Dataset extent

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Updating the estimation of 1-day probable maximum precipitation in South Africa

Updating the estimation of 1-day probable maximum precipitation in South Africa

Data and Resources

Additional Info

Field Value
Email johnsonk1@ukzn.ac.za
Authors
Author 1
Author first name
Katelyn
Author surname
Johnson
Email
johnsonk1@ukzn.ac.za
Author organization
UKZN
Department
Civil Engineering
Is this author a contact person for the dataset?
true
Author 2
Author first name
Jeff
Author surname
Smithers
Email
smithers@ukzn.ac.za
Author organization
UKZN
Department
Bioresources Engineering & CWRR
Is this author a contact person for the dataset?
Contact person
Contact 1
Contact name
Email
Contact organization
Department
Recommended citation Johnson, KA and Smithers, JC. 2020. Updating the estimation of 1-day probable maximum precipitation in South Africa. Journal of Hydrology: Regional Studies 32 (2020): 1-15. DOI: https://doi.org/10.1016/j.ejrh.2020.100736.
Did the author / contact organization collect the data? true
Name of organization that collected the data South African Weather Services
Dataset language English
Publisher UKZN
Publication date 2020-10-31
Project number WRC 2022/2023-00773
License Open (Creative commons)
License URL
Keywords Probable maximum precipitation, extreme design rainfall estimation
Geographic location or bounding box coordinates [-22.1265, 16.4699, -34.8212, 32.8931]
Topic category Hydrological data and modelling
Data structure category Structured (clearly labelled and in a standardised format)
Uploader estimation of extent to which data have been processed Refined
Is the data time series or static Static
Data reference date
Data reference date 1
Data reference date (from)
Data reference date (to)
Alternate identifier https://doi.org/10.1016/j.ejrh.2020.100736
Vertical extent datum
Vertical minimum-maximum extent
Vertical minimum-maximum extent 1
Minimum vertical extent
Maximum vertical extent
I agree to the data management plan and terms and conditions of the WRO true