Uncertainty in rainfall pattern has put rain-fed agriculture in jeopardy, even for the regions considered high rainfall potential like the Central Highlands of Kenya (CHK). The rainfall pattern in the CHK is spatially and temporally variable in terms of onset and cessation dates, frequency and occurrence of dry spells, and seasonal distribution. Appraisal of the variability is further confounded by the lack of sufficient observational data that can enable accurate characterisation of the rainfall pattern in the region. We, therefore, explored the utilisation of satellite daily rainfall estimates from the National Aeronautics and Space Administration (NASA) for rainfall pattern characterisation in the CHK. Observed daily rainfall data sourced from Kenya meteorological department were used as a reference point. The observation period was from 1997 to 2015. Rainfall in the CHK was highly variable, fairly distributed and with low intensity in all the seasons. Onset dates ranged between mid-February to mid-March and mid-August to mid-October for long rains (LR) and short rains (SR) seasons, respectively. Cessation dates ranged from late May to mid-June and mid-December to late December for the LR and SR, respectively. There was a high probability (93%) of dry spell occurrence. More research needs to be done on efficient use of the available soil moisture and on drought tolerant crop varieties to reduce the impact of drought on crop productivity. Comparison between satellite and observed rain gauge data showed close agreement at monthly scale than at daily scale, with general agreement between the two datasets. Hence, we concluded that, given the availability, accessibility, frequency of estimation and spatial resolution, satellite estimates can complement observed rain gauge data. Stakeholders in the fields of agriculture, natural resource management, environment among others, can utilise the findings of this study in planning to reduce rainfall-related risks and enhance food security.

Low adoption of soil water conservation technologies has been one of the main causes for decreased agricultural productivity in the Upper Tana Catchment of Kenya. Proper identification of locations to scale-out the individual technologies necessary to improve water conservation is a key determinant for the rate of adoption. Our main aim was to identify the suitable sites for water conservation technologies using the suitability model created by the model builder function in ArcGIS 10.5®. The model combined the thematic layers of soil texture, slope, rainfall, and stream order, which were acquired from assorted online sources. The factors were converted to raster format and reclassified based on their suitability and were assigned fixed scores and weights by use of multi influencing factor (MIF) method. The suitability evaluation was carried out by use of weighted overlay to produce suitability classes for each of the water conservation technique. The delineated suitability maps indicated that check dams are highly suitable in 50% of the study area. Mulching, on the other hand, is highly suitable for 49% of the study area. Zai pits are highly suitable in 43% of the study area. Majority of the study area is moderately suitable for the use of terraces, covering 41% of the study area. The highly suitable areas for the Checkdams are Machakos, Kitui, Tharaka-Nithi and lower parts of Embu. The highly suitable areas for mulching are Kirinyaga, Murang’a, Nyandarua and Nyeri. The highly suitable areas for the Zai pits are Kitui, lower parts of Tharaka-Nithi and the highly suitable areas for the terraces are Murang’a, Nyeri and Kirinyaga. Furthermore, the results demonstrated the effectiveness of GIS in delineating the suitable areas for the use of water conservation technologies.