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Grass establishment on railway embankment steep slopes for erosion control in Central Queensland, Australia, is aided by drip lateral irrigation systems. The effective field values of the lateral parameters may be different from the manufacturer supplied ones due to manufacturing variations of the emitters, environmental factors, and water quality. This paper has provided a methodology for estimating drip lateral effective parameter values under field conditions. The hydraulic model takes into account the velocity head change and a proper selection of the friction coefficient formula based on the Reynolds number. Fittings and emitter insertion head losses were incorporated into the hydraulic model. Pressure measurements at some locations within the irrigation system, and the inlet discharges, were used to calibrate the lateral parameters in a statistical framework that allows estimation of parameter uncertainties using the Metropolis algorithm. It is observed that the manufacturer’s supplied parameters were significantly different from the calibrated ones, underestimating pressures within the irrigation system for a given inlet discharge, stressing the need for field testing. The parameter posterior distributions were found to be unimodal and nearly normally distributed. The emitter head loss coefficient distribution being very significant suggests the need to incorporate it into the hydraulic modeling. Although the example given in this paper relates to steep slopes, the methodologies are general and can be applied to any use of drip laterals. [ABSTRACT FROM AUTHOR]

A methodology for determining the optimal spatial distribution of a river pollutant detection network using a geographic information system and genetic algorithms (GAs) is developed. Two case studies are investigated to evaluate the performance of the developed methodology: (1) a hypothesized river system consisting of only 11 reaches; (2) the Logan and Albert Rivers in Southeast Queensland. Plausible results are obtained, encouraging the possibility of applying GAs in designing a river monitoring network. [ABSTRACT FROM AUTHOR]

This study investigates the performance of several existing automatic incident detection algorithms along the Central Expressway in Singapore and freeways in Melbourne, Australia. These algorithms were originally developed for freeways in the United States. Thus, it is of interest to evaluate how they would perform when applied to cities in other countries. The evaluation is carried out on two databases containing 160 and 100 incidents collected from Singapore and Melbourne, respectively. These databases reflect differences in vehicle detector system used to collect traffic parameters and in driver behavior. The following empirical findings were obtained: (1) the Minnesota and Standard Normal Deviate (SND) algorithms appear to possess transferable properties as well as being able to receive wide-area traffic measurements from a machine-vision vehicle detector system; (2) California Algorithm number 7 and the Double Exponential Smoothing algorithm performed poorly in Singapore but may be transferable to Melbourne freeways; and (3) no significant difference in average efficiencies between the better-performing algorithms (SND and Minnesota) on both databases. [ABSTRACT FROM AUTHOR]