Validasi Data Curah Hujan Satelit Terhadap Data Curah Hujan Observasi Insitu di Provinsi Kepulauan Riau

Suratman, Suratman (2026) Validasi Data Curah Hujan Satelit Terhadap Data Curah Hujan Observasi Insitu di Provinsi Kepulauan Riau. Masters thesis, Institut Teknologi Sepuluh Nopember.

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Abstract

Provinsi Kepulauan Riau memiliki karakteristik iklim tropis maritim yang ditandai oleh variabilitas curah hujan yang tinggi akibat dominasi proses konvektif dan pengaruh laut. Di lapangan, kondisi ini sering memicu kejadian hujan intensitas sedang hingga lebat dalam durasi singkat yang berdampak pada genangan, gangguan aktivitas transportasi, serta peningkatan risiko bencana hidrometeorologi, khususnya di wilayah perkotaan Pulau Batam dan Pulau Bintan. Namun, keterbatasan jumlah dan sebaran penakar hujan permukaan menyebabkan informasi curah hujan spasial belum sepenuhnya terwakili, sehingga pemanfaatan data curah hujan satelit menjadi alternatif penting. Penelitian ini bertujuan untuk memvalidasi dan membandingkan kinerja dua produk curah hujan satelit, yaitu Climate Hazards Group InfraRed Precipitation with Stations (CHIRPS) dan Global Satellite Mapping of Precipitation (GSMaP), terhadap data observasi curah hujan BMKG selama periode 2019–2023. Evaluasi dilakukan menggunakan metrik statistik Mean Absolute Error (MAE), Root Mean Square Error (RMSE), Nash–Sutcliffe Efficiency (NSE), koefisien korelasi Pearson, dan Relative Bias, serta didukung analisis boxplot untuk menilai distribusi data. Selain itu, pemetaan spasial curah hujan dan pola bias dilakukan dengan metode interpolasi Inverse Distance Weighting (IDW). Hasil analisis menunjukkan bahwa CHIRPS lebih mampu merepresentasikan besaran curah hujan dan pola spasialnya, meskipun menunjukkan kecenderungan overestimate dengan bias positif hingga sekitar +48%, terutama di wilayah Bintan bagian tengah hingga timur. Sebaliknya, GSMaP memiliki korelasi temporal yang lebih baik terhadap data observasi, namun secara konsisten mengalami underestimate dengan bias negatif hingga sekitar –28%. Temuan ini menunjukkan bahwa CHIRPS lebih sesuai untuk estimasi volume curah hujan setelah koreksi bias, sementara GSMaP lebih bermanfaat untuk analisis variabilitas temporal. Hasil validasi ini diharapkan mendukung pemilihan data curah hujan satelit yang lebih tepat dalam pengelolaan sumber daya air dan mitigasi bencana hidrometeorologi di Kepulauan Riau.
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The Riau Islands Province has a maritime tropical climate characterized by high rainfall variability due to the dominance of convective processes and marine influences. In the field, these conditions often trigger moderate to heavy rainfall events in short durations that impact flooding, disrupt transportation activities, and increase the risk of hydrometeorological disasters, especially in urban areas of Batam Island and Bintan Island. However, the limited number and distribution of surface rain gauges mean that spatial rainfall information is not fully represented, so the use of satellite rainfall data is an important alternative. This study aims to validate and compare the performance of two satellite rainfall products, namely the Climate Hazards Group InfraRed Precipitation with Stations (CHIRPS) and Global Satellite Mapping of Precipitation (GSMaP), against BMKG rainfall observation data during the 2019–2023 period. The evaluation was carried out using statistical metrics Mean Absolute Error (MAE), Root Mean Square Error (RMSE), Nash–Sutcliffe Efficiency (NSE), Pearson correlation coefficient, and Relative Bias, and supported by boxplot analysis to assess data distribution. In addition, spatial mapping of rainfall and bias patterns was performed using the Inverse Distance Weighting (IDW) interpolation method. The analysis results showed that CHIRPS was better able to represent rainfall magnitude and its spatial patterns, although it showed a tendency to overestimate with a positive bias of up to +48%, especially in the central to eastern Bintan region. In contrast, GSMaP had better temporal correlation with observational data, but consistently experienced underestimates with a negative bias of up to -28%. These findings indicate that CHIRPS is more suitable for estimating rainfall volume after bias correction, while GSMaP is more useful for analyzing temporal variability. These validation results are expected to support the selection of more appropriate satellite rainfall data in water resource management and hydrometeorological disaster mitigation in the Riau Islands.

Item Type:	Thesis (Masters)
Uncontrolled Keywords:	CHIRPS; Curah hujan; GSMaP; Interpolasi IDW; Validasi satelit. CHIRPS; GSMaP; IDW Interpolation; Rainfall; Satellite Validation.
Subjects:	G Geography. Anthropology. Recreation > G Geography (General) > G70.5.I4 Remote sensing
Divisions:	Faculty of Civil Engineering and Planning > Geomatics Engineering > 29101-(S2) Master Thesis
Depositing User:	Surat man
Date Deposited:	28 Jan 2026 02:23
Last Modified:	28 Jan 2026 02:23
URI:	http://repository.its.ac.id/id/eprint/130850

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