Development of semi dynamic cropping calendar for Indramayu using Pacific sea surface temperature

Abstract

Agriculture is a very important sector in Indramayu’s economy. Approximately 53.52% of Indramayu residents are involved in agriculture. Indramayu has 119.752 Ha (58% of the total area) cultivated as rice fields which generates the majority of the district’s income. Most of the farmers use a traditional cropping method called Pranata Mangsa, which is based on periodic natural events and Primbon, but not climate variability. Climate variability has become a major obstacle to achieving a successful harvest, because it can affect the timing of planting and length of the growing season, which leads to drought and flood vulnerability. The planting date and growing season can be predicted using monthly sea surface temperature (SST) anomalies in Nino 3.4. The August SST anomalies can describe the planting date better than the growing season, which are demonstrated best in Lohbener with R-Sq = 45% with forecast skill reach = 84% and 92% for advanced and delayed planting date. Knowing the planting date and growing season length produces a more efficient cropping calendar, which includes details such as when to prepare the land, plant seeds, and harvest. This cropping calendar is expected to reduce the impacts of climate variability by providing a more efficient cropping pattern and avoiding potential harvest failures.