Open AccessImproving Spatial Rainfall Estimates at Mt. Merapi Area Using Radar-Rain Gauge Conditional Merging
Author(s) -
Roby Hambali,
Djoko Legono,
Rachmad Jayadi,
Satoru Oishi
Publication year - 2019
Publication title -
journal of disaster research
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.332
H-Index - 18
eISSN - 1883-8030
pISSN - 1881-2473
DOI - 10.20965/jdr.2019.p0069
Subject(s) - rain gauge , radar , meteorology , interpolation (computer graphics) , spatial dependence , spatial variability , environmental science , multivariate interpolation , spatial distribution , remote sensing , geology , geography , precipitation , mathematics , computer science , statistics , animation , telecommunications , computer graphics (images) , bilinear interpolation
Rainfall monitoring is important for providing early warning of lahar flow around Mt. Merapi. The X-band multi-parameter radar developed to support these warning systems provides rainfall information with high spatial and temporal resolution. However, this method underestimates the rainfall compared with rain gauge measurements. Herein, we performed conditional radar-rain gauge merging to obtain the optimal rainfall value distribution. By using the cokriging interpolation method, kriged gauge rainfall, and kriged radar rainfall data were obtained, which were then combined with radar rainfall data to yield the adjusted spatial rainfall. Radar-rain gauge conditional merging with cokriging interpolation provided reasonably well-adjusted spatial rainfall pattern.