Vegetation dynamics and responses to climate anomalies in East Africa

Musau, John; Patil, Sopan; Sheffield, Justin; Marshall, Michael

doi:10.5194/esd-2017-123

Cited by 7 publications

(1 citation statement)

References 57 publications

(76 reference statements)

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“…On the other hand, the DRB is warming with an average temperature increasing rate of about 0.45 °C per decades, which is comparable with the global warming rate (i.e., 0.6 °C for the past century) and East African mean annual temperature increasing rate (i.e., 0.35 °C per decades) (Musau et al 2018). Also, the findings of the study were consistent with a study reported for the upper Blue Nile (Tekleab et al 2013;Worku et al 2018;Asfaw et al 2018).…”

Section: Spatiotemporal Climate Trendsmentioning

confidence: 71%

Spatiotemporal climate and vegetation greenness changes and their nexus for Dhidhessa River Basin, Ethiopia

et al. 2019

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Background: Understanding spatiotemporal climate and vegetation changes and their nexus is key for designing climate change adaptation strategies at a local scale. However, such a study is lacking in many basins of Ethiopia. The objectives of this study were (i) to analyze temperature, rainfall and vegetation greenness trends and (ii) determine the spatial relationship of climate variables and vegetation greenness, characterized using Normalized Difference in Vegetation Index (NDVI), for the Dhidhessa River Basin (DRB). Quality checked high spatial resolution satellite datasets were used for the study. Mann-Kendall test and Sen's slope method were used for the trend analysis. The spatial relationship between climate change and NDVI was analyzed using geographically weighted regression (GWR) technique. Results: According to the study, past and future climate trend analysis generally showed wetting and warming for the DRB where the degree of trends varies for the different time and spatial scales. A seasonal shift in rainfall was also observed for the basin. These findings informed that there will be a negative impact on rain-fed agriculture and water availability in the basin. Besides, NDVI trends analysis generally showed greening for most climatic zones for the annual and main rainy season timescales. However, no NDVI trends were observed in all timescales for cool subhumid, tepid humid and warm humid climatic zones. The increasing NDVI trends could be attributed to agroforestry practices but do not necessarily indicate improved forest coverage for the basin. The change in NDVI was positively correlated to rainfall (r 2 = 0.62) and negatively correlated to the minimum (r 2 = 0.58) and maximum (r 2 = 0.45) temperature. The study revealed a strong interaction between the climate variables and vegetation greenness for the basin that further influences the biophysical processes of the land surface like the hydrologic responses of a basin. Conclusion: The study concluded that the trend in climate and vegetation greenness varies spatiotemporally for the DRB. Besides, the climate change and its strong relationship with vegetation greenness observed in this study will further affect the biophysical and environmental processes in the study area; mostly negatively on agricultural and water resource sectors. Thus, this study provides helpful information to device climate change adaptation strategies at a local scale.

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