THIS DATASET HAS BEEN SUPERSEDED The latest version is High-resolution global topographic index values
All pixels north of 4.57 degrees south were found to be shifted consistently 9.3 km to the west, therefore this dataset has been replaced by a corrected version.
If you need access to the archived version, please contact the EIDC
High-resolution global topographic index values
https://doi.org/10.5285/ce391488-1b3c-4f82-9289-4beb8b8aa7da
Cite this dataset as:
Marthews, T.R.; Dadson, S.J.; Lehner, B.; Abele, S.; Gedney, N. (2014). High-resolution global topographic index values. NERC Environmental Information Data Centre. https://doi.org/10.5285/ce391488-1b3c-4f82-9289-4beb8b8aa7da
Download/Access
THIS DATASET HAS BEEN SUPERSEDED The latest version is High-resolution global topographic index values
All pixels north of 4.57 degrees south were found to be shifted consistently 9.3 km to the west, therefore this dataset has been replaced by a corrected version.
If you need access to the archived version, please contact the EIDC
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.
Publication date: 2014-11-30
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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).
Licensing and constraints
THIS DATASET HAS BEEN SUPERSEDED The latest version is High-resolution global topographic index values
All pixels north of 4.57 degrees south were found to be shifted consistently 9.3 km to the west, therefore this dataset has been replaced by a corrected version.
If you need access to the archived version, please contact the EIDC
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. (2014). High-resolution global topographic index values. NERC Environmental Information Data Centre. https://doi.org/10.5285/ce391488-1b3c-4f82-9289-4beb8b8aa7da
© UK Centre for Ecology & Hydrology
Citations
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
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, 91–104. https://doi.org/10.5194/hess-19-91-2015
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. Global Change Biology 26, 7021–7035. 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. Journal of Advances in Modeling Earth Systems 13. https://doi.org/10.1029/2020ms002221
Correspondence/contact details
Other contacts
Rights holder
UK Centre for Ecology & Hydrology
Custodian
NERC EDS Environmental Information Data Centre
info@eidc.ac.uk
Publisher
NERC Environmental Information Data Centre
info@eidc.ac.uk