This report is part of the AFRHINET project under the ACP-EU Cooperation Programme in Science and Technology (S&T II). The overall aims of the project are to enhance options for sustainable integration of rainwater harvesting for irrigation through understanding adoption constraints and developing networks for capacity building and technology transfer. The African partners are Addis Ababa University and WaterAid-Ethiopia in Ethiopia, University of Nairobi and ICRAF-Searnet in Kenya, Eduardo Mondlane University in Mozambique, and University of Zimbabwe and ICRISAT-Zimbabwe in Zimbabwe.

This study has been produced with the overall goal to document and analyse exisiting best practices in the field of RWHI management in sub-Saharan Africa, with a special focus on Ethiopia, Kenya, Mozambique and Zimbabwe. This is meant to determine the suitability of RWHI management under multivariate biophysical and socioeconomic conditions. The best practices include specific information and know-how on the performance, cost-efficiency and impacts of RWHI technologies.

These advanced training materials have been produced to foster the capacity of practitioners from private, nongovernmental and public sectors on one hand, and academics and scientists on the other, to practically implement cost-efficient RWHI technologies and practices in arid and semi-arid areas. Therefore, these training materials intend to provide the required information to support proper planning, design and construction of cost-efficient RWHI technologies and practices, with special emphasis on the specific problems encountered in Ethiopia, Kenya, Mozambique and Zimbabwe.

These training materials have been produced to foster the capacity of key members of local communities to practically implement RWHI systems in a cost-efficient manner. The specific target group of these capacity building materials are local community members who are directly involved in the replication and scale-up of RWHI technologies and practices, i.e.

This article gives insights about collaboration and how this process can help agricultural innovation in Africa.

Decision support systems (DSS) have long been used in research, service provision and extension. Despite the diversity of technological applications in which past agricultural DSS canvass, there has been relatively little information on either the functional aspects of DSS designed for economic decisions in irrigated cropping, or the human and social factors influencing the adoption of knowledge from such DSS.