Magnitudes of Climate Variability and Changes over the Arid and Semi-Arid Lands of Kenya between 1961 and 2013 Period

The magnitude and trend of temperature and rainfall extremes as indicators of climate variability and change were investigated in the Arid and Semi-Arid Lands (ASALs) of Kenya using in-situ measurements and gridded climate proxy datasets, and analysed using the Gaussian-Kernel analysis and the Mann-Kendall statistics. The results show that the maximum and minimum temperatures have been increasing, with warmer temperatures being experienced mostly at night time. The average change in the mean maximum and minimum seasonal surface air temperature for the region were 0.74°C and 0.60°C, respectively between the 1961-1990 and 1991-2013 periods. Decreasing but statistically insignificant trends in the seasonal rainfall were noted in the area, but with mixed patterns in variability. The March-April-May rainfall season indicated the highest decrease in the seasonal rainfall amounts. The southern parts of the region had a decreasing trend in rainfall that was greater than that of the northern areas. The results of this study are expected to support sustainable pastoralism system prevalent with the local communities in the ASALs.

Forage Monitoring and Prediction Model for Early Warning Application over the East of Africa Region

Rangelands dominate arid and semi-arid lands of the Greater Horn of Africa(GHA)region,whereby pastoralism being the primary source of livelihood.The pastoral livelihood is affected by the seasonal variability of pasture and water resources.This research sought to design a grid-based forage monitoring and prediction model for the cross-border areas of the GHA region.A technique known as Geographically Weighted Regression was used in developing the model with monthly rainfall,temperature,soil moisture,and the Normalized Difference Vegetation Index(NDVI).Rainfall and soil moisture had a high correlation with NDVI,and thus formed the model development parameters.The model performed well in predicting the available forage biomass at each grid-cell with March-May and October-December seasons depicting a similar pattern but with a different magnitude in ton/ha.The output is critical for actionable early warning over the GHA region’s rangeland areas.It is expected that this mode can be used operationally for forage monitoring and prediction over the eastern Africa region and further guide the regional,national,sub-national actors and policymakers on issuing advisories before the season.