Development of a Non-Linear Integrated Drought Index (NDI) for Managing Drought and Water Resources Forecasting in the Upper Tana River Basin-Kenya

This article uses the non-linear integrated drought index (NDI) for managing drought and water resources forecasting in a tropical river basin. The NDI was formulated using principal component analysis (PCA). The NDI used hydro-meteorological data and forecasted using recursive multi-step neural net...

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Bibliographic Details
Published inInternational journal of environmental sustainability and green technologies Vol. 11; no. 1; pp. 15 - 33
Main Author Wambua, Raphael Muli
Format Journal Article
LanguageEnglish
Published Hershey IGI Global 01.01.2020
Subjects
Clean technology
Creeks & streams
Dams
Drought
Drought index
Emergency preparedness
Food security
Forecasting
Hydrology
Hydrometeorology
Lead time
Meteorological data
Moisture content
Neural networks
Precipitation
Principal components analysis
Remote sensing
River basins
Rivers
Stream flow
Sustainable development
Vegetation
Water resources
Water shortages
Water supply
Weather forecasting
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Summary:This article uses the non-linear integrated drought index (NDI) for managing drought and water resources forecasting in a tropical river basin. The NDI was formulated using principal component analysis (PCA). The NDI used hydro-meteorological data and forecasted using recursive multi-step neural networks. In this article, drought forecasting and projection is adopted for planning ahead for mitigation and for the adaptation of adverse effects of droughts and food insecurity in the river basin. Results that forecasting ability of NDI model using ANNs decreased with increase in lead time. The formulated NDI as a tool for projecting into the future.
ISSN:2643-7406
2643-7414
DOI:10.4018/IJESGT.2020010102