Flood modelling is an effective way to manage the stormwater network in cities. It aims to understand and predict the behaviour of stormwater network so that it can test and evaluate effective solutions to structural and operational problems. So simulation modelling stays a preoccupation for building a successful hydraulic modelling in urban areas. This study investigates the impact of the design rainfall on the hydraulic modelling results for the Azzaba stormwater network located in the North-East of Algeria by using the Storm Water Management Model (SWMM). Four scenarios of design rainfall events were compared for 10, 25 and 50-year return periods, where we used double triangle and composite curves for the design rainfall event definition. The results show the impact of the choice of design rainfall on the behaviour of the stormwater network, from which the results of simulation by the double triangle method for the short durations represents a great risk on the probability that the stromwater network can overflow and flood the city, with a difference in peak discharge estimated at 62.97% and 58.94% for 2 h and 3 h events compared to the peak discharge simulated by the composite rainfall method.

Water plays an essential role in the everyday lives of the people. To supply subscribers with good quality of water and to ensure continuity of service, the operators use water distribution networks (WDN). The main elements of water distribution network (WDN) are: pipes and valves. The work developed in this paper focuses on a water distribution network rehabilitation in the short and long term. Priorities for rehabilitation actions were defined and the information system consolidated, as well as decision-making. The reliability data were conjugated in decision making tools on water distribution network rehabilitation in a forecasting context. As the pipes are static elements and the valves are dynamic elements, a Bayesian network (static-dynamic) has been developed, which can help to predict the failure scenario regarding water distribution. A relationship between reliability and prioritization of rehabilitation actions has been investigated. Modelling based on a Static Bayesian Network (SBN) is implemented to analyse qualitatively and quantitatively the availability of water in the different segments of the network. Dynamic Bayesian networks (DBN) are then used to assess the valves reliability as function of time, which allows management of water distribution based on water availability assessment in different segments. Before finishing the paper by giving some conclusions, a case study of a network supplying a city was presented. The results show the importance and effectiveness of the proposed Bayesian approach in the anticipatory management and for prioritizing rehabilitation of water distribution networks.