Combining multiple streams of environmental data into a decision support tool for maize based systems in Sub-Saharan Africa

Asfaw, D. T. (2020) Combining multiple streams of environmental data into a decision support tool for maize based systems in Sub-Saharan Africa. PhD thesis, University of Reading. doi: 10.48683/1926.00101664

Abstract/Summary

In sub-Saharan Africa, where agriculture is the primary sector providing a livelihood for communities, effective use of agrometeorological advisories reduces climate risks and provides guidance on impending weather-related hazards. Early warning of weather-related hazards enables farmers, policymakers and aid agencies to mitigate their exposure to risk. To address this need, this thesis developed and investigated a new framework to monitor climatic risk associated with agriculture and support decision making using available satellite environmental data sets and numerical models for sub-Saharan Africa. TAMSAT-ALERT (Tropical Applications of Meteorology using SATellite data and ground-based measurements-AgricuLtural EaRly warning sysTem) is a new operational framework, which provides early warning of meteorological risk to agriculture. TAMSAT-ALERT combines information on land surface properties, seasonal forecasts and historical weather to quantitatively assess the likelihood of adverse weather-related outcomes, such as low yield and drought. On a shorter timescale, TAMSAT-ALERT has also been adopted to support farmer decision making on when to plant - a critically important choice. TAMSAT-ALERT incorporates a new soil moisture model simplified from the Joint UK Land Environment Simulator (JULES). The new soil moisture model runs faster and requires low computing power while providing a similar result compared to JULES soil moisture output. Evaluation against observations shows that TAMSAT-ALERT skillfully predicts the climatic risk associated with maize yield 4-6 weeks before harvest over northern Ghana and in some circumstances can anticipate agricultural drought 2-3 months in advance of the end of the season over Kenya. TAMSAT-ALERT identifies a planting date that results in a maximum yield which can be used to provide advisory to farmers in western Kenya. For this application, TAMSAT-ALERT is used to assess the tradeoff between the risk to germination and insufficient moisture for crop growth and development. Overall, the results proved that the TAMSAT-ALERT framework can be used as a tool in climate service providers across sub-Saharan Africa to produce tailored products that help to make an informed decision related to climatic risk on agriculture.

Item Type	Thesis (PhD)
URI	https://reading-clone.eprints-hosting.org/id/eprint/101664
Identification Number/DOI	10.48683/1926.00101664
Divisions	Science > School of Mathematical, Physical and Computational Sciences > Department of Meteorology
Date on Title Page	September 2019
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