Study of the effect of climate variation on irrigated and rainfed rice productivity based on aquacrop crop modelling simulation (Case Study of Java Island)

Abstract

Abstract Aquacrop is free-licensed Food and Agricultural Organization’s crop modelling that requires minimum inputs of climate variables namely rainfall, maximum temperature, minimum temperature variables and geographic information of the area to be simulated (longitude, latitude, altitude). This study aims to measure the difference in irrigated and rainfed rice productivity from the Aquacrop crop modelling simulation to the influence of climate pattern variations in Java Island, Indonesia. The k-means clustering method applied to the rainfall, maximum, and minimum temperature variables from the bias-corrected MERRA2 data resulted in two climate regions. The principal component analysis result showed that the maximum and minimum temperature variables are the variables that most contribute to the determination of the clustering area using the k-means method compared to the rainfall variable. This study has calculated the probability of the irrigated and rainfed rice productivity resulting from the Aquacrop simulation in those climate regions during La Nina [El Nino] years that will be higher [smaller] than the mean value of rice productivity during neutral years. However, the validation between the actual irrigated and rainfed rice productivity with the Aquacrop simulation results from 2001-2014 showed low correlation values that vary between negative and positive values in all climate regions. Meanwhile, the validation on the El Nino composite years generally showed positive correlation values. In addition, the neutral and La Nina composite years resulted in varying correlation values between negative and positive correlation.