Climate services for agriculture in Rwanda

This report presents analysis of a baseline household survey for the Rwanda Climate Services for Agriculture project – a four-year, USAID-funded initiative that seeks to benefit Rwanda’s farming communities and national economy through climate services and improved climate risk management. The survey intends to provide a baseline assessment of the state of climate services among agricultural households in Rwanda. A random sample of 3,046 respondents was nationally surveyed in the all four provinces of the country and in the city of Kigali. A total of 52% of the sample were female respondents, while two-thirds of the households interviewed were male-headed households. The baseline includes outcome indicators related to access, use of climate information, channels of communication, behavioral change and perceived livelihood benefit/impact. The project evaluation will involve assessing changes over time in these benchmark indicators and eventually comparing the changes across beneficiaries and non-beneficiaries. A qualitative component of the evaluation will provide deeper insights into users’ decision making, behavioral change and any socially differentiated effect.According to the survey, seasonal and indigenous climate forecasts are the main climate information that respondents are aware of, with women being less aware of climate information than men. The content of climate information currently disseminated includes the more traditional information. These are onset of rains, risk of extreme events and daily precipitation. Climate information is disseminated to respondents, but indigenous climate forecasts are still provided at the national or district scale, limiting the relevance for farmers’ decision making.In all districts surveyed, respondents have little access to specific types of climate products, particularly in Kigali and the Northern Provinces. The most common types of climate information products accessed are forecasts for onset of rains, seasonal forecast, daily weather forecasts and forecasts for extreme events. But this access is very variable across districts (as high as 30% of the respondents in the Eastern Province and as low as 2% of the respondents in Kigali Province). Historical climate information and early warnings are received by respondents very infrequently. Overall, men have significantly greater access to climate4information compared to women as their awareness and knowledge of climate information is also greater.Radio is by far the main communication means of climate information in all provinces as stated by at least 74% of the respondents. This is followed by government extension agents, neighbors and farmer-to-farmer communication. Information dissemination through cell phones is almost non-existent, although a cell phone is the most common communication asset owned by respondents followed by radio. This implies that there is vast opportunity to reach a large audience of farmers through interactive radio programs and cell phone-based climate information.Ability to use climate information is very variable across provinces. The Western Province has the highest proportion of respondents who claimed to be able to use climate information while the Northern Province records the lowest proportion. Beyond poverty status, which is correlated with ability to use climate information, lack of trust in the information provided and lack of locally relevant climate information have been cited as the main constraint preventing extensive use of these products. A small percentage of respondents actively seek climate information and question the relevance of the information that is currently routinely available. Current use of climate information has little influence on farmer decision-making. It is therefore expected that planned improvements in climate information will result in behavioral change and enhanced resilience if the information is tailored to meet the needs of the agricultural community.Generally, the benchmark level for resilience is also low, between 0.2 and 0.3 (see annex 3 for details on the benchmark index). Variability across provinces is driven by factors such as differences in livelihood systems, and social and institutional capacity.

---

• View source