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All Journal Jurnal Penelitian Pendidikan IPA (JPPIPA) Journal of Renewable Energy, Electrical, and Computer Engineering
Heri Sulistiyono
Universitas Mataram
Agriculture, Biological Sciences & Forestry Biochemistry, Genetics & Molecular Biology Chemical Engineering, Chemistry & Bioengineering Chemistry Computer Science & IT Control & Systems Engineering Education Electrical & Electronics Engineering Energy Engineering Materials Science & Nanotechnology Physics

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Calibration and Evaluation of GPM Satellite Rainfall for Estimating Annual Maximum Rainfall at Ungauged Sites in the Rea Watershed I Gusti Ngurah Ketut Udara; Heri Sulistiyono; Hartana
Jurnal Penelitian Pendidikan IPA Vol 12 No 3 (2026)
Publisher : Postgraduate, University of Mataram

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29303/jppipa.v12i3.14532

Abstract

Limited rain gauge coverage and uneven station distribution remain major challenges for hydrological analysis in ungauged watersheds. This study calibrated and evaluated GPM IMERG satellite rainfall for estimating annual maximum daily rainfall (AMS) in the Rea Watershed, Indonesia. AMS data from four rain gauge stations (Tepas, Taliwang, Seteluk, and Pototano) were used as ground observations, while nine GPM grid cells represented spatial rainfall over the watershed. A rainfall-range-based multiplicative correction was applied using gauge–satellite AMS pairs. Performance was evaluated using Percent Bias (PBIAS), Root Mean Square Error (RMSE), Mean Absolute Error (MAE), and Sum of Squared Errors (SSE), followed by leave-one-station-out (LOSO) validation. Uncorrected GPM data showed systematic underestimation, with PBIAS of -17.7%, RMSE of 66.64 mm, and MAE of 48.67 mm. After optimized correction, PBIAS shifted to +13.8% and MAE slightly improved to 47.97 mm, but RMSE increased to 75.82 mm and SSE to 201,213 mm2. These results indicate that the correction reduced bias but did not improve overall accuracy. LOSO validation produced RMSE values of 50.83-72.13 mm, indicating sensitivity to station omission. Overall, GPM rainfall can support preliminary AMS estimation in ungauged areas, but its application should be treated cautiously because of persistent uncertainty in extreme rainfall estimation.
Image Processing of Sentinel-1A Data for Ground Displacement Monitoring and Landslide Hazard Assessment in Rinjani Area Ramdani Saputra; Heri Sulistiyono; Teti Zubaidah
Journal of Renewable Energy, Electrical, and Computer Engineering Vol. 6 No. 1 (2026): March 2026
Publisher : Institute for Research and Community Service (LPPM), Universitas Malikussaleh, Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29103/jreece.v6i1.23006

Abstract

Landslides are a persistent geological hazard, especially in seismically active and high-rainfall regions such us Lombok Island, Indonesia. This study addresses landslide susceptibility in Sembalun Bumbung Village, located within the Rinjani Area, by integrating ground displacement monitoring with multi-parameter spatial analysis. Advanced image processing techniques were applied to Sentinel-1A Interferometric Synthetic Aperture Radar (InSAR) data, specifically processed using Differential Interferometric Synthetic Aperture Radar (DInSAR) technique, to observe and quantify annual ground displacement from 2019 to 2024. Simultaneously, a landslide susceptibility map was developed through the analysis of five key environmental parameters: rainfall, rock type, slope gradient, land cover, and soil type; each weighted and scored based on their empirical contributions to landslide risk. The DInSAR analysis revealed annual ground displacement values ranging from 0.030 to 0.105 meters, with the highest rates detected at points T6 and T7 in Benyer Hamlet. The resulting landslide susceptibility map categorized areas into five susceptibility levels (very low, low, moderate, high, and very high). Notably, points exhibiting a very high susceptibility (e.g., T1 in Bebante Daya Hamlet, T2 in Jorong Utara Hamlet, as well as T6 and T7 in Benyer Hamlet) consistently correlated with the highest annual displacement values observed from the DInSAR analysis. This integrated approach offers a solid basis for targeted mitigation strategies, including enhanced monitoring, risk communication, land-use planning, and potential early warning systems.
Co-Authors Hartana I Gusti Ngurah Ketut Udara Ramdani Saputra Teti Zubaidah