Remote sensing maps on climatic trends to improve targeting of climate-smart agricultural technologies in West Africa

This study utilise time series remote sensing data for rainfall, maximum temperature and minimum temperature to investigate the magnitude and significance of spatial-temporal trends over six countries in West Africa. A modified Mann-Kendall test and Theil-Sen's slope are utilised to test the signifi...

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Detalles Bibliográficos
Autor principal: CGIAR Research Program on Maize
Formato: Informe técnico
Lenguaje:Inglés
Publicado: 2019
Materias:
Acceso en línea:https://hdl.handle.net/10568/123566
Descripción
Sumario:This study utilise time series remote sensing data for rainfall, maximum temperature and minimum temperature to investigate the magnitude and significance of spatial-temporal trends over six countries in West Africa. A modified Mann-Kendall test and Theil-Sen's slope are utilised to test the significance and the magnitude of trends respectively for period between 1981 and 2017. June to September rainfall along the Sahel, Sudan and northern Guinea savanna agro-ecological zones revealed a significant increase (0.1 - 3 mm yr -1 ) that peaked in August. Extreme temperatures for period between August and October remained stable while significant positive trend (0.005 - 0.07°C yr -1 ) was observed in rest of months. Areas experiencing significant drying and warming trends are earmarked as priority for targeting appropriate climate smart agricultural technologies. The widespread significant increase of extreme temperatures justifies increased investments in measures to cope with heat stress.