Reservoir Sedimentation Prediction in the Sangatta River: A Comparative Study of the Schoklitsch Method and HEC-RAS Numerical Modeling
Received: 6 November 2025 | Revised: 28 January 2026 | Accepted: 4 February 2026 | Online: 16 February 2026
Corresponding author: Lily Montarcih Limantara
Abstract
The Sangatta River in East Kalimantan plays an important role in water supply, transportation, and socio-economic activities of the nearby region. Intensive land-use changes and human interventions within the watershed have significantly increased sedimentation rates, leading to reduced river capacity and increased flood risk. This study aims to compare the estimation of sediment transport using the empirical Schoklitsch method and numerical modeling with HEC-RAS to evaluate their applicability and limitations in a tropical river system. Hydrological analysis was conducted using the Snyder Synthetic Unit Hydrograph (SUH) to obtain a 1-year return period flood discharge of 257.88 m3/s, which was applied as the dominant discharge for both approaches. The Schoklitsch analysis indicates substantial spatial variation in sediment transport, with sediment discharge ranging from 76.56 to 359,518.71 tons/day. Meanwhile, the HEC-RAS simulation produces sediment discharge values between 6,908.29 and 37,532.07 tons/day. The comparison shows that several river segments exhibit consistent estimates, with differences of less than 1%, while other segments show significant discrepancies exceeding 350%. These discrepancies highlight the limitations of empirical formulations in capturing local morphological controls and demonstrate the capability of numerical modeling to represent spatial variability in sediment transport. The findings indicate that the Schoklitsch method is suitable for rapid preliminary estimation, whereas HEC-RAS provides more reliable spatially distributed predictions to support sediment management and flood mitigation planning in the Sangatta River.
Keywords:
sedimentation, Schoklitsch, HEC-RAS, Snyder SUH, Sangatta RiverDownloads
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Copyright (c) 2026 Muhammad Muhir, Lily Montarcih Limantara, Moh. Sholichin, Sumiadi

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