Application of rapid climate decision analysis support tool in assessing climate-sensitive farming decisions in Calapan and Gloria, Oriental Mindoro, Philippines

Dan Leo Z. Diona, Jeffrey Andrew D. Losloso, Canesio Predo, Juan M. Pulhin, Patricia Ann J. Sanchez, Asa Jose U. Sajise, Catherine C. De Luna, Kevin Parton, Peter T. Hayman

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Abstract

This study aims to assess the influence of weather and climate information on farm decision-making of rice and corn farmers in Oriental Mindoro, Philippines. The rapid climate decision analysis support tool was applied in a stepwise approach for rice and corn weather and climate sensitive risks. These risks were identified through the establishment of a crop climate calendar and subsequently subjected to a verbal decision analysis, which compares outcomes of a binary risk-mitigating decision under a set of possible weather and climate scenarios. In this study, RCDA focused on the choice of rice variety as a response to pest and disease risk occurrence. The value of forecast information is measured by looking at the trade-offs and changes in gross margins across a five-point distribution of climate states (wettest, above normal, normal, below normal, and driest) using 100 percentile points. The results show that it is more efficient to use rice varieties that are resistant to pests and diseases when the probability of rainfall occurrence is high. The forecast is deemed useful and valuable during dry conditions as it suggests that the highly susceptible variety is better 87% of the time and it may lead to a higher average profit of USD 21.43/ha. In the case of corn farming, the VDA result is sufficient to come up with optimal crop choice. By laying out and assessing farmer decision actions in dealing with weather and climate risks, cost-effective options at different weather and climate scenarios are realized, and the importance of forecast information in delivering solutions is highlighted.
Original languageEnglish
Pages (from-to)115-132
Number of pages18
JournalPhilippine Agricultural Scientist
Volume103
Issue numberspecial
Publication statusPublished - Dec 2020

Grant Number

  • ASEM 2014/051

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