Journal of Hydraulic Engineering

The SMEMAX Transformation was tested on samples generated from log‐Pearson Type III and Gumbel Extreme Value Type 1 distributions. Although the transformation results in a distribution with a skew near zero, it is not a true normal distribution. The coefficients of kurtosis for the transformed distributions are always less than three and when the parent distribution approaches a reverse‐J shape, the transformed distribution is bimodal. When the skew coefficient of the logarithms of events is $-0.5$ or greater for samples from the log‐Pearson Type III distribution, the SMEMAX procedure underestimates the magnitude of events with return periods of 50 yr and greater. Similarly, SMEMAX estimates of rare events from the Gumbel Extreme Value Type 1 distribution are always too low. Based on comparisons made in this study, it is likely that application of SMEMAX procedures to any skewed distribution will result in biased estimates of the magnitude of rate events and if the skew is positive the estimates will be too low.

The instability of hyperconcentrated flow observed in nature is reproducible in laboratory flumes using suspensions of bentonite. Similar instabilities are observed in a much simpler hydraulic system consisting of a container feeding a closed conduit. The behavior of two different clay suspensions, kaoline and bentonite, was investigated and the rheological properties were measured in a rotating viscosimeter. The result of the analysis is that the instability is associated with some specific rheological properties. By a simple mathematical model it has been explained why the bentonite suspension was unstable at small discharges and stable at sufficiently large discharges. The kaoline suspensions were always stable. The agreement between calculations and observations is encouraging.

Sedimentation as a diffusion process is described. The concerned differential equation is solved by a numerical method which can avoid numerical diffusion, therefore predicting more accurately removal ratios in settling basins. Also, concentration profiles and diagrams for dimensioning retarding basins can be computed for different initial and boundary conditions.

Ripple geometry provides a bed roughness which governs the bed shear stress and the profile of eddy viscosity or diffusion coefficient required for the description of the sediment concentration profile or rate of sediment transport. An analysis is made of ripple geometries using known tabulated laboratory and field data as well as water tunnel data obtained by the writer. Three different types of ripples can be identified: sand, light sediment, and oscillating bed ripples. They reflect different effects of the fluid shear stress and fluid acceleration on bed sediments. It is also shown that, when the bed shear stress or the amplitude of the water particle motion relative to the sediment size is small, the resulting vortices are more regular with low turbulence intensity, and the generated ripples are two dimensional; they are called growing or vortex ripples, which are strongly influenced by the amplitude of the water particle motion. At the other extreme, when the bed shear stress or the amplitude of the water particle motion relative to the sediment size is large, the resulting vortices are very irregular with high turbulence intensity, and the generated ripples are three dimensional; they are called decaying or turbulent ripples, which correlate well with the relative magnitude of the fluid shear stress and fluid acceleration.

A description is given and results presented of experiments to investigate the sediment capacity of stream flows on flume slopes of up to 20%. A comparison of the results with values predicted by the Meyer‐Peter Mueller equation shows that the latter equation seriously underestimates sediment transport capacity on slopes steeper than 3%, mainly because of deficiencies in the form resistance factor. A new equation is proposed, giving the transport capacity for materials with grain sizes larger than 0.4 mm (0.016 in.). The equation is calibrated by both the original Meyer‐Peter data and new steep flume experiments and modified to incorporate the effect of nonuniform sediment grain size distributions. With flow depths calculated by the Manning‐Strickler equation the new equation still gives excellent estimates of sediment capacity.

Simulation models have proven a durable and useful tool for the development of water resource system operating policies. One important component of any operating policy is streamflow forecasting. Incorporation of streamflow forecasts in a simulation model can be difficult because of the stochastic nature of forecasts and the range of forecast models in use. In this work, a forecast generation algorithm is developed which is applicable for any forecast model, and requires as input only the coefficient of prediction, a measure of forecast accuracy, and the first three moments of the forecast period flows. The algorithm uses a lag one Markov structure for forecast errors, where the correlation coefficient is a function of the forecast model coefficient of prediction. The generation algorithm is demonstrated for simulation of 7 and 120 day forecasts for the Skykomish River, Washington.

The peak flow hydrologic methods of the U.S. Soil Conservation Service (SCS) (as contained in their Technical Release No. 55) are widely used for planning and design on small urban watersheds. The urbanization factors of the TR‐55 methods (i.e., the lag factors for the graphical method and the peak factors for the chart method) were apparently not directly based on analyses of measured data and have not previously been systematically tested. Therefore, the objective of this study was to test the TR‐55 methods and recalibrate the urbanization factors if the methods were found to be biased. A data base was compiled for 51 small urban watersheds under 4,000 acres (1,600 ha) in the United States. The annual maximum flood series were used to develop Log‐Pearson Type III frequency curves, from which peak discharge rates were estimated for the following return periods: 2‐yr, 5‐yr, 10‐yr, 25‐yr, 50‐yr, and 100‐yr. The bias and accuracy of the SCS methods were evaluated using the Log‐Pearson Type III estimate as the expected true value. The results indicate that no urbanization correction factors are needed for the graphical methods when time of concentration is determined using the velocity method. Modifications to the urban adjustment factors used in the chart method are proposed.

A hybrid modeling method for predicting waterway sedimentation was developed and applied to the Columbia River estuary. The method uses physical hydraulic models, two dimensional (2‐D) numerical models, and analytical techniques in an integrated solution scheme. The hybrid modeling system used to study the Columbia consisted of a large physical model of the estuary, RMA‐2V, a depth‐integrated numerical model for sediment transport, and a collection of analytical methods. By using each method to address those phenomena that it is best able to describe, an improved modeling technique is created.

Experiments involving measurements of the bed load transport rates of different fractions in a mixture are reported. A conceptual model for the effect of a particular size of sediment on the transport rates of other sizes of sediment is proposed. The experimental data are analyzed with the dual objectives of assessing the accuracy of existing methods of computation of bed load transport and of proposing a new method of computation.

A method of approximating the solution of the Laplace equation in two‐dimensions is presented. The numerical approach is to determine a complex variable polynomial which satisfies the specified boundary conditions along a simple closed contour. Since the method is simple to apply to time‐stepped, quasi‐steady state saturated ground water problems or moving boundary problems, a significant savings in computational effort over other boundary integral equation methods is available. Applications to a free water surface problem and a moving boundary problem are presented. Error bounds and model stability are considered.