Journal of Hydraulic Engineering

Fast and stable mathematical models for the computation of sewer system outflow are essential for real-time control of urban storm drainage systems. This paper presents a general method to design such models based on the reservoir approach. The unknown inflow-outflow function is developed into a power series. The a priori assumptions made for this are much weaker than the ones for the well-known linear models. The resulting models are nonlinear, but they subsume some of the linear models, depending on the selection of model parameters. Thus, a more general approach to validate the frequently made linearity postulation of the outflow process is provided. The new model is tested with some subcatchments of a larger urban storm drainage network.

It is common for aggrading deposits of sediment mixtures to show a pattern of downstream fining, whereby characteristic grain size becomes finer in the streamwise direction. Although various factors may contribute to this phenomenon, it can often be explained largely or solely in terms of the variation of grain mobility with grain size in sediment mixtures. That is, finer grains exposed on the surface are typically somewhat more mobile than their coarser neighbors, resulting in preferential transport of finer grains. Experiments reported here, document a reversal in this familiar pattern at slopes in excess of 0.02–0.03. At these higher slopes aggrading and prograding deposits are observed to show downstream coarsening in geometric mean size, indicating a mobility reversal associated with preferential transport of the coarser grains. This rather curious behavior is explored herein.

This is the second of two papers about experiments on downstream fining of gravel. Here we briefly summarize the complete series of runs described in the first paper, where the influence of sediment feed rate was evaluated in a narrow channel. We then present results for variation in two more conditions: sand content and channel width. The experiments were carried out in a long flume with an effective 40-m-long test section, with two different widths of 0.3 and 2.7 m. In addition, two sediment mixtures were used with different sand contents (i.e., 33 and 55%) with the remainder being gravel. The following results were obtained. The increase in channel width allowed the formation of transverse topography, enhanced the development of sediment patches, and increased the fining rate of gravel for D₅₀ and finer percentiles. Increasing sand content rendered the long profile of the bed much more concave, caused marked patch development, and most notably increased the fining rate for all percentiles of gravel-sized bed material.

This paper presents a generalized version of the binary velocity distribution law, which combines the logarithmic law of the inner region with the parabolic law of the outer region. This combination is extended for cases of flow where the maximum velocity occurs at some distance below the free surface in a vertical. The study uses the data collected at the Indian Institute of Science over a long period for all of the four regimes of turbulent open channel flow, namely, subcritical smooth, supercritical smooth, subcritical rough, and supercritical rough. The various conditions and limitations at the junction point of the inner and outer region are derived and discussed in this paper. It is shown that the velocity distribution for the flows of narrow open channels can be described by the logarithmic law for the inner region and the parabolic law for the outer region, but the conditions at the junction point will not always be the same.

Theoretic concepts of basic Shannonian information are discussed with special reference to the setting up of relatively simple small-scale computational hydraulics models. It is argued that often the relative mutual information between two distributions, I(X; Y)/S(X), may be a simple, versatile, robust, and approximately consistent quantitative estimate of the degree of fit between measurements (X distribution) and model results (Y distribution). It is proposed that the quantity be named the confluence, Å, and test results are presented in support of its practical utility.