Drought Forecasting Under Climate Change Scenarios Using Artificial Neural Networks for Sustainable Water Resources Management in Upper Tana River Basin, Kenya

6 Pages Posted: 10 Jul 2018

See all articles by Prof. Dr.-Ing. Benedict Mwavu Mutua, PhD, Rer. nat.

Prof. Dr.-Ing. Benedict Mwavu Mutua, PhD, Rer. nat.

Kibabii University

Raphael Muli Wambua

Jomo Kenyatta University of Agriculture and Technology

James Messo Raude

Jomo Kenyatta University of Agriculture and Technology

Date Written: July 9, 2018

Abstract

Climate change has continued to impact negatively on water resources globally. For instance, extreme weather conditions especially the drought phenomena have become frequent in Africa. This has prompted water engineers and hydrologists to formulate mitigation and adaptation measures to address these challenges. The frequency of drought event of a defined severity for a defined return period is fundamental in planning, designing, operating and managing water resources systems within a basin. This paper presents an analysis of the hydrological drought frequency for the upper Tana River basin in Kenya using the absolute Stream flow Drought Index (SDI) and modified Gumbel technique. The study used a 41-year (1970-2010) stream flow data and forecasted hydrological droughts for 2, 5, 10, 20, 50, 100, 200, 500 and 1000-year return periods in relation to the selected stream flows. The results provide an overview of drought trends within the river basin and therefore would be very useful in applying drought adaptation policies by water resource managers.

Keywords: Upper Tana River basin, Hydrological drought, Return period, Gumbel technique, Drought frequency

Suggested Citation

Mutua, Benedict Mwavu and Wambua, Raphael Muli and Raude, James Messo, Drought Forecasting Under Climate Change Scenarios Using Artificial Neural Networks for Sustainable Water Resources Management in Upper Tana River Basin, Kenya (July 9, 2018). PAUWES Research-2-Practice Forum 2018. Available at SSRN: https://ssrn.com/abstract=3210560 or http://dx.doi.org/10.2139/ssrn.3210560

Benedict Mwavu Mutua (Contact Author)

Kibabii University ( email )

1699
Bungoma, Western 50200
Kenya

Raphael Muli Wambua

Jomo Kenyatta University of Agriculture and Technology ( email )

P.O. Box 62000
Nairobi, NAIROBI 00200
Kenya

James Messo Raude

Jomo Kenyatta University of Agriculture and Technology ( email )

P.O. Box 62000
Nairobi, NAIROBI 00200
Kenya

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