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The influence of the weather parameters of temperature, wind and drought on pipe failure of drinking water distribution pipes was studied for the Netherlands. Several data sources were used relating weather effects to pipe failure: pipe failure data, regional weather data from different weather stations in the Netherlands, soil settlement data obtained from satellites and (modelled) pressure data. For asbestos-cement (AC) and cast iron (CI) pipes, temperature was an important factor. CI pipes showed increased pipe failures at low temperatures, which confirms results from previous studies, whereas AC pipes showed increased pipe failures at high temperatures. Pipe failure rates were higher for pipes that on average received higher internal pressures. This study also showed that wind resulted in additional pipe failures caused by uprooting of trees during a severe storm. With respect to drought, in some regions in the Netherlands, increased pipe failures during periods of drought were found. A small influence of soil settlement on pipe failure was found using remote-sensing techniques for a small area (5 × 10 km) in the Netherlands.

An ''all pipes'' hydraulic model of a drinking water distribution system was constructed with a bottom-up approach of demand allocation. This means that each individual home is represented by one demand node with its own stochastic water demand pattern. These water demand patterns were constructed with the end-use model SIMDEUM. A sensitivity test with respect to the resulting residence times was performed for several model parameters: time step, spatial aggregation, spatial correlation, demand pattern and number of simulation runs. The bottom-up approach of demand allocation was also compared to the conventional top-down approach, i.e. a single demand multiplier pattern is allocated to all demand nodes with the base demand to account for the average water demand on that node. The models were compared to measured flows and residence times in a small network. The study showed that the bottom-up approach leads to realistic water demand patterns and residence times, without the need for any flow measurements. The stochastic approach of hydraulic modelling, with a 15 minute time step, some spatial aggregation and 10 simulation runs, gives insight into the variability of residence times as an added feature beyond the conventional way of modelling.Key words 9 9 9 9 demand allocation, stochastic modelling, water quality modelling

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Traditional approaches to optimal water quality sensor placement in drinking water distribution networks can be limiting, because they are oriented towards obtaining information and mitigating effects. Approaches optimizing the utility's response to contamination merit wider study and application. The performance of these different approaches is studied and discussed in this paper. It is also shown that practical considerations can impose significant limitations on the performance that can be achieved by a water quality sensor network. These aspects should be taken into account when optimizing sensor placement in a real drinking water distribution network.