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Marthews, T.R.; Dadson, S.J.; Lehner, B.; Abele, S.; Gedney, N.

High-resolution global topographic index values

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By accessing or using this dataset, you agree to the terms of the relevant licence agreement(s). You will ensure that this dataset is cited in any publication that describes research in which the data have been used.

This product, High-resolution global topographic index values, has been created with use of data from the HydroSHEDS database which is © World Wildlife Fund, Inc. (2006-2013) and has been used herein under license. WWF has not evaluated the data as altered and incorporated within, High-resolution global topographic index values, and therefore gives no warranty regarding its accuracy, completeness, currency or suitability for any particular purpose. Portions of the HydroSHEDS database incorporate data which are the intellectual property rights of © USGS (2006-2008), NASA (2000-2005), ESRI (1992-1998), CIAT (2004-2006), UNEP-WCMC (1993), WWF (2004), Commonwealth of Australia (2007), and Her Royal Majesty and the British Crown and are used under license. The HydroSHEDS database and more information are available at http://www.hydrosheds.org

This dataset is made available under the terms of the Open Government Licence

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https://doi.org/10.5285/6b0c4358-2bf3-4924-aa8f-793d468b92be
This is the most recent version of this dataset (view other versions)
The topographic index is a hydrological quantity describing the propensity of the soil at landscape points to become saturated with water as a result of topographic position (i.e. not accounting for other factors such as climate that also affect soil moisture but are accounted for separately). Modern land surface models require a characterisation of the land surface hydrological regime and this parameter allows the use of the TOPMODEL hydrological model to achieve this .This Geographic Information System layer is intended for use as topographic ancillary files for the TOPMODEL routing model option within the Joint UK Land Environment Simulator (JULES) land surface model. The topographic index variable here is directly comparable to the compound topographic index available from United States Geological Survey's Hydro1K at 30 sec resolution.

PLEASE NOTE: This dataset is a correction to a previous version which was found to contain errors ( https://doi.org/10.5285/ce391488-1b3c-4f82-9289-4beb8b8aa7da ). In the previous version all pixels north of 4.57 degrees south were shifted consistently 9.3 km to the west. This version is correctly aligned at all points.
Publication date: 2015-03-03
12 citations
194 downloads *
3,150 views *

More information

View numbers valid from 01 June 2023 Download numbers valid from 20 June 2024 (information prior to this was not collected)

Format

netCDF

Spatial information

Study area
Spatial representation type
Raster
Spatial reference system
WGS 84

Temporal information

Temporal extent
2014-01-01    to    …

Provenance & quality

The GA2 algorithm has been used to calculate these topographic index values, using base data layers provided by the HydroSHEDS suite of GIS layers. All files were generated using FORTRAN 90 at 15 arc-sec resolution (cells circa 450 m x 450 m at the Equator). PLEASE NOTE: This dataset is a correction to a previous version which was found to contain errors (doi:10/t7d). In the previous version all pixels north of 4.57 degrees south were shifted consistently 9.3 km to the west. This version is correctly aligned at all points.

Licensing and constraints

This dataset is made available under the terms of the Open Government Licence

Cite this dataset as:
Marthews, T.R.; Dadson, S.J.; Lehner, B.; Abele, S.; Gedney, N. (2015). High-resolution global topographic index values. NERC Environmental Information Data Centre. https://doi.org/10.5285/6b0c4358-2bf3-4924-aa8f-793d468b92be

BibTeX RIS

This product, High-resolution global topographic index values, has been created with use of data from the HydroSHEDS database which is © World Wildlife Fund, Inc. (2006-2013) and has been used herein under license. WWF has not evaluated the data as altered and incorporated within, High-resolution global topographic index values, and therefore gives no warranty regarding its accuracy, completeness, currency or suitability for any particular purpose. Portions of the HydroSHEDS database incorporate data which are the intellectual property rights of © USGS (2006-2008), NASA (2000-2005), ESRI (1992-1998), CIAT (2004-2006), UNEP-WCMC (1993), WWF (2004), Commonwealth of Australia (2007), and Her Royal Majesty and the British Crown and are used under license. The HydroSHEDS database and more information are available at http://www.hydrosheds.org

Citations

Marthews, T.R., Dadson, S.J., Lehner, B., Abele, S., & Gedney, N. (2015). High-resolution global topographic index values for use in large-scale hydrological modelling. Hydrology and Earth System Sciences, 19(1), 91–104. https://doi.org/10.5194/hess-19-91-2015
Qian, T., Tsunekawa, A., Masunaga, T., & Wang, T. (2017). Analysis of the Spatial Variation of Soil Salinity and Its Causal Factors in China’s Minqin Oasis. Mathematical Problems in Engineering, 2017, 1–9. https://doi.org/10.1155/2017/9745264
Robinson, E.L., & Clark, D.B. (2020). Using Gravity Recovery and Climate Experiment data to derive corrections to precipitation data sets and improve modelled snow mass at high latitudes. Hydrology and Earth System Sciences, 24(4), 1763–1779. https://doi.org/10.5194/hess-24-1763-2020
McNorton, J., Gloor, E., Wilson, C., Hayman, G.D., Gedney, N., Comyn‐Platt, E., … Chipperfield, M.P. (2016). Role of regional wetland emissions in atmospheric methane variability. Geophysical Research Letters, 43(21). https://doi.org/10.1002/2016gl070649
Brun, P., Thuiller, W., Chauvier, Y., Pellissier, L., Wüest, R.O., Wang, Z., & Zimmermann, N.E. (2019). Model complexity affects species distribution projections under climate change. Journal of Biogeography, 47(1), 130–142. https://doi.org/10.1111/jbi.13734
Brun, P., Psomas, A., Ginzler, C., Thuiller, W., Zappa, M., & Zimmermann, N. E. (2020). Large‐scale early‐wilting response of Central European forests to the 2018 extreme drought. In Global Change Biology (Vol. 26, Issue 12, pp. 7021–7035). Wiley. https://doi.org/10.1111/gcb.15360
Carozza, D. A., & Boudreault, M. (2021). A Global Flood Risk Modeling Framework Built With Climate Models and Machine Learning. In Journal of Advances in Modeling Earth Systems (Vol. 13, Issue 4). American Geophysical Union (AGU). https://doi.org/10.1029/2020MS002221
Levy, P., Clement, R., Cowan, N., Keane, B., Myrgiotis, V., Oijen, M., Smallman, T. L., Toet, S., & Williams, M. (2022). Challenges in Scaling Up Greenhouse Gas Fluxes: Experience From the UK Greenhouse Gas Emissions and Feedbacks Program. In Journal of Geophysical Research: Biogeosciences (Vol. 127, Issue 5). American Geophysical Union (AGU). https://doi.org/10.1029/2021jg006743
Walters, D., Baran, A.J., Boutle, I., Brooks, M., Earnshaw, P., Edwards, J., Furtado, K., Hill, P., Lock, A., Manners, J., Morcrette, C., Mulcahy, J., Sanchez, C., Smith, C., Stratton, R., Tennant, W., Tomassini, L., Van Weverberg, K., Vosper, S., … Zerroukat, M. (2019). The Met Office Unified Model Global Atmosphere 7.0/7.1 and JULES Global Land 7.0 configurations. Geoscientific Model Development, 12(5), 1909-1963 https://doi.org/10.5194/gmd-12-1909-2019
Giardina, F., Gentine, P., Konings, A.G., Seneviratne, S.I., & Stocker, B.D. (2023). Diagnosing evapotranspiration responses to water deficit across biomes using deep learning. In New Phytologist (Vol. 240, Issue 3, pp. 968–983). Wiley. https://doi.org/10.1111/nph.19197
de Albuquerque, F.S., Bateman, H.L., Ryan, M.J., & Montgomery, B. (2023). Model transferability and predicted response of a dryland anuran to climate change in the Southwest United States. In Journal of Biogeography (Vol. 51, Issue 1, pp. 120–130). Wiley. https://doi.org/10.1111/jbi.14733
Zemlianskii, V., Brun, P., Zimmermann, N.E., Ermokhina, K., Khitun, O., Koroleva, N., & Schaepman‐Strub, G. (2024). Current and past climate co‐shape community‐level plant species richness in the Western Siberian Arctic. In Ecology and Evolution (Vol. 14, Issue 3). Wiley. https://doi.org/10.1002/ece3.11140

Correspondence/contact details

Marthews, T.
UK Centre for Ecology & Hydrology
Maclean Building, Benson Lane, Crowmarsh Gifford
Wallingford
Oxfordshire
OX10 8BB
UNITED KINGDOM
 enquiries@ceh.ac.uk

Authors

Marthews, T.R.
University of Oxford
ORCID iD icon https://orcid.org/0000-0003-3727-6468
Dadson, S.J.
University of Oxford
Lehner, B.
McGill University
Abele, S.
University of Oxford
Gedney, N.
Hadley Centre for Climate Prediction and Research

Other contacts

Custodian
NERC EDS Environmental Information Data Centre
 info@eidc.ac.uk
Publisher
NERC Environmental Information Data Centre
 info@eidc.ac.uk

Additional metadata

Topic categories
environment
INSPIRE theme
Hydrography
Keywords
hydrological regimes , hydrology , Hydrology , inundation , soil moisture , spatial data , Topography
Last updated
21 March 2025 13:21