Journal of Hydraulic Engineering

Fuzzy regression is used to investigate the modeling uncertainty in the prediction of bridge pier scour. Fuzzy bias factors, which describe the bias between observed field data and scour estimates based on equations developed from laboratory data, were estimated. The bias exists because of the use of small-scale laboratory results to model large-scale, real-world problems. Fuzzy regression is a method of calibrating fuzzy numerical coefficients in a linear equation. Since the regression coefficients are fuzzy parameters, the output, in this case scour depth, is also a fuzzy number. The fuzzy bias factors developed from the fuzzy regression equations are compared for a variety of input data. The fuzzy bias factor provides useful information in the application of bridge pier scour equations currently available to engineers. The results of this study can be used by experimentalists in the interpretation of small-scale laboratory test results and by practicing engineers to adjust scour estimates.

The friction-slope term in the unsteady open-channel flow equations is examined using two numerical models based on different formulations of the governing equations and employing different solution methods. The purposes of the study are to analyze, evaluate, and demonstrate the behavior of the term in a set of controlled numerical experiments using varied types and combinations of boundary conditions. Results of numerical experiments illustrate that a given model can respond inconsistently for the identical resistance-coefficient value under different types and combinations of boundary conditions. Findings also demonstrate that two models employing different dependent variables and solution methods can respond similarly for the identical resistance-coefficient value under similar types and combinations of boundary conditions. Discussion of qualitative considerations and quantitative experimental results provides insight into the proper treatment, evaluation, and significance of the friction-slope term, thereby offering practical guidelines for model implementation and calibration.

A one-dimensional numerical model describing the internal hydraulics of tunneled sea outfalls is reported. It includes some local two-dimensional techniques to take the effects of buoyancy and stratified flow into account based on an understanding of purging and intrusion phenomena. The model was verified with data collected from laboratory experiments. Effects of varying configuration, geometry, and hydrograph have been investigated in the model. It is concluded that head loss at riser ports, tunnel angle of inclination, and change in elevation of riser tops have significant effects on purging and intrusion characteristics. Any factor causing uneven velocity distribution among risers makes the system much more prone to intrusion. The operation hydrograph is an important factor affecting purging behavior.

When a cylindrical capsule moved by a liquid flowing in a pipe is stopped by the presence of an obstacle or protrusion on the pipe floor, the capsule may tilt in the pipe. This paper presents both an analysis and some experimental data to clarify and predict the minimum velocity required to cause capsule tilt. Capsules of three different aspect ratios and three diameter ratios were tested in a small (50.8 mm inside diameter) pipe loop. The experimental values of the capsule drag coefficient compared well with those from theory and a previous test. Data were used to calculate the lift moment coefficient and the critical tilt Froude number needed for predicting capsule tilt. Three large capsules with six different specific gravities were also tested in a large (190 mm inside diameter) pipe. Data for both small and large capsules showed good correlation between lift moment coefficient and tilt Froude number. It is shown that in some cases the capsule incipient velocity is governed by the critical tilt velocity.

In this paper, a bivariate model is established to characterize the seven-day, two-year (Q _7,2 ) and seven-day, 10-year (Q _7,10 ) low flows of streams in West-Central Florida under the restriction of Q _7,10 ≤ Q _7,2 . Analysis of prediction errors showed that our model describes these stream low flows well. The measurements under the detection limit were treated as censored data and a bivariate imputation method was developed to impute them into pseudo-complete samples. All-subsets regression was applied to these imputed data for selecting appropriate models, which link the low flows to their basin characteristics. The parameters are first estimated by the least-squares method in a bivariate normal regression and then adjusted to yield their maximum likelihood estimates. This process of imputation, model selection and parameter estimation is repeated iteratively until convergence of the selected model terms, parameter estimates, and imputed data. With the established model, predictions of low flows can be made at gauged and ungauged sites according to their basin variables for water-resources management.

Water-elevation variation in rivers can be large due to tides even far away from the coastline. For deep confined aquifers, the possibility of leakage from rivers is small. Nevertheless, the fluctuation of river elevation can induce a stress change in soil and in turn can induce ground-water flow below. The present study focuses on the effect of the fluctuation assuming the time scale for consolidation is much larger than that of the ground water. The total stress change in the deep confined aquifer affects the water-pressure head through deformable soil medium. If the subsurface profile contains only one dominant confined aquifer, a vertically averaged one-dimensional problem with periodic total stress change and constant line pumping is examined. The governing equation is a linear diffusion equation with time-varying forcing terms. Laplace transform and Fourier transform are invoked. The response distribution in space is of the error-function type. The pumping effect can be superimposed due to linearity. Away from the loading, deeper aquifers rather than those close to the ground surface are affected by the dynamic loading. Pressure peaks appear earlier for location farther away from the loading. Field data support the model.

Reliability analysis and other probabilistic techniques are becoming increasingly important tools in hydraulic modeling and decision making. Probabilistic and reliability analyses are based on knowledge of the underlying parameter uncertainties. Hydraulic variables, such as roughness coefficient, channel slope, and critical shear stress, common to many hydraulic-engineering problems, are known to contain considerable uncertainty. However, careful evaluation of the levels of uncertainty has not been conducted for many of these and other variables. Therefore, the underlying assumptions of uncertainty for a reliability-based design may be in error, causing significant error in the computed reliability or probability of failure. The main objective of the present study is to quantify various hydraulic parameter uncertainties in terms of the coefficients of variation and associated distributions. Significant advances are being made in reliability and probabilistic methods and their use in hydraulic and hydrologic engineering is rapidly increasing. If the uncertainties that underlie any of these methods cannot be properly defined, the results of the reliability analysis are inaccurate.