ISIMIP3a Simulation Data from the Global Water Sector

Cite as

Simon N. Gosling, Hannes Müller Schmied, Anna Bradley, Peter Burek, Jinfeng Chang, Philippe Ciais, Manolis Grillakis, Luca Guillaumot, Naota Hanasaki, Andrew Hartley, Huilin Huang, Sian Kou-Giesbrecht, Aristeidis Koutroulis, Sebastian Ostberg, Kedar Otta, Wei Qi, Yusuke Satoh, Tobias Stacke, Qing Zhu, Jacob Schewe (2025): ISIMIP3a Simulation Data from the Global Water Sector (v1.6). ISIMIP Repository. https://doi.org/10.48364/ISIMIP.398165.6

Metadata

DOI:
https://doi.org/10.48364/ISIMIP.398165.6
Title:
ISIMIP3a Simulation Data from the Global Water Sector
Version:
1.6
Creators:
Contact person:

For inquiries concerning this dataset, please contact info@isimip.org.

Abstract:

This dataset contains ISIMIP3a (www.isimip.org, Frieler et al. 2023) simulation data from 9 global water models: CLASSIC (Melton et al. 2020), CWatM (Burek et al. 2020), ELM-ECA (Zhu et al. 2019), H08 (Hanasaki et al. 2017, Yoshida et al. 2021), HydroPy (Stacke et al. 2021), JULES-ES-VN6P3 (), JULES-W2, JULES-W2-DDM30, LPJmL5-7-10-fire (Wirth et al. 2024, Oberhagemann et al. 2024), MIROC-INTEG-LAND (Yokohata et al. 2020, Pokhrel et al. 2014, Takata et al. 2003), ORCHIDEE-MICT, SSiB4-TRIFFID-Fire (Huang et al. 2020, Huang et al. 2021, https://github.com/hhllbao93/SSiB4-TRIFFID-Fire), VISIT (Ito et al. 2018), WaterGAP2-2e (Müller Schmied et al. 2021) and WEB-DHM-SG (Qi et al. 2022, Wang et al. 2009, Qi et al. 2019, Qi et al. 2020, Qi et al. 2022)

The outputs are based on simulations according to the ISIMIP3a protocol (https://protocol.isimip.org). A more detailed description of the models are available on https://www.isimip.org.

Version 1.1 of this dataset adds data from ELM-ECA and additional variables for WaterGAP2-2e, and solves an issue with MIROC-INTEG-LAND (#40).

Version 1.2 of this dataset updates evaporation data from CWatM (#57).

Version 1.3 of this dataset adds the models JULES-ES-VN6P3, ORCHIDEE-MICT, SSiB4-TRIFFID-Fire, and VISIT as well as some additional files for ELM-ECA and H08.

Version 1.4 of this dataset adds the WEB-DHM-SG model.

Version 1.5 of this dataset adds the LPJmL5-7-10-fire model and more climate forcings for CWatM.

Version 1.6 of this dataset fixes an issue with airrusegreen and pirrusegreen files from LPJmL5-7-10-fire.

Publication date:
July 1, 2025
Publisher:
ISIMIP Repository
Contributors:

Here we list the persons and organizations, who are responsible for the collection, the management, and the publication of this dataset.

Rights

The datasets for this DOI are published under different usage rights (please check the license statement for each dataset):
CC0 1.0 Universal Public Domain Dedication
CC0 1.0 Universal Public Domain Dedication (CC0 1.0)
Attribution 4.0 International
Attribution 4.0 International (CC BY 4.0)
When using ISIMIP data for your research, please appropriately credit the data providers, e.g. either by citing the DOI for the dataset, or by appropriate acknowledgment. We strongly encourage to offer co-authorship to at least a representative of the data providers. Further information can be found in our terms of use.

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References

  • Wirth S, Braun J, Heinke J, Ostberg S, Rolinski S, Schaphoff S, Stenzel F, von Bloh W, Müller C, Taube F et al. Biological nitrogen fixation of natural and agricultural vegetation simulated with LPJmL 5.7.9. GMD, 17, 7889–7914, 2024. https://doi.org/10.5194/gmd-17-7889-2024
  • Oberhagemann L, Billing M, von Bloh W, Drüke M, Forrest M, Bowring S, Hetzer J, Ribalaygua Batalla J, Thonicke K et al. Sources of Uncertainty in the Global Fire Model SPITFIRE: Development of LPJmL-SPITFIRE1.9 and Directions for Future Improvements. EGUsphere [preprint], None, 2024. https://doi.org/10.5194/egusphere-2024-1914
  • Best M, Pryor M, Clark D, Rooney G, Essery R, Ménard C, Edwards J, Hendry M, Porson A, Gedney N, Mercado L, Sitch S, Blyth E, Boucher O, Cox P, Grimmond C, Harding R et al. The Joint UK Land Environment Simulator (JULES), model description – Part 1: Energy and water fluxes. Geoscientific Model Development, 4, 677-699, 2011. https://doi.org/10.5194/gmd-4-677-2011
  • Burek P, Satoh Y, Kahil T, Tang T, Greve P, Smilovic M, Guillaumot L, Zhao F, Wada Y et al. Development of the Community Water Model (CWatM v1.04) – a high-resolution hydrological model for global and regional assessment of integrated water resources management. Geoscientific Model Development, 13, 3267-3298, 2020. https://doi.org/10.5194/gmd-13-3267-2020
  • Clark, D. B., Mercado, L. M., Sitch, S., Jones, C. D., Gedney, N., Best, M. J., Pryor, M., Rooney, G. G., Essery, R. L. H., Blyth, E., Boucher, O., Harding, R. J., Huntingford, C., and Cox, P. M. et al. The Joint UK Land Environment Simulator (JULES), model description – Part 2: Carbon fluxes and vegetation dynamics. Geoscientific Model Development, 4, 701–722, 2011. https://doi.org/10.5194/gmd-4-701-2011
  • Huang, H., Xue, Y., Li, F., and Liu, Y. et al. Modeling long-term fire impact on ecosystem characteristics and surface energy using a process-based vegetation–fire model SSiB4/TRIFFID-Fire v1.0. Geosci. Model Dev., 13, 6029–6050, 2020. https://doi.org/10.5194/gmd-13-6029-2020
  • Huilin Huang, Yongkang Xue, Ye Liu, Fang Li, and Gregory S. Okin et al. Modeling the short-term fire effects on vegetation dynamics and surface energy in southern Africa using the improved SSiB4/TRIFFID-Fire model. Geosci. Model Dev., None, 2021. https://doi.org/10.5194/gmd-14-7639-2021
  • Joe R. Melton, Vivek K. Arora, Eduard Wisernig-Cojoc, Christian Seiler, Matthew Fortier, Ed Chan, and Lina Teckentrup et al. CLASSIC v1.0: the open-source community successor to the Canadian Land Surface Scheme (CLASS) and the Canadian Terrestrial Ecosystem Model (CTEM) – Part 1: Model framework and site-level performance. Geoscientific Model Development, 13, 2825–2850, 2020. https://doi.org/10.5194/gmd-13-2825-2020
  • Müller Schmied, H., Trautmann, T., Ackermann, S., Cáceres, D., Flörke, M., Gerdener, H., Kynast, E., Peiris, T. A., Schiebener, L., Schumacher, M., and Döll, P.: The global water resources and use model WaterGAP v2.2e: description and evaluation of modifications and new features, Geosci. Model Dev. Discuss. [preprint], https://doi.org/10.5194/gmd-2023-213, in review, 2023.
  • Pokhrel Y, Koirala S, Yeh P, Hanasaki N, Longuevergne L, Kanae S, Oki T et al. Incorporation of groundwater pumping in a global Land Surface Model with the representation of human impacts. Water Resources Research, 51, 78-96, 2014. https://doi.org/10.1002/2014wr015602
  • Qi W, Feng L, Kuang X, Zheng C, Liu J, Chen D, Tian Y, Yao Y et al. Divergent and Changing Importance of Glaciers and Snow as Natural Water Reservoirs in the Eastern and Southern Tibetan Plateau. Journal of Geophysical Research: Atmospheres, 127, 2022. https://doi.org/10.1029/2021jd035888
  • Qi W, Feng L, Liu J, Yang H et al. Snow as an Important Natural Reservoir for Runoff and Soil Moisture in Northeast China. Journal of Geophysical Research: Atmospheres, 125, 2020. https://doi.org/10.1029/2020jd033086
  • Qi W, Feng L, Yang H, Liu J, Zheng Y, Shi H, Wang L, Chen D et al. Economic growth dominates rising potential flood risk in the Yangtze River and benefits of raising dikes from 1991 to 2015. Environmental Research Letters, 17, 034046, 2022. https://doi.org/10.1088/1748-9326/ac5561
  • Qi W, Liu J, Leung F et al. A framework to quantify impacts of elevated CO2 concentration, global warming and leaf area changes on seasonal variations of water resources on a river basin scale. Journal of Hydrology, 570, 508-522, 2019. https://doi.org/10.1016/j.jhydrol.2019.01.015
  • Takata K, Emori S, Watanabe T et al. Development of the minimal advanced treatments of surface interaction and runoff. Global and Planetary Change, 38, 209-222, 2003. https://doi.org/10.1016/s0921-8181(03)00030-4
  • Tobias Stacke & Stefan Hagemann et al. HydroPy (v1.0): A new global hydrology model written in Python. Geosci. Model Dev., 14, 7795–7816, 2021. https://doi.org/10.5194/gmd-14-7795-2021
  • Tokuta Yokohata et al. MIROC-INTEG-LAND version 1: a global biogeochemical land surface model with human water management, crop growth, and land-use change. Geosci. Model Dev., 13, 4713–4747, 2020. https://doi.org/10.5194/gmd-13-4713-2020
  • Wang L, Koike T, Yang K, Jackson T, Bindlish R, Yang D et al. Development of a distributed biosphere hydrological model and its evaluation with the Southern Great Plains Experiments (SGP97 and SGP99). Journal of Geophysical Research, 114, 2009. https://doi.org/10.1029/2008jd010800
  • Yoshida T, Hanasaki N, Nishina K, Boulange J, Okada M, Troch P et al. Inference of parameters for a global hydrological model by applying Approximate Bayesian Computation: Identifiability of climate-based parameters. 2021. https://doi.org/10.1002/essoar.10507589.1
  • Zhu Q, Riley W, Tang J, Collier N, Hoffman F, Yang X, Bisht G et al. Representing Nitrogen, Phosphorus, and Carbon Interactions in the E3SM Land Model: Development and Global Benchmarking. Journal of Advances in Modeling Earth Systems, 11, 2238-2258, 2019. https://doi.org/10.1029/2018ms001571
  • Hanasaki, N., Yoshikawa, S., Pokhrel, Y., Kanae, S. et al. et al. A global hydrological simulation to specify the sources of water used by humans. 2017. https://doi.org/10.5194/hess-2017-280-rc2
  • Mathison, C., Burke, E., Hartley, A. J., Kelley, D. I., Burton, C., Robertson, E., Gedney, N., Williams, K., Wiltshire, A., Ellis, R. J., Sellar, A. A., and Jones, C. D. et al. Description and evaluation of the JULES-ES set-up for ISIMIP2b. Geoscientific Model Development, 16, 4249-4264, 2023. https://doi.org/10.5194/gmd-16-4249-202

Additional documentation

Other references

This DOI is a new version of

  • Gosling, Simon N.; Müller Schmied, Hannes; Ostberg, Sebastian; Bradley, Anna; Burek, Peter; Chang, Jinfeng; Ciais, Philippe; Grillakis, Manolis; Guillaumot, Luca; Hanasaki, Naota; Hartley, Andrew; Huang, Huilin; Kou-Giesbrecht, Sian; Koutroulis, Aristeidis; Otta, Kedar; Qi, Wei; Satoh, Yusuke; Stacke, Tobias; Zhu, Qing; Schewe, Jacob (2025): ISIMIP3a Simulation Data from the Global Water Sector. Version 1.5. ISIMIP Repository. (Dataset). https://doi.org/10.48364/ISIMIP.398165.5.

GCMD Keywords

  • EARTH SCIENCE > AGRICULTURE > AGRICULTURAL PLANT SCIENCE > IRRIGATION
  • EARTH SCIENCE > CLIMATE INDICATORS > TERRESTRIAL HYDROSPHERE INDICATORS > FRESHWATER RUNOFF
  • EARTH SCIENCE > CRYOSPHERE > SNOW/ICE > SNOW WATER EQUIVALENT
  • EARTH SCIENCE > HUMAN DIMENSIONS > ECONOMIC RESOURCES > ENERGY PRODUCTION/USE > HYDROELECTRIC ENERGY PRODUCTION/USE
  • EARTH SCIENCE > HUMAN DIMENSIONS > ENVIRONMENTAL GOVERNANCE/MANAGEMENT > ENVIRONMENTAL ASSESSMENTS
  • EARTH SCIENCE > HUMAN DIMENSIONS > ENVIRONMENTAL GOVERNANCE/MANAGEMENT > WATER MANAGEMENT
  • EARTH SCIENCE > HUMAN DIMENSIONS > HABITAT CONVERSION/FRAGMENTATION > IRRIGATION
  • EARTH SCIENCE > HUMAN DIMENSIONS > NATURAL HAZARDS > DROUGHTS
  • EARTH SCIENCE > HUMAN DIMENSIONS > NATURAL HAZARDS > FLOODS
  • EARTH SCIENCE > HUMAN DIMENSIONS > SUSTAINABILITY > ENVIRONMENTAL SUSTAINABILITY
  • EARTH SCIENCE > HUMAN DIMENSIONS > SUSTAINABILITY > SUSTAINABLE DEVELOPMENT
  • EARTH SCIENCE > LAND SURFACE > SOILS > SOIL MOISTURE/WATER CONTENT
  • EARTH SCIENCE > TERRESTRIAL HYDROSPHERE > GROUND WATER > GROUND WATER PROCESSES/MEASUREMENTS > DISCHARGE
  • EARTH SCIENCE > TERRESTRIAL HYDROSPHERE > SNOW/ICE > SNOW WATER EQUIVALENT
  • EARTH SCIENCE > TERRESTRIAL HYDROSPHERE > SURFACE WATER > SURFACE WATER FEATURES > RIVERS/STREAMS
  • EARTH SCIENCE > TERRESTRIAL HYDROSPHERE > SURFACE WATER > SURFACE WATER PROCESSES/MEASUREMENTS > AQUIFER RECHARGE
  • EARTH SCIENCE > TERRESTRIAL HYDROSPHERE > SURFACE WATER > SURFACE WATER PROCESSES/MEASUREMENTS > FLOODS
  • EARTH SCIENCE > TERRESTRIAL HYDROSPHERE > SURFACE WATER > SURFACE WATER PROCESSES/MEASUREMENTS > RUNOFF
  • EARTH SCIENCE > TERRESTRIAL HYDROSPHERE > SURFACE WATER > SURFACE WATER PROCESSES/MEASUREMENTS > TOTAL SURFACE WATER
  • Global Change Master Directory (GCMD) Keywords are a hierarchical set of controlled vocabularies maintained by NASA (more information).

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