretical Documentation: Version 2000, U.S. Department of Agriculture – Agricultural Research Service, Grassland Soil and Water Research Laboratory and Texas A&M University, Blackland Research and Extension Center, Temple, TX, https://swat.tamu.edu/media/1290/swat2000theory.pdf (last access: 3 March 2022), 2002.
Noilhan, J. and Planton, S.: A simple parameterization of land surface processes for meteorological models, Mon. Weather Rev., 117, 536–549, 1989.
Norby, R. J., Delucia, E. H., Gielen, B., Calfapietra, C., Giardina, C. P., King, J. S., Ledford, J., McCarthy, H. R., Moore, D. J., Ceulemans, R., De Angelis, P., Finzi, A. C., Karnosky, D. F., Kubiske, M. E., Lukac, M., Pregitzer, K. S., Scarascia-Mugnozza, G. E., Schlesinger, W. H., and Oren, R.: Forest response to elevated CO2 is conserved across a broad range of productivity, P. Natl. Acad. Sci. USA, 102, 18052–18056, 2005.
Novick, K. A., Oren, R., Stoy, P. C., Siqueira, M., and Katul, G. G.: Nocturnal evapotranspiration in eddy-covariance records from three co-located ecosystems in the Southeastern US: Implications for annual fluxes, Agr. Forest Meteorol., 149, 1491–1504, 2009.
Nutini, F., Boschetti, M., Candiani, G., Bocchi, S., and Brivio, P. A.: Evaporative fraction as an indicator of moisture condition and water stress status in semi-arid rangeland ecosystems, Remote Sensing, 6, 6300–6323, 2014.
Odhiambo, L. O. and Irmak, S.: Performance of extended Shuttleworth-Wallace model for estimating and partitioning of evapotranspiration in a partial residue-covered subsurface drip-irrigated soybean field, Transactions of the American Society of Agricultural and Biological Engineers, 54, 915–930, 2011.
O'Keefe, K. and Nippert, J. B.: Drivers of nocturnal water flux in a tallgrass prairie, Funct. Ecol., 32, 1155–1167, 2018.
Padrón, R. S., Gudmundsson, L., Michel, D., and Seneviratne, S. I.: Terrestrial water loss at night: global relevance from observations and climate models, Hydrol. Earth Syst. Sci., 24, 793–807, https://doi.org/10.5194/hess-24-793-2020, 2020.
Papagiannopoulou, C., Miralles, D., Dorigo, W. A., Verhoest, N. E. C., Depoorter, M., and Waegeman, W.: Vegetation anomalies caused by antecedent precipitation in most of the world, Environ. Res. Lett., 12, 074016, https://doi.org/10.1088/1748-9326/aa7145, 2017.
Pastorello, G., Trotta, C., Canfora, E., et al.: The FLUXNET2015 dataset and the ONEFlux processing pipeline for eddy covariance data, Scientific Data, 7, 225, https://doi.org/10.1038/s41597-020-0534-3, 2020.
Peng, Z., Tang, R., Jiang, Y., Liu, M., and Li, Z. L.: Global estimates of 500 m daily aerodynamic roughness length from MODIS data, ISPRS J. Photogramm., 183, 336–351, https://doi.org/10.1016/j.isprsjprs.2021.11.015, 2022.
Penman, H. L.: Natural evaporation from open water, bare soil and grass, P. Roy. Soc. Lond. A Mat., 1032, 120–145, 1948.
Phillips, L. B., Hansen, A. J., Flather, C. H., and Robison-Cox, J.: Applying species-energy theory to conservation: a case study for North American birds, Ecol. Appl., 20, 2007–2023, 2010.
Phillips, N. G., Lewis, J. D., Logan, B. A., and Tissue, D. T.: Inter- and intra-specific variation in nocturnal water transport in Eucalyptus, Tree Physiol., 30, 586–596, 2010.
Piao, S. L., Friedlingstein, P., Ciais, P., de Noblet-Ducoudré, N., Labat, D., and Zaehle, S.: Changes in climate and land use have a larger direct impact than rising CO2 on global river runoff trends, P. Natl. Acad. Sci. USA, 104, 5242–15247, 2007.
Potapov, P., Li, X., Hernandez-Serna, A., Tyukavina, A., Hansen, M. C., Kommareddy, A., Pickens, A., Turubanova, S., Tang, H., Silva, C. E., Armston, J., Dubayah, R., Blair, J. B., and Hofton, M.: Mapping and monitoring global forest canopy height through integration of GEDI and Landsat data, Remote Sens. Environ., 253, 112165, https://doi.org/10.1016/j.rse.2020.112165, 2020.
Powell, T. L., Bracho, R., Li, J., Dore, S., Hinkle, C. R., and Drake, B. G.: Environmental controls over net ecosystem carbon exchange of scrub oak in central Florida, Agr. Forest Meteorol., 141, 19–34, 2006.
Prakash, V., Bera, T., Pradhan, S., and Acharya, S. K.: Potential of Syngonanthus nitens fiber as a reinforcement in epoxy composite and its mechanical characterization, Journal of the Indian Academy of Wood Science, 17, 73–81, 2020.
Raab, N., Meza, F. J., Frank, N., and Bambach, N.: Empirical stomatal conductance models reveal that the isohydric behavior of an Acacia caven Mediterranean Savannah scales from leaf to ecosystem, Agr. Forest Meteorol., 213, 203–216, 2015.
Rao, L. Y., Sun, G., Ford, C. R., and Vose, J. M.: Modeling potential evapotranspiration of two forested watersheds in the southern Appalachians, T. ASABE, 54, 2067–2078, 2011.
Reddy, S. J.: An empirical method for estimating sunshine from total cloud amount, Sol. Energy, 15, 281–285, 1974.
Reichstein, M., Falge, E., Baldocchi, D., Papale, D., Aubinet, M., Berbigier, P., and Valentini, R.: On the separation of net ecosystem exchange into assimilation and ecosystem respiration: review and improved algorithm, Glob. Change Biol., 11, 1424–1439, 2005.
Roderick, M. L., Greve, P., and Farquhar G. D.: On the assessment of aridity with changes in atmospheric CO2, Water Resour. Res., 51, 5450–5463, 2015.
Running, S., Mu, Q., and Zhao, M.: MOD16A2 MODIS/Terra 95Net Evapotranspiration 8-Day L4 Global 500 m SIN Grid V006, NASA EOSDIS Land Processes DAAC [data set], https://doi.org/10.5067/MODIS/MYD16A2.006, 2017.
Saxe, H., Ellsworth, D., and Heath, J.: Tree and forest functioning in an enriched CO2 atmosphere, New Phytol., 139, 395–436, 1998.
Scheff, J.: Drought indices, drought impacts, CO2, and warming: A historical and geologic perspective, Current Climate Change Reports, 4, 202–209, 2018.
Seiller, G. and Anctil, F.: How do potential evapotranspiration formulas influence hydrological projections?, Hydrolog. Sci. J., 61, 2249–2266, 2016.
Sheffield, J., Wood, E. F., and Roderick, M. L.: Little change in global drought over the past 60 years, Nature, 491, 435–438, 2012.
Shuttleworth, W. J., and Gurney, R. J.: The theoretical relationship between foliage temperature and canopy resistance in sparse crops, Q. J. Roy. Meteor. Soc., 116, 497–519, 1990.
Shuttleworth, W. J. and Wallace, J. S.: Evaporation from sparse crops: An energy combination theory, Q. J. Roy. Meteor. Soc., 111, 839–855, 1985.
Simard, M., Pinto, N., Fisher, J. B., and Baccini, A.: Mapping forest canopy height globally with spaceborne lidar, J. Geophys. Res.-Space, 116, G0402, https://doi.org/10.1029/2011JG001708, 2011.
Singer, M. B., Asfaw, D. T., Rosolem, R., Cuthbert, M. O., Miralles, D. G., MacLeod, D., Quichimbo, E. A., and Michaelides, K.: Hourly potential evapotranspiration at 0.1∘ resolution for the global land surface from 1981–present, Scientific Data, 8, 224, https://doi.org/10.1038/s41597-021-01003-9, 2021.
Singh, V. P. and Xu, C.-Y.: Evaluation and generalization of 13 equations for determining free water evaporation, Hydrol. Process., 11, 311–323, 1997.
Sitch, S., Smith, B., Prentice, I. C., Arneth, A., Bondeau, A., Cramer, W., Kaplan, J. O., Levis, S., Lucht, W., Sykes, M. T., Thonicke, K., and Venevsky, S.: Evaluation of ecosystem dynamics, plant geography and terrestrial carbon cycling in the LPJ dynamic global vegetation model, Glob. Change Biol., 9, 161–185. 2003.
Stannard, D. I.: Comparison of Penman-Monteith, Shuttleworth-Wallace, and modified Priestley-Taylor evapotranspiration models for wildland vegetation in semiarid rangeland, Water Resour. Res., 29, 1379–139, 1993.
Sun, G., Alstad, K., Chen, J., Ford, C. R., Lin, G., Liu, C., Nan, L., McNulty, S. G., and Miao, H.: A general predictive model for estimating monthly ecosystem evapotranspiration, Ecohydrology, 4, 245–255, 2011a.
Sun, G., Caldwell, P., Noormets, A., McNulty, S. G., Cohen, E., Myers, J. M., Domec, J.-C., Treasure, E., Mu, Q., Xiao, J., John, R., and Chen, J.: Upscaling key ecosystem functions across the conterminous United States by a water-centric ecosystem model, J. Geophys. Res.-Biogeo., 116, G00J05, https://doi.org/10.1029/2010JG001573, 2011b.
Sun, S., Chen, H., Ju, W., Yu, M., Hua, W., and Yin, Y.: On the attribution of the changing hydrological cycle in Poyang Lake Basin, China. J. Hydrol., 514, 214–225, 2014.
Sun, S., Chen, H., Sun, G., Ju, W., Wang, G., Huang, J., Zhang, F., Zhu, S., and Hua, W.: Attributing the changing reference evapotranspiration in Southwest China using a new separating method, J. Hydrometeorol., 18, 777–798, 2017.
Sun, S., Bi, Z., Zhou, S., Wang, H., Li, Q., Liu, Y., Wang, G., Li, S., Chen, H., and Zhou, Y.: Spatiotemporal shifts in key hydrological variables and dominant factors over China, Hydrol. Process., 35, e14319, https://doi.org/10.1002/hyp.14319, 2021.
Sun, S., Liu, Y., Chen, Ju, W., Xu, C.-Y., Liu, Y., Zhou, B., Zhou, Y., Zhou, Y., and Yu, M.: Causes for the increases in both evapotranspiration and water yield over vegetated mainland China during the last two decades, Agr. Forest Meteorol., 324, 109118, https://doi.org/10.1016/j.agrformet.2022.109118, 2022.
Sun, S., Bi, Z., and Chen, H.: A global 5 km monthly potential evapotranspiration dataset (1982–2015) estimated by the Shuttleworth-Wallace model, National Tibetan Plateau/Third Pole Environment Data Center [data set], https://doi.org/10.11888/Terre.tpdc.300193, 2023.
Suttie, J. M., Reynolds, S. G., and Batello, C.: Grasslands of the World. Plant Production and Protection Series No. 34, Food and Agriculture Organization of the United Nations, Rome, https://www.fao.org/3/y8344e/y8344e00.htm (last access: 7 January 2022), 2005.
Tabari, H. and Talaee, P. H.: Local calibration of the Hargreaves and Priestley-Taylor equations for estimating reference evapotranspiration in arid and cold climates of Iran based on the Penman-Monteith model, J. Hydrol. Eng., 16, 837–845, 2011.
Tahiri, A. Z., Anyoji, H., and Yasuda, H.: Fixed and variable light extinction coefficients for estimating plant transpiration and soil evaporation under irrigated maize, Agr. Water Manage., 84, 184–192, 2006.
Tanguy, M., Prudhomme, C., Smith, K., and Hannaford, J.: Historical gridded reconstruction of potential evapotranspiration for the UK, Earth Syst. Sci. Data, 10, 951–968, https://doi.org/10.5194/essd-10-951-2018, 2018.
Thornthwaite, C. W.: An approach toward a rational classification of climate, Geogr. Rev., 38, 55–94, 1948.
Tomas-Burguera, M., Vicente-Serrano, S. M., Beguería, S., Reig, F., and Latorre, B.: Reference crop evapotranspiration database in Spain (1961–2014), Earth Syst. Sci. Data, 11, 1917–1930, https://doi.org/10.5194/essd-11-1917-2019, 2019.
Tourula, T. and Heikinheimo, M.: Modelling evapotranspiration from a barley field over the growing season, Agr. Forest Meteorol., 91, 237–250, 1998.
Trajkovic, S.: Hargreaves versus Penman-Monteith, J. Irrig. Drain. E., 133, 38–42, 2007.
Trenberth, K. E., Dai, A., van der Schrier, G., Jones, P. D., Barichivich, J., Briffa, K. R., and Sheffield, J.: Global warming and changes in drought, Nat. Clim. Change, 4, 17–22, 2012.
Turc, L.: Estimation of irrigation water requirements, potential evapotranspiration: a simple climatic formula evolved up to date, Ann. Agron., 12, 13–49, 1961.
Urraca, R., Huld, T., Amillo, A. M. G., Martinez-de-Pison, F. J., Kaspar, F., and Sanz-Garcia, A.: Evaluation of global horizontal irradiance estimates from ERA5 and COSMO-REA6 reanalyses using ground and satellite-based data, Sol. Energy, 164, 339–354, 2018.
Vicente-Serrano, S. M., Beguería, S., and López-Moreno, J.: A multiscalar drought index sensitive to global warming: the standardized precipitation evapotranspiration index, J. Climate, 23, 1696–1718, 2010.
Vicente-Serrano, S. M., McVicar, T. R., Miralles, D. G., Yang, Y., and Tomas-Burguera, M.: Unraveling the influence of atmospheric evaporative demand on drought and its response to climate change, WIREs Clim. Change, 11, e632, https://doi.org/10.1002/wcc.632, 2020.
Villagarcía, L., Were, A., Garcíac, M., and Domingo, F.: Sensitivity of a clumped model of evapotranspiration to surface resistance parameterisations: Application in a semi-arid environment, Agr. Forest Meteorol., 150, 1065–1078, 2010.
Wallace, J. S., Roberts, J. M., and Sivakumar, M. V. K.: The estimation of transpiration from sparse dryland millet using stomatal conductance and vegetation area indices, Agr. Forest Meteorol., 51, 35–49, 1990.
Wand, S. J. E., Midgley, G. F., Jones, M. H., and Curtis, P. S.: Responses of wild C4 and C3 grass (Poaceae) species to elevated atmospheric CO2 concentration: a meta-analytic test of current theories and perceptions, Glob. Change Biol., 5, 723–741, 1999.
Wang, H., Guan, H., Liu, N., Soulsby, C., Tetzlaff, D., and Zhang, X.: Improving the Jarvis-type model with modified temperature and radiation functions for sap flow simulations, J. Hydrol., 587, 124981, https://doi.org/10.1016/j.jhydrol.2020.124981, 2020.
Wang, K. C. and Dickinson, R. E.: A review on global terrestrial evapotranspiration: observation, modeling, climatology, and Climatic Variability, Rev. Geophys., 50, RG2005, https://doi.org/10.1029/2011RG000373, 2012.
Wang, Y., Li, G., Ding, J., Guo, Z., Tang, S., Wang, C., Huang, Q., Liu, R., and Chen, J. M.: A combined GLAS and MODIS estimation of the global distribution of mean forest canopy height, Remote Sens. Environ., 74, 24–43, 2016.
Wei, G., Zhou, L., Liu, H., Tian, Q., Ding, L., and Ran, X.: Improving evapotranspiration model performance by treating energy imbalance and interaction, Water Resour. Res., 56, e2020WR027367, https://doi.org/10.1029/2020WR027367, 2020.
Wells, N., Goddard, S., and Hayes, M. J.: A self-calibrating palmer drought severity index, J. Climate, 17, 2335–2351, 2004.
Wever, L. A., Flanagan, L. B., and Carlson, P. J.: Seasonal and interannual variation in evapotranspiration, energy balance and surface conductance in a northern temperate grassland, Agr. Forest Meteorol., 112, 31–49, 2002.
White, F.: The vegetation of Africa: a descriptive memoir to accompany the Unesco/AETFAT/UNSO vegetation map of Africa, in: Natural Resources Research 20, Unesco, Paris, ISBN 9231019554, https://unesdoc.unesco.org/ark:/48223/pf0000058054/PDF/058054engo.pdf.multi (last access: 26 January 2022), 1983.
Wild, M.: Global dimming and brightening: A review, J. Geophys. Res.-Atmos., 114, D00D16, https://doi.org/10.1029/2008JD011470, 2009.
Wilson, K., Goldstein, A., Falge, E., Aubinet, M., Baldocchi, D., Berbigier, P., Bernhofer, C., Ceulemans, R., Dolman, H., Field, C., Grelle, A., Ibrom, A., Law, B. E., Kowalski, A., Meyers, T., Moncrieff, J., Monson, R., Oechel, W., Tenhunen, J., Valentini, R., and Verma, S.: Energy balance closure at FLUXNET sites, Agr. Forest Meteorol., 113, 223–243, 2002.
Winkel, T., Payne, W., and Renno, J. F.: Ontogeny modifies the effects of water stress on stomatal control, leaf area duration and biomass partitioning of Pennisetum glaucum, New Phytol., 149, 71–82, 2001.
Wu, L., Min, L. L., Shen, Y. J., Zhou, X. X., and Liu, F. G.: Simulation of maize evapotranspiration at different growth stages using revised dual-layered model in arid Northwest China, Chinese Journal of Eco-Agriculture, 25, 634–646, 2017 (in Chinese with English Abstract).
Xiang, K., Li, Y., Horton, R., and Feng, H.: Similarity and difference of potential evapotranspiration and reference crop evapotranspiration – A review, Agr. Water Manage., 232, 106043, https://doi.org/10.1016/j.agwat.2020.106043, 2020.
Xiao, X. M., Zhang, Q. Y., Braswell, B., Urbanski, S., Boles, S., Wofsy, S., Moore III, B., and Ojima, D.: Modeling gross primary production of temperate deciduous broadleaf forest using satellite images and climate data, Remote Sens. Environ., 91, 256–270, 2004.
Xiao, Z., Liang, S., Wang, J., Chen, P., Yin, X., and Song, J.: Use of general regression neural networks for generating the GLASS Leaf Area Index product from time-series MODIS surface reflectance, IEEE T. Geosci. Remote, 52, 209–223, 2014.
Xiao, Z., Liang, S., Wang, J., and Zhao, X.: Long time series Global Land Surface Satellite (GLASS) Leaf Area Index product derived from MODIS and AVHRR data, IEEE T. Geosci. Remote, 54, 5301–5318, 2016.
Xiao, Z., Liang, S., and Jiang, B.: Evaluation of four long time-series global leaf area index products, Agr. Forest Meteorol., 246, 218–230, 2017.
Xu, B., Li, J., Park, T., Liu, Q., Zeng, Y., Yin, G., Zhao, J., Fan, W., Yang, L., and Knyazikhin, Y.: An integrated method for validating long-term leaf area index products using global networks of site-based measurements, Remote Sens. Environ., 209, 134–151, 2018.
Xu, C.-Y. and Singh, V. P.: Evaluation and generalization of radiation-based methods for calculating evaporation, Hydrol. Process., 14, 339–349, 2000.
Xu, C.-Y. and Singh, V. P.: Evaluation and generalization of temperature-based methods for calculating evaporation, Hydrol. Process., 15, 305–319, 2001.
Yang, Y. and Shang, S.: Comparison of dual-source evapotranspiration models in estimating potential evaporation and transpiration, Transactions of the Chinese Society of Agricultural Engineering, 28, 85–91, 2012.
Yang, Y., Roderick, M. L., Zhang, S., McVicar, T. R., and Donohue, R. J.: Hydrological implications of vegetation responses to elevated CO2 in climate projections, Nat. Clim. Change, 9, 44–48, 2019.
Yin, J., Feng, Q., Liang, T., Meng, B., Yang, S., Gao, J., Ge, J., Hou, M., Liu, J., Wang, W., Yu, H., and Liu, B.: Estimation of grassland height based on the random forest algorithm and remote sensing in the Tibetan Plateau, IEEE J. Sel. Top. Appl., 13, 178–186, 2019.
Yu, Q., You, L., Wood-Sichra, U., Ru, Y., Joglekar, A. K. B., Fritz, S., Xiong, W., Lu, M., Wu, W., and Yang, P.: A cultivated planet in 2010 – Part 2: The global gridded agricultural-production maps, Earth Syst. Sci. Data, 12, 3545–3572, https://doi.org/10.5194/essd-12-3545-2020, 2020.
Zeppel, M. J. B., Lewis, J. D., Phillips, N. G., and Tissue, D. T.: Consequences of nocturnal water loss: A synthesis of regulating factors and implications for capacitance, embolism and use in models, Tree Physiol., 34, 1047–1055, 2014.
Zhan, C., Orth, R., Migliavacca, M., Zaehle, S., Reichstein, M., Engel, J., Ramming, A., and Winkler, A. J.: Emergence of the physiological effects of elevated CO2 on land-atmosphere exchange of carbon and water, Glob. Change Biol., 28, 7313–7326, 2022.
Zhang, B., Kang, S., Li, F., and Zhang, L.: Comparison of three evapotranspiration models to Bowen ratio-energy balance method for a vineyard in an arid desert region of northwest China, Agr. Forest Meteorol., 148, 1629–1640, 2008.
Zhang, J., Zhao, T., Li, Z., Li, C., Li, Z., Ying, K., Shi, C., Jiang, L., and Zhang, W.: Evaluation of Surface Relative Humidity in China from the CRA-40 and Current Reanalyses, Adv. Atmos. Sci., 38, 1958–1976, 2021.
Zhang, L., Hu, Z., Fan, J., Zhou, D., and Tang, F.: A meta-analysis of the canopy light extinction coefficient in terrestrial ecosystems, Front. Earth Sci.-PRC, 8, 599–609, 2014.
Zhang, Z., Arnault, J., Wagner, S., Laux, P., and Kunstmann, H.: Impact of lateral terrestrial water flow on land-atmosphere interactions in the Heihe River Basin in China: Fully coupled modeling and precipitation recycling analysis, J. Geophys. Res.-Atmos., 124, 8401–8423, 2019.
Zhao, M. and Cao, L.: Regional response of land hydrology and carbon uptake to different amounts of solar radiation modification, Earth's Future, 10, e2022EF003288, https://doi.org/10.1029/2022EF003288, 2022.
Zhao, P., Li, S. E., Li, F. S., Du, T. S., Tong, L., and Kang, S. Z.: Comparison of dual crop coefficient method and Shuttleworth-Wallace model in evapotranspiration partitioning in a vineyard of northwest China, Agr. Water Manage., 160, 41–56, 2015.
Zhou, M. C., Ishidaira, H., Hapuarachchi, H. P., Magome, J., Kiem, A. S., and Takeuchi, K.: Estimating potential evapotranspiration using Shuttleworth-Wallace model and NOAA-AVHRR NDVI data to feed a distributed hydrological model over the Mekong River basin, J. Hydrol., 327, 151–173, 2006.
Zhou, S., Yu, B., Zhang, Y., Huang, Y., and Wang, G.: Partitioning evapotranspiration based on the concept of underlying water use efficiency, Water Resour. Res., 52, 1160–1175, 2016.
Zhou, S., Yu, B., Zhang, Y., Huang, Y., and Wang, G.: Water use efficiency and evapotranspiration partitioning for three typical ecosystems in the Heihe River Basin, Agr. Forest Meteorol., 253–254, 261–273, 2018.
Zhu, Z., Bi, J., Pan, Y., Ganguly, S., Anav, A., Xu, L., Samanta, A., Piao, S., Nemani, R. R., and Myneni, R. B.: Global data sets of vegetation Leaf Area Index (LAI)3g and Fraction of Photosynthetically Active Radiation (FPAR)3g derived from Global Inventory Modeling and Mapping Studies (GIMMS) Normalized Difference Vegetation Index (NDVI3g) for the period 1981 to 2011, Remote Sensing, 5, 927–948, 2013.
Zhu, Z., Piao, S., Myneni, R. B., Huang, M., Zeng, Z., Canadell, J. G., Ciais, P., Sitch, S., Friedlingstein, P., Arneth, A., Cao, C., Cheng, L., Kato, E., Koven, C., Li, Y., Liu, Y., Liu, R., Mao, J., Pan, Y., Peng, S., Peñuelas, J., Poulter, B., Pugh, T. A. M., Stocker, B. D., Viovy, N., Wang, X., Wang, Y., Xioa, Z., Yang, H., Zaehe, S., and Zeng, N.: Greening of the earth and its drivers, Nat. Clim. Change, 6, 791–795, 2016.
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.
Based on various existing datasets, we comprehensively considered spatiotemporal differences in...
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