Stochastic drought forecasting exploration for water resources management in the upper Tana River basin, Kenya

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dc.contributor.author Wambua, Raphael M.
dc.contributor.author Mutua, Benedict M.
dc.contributor.author Raude, James M.
dc.date.accessioned 2022-11-04T11:41:27Z
dc.date.available 2022-11-04T11:41:27Z
dc.date.issued 2016
dc.identifier.citation Handbook of Research on Computational Simulation and Modeling in Engineering, chapter 54, p 508-539 2016 en_US
dc.identifier.uri https://www.igi-global.com/chapter/stochastic-drought-forecasting-exploration-for-water-resources-management-in-the-upper-tana-river-basin-kenya/137452
dc.identifier.uri http://repository.seku.ac.ke/handle/123456789/6915
dc.description DOI: 10.4018/978-1-5225-0788-8.ch054 en_US
dc.description.abstract This chapter presents the trend of drought as a stochastic natural disaster influenced by the climate variability for the upper Tana River basin in Kenya. Drought frequency, duration and intensity in the upper Tana River basin have been increasing over the years. To develop measures for mitigating impacts of drought, the influencing hydro-meteorological parameters and their interaction are necessary. Drought definitions, fundamental concepts of droughts, classification of droughts, types of drought indices, historical droughts and application of artificial neural networks in analyzing impacts of drought on water resources with special focus on a Kenyan river basin is presented. Gaps for more focused research are identified. Although drought forecasting is very vital in managing key sectors such as water, agriculture and hydro-power generation, drought forecasting techniques in Kenya are limited. There is need therefore to develop an effective drought forecasting tool for on-set detection, classification and drought forecasting. The forecasting is necessary for decision making on matters of drought preparedness and proper water resources planning and management. en_US
dc.language.iso en en_US
dc.publisher IGI Global en_US
dc.subject Drought en_US
dc.subject Unsupervised Learning en_US
dc.subject Remote Sensing en_US
dc.subject Upper Tana River Basin en_US
dc.subject Drought Indices en_US
dc.subject Reinforced Learning en_US
dc.subject Global Warming en_US
dc.subject Satellite Based Drought Indices en_US
dc.subject Artificial Neural Networks en_US
dc.title Stochastic drought forecasting exploration for water resources management in the upper Tana River basin, Kenya en_US
dc.type Book chapter en_US


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