Get access

Does a rainfall-based drought index simulate hydrological droughts?

Authors

  • Muhammad Rahiz,

    Corresponding author
    1. School of Geography and the Environment, University of Oxford, Oxford, UK
    2. African Climate and Development Initiative, University of Cape Town, Cape Town, South Africa
    • Correspondence to: M. Rahiz, African Climate and Development Initiative, University of Cape Town, Private Bag X3, Rondebosch 7701, Cape Town, South Africa. E-mail: muhammad.rahiz@uct.ac.za

    Search for more papers by this author
  • Mark New

    1. School of Geography and the Environment, University of Oxford, Oxford, UK
    2. African Climate and Development Initiative, University of Cape Town, Cape Town, South Africa
    3. Department of Environmental and Geographical Science, University of Cape Town, Cape Town, South Africa
    Search for more papers by this author

ABSTRACT

The drought severity index (DSI) is applied at 3-, 6-, 12- and 24-month time scales to both monthly gridded rainfall and monthly river flow datasets to evaluate if a rainfall-based drought index is able to simulate hydrological droughts. Time series of the rainfall-based and the flow-based DSIs are analysed at different drought severities and seasons at seven benchmark catchments in England. The analysis also includes the ability of the indices to reproduce the statistics of three drought characteristics, namely drought intensity, frequency of drought months and frequency of drought events at a given duration. Results of this study show that: (1) the rainfall-based DSI is able to capture periods of low flows as can be seen in its ability to represent major hydrological drought events as simulated by the flow-based DSI, (2) the rainfall-based DSIs generally represent moderate hydrological droughts better than extremes as shown by the smaller difference between the rainfall-based and the flow-based DSIs in terms of the statistics of the three drought characteristics and (3) there is a positive relationship between the time scale of DSI and the intensity (and duration) of the drought event it produces. As a secondary objective, the study has shown that the monthly gridded rainfall is a good proxy for monthly catchment rainfall and can therefore be considered a reliable dataset against which climate change experiments can be evaluated. The study concludes that the DSI is a credible index in estimating hydrological droughts. The strong positive correlation between the rainfall-based and the flow-based DSI time series suggests that changes and trends in rainfall-based DSIs can provide useful inferences for understanding changes in future hydrological droughts, as well as meteorological droughts. It is hoped that results from this study provide useful information when utilizing the DSI for assessment of drought impacts and future planning and management of water resources.

Ancillary