Simulating Rainfall Seasonal Pattern in Kandangan Subregency Using Statistical Method

Rainfall is an important climate element which affects water resources availability in a certain area. Water resources availability itself are an important factor for human life. In this research, daily rainfall from 2014 to 2016 was statistically analyzed to obtain form and scale parameter for 2-parameter gamma distribution for each month. Then obtained parameter is clustered based on seasons resulting in four clusters. Then each obtained parameter within each cluster is modeled as dependent variable using simple linear regression with Sea Surface Temperature Anomaly over Nino 3,4 Zone as its independent variable. Those processes resulted in the regression model for each gamma distribution parameter and for each season. Then obtained model used and combined with random seed algorithm to simulate rainfall during 2017. Resulted rainfall showed that statistical model that had been built was capable to simulate the temporal pattern of rainfall although with underestimated rainfall value. © Published under licence by IOP Publishing Ltd.