This study investigates the spatial-temporal trends and variability of rainfall within East and South Africa (ESA) region. The newly available Climate Hazards group Infrared Precipitation with Stations (CHIRPS-v2) gridded data spanning 37 years (1981 to 2017) was validated against gauge observations (N = 4243) and utilised to map zones experiencing significant monotonic rainfall trends. Standardised annual rainfall anomalies revealed the spatial-temporal distribution of below and above normal rains that are associated with droughts and floods respectively. Results showed that CHIRPS-v2 data had a satisfactory skill to estimate monthly rainfall with Kling-Gupta efficiency (KGE = 0.68 and a high temporal agreement (r = 0.73) while also preserving total amount (β = 0.99) and variability (γ = 0.8). Two contiguous zones with significant increase in annual rainfall (3-15 mm year −1) occurred in Southwest Zambia and in Northern Lake Victoria Basin between Kenya and Uganda. The most significant decrease in annual rainfall (− 20 mm year −1) was recorded at Mount Kilimanjaro in Tanzania. Other significant decreases in annual rainfall ranging between − 4 and − 10 mm year −1 were observed in Southwest Tanzania, Central-South Kenya, Central Uganda and Western Rwanda. CHIRPS-v2 rainfall product provides reliable high spatial resolution information on amount of rainfall that can complement sparse rain gauge network in rain-fed agricultural systems in ESA region. The observed spatial-temporal trends and variability in rainfall are important basis for guiding targeting of appropriate adaptive measures across multiple sectors.

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ArticleLow adoption of sustainable intensification technologies hinders achievement of their potential impacts on increasing agricultural productivity. Proper targeting of locations to scale-out particular technologies is a key determinant of the rate of adoption. Targeting locations with similar biophysical and socio-economic characteristics significantly increases the probability of adoption. Areas with similar biophysical and socio-economic characteristics are referred to as recommendation domains (RDs). This study used geospatial analysis to delineate sustainable recommendation domains (SRDs) for scaling improved crop varieties and good agronomic practices in Tanzania. The study uses K-means clustering to identify relatively similar clusters from grid raster’s representing biophysical and socio-economic environments. Critical ecosystems are masked-out from the clusters to generate the SRDs. The potential impacts of scaling technologies in the generated SRDs were assessed and a spatial targeting index developed. Results identify 20 SRDs and the bio-socio-economic gradients that delineate them. This study proposes an Impact Based Spatial Targeting Index (IBSTI) as an objective tool for priority setting when scaling agricultural technologies. IBSTI identified priority areas within each SRD that should be targeted to maximize potential impacts of a scaling intervention. The data-driven clustering method is recommended for regions with limited technology trials. Results demonstrate the potential of geospatial tools in generating evidence-based policies on scaling of sustainable intensification technologies.IFPRI3; ISIEPTDP

This study investigates the magnitude and signifi-1 cance of spatial-temporal trends of 37 years' time series of gridded data for rainfall, maximum (Tmax) and minimum (Tmin) 3 temperature for West Africa. A modified Mann-Kendall test and 4 Theil-Sen's slope estimator were utilized to test the significance 5 and the magnitude of trends, respectively. The magnitude of 6 significant trends for three variables between six agroecological 7 zones (AEZ's) was compared. Gridded climate data represented gauge data with high accuracy and, therefore, can reliably 9 complement the sparse observation network in West Africa. The 10 three variables showed significant positive and negative trends of 11 varying magnitude and spatial extent. June to September rainfall 12 showed a positive increase (0.1-5 mm month −1 year −1) that 13 mostly occurred north of 11 o latitude. October rainfall showed 14 a positive trend across the region, but the magnitude was higher 15 south of the same latitude. A widespread significant warming 16 trend was observed across all AEZ's and months. However, a 17 localized cooling in August and September over the Sahel and 18 Sudan Savanna was an exception. The cooling over the two 19 AEZ's coincided with a positive trend of rainfall. The zonal 20 analysis revealed that the magnitude of the positive trend of June, 21 September, and October rain increased following a North-South 22 gradient from the Sahel to humid forest AEZ's. Results provide 23 spatial evidence of climate change in a limited data environment 24 to guide the targeting of appropriate adaptation measures. The 25 information generated from this study helps the design of early 26 warning systems against droughts and floods. 27 Index Terms-Agro-ecological zones, CHIRPS, CHIRTSmax, 28 satellite time series, spatial temporal trends, TerraClimate 29 I. INTRODUCTION 30 Climate change and variability have significant positive or 31 negative impacts on the productivity and resilience of agroe-32 cosystems across different regions [1], [2], [3]. These impacts 33 are more severe in predominantly rain-fed agricultural systems 34 in Africa, where they confound with extreme poverty and 35 rapid population growth [4]. The fifth assessment report of the 36 United Nations Intergovernmental Panel on Climate Change 37 (IPCC) estimated increased warming and wet season rainfall 38 over Africa's landmass [5]. Trend analysis using time series 39 of coarse resolution remote sensing data over tropical Africa 40 shows an annual mean temperature increase at a rate of 0.15 41 o C per decade from 1979 to 2010 [6]. Predictions for rainfall 42 are most uncertain primarily due to limited understanding of 43 tropical rain forming processes.

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