The necessity of sewers to carry sediment has been recognized for many years. Typically, old sewage systems were designated based on self-cleansing concept where there is no deposition in sewer. These codes were applicable to non-cohesive sediments (typically storm sewers). This study presents adaptive neuro-fuzzy inference system (ANFIS), which is a combination of neural network and fuzzy logic, as an alternative approach to predict the functional relationships of sediment transport in sewer pipe systems. The proposed relationship can be applied to different boundaries with partially full flow. The present ANFIS approach gives satisfactory results (r2 = 0.98 and RMSE = 0.002431) compared to the existing predictor.

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Bridge pier scouring is a significant problem for the safety of bridges. Extensive laboratory and field studies have been conducted examining the effect of relevant variables. This note presents an alternative to the conventional regression-based equations (HEC-18 and regression equation developed by authors), in the form of artificial neural networks (ANNs) and genetic programming (GP). 398 data sets of field measurements were collected from published literature and used to train the network or evolve the program. The developed network and evolved programs were validated by using the observations that were not involved in training. The performance of GP was found more effective when compared to regression equations and ANNs in predicting the scour depth of bridge piers.

One of the best management practices (BMPs) for stormwater quality and quantity control is a bioretention system. The removal efficiency of different pollutants under this system is generally satisfactory, except for nitrogen which is deficient in certain bioretention systems. Nitrogen has a complex biogeochemical cycle, and thus the removal processes of nitrogen are typically slower than other pollutants. This study summarizes recent studies that have focused on nitrogen removal for urban stormwater runoff and discusses the latest advances in bioretention systems. The performance, influencing factors, and design enhancements are comprehensively reviewed in this paper. The review of current literature reveals that a bioretention system shows great promise due to its ability to remove nitrogen from stormwater runoff. Combining nitrification and denitrification zones with the addition of a carbon source and selecting different plant species promote nitrogen removal. Nevertheless, more studies on nitrogen transformations in a bioretention system and the relationships between different design factors need to be undertaken.

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The current study aims to verify the existing equations for incipient motion for a rigid rectangular channel. Data from experimental work on incipient motion from a rectangular flume with two different widths, namely 0.3 and 0.6 m, were compared with the critical velocity value predicted by the equations of Novak & Nalluri and El-Zaemey. The equation by El-Zaemey performed better with an average discrepancy ratio value of 1.06 compared with the equation by Novak & Nalluri with an average discrepancy ratio value of 0.87. However, as the sediment deposit thickness increased, the equation by El-Zaemey became less accurate. A plot on the Shields Diagram using the experimental data had shown the significant effect of the sediment deposit thickness where, as the deposit becomes thicker, the dimensionless shear stress θ value also increased. A new equation had been proposed by incorporating the sediment deposit thickness. The new equation gave improved prediction with an average discrepancy ratio value of 1.02.

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