Slope Stability Analysis of Main Irrigation Canals Due to Rapid Drawdown Fluctuations Using Numerical Modeling
DOI:
https://doi.org/10.69855/sipil.v2i1.499Keywords:
irrigation canal stability, rapid drawdown, pore water pressure, finite element method, factor of safetyAbstract
Rapid drawdown conditions frequently threaten the stability of irrigation canal embankments, especially in cohesive alluvial soils with low hydraulic conductivity. This study investigated the effect of water level recession rates on embankment stability and identified safe operational drawdown limits for irrigation infrastructure. A quantitative numerical modeling approach based on the Finite Element Method (FEM) and transient seepage analysis was applied using secondary geotechnical data obtained from the Ministry of Public Works and Housing (PUPR), Indonesia. The model integrated coupled seepage-stability analysis with the Mohr-Coulomb failure criterion to evaluate pore water pressure behavior, deformation, and Factor of Safety (FoS) under drawdown rates ranging from 0.0 to 2.0 m/day. The results showed that delayed pore water pressure dissipation during rapid drawdown significantly reduced effective stress within the embankment. Higher drawdown rates progressively decreased slope stability, where the FoS declined from 1.68 under normal conditions to 1.05 at a drawdown rate of 2.0 m/day. The simulation also identified lateral deformation of approximately 0.18 m near the embankment crest under critical conditions. Statistical analysis indicated that soils with hydraulic conductivity lower than 1 × 10⁻⁷ m/s were highly vulnerable to rapid drawdown failure. The findings demonstrate that drawdown rates exceeding 1.0 m/day do not satisfy the minimum safety criterion of 1.25 required by Indonesian irrigation standards. Therefore, a maximum operational drawdown rate of 0.75 m/day is recommended to maintain embankment stability. This study emphasizes the importance of incorporating transient hydraulic behavior into irrigation canal management and supports future implementation of IoT-based pore pressure monitoring systems for adaptive infrastructure safety.
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