Task 1.1   Choice of performance indicators PI

Major research is currently being carried out in international programmes to define appropriate performance indicators (PI) for water and wastewater systems. The project objective was to select and define those indicators to be used for the analyses of short-term as well as long-term rehabilitation needs. We distinguished between PI actually used today in decision making and PI that presumably should be used for decision making (relevant PI). Examples of PI were: Real losses per service connection, mains failure rate, annual renewal rate. Included were also PI that are defined by elected bodies, e.g. service complaint rate, water interruptions rate, continuity of supply rates etc.

Task 1.2   Test of performance indicators on cities

Based on the Performance Indicators (PI) selected in task 1.1, a test programme was carried out towards the co-operating cities, as well as other European cities. The programme included the collection of information on failure records and management systems from the co-operating cities. Additionally, a questionnaire was sent to a large number of other cities. This research comprised questions on existing planning systems and included the same questions on rehabilitation planning. Since this information was necessary for the development of the succeeding project activities the set of selected PI had to be accepted by the partners and the end-users. Two major aspects in the test programme were the water network databases and the condition of pipe materials. The inquiry did not only focus on data availability but also on the reliability and accuracy of the existing data.

Task 1.3   Predictable performance indicators

Based on the results from the test programme and questionnaire, a set of PI was selected for further use in the CARE-W system. The selected PI was of a static nature (e.g. length of asbestos cement pipe) or dynamic nature (e.g. real losses per service connection). The temporal development of some PI could be expressed as a function of explanatory variables. Those PI were of special interest because it could be assumed that they can be predicted and, in case they are also designated as relevant PI, be used to evaluate rehabilitation measures in term of the expected development of the respective PI.
The PI selected as being part of the control panel was defined and stored in an easy to use database, that also included the definitions and all the data variables used to assess the indicators. For each data variable not only their values but also their reliability and accuracy were stored, according to the criterion established by IWA.