Articles | Volume 10, issue 2
https://doi.org/10.5194/essd-10-787-2018
© Author(s) 2018. 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-10-787-2018
© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
17 Apr 2018
The Global Streamflow Indices and Metadata Archive (GSIM) – Part 2: Quality control, time-series indices and homogeneity assessment
Lukas Gudmundsson
CORRESPONDING AUTHOR
Institute for Atmospheric and Climate Science, Department of
Environmental Systems Science, ETH Zurich,
Universitaetstrasse 16, Zurich 8092, Switzerland
Hong Xuan Do
School of Civil, Environmental and Mining Engineering, University of
Adelaide, Adelaide, Australia
Michael Leonard
School of Civil, Environmental and Mining Engineering, University of
Adelaide, Adelaide, Australia
Seth Westra
School of Civil, Environmental and Mining Engineering, University of
Adelaide, Adelaide, Australia
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Dominik L. Schumacher, Mariam Zachariah, Friederike Otto, Clair Barnes, Sjoukje Philip, Sarah Kew, Maja Vahlberg, Roop Singh, Dorothy Heinrich, Julie Arrighi, Maarten van Aalst, Mathias Hauser, Martin Hirschi, Verena Bessenbacher, Lukas Gudmundsson, Hiroko K. Beaudoing, Matthew Rodell, Sihan Li, Wenchang Yang, Gabriel A. Vecchi, Luke J. Harrington, Flavio Lehner, Gianpaolo Balsamo, and Sonia I. Seneviratne
EGUsphere, https://doi.org/10.5194/egusphere-2023-717, https://doi.org/10.5194/egusphere-2023-717, 2023
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Climate models are powerful tools, but with high computational costs, hindering their use to explore future climate extremes. We demonstrate here MESMER-X, the only existing emulator for spatial climate extremes (heatwaves, fires, droughts) that mimics all their relevant properties. Thanks to its negligible computational cost, MESMER-X may greatly accelerate the exploration of future climate extremes or enable the integration of climate extremes in economic and finance models.
Ryan S. Padrón, Lukas Gudmundsson, Laibao Liu, Vincent Humphrey, and Sonia I. Seneviratne
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The answer to how much carbon land ecosystems are projected to remove from the atmosphere until 2100 is different for each Earth system model. We find that differences across models are primarily explained by the annual land carbon sink dependence on temperature and soil moisture, followed by the dependence on CO2 air concentration, and by average climate conditions. Our insights on why each model projects a relatively high or low land carbon sink can help to reduce the underlying uncertainty.
Shruti Nath, Lukas Gudmundsson, Jonas Schwaab, Gregory Duveiller, Steven Johan De Hertog, Suqi Guo, Felix Havermann, Fei Luo, Iris Manola, Julia Pongratz, Sonia Isabelle Seneviratne, Carl Friedrich Schleussner, Wim Thiery, and Quentin Lejeune
EGUsphere, https://doi.org/10.5194/egusphere-2022-1024, https://doi.org/10.5194/egusphere-2022-1024, 2022
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The COP26 saw significant pledges made to to halt and reverse deforestation. The regional impacts of this are key in informing national-level decisions and prioritising areas for conservation efforts. We present a first step towards agilely exploring these regional impacts using a simple statistical device, i.e. emulator. The emulator only needs to train on climate model output representing the maximal impacts of aff/re/deforestation from which it explores plausible in-between outcomes itself.
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Earth observations have many missing values. They are often filled using information from spatial and temporal contexts that mostly ignore information from related observed variables. We propose the gap-filling method CLIMFILL that additionally uses information from related variables. We test CLIMFILL using gap-free reanalysis data of variables related to soil–moisture climate interactions. CLIMFILL creates estimates for the missing values that recover the original dependence structure.
Lea Beusch, Zebedee Nicholls, Lukas Gudmundsson, Mathias Hauser, Malte Meinshausen, and Sonia I. Seneviratne
Geosci. Model Dev., 15, 2085–2103, https://doi.org/10.5194/gmd-15-2085-2022, https://doi.org/10.5194/gmd-15-2085-2022, 2022
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We introduce the first chain of computationally efficient Earth system model (ESM) emulators to translate user-defined greenhouse gas emission pathways into regional temperature change time series accounting for all major sources of climate change projection uncertainty. By combining the global mean emulator MAGICC with the spatially resolved emulator MESMER, we can derive ESM-specific and constrained probabilistic emulations to rapidly provide targeted climate information at the local scale.
Hong Xuan Do, Fang Zhao, Seth Westra, Michael Leonard, Lukas Gudmundsson, Julien Eric Stanislas Boulange, Jinfeng Chang, Philippe Ciais, Dieter Gerten, Simon N. Gosling, Hannes Müller Schmied, Tobias Stacke, Camelia-Eliza Telteu, and Yoshihide Wada
Hydrol. Earth Syst. Sci., 24, 1543–1564, https://doi.org/10.5194/hess-24-1543-2020, https://doi.org/10.5194/hess-24-1543-2020, 2020
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We presented a global comparison between observed and simulated trends in a flood index over the 1971–2005 period using the Global Streamflow Indices and Metadata archive and six global hydrological models available through The Inter-Sectoral Impact Model Intercomparison Project. Streamflow simulations over 2006–2099 period robustly project high flood hazard in several regions. These high-flood-risk areas, however, are under-sampled by the current global streamflow databases.
Ryan S. Padrón, Lukas Gudmundsson, Dominik Michel, and Sonia I. Seneviratne
Hydrol. Earth Syst. Sci., 24, 793–807, https://doi.org/10.5194/hess-24-793-2020, https://doi.org/10.5194/hess-24-793-2020, 2020
Short summary
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We focus on the net exchange of water between land and air via evapotranspiration and dew during the night. We provide, for the first time, an overview of the magnitude and variability of this flux across the globe from observations and climate models. Nocturnal water loss from land is 7 % of total evapotranspiration on average and can be greater than 15 % locally. Our results highlight the relevance of this often overlooked flux, with implications for water resources and climate studies.
Lea Beusch, Lukas Gudmundsson, and Sonia I. Seneviratne
Earth Syst. Dynam., 11, 139–159, https://doi.org/10.5194/esd-11-139-2020, https://doi.org/10.5194/esd-11-139-2020, 2020
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Earth system models (ESMs) are invaluable to study the climate system but expensive to run. Here, we present a statistical tool which emulates ESMs at a negligible computational cost by creating stochastic realizations of yearly land temperature field time series. Thereby, 40 ESMs are considered, and for each ESM, a single simulation is required to train the tool. The resulting ESM-specific realizations closely resemble ESM simulations not employed during training at point to regional scales.
Gionata Ghiggi, Vincent Humphrey, Sonia I. Seneviratne, and Lukas Gudmundsson
Earth Syst. Sci. Data, 11, 1655–1674, https://doi.org/10.5194/essd-11-1655-2019, https://doi.org/10.5194/essd-11-1655-2019, 2019
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Freshwater resources are of high societal relevance and understanding their past variability is vital to water management in the context of current and future climatic change. This study introduces GRUN: the first global gridded monthly reconstruction of runoff covering the period from 1902 to 2014. The dataset agrees on average much better with the streamflow observations than an ensemble of 13 state-of-the-art global hydrological models and will foster the understanding of freshwater dynamics.
Inne Vanderkelen, Jakob Zschleischler, Lukas Gudmundsson, Klaus Keuler, Francois Rineau, Natalie Beenaerts, Jaco Vangronsveld, and Wim Thiery
Biogeosciences Discuss., https://doi.org/10.5194/bg-2019-267, https://doi.org/10.5194/bg-2019-267, 2019
Manuscript not accepted for further review
Vincent Humphrey and Lukas Gudmundsson
Earth Syst. Sci. Data, 11, 1153–1170, https://doi.org/10.5194/essd-11-1153-2019, https://doi.org/10.5194/essd-11-1153-2019, 2019
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Because changes in freshwater availability can impact many natural ecosystems and human activities, it is crucial to better understand long-term changes in the water cycle. This dataset is a reconstruction of past changes in land water storage over the last century, obtained by combining satellite observations with historical weather data. It can be used to investigate both regional changes in freshwater availability or drought frequency and long-term changes in the global water cycle.
Hong Xuan Do, Lukas Gudmundsson, Michael Leonard, and Seth Westra
Earth Syst. Sci. Data, 10, 765–785, https://doi.org/10.5194/essd-10-765-2018, https://doi.org/10.5194/essd-10-765-2018, 2018
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The production of 30 959 daily streamflow time series in the Global Streamflow and Metadata Archive (GSIM) project is presented. The paper also describes the development of three metadata products that are freely available. Having collated an unprecedented number of stations and associated metadata, GSIM can be used to advance large-scale hydrological research and improve understanding of the global water cycle.
Peter Greve, Lukas Gudmundsson, and Sonia I. Seneviratne
Earth Syst. Dynam., 9, 227–240, https://doi.org/10.5194/esd-9-227-2018, https://doi.org/10.5194/esd-9-227-2018, 2018
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Assessing projected hydroclimatological changes is crucial, but associated with large uncertainties. We statistically assess here the response of precipitation and water availability to global temperature change, enabling us to estimate the significance of drying/wetting tendencies under anthropogenic climate change. We further show that opting for a 1.5 K warming target just slightly influences the mean response but could substantially reduce the risk of experiencing extreme changes.
Lukas Gudmundsson and Sonia I. Seneviratne
Earth Syst. Sci. Data, 8, 279–295, https://doi.org/10.5194/essd-8-279-2016, https://doi.org/10.5194/essd-8-279-2016, 2016
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Despite the scientific and societal relevance of freshwater, there are to date no observation-based pan-European runoff estimates available. Here we employ state-of-the-art techniques to estimate monthly runoff rates in Europe. The new data product is based on an unprecedented collection of river flow observations which are combined with atmospheric variables using machine learning. Potential applications of the presented product include climatological assessments and drought monitoring.
Peter Greve, Lukas Gudmundsson, Boris Orlowsky, and Sonia I. Seneviratne
Hydrol. Earth Syst. Sci., 20, 2195–2205, https://doi.org/10.5194/hess-20-2195-2016, https://doi.org/10.5194/hess-20-2195-2016, 2016
Short summary
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The widely used Budyko framework is by definition limited to steady-state conditions. In this study we analytically derive a new, two-parameter formulation of the Budyko framework that represents conditions under which evapotranspiration exceeds precipitation. This is technically achieved by rotating the water supply limit within the Budyko space. The new formulation is shown to be capable to represent first-order seasonal dynamics within the hydroclimatological system.
L. Gudmundsson and S. I. Seneviratne
Hydrol. Earth Syst. Sci., 19, 2859–2879, https://doi.org/10.5194/hess-19-2859-2015, https://doi.org/10.5194/hess-19-2859-2015, 2015
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Water storages and fluxes on land are key variables in the Earth system. To provide context for local investigations and to understand phenomena that emerge at large spatial scales, information on continental freshwater dynamics is needed. This paper presents a methodology to estimate continental-scale runoff on a 0.5° spatial grid, which combines the advantages of in situ observations with the power of machine learning regression. The resulting runoff estimates compare well with observations.
L. Gudmundsson and S. I. Seneviratne
Proc. IAHS, 369, 75–79, https://doi.org/10.5194/piahs-369-75-2015, https://doi.org/10.5194/piahs-369-75-2015, 2015
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Recent climate projections suggest changes in European drought frequency, indicating increased drought risk in the south and less droughts in the north. Here we show that a similar change pattern can be identified in the observed record. The results raise the question whether observed changes in European drought frequency are a consequence of anthropogenic climate change.
L. Gudmundsson and S. I. Seneviratne
Hydrol. Earth Syst. Sci. Discuss., https://doi.org/10.5194/hessd-10-13191-2013, https://doi.org/10.5194/hessd-10-13191-2013, 2013
Manuscript not accepted for further review
Dominik L. Schumacher, Mariam Zachariah, Friederike Otto, Clair Barnes, Sjoukje Philip, Sarah Kew, Maja Vahlberg, Roop Singh, Dorothy Heinrich, Julie Arrighi, Maarten van Aalst, Mathias Hauser, Martin Hirschi, Verena Bessenbacher, Lukas Gudmundsson, Hiroko K. Beaudoing, Matthew Rodell, Sihan Li, Wenchang Yang, Gabriel A. Vecchi, Luke J. Harrington, Flavio Lehner, Gianpaolo Balsamo, and Sonia I. Seneviratne
EGUsphere, https://doi.org/10.5194/egusphere-2023-717, https://doi.org/10.5194/egusphere-2023-717, 2023
Short summary
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As our climate warms, soils in West-Central Europe and across much of the northern extratropics are expected to dry out more often. An event such as the 2022 summer soil drought in Europe would naturally occur about once per century, but the current global warming of 1.2 °C has already increased the probability of such an event five-fold. With even more warming, at +2 °C, we expect a 2022-like drought or worse every 10th summer, being 10 times more likely due to human-induced climate change.
Yann Quilcaille, Lukas Gudmundsson, and Sonia Isabelle Seneviratne
EGUsphere, https://doi.org/10.5194/egusphere-2023-589, https://doi.org/10.5194/egusphere-2023-589, 2023
Short summary
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Climate models are powerful tools, but with high computational costs, hindering their use to explore future climate extremes. We demonstrate here MESMER-X, the only existing emulator for spatial climate extremes (heatwaves, fires, droughts) that mimics all their relevant properties. Thanks to its negligible computational cost, MESMER-X may greatly accelerate the exploration of future climate extremes or enable the integration of climate extremes in economic and finance models.
Ryan S. Padrón, Lukas Gudmundsson, Laibao Liu, Vincent Humphrey, and Sonia I. Seneviratne
Biogeosciences, 19, 5435–5448, https://doi.org/10.5194/bg-19-5435-2022, https://doi.org/10.5194/bg-19-5435-2022, 2022
Short summary
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The answer to how much carbon land ecosystems are projected to remove from the atmosphere until 2100 is different for each Earth system model. We find that differences across models are primarily explained by the annual land carbon sink dependence on temperature and soil moisture, followed by the dependence on CO2 air concentration, and by average climate conditions. Our insights on why each model projects a relatively high or low land carbon sink can help to reduce the underlying uncertainty.
Shruti Nath, Lukas Gudmundsson, Jonas Schwaab, Gregory Duveiller, Steven Johan De Hertog, Suqi Guo, Felix Havermann, Fei Luo, Iris Manola, Julia Pongratz, Sonia Isabelle Seneviratne, Carl Friedrich Schleussner, Wim Thiery, and Quentin Lejeune
EGUsphere, https://doi.org/10.5194/egusphere-2022-1024, https://doi.org/10.5194/egusphere-2022-1024, 2022
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The COP26 saw significant pledges made to to halt and reverse deforestation. The regional impacts of this are key in informing national-level decisions and prioritising areas for conservation efforts. We present a first step towards agilely exploring these regional impacts using a simple statistical device, i.e. emulator. The emulator only needs to train on climate model output representing the maximal impacts of aff/re/deforestation from which it explores plausible in-between outcomes itself.
Verena Bessenbacher, Sonia Isabelle Seneviratne, and Lukas Gudmundsson
Geosci. Model Dev., 15, 4569–4596, https://doi.org/10.5194/gmd-15-4569-2022, https://doi.org/10.5194/gmd-15-4569-2022, 2022
Short summary
Short summary
Earth observations have many missing values. They are often filled using information from spatial and temporal contexts that mostly ignore information from related observed variables. We propose the gap-filling method CLIMFILL that additionally uses information from related variables. We test CLIMFILL using gap-free reanalysis data of variables related to soil–moisture climate interactions. CLIMFILL creates estimates for the missing values that recover the original dependence structure.
Lea Beusch, Zebedee Nicholls, Lukas Gudmundsson, Mathias Hauser, Malte Meinshausen, and Sonia I. Seneviratne
Geosci. Model Dev., 15, 2085–2103, https://doi.org/10.5194/gmd-15-2085-2022, https://doi.org/10.5194/gmd-15-2085-2022, 2022
Short summary
Short summary
We introduce the first chain of computationally efficient Earth system model (ESM) emulators to translate user-defined greenhouse gas emission pathways into regional temperature change time series accounting for all major sources of climate change projection uncertainty. By combining the global mean emulator MAGICC with the spatially resolved emulator MESMER, we can derive ESM-specific and constrained probabilistic emulations to rapidly provide targeted climate information at the local scale.
Wenyan Wu, Seth Westra, and Michael Leonard
Hydrol. Earth Syst. Sci., 25, 2821–2841, https://doi.org/10.5194/hess-25-2821-2021, https://doi.org/10.5194/hess-25-2821-2021, 2021
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Flood probability estimation is important for applications such as land use planning, reservoir operation, infrastructure design and safety assessments. However, it is a challenging task, especially in estuarine areas where floods are caused by both intense rainfall and storm surge. This study provides a review of approaches to flood probability estimation in these areas. Based on analysis of a real-world river system, guidance on method selection is provided.
Songyan Yu, Hong Xuan Do, Albert I. J. M. van Dijk, Nick R. Bond, Peirong Lin, and Mark J. Kennard
Hydrol. Earth Syst. Sci., 24, 5279–5295, https://doi.org/10.5194/hess-24-5279-2020, https://doi.org/10.5194/hess-24-5279-2020, 2020
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There is a growing interest globally in the spatial distribution and temporal dynamics of intermittently flowing streams and rivers. We developed an approach to quantify catchment-wide flow intermittency over long time frames. Modelled patterns of flow intermittency in eastern Australia revealed highly dynamic behaviour in space and time. The developed approach is transferable to other parts of the world and can inform hydro-ecological understanding and management of intermittent streams.
Hong Xuan Do, Fang Zhao, Seth Westra, Michael Leonard, Lukas Gudmundsson, Julien Eric Stanislas Boulange, Jinfeng Chang, Philippe Ciais, Dieter Gerten, Simon N. Gosling, Hannes Müller Schmied, Tobias Stacke, Camelia-Eliza Telteu, and Yoshihide Wada
Hydrol. Earth Syst. Sci., 24, 1543–1564, https://doi.org/10.5194/hess-24-1543-2020, https://doi.org/10.5194/hess-24-1543-2020, 2020
Short summary
Short summary
We presented a global comparison between observed and simulated trends in a flood index over the 1971–2005 period using the Global Streamflow Indices and Metadata archive and six global hydrological models available through The Inter-Sectoral Impact Model Intercomparison Project. Streamflow simulations over 2006–2099 period robustly project high flood hazard in several regions. These high-flood-risk areas, however, are under-sampled by the current global streamflow databases.
Ryan S. Padrón, Lukas Gudmundsson, Dominik Michel, and Sonia I. Seneviratne
Hydrol. Earth Syst. Sci., 24, 793–807, https://doi.org/10.5194/hess-24-793-2020, https://doi.org/10.5194/hess-24-793-2020, 2020
Short summary
Short summary
We focus on the net exchange of water between land and air via evapotranspiration and dew during the night. We provide, for the first time, an overview of the magnitude and variability of this flux across the globe from observations and climate models. Nocturnal water loss from land is 7 % of total evapotranspiration on average and can be greater than 15 % locally. Our results highlight the relevance of this often overlooked flux, with implications for water resources and climate studies.
Lea Beusch, Lukas Gudmundsson, and Sonia I. Seneviratne
Earth Syst. Dynam., 11, 139–159, https://doi.org/10.5194/esd-11-139-2020, https://doi.org/10.5194/esd-11-139-2020, 2020
Short summary
Short summary
Earth system models (ESMs) are invaluable to study the climate system but expensive to run. Here, we present a statistical tool which emulates ESMs at a negligible computational cost by creating stochastic realizations of yearly land temperature field time series. Thereby, 40 ESMs are considered, and for each ESM, a single simulation is required to train the tool. The resulting ESM-specific realizations closely resemble ESM simulations not employed during training at point to regional scales.
Phuong Dong Le, Michael Leonard, and Seth Westra
Hydrol. Earth Syst. Sci., 23, 4851–4867, https://doi.org/10.5194/hess-23-4851-2019, https://doi.org/10.5194/hess-23-4851-2019, 2019
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While conventional approaches focus on flood designs at individual locations, there are many situations requiring an understanding of spatial dependence of floods at multiple locations. This research describes a new framework for analyzing flood characteristics across civil infrastructure systems, including conditional and joint probabilities of floods. This work leads to a new flood estimation paradigm, which focuses on the risk of the entire system rather than each system element in isolation.
Bree Bennett, Mark Thyer, Michael Leonard, Martin Lambert, and Bryson Bates
Hydrol. Earth Syst. Sci., 23, 4783–4801, https://doi.org/10.5194/hess-23-4783-2019, https://doi.org/10.5194/hess-23-4783-2019, 2019
Short summary
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A new stochastic rainfall model evaluation framework is introduced, with three key features: (1) streamflow-based, to directly evaluate modelled streamflow performance, (2) virtual, to avoid confounding errors in hydrological models or data, and (3) targeted, to isolate errors according to specific sites/months. The framework identified the importance of rainfall in the
wetting-upmonths for providing reliable predictions of streamflow over the entire year despite their low flow volumes.
Gionata Ghiggi, Vincent Humphrey, Sonia I. Seneviratne, and Lukas Gudmundsson
Earth Syst. Sci. Data, 11, 1655–1674, https://doi.org/10.5194/essd-11-1655-2019, https://doi.org/10.5194/essd-11-1655-2019, 2019
Short summary
Short summary
Freshwater resources are of high societal relevance and understanding their past variability is vital to water management in the context of current and future climatic change. This study introduces GRUN: the first global gridded monthly reconstruction of runoff covering the period from 1902 to 2014. The dataset agrees on average much better with the streamflow observations than an ensemble of 13 state-of-the-art global hydrological models and will foster the understanding of freshwater dynamics.
Inne Vanderkelen, Jakob Zschleischler, Lukas Gudmundsson, Klaus Keuler, Francois Rineau, Natalie Beenaerts, Jaco Vangronsveld, and Wim Thiery
Biogeosciences Discuss., https://doi.org/10.5194/bg-2019-267, https://doi.org/10.5194/bg-2019-267, 2019
Manuscript not accepted for further review
Vincent Humphrey and Lukas Gudmundsson
Earth Syst. Sci. Data, 11, 1153–1170, https://doi.org/10.5194/essd-11-1153-2019, https://doi.org/10.5194/essd-11-1153-2019, 2019
Short summary
Short summary
Because changes in freshwater availability can impact many natural ecosystems and human activities, it is crucial to better understand long-term changes in the water cycle. This dataset is a reconstruction of past changes in land water storage over the last century, obtained by combining satellite observations with historical weather data. It can be used to investigate both regional changes in freshwater availability or drought frequency and long-term changes in the global water cycle.
Stephen Blenkinsop, Hayley J. Fowler, Renaud Barbero, Steven C. Chan, Selma B. Guerreiro, Elizabeth Kendon, Geert Lenderink, Elizabeth Lewis, Xiao-Feng Li, Seth Westra, Lisa Alexander, Richard P. Allan, Peter Berg, Robert J. H. Dunn, Marie Ekström, Jason P. Evans, Greg Holland, Richard Jones, Erik Kjellström, Albert Klein-Tank, Dennis Lettenmaier, Vimal Mishra, Andreas F. Prein, Justin Sheffield, and Mari R. Tye
Adv. Sci. Res., 15, 117–126, https://doi.org/10.5194/asr-15-117-2018, https://doi.org/10.5194/asr-15-117-2018, 2018
Short summary
Short summary
Measurements of sub-daily (e.g. hourly) rainfall totals are essential if we are to understand short, intense bursts of rainfall that cause flash floods. We might expect the intensity of such events to increase in a warming climate but these are poorly realised in projections of future climate change. The INTENSE project is collating a global dataset of hourly rainfall measurements and linking with new developments in climate models to understand the characteristics and causes of these events.
Hong Xuan Do, Lukas Gudmundsson, Michael Leonard, and Seth Westra
Earth Syst. Sci. Data, 10, 765–785, https://doi.org/10.5194/essd-10-765-2018, https://doi.org/10.5194/essd-10-765-2018, 2018
Short summary
Short summary
The production of 30 959 daily streamflow time series in the Global Streamflow and Metadata Archive (GSIM) project is presented. The paper also describes the development of three metadata products that are freely available. Having collated an unprecedented number of stations and associated metadata, GSIM can be used to advance large-scale hydrological research and improve understanding of the global water cycle.
Peter Greve, Lukas Gudmundsson, and Sonia I. Seneviratne
Earth Syst. Dynam., 9, 227–240, https://doi.org/10.5194/esd-9-227-2018, https://doi.org/10.5194/esd-9-227-2018, 2018
Short summary
Short summary
Assessing projected hydroclimatological changes is crucial, but associated with large uncertainties. We statistically assess here the response of precipitation and water availability to global temperature change, enabling us to estimate the significance of drying/wetting tendencies under anthropogenic climate change. We further show that opting for a 1.5 K warming target just slightly influences the mean response but could substantially reduce the risk of experiencing extreme changes.
Danlu Guo, Seth Westra, and Holger R. Maier
Hydrol. Earth Syst. Sci., 21, 2107–2126, https://doi.org/10.5194/hess-21-2107-2017, https://doi.org/10.5194/hess-21-2107-2017, 2017
Short summary
Short summary
This study assessed the impact of baseline climate conditions on the sensitivity of potential evapotranspiration (PET) to a large range of plausible changes in temperature, relative humidity, solar radiation and wind speed at 30 Australian locations. Around 2-fold greater PET changes were observed at cool and humid locations compared to others, indicating potential for elevated water loss in the future. These impacts can be useful to inform the selection of PET models under a changing climate.
Lukas Gudmundsson and Sonia I. Seneviratne
Earth Syst. Sci. Data, 8, 279–295, https://doi.org/10.5194/essd-8-279-2016, https://doi.org/10.5194/essd-8-279-2016, 2016
Short summary
Short summary
Despite the scientific and societal relevance of freshwater, there are to date no observation-based pan-European runoff estimates available. Here we employ state-of-the-art techniques to estimate monthly runoff rates in Europe. The new data product is based on an unprecedented collection of river flow observations which are combined with atmospheric variables using machine learning. Potential applications of the presented product include climatological assessments and drought monitoring.
Peter Greve, Lukas Gudmundsson, Boris Orlowsky, and Sonia I. Seneviratne
Hydrol. Earth Syst. Sci., 20, 2195–2205, https://doi.org/10.5194/hess-20-2195-2016, https://doi.org/10.5194/hess-20-2195-2016, 2016
Short summary
Short summary
The widely used Budyko framework is by definition limited to steady-state conditions. In this study we analytically derive a new, two-parameter formulation of the Budyko framework that represents conditions under which evapotranspiration exceeds precipitation. This is technically achieved by rotating the water supply limit within the Budyko space. The new formulation is shown to be capable to represent first-order seasonal dynamics within the hydroclimatological system.
L. Gudmundsson and S. I. Seneviratne
Hydrol. Earth Syst. Sci., 19, 2859–2879, https://doi.org/10.5194/hess-19-2859-2015, https://doi.org/10.5194/hess-19-2859-2015, 2015
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Water storages and fluxes on land are key variables in the Earth system. To provide context for local investigations and to understand phenomena that emerge at large spatial scales, information on continental freshwater dynamics is needed. This paper presents a methodology to estimate continental-scale runoff on a 0.5° spatial grid, which combines the advantages of in situ observations with the power of machine learning regression. The resulting runoff estimates compare well with observations.
L. Gudmundsson and S. I. Seneviratne
Proc. IAHS, 369, 75–79, https://doi.org/10.5194/piahs-369-75-2015, https://doi.org/10.5194/piahs-369-75-2015, 2015
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Recent climate projections suggest changes in European drought frequency, indicating increased drought risk in the south and less droughts in the north. Here we show that a similar change pattern can be identified in the observed record. The results raise the question whether observed changes in European drought frequency are a consequence of anthropogenic climate change.
L. Gudmundsson and S. I. Seneviratne
Hydrol. Earth Syst. Sci. Discuss., https://doi.org/10.5194/hessd-10-13191-2013, https://doi.org/10.5194/hessd-10-13191-2013, 2013
Manuscript not accepted for further review
Related subject area
Hydrology
Generation of global 1 km daily soil moisture product from 2000 to 2020 using ensemble learning
Panta Rhei benchmark dataset: socio-hydrological data of paired events of floods and droughts
Twelve years of profile soil moisture and temperature measurements in Twente, the Netherlands
Shallow-groundwater-level time series and a groundwater chemistry survey from a boreal headwater catchment, Krycklan, Sweden
Weekly high-resolution multi-spectral and thermal uncrewed-aerial-system mapping of an alpine catchment during summer snowmelt, Niwot Ridge, Colorado
Nunataryuk field campaigns: understanding the origin and fate of terrestrial organic matter in the coastal waters of the Mackenzie Delta region
Integrated ecohydrological hydrometric and stable water isotope data of a drought-sensitive mixed land use lowland catchment
Regional data sets of high-resolution (1 and 6 km) irrigation estimates from space
Lake surface temperature retrieved from Landsat satellite series (1984 to 2021) for the North Slave Region
Global hourly, 5 km, all-sky land surface temperature data from 2011 to 2021 based on integrating geostationary and polar-orbiting satellite data
Flood detection using Gravity Recovery and Climate Experiment (GRACE) terrestrial water storage and extreme precipitation data
The pan-Arctic catchment database (ARCADE)
Multi-hazard susceptibility mapping of cryospheric hazards in a high-Arctic environment: Svalbard Archipelago
The UKSCAPE-G2G river flow and soil moisture datasets: Grid-to-Grid model estimates for the UK for historical and potential future climates
High-resolution water level and storage variation datasets for 338 reservoirs in China during 2010–2021
WaterBench-Iowa: a large-scale benchmark dataset for data-driven streamflow forecasting
A long-term monthly surface water storage dataset for the Congo basin from 1992 to 2015
A dataset of 10-year regional-scale soil moisture and soil temperature measurements at multiple depths on the Tibetan Plateau
OpenMRG: Open data from Microwave links, Radar, and Gauges for rainfall quantification in Gothenburg, Sweden
A 1 km daily soil moisture dataset over China using in situ measurement and machine learning
Downscaled hyper-resolution (400 m) gridded datasets of daily precipitation and temperature (2008–2019) for the East–Taylor subbasin (western United States)
HRLT: a high-resolution (1 d, 1 km) and long-term (1961–2019) gridded dataset for surface temperature and precipitation across China
RC4USCoast: A river chemistry dataset for regional ocean model applications in the U.S. East, Gulf of Mexico, and West Coasts
The Surface Water Chemistry (SWatCh) database: a standardized global database of water chemistry to facilitate large-sample hydrological research
Hydrography90m: a new high-resolution global hydrographic dataset
GLOBMAP SWF: a global annual surface water cover frequency dataset during 2000–2020
An ensemble of 48 physically perturbed model estimates of the 1/8° terrestrial water budget over the conterminous United States, 1980–2015
Streamflow data availability in Europe: a detailed dataset of interpolated flow-duration curves
High-resolution streamflow and weather data (2013–2019) for seven small coastal watersheds in the northeast Pacific coastal temperate rainforest, Canada
A 500-year annual runoff reconstruction for 14 selected European catchments
A comprehensive geospatial database of nearly 100 000 reservoirs in China
Stable water isotope monitoring network of different water bodies in Shiyang River basin, a typical arid river in China
A dataset of lake-catchment characteristics for the Tibetan Plateau
QUADICA: water QUAlity, DIscharge and Catchment Attributes for large-sample studies in Germany
A global terrestrial evapotranspiration product based on the three-temperature model with fewer input parameters and no calibration requirement
A new snow depth data set over northern China derived using GNSS interferometric reflectometry from a continuously operating network (GSnow-CHINA v1.0, 2013–2022)
Microwave radiometry experiment for snow in Altay, China: time series of in situ data for electromagnetic and physical features of snowpack
An integrated dataset of daily lake surface water temperature over the Tibetan Plateau
Meteorological and hydrological data from the Alder Creek watershed, SW Ontario
Daily soil moisture mapping at 1 km resolution based on SMAP data for desertification areas in northern China
High-temporal-resolution hydrometeorological data collected in the tropical Cordillera Blanca, Peru (2004–2020)
Escherichia coli concentration, multiscale monitoring over the decade 2011–2021 in the Mekong River basin, Lao PDR
A 1 km daily surface soil moisture dataset of enhanced coverage under all-weather conditions over China in 2003–2019
Soil moisture observation in a forested headwater catchment: combining a dense cosmic-ray neutron sensor network with roving and hydrogravimetry at the TERENO site Wüstebach
Concentrations and fluxes of suspended particulate matter and associated contaminants in the Rhône River from Lake Geneva to the Mediterranean Sea
A global drought dataset of standardized moisture anomaly index incorporating snow dynamics (SZIsnow) and its application in identifying large-scale drought events
River network and hydro-geomorphological parameters at 1∕12° resolution for global hydrological and climate studies
Integrated hydrogeological and hydrogeochemical dataset of an alpine catchment in the northern Qinghai–Tibet Plateau
GeoDAR: georeferenced global dams and reservoirs dataset for bridging attributes and geolocations
Spatial and seasonal patterns of water isotopes in northeastern German lakes
Yufang Zhang, Shunlin Liang, Han Ma, Tao He, Qian Wang, Bing Li, Jianglei Xu, Guodong Zhang, Xiaobang Liu, and Changhao Xiong
Earth Syst. Sci. Data, 15, 2055–2079, https://doi.org/10.5194/essd-15-2055-2023, https://doi.org/10.5194/essd-15-2055-2023, 2023
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Soil moisture observations are important for a range of earth system applications. This study generated a long-term (2000–2020) global seamless soil moisture product with both high spatial and temporal resolutions (1 km, daily) using an XGBoost model and multisource datasets. Evaluation of this product against dense in situ soil moisture datasets and microwave soil moisture products showed that this product has reliable accuracy and more complete spatial coverage.
Heidi Kreibich, Kai Schröter, Giuliano Di Baldassarre, Anne F. Van Loon, Maurizio Mazzoleni, Guta Wakbulcho Abeshu, Svetlana Agafonova, Amir AghaKouchak, Hafzullah Aksoy, Camila Alvarez-Garreton, Blanca Aznar, Laila Balkhi, Marlies H. Barendrecht, Sylvain Biancamaria, Liduin Bos-Burgering, Chris Bradley, Yus Budiyono, Wouter Buytaert, Lucinda Capewell, Hayley Carlson, Yonca Cavus, Anaïs Couasnon, Gemma Coxon, Ioannis Daliakopoulos, Marleen C. de Ruiter, Claire Delus, Mathilde Erfurt, Giuseppe Esposito, Didier François, Frédéric Frappart, Jim Freer, Natalia Frolova, Animesh K. Gain, Manolis Grillakis, Jordi Oriol Grima, Diego A. Guzmán, Laurie S. Huning, Monica Ionita, Maxim Kharlamov, Dao Nguyen Khoi, Natalie Kieboom, Maria Kireeva, Aristeidis Koutroulis, Waldo Lavado-Casimiro, Hong-Yi Li, Maria Carmen LLasat, David Macdonald, Johanna Mård, Hannah Mathew-Richards, Andrew McKenzie, Alfonso Mejia, Eduardo Mario Mendiondo, Marjolein Mens, Shifteh Mobini, Guilherme Samprogna Mohor, Viorica Nagavciuc, Thanh Ngo-Duc, Huynh Thi Thao Nguyen, Pham Thi Thao Nhi, Olga Petrucci, Nguyen Hong Quan, Pere Quintana-Seguí, Saman Razavi, Elena Ridolfi, Jannik Riegel, Md Shibly Sadik, Nivedita Sairam, Elisa Savelli, Alexey Sazonov, Sanjib Sharma, Johanna Sörensen, Felipe Augusto Arguello Souza, Kerstin Stahl, Max Steinhausen, Michael Stoelzle, Wiwiana Szalińska, Qiuhong Tang, Fuqiang Tian, Tamara Tokarczyk, Carolina Tovar, Thi Van Thu Tran, Marjolein H. J. van Huijgevoort, Michelle T. H. van Vliet, Sergiy Vorogushyn, Thorsten Wagener, Yueling Wang, Doris E. Wendt, Elliot Wickham, Long Yang, Mauricio Zambrano-Bigiarini, and Philip J. Ward
Earth Syst. Sci. Data, 15, 2009–2023, https://doi.org/10.5194/essd-15-2009-2023, https://doi.org/10.5194/essd-15-2009-2023, 2023
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As the adverse impacts of hydrological extremes increase in many regions of the world, a better understanding of the drivers of changes in risk and impacts is essential for effective flood and drought risk management. We present a dataset containing data of paired events, i.e. two floods or two droughts that occurred in the same area. The dataset enables comparative analyses and allows detailed context-specific assessments. Additionally, it supports the testing of socio-hydrological models.
Rogier van der Velde, Harm-Jan F. Benninga, Bas Retsios, Paul C. Vermunt, and M. Suhyb Salama
Earth Syst. Sci. Data, 15, 1889–1910, https://doi.org/10.5194/essd-15-1889-2023, https://doi.org/10.5194/essd-15-1889-2023, 2023
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From 2009, a network of 20 profile soil moisture and temperature monitoring stations has been operational in the Twente region, east of the Netherlands. In addition, field campaigns have been conducted covering four growing seasons during which soil moisture was measured near 12 monitoring stations. We describe the monitoring network and field campaigns, and we provide an overview of open third-party datasets that may support the use of the Twente datasets.
Jana Erdbrügger, Ilja van Meerveld, Jan Seibert, and Kevin Bishop
Earth Syst. Sci. Data, 15, 1779–1800, https://doi.org/10.5194/essd-15-1779-2023, https://doi.org/10.5194/essd-15-1779-2023, 2023
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Groundwater can respond quickly to precipitation and is the main source of streamflow in most catchments in humid, temperate climates. To better understand shallow groundwater dynamics, we installed a network of groundwater wells in two boreal headwater catchments in Sweden. We recorded groundwater levels in 75 wells for 2 years and sampled the water and analyzed its chemical composition in one summer. This paper describes these datasets.
Oliver Wigmore and Noah P. Molotch
Earth Syst. Sci. Data, 15, 1733–1747, https://doi.org/10.5194/essd-15-1733-2023, https://doi.org/10.5194/essd-15-1733-2023, 2023
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We flew a custom-built drone fitted with visible, near-infrared and thermal cameras every week over a summer season at Niwot Ridge in Colorado's alpine tundra. We processed these images into seamless orthomosaics that record changes in snow cover, vegetation health and the movement of water over the land surface. These novel datasets provide a unique centimetre resolution snapshot of ecohydrologic processes, connectivity and spatial and temporal heterogeneity in the alpine zone.
Martine Lizotte, Bennet Juhls, Atsushi Matsuoka, Philippe Massicotte, Gaëlle Mével, David Obie James Anikina, Sofia Antonova, Guislain Bécu, Marine Béguin, Simon Bélanger, Thomas Bossé-Demers, Lisa Bröder, Flavienne Bruyant, Gwénaëlle Chaillou, Jérôme Comte, Raoul-Marie Couture, Emmanuel Devred, Gabrièle Deslongchamps, Thibaud Dezutter, Miles Dillon, David Doxaran, Aude Flamand, Frank Fell, Joannie Ferland, Marie-Hélène Forget, Michael Fritz, Thomas J. Gordon, Caroline Guilmette, Andrea Hilborn, Rachel Hussherr, Charlotte Irish, Fabien Joux, Lauren Kipp, Audrey Laberge-Carignan, Hugues Lantuit, Edouard Leymarie, Antonio Mannino, Juliette Maury, Paul Overduin, Laurent Oziel, Colin Stedmon, Crystal Thomas, Lucas Tisserand, Jean-Éric Tremblay, Jorien Vonk, Dustin Whalen, and Marcel Babin
Earth Syst. Sci. Data, 15, 1617–1653, https://doi.org/10.5194/essd-15-1617-2023, https://doi.org/10.5194/essd-15-1617-2023, 2023
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Permafrost thaw in the Mackenzie Delta region results in the release of organic matter into the coastal marine environment. What happens to this carbon-rich organic matter as it transits along the fresh to salty aquatic environments is still underdocumented. Four expeditions were conducted from April to September 2019 in the coastal area of the Beaufort Sea to study the fate of organic matter. This paper describes a rich set of data characterizing the composition and sources of organic matter.
Doerthe Tetzlaff, Aaron Smith, Lukas Kleine, Hauke Daempfling, Jonas Freymueller, and Chris Soulsby
Earth Syst. Sci. Data, 15, 1543–1554, https://doi.org/10.5194/essd-15-1543-2023, https://doi.org/10.5194/essd-15-1543-2023, 2023
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We present a comprehensive set of ecohydrological hydrometric and stable water isotope data of 2 years of data. The data set is unique as the different compartments of the landscape were sampled and the effects of a prolonged drought (2018–2020) captured by a marked negative rainfall anomaly (the most severe regional drought of the 21st century). Thus, the data allow the drought effects on water storage, flux and age dynamics, and persistence of lowland landscapes to be investigated.
Jacopo Dari, Luca Brocca, Sara Modanesi, Christian Massari, Angelica Tarpanelli, Silvia Barbetta, Raphael Quast, Mariette Vreugdenhil, Vahid Freeman, Anaïs Barella-Ortiz, Pere Quintana-Seguí, David Bretreger, and Espen Volden
Earth Syst. Sci. Data, 15, 1555–1575, https://doi.org/10.5194/essd-15-1555-2023, https://doi.org/10.5194/essd-15-1555-2023, 2023
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Irrigation is the main source of global freshwater consumption. Despite this, a detailed knowledge of irrigation dynamics (i.e., timing, extent of irrigated areas, and amounts of water used) are generally lacking worldwide. Satellites represent a useful tool to fill this knowledge gap and monitor irrigation water from space. In this study, three regional-scale and high-resolution (1 and 6 km) products of irrigation amounts estimated by inverting the satellite soil moisture signals are presented.
Gifty Attiah, Homa Kheyrollah Pour, and K. Andrea Scott
Earth Syst. Sci. Data, 15, 1329–1355, https://doi.org/10.5194/essd-15-1329-2023, https://doi.org/10.5194/essd-15-1329-2023, 2023
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Lake surface temperature (LST) is a significant indicator of climate change and influences local weather and climate. This study developed a LST dataset retrieved from Landsat archives for 535 lakes across the North Slave Region, NWT, Canada. The data consist of individual NetCDF files for all observed days for each lake. The North Slave LST dataset will provide communities, scientists, and stakeholders with the changing spatiotemporal trends of LST for the past 38 years (1984–2021).
Aolin Jia, Shunlin Liang, Dongdong Wang, Lei Ma, Zhihao Wang, and Shuo Xu
Earth Syst. Sci. Data, 15, 869–895, https://doi.org/10.5194/essd-15-869-2023, https://doi.org/10.5194/essd-15-869-2023, 2023
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Satellites are now producing multiple global land surface temperature (LST) products; however, they suffer from data gaps caused by cloud cover, seriously restricting the applications, and few products provide gap-free global hourly LST. We produced global hourly, 5 km, all-sky LST data from 2011 to 2021 using geostationary and polar-orbiting satellite data. Based on the assessment, it has high accuracy and can be used to estimate evapotranspiration, drought, etc.
Jianxin Zhang, Kai Liu, and Ming Wang
Earth Syst. Sci. Data, 15, 521–540, https://doi.org/10.5194/essd-15-521-2023, https://doi.org/10.5194/essd-15-521-2023, 2023
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This study successfully extracted global flood days based on gravity satellite and precipitation data between 60° S and 60° N from 1 April 2002 to 31 August 2016. Our flood days data performed well compared with current available observations. This provides an important data foundation for analyzing the spatiotemporal distribution of large-scale floods and exploring the impact of ocean–atmosphere oscillations on floods in different regions.
Niek Jesse Speetjens, Gustaf Hugelius, Thomas Gumbricht, Hugues Lantuit, Wouter R. Berghuijs, Philip A. Pika, Amanda Poste, and Jorien E. Vonk
Earth Syst. Sci. Data, 15, 541–554, https://doi.org/10.5194/essd-15-541-2023, https://doi.org/10.5194/essd-15-541-2023, 2023
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The Arctic is rapidly changing. Outside the Arctic, large databases changed how researchers look at river systems and land-to-ocean processes. We present the first integrated pan-ARctic CAtchments summary DatabasE (ARCADE) (> 40 000 river catchments draining into the Arctic Ocean). It incorporates information about the drainage area with 103 geospatial, environmental, climatic, and physiographic properties and covers small watersheds , which are especially subject to change, at a high resolution
Ionut Cristi Nicu, Letizia Elia, Lena Rubensdotter, Hakan Tanyaş, and Luigi Lombardo
Earth Syst. Sci. Data, 15, 447–464, https://doi.org/10.5194/essd-15-447-2023, https://doi.org/10.5194/essd-15-447-2023, 2023
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Thaw slumps and thermo-erosion gullies are cryospheric hazards that are widely encountered in Nordenskiöld Land, the largest and most compact ice-free area of the Svalbard Archipelago. By statistically analysing the landscape characteristics of locations where these processes occurred, we can estimate where they may occur in the future. We mapped 562 thaw slumps and 908 thermo-erosion gullies and used them to create the first multi-hazard susceptibility map in a high-Arctic environment.
Alison L. Kay, Victoria A. Bell, Helen N. Davies, Rosanna A. Lane, and Alison C. Rudd
Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2022-439, https://doi.org/10.5194/essd-2022-439, 2023
Revised manuscript accepted for ESSD
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Climate change will affect the water cycle, including river flows and soil moisture. We have used both observational data (1980–2011) and the latest UK climate projections (1980–2080) to drive a national-scale grid-based hydrological model. The data, covering Great Britain and Northern Ireland, suggest potential future decreases in summer flows, low flows, and summer/autumn soil moisture, and possible future increases in winter and high flows. Society must plan how to adapt to such impacts.
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
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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).
Ibrahim Demir, Zhongrun Xiang, Bekir Demiray, and Muhammed Sit
Earth Syst. Sci. Data, 14, 5605–5616, https://doi.org/10.5194/essd-14-5605-2022, https://doi.org/10.5194/essd-14-5605-2022, 2022
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We provide a large benchmark dataset, WaterBench-Iowa, with valuable features for hydrological modeling. This dataset is designed to support cutting-edge deep learning studies for a more accurate streamflow forecast model. We also propose a modeling task for comparative model studies and provide sample models with codes and results as the benchmark for reference. This makes up for the lack of benchmarks in earth science research.
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 Discuss., https://doi.org/10.5194/essd-2022-376, https://doi.org/10.5194/essd-2022-376, 2022
Preprint under review for ESSD
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The surface water storage (SWS) in the Congo basin (CB) remains unknown. In this study, the multi-satellite and hypsometric curve approaches are used to estimate SWS at the CB over 1992–2015. The results provide monthly SWS characterized by a 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.
Pei Zhang, Donghai Zheng, Rogier van der Velde, Jun Wen, Yaoming Ma, Yijian Zeng, Xin Wang, Zuoliang Wang, Jiali Chen, and Zhongbo Su
Earth Syst. Sci. Data, 14, 5513–5542, https://doi.org/10.5194/essd-14-5513-2022, https://doi.org/10.5194/essd-14-5513-2022, 2022
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Soil moisture and soil temperature (SMST) are important state variables for quantifying the heat–water exchange between land and atmosphere. Yet, long-term, regional-scale in situ SMST measurements at multiple depths are scarce on the Tibetan Plateau (TP). The presented dataset would be valuable for the evaluation and improvement of long-term satellite- and model-based SMST products on the TP, enhancing the understanding of TP hydrometeorological processes and their response to climate change.
Jafet C. M. Andersson, Jonas Olsson, Remco (C. Z.) van de Beek, and Jonas Hansryd
Earth Syst. Sci. Data, 14, 5411–5426, https://doi.org/10.5194/essd-14-5411-2022, https://doi.org/10.5194/essd-14-5411-2022, 2022
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This article presents data from three types of sensors for rain measurement, i.e. commercial microwave links (CMLs), gauges, and weather radar. Access to CML data is typically restricted, which limits research and applications. We openly share a large CML database (364 CMLs at 10 s resolution with true coordinates), along with 11 gauges and one radar composite. This opens up new opportunities to study CMLs, to benchmark algorithms, and to investigate how multiple sensors can best be combined.
Qingliang Li, Gaosong Shi, Wei Shangguan, Vahid Nourani, Jianduo Li, Lu Li, Feini Huang, Ye Zhang, Chunyan Wang, Dagang Wang, Jianxiu Qiu, Xingjie Lu, and Yongjiu Dai
Earth Syst. Sci. Data, 14, 5267–5286, https://doi.org/10.5194/essd-14-5267-2022, https://doi.org/10.5194/essd-14-5267-2022, 2022
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SMCI1.0 is a 1 km resolution dataset of daily soil moisture over China for 2000–2020 derived through machine learning trained with in situ measurements of 1789 stations, meteorological forcings, and land surface variables. It contains 10 soil layers with 10 cm intervals up to 100 cm deep. Evaluated by in situ data, the error (ubRMSE) ranges from 0.045 to 0.051, and the correlation (R) range is 0.866-0.893. Compared with ERA5-Land, SMAP-L4, and SoMo.ml, SIMI1.0 has higher accuracy and resolution.
Utkarsh Mital, Dipankar Dwivedi, James B. Brown, and Carl I. Steefel
Earth Syst. Sci. Data, 14, 4949–4966, https://doi.org/10.5194/essd-14-4949-2022, https://doi.org/10.5194/essd-14-4949-2022, 2022
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We present a new dataset that estimates small-scale variations in precipitation and temperature in mountainous terrain. The dataset is generated using a new machine learning framework that extracts relationships between climate and topography from existing coarse-scale datasets. The generated dataset is shown to capture small-scale variations more reliably than existing datasets and constitutes a valuable resource to model the water cycle in the mountains of Colorado, western United States.
Rongzhu Qin, Zeyu Zhao, Jia Xu, Jian-Sheng Ye, Feng-Min Li, and Feng Zhang
Earth Syst. Sci. Data, 14, 4793–4810, https://doi.org/10.5194/essd-14-4793-2022, https://doi.org/10.5194/essd-14-4793-2022, 2022
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This work presents a new high-resolution daily gridded maximum temperature, minimum temperature, and precipitation dataset for China (HRLT) with a spatial resolution of 1 × 1 km for the period 1961 to 2019. This dataset is valuable for crop modelers and climate change studies. We created the HRLT dataset using comprehensive statistical analyses, which included machine learning, the generalized additive model, and thin-plate splines.
Fabian A. Gomez, Sang-Ki Lee, Charles A. Stock, Andrew C. Ross, Laure Resplandy, Samantha A. Siedlecki, Filippos Tagklis, and Joseph E. Salisbury
Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2022-341, https://doi.org/10.5194/essd-2022-341, 2022
Revised manuscript accepted for ESSD
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We present a river chemistry and discharge dataset for 140 rivers in the United States, which integrates information from the Water Quality Database of the U.S. Geological Survey (USGS), the USGS’s Surface-Water Monthly Statistics for the Nation, and the U.S. Army Corps of Engineers. This dataset includes dissolved inorganic carbon and alkalinity, two key properties to characterize the carbonate system, as well as nutrient concentration, such as nitrate and phosphate, and silica.
Lobke Rotteveel, Franz Heubach, and Shannon M. Sterling
Earth Syst. Sci. Data, 14, 4667–4680, https://doi.org/10.5194/essd-14-4667-2022, https://doi.org/10.5194/essd-14-4667-2022, 2022
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Data are needed to detect environmental problems, find their solutions, and identify knowledge gaps. Existing datasets have limited availability, sample size and/or frequency, or geographic scope. Here, we begin to address these limitations by collecting, cleaning, standardizing, and compiling the Surface Water Chemistry (SWatCh) database. SWatCh contains global surface water chemistry data for seven continents, 24 variables, 33 722 sites, and > 5 million samples collected between 1960 and 2022.
Giuseppe Amatulli, Jaime Garcia Marquez, Tushar Sethi, Jens Kiesel, Afroditi Grigoropoulou, Maria M. Üblacker, Longzhu Q. Shen, and Sami Domisch
Earth Syst. Sci. Data, 14, 4525–4550, https://doi.org/10.5194/essd-14-4525-2022, https://doi.org/10.5194/essd-14-4525-2022, 2022
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Streams and rivers drive several processes in hydrology, geomorphology, geography, and ecology. A hydrographic network that accurately delineates streams and rivers, along with their topographic and topological properties, is needed for environmental applications. Using the MERIT Hydro Digital Elevation Model at 90 m resolution, we derived a globally seamless, standardised hydrographic network: Hydrography90m. The validation demonstrates improved accuracy compared to other datasets.
Yang Liu, Ronggao Liu, and Rong Shang
Earth Syst. Sci. Data, 14, 4505–4523, https://doi.org/10.5194/essd-14-4505-2022, https://doi.org/10.5194/essd-14-4505-2022, 2022
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Surface water has been changing significantly with high seasonal variation and abrupt change, making it hard to capture its interannual trend. Here we generated a global annual surface water cover frequency dataset during 2000–2020. The percentage of the time period when a pixel is covered by water in a year was estimated to describe the seasonal dynamics of surface water. This dataset can be used to analyze the interannual variation and change trend of highly dynamic inland water extent.
Hui Zheng, Wenli Fei, Zong-Liang Yang, Jiangfeng Wei, Long Zhao, and Lingcheng Li
Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2022-133, https://doi.org/10.5194/essd-2022-133, 2022
Revised manuscript accepted for ESSD
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The information on evapotranspiration, runoff, and water storage in groundwater, snow, and soil is useful for monitoring and understanding the variability of water resources. An ensemble of spatially continuous estimates is generated here using a land surface model with consideration of the uncertainty associated with the model formulation.
Simone Persiano, Alessio Pugliese, Alberto Aloe, Jon Olav Skøien, Attilio Castellarin, and Alberto Pistocchi
Earth Syst. Sci. Data, 14, 4435–4443, https://doi.org/10.5194/essd-14-4435-2022, https://doi.org/10.5194/essd-14-4435-2022, 2022
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For about 24000 river basins across Europe, this study provides a continuous representation of the streamflow regime in terms of empirical flow–duration curves (FDCs), which are key signatures of the hydrological behaviour of a catchment and are widely used for supporting decisions on water resource management as well as for assessing hydrologic change. FDCs at ungauged sites are estimated by means of a geostatistical procedure starting from data observed at about 3000 sites across Europe.
Maartje C. Korver, Emily Haughton, William C. Floyd, and Ian J. W. Giesbrecht
Earth Syst. Sci. Data, 14, 4231–4250, https://doi.org/10.5194/essd-14-4231-2022, https://doi.org/10.5194/essd-14-4231-2022, 2022
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The central coastline of the northeast Pacific coastal temperate rainforest contains many small streams that are important for the ecology of the region but are sparsely monitored. Here we present the first 5 years (2013–2019) of streamflow and weather data from seven small streams, using novel automated methods with estimations of measurement uncertainties. These observations support regional climate change monitoring and provide a scientific basis for environmental management decisions.
Sadaf Nasreen, Markéta Součková, Mijael Rodrigo Vargas Godoy, Ujjwal Singh, Yannis Markonis, Rohini Kumar, Oldrich Rakovec, and Martin Hanel
Earth Syst. Sci. Data, 14, 4035–4056, https://doi.org/10.5194/essd-14-4035-2022, https://doi.org/10.5194/essd-14-4035-2022, 2022
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This article presents a 500-year reconstructed annual runoff dataset for several European catchments. Several data-driven and hydrological models were used to derive the runoff series using reconstructed precipitation and temperature and a set of proxy data. The simulated runoff was validated using independent observed runoff data and documentary evidence. The validation revealed a good fit between the observed and reconstructed series for 14 catchments, which are available for further analysis.
Chunqiao Song, Chenyu Fan, Jingying Zhu, Jida Wang, Yongwei Sheng, Kai Liu, Tan Chen, Pengfei Zhan, Shuangxiao Luo, Chunyu Yuan, and Linghong Ke
Earth Syst. Sci. Data, 14, 4017–4034, https://doi.org/10.5194/essd-14-4017-2022, https://doi.org/10.5194/essd-14-4017-2022, 2022
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Over the last century, many dams/reservoirs have been built globally to meet various needs. The official statistics reported more than 98 000 dams/reservoirs in China. Despite the availability of several global-scale dam/reservoir databases, these databases have insufficient coverage in China. Therefore, we present the China Reservoir Dataset (CRD), which contains 97 435 reservoir polygons. The CRD reservoirs have a total area of 50 085.21 km2 and total storage of about 979.62 Gt.
Guofeng Zhu, Yuwei Liu, Peiji Shi, Wenxiong Jia, Junju Zhou, Yuanfeng Liu, Xinggang Ma, Hanxiong Pan, Yu Zhang, Zhiyuan Zhang, Zhigang Sun, Leilei Yong, and Kailiang Zhao
Earth Syst. Sci. Data, 14, 3773–3789, https://doi.org/10.5194/essd-14-3773-2022, https://doi.org/10.5194/essd-14-3773-2022, 2022
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From 2015 to 2020, we studied the Shiyang River basin, which has the highest utilization rate of water resources and the most prominent contradiction of water use, as a typical demonstration basin to establish and improve the isotope hydrology observation system, including river source region, oasis region, reservoir channel system region, oasis farmland region, ecological engineering construction region, and salinization process region.
Junzhi Liu, Pengcheng Fang, Yefeng Que, Liang-Jun Zhu, Zheng Duan, Guoan Tang, Pengfei Liu, Mukan Ji, and Yongqin Liu
Earth Syst. Sci. Data, 14, 3791–3805, https://doi.org/10.5194/essd-14-3791-2022, https://doi.org/10.5194/essd-14-3791-2022, 2022
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The management and conservation of lakes should be conducted in the context of catchments because lakes collect water and materials from their upstream catchments. This study constructed the first dataset of lake-catchment characteristics for 1525 lakes with an area from 0.2 to 4503 km2 on the Tibetan Plateau (TP), which provides exciting opportunities for lake studies in a spatially explicit context and promotes the development of landscape limnology on the TP.
Pia Ebeling, Rohini Kumar, Stefanie R. Lutz, Tam Nguyen, Fanny Sarrazin, Michael Weber, Olaf Büttner, Sabine Attinger, and Andreas Musolff
Earth Syst. Sci. Data, 14, 3715–3741, https://doi.org/10.5194/essd-14-3715-2022, https://doi.org/10.5194/essd-14-3715-2022, 2022
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Environmental data are critical for understanding and managing ecosystems, including the mitigation of water quality degradation. To increase data availability, we present the first large-sample water quality data set (QUADICA) of riverine macronutrient concentrations combined with water quantity, meteorological, and nutrient forcing data as well as catchment attributes. QUADICA covers 1386 German catchments to facilitate large-sample data-driven and modeling water quality assessments.
Leiyu Yu, Guo Yu Qiu, Chunhua Yan, Wenli Zhao, Zhendong Zou, Jinshan Ding, Longjun Qin, and Yujiu Xiong
Earth Syst. Sci. Data, 14, 3673–3693, https://doi.org/10.5194/essd-14-3673-2022, https://doi.org/10.5194/essd-14-3673-2022, 2022
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Accurate evapotranspiration (ET) estimation is essential to better understand Earth’s energy and water cycles. We estimate global terrestrial ET with a simple three-temperature model, without calibration and resistance parameterization requirements. Results show the ET estimates agree well with FLUXNET EC data, water balance ET, and other global ET products. The proposed daily and 0.25° ET product from 2001 to 2020 could provide large-scale information to support water-cycle-related studies.
Wei Wan, Jie Zhang, Liyun Dai, Hong Liang, Ting Yang, Baojian Liu, Zhizhou Guo, Heng Hu, and Limin Zhao
Earth Syst. Sci. Data, 14, 3549–3571, https://doi.org/10.5194/essd-14-3549-2022, https://doi.org/10.5194/essd-14-3549-2022, 2022
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The GSnow-CHINA data set is a snow depth data set developed using the two Global Navigation Satellite System station networks in China. It includes snow depth of 24, 12, and 2/3/6 h records, if possible, for 80 sites from 2013–2022 over northern China (25–55° N, 70–140° E). The footprint of the data set is ~ 1000 m2, and it can be used as an independent data source for validation purposes. It is also useful for regional climate research and other meteorological and hydrological applications.
Liyun Dai, Tao Che, Yang Zhang, Zhiguo Ren, Junlei Tan, Meerzhan Akynbekkyzy, Lin Xiao, Shengnan Zhou, Yuna Yan, Yan Liu, Hongyi Li, and Lifu Wang
Earth Syst. Sci. Data, 14, 3509–3530, https://doi.org/10.5194/essd-14-3509-2022, https://doi.org/10.5194/essd-14-3509-2022, 2022
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An Integrated Microwave Radiometry Campaign for Snow (IMCS) was conducted to collect ground-based passive microwave and optical remote-sensing data, snow pit and underlying soil data, and meteorological parameters. The dataset is unique in continuously providing electromagnetic and physical features of snowpack and environment. The dataset is expected to serve the evaluation and development of microwave radiative transfer models and snow process models, along with land surface process models.
Linan Guo, Hongxing Zheng, Yanhong Wu, Lanxin Fan, Mengxuan Wen, Junsheng Li, Fangfang Zhang, Liping Zhu, and Bing Zhang
Earth Syst. Sci. Data, 14, 3411–3422, https://doi.org/10.5194/essd-14-3411-2022, https://doi.org/10.5194/essd-14-3411-2022, 2022
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Lake surface water temperature (LSWT) is a critical physical property of the aquatic ecosystem and an indicator of climate change. By combining the strengths of satellites and models, we produced an integrated dataset on daily LSWT of 160 large lakes across the Tibetan Plateau (TP) for the period 1978–2017. LSWT increased significantly at a rate of 0.01–0.47° per 10 years. The dataset can contribute to research on water and heat balance changes and their ecological effects in the TP.
Andrew J. Wiebe and David L. Rudolph
Earth Syst. Sci. Data, 14, 3229–3248, https://doi.org/10.5194/essd-14-3229-2022, https://doi.org/10.5194/essd-14-3229-2022, 2022
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Multiple well fields in Waterloo Region, ON, Canada, draw water that enters the groundwater system from rainfall and snowmelt within the Alder Creek watershed. The rates of recharge of the underground aquifers and human impacts on streamflow are important issues that are typically addressed using computer models. Field observations such as groundwater and stream levels were collected between 2013 and 2018 to provide data for models. The data are available at https://doi.org/10.20383/101.0178
Pinzeng Rao, Yicheng Wang, Fang Wang, Yang Liu, Xiaoya Wang, and Zhu Wang
Earth Syst. Sci. Data, 14, 3053–3073, https://doi.org/10.5194/essd-14-3053-2022, https://doi.org/10.5194/essd-14-3053-2022, 2022
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It is urgent to obtain accurate soil moisture (SM) with high temporal and spatial resolution for areas affected by desertification in northern China. A combination of multiple machine learning methods, including multiple linear regression, support vector regression, artificial neural networks, random forest and extreme gradient boosting, has been applied to downscale the 36 km SMAP SM products and produce higher-spatial-resolution SM data based on related surface variables.
Emilio I. Mateo, Bryan G. Mark, Robert Å. Hellström, Michel Baraer, Jeffrey M. McKenzie, Thomas Condom, Alejo Cochachín Rapre, Gilber Gonzales, Joe Quijano Gómez, and Rolando Cesai Crúz Encarnación
Earth Syst. Sci. Data, 14, 2865–2882, https://doi.org/10.5194/essd-14-2865-2022, https://doi.org/10.5194/essd-14-2865-2022, 2022
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This article presents detailed and comprehensive hydrological and meteorological datasets collected over the past two decades throughout the Cordillera Blanca, Peru. With four weather stations and six streamflow gauges ranging from 3738 to 4750 m above sea level, this network displays a vertical breadth of data and enables detailed research of atmospheric and hydrological processes in a tropical high mountain region.
Laurie Boithias, Olivier Ribolzi, Emma Rochelle-Newall, Chanthanousone Thammahacksa, Paty Nakhle, Bounsamay Soulileuth, Anne Pando-Bahuon, Keooudone Latsachack, Norbert Silvera, Phabvilay Sounyafong, Khampaseuth Xayyathip, Rosalie Zimmermann, Sayaphet Rattanavong, Priscia Oliva, Thomas Pommier, Olivier Evrard, Sylvain Huon, Jean Causse, Thierry Henry-des-Tureaux, Oloth Sengtaheuanghoung, Nivong Sipaseuth, and Alain Pierret
Earth Syst. Sci. Data, 14, 2883–2894, https://doi.org/10.5194/essd-14-2883-2022, https://doi.org/10.5194/essd-14-2883-2022, 2022
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Fecal pathogens in surface waters may threaten human health, especially in developing countries. The Escherichia coli (E. coli) database is organized in three datasets and includes 1602 records from 31 sampling stations located within the Mekong River basin in Lao PDR. Data have been used to identify the drivers of E. coli dissemination across tropical catchments, including during floods. Data may be further used to interpret new variables or to map the health risk posed by fecal pathogens.
Peilin Song, Yongqiang Zhang, Jianping Guo, Jiancheng Shi, Tianjie Zhao, and Bing Tong
Earth Syst. Sci. Data, 14, 2613–2637, https://doi.org/10.5194/essd-14-2613-2022, https://doi.org/10.5194/essd-14-2613-2022, 2022
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Soil moisture information is crucial for understanding the earth surface, but currently available satellite-based soil moisture datasets are imperfect either in their spatiotemporal resolutions or in ensuring image completeness from cloudy weather. In this study, therefore, we developed one soil moisture data product over China that has tackled most of the above problems. This data product has the potential to promote the investigation of earth hydrology and be extended to the global scale.
Maik Heistermann, Heye Bogena, Till Francke, Andreas Güntner, Jannis Jakobi, Daniel Rasche, Martin Schrön, Veronika Döpper, Benjamin Fersch, Jannis Groh, Amol Patil, Thomas Pütz, Marvin Reich, Steffen Zacharias, Carmen Zengerle, and Sascha Oswald
Earth Syst. Sci. Data, 14, 2501–2519, https://doi.org/10.5194/essd-14-2501-2022, https://doi.org/10.5194/essd-14-2501-2022, 2022
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This paper presents a dense network of cosmic-ray neutron sensing (CRNS) to measure spatio-temporal soil moisture patterns during a 2-month campaign in the Wüstebach headwater catchment in Germany. Stationary, mobile, and airborne CRNS technology monitored the root-zone water dynamics as well as spatial heterogeneity in the 0.4 km2 area. The 15 CRNS stations were supported by a hydrogravimeter, biomass sampling, and a wireless soil sensor network to facilitate holistic hydrological analysis.
Hugo Lepage, Alexandra Gruat, Fabien Thollet, Jérôme Le Coz, Marina Coquery, Matthieu Masson, Aymeric Dabrin, Olivier Radakovitch, Jérôme Labille, Jean-Paul Ambrosi, Doriane Delanghe, and Patrick Raimbault
Earth Syst. Sci. Data, 14, 2369–2384, https://doi.org/10.5194/essd-14-2369-2022, https://doi.org/10.5194/essd-14-2369-2022, 2022
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The dataset contains concentrations and fluxes of suspended particle matter (SPM) and several particle-bound contaminants along the Rhône River downstream of Lake Geneva. These data allow us to understand the dynamics and origins. They show the impact of flood events which mainly contribute to a decrease in the contaminant concentrations while fluxes are significant. On the contrary, concentrations are higher during low flow periods probably due to the increase of organic matter.
Lei Tian, Baoqing Zhang, and Pute Wu
Earth Syst. Sci. Data, 14, 2259–2278, https://doi.org/10.5194/essd-14-2259-2022, https://doi.org/10.5194/essd-14-2259-2022, 2022
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We propose a global monthly drought dataset with a resolution of 0.25° from 1948 to 2010 based on a multitype and multiscalar drought index, the standardized moisture anomaly index adding snow processes (SZIsnow). The consideration of snow processes improved its capability, and the improvement is prominent over snow-covered high-latitude and high-altitude areas. This new dataset is well suited to monitoring, assessing, and characterizing drought and is a valuable resource for drought studies.
Simon Munier and Bertrand Decharme
Earth Syst. Sci. Data, 14, 2239–2258, https://doi.org/10.5194/essd-14-2239-2022, https://doi.org/10.5194/essd-14-2239-2022, 2022
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This paper presents a new global-scale river network at 1/12°, generated automatically and assessed over the 69 largest basins of the world. A set of hydro-geomorphological parameters are derived at the same spatial resolution, including a description of river stretches (length, slope, width, roughness, bankfull depth), floodplains (roughness, sub-grid topography) and aquifers (transmissivity, porosity, sub-grid topography). The dataset may be useful for hydrology modelling or climate studies.
Zhao Pan, Rui Ma, Ziyong Sun, Yalu Hu, Qixin Chang, Mengyan Ge, Shuo Wang, Jianwei Bu, Xiang Long, Yanxi Pan, and Lusong Zhao
Earth Syst. Sci. Data, 14, 2147–2165, https://doi.org/10.5194/essd-14-2147-2022, https://doi.org/10.5194/essd-14-2147-2022, 2022
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We drilled four sets of cluster wells and monitored groundwater level and temperature at different depths in an alpine catchment, northern Tibet plateau. The chemical and isotopic compositions of different waters, including stream water, glacier/snow meltwater, soil water, spring, and groundwater from boreholes, were measured for 6 years. The data can be used to study the impact of soil freeze-thaw process and permafrost degradation on the groundwater flow and its interaction with surface water.
Jida Wang, Blake A. Walter, Fangfang Yao, Chunqiao Song, Meng Ding, Abu Sayeed Maroof, Jingying Zhu, Chenyu Fan, Jordan M. McAlister, Safat Sikder, Yongwei Sheng, George H. Allen, Jean-François Crétaux, and Yoshihide Wada
Earth Syst. Sci. Data, 14, 1869–1899, https://doi.org/10.5194/essd-14-1869-2022, https://doi.org/10.5194/essd-14-1869-2022, 2022
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Improved water infrastructure data on dams and reservoirs remain to be critical to hydrologic modeling, energy planning, and environmental conservation. We present a new global dataset, GeoDAR, that includes nearly 25 000 georeferenced dam points and their associated reservoir boundaries. A majority of these features can be linked to the register of the International Commission on Large Dams, extending the potential of registered attribute information for spatially explicit applications.
Bernhard Aichner, David Dubbert, Christine Kiel, Katrin Kohnert, Igor Ogashawara, Andreas Jechow, Sarah-Faye Harpenslager, Franz Hölker, Jens Christian Nejstgaard, Hans-Peter Grossart, Gabriel Singer, Sabine Wollrab, and Stella Angela Berger
Earth Syst. Sci. Data, 14, 1857–1867, https://doi.org/10.5194/essd-14-1857-2022, https://doi.org/10.5194/essd-14-1857-2022, 2022
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Water isotopes were measured along transects and in the form of time series in northeastern German lakes. The spatial patterns within the data and their seasonal variability are related to morphological and hydrological properties of the studied lake systems. They are further useful for the understanding of biogeochemical and ecological characteristics of these lakes.
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Short summary
Time-series indices characterizing streamflow at annual, seasonal and monthly resolution at more than 30 000 stations around the world are presented. The data belong to the Global Streamflow and Metadata Archive (GSIM) and allow for an assessment of water balance components, hydrological extremes and the seasonality of water availability. The quality of the data is tested using automated methods to aid potential users to gauge the suitability of the data for specific applications.
Time-series indices characterizing streamflow at annual, seasonal and monthly resolution at more...
