This document summarizes water scarcity issues in Australia. It finds: 1) Water resources are unevenly distributed, with more in the north and less in the populated south, exacerbating scarcity. 2) A multi-criteria analysis was used to assess water stress levels across regions, considering population, water usage, flow, and precipitation. 3) The analysis found the highest stress levels in the most populated southeast regions like Sydney and Melbourne, which have high water demand but lower renewable supplies.

1. Water Scarcity in Australia
2016
SYRENA LY CHAN
UNIVERSITY OF SOUTHAMPTON |

2. 1.Introduction:
Fresh and renewable water scarcity is a growing concern, addressing great consideration on
the accuracy of indicators which used to characterize and highlight the vary water scarcity
level over the world. Numbers of indices in classifying the significance of water shortage are
presented and applied in some water resource assessment (Asheesh,2003; Alcamo, 2000;
Gleick, 1996; McNulty et al., 2010; Raskin et al., 1997 ), such as the Australia Water
Resource Assessment (AWRA) modelling system (Elmahdi et al., 2015). In 2004, the National
Water Initiative introduced a blue print for water reforms in Australia (Hoekstra et al.,
2012). Multiple concomitant pressures have been identified as causes inducing to water
scarcity, such as population growth, agricultural and industrial water withdraw, surface
runoff and topographical effects (Vaze et al., 2013).
In a review of water scarcity indices and mythologies (Brown and Matlock,2011), and their
application, about three out of five water scarcity indices are applicable to assess Australia
water resources. This report depicts the areas in Australia where are suffering water
shortage and are vulnerable to water scarcity. Two major outputs show the national water
stress level (WSL), the first one is created with the Falkenmark Indicator and secondly a map
shows an alternative stress level which created by weighted multi-criteria assessment.

3. 2.Renewable Water Resource in Australia
Australia has been facing two major problems as limited renewable water resources and
economic scarcity exacerbated by the uneven distribution of water, relatively abundant in
the less populated north but more scarce in the densely populated south region (King,
2012); the extraction of water for drinking and industrial application in cities could lead to
economic water scarcity and for some cities such as Perth, and also the declining rainfall
run-off enhanced the further pressure on the water resources. Australia has various climatic
pattern all over the country, there is mostly determined by the hot, sinking air of the
subtropical high pressure belt (Laity, 2009), and the dry conditions are associated with an El
Niño–Southern Oscillation in Australia. Climatic zones classification as shows in Figure,
about 70% of Australian Continental areas suffer the dry and hot weather, whereas most
humid and hot weather distribute in top North and southeast regions.
Figure 1: Climatic Zone Classification Australian Continent. (AGBOM, 2011)

4. Climatic pattern of the country has a significant influence to inland water resource supply.
Due to the unequal national run-off, particularly in North region and southern areas, the
irrigated agriculture draws large volumes of water from the Murray-Darling Basin (King,
2012). The long-term low irrigational and domestic water supply induces to serious
economic impacts on the agricultural sector, as drought relief funds are needed to support
farmers and maintain jobs (AGBOM,2011).
Water Scarcity level is more concerned in the volume of water consumption in terms of
agriculture and industrial and household water use, some studies have clarified that
approximately 40% of agricultural use of water and 90% industrial and household
application return to the nature (Shiklomanov,2000; Perry, 2007; FAO, 2010), therefore,
these types of water resource withdraw would be concern as the renewable water resource
and become one of the factors in the following assessment.
As the renewable freshwater supply is finite (Falkenmark et al., 1989), Australian continent
is a combination of 12 catchments with 191 basins, surface runoff distributes unequally over
the nation, as well as population density are various. Perth, Adelaide, Melbourne, Canberra,
Sydney and Southeast Queensland are the most populated regions. Falkenmark indicator
apply the index of water utilization level in assess the WSL in semi-arid regions of the world.
It is useful to measure the water demanding scale related to population density (Falkenmark
et al., 1989). Thus, Falkenmark index is applied to measure the competition for water
increases by population density, and generate an output to depicts which water stress
management significance.
A new alternative water stress index is created to enhance the mapping function and these
multi-criteria evaluation (MCE) process shows in section 3.

5. 3.Methodology (MCE):
3.1 Pre-processing:
Layer Data
Type
Pixel resolution Projection Source Parameters /
Function
Population count
and density
(2011, 2015)
Raster 1000,1000
(0.01 degree)
GDA 1994
Albers
DIVA GIS
Nasa Earth Data
Falkermark water
stress index,
Population
regrowth Rate
Surface Flow
Accumulation
Raster 0.0041666667,
0.0041666667
GCS WGS
1984
USGS Falkermark water
stress index
Land-use and
Water application
(LUWA)categories
Raster 1000,1000
(0.01 degree)
GDA 1994
Albers
Australian
Collaborative Land
Use and
Management
Program
(ACLUMP).
Water Resource
application and
demand level
Monthly
Precipitation data
Raster 310.4814814,
310.4814814
(30 second)
GCS WGS
1984
WorldClim - Global
Climate Data
Annual average
precipitation
City and
Administrative
boundary
Polygon N/A GCS WGS
1984
DIVA GIS Use to pre-
process the facto
layers
Table 1: Metadata of the factors that used in the report.
To understand the WSL across regions in Australia, four factors were considered and applied
in the following multi-criteria evaluation, they are population count and density of years
2011 and 2015, surface flow accumulation, monthly precipitation data, Land-use and water
application (LUWA) groups and Administrative boundaries. All layers are clipped to the
country boundary by Extract by mask and reprojected the layer coordinate system from
WGS84 to GDA 1994 Albers. Secondly, all data layers are Resample to the same pixel size
and Snap raster to the same location for further MCE.

6. 3.2 Domestic Water application:
Table 2: The Nature of the problem and difficulty in management related to population, the table
shows reclassification level of water stress level (Falkenmark et al., 1989).
Number of Persons / Flow unit Falkermark Water Stress Level
0 0 (No water application)
Less than 100 1 (Limited Water management problem)
100-600 2 (General Water management Problem)
600-1000 3 (Water Stress)
1000-2000 4 (Chronic Water Scarcity)
More than 2000 5 (Beyond Water management capability)
After pre-processing the layers, 2011 population layer and Surface flow accumulation layer
are Raster Calculated as below:
[Population2011 / Surface Flow Accumulation],
then Reclassify into the Falkermark WSL values shows in Table 2.
3.3 Water resource application:
Table 3: Water Resource application categories and relative water demand level (WDL).
A series of LUWA tertiary code as three-digit integer are established and published in
Australian Collaborative Land Use and Management Program (ACLUMP). In table 3, column
Land-use coding is a label of each type of land-use and each of them are representing
different agricultural and industrial uses of water resource, description in details shows in
appendix 1.
This water demand level is defined by the amount of water usage for each land-use type,
unused water resource and unknown water application area are considered as no demand
of water. Water demand level 1 and 2 are referring to low water demands, level 3 refers to
Land-use Coding Water Demand Level
0 and >600 (Unused Water Resource / No water resource application) 0
100-199 (Conservation and Natural Environments) 1
200-299 (Production from relatively Natural Environment) 2
300-399 (Production from Dryland Agriculture and Plantations) 3
400-499 (Production from Irrigation Agriculture and Plantations) 4
500-599 (Intensive Water Uses) 5

7. LUWA require extra irrigation, that is including conventional and non-conventional water
use; third, level 4 and 5 indicate to the areas significantly water resource demanding.
3.4 Population Growth rate:
Table 4: Population growth Rate between 2011 and 2015 in percentages and the relative WSLs.
Proportion of Population growth Water Stress Level
Below and equal to 0 0
0-100% 1
100-200% 2
200-350% 3
350-500% 4
More than 500% 5
Due to the population density highly affects the competition of water in Australia,
population growth analysis is beneficial in predicting the potential water shortage
vulnerable areas for any mitigation and preparedness plans in the future.
Both population layer of 2011 and 2015 are Raster Calculated, the output result display the
proportion of population change of which pixels, as below:
[ ((Population2015 – Population2011)/Population2011) *100 ],
then results are Reclassify and assigned values from 0 to 5 as WSLs as showing in Table 4.
3.5 Annual Average Precipitation scale:
Table 5: New (Alternative) Water Stress Index and relative levels.
Annual Average Precipitation scale Water Stress Level
0-49 1 (Water Scarcity)
50-99 2 (Vulnerable to Water Scarcity)
100-149 3 (Water Stress)
150-249 4 (Water stress in Certain adverse weather pattern)
250-323 5 (No water Stress)
This annual average precipitation values data is the water input factor and is the mean value
of monthly precipitation records. This WSL is designed to reclassify for the further analysis.

8. 3.6 New Water stress index:
Table 6: New (Alternative) Water Stress Index and relative levels.
Weighted index Result Water Stress Level
0-1 No Water Stress
1-2 Limited water Stress
2-3 Potentially Water Stress
3-4 Vulnerable to Water scarcity
4-5 Absolute Water Scarcity
Throughout four Reclassify calculations, a multi-criteria evaluation is applied to generate a
new water stress index by Weighting each layers. Weighted Sum Tool, is used to calculate
the final water scarcity map through weighting the WSL of those four new layers
(ESRI,2016), as below:
[ Water_Application_WSL *0.25,
Falkermark_WSL * 0.35,
Population_growth_WDL * 0.15,
Annual Average Precipitation * 0.25],
then it outputs a result of New Water Stress Index (NewWSI) with the value between 0.25 –
4.4 and also Reclassify into five Water Stress levels, as no water stress, Limited water Stress,
potentially water stressed area, area vulnerable to water scarcity and absolute water
scarcity area.
In the Weighted Sum evaluation, it aims to balance water supply and demand rate, and put
more weights on the rapidly increased population areas (pixels).

9. Figure 2: Reclassify output map shows 6 water stress levels calculated by Falkenmark WSL index. a) Perth, West Australia b)Adelaide, South
Australia c) Melbourne, Victoria ,and d)Sydney, New South Wale
a.
b. c.
d.
4. Results:

10. 2%
38%
46%
13%
~0% 1%
Unused Water Resource / No
Water Application
Conservation and Natural
Environments
Production from relatively
Natural Environments
Production from Dryland
Agriculture and Plantation
Production from Irrigated
agriculture and plantations
Intensive water uses
Figure 3: Map of Land-use and Water application distribution
and a pie chart shows the proportion of each water
application type.

11. Figure 4: Output Raster of Reclassified Population growth rate from 2011 to 2015, and annotated the extreme values.

12. Figure 5: New (Alternative) Water stress level map and the annotation maps of the areas suffering water scarcity, as Perth, Adelaide,
Melbourne, Sydney and Queensland.

13. 5: Result and Discussion:
As shown in section 4, Water income and withdraw values are applied to interpolate the
NewWSI, and also a four years’ population growth rate is calculated. Throughout MCE with
the factors as annual average precipitation, LUWA distribution and population growth, a
map of NewWSI classification present a more realistic water stress phenomenon.
5.1 Comparing Falkenmark Index and NewWSI:
In comparison of the widely used WSL as Falkenmark index and the NewWSI, a great
increased coverage in most levels. The level of water stress (in Figure 2) and the level of
potentially water stress (in Figure 5) cover 0.26% and 68.22% of Australia respectively; also
there is a 4.5 times more from Falkenmark index count to New WS Index in the coverage of
areas which is vulnerable to water scarcity; the absolute water scarcity areas remain similar
coverage. However, both results show the similar four regions are suffering water stress in
Figure 2 and 5, and three of them are distributed in Murray-Darling Basin, as mentioned in
section 2.
Falkenmark index calculation consider the general amount of daily water usage per person
in terms of industrial, agricultural and domestic (Falkenmark et al., 1989); whereas the
NewWSI enhances its values with the local LUWA with different values of various water
demand application, such as irrigation for plantation require more freshwater than the
Conservation Natural Environment use of water, and also the water income by precipitation
and possible population increases.
The significantly increased result shows in both water stress and high water scarcity risk
areas. NewWSi map presents one more water demand stressed area, Queensland, and
increased coverage in those five areas, these results address the water scarcity level
correlates to water income and output scale, instead of population only.

14. 5.2 Strength of MCE and Weighting analysis:
The Weighting logic analysis has played a significant role in two ways, firstly it highlights the
high water scarcity risk areas in Figure 5 and filters out extreme values (shows in Figure 4);
secondly, it provides the flexible control in the criteria importance decision, such as
balancing water application and water income level, and modify the population count with
the possible growth rate by counting 70% and 30% of their values respectively.
Multi-criteria evaluation in water resource assessment are critical, it provides supportive
evidence with target factors studies. For example, waste water emitting location, the
distance between waste water treatment area and water bodies, residential areas and
natural habitat distribution could be target factors in water quality assessment, which could
apply weighting logic or fuzzy membership to map the potential water pollution affected
area and magnitude of impacts.
5.3 Limitation and Suggestion:
- Surface accumulation data and precipitation layer are weak to present the total
runoff of the area, due to water loss and recharge rate are vary in the hydro-cycle.
The problematic water income layer could affect the New Water stress index
counting. It is suggested to consider the ground water penetrate rate and
precipitation values to generate the more accurate surface runoff values.
- The pixel values could be modified in the process of reprojecting the coordinate
system, resampling and reclassify, due to compensate the issue as lack of available
open data in Australia.
- Water application and Land-use layers was Reclassify by the three-digit coding, but not the
water demand values. Therefore, this New WS index would be less supportive and it is
suggested to input the water demanding values into the application and create a new layer
for weighting analysis.
- Topographical data, annual average temperature and groundwater are three important
factors that could affect the renewable water supply and losses, hence, they are suggested
to be included into the multi-criteria evaluation assessment.

15. 6.Conclusion:
Hydro-climatic variation, precipitation distribution, Land-use and water usage, and population
density are four major factors in controlling water stress level. A multi-criteria evaluation assessment
has been done and present a new water scarcity risk map, which depicts the values of alternative
water stress index across Australia. Perth, Adelaide, Melbourne, Sydney and Queensland are found
as suffering or are vulnerable to serious water shortage problems.

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18. 8. Appendix 1:
Source: Smart R. (2011).
This Table displays Values and meanings of Land-use and Water application.
primary_v7 Meaning
0 No data No data
100 to less than 200 Conservation and natural
environments
Land used primarily for
conservation purposes, based
on the maintenance of the
essentially natural ecosystems
present
200 to less than 300 Production from relatively
natural environments
Land used primarily for primary
production based on limited
change to the native vegetation
300 to less than 400 Production from dryland
agriculture and plantations
Land used mainly for primary
production, based on dryland
farming systems
400 to less than 500 Production from irrigated
agriculture and plantations
Land used mostly for primary
production, based on irrigated
farming
500 to less than 600 Intensive uses Land subject to extensive
modification, generally in
association with closer
residential settlement,
commercial or industrial uses
600 to less than 700 Water Water features. Water is
regarded as an essential aspect
of the classification, but it is
primarily a cover type.

19. The values of the columns classes_18 and c18_description and their meanings.
This Table display Values and meanings of detailed Land-use and Water application.
c18_description Meaning
0 No data No data
1 Nature conservation (1.1) Groups lu_codev7n values 110, 111, 112, 113,
114, 115, 116, 117
2 Other protected areas
including indigenous uses (1.2)
Groups lu_codev7n values 120, 122, 125
3 Other minimal use (1.3) Groups lu_codev7n values 130, 131, 133
4 Grazing native vegetation (2.1) Same as lu_codev7n value 210
5 Production forestry (2.2) Same as lu_codev7n value 220
6 Plantation forestry (3.1, 4.1) Groups lu_codev7n values 310, 311, 312, 313,
314, 410, 411, 412
7 Grazing modified pastures (3.2) Same as lu_codev7n value 320
8 Dryland cropping (3.3) Groups lu_codev7n values 330, 331, 332, 333,
334, 335, 336, 338
9 Dryland horticulture (3.4, 3.5) Groups lu_codev7n values 340, 341, 343, 346,
348, 349, 354
10 Irrigated pastures (4.2) Same as lu_codev7n value 420
11 Irrigated cropping (4.3) Groups lu_codev7n values 430, 431, 432, 433,
434, 435, 436, 438, 439
12 Irrigated horticulture (4.4, 4.5) Groups lu_codev7n values 440, 441, 443, 446,
448, 449, 454, 455
13 Intensive animal and plant
production (5.1, 5.2)
Groups lu_codev7n values 510, 511, 512, 520,
521, 522, 524, 525, 526, 527, 528, 529
14 Rural residential and farm
infrastructure (5.4.2, 5.4.3,
5.4.4, 5.4.5)
Groups lu_codev7n values 500, 542, 543, 545
15 Urban intensive uses (5.3, 5.4,
5.4.1, 5.5, 5.6, 5.7)
Groups lu_codev7n values 530, 531, 532, 533,
534, 535, 536, 537, 540, 541, 550, 551, 552,
553, 554, 555, 560, 561, 562, 563, 564, 565,
570, 571, 572, 573, 574, 575
16 Mining and waste (5.8, 5.9) Groups lu_codev7n values 580, 581, 582, 583,
584, 590, 591, 592, 593, 595
17 Water (6.0) Groups lu_codev7n values 610, 611, 620, 623,
630, 631, 650, 651, 660, 661