Improvement of The Observation Method to Predict Meander Migration by Using A Probabilistic Analysis
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River meander migration is a product of fluvial activities including erosion and deposition. It may cause problems if it is close to vital infrastructure and its migration rate is noticeable for design life of infrastructure. Different methods to predict meander migration have been proposed. However, most of them do not integrate all general components of meander: geometry, flow, and soil. The Observation Method for Meander (OMM) is a prediction method which is developed by accommodating those components. River geometry is represented by past river movement from aerial photos or map observation, river flow is represented by discharge data from United States Geological Survey, and soil properties are represented by erosion function parameters obtained from erosion tests. This method results critical velocity in the field and soil parameters to create calibrated and observed migration versus time plot. For future prediction, the previous OMM used deterministic analysis which results in a single precise predicted migration. By including probabilistic method, uncertainty that might exist in the prediction is considered. Eight meanders in Brazos River near City of Sugar Land were selected for this study. The prediction was conducted for next 30 years. Deterministic prediction was carried out by using the same method of the previous OMM. Probabilistic prediction was carried out by generating 100 equally possible future flows from statistical parameters of the past flow. A code was written in a single MATLAB code to do calibration, deterministic prediction, and probabilistic prediction. The results showed that there was a slight difference between deterministic and probabilistic prediction.
Haniffa, Mifrokhah (2019). Improvement of The Observation Method to Predict Meander Migration by Using A Probabilistic Analysis. Master's thesis, Texas A&M University. Available electronically from