The problem of bursts and leakages in water distribution systems has received significantly increased attention over the past two decades. As they represent both an environmental and an economical issue, how to reduce water loss through bursts and leakages is a challenging task for water utilities.Consequently, various techniques have been developed to detect the location and size of leakages.The methods for bursts (or leaks) detection and location can be broadly divided into two main categories, one based on hardware and the other based on software. Hardware-based methods include (i) acoustic detection methods such as listening rods, leak correlators, leak noise loggers and (ii) non-acoustic detection methods such as gas injection, ground penetrating radar technology and infrared photography. Software-based methods make use of the data collected by real-time pressure and/or flow sensors and several artificial intelligence techniques and statistical data analysis tools, including (i) methods based on numerical modeling methods, such as inverse transient analysis, time domain analysis and frequency domain analysis, and (ii) some non-numerical modeling methods, such as artificial neural networks, Bayesian inference systems, the Golden section method, and Kalman filtering. In this article, the authors describe the methods for pipe network burst location and detection, summarize the features of each method, and propose a suggestion for future work.

No abstract

No abstract

No abstract

The determination of locations and sizes for such a system is important in a drainage master plan or a storm-water management system. However, the distribution of detentions in the upstream and midstream is often more dispersed using many combinations of volume scales. This paper uses the non-dominated sorting genetic algorithm combined with the Storm Water Management Model to explore and calculate the optimal layout scheme for decentralized rainwater detention. The purpose is to find a design and planning method that can achieve the optimal balance of decentralized detention considering the aspects of flood disaster control, peak flow reduction, and investment cost. The optimal results of Pareto in applied case show that among the five most unfavourable nodes, the detentions with different layout volumes and relatively smaller size can control water logging from rainstorm. The project cost is effectively reduced and the standard of the return period of the regional rainwater system is enhanced from 2 to 20 years.

Quantification of spatial and temporal patterns of rainfall is an important step toward developing regional water sewage models, the intensity and spatial distribution of rainfall can affect the magnitude and duration of water sewage. However, this input is subject to uncertainty, mainly as a result of the interpolation method and stochastic error due to the random nature of rainfall. In this study, we analyze some rainfall series from 30 rain gauges located in the Great Lyon area, including annual, month, day and intensity of 6mins, aiming at improving the understanding of the major sources of variation and uncertainty in small scale rainfall interpolation in different input series. The main results show the model and the parameter of Kriging should be different for the different rainfall series, even if in the same research area. To the small region with high density of rain gauges (15km 2), the Kriging method superiority is not obvious, IDW and the spline interpolation result maybe can be better. The different methods will be suitable for the different research series, and it must be determined by the data series distribution.

No abstract

No abstract