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Hydrological modeling of small coastal peat island in degraded peatlands of Bengkalis Island, Riau Province Sutikno, Sigit; Yusa, Muhamad; Rinaldi, Rinaldi; Muhammad, Ahmad; Saputra, Hendra; Wardani, Khusnul Setia; Yamamoto, Koichi
Journal of Degraded and Mining Lands Management Vol. 13 No. 1 (2026)
Publisher : Brawijaya University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15243/jdmlm.2026.131.9163

Abstract

Small coastal peat islands such as Bengkalis (Riau, Indonesia) are hydrologically sensitive systems where groundwater level (GWL) controls ecosystem stability. Both extremes are hazardous: prolonged low GWL elevates peat-fire, subsidence, and carbon-loss risks, while excessively high GWL can trigger bog-burst. This study developed a simple empirical model to predict daily GWL in degraded peatlands on Bengkalis Island using in situ GWL data from three sites (drained, undrained inland, and undrained coastal) and GPM satellite rainfall (October 2023-April 2025). Calibrated over one year and validated over the next seven months, the model performed well at drained and coastal sites (R ~0.82, MAPE ~14%), capturing seasonal dynamics. In contrast, its performance at the inland site was lower (R ~0.5) due to minimal water table fluctuation. Coefficient values indicate the strongest rainfall response and fastest losses at the drained site, negligible daily loss at the inland site, and intermediate behavior at the coastal site. Scenario simulations highlight management-relevant risks: 15 rain-free days cause GWL to drop below the critical -0.40 m fire-risk threshold at the drained site and coastal site, whereas undrained inland remains just above it; conversely, 60 mm/day of rain for four days can raise GWL to the surface at coastal site (bog-burst risk). The model provides a practical tool for informing rewetting strategies to manage fire and collapse risks in degraded tropical peatlands.
Predictive model for California Bearing Ratio (CBR) in expansive coastal subgrades: a rapid geotechnical assessment for degraded and marginal lowland areas Nugroho, Soewignjo Agus; Satibi, Syawal; Putra, Agus Ika; Zulkifli, Zulkifli; Sutikno, Sigit; Yusa, Muhamad; Rinaldi, Rinaldi; Yamamoto, Koichi
Journal of Degraded and Mining Lands Management Vol. 13 No. 1 (2026)
Publisher : Brawijaya University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15243/jdmlm.2026.131.9329

Abstract

In geotechnical engineering, professional actions and expert judgment are often essential in soil investigation methods. In lowland and coastal areas, expansive, fine-grained soils and sandy sedimentation lead to reduced bearing capacity, posing significant challenges for sustainable infrastructure development on marginal and degraded lands. Such conditions are prevalent in post-mining or naturally poor coastal environments, necessitating cost-effective and rapid assessment tools. This study modeled a clayey sand mixture using bentonite and kaolin as fine fractions, which exhibit expansive behavior and poor gradation, simulating worst-case geotechnically degraded subgrades. The mechanical behavior of the soil was evaluated through modified compaction, using the CBR test and CPT test as bearing capacity parameters. Soil mixtures were simulated with sand fractions ?65% and bentonite-kaolin compositions with ?50% bentonite. Compaction was modeled using variations in energy compaction and water content under conditions below the maximum dry density. CBR prediction was conducted using Qc as the primary predictor and dry density as a supporting predictor. A hybrid stepwise regression analysis in the         Z-score scale identified positively correlated predictors: +3.00 (Qc), +0.55 (?dry), and +1.28 (Qc ?dry interaction). The regression model showed strong statistical performance with R² = 0.84 and high significance with the lowest p-values. The resulting regression equation offers an applicable approach to rapidly evaluate the bearing capacity of subgrade soils in degraded coastal or marginal conditions, thereby facilitating geotechnical engineering design and initial site assessment crucial for land management and rehabilitation actions.
Spatial and temporal analysis of wild peat fire on island peatlands using remote sensing data Sutikno, Sigit; Hidayati, Nur; Ahmad Muhammad; Qomar, Nurul; Yamamoto, Koichi
Journal of Degraded and Mining Lands Management Vol. 13 No. 3 (2026)
Publisher : Brawijaya University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15243/jdmlm.2026.133.10773

Abstract

Indonesia has the largest areas of tropical peatland, which is becoming vulnerable to fires. Smoke haze crises due to forest fires that occur annually have plagued many parts of Southeast Asia between 2013-2015 with devastating effects on human health and economy. Fires spread fast on island peatlands in eastern Sumatra because their small catchments drain quickly into the sea. This research dived into the spatial and temporal patterns of peat wildfires in the Peat Hydrological Unit of Bengkalis Island. Drawing on remote sensing sources such as MODIS-C6 Terra/Aqua thermal hotspots from 2001 to 2020 and Landsat images, the findings revealed two clear yearly fire peaks in Bengkalis: Period I (January-March) and Period II (June-August). Hotspot density was concentrated in deep peat areas 57.3% of detections are from the 500-700 cm thickness class, and 93.1% from peat >300 cm. During 20 years, 343 fire-days burned a total of 56,202 ha; the largest single occurrence involved a burnt area of 19,999 ha in 2014. Monthly rainfall is the dominant climatic control, exhibiting a clear inverse relationship with hotspot frequency; rainfall below 100 mm/month defines elevated fire-risk conditions. These findings establish that MODIS hotspot monitoring combined with Landsat burned area mapping provides a robust long-term fire assessment framework, and that rainfall thresholds offer a practical operational basis for fire early warning systems on island peatlands.