Advancing operational flood forecasting, early warning and risk management with new emerging science: Gaps, opportunities and barriers in Kenya

Augustine Kiptum*, Emmah Mwangi, George Otieno, Andrew Njogu, Mary Kilavi, Zacharia Mwai, Dave MacLeod, Jeff Neal, Laurence Hawker, Tom O'Shea, Halima Saado, Emma Visman, Bernard Majani, Martin C. Todd

*Corresponding author for this work

Research output: Contribution to journalArticle (Academic Journal)peer-review

2 Citations (Scopus)

Abstract

Kenya and the wider East African region suffer from significant flood risk, as illustrated by major losses of lives, livelihoods and assets in the most recent years. This is likely to increase in future as exposure rises and rainfall intensifies under climate change. Accordingly, flood risk management is a priority action area in Kenya's national climate change adaptation planning. Here, we outline the opportunities and challenges to improve end-to-end flood early warning systems, considering the scientific, technical and institutional/governance dimensions. We demonstrate improvements in rainfall forecasts, river flow, inundation and baseline flood risk information. Notably, East Africa is a ‘sweetspot’ for rainfall predictability at sub-seasonal to seasonal timescales for extending forecast lead times beyond a few days and for ensemble flood forecasting. Further, we demonstrate coupled ensemble flow forecasting, new flood inundation simulation, vulnerability and exposure data to support Impact based Forecasting (IbF). We illustrate these advances in the case of fluvial and urban flooding and reflect on the potential for improved flood preparedness action. However, we note that, unlike for drought, there remains no national flood risk management framework in Kenya and there is need to enhance institutional capacities and arrangements to take full advantage of these scientific advances.
Original languageEnglish
Article numbere12884
JournalJournal of Flood Risk Management
Early online date29 Mar 2023
DOIs
Publication statusE-pub ahead of print - 29 Mar 2023

Bibliographical note

Funding Information:
At the present, Kenya does not have a FldEWS operational at the national scale (Weingärtner et al., 2019 ). Figure 4 shows the KMD's NFFEWC that is operational only for the Nzoia River in Western Kenya. However, efforts to expand to other flood‐prone basins are currently ongoing which we discuss in detail in the next sub‐sections of this article (see Sections 2.4.1 and 2.4.2 ). The Nzoia River FldEWS was established in 2008 through World Bank support to the Kenyan government and was aimed at enhancing the flood early warning systems within the basin amongst other project components. This has recently been upgraded under an addendum to KWSCRP (funded by the Korean government) by installing additional monitoring stations and enhancing capacity for flood forecasting at KMD. The current operational FldEWS (Figure 4 ) is automated using the Water Information Management and Ecosystem and Services (WIMES) interface. WIMES ingests hydrometeorological data from 23 telemetric Automatic Weather Stations (AWSs; transmitting data in real‐time to the NFFEWC servers), and nine telemetric river gauging stations along the river (transmitting to WRA observation database servers). See Figure 5 for the hydrometeorological network of the Nzoia FldEWS. WIMES uses 3‐day lead time rainfall forecasts from the KMD Weather Research and Forecasting (WRF) regional model.

Publisher Copyright:
© 2023 The Authors. Journal of Flood Risk Management published by Chartered Institution of Water and Environmental Management and John Wiley & Sons Ltd.

Keywords

  • early warning
  • flood
  • forecast-based action
  • forecasting
  • impact based forecasting
  • inundation
  • Kenya

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