Analisis Validasi Data Hujan Satelit Imerg Terkalibrasi terhadap Data Curah Hujan Terukur di Wilayah Kota Kupang

MEE, Roymond Agustinus Basi (2025) Analisis Validasi Data Hujan Satelit Imerg Terkalibrasi terhadap Data Curah Hujan Terukur di Wilayah Kota Kupang. Undergraduate thesis, Universitas Katolik Widya Mandira Kupang.

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Abstract

Rainfall monitoring plays a crucial role with broad coverage in various sectors, however, rainfall data obtained from conventional ground-based rainfall observation stations are often limited in terms of area and time coverage. As technology advances, remote sensing now makes it possible to monitor rainfall in hard-to-reach areas, such as Integrated Multi-satellite Retrievals for Global Precipitation Measurement (IMERG). Although hydrometeorological data obtained via satellite currently has a high level of accuracy and easy access in various locations and times, the use of satellite data still requires a correction process first. This study aims to analyze the level of validity and accuracy of IMERG rainfall data that has been calibrated against rainfall data from rainfall observation stations in Kupang City. The research method includes data collection and analysis. The data required and obtained in this study are secondary data. The data obtained and used in this study include rainfall data at two rain post points downloaded from the website https://dataonline.bmkg.go.id/dataonline and NASA GPM satellite rainfall data downloaded from the website https://giovanni.gsfc.nasa.gov/giovanni. Data analysis in this study includes data quality testing, rainfall data evaluation, satellite rainfall data calibration, and validation of the calibrated rainfall data. The results of the data analysis will be in the form of correction factors. In conducting validation, calibration of satellite rainfall data is required to obtain correction factors. Calibration analysis is carried out with 3 simulations with different periods, namely 7 years, 8 years and 9 years. Calibration of rainfall data carried out produces 2 types of regression per period, namely linear regression and polynomial regression. Each IMERG grid calibrated against 1 rainfall station per calibration period produces 1 linear equation and 1 polynomial equation. In the calibration of rainfall data carried out with 2 regression equations, 12 linear equations and 12 polynomial equations are obtained which will then be validated against rainfall data from 2 rainfall stations. The equations obtained produce the R value of each IMERG satellite grid against 2 rainfall stations. Validation testing for periods of 3 years, 2 years and 1 year uses equations obtained from calibration periods of 7 years, 8 years and 9 years, respectively. In the validation stage, R, RMSE, NSE and KR values are tested for each IMERG satellite grid. The best results are the R, RMSE, NSE and KR values. The best validation value of calibrated IMERG satellite data against station rainfall data was obtained at a period of 9:1 years. This indicates that the longer the data range used for calibration, the better the correlation coefficient will be, meaning that there is a close relationship between the corrected IMERG rainfall data and the field rainfall data.

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