Installation of Automatic Weather Stations (AWS) on Selected Farms and Its Integration with Satellite Data to Provide Weather Information to Farmers
The general objective of the agro-Automated Weather Stations (AWS) is to collaborate with industry experts to develop and install innovative weather system technology in key farming areas of Ghana (Brong Ahafo, Eastern and Volta Regions) to communicate critical real-time and forecasted weather data to the farmers to significantly improve livelihoods and farming as an economic activity in Ghana.
Brief Overview of AWS
As a brief overview of the innovation, the Network of Automatic Weather Stations (AWS) will consist of small cost-efficient weather stations that are powered by Solar Energy with internet connectivity. These stations will be established in conjunction with mobile telephone operators’ booster stations. The weather data from the individually sited weather stations will be collected and sent to a server for analysis at the Satellite, Weather and Climate Division of EORIC-UENR. Weather forecasts will be done and sent to farmers in collaboration with the Ghana Meteorological Agency. In addition to this, farmers will also receive real-time weather information via voice and SMS messages as well as a smartphone application. The beneficiaries of this proposed project will be farmers, agricultural extension workers, researchers, students and commercial entities. The project will also have regular training and workshops for farmers and relevant stakeholders on the importance and use of the system and its application.
The main objective of the project is to develop a Ghana-based Advanced Fire Information System (AFIS) to serve the needs of farmers. The specific objectives of the proposed proposal are;
1. EORIC-UENR currently receives satellite data such as MODIS, NOAA, MSG, LANDSAT, and VIIRS, which are used for weather and land-use modelling. Therefore the integration of such satellite data with the agro-Automated Weather Stations will complement the skill of weather forecast in Ghana. This would also allow for farmer specific seasonal weather forecasts, which is very crucial to farmers for their planning. The satellite data has the advantage of covering a wider distance away from the farm and coupled with the agro-climatic data gathered on-site, the accuracy of the forecast is enhanced to capture moving convective systems that can affect farms. Through these forecasts, anticipated weather conditions that may otherwise aggravate plant diseases or lead to pest or insect intrusion can easily be forecasted and strict measures taken by the farmers to avert such situations and reduce losses significantly.
2. Furthermore, due to the unpredictability and variability of annual rainfall as a result of climate change on an agrarian Ghanaian economy, the proposed network of agro Automatic Weather Station (AWS) will serve as a reliable tool to provide farmers with agro-related weather data that enhances best agronomy practices in farming. The innovative solution will also support current agricultural innovation practices such as greenhouse and intensive open field farming that thrives on timely, accurate, and precise climate data. For example, the agro-climatic data to be collected can be analyzed to determine the temperature and exact water requirements for specific crops. This will help farmers to irrigate more efficiently and effectively for enhanced agricultural production. Through this, local farmers can move from a rather low productivity risk- aversion orientation approach to a more tactical response approach that optimizes agricultural production with increased scale towards sustainability, while reducing the associated vulnerabilities to climate extremes. Based on results seen in South Africa, it is expected that farmer-based organizations in Ghana can potentially increase the scale of farming activity by about 40%.
3. AWS’ dense distribution will ensure the monitoring and tracking of micro-climatic conditions at different places. Monitoring these micro-climates for the respective soil moisture and temperature analysis at the correct levels is crucial for cash crops that have short harvest cycles. Usually, farms need to be sprayed periodically against pests and insects’ invasion. As such data about temperature and wind speeds and direction will help the farmer to determine the best time to spray pesticides on the crop. Choosing the wrong time can significantly increase the consumption of the pesticide and the labour time spent.
4. Information dissemination and Data accessibility is a key objective and therefore the AWS weather stations would operate without any manual intervention whereby the data can be accessed using the internet and other mobile applications. The connection of automated stations to other satellites information systems to automatically relay the recorded information on site via the internet to the EORIC-UENR administrator’s website on a timely basis for quick analysis and dissemination to farmers via phone notifications (voice, text and smartphone). This will make the system more operational and quick to use as compared to how other Automatic Weather Stations are used.
5. EORIC-UENR will conduct capacity-building workshops to teach local farmers how to move from a rather low productivity risk- aversion orientation approach to a more tactical response approach that optimizes agricultural production towards sustainability, while reducing the associated vulnerabilities to climate extremes. The training programs will also seek to equip farmers with new techniques for integrating site-specific and scientific weather and climatic information into their daily farming practices.