Articles | Volume 25, issue 7
https://doi.org/10.5194/hess-25-3805-2021
© Author(s) 2021. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/hess-25-3805-2021
© Author(s) 2021. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
02 Jul 2021
Research article |
| 02 Jul 2021
| 02 Jul 2021
Long-term relative decline in evapotranspiration with increasing runoff on fractional land surfaces
Key Laboratory of Virtual Geographical Environment (Nanjing Normal
University), Ministry of Education, Nanjing, 210023, China
School of Geographical Sciences, Nanjing Normal University, Nanjing, 210023, China
Jiangsu Center for Collaborative Innovation in Geographical
Information Resource Development and Application, Nanjing, 210023, China
Pierre Gentine
CORRESPONDING AUTHOR
Earth and Environmental Engineering Department, Columbia University, New York, NY 10027, USA
Earth Institute, Columbia University, New York, NY 10025, USA
Jiabo Yin
State Key Laboratory of Water Resources and Hydropower Engineering
Science, Wuhan University, Wuhan, 430072, China
Lijuan Chen
Key Laboratory of Virtual Geographical Environment (Nanjing Normal
University), Ministry of Education, Nanjing, 210023, China
School of Geographical Sciences, Nanjing Normal University, Nanjing, 210023, China
Jiangsu Center for Collaborative Innovation in Geographical
Information Resource Development and Application, Nanjing, 210023, China
Jianyao Chen
School of Geography and Planning, Sun Yat-sen University, Guangzhou, 510275, China
Guandong Key Laboratory for Urbanization and Geo-simulation, Sun
Yat-sen University, Guangzhou, 510275, China
Longhui Li
Key Laboratory of Virtual Geographical Environment (Nanjing Normal
University), Ministry of Education, Nanjing, 210023, China
School of Geographical Sciences, Nanjing Normal University, Nanjing, 210023, China
Jiangsu Center for Collaborative Innovation in Geographical
Information Resource Development and Application, Nanjing, 210023, China
Related authors
No articles found.
Chao Ma, Weifeng Hao, Qing Cheng, Fan Ye, Ying Qu, Jiabo Yin, Fang Xu, Haojian Wu, and Fei Li
Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2025-79, https://doi.org/10.5194/essd-2025-79, 2025
Preprint under review for ESSD
Short summary
Short summary
Antarctic sea ice albedo is a key factor influencing the energy balance of the cryosphere. Here we present a daily 1 km shortwave albedo product for Antarctic sea ice from 2012 to 2021, based on VIIRS reflectance data. Additionally, we reconstructed the albedo for missing pixels due to cloud cover. This dataset can be used to assess changes in Antarctic sea ice, radiation budget, and the strength of sea ice albedo feedback mechanisms, as well as their potential interconnections.
Mitra Cattry, Wenli Zhao, Juan Nathaniel, Jinghao Qiu, Yao Zhang, and Pierre Gentine
EGUsphere, https://doi.org/10.5194/egusphere-2024-3726, https://doi.org/10.5194/egusphere-2024-3726, 2025
This preprint is open for discussion and under review for Geoscientific Model Development (GMD).
Short summary
Short summary
Climate change alters Mediterranean biota, affecting how they absorb and store carbon. These associated impacts arise from short- and long-term effects of rainfall, temperature, and other atmospheric forcings, which existing tools struggle to capture. This study presents a memory-integrated model combining high- and low-resolution data to track daily ecosystem responses. By analyzing past conditions, we show how earlier conditions shape plant carbon uptake and improve predictions.
Wenli Zhao, Alexander J. Winkler, Markus Reichstein, Rene Orth, and Pierre Gentine
EGUsphere, https://doi.org/10.5194/egusphere-2025-365, https://doi.org/10.5194/egusphere-2025-365, 2025
Preprint archived
Short summary
Short summary
We developed a machine learning model that accounts for the memory effects of soil moisture and vegetation to predict Evaporative Fraction (EF) without relying on soil moisture as a direct input. The model accurately predicts EF during dry periods for the unseen sites, highlighting the key of meteorological memory effects. The learned memory effect related to rooting depth and soil water holding capacity could potentially serve as proxies for assessing the plant water stress.
Jiaoyang Wang, Dedi Liu, Shenglian Guo, Lihua Xiong, Pan Liu, Hua Chen, Jie Chen, Jiabo Yin, and Yuling Zhang
Hydrol. Earth Syst. Sci. Discuss., https://doi.org/10.5194/hess-2024-399, https://doi.org/10.5194/hess-2024-399, 2025
Revised manuscript accepted for HESS
Short summary
Short summary
The unclear feedback loops of water supply-hydropower generation-environmental conservation (SHE) nexus with inter-basin water diversion projects (IWDPs) increase the uncertainty in the rational scheduling of water resources for the water receiving and water donation areas. To address the different impacts of IWDPs on the dynamic SHE nexus and explore collaborative states, a framework was proposed to identify these impacts across the multiple temporal and spatial scales in a reservoirs group.
Ruikang Zhang, Dedi Liu, Lihua Xiong, Jie Chen, Hua Chen, and Jiabo Yin
Hydrol. Earth Syst. Sci., 28, 5229–5247, https://doi.org/10.5194/hess-28-5229-2024, https://doi.org/10.5194/hess-28-5229-2024, 2024
Short summary
Short summary
Flash flood warnings cannot be effective without people’s responses to them. We propose a method to determine the threshold of issuing warnings based on a people’s response process simulation. The results show that adjusting the warning threshold according to people’s tolerance levels to the failed warnings can improve warning effectiveness, but the prerequisite is to increase forecasting accuracy and decrease forecasting variance.
Rutong Liu, Jiabo Yin, Louise Slater, Shengyu Kang, Yuanhang Yang, Pan Liu, Jiali Guo, Xihui Gu, Xiang Zhang, and Aliaksandr Volchak
Hydrol. Earth Syst. Sci., 28, 3305–3326, https://doi.org/10.5194/hess-28-3305-2024, https://doi.org/10.5194/hess-28-3305-2024, 2024
Short summary
Short summary
Climate change accelerates the water cycle and alters the spatiotemporal distribution of hydrological variables, thus complicating the projection of future streamflow and hydrological droughts. We develop a cascade modeling chain to project future bivariate hydrological drought characteristics over China, using five bias-corrected global climate model outputs under three shared socioeconomic pathways, five hydrological models, and a deep-learning model.
Jinghua Xiong, Shenglian Guo, Abhishek, Jiabo Yin, Chongyu Xu, Jun Wang, and Jing Guo
Hydrol. Earth Syst. Sci., 28, 1873–1895, https://doi.org/10.5194/hess-28-1873-2024, https://doi.org/10.5194/hess-28-1873-2024, 2024
Short summary
Short summary
Temporal variability and spatial heterogeneity of climate systems challenge accurate estimation of probable maximum precipitation (PMP) in China. We use high-resolution precipitation data and climate models to explore the variability, trends, and shifts of PMP under climate change. Validated with multi-source estimations, our observations and simulations show significant spatiotemporal divergence of PMP over the country, which is projected to amplify in future due to land–atmosphere coupling.
Jiabo Yin, Louise J. Slater, Abdou Khouakhi, Le Yu, Pan Liu, Fupeng Li, Yadu Pokhrel, and Pierre Gentine
Earth Syst. Sci. Data, 15, 5597–5615, https://doi.org/10.5194/essd-15-5597-2023, https://doi.org/10.5194/essd-15-5597-2023, 2023
Short summary
Short summary
This study presents long-term (i.e., 1940–2022) and high-resolution (i.e., 0.25°) monthly time series of TWS anomalies over the global land surface. The reconstruction is achieved by using a set of machine learning models with a large number of predictors, including climatic and hydrological variables, land use/land cover data, and vegetation indicators (e.g., leaf area index). Our proposed GTWS-MLrec performs overall as well as, or is more reliable than, previous TWS datasets.
Jatan Buch, A. Park Williams, Caroline S. Juang, Winslow D. Hansen, and Pierre Gentine
Geosci. Model Dev., 16, 3407–3433, https://doi.org/10.5194/gmd-16-3407-2023, https://doi.org/10.5194/gmd-16-3407-2023, 2023
Short summary
Short summary
We leverage machine learning techniques to construct a statistical model of grid-scale fire frequencies and sizes using climate, vegetation, and human predictors. Our model reproduces the observed trends in fire activity across multiple regions and timescales. We provide uncertainty estimates to inform resource allocation plans for fuel treatment and fire management. Altogether the accuracy and efficiency of our model make it ideal for coupled use with large-scale dynamical vegetation models.
Youjiang Shen, Dedi Liu, Liguang Jiang, Karina Nielsen, Jiabo Yin, Jun Liu, and Peter Bauer-Gottwein
Earth Syst. Sci. Data, 14, 5671–5694, https://doi.org/10.5194/essd-14-5671-2022, https://doi.org/10.5194/essd-14-5671-2022, 2022
Short summary
Short summary
A data gap of 338 Chinese reservoirs with their surface water area (SWA), water surface elevation (WSE), and reservoir water storage change (RWSC) during 2010–2021. Validation against the in situ observations of 93 reservoirs indicates the relatively high accuracy and reliability of the datasets. The unique and novel remotely sensed dataset would benefit studies involving many aspects (e.g., hydrological models, water resources related studies, and more).
Jinghua Xiong, Shenglian Guo, Abhishek, Jie Chen, and Jiabo Yin
Hydrol. Earth Syst. Sci., 26, 6457–6476, https://doi.org/10.5194/hess-26-6457-2022, https://doi.org/10.5194/hess-26-6457-2022, 2022
Short summary
Short summary
Although the "dry gets drier, and wet gets wetter (DDWW)" paradigm is prevalent in summarizing wetting and drying trends, we show that only 11.01 %–40.84 % of the global land confirms and 10.21 %–35.43 % contradicts the paradigm during 1985–2014 from a terrestrial water storage change perspective. Similar proportions that intensify with the increasing emission scenarios persist until the end of the 21st century. Findings benefit understanding of global hydrological responses to climate change.
Jing Tian, Zhengke Pan, Shenglian Guo, Jiabo Yin, Yanlai Zhou, and Jun Wang
Hydrol. Earth Syst. Sci., 26, 4853–4874, https://doi.org/10.5194/hess-26-4853-2022, https://doi.org/10.5194/hess-26-4853-2022, 2022
Short summary
Short summary
Most of the literature has focused on the runoff response to climate change, while neglecting the impacts of the potential variation in the active catchment water storage capacity (ACWSC) that plays an essential role in the transfer of climate inputs to the catchment runoff. This study aims to systematically identify the response of the ACWSC to a long-term meteorological drought and asymptotic climate change.
Yujie Zeng, Dedi Liu, Shenglian Guo, Lihua Xiong, Pan Liu, Jiabo Yin, and Zhenhui Wu
Hydrol. Earth Syst. Sci., 26, 3965–3988, https://doi.org/10.5194/hess-26-3965-2022, https://doi.org/10.5194/hess-26-3965-2022, 2022
Short summary
Short summary
The sustainability of the water–energy–food (WEF) nexus remains challenge, as interactions between WEF and human sensitivity and water resource allocation in water systems are often neglected. We incorporated human sensitivity and water resource allocation into a WEF nexus and assessed their impacts on the integrated system. This study can contribute to understanding the interactions across the water–energy–food–society nexus and improving the efficiency of resource management.
Jinghua Xiong, Shenglian Guo, Jie Chen, and Jiabo Yin
Hydrol. Earth Syst. Sci. Discuss., https://doi.org/10.5194/hess-2021-645, https://doi.org/10.5194/hess-2021-645, 2022
Manuscript not accepted for further review
Short summary
Short summary
Although the “dry gets drier and wet gets wetter” (DDWW) paradigm is widely used to describe the trends in wetting and drying globally, we show that 27.1 % of global land agrees with the paradigm, while 22.4 % shows the opposite pattern during the period 1985–2014 from the perspective of terrestrial water storage change. Similar percentages are discovered under different scenarios during the future period. Our findings will benefit the understanding of hydrological responses under climate change.
Ana Bastos, René Orth, Markus Reichstein, Philippe Ciais, Nicolas Viovy, Sönke Zaehle, Peter Anthoni, Almut Arneth, Pierre Gentine, Emilie Joetzjer, Sebastian Lienert, Tammas Loughran, Patrick C. McGuire, Sungmin O, Julia Pongratz, and Stephen Sitch
Earth Syst. Dynam., 12, 1015–1035, https://doi.org/10.5194/esd-12-1015-2021, https://doi.org/10.5194/esd-12-1015-2021, 2021
Short summary
Short summary
Temperate biomes in Europe are not prone to recurrent dry and hot conditions in summer. However, these conditions may become more frequent in the coming decades. Because stress conditions can leave legacies for many years, this may result in reduced ecosystem resilience under recurrent stress. We assess vegetation vulnerability to the hot and dry summers in 2018 and 2019 in Europe and find the important role of inter-annual legacy effects from 2018 in modulating the impacts of the 2019 event.
Andrew F. Feldman, Daniel J. Short Gianotti, Alexandra G. Konings, Pierre Gentine, and Dara Entekhabi
Biogeosciences, 18, 831–847, https://doi.org/10.5194/bg-18-831-2021, https://doi.org/10.5194/bg-18-831-2021, 2021
Short summary
Short summary
We quantify global plant water uptake durations after rainfall using satellite-based plant water content measurements. In wetter regions, plant water uptake occurs within a day due to rapid coupling between soil and plant water content. Drylands show multi-day plant water uptake after rain pulses, providing widespread evidence for slow rehydration responses and pulse-driven growth responses. Our results suggest that drylands are sensitive to projected shifts in rainfall intensity and frequency.
Manuel Schlund, Axel Lauer, Pierre Gentine, Steven C. Sherwood, and Veronika Eyring
Earth Syst. Dynam., 11, 1233–1258, https://doi.org/10.5194/esd-11-1233-2020, https://doi.org/10.5194/esd-11-1233-2020, 2020
Short summary
Short summary
As an important measure of climate change, the Equilibrium Climate Sensitivity (ECS) describes the change in surface temperature after a doubling of the atmospheric CO2 concentration. Climate models from the Coupled Model Intercomparison Project (CMIP) show a wide range in ECS. Emergent constraints are a technique to reduce uncertainties in ECS with observational data. Emergent constraints developed with data from CMIP phase 5 show reduced skill and higher ECS ranges when applied to CMIP6 data.
Karina von Schuckmann, Lijing Cheng, Matthew D. Palmer, James Hansen, Caterina Tassone, Valentin Aich, Susheel Adusumilli, Hugo Beltrami, Tim Boyer, Francisco José Cuesta-Valero, Damien Desbruyères, Catia Domingues, Almudena García-García, Pierre Gentine, John Gilson, Maximilian Gorfer, Leopold Haimberger, Masayoshi Ishii, Gregory C. Johnson, Rachel Killick, Brian A. King, Gottfried Kirchengast, Nicolas Kolodziejczyk, John Lyman, Ben Marzeion, Michael Mayer, Maeva Monier, Didier Paolo Monselesan, Sarah Purkey, Dean Roemmich, Axel Schweiger, Sonia I. Seneviratne, Andrew Shepherd, Donald A. Slater, Andrea K. Steiner, Fiammetta Straneo, Mary-Louise Timmermans, and Susan E. Wijffels
Earth Syst. Sci. Data, 12, 2013–2041, https://doi.org/10.5194/essd-12-2013-2020, https://doi.org/10.5194/essd-12-2013-2020, 2020
Short summary
Short summary
Understanding how much and where the heat is distributed in the Earth system is fundamental to understanding how this affects warming oceans, atmosphere and land, rising temperatures and sea level, and loss of grounded and floating ice, which are fundamental concerns for society. This study is a Global Climate Observing System (GCOS) concerted international effort to obtain the Earth heat inventory over the period 1960–2018.
Lei Gu, Jie Chen, Jiabo Yin, Sylvia C. Sullivan, Hui-Min Wang, Shenglian Guo, Liping Zhang, and Jong-Suk Kim
Hydrol. Earth Syst. Sci., 24, 451–472, https://doi.org/10.5194/hess-24-451-2020, https://doi.org/10.5194/hess-24-451-2020, 2020
Short summary
Short summary
Focusing on the multifaceted nature of droughts, this study quantifies the change in global drought risks for 1.5 and 2.0 °C warming trajectories by a multi-model ensemble under three representative concentration pathways (RCP2.6, 4.5 and 8.5). Socioeconomic exposures are investigated by incorporating the dynamic shared socioeconomic pathways (SSPs) into the drought impact assessment. The results show that even the ambitious 1.5 °C warming level can cause substantial increases on the global scale.
Pierre Gentine, Adam Massmann, Benjamin R. Lintner, Sayed Hamed Alemohammad, Rong Fu, Julia K. Green, Daniel Kennedy, and Jordi Vilà-Guerau de Arellano
Hydrol. Earth Syst. Sci., 23, 4171–4197, https://doi.org/10.5194/hess-23-4171-2019, https://doi.org/10.5194/hess-23-4171-2019, 2019
Short summary
Short summary
Land–atmosphere interactions are key for the exchange of water, energy, and carbon dioxide, especially in the tropics. We here review some of the recent findings on land–atmosphere interactions in the tropics and where we see potential challenges and paths forward.
Paul C. Stoy, Tarek S. El-Madany, Joshua B. Fisher, Pierre Gentine, Tobias Gerken, Stephen P. Good, Anne Klosterhalfen, Shuguang Liu, Diego G. Miralles, Oscar Perez-Priego, Angela J. Rigden, Todd H. Skaggs, Georg Wohlfahrt, Ray G. Anderson, A. Miriam J. Coenders-Gerrits, Martin Jung, Wouter H. Maes, Ivan Mammarella, Matthias Mauder, Mirco Migliavacca, Jacob A. Nelson, Rafael Poyatos, Markus Reichstein, Russell L. Scott, and Sebastian Wolf
Biogeosciences, 16, 3747–3775, https://doi.org/10.5194/bg-16-3747-2019, https://doi.org/10.5194/bg-16-3747-2019, 2019
Short summary
Short summary
Key findings are the nearly optimal response of T to atmospheric water vapor pressure deficits across methods and scales. Additionally, the notion that T / ET intermittently approaches 1, which is a basis for many partitioning methods, does not hold for certain methods and ecosystems. To better constrain estimates of E and T from combined ET measurements, we propose a combination of independent measurement techniques to better constrain E and T at the ecosystem scale.
Wen Li Zhao, Yu Jiu Xiong, Kyaw Tha Paw U, Pierre Gentine, Baoyu Chen, and Guo Yu Qiu
Hydrol. Earth Syst. Sci. Discuss., https://doi.org/10.5194/hess-2019-160, https://doi.org/10.5194/hess-2019-160, 2019
Manuscript not accepted for further review
Short summary
Short summary
Accurate evapotranspiration (ET) estimation requires an in-depth identification of uncertainty sources. Using high density eddy covariance observations, we evaluated the effects of resistances on ET estimation and discussed possible solutions. The results show that more complex resistance parameterizations leads to more uncertainty, although prior calibration can improve the ET estimates and that a new model without resistance parameterization introduces less uncertainty into the ET estimation.
Wouter H. Maes, Pierre Gentine, Niko E. C. Verhoest, and Diego G. Miralles
Hydrol. Earth Syst. Sci., 23, 925–948, https://doi.org/10.5194/hess-23-925-2019, https://doi.org/10.5194/hess-23-925-2019, 2019
Short summary
Short summary
Potential evaporation (Ep) is the amount of water an ecosystem would consume if it were not limited by water availability or other stress factors. In this study, we compared several methods to estimate Ep using a global dataset of 107 FLUXNET sites. A simple radiation-driven method calibrated per biome consistently outperformed more complex approaches and makes a suitable tool to investigate the impact of water use and demand, drought severity and biome productivity.
Adam Massmann, Pierre Gentine, and Changjie Lin
Hydrol. Earth Syst. Sci. Discuss., https://doi.org/10.5194/hess-2018-553, https://doi.org/10.5194/hess-2018-553, 2018
Revised manuscript not accepted
Short summary
Short summary
Plants can sense increasing dryness in the air and close up the pores
on their leaves, preventing water loss. However, drier air also
naturally demands more water from the land surface. Here we develop a
simplified theory for when land surface water loss increases
(atmospheric demand dominates) or decreases (plant response dominates)
in response to increased dryness in the air. This theory provides
intuition for how ecosystems regulate water in response to changes in
atmospheric dryness.
Tim van Emmerik, Susan Steele-Dunne, Pierre Gentine, Rafael S. Oliveira, Paulo Bittencourt, Fernanda Barros, and Nick van de Giesen
Biogeosciences, 15, 6439–6449, https://doi.org/10.5194/bg-15-6439-2018, https://doi.org/10.5194/bg-15-6439-2018, 2018
Short summary
Short summary
Trees are very important for the water and carbon cycles. Climate and weather models often assume constant vegetation parameters because good measurements are missing. We used affordable accelerometers to measure tree sway of 19 trees in the Amazon rainforest. We show that trees respond very differently to the same weather conditions, which means that vegetation parameters are dynamic. With our measurements trees can be accounted for more realistically, improving climate and weather models.
Seyed Hamed Alemohammad, Jana Kolassa, Catherine Prigent, Filipe Aires, and Pierre Gentine
Hydrol. Earth Syst. Sci., 22, 5341–5356, https://doi.org/10.5194/hess-22-5341-2018, https://doi.org/10.5194/hess-22-5341-2018, 2018
Short summary
Short summary
A new machine learning algorithm is developed to downscale satellite-based soil moisture estimates from their native spatial scale of 9 km to 2.25 km.
Yao Zhang, Joanna Joiner, Seyed Hamed Alemohammad, Sha Zhou, and Pierre Gentine
Biogeosciences, 15, 5779–5800, https://doi.org/10.5194/bg-15-5779-2018, https://doi.org/10.5194/bg-15-5779-2018, 2018
Short summary
Short summary
Using satellite reflectance measurements and a machine learning algorithm, we generated a new solar-induced chlorophyll fluorescence (SIF) dataset that is closely linked to plant photosynthesis. This new dataset has higher spatial and temporal resolutions, and lower uncertainty compared to the existing satellite retrievals. We also demonstrated its application in monitoring drought and improving the understanding of the SIF–photosynthesis relationship.
Wouter H. Maes, Pierre Gentine, Niko E. C. Verhoest, and Diego G. Miralles
Hydrol. Earth Syst. Sci. Discuss., https://doi.org/10.5194/hess-2017-682, https://doi.org/10.5194/hess-2017-682, 2018
Revised manuscript not accepted
Short summary
Short summary
Potential evaporation is a key parameter in numerous models used for assessing water use and drought severity. Yet, multiple incompatible methods have been proposed, thus estimates of potential evaporation remain uncertain. Based on the largest available dataset of FLUXNET data, we identify the best method to calculate potential evaporation globally. A simple radiation-driven method calibrated per biome consistently performed best; more complex models did not perform as good.
Seyed Hamed Alemohammad, Bin Fang, Alexandra G. Konings, Filipe Aires, Julia K. Green, Jana Kolassa, Diego Miralles, Catherine Prigent, and Pierre Gentine
Biogeosciences, 14, 4101–4124, https://doi.org/10.5194/bg-14-4101-2017, https://doi.org/10.5194/bg-14-4101-2017, 2017
Short summary
Short summary
Water, Energy, and Carbon with Artificial Neural Networks (WECANN) is a statistically based estimate of global surface latent and sensible heat fluxes and gross primary productivity. The retrieval uses six remotely sensed observations as input, including the solar-induced fluorescence. WECANN provides estimates on a 1° × 1° geographic grid and on a monthly time scale and outperforms other global products in capturing the seasonality of the fluxes when compared to eddy covariance tower data.
Carolin Klinger, Bernhard Mayer, Fabian Jakub, Tobias Zinner, Seung-Bu Park, and Pierre Gentine
Atmos. Chem. Phys., 17, 5477–5500, https://doi.org/10.5194/acp-17-5477-2017, https://doi.org/10.5194/acp-17-5477-2017, 2017
Short summary
Short summary
Radiation is driving weather and climate. Yet, the effect of radiation on clouds is not fully understood and often only poorly represented in models. Better understanding and better parameterizations of the radiation–cloud interaction are therefore essential. Using our newly developed fast
neighboring column approximationfor 3-D thermal heating and cooling rates, we show that thermal radiation changes cloud circulation and causes organization and a deepening of the clouds.
Nir Y. Krakauer, Michael J. Puma, Benjamin I. Cook, Pierre Gentine, and Larissa Nazarenko
Earth Syst. Dynam., 7, 863–876, https://doi.org/10.5194/esd-7-863-2016, https://doi.org/10.5194/esd-7-863-2016, 2016
Short summary
Short summary
We simulated effects of irrigation on climate with the NASA GISS global climate model. Present-day irrigation levels affected air pressures and temperatures even in non-irrigated land and ocean areas. The simulated effect was bigger and more widespread when ocean temperatures in the climate model could change, rather than being fixed. We suggest that expanding irrigation may affect global climate more than previously believed.
B. R. Lintner, P. Gentine, K. L. Findell, and G. D. Salvucci
Hydrol. Earth Syst. Sci., 19, 2119–2131, https://doi.org/10.5194/hess-19-2119-2015, https://doi.org/10.5194/hess-19-2119-2015, 2015
B. P. Guillod, B. Orlowsky, D. Miralles, A. J. Teuling, P. D. Blanken, N. Buchmann, P. Ciais, M. Ek, K. L. Findell, P. Gentine, B. R. Lintner, R. L. Scott, B. Van den Hurk, and S. I. Seneviratne
Atmos. Chem. Phys., 14, 8343–8367, https://doi.org/10.5194/acp-14-8343-2014, https://doi.org/10.5194/acp-14-8343-2014, 2014
Related subject area
Subject: Hydrometeorology | Techniques and Approaches: Modelling approaches
Enhanced evaluation of hourly and daily extreme precipitation in Norway from convection-permitting models at regional and local scales
Deep-learning-based sub-seasonal precipitation and streamflow ensemble forecasting over the source region of the Yangtze River
High-resolution land surface modelling over Africa: the role of uncertain soil properties in combination with forcing temporal resolution
Investigating the global and regional response of drought to idealized deforestation using multiple global climate models
Distribution, trends, and drivers of flash droughts in the United Kingdom
Are dependencies of extreme rainfall on humidity more reliable in convection-permitting climate models?
Leveraging a radar-based disdrometer network to develop a probabilistic precipitation phase model in eastern Canada
Assessment of seasonal soil moisture forecasts over the Central Mediterranean
Do land models miss key soil hydrological processes controlling soil moisture memory?
Observation-driven model for calculating water-harvesting potential from advective fog in (semi-)arid coastal regions
Review of gridded climate products and their use in hydrological analyses reveals overlaps, gaps, and the need for a more objective approach to selecting model forcing datasets
Downscaling the probability of heavy rainfall over the Nordic countries
Modelling convective cell life cycles with a copula-based approach
Downscaling precipitation over High-mountain Asia using multi-fidelity Gaussian processes: improved estimates from ERA5
Mapping soil moisture across the UK: assimilating cosmic-ray neutron sensors, remotely sensed indices, rainfall radar and catchment water balance data in a Bayesian hierarchical model
Assessing rainfall radar errors with an inverse stochastic modelling framework
Towards a Robust Hydrologic Data Assimilation System for Hurricane-induced River Flow Forecasting
Enhanced hydrological modelling with the WRF-Hydro lake/reservoir module at Convection-Permitting scale: a case study of the Tana River basin in East Africa
Multi-objective calibration and evaluation of the ORCHIDEE land surface model over France at high resolution
Probabilistic precipitation downscaling for ungauged mountain sites: a pilot study for the Hindu Kush Karakoram Himalaya
Spatiotemporal responses of runoff to climate change in the southern Tibetan Plateau
Skilful probabilistic predictions of UK floods months ahead using machine learning models trained on multimodel ensemble climate forecasts
FROSTBYTE: a reproducible data-driven workflow for probabilistic seasonal streamflow forecasting in snow-fed river basins across North America
The role of land-atmosphere coupling in subseasonal surface air temperature prediction
On the combined use of rain gauges and GPM IMERG satellite rainfall products for hydrological modelling: impact assessment of the cellular-automata-based methodology in the Tanaro River basin in Italy
An increase in the spatial extent of European floods over the last 70 years
140-year daily ensemble streamflow reconstructions over 661 catchments in France
The agricultural expansion in South America's Dry Chaco: regional hydroclimate effects
Machine-learning-constrained projection of bivariate hydrological drought magnitudes and socioeconomic risks over China
Improving runoff simulation in the Western United States with Noah-MP and VIC models
Spatial variability in the seasonal precipitation lapse rates in complex topographical regions – application in France
Global catalog of soil moisture droughts over the past four decades
Assessing downscaling methods to simulate hydrologically relevant weather scenarios from a global atmospheric reanalysis: case study of the upper Rhône River (1902–2009)
Global total precipitable water variations and trends over the period 1958–2021
Assessing decadal- to centennial-scale nonstationary variability in meteorological drought trends
Identification of compound drought and heatwave events on a daily scale and across four seasons
Implementation of global soil databases in NOAH-MP model and the effects on simulated mean and extreme soil hydrothermal changes
Potential for historically unprecedented Australian droughts from natural variability and climate change
Flood risk assessment for Indian sub-continental river basins
Key ingredients in regional climate modelling for improving the representation of typhoon tracks and intensities
Divergent future drought projections in UK river flows and groundwater levels
Predicting extreme sub-hourly precipitation intensification based on temperature shifts
Hydroclimatic processes as the primary drivers of the Early Khvalynian transgression of the Caspian Sea: new developments
Accounting for hydroclimatic properties in flood frequency analysis procedures
Understanding the influence of “hot” models in climate impact studies: a hydrological perspective
A semi-parametric hourly space–time weather generator
A principal-component-based strategy for regionalisation of precipitation intensity–duration–frequency (IDF) statistics
Accounting for precipitation asymmetry in a multiplicative random cascade disaggregation model
Seasonal soil moisture and crop yield prediction with fifth-generation seasonal forecasting system (SEAS5) long-range meteorological forecasts in a land surface modelling approach
A genetic particle filter scheme for univariate snow cover assimilation into Noah-MP model across snow climates
Kun Xie, Lu Li, Hua Chen, Stephanie Mayer, Andreas Dobler, Chong-Yu Xu, and Ozan Mert Göktürk
Hydrol. Earth Syst. Sci., 29, 2133–2152, https://doi.org/10.5194/hess-29-2133-2025, https://doi.org/10.5194/hess-29-2133-2025, 2025
Short summary
Short summary
We compared hourly and daily extreme precipitation across Norway from HARMONIE Climate models at convection-permitting 3 km (HCLIM3) and 12 km (HCLIM12) resolutions. HCLIM3 more accurately captures the extremes in most regions and seasons (except in summer). Its advantages are more pronounced for hourly extremes than for daily extremes. The results highlight the value of convection-permitting models in improving extreme-precipitation predictions and in helping the local society brace for extreme weather.
Ningpeng Dong, Haoran Hao, Mingxiang Yang, Jianhui Wei, Shiqin Xu, and Harald Kunstmann
Hydrol. Earth Syst. Sci., 29, 2023–2042, https://doi.org/10.5194/hess-29-2023-2025, https://doi.org/10.5194/hess-29-2023-2025, 2025
Short summary
Short summary
Hydrometeorological forecasting is crucial for managing water resources and mitigating extreme weather events, yet current long-term forecast products are often embedded with uncertainties. We develop a deep-learning-based modelling framework to improve 30 d rainfall and streamflow forecasts by combining advanced neural networks and physical models. With the flow forecast error reduced by up to 33 %, the framework has the potential to enhance water management and disaster prevention.
Bamidele Oloruntoba, Stefan Kollet, Carsten Montzka, Harry Vereecken, and Harrie-Jan Hendricks Franssen
Hydrol. Earth Syst. Sci., 29, 1659–1683, https://doi.org/10.5194/hess-29-1659-2025, https://doi.org/10.5194/hess-29-1659-2025, 2025
Short summary
Short summary
We studied how soil and weather data affect land model simulations over Africa. By combining soil data processed in different ways with weather data of varying time intervals, we found that weather inputs had a greater impact on water processes than soil data type. However, the way soil data were processed became crucial when paired with high-frequency weather inputs, showing that detailed weather data can improve local and regional predictions of how water moves and interacts with the land.
Yan Li, Bo Huang, Chunping Tan, Xia Zhang, Francesco Cherubini, and Henning W. Rust
Hydrol. Earth Syst. Sci., 29, 1637–1658, https://doi.org/10.5194/hess-29-1637-2025, https://doi.org/10.5194/hess-29-1637-2025, 2025
Short summary
Short summary
Deforestation has a significant impact on climate, yet its effects on drought remain less understood. This study investigates how deforestation affects drought across various climate zones and timescales. Findings indicate that deforestation leads to drier conditions in tropical regions and wetter conditions in arid areas, with minimal effects in temperate zones. Long-term drought is more affected than short-term drought, offering valuable insights into vegetation–climate interactions.
Iván Noguera, Jamie Hannaford, and Maliko Tanguy
Hydrol. Earth Syst. Sci., 29, 1295–1317, https://doi.org/10.5194/hess-29-1295-2025, https://doi.org/10.5194/hess-29-1295-2025, 2025
Short summary
Short summary
The study provides a detailed characterisation of flash drought in the UK for 1969–2021. The spatio-temporal distribution and trends of flash droughts are highly variable, with important regional and seasonal contrasts. In the UK, flash drought development responds primarily to precipitation variability, while the atmospheric evaporative demand plays a secondary role. We also found that the North Atlantic Oscillation is the main circulation pattern controlling flash drought development.
Geert Lenderink, Nikolina Ban, Erwan Brisson, Ségolène Berthou, Virginia Edith Cortés-Hernández, Elizabeth Kendon, Hayley J. Fowler, and Hylke de Vries
Hydrol. Earth Syst. Sci., 29, 1201–1220, https://doi.org/10.5194/hess-29-1201-2025, https://doi.org/10.5194/hess-29-1201-2025, 2025
Short summary
Short summary
Future extreme rainfall events are influenced by changes in both absolute and relative humidity. The impact of increasing absolute humidity is reasonably well understood, but the role of relative humidity decreases over land remains largely unknown. Using hourly observations from France and the Netherlands, we find that lower relative humidity generally leads to more intense rainfall extremes. This relation is only captured well in recently developed convection-permitting climate models.
Alexis Bédard-Therrien, François Anctil, Julie M. Thériault, Olivier Chalifour, Fanny Payette, Alexandre Vidal, and Daniel F. Nadeau
Hydrol. Earth Syst. Sci., 29, 1135–1158, https://doi.org/10.5194/hess-29-1135-2025, https://doi.org/10.5194/hess-29-1135-2025, 2025
Short summary
Short summary
Precipitation data from an automated observational network in eastern Canada showed a temperature interval where rain and snow could coexist. Random forest models were developed to classify the precipitation phase using meteorological data to evaluate operational applications. The models demonstrated significantly improved phase classification and reduced error compared to benchmark operational models. However, accurate prediction of mixed-phase precipitation remains challenging.
Lorenzo Silvestri, Miriam Saraceni, Bruno Brunone, Silvia Meniconi, Giulia Passadore, and Paolina Bongioannini Cerlini
Hydrol. Earth Syst. Sci., 29, 925–946, https://doi.org/10.5194/hess-29-925-2025, https://doi.org/10.5194/hess-29-925-2025, 2025
Short summary
Short summary
This work demonstrates that seasonal forecasts of soil moisture are a valuable resource for groundwater management in the areas of the Central Mediterranean where longer memory timescales are found. In particular, they show significant correlation coefficients and forecast skill for the deepest soil moisture at 289 cm depth. Wet and dry events can be predicted 6 months in advance, and, in general, dry events are better captured than wet events.
Mohammad A. Farmani, Ali Behrangi, Aniket Gupta, Ahmad Tavakoly, Matthew Geheran, and Guo-Yue Niu
Hydrol. Earth Syst. Sci., 29, 547–566, https://doi.org/10.5194/hess-29-547-2025, https://doi.org/10.5194/hess-29-547-2025, 2025
Short summary
Short summary
Soil moisture memory (SMM) shows how long soil stays moist after rain, impacting climate and ecosystems. Current models often overestimate SMM, causing inaccuracies in evaporation predictions. We enhanced a land model, Noah-MP, to include better water flow and ponding processes, and we tested it against satellite and field data. This improved model reduced overestimations and enhanced short-term predictions, helping create more accurate climate and weather forecasts.
Felipe Lobos-Roco, Jordi Vilà-Guerau de Arellano, and Camilo del Río
Hydrol. Earth Syst. Sci., 29, 109–125, https://doi.org/10.5194/hess-29-109-2025, https://doi.org/10.5194/hess-29-109-2025, 2025
Short summary
Short summary
Water resources are fundamental for the social, economic, and natural development of (semi-)arid regions. Precipitation decreases due to climate change obligate us to find new water resources. Fog harvesting (FH) emerges as a complementary resource in regions where it is abundant but untapped. This research proposes a model to estimate FH potential in coastal (semi-)arid regions. This model could have broader applicability worldwide in regions where FH could be a viable water source.
Kyle R. Mankin, Sushant Mehan, Timothy R. Green, and David M. Barnard
Hydrol. Earth Syst. Sci., 29, 85–108, https://doi.org/10.5194/hess-29-85-2025, https://doi.org/10.5194/hess-29-85-2025, 2025
Short summary
Short summary
We assess 63 gridded ground (G), satellite (S), and reanalysis (R) climate datasets. Higher-density station data and less-hilly terrain improved climate data. In mountainous and humid regions, dataset types performed similarly; however, R outperformed G when underlying data had low station density. G outperformed S or R datasets, although better streamflow modeling did not always follow. Hydrologic analyses need datasets that better represent climate variable dependencies and complex topography.
Rasmus E. Benestad, Kajsa M. Parding, and Andreas Dobler
Hydrol. Earth Syst. Sci., 29, 45–65, https://doi.org/10.5194/hess-29-45-2025, https://doi.org/10.5194/hess-29-45-2025, 2025
Short summary
Short summary
We present a new method to calculate the chance of heavy downpour and the maximum rainfall expected over a 25-year period. It is designed to analyse global climate models' reproduction of past and future climates. For the Nordic countries, it projects a wetter climate in the future with increased intensity but not necessarily more wet days. The analysis also shows that rainfall intensity is sensitive to future greenhouse gas emissions, while the number of wet days appears to be less affected.
Chien-Yu Tseng, Li-Pen Wang, and Christian Onof
Hydrol. Earth Syst. Sci., 29, 1–25, https://doi.org/10.5194/hess-29-1-2025, https://doi.org/10.5194/hess-29-1-2025, 2025
Short summary
Short summary
This study presents a new algorithm to model convective storms. We used advanced tracking methods to analyse 165 storm events in Birmingham (UK) and reconstruct storm cell life cycles. We found that cell properties like intensity and size are interrelated and vary over time. The new algorithm, based on vine copulas, accurately simulates these properties and their evolution. It also integrates an exponential shape function for realistic rainfall patterns, enhancing its hydrological applicability.
Kenza Tazi, Andrew Orr, Javier Hernandez-González, Scott Hosking, and Richard E. Turner
Hydrol. Earth Syst. Sci., 28, 4903–4925, https://doi.org/10.5194/hess-28-4903-2024, https://doi.org/10.5194/hess-28-4903-2024, 2024
Short summary
Short summary
This work aims to improve the understanding of precipitation patterns in High-mountain Asia, a crucial water source for around 1.9 billion people. Through a novel machine learning method, we generate high-resolution precipitation predictions, including the likelihoods of floods and droughts. Compared to state-of-the-art methods, our method is simpler to implement and more suitable for small datasets. The method also shows accuracy comparable to or better than existing benchmark datasets.
Peter E. Levy and the COSMOS-UK team
Hydrol. Earth Syst. Sci., 28, 4819–4836, https://doi.org/10.5194/hess-28-4819-2024, https://doi.org/10.5194/hess-28-4819-2024, 2024
Short summary
Short summary
Having accurate up-to-date maps of soil moisture is important for many purposes. However, current modelled and remotely sensed maps are rather coarse and not very accurate. Here, we demonstrate a simple but accurate approach that is closely linked to direct measurements of soil moisture at a network sites across the UK, to the water balance (precipitation minus drainage and evaporation) measured at a large number of catchments (1212) and to remotely sensed satellite estimates.
Amy C. Green, Chris Kilsby, and András Bárdossy
Hydrol. Earth Syst. Sci., 28, 4539–4558, https://doi.org/10.5194/hess-28-4539-2024, https://doi.org/10.5194/hess-28-4539-2024, 2024
Short summary
Short summary
Weather radar is a crucial tool in rainfall estimation, but radar rainfall estimates are subject to many error sources, with the true rainfall field unknown. A flexible model for simulating errors relating to the radar rainfall estimation process is implemented, inverting standard processing methods. This flexible and efficient model performs well in generating realistic weather radar images visually for a large range of event types.
Peyman Abbaszadeh, Keyhan Gavahi, and Hamid Moradkhani
Hydrol. Earth Syst. Sci. Discuss., https://doi.org/10.5194/hess-2024-209, https://doi.org/10.5194/hess-2024-209, 2024
Revised manuscript accepted for HESS
Short summary
Short summary
The Hybrid Ensemble and Variational Data Assimilation framework for Environmental System (HEAVEN) enhances flood predictions by refining hydrologic models through improved data integration and uncertainty management. Tested in three Southeastern U.S. watersheds during hurricanes, HEAVEN assimilates real-time USGS streamflow data, boosting forecast accuracy.
Ling Zhang, Lu Li, Zhongshi Zhang, Joël Arnault, Stefan Sobolowski, Anthony Musili Mwanthi, Pratik Kad, Mohammed Abdullahi Hassan, Tanja Portele, and Harald Kunstmann
Hydrol. Earth Syst. Sci. Discuss., https://doi.org/10.5194/hess-2024-278, https://doi.org/10.5194/hess-2024-278, 2024
Revised manuscript accepted for HESS
Short summary
Short summary
To address challenges related to unreliable hydrological simulations, we present an enhanced hydrological simulation with a refined climate model and a more comprehensive hydrological model. The model with the two parts outperforms that without, especially in migrating bias in peak flow and dry-season flow. Our findings highlight the enhanced hydrological simulation capability with the refined climate and lake module contributing 24 % and 76 % improvement, respectively.
Peng Huang, Agnès Ducharne, Lucia Rinchiuso, Jan Polcher, Laure Baratgin, Vladislav Bastrikov, and Eric Sauquet
Hydrol. Earth Syst. Sci., 28, 4455–4476, https://doi.org/10.5194/hess-28-4455-2024, https://doi.org/10.5194/hess-28-4455-2024, 2024
Short summary
Short summary
We conducted a high-resolution hydrological simulation from 1959 to 2020 across France. We used a simple trial-and-error calibration to reduce the biases of the simulated water budget compared to observations. The selected simulation satisfactorily reproduces water fluxes, including their spatial contrasts and temporal trends. This work offers a reliable historical overview of water resources and a robust configuration for climate change impact analysis at the nationwide scale of France.
Marc Girona-Mata, Andrew Orr, Martin Widmann, Daniel Bannister, Ghulam Hussain Dars, Scott Hosking, Jesse Norris, David Ocio, Tony Phillips, Jakob Steiner, and Richard E. Turner
EGUsphere, https://doi.org/10.5194/egusphere-2024-2805, https://doi.org/10.5194/egusphere-2024-2805, 2024
Short summary
Short summary
We introduce a novel method for improving daily precipitation maps in mountain regions and pilot it across three basins in the Hindu Kush Karakoram Himalaya (HKH). The approach leverages climate model and weather station data, along with statistical / machine learning techniques. Our results show this approach outperforms traditional methods, especially in remote, ungauged areas, suggesting it could be used to improve precipitation maps across much of the HKH, as well as other mountain regions.
He Sun, Tandong Yao, Fengge Su, Wei Yang, and Deliang Chen
Hydrol. Earth Syst. Sci., 28, 4361–4381, https://doi.org/10.5194/hess-28-4361-2024, https://doi.org/10.5194/hess-28-4361-2024, 2024
Short summary
Short summary
Our findings show that runoff in the Yarlung Zangbo (YZ) basin is primarily driven by rainfall, with the largest glacier runoff contribution in the downstream sub-basin. Annual runoff increased in the upper stream but decreased downstream due to varying precipitation patterns. It is expected to rise throughout the 21st century, mainly driven by increased rainfall.
Simon Moulds, Louise Slater, Louise Arnal, and Andrew Wood
EGUsphere, https://doi.org/10.31223/X5X405, https://doi.org/10.31223/X5X405, 2024
Short summary
Short summary
Seasonal streamflow forecasts are an important component of flood risk management. Here, we train and test a machine learning model to predict the monthly maximum daily streamflow up to four months ahead. We train the model on precipitation and temperature forecasts to produce probabilistic hindcasts for 579 stations across the UK for the period 2004–2016. We show skilful results up to four months ahead in many locations, although in general the skill declines with increasing lead time.
Louise Arnal, Martyn P. Clark, Alain Pietroniro, Vincent Vionnet, David R. Casson, Paul H. Whitfield, Vincent Fortin, Andrew W. Wood, Wouter J. M. Knoben, Brandi W. Newton, and Colleen Walford
Hydrol. Earth Syst. Sci., 28, 4127–4155, https://doi.org/10.5194/hess-28-4127-2024, https://doi.org/10.5194/hess-28-4127-2024, 2024
Short summary
Short summary
Forecasting river flow months in advance is crucial for water sectors and society. In North America, snowmelt is a key driver of flow. This study presents a statistical workflow using snow data to forecast flow months ahead in North American snow-fed rivers. Variations in the river flow predictability across the continent are evident, raising concerns about future predictability in a changing (snow) climate. The reproducible workflow hosted on GitHub supports collaborative and open science.
Yuna Lim, Andrea M. Molod, Randal D. Koster, and Joseph A. Santanello
EGUsphere, https://doi.org/10.5194/egusphere-2024-2312, https://doi.org/10.5194/egusphere-2024-2312, 2024
Short summary
Short summary
To better utilize a given set of predictions, identifying “forecasts of opportunity” has great value. It can help anticipate when prediction skill will be higher. This study reveals that when strong L-A coupling is detected 3–4 weeks into a forecast, the prediction skill for surface air temperature at this lead increases across the Midwest and northern Great Plains. Regions experiencing strong L-A coupling exhibit warm and dry anomalies, leading to improved predictions of abnormally warm events.
Annalina Lombardi, Barbara Tomassetti, Valentina Colaiuda, Ludovico Di Antonio, Paolo Tuccella, Mario Montopoli, Giovanni Ravazzani, Frank Silvio Marzano, Raffaele Lidori, and Giulia Panegrossi
Hydrol. Earth Syst. Sci., 28, 3777–3797, https://doi.org/10.5194/hess-28-3777-2024, https://doi.org/10.5194/hess-28-3777-2024, 2024
Short summary
Short summary
The accurate estimation of precipitation and its spatial variability within a watershed is crucial for reliable discharge simulations. The study is the first detailed analysis of the potential usage of the cellular automata technique to merge different rainfall data inputs to hydrological models. This work shows an improvement in the performance of hydrological simulations when satellite and rain gauge data are merged.
Beijing Fang, Emanuele Bevacqua, Oldrich Rakovec, and Jakob Zscheischler
Hydrol. Earth Syst. Sci., 28, 3755–3775, https://doi.org/10.5194/hess-28-3755-2024, https://doi.org/10.5194/hess-28-3755-2024, 2024
Short summary
Short summary
We use grid-based runoff from a hydrological model to identify large spatiotemporally connected flood events in Europe, assess extent trends over the last 70 years, and attribute the trends to different drivers. Our findings reveal a general increase in flood extent, with regional variations driven by diverse factors. The study not only enables a thorough examination of flood events across multiple basins but also highlights the potential challenges arising from changing flood extents.
Alexandre Devers, Jean-Philippe Vidal, Claire Lauvernet, Olivier Vannier, and Laurie Caillouet
Hydrol. Earth Syst. Sci., 28, 3457–3474, https://doi.org/10.5194/hess-28-3457-2024, https://doi.org/10.5194/hess-28-3457-2024, 2024
Short summary
Short summary
Daily streamflow series for 661 near-natural French catchments are reconstructed over 1871–2012 using two ensemble datasets: HydRE and HydREM. They include uncertainties coming from climate forcings, streamflow measurement, and hydrological model error (for HydrREM). Comparisons with other hydrological reconstructions and independent/dependent observations show the added value of the two reconstructions in terms of quality, uncertainty estimation, and representation of extremes.
María Agostina Bracalenti, Omar V. Müller, Miguel A. Lovino, and Ernesto Hugo Berbery
Hydrol. Earth Syst. Sci., 28, 3281–3303, https://doi.org/10.5194/hess-28-3281-2024, https://doi.org/10.5194/hess-28-3281-2024, 2024
Short summary
Short summary
The Gran Chaco is a large, dry forest in South America that has been heavily deforested, particularly in the dry Chaco subregion. This deforestation, mainly driven by the expansion of the agricultural frontier, has changed the land's characteristics, affecting the local and regional climate. The study reveals that deforestation has resulted in reduced precipitation, soil moisture, and runoff, and if intensive agriculture continues, it could make summers in this arid region even drier and hotter.
Rutong Liu, Jiabo Yin, Louise Slater, Shengyu Kang, Yuanhang Yang, Pan Liu, Jiali Guo, Xihui Gu, Xiang Zhang, and Aliaksandr Volchak
Hydrol. Earth Syst. Sci., 28, 3305–3326, https://doi.org/10.5194/hess-28-3305-2024, https://doi.org/10.5194/hess-28-3305-2024, 2024
Short summary
Short summary
Climate change accelerates the water cycle and alters the spatiotemporal distribution of hydrological variables, thus complicating the projection of future streamflow and hydrological droughts. We develop a cascade modeling chain to project future bivariate hydrological drought characteristics over China, using five bias-corrected global climate model outputs under three shared socioeconomic pathways, five hydrological models, and a deep-learning model.
Lu Su, Dennis P. Lettenmaier, Ming Pan, and Benjamin Bass
Hydrol. Earth Syst. Sci., 28, 3079–3097, https://doi.org/10.5194/hess-28-3079-2024, https://doi.org/10.5194/hess-28-3079-2024, 2024
Short summary
Short summary
We fine-tuned the variable infiltration capacity (VIC) and Noah-MP models across 263 river basins in the Western US. We developed transfer relationships to similar basins and extended the fine-tuned parameters to ungauged basins. Both models performed best in humid areas, and the skills improved post-calibration. VIC outperforms Noah-MP in all but interior dry basins following regionalization. VIC simulates annual mean streamflow and high flow well, while Noah-MP performs better for low flows.
Valentin Dura, Guillaume Evin, Anne-Catherine Favre, and David Penot
Hydrol. Earth Syst. Sci., 28, 2579–2601, https://doi.org/10.5194/hess-28-2579-2024, https://doi.org/10.5194/hess-28-2579-2024, 2024
Short summary
Short summary
The increase in precipitation as a function of elevation is poorly understood in areas with complex topography. In this article, the reproduction of these orographic gradients is assessed with several precipitation products. The best product is a simulation from a convection-permitting regional climate model. The corresponding seasonal gradients vary significantly in space, with higher values for the first topographical barriers exposed to the dominant air mass circulations.
Jan Řehoř, Rudolf Brázdil, Oldřich Rakovec, Martin Hanel, Milan Fischer, Rohini Kumar, Jan Balek, Markéta Poděbradská, Vojtěch Moravec, Luis Samaniego, and Miroslav Trnka
EGUsphere, https://doi.org/10.5194/egusphere-2024-1434, https://doi.org/10.5194/egusphere-2024-1434, 2024
Short summary
Short summary
We present a robust method for identification and classification of global land drought events (GLDEs) based on soil moisture. Two models were used to calculate soil moisture and delimit soil drought over global land from 1980–2022, which was clustered into 775/630 GLDEs. Using four spatiotemporal and three motion-related characteristics, we categorized GLDEs into seven severity and seven dynamic categories. The frequency of GLDEs has generally increased in recent decades.
Caroline Legrand, Benoît Hingray, Bruno Wilhelm, and Martin Ménégoz
Hydrol. Earth Syst. Sci., 28, 2139–2166, https://doi.org/10.5194/hess-28-2139-2024, https://doi.org/10.5194/hess-28-2139-2024, 2024
Short summary
Short summary
Climate change is expected to increase flood hazard worldwide. The evolution is typically estimated from multi-model chains, where regional hydrological scenarios are simulated from weather scenarios derived from coarse-resolution atmospheric outputs of climate models. We show that two such chains are able to reproduce, from an atmospheric reanalysis, the 1902–2009 discharge variations and floods of the upper Rhône alpine river, provided that the weather scenarios are bias-corrected.
Nenghan Wan, Xiaomao Lin, Roger A. Pielke Sr., Xubin Zeng, and Amanda M. Nelson
Hydrol. Earth Syst. Sci., 28, 2123–2137, https://doi.org/10.5194/hess-28-2123-2024, https://doi.org/10.5194/hess-28-2123-2024, 2024
Short summary
Short summary
Global warming occurs at a rate of 0.21 K per decade, resulting in about 9.5 % K−1 of water vapor response to temperature from 1993 to 2021. Terrestrial areas experienced greater warming than the ocean, with a ratio of 2 : 1. The total precipitable water change in response to surface temperature changes showed a variation around 6 % K−1–8 % K−1 in the 15–55° N latitude band. Further studies are needed to identify the mechanisms leading to different water vapor responses.
Kyungmin Sung, Max C. A. Torbenson, and James H. Stagge
Hydrol. Earth Syst. Sci., 28, 2047–2063, https://doi.org/10.5194/hess-28-2047-2024, https://doi.org/10.5194/hess-28-2047-2024, 2024
Short summary
Short summary
This study examines centuries of nonstationary trends in meteorological drought and pluvial climatology. A novel approach merges tree-ring proxy data (North American Seasonal Precipitation Atlas – NASPA) with instrumental precipitation datasets by temporally downscaling proxy data, correcting biases, and analyzing shared trends in normal and extreme precipitation anomalies. We identify regions experiencing recent unprecedented shifts towards drier or wetter conditions and shifts in seasonality.
Baoying Shan, Niko E. C. Verhoest, and Bernard De Baets
Hydrol. Earth Syst. Sci., 28, 2065–2080, https://doi.org/10.5194/hess-28-2065-2024, https://doi.org/10.5194/hess-28-2065-2024, 2024
Short summary
Short summary
This study developed a convenient and new method to identify the occurrence of droughts, heatwaves, and co-occurring droughts and heatwaves (CDHW) across four seasons. Using this method, we could establish the start and/or end dates of drought (or heatwave) events. We found an increase in the frequency of heatwaves and CDHW events in Belgium caused by climate change. We also found that different months have different chances of CDHW events.
Kazeem Ishola, Gerald Mills, Ankur Sati, Benjamin Obe, Matthias Demuzere, Deepak Upreti, Gourav Misra, Paul Lewis, Daire Walsh, Tim McCarthy, and Rowan Fealy
Hydrol. Earth Syst. Sci. Discuss., https://doi.org/10.5194/hess-2023-304, https://doi.org/10.5194/hess-2023-304, 2024
Revised manuscript accepted for HESS
Short summary
Short summary
The global soil information contributes to uncertainty in many models that monitor soil hydrothermal changes. Using the NOAH-MP model with two different global soil information, we show under-represented soil properties in wet loam soil, leading to dry bias in soil moisture. The dry bias is higher and drought categories are more severe in SOILGRIDS. We conclude that models should consider using detailed regionally-derived soil information, to reduce model uncertainties.
Georgina M. Falster, Nicky M. Wright, Nerilie J. Abram, Anna M. Ukkola, and Benjamin J. Henley
Hydrol. Earth Syst. Sci., 28, 1383–1401, https://doi.org/10.5194/hess-28-1383-2024, https://doi.org/10.5194/hess-28-1383-2024, 2024
Short summary
Short summary
Multi-year droughts have severe environmental and economic impacts, but the instrumental record is too short to characterise multi-year drought variability. We assessed the nature of Australian multi-year droughts using simulations of the past millennium from 11 climate models. We show that multi-decadal
megadroughtsare a natural feature of the Australian hydroclimate. Human-caused climate change is also driving a tendency towards longer droughts in eastern and southwestern Australia.
Urmin Vegad, Yadu Pokhrel, and Vimal Mishra
Hydrol. Earth Syst. Sci., 28, 1107–1126, https://doi.org/10.5194/hess-28-1107-2024, https://doi.org/10.5194/hess-28-1107-2024, 2024
Short summary
Short summary
A large population is affected by floods, which leave their footprints through human mortality, migration, and damage to agriculture and infrastructure, during almost every summer monsoon season in India. Despite the massive damage of floods, sub-basin level flood risk assessment is still in its infancy and needs to be improved. Using hydrological and hydrodynamic models, we reconstructed sub-basin level observed floods for the 1901–2020 period.
Qi Sun, Patrick Olschewski, Jianhui Wei, Zhan Tian, Laixiang Sun, Harald Kunstmann, and Patrick Laux
Hydrol. Earth Syst. Sci., 28, 761–780, https://doi.org/10.5194/hess-28-761-2024, https://doi.org/10.5194/hess-28-761-2024, 2024
Short summary
Short summary
Tropical cyclones (TCs) often cause high economic loss due to heavy winds and rainfall, particularly in densely populated regions such as the Pearl River Delta (China). This study provides a reference to set up regional climate models for TC simulations. They contribute to a better TC process understanding and assess the potential changes and risks of TCs in the future. This lays the foundation for hydrodynamical modelling, from which the cities' disaster management and defence could benefit.
Simon Parry, Jonathan D. Mackay, Thomas Chitson, Jamie Hannaford, Eugene Magee, Maliko Tanguy, Victoria A. Bell, Katie Facer-Childs, Alison Kay, Rosanna Lane, Robert J. Moore, Stephen Turner, and John Wallbank
Hydrol. Earth Syst. Sci., 28, 417–440, https://doi.org/10.5194/hess-28-417-2024, https://doi.org/10.5194/hess-28-417-2024, 2024
Short summary
Short summary
We studied drought in a dataset of possible future river flows and groundwater levels in the UK and found different outcomes for these two sources of water. Throughout the UK, river flows are likely to be lower in future, with droughts more prolonged and severe. However, whilst these changes are also found in some boreholes, in others, higher levels and less severe drought are indicated for the future. This has implications for the future balance between surface water and groundwater below.
Francesco Marra, Marika Koukoula, Antonio Canale, and Nadav Peleg
Hydrol. Earth Syst. Sci., 28, 375–389, https://doi.org/10.5194/hess-28-375-2024, https://doi.org/10.5194/hess-28-375-2024, 2024
Short summary
Short summary
We present a new physical-based method for estimating extreme sub-hourly precipitation return levels (i.e., intensity–duration–frequency, IDF, curves), which are critical for the estimation of future floods. The proposed model, named TENAX, incorporates temperature as a covariate in a physically consistent manner. It has only a few parameters and can be easily set for any climate station given sub-hourly precipitation and temperature data are available.
Alexander Gelfan, Andrey Panin, Andrey Kalugin, Polina Morozova, Vladimir Semenov, Alexey Sidorchuk, Vadim Ukraintsev, and Konstantin Ushakov
Hydrol. Earth Syst. Sci., 28, 241–259, https://doi.org/10.5194/hess-28-241-2024, https://doi.org/10.5194/hess-28-241-2024, 2024
Short summary
Short summary
Paleogeographical data show that 17–13 ka BP, the Caspian Sea level was 80 m above the current level. There are large disagreements on the genesis of this “Great” Khvalynian transgression of the sea, and we tried to shed light on this issue. Using climate and hydrological models as well as the paleo-reconstructions, we proved that the transgression could be initiated solely by hydroclimatic factors within the deglaciation period in the absence of the glacial meltwater effect.
Joeri B. Reinders and Samuel E. Munoz
Hydrol. Earth Syst. Sci., 28, 217–227, https://doi.org/10.5194/hess-28-217-2024, https://doi.org/10.5194/hess-28-217-2024, 2024
Short summary
Short summary
Flooding presents a major hazard for people and infrastructure along waterways; however, it is challenging to study the likelihood of a flood magnitude occurring regionally due to a lack of long discharge records. We show that hydroclimatic variables like Köppen climate regions and precipitation intensity explain part of the variance in flood frequency distributions and thus reduce the uncertainty of flood probability estimates. This gives water managers a tool to locally improve flood analysis.
Mehrad Rahimpour Asenjan, Francois Brissette, Jean-Luc Martel, and Richard Arsenault
Hydrol. Earth Syst. Sci., 27, 4355–4367, https://doi.org/10.5194/hess-27-4355-2023, https://doi.org/10.5194/hess-27-4355-2023, 2023
Short summary
Short summary
Climate models are central to climate change impact studies. Some models project a future deemed too hot by many. We looked at how including hot models may skew the result of impact studies. Applied to hydrology, this study shows that hot models do not systematically produce hydrological outliers.
Ross Pidoto and Uwe Haberlandt
Hydrol. Earth Syst. Sci., 27, 3957–3975, https://doi.org/10.5194/hess-27-3957-2023, https://doi.org/10.5194/hess-27-3957-2023, 2023
Short summary
Short summary
Long continuous time series of meteorological variables (i.e. rainfall, temperature) are required for the modelling of floods. Observed time series are generally too short or not available. Weather generators are models that reproduce observed weather time series. This study extends an existing station-based rainfall model into space by enforcing observed spatial rainfall characteristics. To model other variables (i.e. temperature) the model is then coupled to a simple resampling approach.
Kajsa Maria Parding, Rasmus Emil Benestad, Anita Verpe Dyrrdal, and Julia Lutz
Hydrol. Earth Syst. Sci., 27, 3719–3732, https://doi.org/10.5194/hess-27-3719-2023, https://doi.org/10.5194/hess-27-3719-2023, 2023
Short summary
Short summary
Intensity–duration–frequency (IDF) curves describe the likelihood of extreme rainfall and are used in hydrology and engineering, for example, for flood forecasting and water management. We develop a model to estimate IDF curves from daily meteorological observations, which are more widely available than the observations on finer timescales (minutes to hours) that are needed for IDF calculations. The method is applied to all data at once, making it efficient and robust to individual errors.
Kaltrina Maloku, Benoit Hingray, and Guillaume Evin
Hydrol. Earth Syst. Sci., 27, 3643–3661, https://doi.org/10.5194/hess-27-3643-2023, https://doi.org/10.5194/hess-27-3643-2023, 2023
Short summary
Short summary
High-resolution precipitation data, needed for many applications in hydrology, are typically rare. Such data can be simulated from daily precipitation with stochastic disaggregation. In this work, multiplicative random cascades are used to disaggregate time series of 40 min precipitation from daily precipitation for 81 Swiss stations. We show that very relevant statistics of precipitation are obtained when precipitation asymmetry is accounted for in a continuous way in the cascade generator.
Theresa Boas, Heye Reemt Bogena, Dongryeol Ryu, Harry Vereecken, Andrew Western, and Harrie-Jan Hendricks Franssen
Hydrol. Earth Syst. Sci., 27, 3143–3167, https://doi.org/10.5194/hess-27-3143-2023, https://doi.org/10.5194/hess-27-3143-2023, 2023
Short summary
Short summary
In our study, we tested the utility and skill of a state-of-the-art forecasting product for the prediction of regional crop productivity using a land surface model. Our results illustrate the potential value and skill of combining seasonal forecasts with modelling applications to generate variables of interest for stakeholders, such as annual crop yield for specific cash crops and regions. In addition, this study provides useful insights for future technical model evaluations and improvements.
Yuanhong You, Chunlin Huang, Zuo Wang, Jinliang Hou, Ying Zhang, and Peipei Xu
Hydrol. Earth Syst. Sci., 27, 2919–2933, https://doi.org/10.5194/hess-27-2919-2023, https://doi.org/10.5194/hess-27-2919-2023, 2023
Short summary
Short summary
This study aims to investigate the performance of a genetic particle filter which was used as a snow data assimilation scheme across different snow climates. The results demonstrated that the genetic algorithm can effectively solve the problem of particle degeneration and impoverishment in a particle filter algorithm. The system has revealed a low sensitivity to the particle number in point-scale application of the ground snow depth measurement.
Cited articles
Alkama, R., Marchand, L., Ribes, A., and Decharme, B.: Detection of global runoff changes: results from observations and CMIP5 experiments, Hydrol. Earth Syst. Sci., 17, 2967–2979, https://doi.org/10.5194/hess-17-2967-2013, 2013.
Baruga, C. K., Kim, D., and Choi, M.: A national-scale drought assessment in
Uganda based on evapotranspiration deficits from the Bouchet hypothesis, J.
Hydrol., 580, 124348, https://doi.org/10.1016/j.jhydrol.2019.124348, 2020.
Berg, A., Findell, K., Lintner, B., Giannini, A., Seneviratne, S. I., van
den Hurk, B., Lorenz, R., Pitman, A., Hagemann, S., Meier, A., Cheruy, F.,
Ducharne, A., Malyshev, S., and Milly, P. C. D.: Land-atmosphere feedbacks
amplify aridity increase over land under global warming, Nat. Clim. Change,
6, 869–874, https://doi.org/10.1038/nclimate3029, 2016.
Biasutti, M.: Rainfall trends in the African Sahel: Characteristics,
processes, and causes, WIREs Clim. Change, 10, e591,
https://doi.org/10.1002/wcc.591, 2019.
Bosmans, J. H. C., van Beek, L. P. H., Sutanudjaja, E. H., and Bierkens, M. F. P.: Hydrological impacts of global land cover change and human water use, Hydrol. Earth Syst. Sci., 21, 5603–5626, https://doi.org/10.5194/hess-21-5603-2017, 2017.
Byrne, M. P. and O'Gorman, P. A.: The response of precipitation minus
evapotranspiration to climate warming: Why the “wet-get-wetter,
dry-get-drier” scaling does not hold over land, J. Climate, 28, 8078–8092,
https://doi.org/10.1175/JCLI-D-15-0369.1, 2015.
Chen, Z. J., Zhu, Z. C., Jiang, H., and Sun S. J.: Estimating daily
reference evapotranspiration based on limited meteorological data using deep
learning and classical machine learning methods, J. Hydrol., 591, 125286,
https://doi.org/10.1016/j.jhydrol.2020.125286, 2020.
Chou, C., Neelin, J. D., Chen, C. A., and Tu, J. Y.: Evaluating the
“rich-get-richer” mechanism in tropical precipitation change under global
warming, J. Climate, 22, 1982–2005, https://doi.org/10.1175/2008JCLI2471.1,
2009.
Cook, B. I., Smerdon, J. E., Seager, R., and Coats, S.: Global warming and
21st century drying, Clim. Dynam., 43, 2607–2627,
https://doi.org/10.1007/s00382-014-2075-y, 2014.
Costa, M. H., Biajoli, M. C., Sanches, L., Malhado, A. C. M., Hutyra, L. R.,
da Rocha, H. R., Aguiar, R. G., and de Araújo, A. C.: Atmospheric versus
vegetation controls of Amazonian tropical rain forest evapotranspiration:
Are the wet and seasonally dry rain forests any different?, J. Geophys.
Res.-Biogeo., 115, G04021, https://doi.org/10.1029/2009jg001179, 2010.
Dai, A.: Increasing drought under global warming in observations and models,
Nat. Clim. Change, 3, 171–171, https://doi.org/10.1038/nclimate1633, 2013.
Durre, I., Menne, M. J., Gleason, B. E., Houston, T. G., and Vose, R. S.:
Comprehensive automated quality assurance of daily surface observations, J.
Appl. Meteorol. Clim., 49, 1615–1633,
https://doi.org/10.1175/2010JAMC2375.1, 2010.
Dong, B. and Sutton, R.: Dominant role of greenhouse-gas forcing in the
recovery of Sahel rainfall, Nat. Clim. Change, 5, 757–760,
https://doi.org/10.1038/nclimate2664, 2015.
GRDC: The global runoff data base, available at: https://www.bafg.de/GRDC/EN/01_GRDC/13_dtbse/database_node.html, last access: 23 June 2021.
FLUXET community: FLUXNET2015 FULLSET data, available at: https://fluxnet.org/data/download-data/, last access: 23 June 2021.
Food and Agriculture Organization (FAO) of the United Nations: The global map of irrigated areas, available at: http://www.fao.org/aquastat/en/geospatial-information/global-maps-irrigated-areas/latest-version/, last access: 23 June 2021.
Forzieri, G., Miralles, D., Ciais, P., Alkama, R., Ryu, Y., Duveiller, G.,
Zhang, K., Robertson, E., Kautz, M., Martens, B., Jiang, C., Arneth, A.,
Georgievski, G., Li, W., Ceccherini, G., Anthoni, P., Lawrence, P.,
Wiltshire, A., Pongratz, J., Piao, S., Sitch, S., Goll, D. S., Arora, V. K.,
Lienert, S., Lombardozzi, D., Kato, E., Nabel, J. E. M. S., Tian, H.,
Friedlingstein, P., and Cescatti, A.: Increased control of vegetation on
global terrestrial energy fluxes, Nat. Clim. Change, 10, 356–362,
https://doi.org/10.1038/s41558-020-0717-0, 2020.
Fu, C., James, A. L., and Wachowiak, M. P.: Analyzing the combined influence of
solar activity and El Niño on streamflow across southern Canada, Water
Resour. Res., 48, W05507, https://doi.org/10.1029/2011WR011507, 2012.
Fu, Q. and Feng, S.: Responses of terrestrial aridity to global warming, J.
Geophys. Res.-Atmos., 119, 7863–7875, https://doi.org/10.1002/2014JD021608,
2014.
Francesco, N., Mirco, B., Gabriele, C., Stefano, B., and Pietro, B.:
Evaporative fraction as an indicator of moisture condition and water stress
status in semi-arid range land ecosystems, Remote Sens., 6, 6300–6323,
https://doi.org/10.3390/rs6076300, 2014.
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,
https://doi.org/10.1175/2011JHM1261.1, 2011.
Gentine, P., Holtslag, A. A., D'Andrea, F., and Ek, M.: Surface and atmospheric
controls on the onset of moist convection over land, J.
Hydrometeorol., 14, 1443–1462, 2013a.
Gentine, P., Ferguson, C. R., and Holtslag, A. A.: Diagnosing evaporative
fraction over land from boundary-layer clouds, J. Geophys.
Res.-Atmos., 118, 8185–8196, 2013b.
Gentine, P., Chhang, A., Rigden, A., and Salvucci, G.: Evaporation estimates
using weather station data and boundary layer theory, Geophys. Res. Lett.,
43, 11661–11670, https://doi.org/10.1002/2016GL070819, 2016.
Greve, P., Orlowsky, B., Mueller, B., Sheffield, J., Reichstein, M., and
Seneviratne, S. I.: Global assessment of trends in wetting and drying over
land, Nat. Geosci., 7, 716–721, https://doi.org/10.1038/ngeo2247, 2014.
Haughton, N., Abramowitz, G., and Pitman, A. J.: On the predictability of land surface fluxes from meteorological variables, Geosci. Model Dev., 11, 195–212, https://doi.org/10.5194/gmd-11-195-2018, 2018.
Held, I. M. and Soden, B. J.: Robust Responses of the Hydrological Cycle to
Global Warming, J. Climate, 19, 5686–5699,
https://doi.org/10.1175/JCLI3990.1, 2006.
Hoek van Dijke, A. J., Mallick, K., Schlerf, M., Machwitz, M., Herold, M., and Teuling, A. J.: Examining the link between vegetation leaf area and land–atmosphere exchange of water, energy, and carbon fluxes using FLUXNET data, Biogeosciences, 17, 4443–4457, https://doi.org/10.5194/bg-17-4443-2020, 2020.
Jaramillo, F., Cory, N., Arheimer, B., Laudon, H., van der Velde, Y., Hasper, T. B., Teutschbein, C., and Uddling, J.: Dominant effect of increasing forest biomass on evapotranspiration: interpretations of movement in Budyko space, Hydrol. Earth Syst. Sci., 22, 567–580, https://doi.org/10.5194/hess-22-567-2018, 2018.
Jung, M., Reichstein, M., Ciais, P., Seneviratne, S.I., Goulden, M.
L., Bonan, G., Cescatti, A., Chen, J., de Jeu, R., Dolman, A. J.,, Eugster,
W., Gerten, D., Gianelle, D., Gobron, N., Heinke, J., Kimball, J., Law B.
E., Montagnani, L., Mu, Q., Mueller, B., Oleson, K., Papale, D., Richardson,
A. D., Roupsard, O., Running, S., Tomelleri, E., Viovy, N., Weber,
U., Williams, C., Wood, E., Zaehle, S., and Zhang, K.: Recent decline in the
global land evapotranspiration trend due to limited moisture supply, Nature,
467, 951–954, https://doi.org/10.1038/nature09396, 2010.
Jung, M., Reichstein, M., Margolis, H. A., Cescatti, A., Richardson, A. D.,
Arain, M. A., Arneth, A., Bernhofer, C., Bonal, D., Chen, J., Gianelle, D.,
Gobron, N., Kiely, G., Kutsch, W., Lasslop, G., Law, B. E., Lindroth, A.,
Merbold, L., Montagnani, L., Moors, E. J., Pagpale, D., Sottocornola, M.,
Vaccari, F., and Williams, C.: Global patterns of land-atmosphere fluxes of
carbon dioxide, latent heat, and sensible heat derived from eddy covariance,
satellite, and meteorological observations. J. Geophys. Res.-Biogeo., 116,
G00J07, https://doi.org/10.1029/2010JG001566, 2011.
Keenan, T. F., Hollinger, D. Y., Bohrer, G., Dragoni, D., Munger, J. W.,
Schmid, H. P., and Richardson, A. D.: Increase in forest water-use
efficiency as atmospheric carbon dioxide concentrations rise, Nature, 499,
324–327, https://doi.org/10.1038/nature12291, 2013.
Komatsu, H. and Kume, T.: Modeling of evapotranspiration changes with forest
management practices: A genealogical review, J. Hydrol., 585, 124835,
https://doi.org/10.1016/j.jhydrol.2020.124835, 2020.
Lehner, B., Liermann, C. R., Revenga, C., Vörösmarty, C., Fekete,
B., Crouzet, P., Döll, P., Endejan, M., Frenken, K., Magome, J.,
Nilsson, C., Robertson, J. C., Rödel, R., Sindorf, N., and Wisser,
D.: High-resolution mapping of the world's reservoirs and dams for
sustainable river-flow management, Front. Ecol. Environ., 9, 494–502,
https://doi.org/10.1890/100125, 2011.
Lemordant, L., Gentine, P., Swann, A. S., Cook, B. I., and Scheff, J.:
Critical impact of vegetation physiology on the continental hydrologic cycle
in response to increasing CO2, P. Natl. Acad. Sci. USA, 16,
4093–4098, https://doi.org/10.1073/pnas.1720712115, 2018.
Liu, C. and Allan, R. P.: Observed and simulated precipitation responses in
wet and dry regions 1850–2100, Environ. Res. Lett., 8, 034002,
https://doi.org/10.1088/1748-9326/8/3/034002, 2013.
Mallick, K., Trebs, I., Boegh, E., Giustarini, L., Schlerf, M., Drewry, D. T., Hoffmann, L., von Randow, C., Kruijt, B., Araùjo, A., Saleska, S., Ehleringer, J. R., Domingues, T. F., Ometto, J. P. H. B., Nobre, A. D., de Moraes, O. L. L., Hayek, M., Munger, J. W., and Wofsy, S. C.: Canopy-scale biophysical controls of transpiration and evaporation in the Amazon Basin, Hydrol. Earth Syst. Sci., 20, 4237–4264, https://doi.org/10.5194/hess-20-4237-2016, 2016.
Margulis, S. A.: Introduction to hydrology,
available at: https://margulis-group.github.io/teaching/ (last access: 23 June 2021), 2017.
Massmann, A., Gentine, P., and Lin, C.: When does vapor pressure deficit
drive or reduce evapotranspiration?, J. Adv. Model. Earth Sy., 11,
3305–3320, https://doi.org/10.1029/2019MS001790, 2019.
Miralles, D. G., De Jeu, R. A. M., Gash, J. H., Holmes, T. R. H., and Dolman, A. J.: Magnitude and variability of land evaporation and its components at the global scale, Hydrol. Earth Syst. Sci., 15, 967–981, https://doi.org/10.5194/hess-15-967-2011, 2011.
Miralles, D. G., Van, d. B. M. J., Gash, J. H., Parinussa, R. M., de Jeu, R.
A. M., Beck, H. E., Holmes, T. R. H., Carlos Jiménez, C., Verhoest, N.
E. C., Dorigo, W. A., Teuling, A. J., and Dolman, A. J.: El Niño–La
Niña cycle and recent trends in continental evaporation, Nat. Clim.
Change, 4, 122–126, https://doi.org/10.1038/nclimate2068, 2013.
Miralles, D. G., Brutsaert, W., Dolman, A. J., and Gash, J. H.: On the use
of the term “evapotranspiration”, Water Resour. Res., 56, e2020WR028055,
https://doi.org/10.1029/2020WR028055, 2020.
Milly, P. C. D. and Dunne, K. A.: Potential evapotranspiration and continental
drying, Nat. Clim. Change, 6, 946–949,
https://doi.org/10.1038/nclimate3046, 2016.
Nalley, D., Adamowski, J., Biswas, A., Gharabaghi, B., and Hu, W.: A
multiscale and multivariate analysis of precipitation and streamflow
variability in relation to ENSO, NAO and PDO, J. Hydrol., 574, 288–307,
https://doi.org/10.1016/j.jhydrol.2019.04.024, 2019.
NASA: The global reservoir and dam (GRanD) data, available at: https://sedac.ciesin.columbia.edu/data/collection/grand-v1/sets/browse, last access: 23 June 2021.
Naumann, G., Alfieri, L., Wyser, K., Mentaschi, L., Betts, R. A., Carrao,
H., Spinoni, J., Vogt, J., and Feyen, L.: Global changes in drought
conditions under different levels of warming, Geophys. Res. Lett., 45,
3285–3296, https://doi.org/10.1002/2017GL076521, 2018.
NOAA: The Global Summary of the Day and the Global Historical Climatology Network-daily (GHCND), available at: https://www.ncdc.noaa.gov/data-access/land-based-station-data/land-based-datasets, last access: 23 June 2021a.
NOAA: The multivariate ENSO index (MEI), available at: https://psl.noaa.gov/enso/mei/, last access: 23 June 2021b.
Orth, R. and Destouni, G.: Drought reduces blue-water fluxes more strongly
than green-water fluxes in Europe, Nat. Commun., 9, 3602,
https://doi.org/10.1038/s41467-018-06013-7, 2018.
Padrón, R. S., Gudmundsson, L., Decharme, B., Ducharne, A., Lawrence, D.
M., Mao, J., Peano, D., Krinner, G., Hyungjun Kim, H., and Seneviratne, S.
I.: Observed changes in dry-season water availability attributed to
human-induced climate change, Nat. Geosci., 13, 477–481,
https://doi.org/10.1038/s41561-020-0594-1, 2020.
Pastorello, G., Trotta, C., Canfora, E., Chu, H., Christianson, D., Frank,
J., Massman, W., and Urbanski, S.: The FLUXNET2015 dataset and the ONEFlux
processing pipeline for eddy covariance data, Sci. Data, 7, 225,
https://doi.org/10.1038/s41597-020-0534-3, 2020.
Rigden, A. J. and Salvucci, G. D.: Evapotranspiration based on equilibrated
relative humidity (ETRHEQ): Evaluation over the continental US, Water
Resour. Res., 51, 2951–2973, https://doi.org/10.1002/2014WR016072, 2015.
Rigden, A. J. and Salvucci, G. D.: Stomatal response to humidity and
CO2 implicated in recent decline in US evaporation, Glob. Change
Biol., 23, 1140–1150, https://doi.org/10.1111/gcb.13439, 2016.
Salvucci, G. D. and Gentine, P.: Emergent relation between surface vapor
conductance and relative humidity profiles yields evaporation rates from
weather data, P. Natl. Acad. Sci. USA, 110, 6287–6291,
https://doi.org/10.1073/pnas.1215844110, 2013.
Samaniego, L., Thober, S., Kumar, R., Wanders, N., Rakovec, O., Pan, M.,
Zink, M., Sheffield, J., Wood, E. F., and Marx, A.: Anthropogenic warming
exacerbates European soil moisture droughts, Nat. Clim. Change, 8, 421–428,
https://doi.org/10.1038/s41558-018-0138-5, 2018.
Sheffield, J., Wood, E. F., and Roderick, M. L.: Little change in global
drought over the past 60 years, Nature, 491, 435–438,
https://doi.org/10.1038/nature11575, 2012.
Sorokin, Y., Jane Zelikova, T., Blumenthal, D., Williams, D. G., and
Pendall, E.: Seasonally contrasting responses of evapotranspiration to
warming and elevated CO2 in a semi-arid grassland, Ecohydrology, 10,
e1880, https://doi.org/10.1002/eco.1880, 2017.
Sophocleous, M.: Interactions between ground water and surface water: the
state of the science, Hydrogeol. J., 10, 348–348,
https://doi.org/10.1007/s10040-001-0170-8, 2002.
Swann, A. L., Hoffman, F. M., Koven, C. D., and Randerson, J. T.: Plant
responses to increasing CO2 reduce estimates of climate impacts on
drought severity, P. Natl. Acad. Sci. USA, 113, 10019–10024,
https://doi.org/10.1073/pnas.1604581113, 2016.
Thiery, W., Davin, E. L., Lawrence, D. M., Hirsch, A. L., and Seneviratne,
S. I.: Present-day irrigation mitigates heat extremes, J. Geophys. Res.-Atmos., 122, 1403–1422, https://doi.org/10.1002/2016JD025740, 2017.
Trenberth, K. E., Dai, A., van der Schrier, G., Jones, P. D., Barichivich,
J., Briffa, K. R., and Sheffifield, J.: Global warming and changes in
drought, Nat. Clim. Change, 4, 17–22, https://doi.org/10.1038/NCLIMATE2067,
2014.
Teuling, A. J., de Badts, E. A. G., Jansen, F. A., Fuchs, R., Buitink, J., Hoek van Dijke, A. J., and Sterling, S. M.: Climate change, reforestation/afforestation, and urbanization impacts on evapotranspiration and streamflow in Europe, Hydrol. Earth Syst. Sci., 23, 3631–3652, https://doi.org/10.5194/hess-23-3631-2019, 2019.
van der Schrier, G., Jones, P. D., and Briffa, K. R.: The sensitivity of the
PDSI to the Thornthwaite and Penman-Monteith parameterizations for potential
evapotranspiration, J. Geophys. Res.-Atmos., 116, D03106,
https://doi.org/10.1029/2010JD015001, 2011.
Van Der Sleen, P., Groenendijk, P., Vlam, M., Anten, N. P. R., Boom, A.,
Bongers, F., Pons, T. L., Terburg, G., and Zuidema, P. A.: No growth
stimulation of tropical trees by 150 years of CO2 fertilization but
water-use efficiency increased, Nat. Geosci., 8, 24–28,
https://doi.org/10.1038/NGEO2313, 2015.
Vicente-Serrano, S. M., Van Gerard, V. D. S., Beguería, S.,
Azorin-Molina, C., and Lopez-Moreno, J. I.: Contribution of precipitation
and reference evapotranspiration to drought indices under different
climates, J. Hydrol., 526, 42–54,
https://doi.org/10.1016/j.jhydrol.2014.11.025, 2015.
Wagle, P., Xiao, X., Scott, R. L., Kolb, T. E., Cook, D. R., Brunsell, N.,
Baldocchi, D. D., Basara, J., Matamala, R., Zhou, Y., and Bajgain, R.:
Biophysical controls on carbon and water vapor fluxes across a grassland
climatic gradient in the United States, Agr. Forest Meteorol., 214,
293–305, https://doi.org/10.1016/j.agrformet.2015.08.265, 2015.
Wang, R., Chen, J. Y., Chen, X. W., and Wang, Y. F.: Variability of precipitation extremes and dryness/wetness over the southeast coastal region of China, 1960–2014, Int. J. Climatol., 37, 4656–4669, https://doi.org/10.1002/joc.5113, 2017.
Wang, R., Lü, G., Ning, L., Yuan, L., and Li, L.: Likelihood of compound dry and hot extremes increased with stronger dependence during warm seasons, Atmos. Res., 105692, https://doi.org/10.1016/j.atmosres.2021.105692, 2021.
Wang, S., Zhang, Y., Ju, W., Chen, J. M., Ciais, P., Cescatti, A., Sardans,
J., Janssens, I. A., Wu, M., Berry, J. A., Campbell, E.,
Fernández-Martínez, M., Alkama, R., Sitch, S., Friedlingstein, P.,
Smith, W. K., Yuan, W., He, W., Lombardozzi, D., Kautz, M., Zhu, D.,
Lienert, S., Kato, E., Poulter, B., Sanders, T. G. M., Krüger, I., Wang,
R., Zeng, N., Tian, H., Vuichard, N., Jain, A. K., Wiltshire, A., Haverd,
V., Goll, D. S., and Peñuelas, J.: Recent global decline of CO2
fertilization effects on vegetation photosynthesis, Science, 370, 1295–1300,
https://doi.org/10.1126/science.abb7772, 2020.
Williams, I. N. and Torn, M. S.: Vegetation controls on surface heat flux
partitioning, and land-atmosphere coupling, Geophys. Res. Lett., 42,
9416–9424, https://doi.org/10.1002/2015gl066305, 2015.
Williams, C. A., Reichstein, M., Buchmann, N., Baldocchi, D., Beer, C.,
Schwalm, C., Wohlfahrt, G., Hasler, N., Bernhofer, C., Foken, T., Papale,
D., Schymanski, S., and Schaefer, K.: Climate and vegetation controls on the
surface water balance: Synthesis of evapotranspiration measured across a
global network of flux towers, Water Resour. Res., 48, W06523,
https://doi.org/10.1029/2011WR011586, 2012.
Wei, Z., Yoshimura, K., Wang, L., Miralles, D. G., Jasechko, S., and Lee, X.
H.: Revisiting the contribution of transpiration to global terrestrial
evapotranspiration, Geophys. Res. Lett., 44, 2792–2801,
https://doi.org/10.1002/2016GL072235, 2017.
Yang, Y., Zhang, S., Roderick, M. L., McVicar, T. R., Yang, D., Liu, W., and Li, X.: Comparing Palmer Drought Severity Index drought assessments using the traditional offline approach with direct climate model outputs, Hydrol. Earth Syst. Sci., 24, 2921–2930, https://doi.org/10.5194/hess-24-2921-2020, 2020.
Yang, Y. T., Roderick, M. L., Zhang, S., McVicar, T. R., and Donohue, R. J.:
Hydrologic implications of vegetation response to elevated CO2 in
climate projections, Nat. Clim. Change, 9, 44–48,
https://doi.org/10.1038/s41558-018-0361-0, 2019.
Yin, J. B., Gentine, P., Zhou, S., Sullivan, S. C., Wang, R., Zhang, Y., and
Guo, S. L.: Large increase in global storm runoff extremes driven by climate
and anthropogenic changes, Nat. Commun., 22, 4389,
https://doi.org/10.1038/s41467-018-06765-2, 2018.
Zhao, W. L., Gentine, P., Reichstein, M., Zhang, Y., Zhou, S., Wen, Y., Lin,
C., Li, X., and Qiu, G. Y.: Physics-constrained machine learning of
evapotranspiration, Geophys. Res. Lett., 46, 14496–14507,
https://doi.org/10.1029/2019GL085291, 2019.
Zhou, C. and Wang, K.: Biological and environmental controls on evaporative
fractions at AmeriFlux sites, J. Appl. Meteorol. Clim., 55, 145–161,
https://doi.org/10.1175/JAMC-D-15-0126.1, 2016.
Zhou, S., Williams, A. P., Berg, A. M., Cook, B. I., Zhang, Y., Stefan, H.,
Ruth, L., Seneviratne, S. I., and Gentine, P.: Land–atmosphere feedbacks
exacerbate concurrent soil drought and atmospheric aridity. Proc. Natl.
Acad. Sci. USA, 116, 18848–18853, https://doi.org/10.1073/pnas.1904955116,
2019.
Download
The requested paper has a corresponding corrigendum published. Please read the corrigendum first before downloading the article.
- Article
(8320 KB) - Full-text XML
- Corrigendum
-
Supplement
(8598 KB) - BibTeX
- EndNote
Short summary
Assessment of changes in the global water cycle has been a challenge. This study estimated long-term global latent heat and sensible heat fluxes for recent decades using machine learning and ground observations. The results found that the decline in evaporative fraction was typically accompanied by an increase in long-term runoff in over 27.06 % of the global land areas. The observation-driven findings emphasized that surface vegetation has great impacts in regulating water and energy cycles.
Assessment of changes in the global water cycle has been a challenge. This study estimated...
