Integrasi Data Water Vapor dari Pengamatan GPS InaCORS dan Model ECMWF Menggunakan Kriging External Drift (KED) di Jawa Timur

Meivanda, Clara Sapaduma (2026) Integrasi Data Water Vapor dari Pengamatan GPS InaCORS dan Model ECMWF Menggunakan Kriging External Drift (KED) di Jawa Timur. Other thesis, Institut Teknologi Sepuluh Nopember.

Text 5016221036_Undergraduate_Thesis.pdf - Accepted Version Restricted to Repository staff only Download (15MB) | Request a copy

Abstract

Pemantauan distribusi spasial water vapor di Jawa Timur terkendala keterbatasan resolusi spasial jaringan GPS InaCORS dan bias sistematis model reanalysis ERA5 di wilayah tropis bertopografi kompleks. Penelitian ini mengintegrasikan data Precipitable Water Vapor (PWV) dari 17 stasiun GPS InaCORS dengan data Total Column Water Vapor (TCWV) ERA5 sebagai variabel external drift menggunakan metode Kriging with External Drift (KED) untuk menghasilkan peta distribusi water vapor beresolusi tinggi di Jawa Timur pada periode Januari 2023 – Desember 2024. Pemodelan tren deterministik dilakukan menggunakan Least Squares Support Vector Regression (LSSVR) dengan kernel RBF yang terpilih sebagai estimator terbaik dengan RMSE 8,388 mm. Evaluasi melalui Leave-One-Out Cross Validation (LOOCV) menunjukkan bahwa konfigurasi variogram Gaussian dengan segmentasi temporal bulanan menghasilkan kinerja optimal dengan RMSE 4,660 mm, CC 0,920, KGE 0,907, dan TSS 0,847, mereduksi galat ERA5 sebesar 60,07%. Validasi independen terhadap radiosonde BMKG Juanda menghasilkan CC 0,899 dan perbaikan bias rata-rata dari -2,092 mm menjadi -1,535 mm. Hasil penelitian membuktikan bahwa metode KED efektif mengintegrasikan presisi observasi GPS dengan cakupan spasial ERA5 untuk menghasilkan estimasi water vapor yang lebih representatif di wilayah tropis.
===========================================================================================================================================
Monitoring the spatial distribution of water vapor in East Java is constrained by the limited spatial resolution of the InaCORS GPS network and the systematic bias of ERA5 reanalysis data over complex tropical terrain. This study integrates Precipitable Water Vapor (PWV) derived from 17 InaCORS GPS stations with Total Column Water Vapor (TCWV) from ERA5 as an external drift variable using the Kriging with External Drift (KED) method to produce high resolution water vapor distribution maps over East Java for the period January 2023 – December 2024. Deterministic trend modeling was performed using Least Squares Support Vector Regression (LSSVR) with an RBF kernel, which was selected as the best estimator with an RMSE of 8.388 mm. Evaluation through Leave-One-Out Cross Validation (LOOCV) demonstrated that the Gaussian variogram configuration with monthly temporal segmentation achieved optimal performance with RMSE of 4.660 mm, CC of 0.920, KGE of 0.907, and TSS of 0.847, reducing ERA5 baseline error by 60.07%. Independent validation against BMKG Juanda radiosonde data yielded CC of 0.899 and improved mean bias from -2.092 mm to -1.535 mm. These results demonstrate that the KED method effectively integrates the precision of GPS observations with the spatial coverage of ERA5 to produce more representative water vapor estimates over tropical regions.

Item Type:	Thesis (Other)
Uncontrolled Keywords:	water vapor, GPS InaCORS, ERA5, Kriging with External Drift, LSSVR, Jawa Timur, water vapor, InaCORS GPS, ERA5, Kriging with External Drift, LSSVR, East Java
Subjects:	G Geography. Anthropology. Recreation > G Geography (General) > G70.217 Geospatial data
Divisions:	Faculty of Civil, Planning, and Geo Engineering (CIVPLAN) > Geomatics Engineering > 29202-(S1) Undergraduate Thesis
Depositing User:	Clara Sapaduma Meivanda
Date Deposited:	24 Jul 2026 08:29
Last Modified:	24 Jul 2026 08:29
URI:	http://repository.its.ac.id/id/eprint/137646

Actions (login required)

View Item