The term 'unregulated river' applies to rivers without major storages, or dams, as well as to rivers where the storages do not release water downstream (in these cases, water is piped to where it is needed, such as metropolitan centres).

A large number of unregulated rivers are covered by water sharing plans. The Office of Water aims to have all unregulated rivers covered by 2011. Unregulated rivers covered by water sharing plans are monitored to check that environmental flow rules in the plans are benefiting the river.

Project aims

The first aim of ecological monitoring is to determine whether the environmental objectives of the water sharing plans are being achieved.

The second aim is to demonstrate how achievement (or non-achievement) of these objectives is related to the plan strategies. For example, factors such as climate change and land use may affect the condition of a river, and monitoring programs must be able to discriminate between plan and non-plan related impacts.

Design challenges in monitoring unregulated rivers

Environmental water provisions in the unregulated river water sharing plans are different to those for regulated rivers. Generally, in unregulated rivers the environmental flow rules consist mainly of annual extraction limits and 'cease to pump' levels which prevent pumping when river flow drops below a specified level.

The protection of these low flows is important to the survival of many aquatic species.

Our understanding of hydrology and water extraction in unregulated streams is limited, as we tend not to use a predictive modelling approach so often employed when monitoring regulated rivers. Instead, we compare randomly chosen sites on the river affected by water extraction with physically matched reference sites on rivers unaffected by extraction (known as 'positive' reference sites). The use of reference sites enables changes due to plan implementation to be distinguished from natural changes and changes due to other human influences.

Selection of attributes for monitoring

Measuring trends in attributes with respect to reference conditions is the main way in which the benefits of the environmental rules are monitored and it is vital that the right ones are selected. To refine the selection process, we make use of conceptual models. One such conceptual model is shown below, illustrating how an attribute such as tadpoles can be logically selected by following the linkages through the ecosystem.

Conceptual model: Ecosystem responses to upstream water extraction in rivers under medium–flow and high-flow conditions (freshes and floods). Responses will vary with natural discharge patterns and the timing, frequency and magnitude of extraction.

Conceptual model: Ecosystem responses to upstream water extraction in rivers under medium–flow and high-flow conditions (freshes and floods). Responses will vary with natural discharge patterns and the timing, frequency and magnitude of extraction

No matter what attributes are selected, they must have:

  1. Relevance: Attributes must be relevant to the various types of environment, flow classes and ecosystem properties included in the objectives of the plans.
  2. Sensitivity: Attributes must be relevant to the various types of environment, flow classes and ecosystem properties included in the objectives of the water sharing plans.
  3. Practicality: Attributes must be measurable in a repeatable and representative manner with the resources that are likely to be available.
  4. Interpretability: It must be feasible to distinguish the response of the attributes to water extraction, and ideally to plan strategies, from their responses to other factors.

For more details on the framework and design of the monitoring program, see Program framework for ecological monitoring and reporting of water sharing plans for unregulated rivers – scoping paper (PDF 1.1 MB).

Journal articles

Brooks A.J., Chessman B.C. and Haeusler T. (2011). Macroinvertebrate traits distinguish unregulated rivers subject to water abstraction. Journal of the North American Benthological Society 30, 419-435. doi: 10.1899/10-074.1