EGU22-9872
https://doi.org/10.5194/egusphere-egu22-9872
EGU General Assembly 2022
© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.

Detecting trends in flood series and shifts in flood timing across Kenya

Maureen Wanzala1, Hannah Cloke1,2, Elisabeth Stephens1,5, Andrea Ficchi1,6, and Shaun Harrigan7
Maureen Wanzala et al.
  • 1Geography and Environmental Science, University of Reading, Reading, United Kingdom of Great Britain – England, Scotland, Wales (m.a.wanzala@pgr.reading.ac.uk)
  • 2Department of Meteorology, University of Reading, Reading, UK
  • 5Red Cross Red Crescent Climate Centre, The Hague, Netherlands
  • 6Politecnico di Milano, Milan, Italy
  • 7European Centre for Medium-Range Weather Forecasts, Reading, UK

The frequency and magnitude of flood events in Kenya have increased over the past decade. Observations show a shift in timing and variability in flood occurrences in most parts of the country. Trend analysis is useful in detecting and supporting the evidence of change in flow series, as well as variability in flood timing. In this study, the frequency and magnitude of floods observed in the annual maximum flood (AMAX) and peak over threshold (POT) flood series from 1981 to 2016 are compared in 19 Kenyan catchments. Flood peaks are identified using a threshold technique from Kenyan daily discharge data, and notable patterns in the AMAX series are compared to those in the POT series, which is created for three distinct exceedance criteria. The timing and variability of the annual floods is determined from the AMAX flow. Our findings show that, the AMAX series detects more trends in flood magnitude than the POT series, while the POT series detects more significant trends in flood frequency than flood magnitude. Sensitivity of trends to different exceedance thresholds selection reveal variable trend patterns across the stations. The timing of inter-annual floods occurs in peak rainfall months of April, May and November and shows a higher variability index in most of the coastal and western stations, and a low variability in stations whose annual floods occur in dry months of June, July, and August. This information is useful to hydrological applications such as flood protection facility design, risk assessment, and risk management for improved livelihoods in Kenya

How to cite: Wanzala, M., Cloke, H., Stephens, E., Ficchi, A., and Harrigan, S.: Detecting trends in flood series and shifts in flood timing across Kenya, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-9872, https://doi.org/10.5194/egusphere-egu22-9872, 2022.

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