Groundwater abstraction

Groundwater abstraction from licensed bores in the Superficial and Leederville aquifers was modelled. Due to the lack of reliable metered data for the majority of bores, a dataset for

groundwater abstraction was synthesized from available information. Previous models for the study area have also experienced issues with estimating extraction and used synthesized datasets of abstraction in a similar manner as discussed below.

The DoW provided licensed abstraction in terms of the maximum volume of water that may be extracted annually from specified wells. The database contained information about the aquifer for licensed abstraction, bore depths and locations. The private licensed abstraction database includes data for Water Corporation bores. For some licenses, the location for abstraction and a listing of the number of licensed bores at the site was provided, rather than the spatial coordinates for individual bores. For these sites, the unknown bore locations were approximated by evenly distributing them across the site. As the database did not contain the screened intervals for individual bores, it was assumed that abstraction occurred over the entire thickness of the aquifer at each location. Groundwater use was assumed to be 80% of the allocation limits given in the license allocation database. This percentage was used in the models by Nield (1999) and Marillier et al. (2012a) as well as other modelling studies on the Swan Coastal Plain, which refer to original estimates between 1985 and 1995 from Davidson (1995). This approximation was not used in PRAMS 3.0; however, 20% of abstracted water was assumed to return to the Superficial Aquifer (CyMod Systems 2009), which in essence would achieve the same effect.

The licensed allocation database did not contain seasonal patterns of water use. According to a review of water use for licensed bores for the PRAMS model, the majority of licensed bores provide irrigation water, which has a strong season pattern (CyMod Systems 2009). This assessment was for the large area covered by PRAMS and may not be entirely applicable to the study area. However, in the model developed by Marillier et al. (2012b) monthly scaling factors from Sun (2005) were used based on estimates from different industries. Annual allocation was converted to a monthly abstraction rate using the scaling factors given in Table 8.6. This approach was adopted for this model as this was used for the Lower Serpentine model by Marillier et al. (2012 b), which overlaps with the catchment.

Table 8.6 Monthly scaling factors applied to annual allocation in Marillier et al. (2012b) that were applied in the CSC model

MONTH JAN FEB MAR APR MAR JUN JUL AUG SEP OCT NOV DEC

Scaling

The synthesized dataset for abstraction from 1990 to 2012 was anomalously low in certain years and the overall pattern of variations in annual abstraction did not correspond well to other estimates (Carey Johnston, Department of Water, pers. comm.). There were likely omissions in some of the files of licensed abstraction that were compiled to create the synthesized dataset. The likely underestimation of abstraction in the synthesized dataset was confirmed by comparing it with the abstraction data file for PRAMS 3.5, which showed total annual abstraction of approximately 40 GL for the study area from 2006 to 2012. Over the entire modelled time period (1990-2012), the dataset synthesized for the study contained about 4200 abstraction bores operating at different times, whereas PRAMS 3.5 models abstraction from about 790 bores. PRAMS 3.0 models abstraction from about 300 bores in the study area. The PRAMS model also locates abstraction bores at the spacing of the 500 m grid resolution rather than the geographic coordinates of individual bores. As the synthesized dataset for total abstraction in 2001 was 39 GL/yr, it was assumed that this was likely correct for that year. In that year, 1550 bores were licensed to abstract. Given the unreliability of the synthesized dataset of abstraction for the majority of the model years, it was decided to apply the abstraction estimates for 2001 to all of the years in the model. There was no assumed growth rate and the abstraction was modelled as constant in space. This approach is not an ideal

representation as bore locations have changed over time. To provide context for this estimate, it was compared with the sum of licensed entitlement volumes for the Kogalup, Thompsons, Valley and Wellard subareas that comprise the Cockburn Groundwater Area . The total of licensed entitlements for recent years, declined from 29.6 GL in 2009 to 28 GL in 2014 based on data from the Department of Water (Carey Johnston, Department of Water, pers. comm.). It should be noted that Kogalup extends 5 km north of the study area, and the data provided does not entirely cover the study area. It does not include the area that extends from Wellard to the south boundary of the study area (Rockingham GA) and the area between the four subareas and the east boundary of the study area.

Different approaches have been used in other models to hind-cast groundwater abstraction. In PRAMS 3.0, the year 1997 was identified as the time after which bore allocation records were most reliable. The abstraction for years prior to 1997 was modelled as constant in space with a 3% growth rate in time (CyMod Systems 2009). For the Lower Serpentine model, Marillier et al. (2012a) used the DoW’s allocation records to synthesize a representative, estimated history of abstraction and used licenced abstraction locations from 2011, which assumes abstraction locations did not vary through time.

Previous models of the area have either neglected or estimated unlicensed groundwater

abstraction. Unlicensed abstraction is permitted by the DoW from bores that abstract less than 1500 kL/yr. These are mostly private garden bores and are taken into account in a general manner in the DoW’s database when allocation limits and estimates are made. The groundwater model in Nield (1999) commissioned by the DoW (then, the Water and Rivers Commission) for their review of groundwater allocation in the Cockburn Groundwater Area did not include unlicensed groundwater abstraction. Marillier et al. (2012a) included unlicensed garden bores by assuming 30% of residential properties used 800 KL/yr. In the model for the Lower Serpentine (Marillier et al. 2012a), garden bores within each 200 m grid cell were lumped as a single drawpoint; however, licensed allocations of less than 1500 kL/yr were excluded from the model because the volume abstracted was

considered negligible. In PRAMS, estimates of abstraction by garden bores are included. Estimates were obtained from the DoW of the number of garden bores in each groundwater subarea.

Abstraction from these bores was implemented in PRAMS using recharge flux values calculated from the number of bores estimated in each subarea, and the average bore usage divided by the size of the area. Recharge flux is then scaled by irrigation coefficients (PRAMS 3.5 documentation from CyMod Systems, Neil Milligan, 2015).

The model developed for this study did not included unlicensed bore use as estimates were not readily available. Figure 8.6 shows the spatial coverage of land cover. In 2012, the proportion

categorised as urban residential was about 23% of the study area. Most private bores are likely to be located in the Rockingham area to the south because of the shallowness to the watertable and the large block sizes. Newly urban areas in the north and east, which MAR is more likely to affect, have small lot sizes and large houses making gardens very small and private bores of little value. The few bores that do occur in these areas may be offset by increased recharge from roofs and roads. Therefore their absence from the model is unlikely to cause a problem with estimating levels.

Figure 8.6 Estimates of land cover from Landsat images for 2012. About 23% of the study area was categorised as urban residential