Summary 1. An Index of Stream Condition (ISC) has been developed to assist broad scale management of waterways by providing an integrated measure of their environmental condition. 2. The ISC provides scores for five components of stream condition: (i) hydrology (based on change in volume and seasonality of flow from natural conditions); (ii) physical form (based on bank stability, bed erosion or aggradation, influence of artificial barriers, and abundance and origin of coarse woody debris); (iii) streamside zone (based on types of plants; spatial extent, width, and intactness of riparian vegetation; regeneration of overstorey species, and condition of wetlands and billabongs); (iv) water quality (based on an assessment of phosphorus, turbidity, electrical conductivity and pH); and (v) aquatic life (based on number of families of macroinvertebrates). 3. The ISC is intended for use by managers at state and regional levels and can be used to report on stream condition, assist with priority setting, judge the long‐term effectiveness of rehabilitation programs and assist with adaptive management. The best available scientific information was used by a multidisciplinary group of scientists and managers to create a stream assessment procedure that can be used routinely by people with limited scientific training. 4. ISC development included trials in four catchments in Victoria, Australia. Over 80 stream reaches were assessed and the results were used to refine the ISC to improve the ease of measurement and ensure that outcomes met the expectations of users. The ISC is now available to be used more widely for reporting on stream condition.

There is widespread application of indicators to the assessment of environmental condition of streams. These indicators are intended for use by managers in making various comparative and absolute assessments and often have a role in resource allocation and performance assessment. Therefore, the problem of formally defining confidence in the results is important but difficult because the sampling strategies used are commonly based on a compromise between the requirements of statistical rigour and the pragmatic issues of access and resources. It is rare to see this compromise explicitly considered and consequently there is seldom quantification of the uncertainty that could affect the confidence a manager has in an indicator.In this paper, we present a method for quantitatively assessing the tradeoffs between sampling density and uncertainty in meeting various monitoring objectives. Assessments using judgement-based representative reaches are shown to be unreliable; instead a sampling approach is recommended based on the random selection of measuring sites. A detailed dataset was collected along two streams in Victoria, Australia, and the effect of sampling density was assessed by subsampling from this dataset with precision related to the number of sites assessed per reach length and the intensity of the sampling at each site.The sampling scheme to achieve a given precision is shown to depend on the monitoring objective. In particular, three objectives were considered: (1) making a baseline assessment of current condition; (2) change detection; and (3) detection of a critical threshold in condition. Change detection is shown to be more demanding than assessing baseline condition with additional sampling effort required to achieve the same precision. Sampling to detect a critical threshold depends on nominating acceptable values of Type I and II error and the size of the effect to be detected.