Water Scarcity in Australia

2016

SYRENA LY CHAN

UNIVERSITY OF SOUTHAMPTON |

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.

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)

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.

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.

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

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.

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).

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:

2%

38%

46%

13%

~0% 1%

Unused Water Resource / NoWater Application

Conservation and NaturalEnvironments

Production from relativelyNatural Environments

Production from DrylandAgriculture and Plantation

Production from Irrigatedagriculture 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.

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

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.

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.

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.

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.

7. Reference:

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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.

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