Development of a smart system for evaluating gully and dam sediment interaction using a web-based R-shiny application in Benin City, Nigeria

Abstract

The Ikpoba Dam in Benin City plays a crucial role in water resource management but faces challenges due to sedimentation which reduces the storage capacity and impacts its functionality. This study develops a web-based R-Shiny application to evaluate gully and dam sediment interactions. Data were collected from two gullies contributing sediment to the dam and processed using a Coactive Adaptive Neuro-Fuzzy Inference System (CANFIS) for predictive modeling. The total sediment contribution from Uniben Gully was 802,698.328 m³, while Iguosa-Oluku Gully contributed 940,763.681 m³ over three years. The total annual sediment accumulation at the dam was 217,336.704 m³ (2017), 222,790.642 m³ (2018), and 400,000.000 m³ (2019). The R-Shiny application integrates real-time data visualization and model comparisons, with CANFIS achieving an RMSE of 0.57 for sediment
volume prediction and an R² of 93%. Results indicate that the tool effectively predicts sediment volume and sources thereby enhancing sediment management strategies. This study contributes to sustainable dam operations and aligns with Sustainable Development Goal 6 on clean water and sanitation.