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Asian Journal of Agriculture and Development (AJAD) - Call for papers!

Assessing rice farmer’s use of seasonal weather forecast data to cope with climate variability in central highland of Vietnam

(Vietnam), Master of Science in Agricultural Systems Management (Chiang Mai University)

Thesis Abstract:

Nam Dong is a poor mountain district that belongs to Thua Thien Hue Province, where 90 percent of local inhabitants are ethnic groups. Paddy rice is not only traditional production of population, but also a major food crop to contribute to food security of this district. While facing the increasing weather variability, traditional farming calendar, existing local knowledge, and experiences on predicting weather become less reliable to rice farmers. As a result, farmers, particularly poor ones in highland area, who own mainly rainfed farming land, may have higher risks of failure in agricultural production in general, and rice production in particular. In this circumstance, the support from seasonal weather forecasts (SWFs) plays a significant role for farmers in terms of making related decisions to adapt with complicated weather conditions, which have change trend in Nam Dong District, Thua Thien Hue Province, Vietnam. Therefore, this study aimed to find out how weather variability impacts on rice production, how farmers use the SWFs in their rice production decisions to cope with weather variability, and which factors can influence the farmers’ SWFs use in rice production decisions.

Data were collected by using participatory rural approach (PRA), and doing questionnaire survey with 180 rice households. To determine the effect of weather variability on rice production, Ordinary Least Square Model was applied. Theory of Planned Behaviour and Structural Equation Model Analysis were used to find out factors that can influence the farmers’ SWFs use in rice production decisions.

The results from Ordinary Least Square Model showed that seasonal average rainfall,  average  highest  temperatures,  and  average  lowest  temperatures  had significant effect on rice yield. While it was found that the seasonal rainfall factor had positive relationship with rice yield in both seasons, the seasonal maximum temperatures affected adversely on rice yield in two seasons. In addition, rice yield during the summer-autumn season did not relate to seasonal minimum temperatures, but this weather variable had advantage impact on winter-spring rice yield at statistical significant level. Moreover, participants in the focus group forum reported that they believed many weather events were irregular and unpredictable as local experiences, particularly, droughts tend to occur more frequently, and this had negative impact on rice production.

The results from PRA tools indicated that the SWFs, particularly related to drought, flood, and storm events were the most concerned on the decisions of rice production activities. The influence and use of seasonal weather forecasts in specific rice production decisions were still low. Planting date selection, harvesting date selection, and pesticide application decision were three main keys of rice production decision that had the influence of SWFs. Moreover, it was noted that spouses, children, relatives, neighbors, local leader, women’s union, extension officers, television, and radio were key sources of SWFs to farmers.

Theory of Planned Behavior by applying Structural Equation Model Analysis proved that farmer’s attitude, social subjective norms, and perceived controls had positive and significant relationship to farmer’s SWFs use in rice production decisions. While farmer’s attitude was determined as the greatest direct effect on farmer’s use of SWFs and perceived controls followed by second factor of influence, subjective norms had the least effect on farmer use of SWFs in rice production decision making.

The research results provided useful data that could assist local governments in rural socioeconomic development plans to minimize the impacts of adverse weather conditions. It would also help meteorological stations and agricultural and extension units to improve their methods of communication about weather variability to farmers, and to have proper adjustments in terms of communication of weather information to farmers.