Abstraction index

Find further information on the Conservation of Freshwater Ecosystem Values (CFEV) Program and its data at www.dpipwe.tas.gov.au/cfev.

Attribute data

TitleAbstraction index

CustodianWater and Marine Resources Division, Department of Primary Industries, Parks, Water and Environment

CreatorGIS Unit, Information and Land Services Division, Department of Primary Industries and Water (DPIW)

DescriptionThe amount of change in volume of long term mean annual flow (‘yield’) due to the net effects of all abstractions and diversions of water.

Input data

  1. CFEV Mean Annual Run-off (MAR) attribute data
  2. CFEV River Section Catchments (RSC) spatial data
  3. Hydro infrastructure and discharge data (licensed abstractions), Hydro Tasmania
  4. Water Information Management System (WIMS) database, DPIW

Lineage

The flow abstraction index rates all RSCs according to the amount of change in volume of flow due to the net abstraction (removal) and diversion (into and out of the catchment) of water:

For every RSC, the sum of all abstractions and diversions within the upstream accumulated catchment (including the local RSC) was divided by the upstream accumulated natural MAR (RSC_AMARNT) for the RSC. The natural MAR (ML/year) was modelled for all RSCs.

Calculation of the abstraction index was undertaken in several steps. Net abstraction and diversion was calculated using data from the WIMS database (DPIWE 2005) (including all private and other licensed takes and diversions) and data from Hydro Tasmania using the following rules and subsequently divided by the natural MAR.

  1. Calculate the net abstractions for each RSC:
    1. Net Hydro Tasmania abstractions

      2. Use the upstream accumulated natural MAR (RSC_AMARNT) and the upstream accumulated current MAR (RSC_AMARNM) (both in ML/year) and calculate as:

      Net Hydro Tasmania abstraction = Natural MAR – Current MAR

    2. WIMS abstractions

      3. Assign ‘Period amount’ data (ML) from the WIMS database (the annual licensed allocation) to the RSCs containing point locations of WIMS licensed takes, noting that:

      1. WIMS ‘Purpose’ categories of Town and Water Supply, Fish Farm and Industrial are to be assigned to the RSCs with no adjustment.
      2. All other allocations are to be multiplied by 3.0 (see data limitations below for rationale).
    3. Other (non-Hydro and non-WIMS) (i.e. farm dams not in WIMS and other storages (e.g. mine tailings ponds, Lake Leake and Tooms Lake etc.))

      4. Calculated storage volume (ML) using SKM farm dam surface area/volume relationship:

      This equation was developed by analysis of relationships between farm dam volume and surface area, using the WIMS data for off-stream and catchment dams (n = 167, after reviewing and screening the data for unreliable and bad records). The relationship compared favourably against a similar relationship developed by Sinclair Knight Merz (SKM 2003; Lowe et al. 2005).

  2. Sum the values calculated in 1b + 1c and assign to each RSC.
  3. Accumulate the value (in rule 2) downstream (added values for all upstream RSCs) and then add in 1a to give total accumulated abstractions.
  4. Calculate the sum of net abstractions for all upstream RSCs and the local RSC (combined).
  5. Divide the sum of upstream net abstractions (value from rule 4) by the natural MAR (RSC_AMARNT). Assign value to each RSC.

The specific GIS rules for assigning river sections, waterbodies, wetlands and karst with an abstraction index are outlined below. The abstraction index has no units and ranges from a large negative number to a large positive number.

The abstraction index was considered to be high with regard to its impact on fluvial geomorphology when >0.50 (50% of MAR abstracted) or <-0.50 (increase in MAR by >50%), with medium impacts occurring between 0.1 and 0.5 (and -0.1 and -0.5), and negligible impact occurring between -0.1 and 0.1.

The abstraction index was initially considered to be high with regard to its impact on stream biota (macroinvertebrates and fish) when >0.75 (75% of MAR abstracted) or <-0.75 (increase in MAR by >50%), with medium impacts occurring between 0.5 and 0.75 (and, -0.5 and -0.75), and negligible impact occurring between -0.5 and 0.5. However, evaluation of the relationship between abstraction index and changes in summer (irrigation season) flows, when most abstractions occur, indicated that abstraction index values of >0.5 represented losses of >100% of summer flows. Hence the following ranges were adopted: high impact = low condition (>0.15 or <-0.15); moderate impact (0.05-0.15, or -0.05 to -0.15): low to no impact = high condition (-0.05 to 0.05).

Data limitations

The abstraction index is limited to mean annual estimates only. No smaller time scale resolution was possible due to data and modelling constraints.

Data quality was a significant issue in calculating this index. Diversion and abstraction data from Hydro Tasmania was taken as being reasonably accurate (certainly within 20%, M. Howland, Hydro Tasmania, pers. comm.). WIMS data on licensed takes and farm dams contained a number of major sources of error. Licensed take and dam locations were frequently erroneous, or not linked to the locations where they occurred. To partially overcome this, WIMS licensed takes were assigned to the RSC in which they fell rather than ‘snapped’ to a particular location on a drainage section.

A major source of error was that the WIMS database contains only licensed allocation data, with no confirmation that these amounts are complied with. Recent studies by the former DPIW (R. Phillips, DPIW, pers. comm.) within a number of Tasmanian catchments indicate that total takes are substantially greater than the sum of licensed takes. This exceedence can range between 2 and 6 times, with an overall average figure of around 3 times. A factor of 3 was applied to the sum of all WIMS licensed take figures (known as ‘Period amount’ in the WIMS database) to partially correct for these errors, with the exception of records associated with the following purposes: Town and Water Supply, Fish Farm and Industrial, which are deemed reasonably accurate.

Date createdOctober 2004

Scale and coverage1:25 000; Statewide

References

DPIWE. (2005). Water Information Management System. Department of Primary Industries, Water and Environment. http://wims.dpiwe.tas.gov.au/

Lowe, L., Nathan, R., and Morden, R. (2005). Assessing the impact of farm dams on stream flows, Part II: Regional characterisation. Australian Journal of Water Resources 9: 13-26.

SKM. (2003). Estimating available water in catchment using sustainable diversion limits. Farm dam surface area and volume relationship. Report to the Department of Sustainability and Environment. Draft B. Sinclair Knight Merz, Melbourne.

Column headingKT_ABSTI, RS_ABSTI, WB_ABSTI, WL_ABSTI

Type of dataContinuous but has been converted to categorical format (see Table 1).

Number of classesKarst = 6, Rivers = 8, Waterbodies = 6, Wetlands = 8

Assigning values to ecosystem spatial units

An abstraction index was assigned to river, waterbody, wetland and karst spatial units using the following rules. Note that the abstraction index may be negative (<0) if the result is a net increase in flow from inter-catchment transfers.

Karst (KT_ABSTI)

  1. Divide karst RSCs into two subsets: ‘big river catchments’ (those RSCs with an accumulated current MAR (RSC_AMARNM)>48.2 GL) and ‘small river catchments’ (all other RSCs). Note, more details on the rationale for the big and small catchment split are provided in the MAR section (Appendix 0).
  2. Calculate the abstraction index for ‘big river catchments’ by a MAR weighted average of all downstream-most catchments in the big river catchment group for each karst area as:

    3. Where:

    Big river abstraction index = Abstraction index for the karst spatial unit (only taking into account the RSCs of the karst local catchment which have RSC_AMARNM>42.8 GL)

    RSC_ABSTI (1…n) = Abstraction index for the RSCs of the karst local catchment which have RSC_AMARNM>42.8 GL

    RSC_MAR (1…n) = Current MAR value for the RSCs of the karst local catchment which have RSC_AMARNM>42.8 GL

    RSC_ACNMAR = Upstream accumulated current MAR value for the RSCs of the karst local catchment which have RSC_AMARNM>42.8 GL

  3. Calculate the abstraction index for ‘small river catchments’ by a MAR weighted average of all downstream-most catchments in the small river catchment group for each karst area as:

    4. Where:

    Small river abstraction index = Abstraction index for the karst spatial unit (only taking into account the RSCs of the karst local catchment which have RSC_AMARNM≤42.8 GL)

    RSC_ABSTI (1…n) = Abstraction index for the RSCs of the karst local catchment which have RSC_AMARNM≤42.8 GL

    RSC_MAR (1…n) = Current MAR value for the RSCs of the karst local catchment which have RSC_AMARNM≤42.8 GL

    RSC_ACNMAR = Upstream accumulated current MAR value for the RSCs of the karst local catchment which have RSC_AMARNM≤42.8 GL

  4. Assign all karst spatial units with an abstraction index as a weighted average of the big and small abstraction values as follows:
    1. Karst spatial units associated with both big and small catchments:

Where:

KT_ABSTI = Abstraction index of the karst spatial unit

Big river abstraction index = Abstraction index for the karst spatial unit (only taking into account the RSCs of the karst local catchment which have RSC_AMARNM>42.8 GL) (calculated in Step 2)

Small river abstraction index = Abstraction index for the karst spatial unit (only taking into account the RSCs of the karst local catchment which have RSC_AMARNM≤42.8 GL) (calculated in Step 3)

River sections (RS_ABSTI)

Assign the abstraction index of the RSC (as calculated above) directly to the river section it is associated with.

Waterbodies (WB_ABSTI)

Assign the abstraction index of the RSC (as calculated above) directly to the waterbody it is associated with.

Wetlands (WL_ABSTI)

  1. Add all abstraction indices for RSCs associated with the wetland spatial unit (making up the local wetland catchment).
  2. Assign the summed value to wetland spatial unit.

Each of the karst, river, waterbody and wetland spatial data layers had the continuous abstraction index data categorised according to Table 1. The categorical data was used for reporting and mapping purposes.

Table 1. Abstraction index categories for karst, rivers, waterbodies and wetlands.

Category

Karst

(Min to max values)

Rivers

(Min to max values)

Waterbodies

(Min to max values)

Wetlands

(Min to max values)

1

-117.0026368 to

<-0.4

-200852040 to

<-0.4

-3.5 to <-0.4

-14.7 to <-0.4

2

-0.4 to <-0.1

-0.4 to <-0.2

-0.4 to <-0.1

-0.4 to <-0.2

3

-0.1 to <0

-0.2 to <-0.05

-0.1 to <0

-0.2 to <-0.05

4

0 to <0.1

-0.05 to <0

0 to <0.1

-0.05 to <0

5

0.1 to <0.4

0 to <0.05

0.1 to <0.4

0 to <0.05

6

0.4 to 0.980860665

0.05 to <0.2

0.4 to 1.3

0.05 to <0.2

7

0.2 to <0.4

0.2 to <0.4

8

0.4 to 242327

0.4 to 15.1

CFEV assessment framework hierarchy

  1. Karst>Statewide audit>Condition assessment>Naturalness score (KT_NSCORE)>Hydrology (KT_HYDRO)
  2. Rivers>Statewide audit>Condition assessment>Naturalness score (RS_NSCORE)>Geomorphic condition (RS_GEOM)>Flow change (RS_FLOW)
  3. Rivers>Statewide audit>Condition assessment>Naturalness score (RS_NSCORE)>Biological condition (RS_BIOL)>Macroinvertebrate condition (RS_BUGCO)
  4. Waterbodies>Statewide audit>Condition assessment>Naturalness score (WB_NSCORE)>Hydrology (WB_HYDRO)
  5. Wetlands>Statewide audit>Condition assessment>Naturalness score (WL_NSCORE)>Hydrology (WL_HYDRO)