International Symposium on
Drylands Ecology and Human Security

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Adoption and Abandonment of Rainfall Forecasting Reports by Farmers:
A Case of Iran

S.M.J. Nazemos'sadat1, M. Sharifzadeh2, A.A. Kamgar-Haghighi1, and M. Ahmadvand2

1 Water Department, College of Agriculture, Shiraz University, Iran
2 Agricultural Extension and Education, College of Agriculture, Shiraz University, Iran
Presenting Author: M. Sharifzadeh


The climate impacts are not only an effect of changes in water availability, but also emerge from the confrontation of availability and societal demands and the role these demands play in the use of natural resources. In many countries of the Middle East, the annual withdrawal of water has already exceeded the renewable amount, and water scarcity has increased with the rapid population growth in the region. In Iran, with annual average precipitation of 250 mm, most of the territory receives less than 100 mm of rain, where, of total national water consumption, 95 percent is allocated to agricultural uses, 4 percent to domestic water supply and 1 percent to industrial uses, respectively.
Although rainfall forecasting as potentially a valuable way of reducing risks on climatic disasters has an important effect on agricultural production especially in wheat cropping areas of Iran, but the subject doesn’t take care of farmers as adopting this innovation as well. On the other hand, adoption of rainfall forecasting reports isn't only a technical decision and many factors affect on this soft technology. Recognizing these factors and effective characteristics could help identifying probable adopters and may affect to extend this process.

This research aims at investigation of long-term rainfall forecasting acceptance among Fars Province wheat growers with a survey research method and cluster sampling technique. The survey instrument was a structural questionnaire which validity and reliability were confirmed. Results revealed that statistically there was no difference between adopters and non-adopters of rainfall forecasting information in the field of personal, social, economical and cultural characteristics. Although the Knowledge, perception and behavior about using results of rainfall forecasting are different among various stakeholder, the innovation characteristics; relative advantage, triability, compatibility and complexity are statistically different among two groups of adopter and non-adopter farmers. Logistic regression modeling results showed that, farmer's access to information sources, relative advantage, and compatibility were the most important factors to predict adoption of rainfall forecasting usage. Optimizing use of rainfall forecasting information, it is necessary to use extension programs for changing knowledge, perception and behavior among wheat farmers.