Model Statistical Downscaling Nonparametrik pada Simulasi Data Curah Hujan Harian Pos Jurang Malang Daerah Aliran Sungai Jangkok - Mustika Hadijati; Desy Komalasari; Irwansyah Irwansyah (University of Mataram, 2018)
The prediction of river water discharge can be determined by developing a river water discharge model based on climate information, especially rainfall information. This research aims to obtain a simulation of rainfall data that will be used to river water discharge modeling. The simulation of rainfall data is obtained using statistical downscaling model which develop the functional model between global climate data and local climate data. Daily precipitation of General Circulation Model (GCM) is used to be predictor variables. It is global climate data.. And, daily rainfall of Jangkok watershed, the local climate data, is used to be response variable.. In order to reduce the dimension of GCM global data, GCM data is projected to a litle number of variable using classification and regression tree (CART) method. Then, the projection variables are used to develop statistical downscaling model of rainfall based on Kernel nonparametric regression. Daily rainfall data of Jurang Malang station, Jangkok watershed, is simulated based on the model obtained.