Geographic pattern of river water clarity

  • Image, Geographic pattern of river water clarity.

    Archived 27 April 2017

    Water clarity is a measure of underwater visibility in rivers and streams. It varies geographically due to the influence of land use, climate, slope, and geology. Fine particles like silt, mud, and organic material can reduce the clarity of water. Water clarity affects the habitat and food supply of aquatic life such as fish and aquatic birds. It can also impact on the aesthetic values and recreational use of rivers and streams.

    We classified Geographic pattern of river water clarity as a case study.

    Key findings

    Over the 2009–13 period, median water clarity was greatest (2.6m) at sites where the dominant land cover was indigenous. This compares with sites in catchments where the dominant land cover was exotic forest (1.7m), urban (1.5m), or pastoral (1.1m).  

    Figure 1

    Water clarity median and trends – interactive map

    Figure 2

    Note: The ends of each ‘box’ in the box-plot are the upper and lower quartiles (25 percent) of the sites are either higher or lower than these values). The top and bottom ‘whiskers’ represent the highest and lowest value. The middle line of the box represents the median (middle) data point (half the sites are above and half below this value). The ANZECC 2000 guidelines recommend a minimum trigger value of 0.6 metres for lowland rivers and 0.8 metres for upland rivers. The guidelines recommend that rivers with water clarity below these levels be actively managed. Nationally, the proportion of river length classified as predominantly urban is 0.8 percent; pastoral, 45.8 percent; indigenous forest, 47.7 percent; and exotic forest, 5.6 percent.

    Definition and methodology

    Water clarity is measured by placing a black disc in the water. The disc is viewed horizontally through an underwater periscope at increasing distances, until it disappears from sight. This method provides a consistent measure of the greatest distance an object is visible through the water (Davies-Colley, 1988).

    Data are from 454 river sites monitored by NIWA and the 16 regional councils.

    Sites were classified by land cover using the River Environment Classification (Snelder & Biggs, 2002).

    About 48.4 percent of New Zealand’s river length is fed by catchments that are mainly influenced by indigenous land cover, while 45.7 percent are influenced mainly by pasture, 5.1 percent by exotic forest, and 0.8 percent by urban land cover.

    Regional councils monitor river water quality to manage environmental impacts. These sites tend to be in catchments dominated by agricultural land use. Rivers in most areas, particularly low-lying and hilly areas in the North and South islands, are well represented, while mountainous areas in the South Island and parts of the central North Island are not well represented.

    If you want detailed regional-level information, we recommend you review the relevant regional council’s environmental reports.

    This is because although our data are sourced from regional councils, we adjust some datasets to ensure our reports are nationally consistent. The adjustments may include omitting information produced by non-comparable methods. As a result, our evaluations may differ from those produced by regional councils.

    Data quality

    We classified Geographic pattern of river water clarity as a case study.

    Relevance

    relevance-partial This case study is a partial measure of the ‘Condition and physical characteristics of freshwater habitats’ topic.

    Accuracy

    accuracy-medium The accuracy of the data source is of medium quality.

    See Data quality information for more detail.

    References

    Davies-Colley, RJ (1988). Measuring water clarity with a black disc. Limnology and Oceanography, 33(4), 616–623. Accessed 18 August 2015 from www.horizons.govt.nz.

    Snelder, T & Biggs, B (2002). Multiscale river environment classification for water resources management. Journal of the American Water Resources Association, 38(5), 1225–1239.

     

    Published 21 October 2015

Top
  • Share this page
  • Share this page to Facebook
  • Share this page to Twitter
  • Share this page to Google+