Discussion notes and summay from Polokwane workshop, June 2nd

Below are some brief notes from discussions held during the day (For information on the workshop content, see the presentations and program, to be found separately).

Local signs in nature:

One person commented that the signs seen at the beginning of the rainy season e.g. much fruit on the trees, more calves, etc. might actually be a reflection on the conditions the year before instead of predictions of the coming season. More observations and comparisons would need to be made than on just the two seasons in this study.

For the two years in which the study was held, the signs in nature and the seasonal forecasts gave the same indications. IK is important to include because if you respect the knowledge have themselves, they might be also being open to new technology and knowledge. It is important that all types of knowledge be gathered and studied in order to increase understanding and use in a proactive manner.

Empowerment of Extension Service officers

The project has empowered extension service officers in uploading wireless sensor data and reading the output graphs and understanding the modeling-assisted seasonal forecast information. Training is needed as part of any sensor-based information collection exercises to make the outputs useful on the ground. Training would be needed in the care and data collection as related to the sensors, hydrological modeling and analysis of seasonal forecasts as well as scale issues. Early warning is only one part of the story. There must be willingness and opportunity from farmers to act on the information they receive.

How do we tackle the uncertainty issue in seasonal forecasting?

There are always uncertainties in predictions. The best way to handle this is by combining different sources and types of information. Uncertainty is not only related to the resolution of rainfall forecasting but also about how soil moisture is different according to soil types, vegetation, etc. There must be systems in place to improve the accuracy of information. Sensors only measure conditions at specific points. Much thought must be put into choosing where to put the sensors. GIS could be used to detect drought prone areas by using the information from sensors placed at strategic and representative areas in terms of soil, etc. System thinking is key to create a sustainable and useful program. Different incidents have been built into the disaster management database LADMSI.

How to continue the North-South collaboration?

Both sides will look for funding opportunities related to networking as well as continued project work to bring the project to the next stage. One possibility is WRC funding.