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Agro-meteorological assistance in Tanzania to increase the resilience of farming communities to climate challenges
- Progress stage
- Nov 2023 to Apr 2025
To support climate-smart farm-decision making, Weather Impact, Tanzania Agricultural Research Institute (TARI), ESOKO and Tanzania Youth Espouse for Gender and Development (TYEGD) develop and test in the Mara region a location-specific dynamic Agri-Weather Advisory.
Project deployed by:
Context
Tanzania is home to over 63 million people, 80% of which is dependent on the agricultural sector. The agricultural sector of Tanzania is dominated by smallholder farmers producing 95% of the national food requirements.
Many cultivate staple crops such as maize and cassava, which are part of the top three most consumed foods in the country. These crops which represent the two largest planted areas in the Mara region are not only consumed domestically but also serve as cash crops for export. For years, local populations have experienced aggravating droughts, floods and delays in the start of the rain season coupled with uneven rainfall distribution during the season. Due to climate change, crop yields of staple produce (i.e., maize, cassava) are projected to decrease (USAID 2018). Tanzania is the 26th most vulnerable country to climate risks.
A baseline survey carried out by the project team has highlighted the significant impact of climate change on agricultural practices in three districts - Bunda DC, Bunda TC, and Butiama of the Mara region in Tanzania. Majority of farmers in these districts have experienced adverse effects such as variations in crop yields (44%), increased pest pressure (36%), and poor rain distribution. Despite the challenges posed by climate change, many farmers rely on traditional methods and personal experience for weather forecasting (46% do not check weather information, only 8% have received training on climate adaptation), with limited access to advanced meteorological data (only 14% own a smartphone). These data/results confirm and reinforce the relevance of the piloted innovation.
Innovation
The enterprise Weather Impact has been using the European Centre for Medium-Range Weather Forecasts (ECMWF) model and has been developing agri-weather solutions across Sub-Saharan Africa to provide weather forecasts to smallholder farmers in order to optimize their agricultural strategies and increase their resilience to weather shocks.
The project "Kilimo Thabiti" aims to go further by not only sending weather forecasting and general agro advisories but making those farmer- and crop-specific. The project plans:
- A communication channel by sms allowing farmers to send and receive Agri-weather info as well as cassava and maize agronomic advice based on real time weather forecasts and extreme weather alerts.
- Farmer trainings on good agricultural practices and the interpretation of agro-weather information.
- The recruitment of “citizen scientists” to collect data for validation and calibration of the agro-weather advisories and to serve as voices for weather and climate smart agriculture in their communities.
Three local partners are involved in the development of this innovation:
- The Tanzania Agricultural Research Institute (TARI) who has developed an agronomic package to advise cassava and maize farmers on when to plant, harvest, weed, etc.
- ESOKO for their IT and platform expertise
- Tanzania Youth Espouse for Gender and Development (TYEGD) to ensure inclusion and diversity
Achieved results
At the end of the project, 2657 farmers have been registered for SMS (beyond the 2400 expected), 541 were trained (expected: 500), 4744 measurements collected by Citizen Scientists (daily rainfall, weekly soil measures) and 556 households interviewed during the baseline and endline survey. Although it was not a rigorous impact evaluation as such, the endline survey included a control and a treatment group to observe some of the effects of the innovation on the farmers.
The endline survey shows that:
Through tailored SMS messages, farmers received timely weather forecasts and agronomic advice, which were widely accepted and often shared with others, amplifying the project's reach. The vast majority of farmers (99%) would recommend the service to peers, and each farmer shared on average the information to 6 other peers. Furthermore, farmers across districts exhibited willingness to pay for the weather forecast SMS.
The precision of the information was reported as highly reliable by more than half of the farmers across all districts, despite variations, acknowledging as “accurate” for 52% of them and “mostly accurate” for 69%. The “citizenship scientists” component, which involved mobilizing and training farmers to collect localized and valuable data directly, contributed to the relevance and accuracy of the messages delivered.
The messages and trainings significantly influenced various farming decisions and practices, with notable differences across districts. Furthermore, while planting seem to be the most influenced farming practice (24% of influenced practice is planning), other have been influences as well, such as purchase of input (17%), seed selection (16%), land preparation (14%), pest and disease management (10%) etc…
The most influenced farming decision seem to be in the fields of improved agricultural planning (32%), followed by market timing (22%) and drying products and irrigation scheduling (19%).
Regarding the results on income and farming production, the results suggest that the SMS service had a positive effect on maize production with a 60 % increase (from 5 to 8 bags per acre), leading to a 36% income increase.
Learnings and perspectives
The team project was able to learn from this pilot in order to better tailor the solution’s implementation, such as the timing of agro-weather SMS to have the most influence on farming practices and decision-making, making the training sessions more recurrent, etc…
An important learning for the team project came from the “citizen scientists” component. Initially dedicated to provide valuable localized data, these citizens trained and informed became “champions” of their communities. Highly recognized at the community level, their experience proved to be useful for peer farmers for interpretation of weather information.
Finally, experimenting with data collection methods, including baseline and endline surveys conducted during the project was a source of learning for the project team. During stage 1, the team was able to make significant progress to position the solution for an impact evaluation, such as experimenting with the inclusion of a control group, mobilizing research partners and developing an evaluation design that could be implemented in the future.
Projects
Projects funded by FID
