Bringing Climate Smart Agriculture to Scale: Experiences from the Water Productivity Project in East and Central Africa

Since 2010, six research organizations in the region have implemented a regional project that sought to combat food insecurity, poverty and climate change by up-scaling Climate-Smart Agriculture (CSA) technologies across farms and landscapes using the Climate Smart Landscape (CSL) approach. Several CSA technologies were evaluated and promoted across landscapes using this approach with remarkable success. Maize yields in Kenya rose from 0.5 to 3.2 t ha-1, resulting in over 90% of the watershed communities being food secure. In Madagascar, rice yields increased from 2 to 4 t ha-1 whilst onion yields increased from 10 to 25 t ha-1, resulting in watershed communities being 60% food-secure. In Eritrea, sorghum yields increased from 0.6 to 2 t ha-1. Farmers in Ethiopia earned US$10,749 from the sale of pasture whilst in Madagascar, watershed communities earned additional income of about US$2500/ha/year from the sale of onions and potatoes during off-season. Adoption levels of various CSA technologies rose from less than 30% to over 100% across the participating countries, resulting in rehabilitation of huge tracts of degraded land. In a nutshell, the potential for CSL in the region is huge and if exploited could significantly improve our economies, lives and environment

Assessment of Land Cover and Land Use Change Dynamics in Kibwezi Watershed, Kenya

Land use and land cover (LULC) parameters influence the hydrological and ecological processes taking place in a watershed. Understanding the changes in LULC is essential in the planning and development of management strategies for water resources. The purpose of the study was to detect changes in LULC in the Kibwezi watershed in Kenya, using geospatial approaches. Supervised and unsupervised classification techniques using remote sensing (RS) and geographical information system (GIS) were used to process Landsat imagery for 1999, 2009, and 2019 while ERDAS IMAGINE™ 14 and MS Excel software were used to derive change detection, and the Soil and Water Assessment Tool (SWAT) model was used to delineate the watershed using an in-built watershed delineation tool. The watershed was classified into ten major LULC classes, namely cropland (rainfed), cropland (irrigated), cropland (perennial), crop and shrubs/trees, closed shrublands, open shrubland, shrub grasslands, wooded shrublands, riverine woodlands, and built-up land. The results showed that LULC under shrub grassland, urban areas, and crops and shrubs increased drastically by 552.5%, 366.2%, and 357.1% respectively between 1999 and 2019 with an annual increase of 35.55%, 35.38%, and 33.86% per annum. The area under open shrubland and closed shrubland declined by73.7%, and 30.4% annually. These LULC transformations pose a negative impact on the watershed resources. There is therefore a need for proper management of the watershed for sustainable socio-economic development of the Kibwezi area