Metode Koreksi Bias dan Downscaling Data Iklim untuk Simulasi Hidrologi Tropis: Tinjauan Sistematis Literatur

Rafika Andari; Yolanda Wulandari

Authors

Rafika Andari Institut Teknologi Padang Author
Yolanda Wulandari Institut Teknologi Padang Author

Keywords:

bias correction, climate projection, downscaling, PRISMA, tropical hydrology

Abstract

Proyeksi model iklim global umumnya mengandung bias sistematis yang membatasi akurasinya dalam simulasi hidrologi tropis. Penelitian ini bertujuan mengkaji perkembangan, performa, dan tantangan metode koreksi bias serta downscaling data iklim untuk pemodelan hidrologi di Indonesia melalui Systematic Literature Review (SLR) periode 2016–2025. Evaluasi sistematis dilakukan terhadap literatur ilmiah nasional dan internasional menggunakan protokol PRISMA. Hasil sintesis menunjukkan adanya ketimpangan spasial riset yang didominasi oleh wilayah Indonesia barat. Pendekatan Statistical Downscaling berbasis algoritma Quantile Mapping (QM) menjadi metode paling dominan. QM terbukti sangat andal dalam mereproduksi curah hujan ekstrem untuk pemodelan banjir rancangan pada wilayah monsoonal (NSE lebih besar dari 0,75). Namun, QM rentan memicu ketidakpastian tinggi akibat estimasi berlebih (overestimation) pada musim kemarau di wilayah ekuatorial. Keterbatasan utama dalam literatur saat ini mencakup asumsi stasioneritas iklim dan buruknya kontinuitas data lapangan. Riset mendatang perlu diarahkan pada penerapan algoritma berbasis Machine Learning serta perumusan standardisasi nasional reduksi skala iklim guna menjamin ketahanan infrastruktur keairan.

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