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The effect of land clearing on rainfall and fresh water resources in Western Australia: A multi-functional sustainability analysis

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It is widely recognised that southwest Western Australia has experienced a decline in rainfall over the last 40 years. It is generally thought that this decline is due to natural periodic variations and changes induced by global warming, but recently evidence has emerged suggesting that a substantial part of the decline may be due to extensive logging close to the coast to make way for housing developments and the clearing of native vegetation for wheat planting on the higher ground. We compare coastal and inland rainfall to show empirically that 55% to 62% of the observed rainfall decline is the result of land clearing alone. Using the index of sustainable functionality, we show that the economic consequences associated with this change of land use on fresh water resource availability have been underestimated to date and disproportionately affect the environment and poorest members of the population.
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International Journal of Sustainable Development &
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The effect of land clearing on rainfall and fresh
water resources in Western Australia: a multi-
functional sustainability analysis
Mark A. Andricha & Jörg Imbergera
a Centre for Water Research, University of Western Australia, Crawley, WA 6009,
Australia
Published online: 28 Oct 2013.
To cite this article: Mark A. Andrich & Jörg Imberger , International Journal of Sustainable Development &
World Ecology (2013): The effect of land clearing on rainfall and fresh water resources in Western Australia: a
multi-functional sustainability analysis, International Journal of Sustainable Development & World Ecology, DOI:
10.1080/13504509.2013.850752
To link to this article: http://dx.doi.org/10.1080/13504509.2013.850752
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The effect of land clearing on rainfall and fresh water resources in Western Australia:
a multi-functional sustainability analysis
Mark A. Andrich*and Jörg Imberger
Centre for Water Research, University of Western Australia, Crawley, WA 6009, Australia
(Received 1 August 2013; final version received 28 September 2013)
It is widely recognised that southwest Western Australia has experienced a decline in rainfall over the last 40 years. It is
generally thought that this decline is due to natural periodic variations and changes induced by global warming, but recently
evidence has emerged suggesting that a substantial part of the decline may be due to extensive logging close to the coast to
make way for housing developments and the clearing of native vegetation for wheat planting on the higher ground. We
compare coastal and inland rainfall to show empirically that 55% to 62% of the observed rainfall decline is the result of land
clearing alone. Using the index of sustainable functionality, we show that the economic consequences associated with this
change of land use on fresh water resource availability have been underestimated to date and disproportionately affect the
environment and poorest members of the population.
Keywords: sustainability; water; rainfall; Western Australia; climate change; inequality; land-use change
1. Introduction
Land-use change has significantly impacted climate in the
past. For example, Miller et al. (1999) suggest that indi-
genous land-use practices contributed to the semi-arid
conditions now found in Australians interior. Pielke
et al. (1999) showed that in Florida, landscape changes
have reduced summer rainfall by 11%.
The importance of quantifying the impact of climate
change on sustainable development for water resources has
been shown by Bates et al. (2008), and for well-being by
Apantaku (2013). Zhao et al. (2013) show in the context of
sustainable development how humans can induce desertifi-
cation through over-exploitation of natural resources, and
Jowsey (2012) shows that water has been moving in many
locations worldwide from being a renewable resource
towards becoming a non-renewable resource.
The dominant scientific focus on climate change is
carbon dioxide centric (Pielke et al. 2012). However,
topographic vegetation and soil moisture heterogeneities
strongly affect the mesoscale atmosphere (Wu et al. 2009),
and recently, Kala et al. (2010) and Pitman et al. (2004)
have shown using numerical modelling that deforestation
has been a cause of climatic change causing rainfall
decline in southwest Western Australia (SWWA).
SWWA is considered to be all land to the southwest of
the line shown in Figure 1A from Esperance to Geraldton.
It has an area of 196,000 km
2
(Landgate 2011) and is
geographically isolated by the Indian Ocean to the west,
the Southern Ocean to the south and desert to the north
and east. It consists of two distinct regions, first a western
coastal plain around 500 km from north to south and
between 30 and 100 km from east to west. This plain,
referred to as the coastal strip, has an area of about
25,000 km
2
and leads up to low hills (escarpment) that
range in height from about 300 to 500 m. To the northeast
of the escarpment, there is a second region, a large flat
plain, 300 m above sea level, that covers an area of
171,000 km
2
. This plain is used primarily to grow wheat
and is known as the wheatbelt. To the east of the wheat-
belt is a separate region called the goldfieldsthat extends
further east from the rabbit fence (Figure 1A) into the
desert, an area that is too dry for agriculture. Figure 1B
shows the annual rainfall decline after 1970, where it is
seen that the transition line of zero rainfall change roughly
matches the delineation of the rabbit proof fence, to the
east of which the vegetation has remained uncleared.
The region in west of the zero transition line
(Figure 1B) has experienced a significant decline of rain-
fall over the past 40 years (Cai et al. 2009; Petrone et al.
2010) that has affected agricultural production (Zhang
et al. 2010) and (renewable) surface water availability for
metropolitan Perth, the capital of Western Australia, and
water for industrial production supplied by the Western
Australian Water Corporation (WC) (2010a).
To date, the timing, magnitude and effect of this rain-
fall decline have not been examined in detail. The present
paper uses empirical data to calculate the effect of land-use
change on rainfall in the coastal strip and escarpment
transition zone where the drinking water reservoirs are
located (Figure 1A), on the inland wheatbelt, and on the
agricultural and water productivity in each sub-region. We
use the index of sustainable functionality (ISF) (Figure 2)
(Imberger et al. 2007; Andrich et al. 2010; Kristiana et al.
2011) to quantify the impact of this water loss on
*Corresponding author. Email: andrich@cwr.uwa.edu.au
International Journal of Sustainable Development & World Ecology, 2013
http://dx.doi.org/10.1080/13504509.2013.850752
© 2013 Taylor & Francis
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Figure 1. Southwest Western Australia (SWWA). As (A) shows, rainfall station locations are shown as black dots, Perth city is a red dot
and reservoirs (except for Mundaring Weir in black) are shown in blue. From North to South: Canning Reservoir (C); Wungon (W);
Serpentine (SE); North Dandalup (ND); South Dandalup (SD); Stirling (ST). (B) The rainfall trend from 19702010. (C) Winter cold
front reaching SWWA. The cold front moves in an eastnorth-east direction as shown by the heavy black arrow. (D) The total rainfall for
the 24 hours to 4 am on 2 June 2011, corresponding to the same period shown in Figure 1C. The effect of orography on rainfall from the
cold front seen in Figure 1C can be seen clearly in where the green (2550 mm rainfall) matches orography (300500 m) escarpment.
Typically, a cold front brings rain to the southwest coast (Cape Leeuwin) and moves inland towards Merredin, as shown by the black line
in Figure 1D.
STEP 1: Define the Domain
The domain, D, is the geographic entity under consideration, with
N sub-domains
Systems, K, are collections of processes organised to accomplish specific
functions; whilst perspectives, J, are viewpoints or stakeholders.
Collectively they comprise the matrix approach to measuring sustainability
Functions, F, are actions of a system that provide services to a
particular perspective
The indicators, I, are the data sets which quantify the functionality of
each function (or which capture the changes in sustainability over time)
Normalisation sets the indicator values between zero and one so that
they can be compared and aggregated
The weightings, W, reflect the importance of the different elements of the
fundamental matrix acrosss all stakeholders. The final values are then
averaged to form the final ISF
STEP 2: Define the Systems and Perspectives
STEP 3: Define the Functions
STEP 4: Define the Indicators
STEP 5: Data Normalisation
STEP 6: Weighting and Aggregation
Figure 2. The index of sustainable functionality (ISF) methodology.
2M.A. Andrich and J. Imberger
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sustainable development in SWWA from a perspective of
different household wealth levels and agricultural and
water supply organisations.
The domain of SWWA is ideal for this analysis, as all
the water available to the domain is derived from a single
source, the rain that is brought in by cold fronts moving
west from the Indian Ocean over the coast (Wright 1974),
consistently arriving during the months of April to
October. Typically, the cold fronts move in a north-easterly
direction (Figure 1C), aligned roughly parallel to a line
between Cape Leeuwin on the coast and Merredin inland,
as shown in Figure 1D.
1.1. Rainfall decline in SWWA
Three hypotheses have been separately suggested and
modelled to explain, in part, the inland rainfall decline in
SWWA (Kala et al. 2010). First, Cullen and Grierson
(2009) suggested that the decline was caused by global
meteorological conditions affected by natural periodic
variations; second, Cai and Cowan (2006) made a case
that anthropogenic induced global warming raised ocean
temperatures that in turn shifted the rain bearing, cold
front weather patterns south; and third, Kala et al. (2010)
and Pielke et al. (2011) used numerical modelling to
demonstrate that land clearing resulted in a rainfall
decline. Pitman et al. (2004) estimated that up to half of
the decline in observed rainfall across SWWA may be
attributed to land-use change. The various mechanisms
of how land clearing reduces inland rainfall have been
explored by different authors:
(1) Crops have lower transpiration rates and an
increased albedo, lowering the latent heat flux
into the meteorological boundary layer (Lyons
2002; Nair et al. 2007; Junkermann et al. 2009;
Kala et al. 2010).
(2) Cleared land has a reduced surface roughness
leading to an increased horizontal wind speed
and moisture divergence (Pitman et al. 2004;
Cotton & Pielke 2007; Nair et al. 2011).
(3) Rainfall increases by approximately 40 mm for
every 100 m altitude between Fremantle and the
scarp reservoirs (Wright 1974). We suggest that
the orographic effect of clearing tall trees is likely
to be most predominant in the coastal plain and
the foothills of the scarp where the land is low-
lying and the canopies of the trees were very tall
(Fraser 1904).
(4) Trees act as biotic pumps and their removal inter-
rupts this moisture flux (Makarieva & Gorshkov
2007,2009).
(5) Clearing native Eucalyptus trees reduces the
expulsion of volatile organic compounds that act
as seeding nuclei (King et al. 2004; Junkermann
et al. 2009).
1.2. The implications of land-use change on the econ-
omy, water resources and society
Western Australia was colonised in 1829 and according
to the Western Australian State Library Collection (2001)
from this time on, up until 1910, more than 90% of
SWWA land remained under native vegetation. By the
year 2000, a period of 90 years, 80% of land had been
cleared, mainly for the production of 287 million tonnes
(Mt) of wheat worth around $86 billion and 80,800 km
2
of Karri, Jarrah, York Gum and Wandoo forests worth
around $16 billion (Fraser 1904; Reserve Bank of
Australia 2012) (all dollar values are Australian 2012
dollars; 1 AUD ~ 1 USD).
However, the land clearing caused the water table
across the region to rise, bringing saline groundwater to
the surface, resulting variously in dryland salinity and
water logging (Middlemis 2001). According to the
Australian Bureau of Statistics (ABS 4615.0 2002), by
2002 dryland salinity was recognised to affect over
5000 km
2
of previously productive agricultural land and
51% of farms showed some signs of salinity. The
Australian National Resources Audit (2002) highlighted
that the same land clearing also resulted in increased
salinity in 1600 km of streams and 21 important wetlands
in the SWWA. The impact of this salinisation includes the
loss of freshwater species biodiversity and the salinisation
of bulk water reservoirs. For example, according the
Department of Water (2007,2009a, 2009b, 2010),
Wellington dam, with a capacity of 186 gigalitres (GL; 1
GL = 1 million m
3
), had an annual average inflow of 70
GL between 2001 and 2010 (WC 2010b), but the inflow
salinities have risen to between 950 and 1200 mg/L and
the reservoir has become no longer useable as a freshwater
resource over the same period. The combination of rainfall
decline and stream flow salinisation in the SWWA has
necessitated the construction of two desalination plants at
a cost of more than $1.3 billion, substantially increasing
the price of water to the Perth metropolitan area (WC
2012).
These complex economic, social and environmental
interactions explain why understanding the consequences of
land-use change requires transcending traditional boundaries
between disciplines such as hydrology, ecology, geography
and even the social sciences(DeFries & Eshleman 2004,p.
2183). Pielke et al. (1999), Pitman (2004) and Bonan (2008)
have suggested that the socio-economic and political involve-
ment of humans should be factored into interactions between
the atmosphere and land surface.
During the period of extreme land-use change, primar-
ily from 1960 to 1980, little attention was paid to the
possible impact of deforestation on local and regional
climate. From the 1990s onwards, it became to be realised
that land clearing could have an impact on the local
climate and that this required analysis (Lyons et al. 1993;
Lyons 2002; Pitman 2004). As seen from Figure 3A,
which shows the cumulative dam inflow and storage capa-
city over time (Berti et al. 2004; Department of Water
International Journal of Sustainable Development & World Ecology 3
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2007,2009b; Petrone et al. 2010;WC2010b), it is well
known that the recorded reductions of rainfall led to an
amplified reduction of surface run-off into the supply
reservoirs constructed on the rivers flowing down the
escarpment. The total storage capacity of the dams servi-
cing the Perth metropolitan area is 602 GL compared to
350 GL presently being supplied by the WC. The annual
surface run-off into these dams from 1975 onwards has
averaged less than one-third of the capacity, requiring the
WC to develop other sources of water, namely ground-
water and desalinised water. The impact of land clearing,
on rainfall and surface water resources has, however, not
been separated from other rainfall decline causes, nor have
attempts been made to quantify the social and economic
impacts of native vegetation clearing, on rainfall reduc-
tion; this is the focus of the present paper.
2. The index of sustainable functionality
The ISF (Figure 2) was chosen for this study because it
offers a quantitative measure of the functionality of a
system to be evaluated from different perspectives
(Imberger et al. 2007). In summary, the ISF quantifies
sustainable development by defining normalised indicators
of functionality and then attaching weights to these
indicators that reflect the relative importance of each indi-
cator (Andrich et al. 2013). The functionality of the agri-
cultural (S
1
) and water (S
2
) systems in the SWWA domain,
as impacted by land clearing, was evaluated with indica-
tors for the perspectives of two households wealth cate-
gories, J
j
, the poor(J
1
) and rich(J
2
) households, and
the farmers perspective (J
3
). The poor were defined as
those households with disposable income in the lower
10th percentile (P10) of income and the rich were defined
as households with a disposable income in the 90th per-
centile (P90) income level. The farm and water organisa-
tionsperspectives were designed to capture the impact of
rainfall reduction on farm functionality and on the Water
Corporation. Income data used for this study were
obtained from the Australian Bureau of Statistics (ABS
6523.0 2011). Functionality refers to the ability of a sys-
tem to meet its objectives, in relation to the purpose of that
system from a particular perspective (Imberger et al.
2007). Functionality was quantified in general, with K
ij
measures or indicators (I
ijk
; k = 1,K
ij
), that measure the
functionality of system i, from perspective jwith the
assumption that a value one being fully functionaland
zero representing a dysfunctionalaction on the system.
As such, an ISF value of one (1) indicates full function-
ality (sustainable use of resources), and zero (0) an action
Figure 3. Escarpment rainfall. (A) Dam storage capacity and inflow. Inflow shown between 1902 and 2010 for the seven largest
reservoirs (97% of total capacity) that supply bulk water to the metropolitan area. Reservoir locations are also shown here (A). (B) Native
vegetation remaining as a percentage of the coastal strip region. The change in ground water level at Frederick Baldwin Park, 10 km
south of Perth city increases from 1960, when clearing begins to accelerate. The 5-year average ratios of winter rainfall at the inland
station of Boyanup compared to Cape Leeuwin as well as the 5-year average ratio of winter rainfall at Mundaring Weir compared to Cape
Leeuwin are shown. The period of non-stationarity is shaded.
4M.A. Andrich and J. Imberger
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(e.g. land clearing) that implies a dysfunctional impact on
the systems in the domain. Normally, each system
functionality is assigned a weighting, W
ij
, reflecting the
relative importance of that particular functionality with
P
I
i¼1P
J
j¼1
Wij ¼1 and the ISF is defined as
ISF ¼X
I
j¼1X
J
j¼1
Wij
1
Kij X
Kij
k¼1
Iijk

()"#
:(1)
For this study, we assumed that each functionality was of
equal importance, so that (1) becomes
ISF ¼X
2
j¼1X
3
j¼1
1
Kij X
Kij
k¼1
Iijk

"#
;(2)
where i= 1, 2 are the two systems, agriculture and bulk
water, j= 1, 2, 3, are poor, rich and the organisations
(farmers and water) perspectives and K
ij
are the
number of indicators of functionality system (i) and per-
spective (j).
In setting up the ISF, it was assumed that the function
of the agricultural system (S
1
), in the SWWA, was to
provide food, measured by the affordability of wheat,
and providing employment for Western Australians.
Similarly, the function of the Bulk Water System (water
system)(S
2
) was to provide the Western Australian Water
Corporation with bulk water from the historical infrastruc-
ture of escarpment reservoirs.
Given that wheat is grown in the plateau called the
wheatbeltand the reservoir catchments are located in the
escarpment, it was necessary to separate the impact of land
clearing for these two regions. Climate modelling (Pitman
et al. 2004) suggests that up to 50% of the observed
inland, winter rainfall decline in SWWA as a whole had
resulted from land clearing. In order to confirm and unfurl
these modelling results, we first present a detailed statis-
tical analysis of inland and coastal rainfall records and
confirm the correlation of the non-stationarity in these
rainfall records to changes in land use.
2.1. The history of land-use change
Geographical and historical land-clearing trends for the
SWWA coastal strip were compiled using data from that
Australian Bureau of Statistics (ABS 1300.5, 18861988),
Fraser (1904) and from the West Australian State Library
Collection (WASLC) (2001). Historical photos and satel-
lite images near Perth obtained from Landgate (2011) were
used to estimate the rate of land clearing in the coastal
strip. The native vegetation remaining was estimated by
adding vegetatedpixels at 5-year intervals and dividing
the vegetated area by the total area of the coastal strip,
leading to the percentage native vegetation remaining for
the entire coastal strip, the results of which are shown in
Figure 3B. The historical land-use change data were also
correlated with the ground water levels recorded at
Frederick Baldwin Park, 10 km south of Perth city
(Figure 1A); the station that has the longest continuous
ground water level records, with water levels recorded
from the 1920s to the present as shown in Figure 3B
(DoW 2011). The time of the rise in the water table,
indicative of land clearing, corresponded closely to the
time of rapid land clearing in the 1970s. If is it assumed
that the average porosity of sand aquifer is 0.25 (Smith &
Pollock 2010; Yesertener 2010), then between 1965 and
1980, the groundwater rise was equivalent to an increase
in infiltration of about 35 mm/year (equivalent to ~5% of
annual rainfall); this is similar to that estimated by Nulsen
and Baxter (2004) and is almost the same as may be
explained by the difference of evapotranspiration from the
coastal strip native vegetation compared to generally devel-
oped land use of 32 mm/year (Zhang et al. 2010).
As shown in Figure 3B, the rate of land clearing in the
coastal strip between 1880 and 1970 was relatively slow,
with 70% of the land area, including regrowth, remaining
under vegetation after 90 years. Land clearing accelerated
after 1970 with 50% of the coastal strip (12,500 km
2
)
being cleared between 1970 and 1980.
The history of land-use changes in the wheatbelt was
quantified by assuming that the area under wheat cropping
represents the area cleared (WASLC 2001). The wheat
crop area for the period from 1861 to 2011 (ABS 7120.0
2013) and percentage of land remaining under native
vegetation are shown in Figure 4A and B. It was found
that from the time of colonisation in 1829 to about 1960,
clearing was slow, but clearing accelerated between 1950
and 1980, during which a further 40% of the land was
cleared; by 1980, around only 20% of native vegetation
remained.
2.2. The history of rainfall changes
The monthly rainfall data from more than 500 rainfall
stations in SWWA, as provided by the Australian Bureau
of Meteorology (2012), were reviewed to determine which
stations had sufficient (90 years or more) and reliable (the
rainfall stations had not been moved) monthly winter rain-
fall data. The eight locations that satisfied these criteria are
shown in Figure 1A. Data from these stations were then
aggregated, into coastal and inland, over the May
September winter period for each year. Because winter
rainfall arrives, to the SWWA, via cold fronts from the
west and south west (Figure 1D), rainfall at west coast
station locations were assumed to be independent of land-
use change. These are not strictly correct, as the removal
of the forest in the coastal margin would, as shown by
Makarieva et al. (2013), affect the regional water balance
and slightly decrease the cold front activity and/or shift
low-pressure systems southward. The coastal station loca-
tions with reliable data were Dongara [Station 008044],
Cape Naturaliste [Station 009519] and Cape Leeuwin
[Station 009518]; all other station locations had either
been moved, closed or multiple years of data were
International Journal of Sustainable Development & World Ecology 5
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missing. To test whether the coastal rainfall, recorded at
these stations, was stationary, we formed a time series of
the rainfall ratio (winter rainfall in a particular year,
divided by the respective historical (1st 10 years of avail-
able data) rainfall average). Figures 3B,4B and 5show the
rainfall ratios for the escarpment, wheatbelt and coastal
station locations.
The coastal rainfall ratio time series were tested for
stationarity by using the analysis of variance (ANOVA)
test to calculate variances and check that data had normal
probability distributions and then used a pairwise t-test
(Bonferoni method with two-sided 95% confidence inter-
vals) to compare data for time periods of equal lengths. In
order to maximise data usage, different lengths of time
were used (e.g. 5-, 8-, 10- and 20-year periods) and then
where non-stationary rainfall was apparent the mean and
standard deviation of the earlier and later periods were
calculated (see also Imberger & Boashash 1986). By this
method, the number of original data points and the relia-
bility of the results in each test were maximised. Non-
stationarity occurred where the difference in ratio means
between periods had p-values less than 0.05, large
F-values and similar variances. The statistical package R
(Cran R 2012) was used to conduct these analyses. For
these time series analyses, original data were used and if
any monthly rainfall data were missing then the winter
rainfall aggregate for that year was ignored.
The coastal rainfall ratio data, shown in Figure 5, exhib-
ited stationarity for coastal rainfall at Cape Naturaliste
(Figure 5A) and Cape Leeuwin (Figure 5B) from 1884 up
until 1997 (from which time onwards partial rainfall data
were available, but were not quality controlled). Dongara
(Figure 5C), latitude 29° S, had the only quality-controlled
coastal data after 1997. It was found that from 1971 to 2011,
rainfall at Dongara (29.25° S, 114.93 E) was 13.3% below
its pre-1970 average; the data suggest therefore that coastal
rainfall started to decline at a latitude 29° S around 1970.
Figure 5D shows the ratio of Dongara to Cape Leeuwin
(34.37° S, 115.14 E) rainfall from 1897 to 1997 and it is
seen that this ratio was stationary to about 1970, whereupon
it fell by about 12.8% for 20 years, and 11.8% to 1997. This
fall is consistent with the above observation that the rainfall at
(A)
Wheat Crop Area (km2)
(B)
Wheatbelt land under native vegetation (%)
100
90
80
70
60
50
40
30
20
10
00.30
0.40
0.50
0.60
Inland to coastal rainfall ratios
0.70
0.80
0.90
1.00
1.10
60,000
50,000
40,000
30,000
20,000
10,000
0
1850
1880 1890
Wilgarrup winter rainfall (May–Sep)/Cape Leeuwin winter rainfall (May–Sep)
Duranillin winter rainfall (May–Sep)/Cape Naturaliste winter rainfall (May–Sep)
Average 5-year winter rainfall ratio for Duranillin and Wilgarrup vs. coastal stations
Land under native vegetation
1900 1910 1920 1930 1940 1950 1960 1970 1980 1990 2000 2010
1860 1870 1880 1890 1900 1910 1920 1930 1940 1950
SWWA wheat production (tonnes)SWWA wheat crop area (km2)
1960 1970 1980 1990 2000 2010 2020
M
2M
4M
6M
Wheat production (tonnes)
8M
10M
12M
14M
16M
Figure 4. Wheatbelt rainfall. (A) Wheat crop area and wheat production in the southwest of Western Australia; the period between 1960
and 1980 when the greatest clearing occurred is shaded. Wheatbelt land-use and winter rainfall. (B) The winter rainfall at Wilgarrup and
Duranillin relative to winter rainfall at Cape Leeuwin and Cape Naturaliste, respectively; periods of non-stationarity are shaded. The
proportion of land under native vegetation in the wheatbelt is shown from 1890 onwards.
6M.A. Andrich and J. Imberger
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Cape Leeuwin remained stationary to 1997 when data were
no longer quality controlled, but then there is a suggestion of a
slight rise from 1990 onward as a result of a slight decrease in
rainfall at Cape Leeuwin. These observations suggest that
global change had begun to effect the cold front activity at
Dongara around 1970 and this effect had moved south to
Cape Leeuwin only by 19902000; the escarpment and
wheatbelt stations appear not to have felt impacts of shifting
cold front activity until the 1990s or later.
The escarpment station locations, at similar latitudes to
the southern coastal stations (Cape Leeuwin and Cape
Naturaliste), with reliable overlapping data were
Boyanup [Station 009503] and Mundaring Weir [Station
009031] (in the escarpment) and Duranillin [Station
010547] and Wilgarrup [Station 009619] in the wheatbelt.
Mundaring Weir is not at the same latitude as any of the
coastal stations, but rainfall data for this location were
included in the analysis because Mundaring Weir was the
earliest reservoir built (Figure 3A) and the weather station
had the longest reliable rainfall data series of all reservoir
locations.
Figure 3B shows the escarpment rainfall ratios. As
shown for the reservoir station location of Mundaring
Weir, annual winter rainfall compared to that at Cape
Naturaliste averaged 1.38 up to and including 1970
(from when records began in 1904). After 1970, the
mean rainfall ratio declined by 15%. Similarly, the rainfall
at Boyanup decreased by 18% after 1975 compared to
Cape Leeuwin and by 17% after 1965 compared to Cape
Naturaliste (not shown). The average escarpment rainfall
decline from 1960 onwards, relative to the coastal station
locations, was about 16%.
A similar procedure was applied to the rainfall records
from the inland stations in the wheatbelt and the time
series are shown in Figure 4B. In order to eliminate
inter-annual variability of the cold front activity, the inland
rainfall records were first divided by the relevant coastal
rainfall record to form the inland rainfall ratios shown in
Figure 4A. This rainfall ratio was then tested for non-
stationarity and the periods of non-stationarity were then
correlated against the land-clearing records.
Figure 4B shows decline in wheatbelt winter rainfall
relative to rainfall at the west coast station locations start-
ing around 1960. As shown by the shaded area, the 5-year
winter rainfall ratio for Wilgarrup compared to Cape
Leeuwin declined by 28% between 1960 and 1970. Over
the same period, the rainfall ratio for Duranillin in the
central wheatbelt compared to Cape Naturaliste at the
coast declined by 13%. Also shown is the average rainfall
decline at these wheatbelt stations, relative to coastal win-
ter rainfall, that has occurred since 1960; this average
decline was 21%.
In summary, comparing the inland rainfall decline
(affectedbylanduse)withthatobservedatthewest
coast (unaffected by land use except from the biotic
pump effect) suggests that the change in winter rainfall
in the escarpment due to land clearing was 55% of the
total change in rainfall observed in the region (16%
average escarpment rainfall decline relative to coastal
rainfall decline)/(average decline of escarpment rainfall
relative to the coast plus the maximum coastal rainfall
decline observed at Dongara, i.e. 16% + 13%). In the
wheatbelt, the rainfall decline that may be attributed to
land clearing alone was 62% (average decline of wheat-
belt rainfall relative to the coast of 21% divided by
wheatbelt average decline relative to coastal rainfall
plus the maximum coastal rainfall decline observed at
Dongara, i.e. 21% + 13%).
The remaining 45% to 38% of the inland rainfall
decline is therefore attributable to some combination of
long-term natural variation, other human climate forcing
andbioticpumpeffects(alsocausedbydeforestation)
that are affecting regional climate. Figure 4B shows that
rainfall decline occurred inland relative to stationary
coastal rainfall between the years 1950 and 1970.
During the 1950 to 1970 period of wheatbelt rainfall
decline, 48,000 km
2
or 28% of the wheatbelt area had
been cleared, reducing the native vegetation from
around 60% to 30% of the total area. Comparing the
coastal strip land clearing and rainfall ratio results simi-
larly suggests that the native vegetation reduction from
60%to30%ofthecoastalstripcorrelatedwiththe
decline in inland winter rainfall.
(A)
(B)
(C)
(D)
Ratio
Ratio
1.5
1.3
1.1
0.9
0.7
0.5
1.2
1.0
0.8
0.6
0.4
Ratio
Ratio
0.8
0.6
0.4
0.2
1.2
1.0
0.8
0.6
0.4
0.2
0.0
1880 1900
Cape Leeuwin Rainfall/Cape Leeuwin Historical (1897–1906)
average rainfall (5-year ratio average)
Cape Naturaliste Rainfall/Cape Naturaliste Historical (1903–1912)
average rainfall (5-year ratio average)
Dongara annual rainfall ratio compared with historical (1884–1893) average (5-yea
r
ratio average)
Ratio of annual winter rainfall at Dongara compared with Cape Leeuwin (5-year
ratio average)
1920 1940 1960 1980 2000 2020
1880 1900 1920 1940 1960 1980 2000 2020
1880 1900 1920 1940 1960 1980 2000 2020
1880 1900 1920 1940 1960 1980 2000 2020
Figure 5. Coastal rainfall ratios for Cape Leeuwin (A), Cape
Naturaliste (B) and Dongara (C) relative to their historical aver-
age, and Dongara rainfall compared to Cape Leeuwin rainfall
(D). Station locations can be seen in Figure 1A. The boxes
represent years where data are stationary (using the original
annual data). Only quality controlled data provided by the
Australian Bureau of Meteorology (2012) are shown.
International Journal of Sustainable Development & World Ecology 7
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3. ISF indicator results
The indicators chosen for the agricultural system (S
1
)
represent the ability of the region to grow affordable
wheat for the population of Western Australia and use
Western Australian labour efficiently, so as to make farm-
ing an attractive economic activity.
For the water system (S
2
), indicators were chosen to
represent the affordability of water for households, as well
as the ability of the water supply organisation (Water
Corporation of Western Australia) to supply water effi-
ciently and with low environmental impact.
Indicators were chosen on the basis that they were
representative of the functionality of the systems, as well
as being available from reputable data sources, primarily
the Australian Bureau of Statistics and other Australian
and West Australian Government agencies.
The list of indicators is as follows:
I
111
(agriculture system, low-income perspective, first
indicator): employment potential of the agriculture
system
I
112
(agriculture system, low-income perspective, second
indicator): food affordability for low-income
households
I
121
(agriculture system, high-income perspective, first
indicator): food affordability for high-income
households
I
122
(agriculture system, high-income perspective, second
indicator): wealth creation from farming
I
131
(agriculture system, farmers perspective, first indica-
tor): productivity and efficiency of farming
I
211
(water system, low-income perspective, first indica-
tor): water affordability for low-income households
I
221
(water system, high-income perspective, first indica-
tor): water affordability for high-income households
I
231
(water system, water organisations perspective, first
indicator): environmental impact of water supply.
3.1. Indicators for the agricultural system
3.1.1. I
111
: employment potential of agriculture system
The first indicator of functionality was obtained by con-
sidering the employment or job creation potential of the
agricultural system as measured against the contribution
the agricultural system makes to the State of Western
Australias GDP. The indicator measures the number of
people employed in farming relative to total state employ-
ment, and the importance of farming to GDP and its
ranking by size among government categories of industry:
The data sources for I
111
were the Australian Bureau of
Statistics, ABS 6291.0.55.003 (2012) and ABS 5220.0
(2012).
The second and third indicators of the agricultural
system (I
112
and I
121
) represent the affordability of the
agricultural system from the low- and high-income house-
hold perspectives. These indicators were quantified by
taking the cost of wheat flour as a proportion of annual
disposable household income at the 10th percentile (P10)
income level and 90th percentile income level, respec-
tively, relative to the amount of income at which food
stress occurs for households in Australia; Pollard et al.
(2013) found that food stress occurs for households
when 25% of income is spent on food:
3.1.2. I
112
: food affordability for low-income households
3.1.3. I
121
: food affordability for high-income households
The data used in Equations (4) and (5) are from the same
source. The average wholesale price of wheat flour was
estimated to be $0.70/kg and demand was 69 kg/capita
(186 kg/household) in 2009 (van Gool 2009; ABS 1367.5
2010). We then assume that the retail price is twice the
wholesale price (i.e. $1.40/kg), taking into account the
distribution, retail mark-up and any final products (e.g.
bread). The time series price is provided by the consumer
I111 ¼People employed in the agricultural sector=Total number of people employed
Value of agricultural production=State domestic product Agricultural industry rank
No:of industry categories ð20Þ:
(3)
I121 ¼1
Household cost of 186 kg wheat flour
Annual disposable household income at high income level
Income spent on food where food stress occurs 25%ðÞwheat flour as %of food budget ð10%Þ:(5)
I112 ¼1
Household cost of 186 kg wheat flour
Annual disposable household income at low income level
Income spent on food where food stress occurs 25%ðÞwheat flour as %of food budget ð10%Þ:(4)
8M.A. Andrich and J. Imberger
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price index (CPI) for bread and cereal products (ABS
6401.0 2013). Household disposable income at the P10
(poor) level and P90 (rich) level are provided by the
Australian Bureau of Statistics Household Income and
Income Distribution (ABS 6523.0 2011) for each year.
Finally, we assume that 10% of food expenditure is used
to pay for wheat flour.
Indicator I
122
is calculated according to Equation (6)
which measures the wealth creation for farmers by calcu-
lating the percentage of farmer owners with high incomes
relative to the general population with the same high-
income levels (ABS 1367.5 2010). This is calculated for
the only 2 years in which data were available (2001 and
2006) for the wheatbelt area statistical division (ABS
Census 2012).
3.1.4. I
122
: wealth creation from farming
3.1.5. I
313
: productivity and efficiency of farming
The functionality of the agricultural system from the farm-
ing organisations perspective (I
131
) was quantified as the
efficiency of wheat production measured by tonnes of
wheat production per hectare compared with the original
production per hectare (average first 20 years of contin-
uous records, 18761895), measured relative to the peak
area under production divided by the actual area under
production in each year. It is assumed that the actual area
under production is proportional to the area lost to dryland
salinity and/or rainfall decline that has made the area
unprofitable. All data for this indicator were from ABS
7124.0 (2011):
3.2. Indicators of the water system
3.2.1. I
211
: water affordability for low-income households
It was found that best way to represent the water system
from the perspective of households with different income
levels was to calculate water expenses relative to dispo-
sable household income (WERHI). I
211
was calculated by
taking water expenses for low-income households based
on an average water consumption that was 10% below the
average consumption (Loh & Coghlan 2003;WC2012)
(i.e. 266 kL/year) and annual water rates (Thomas et al.
1983;WC2004, 2011, 2012), and dividing these water
expenses by disposable household income level (ABS
6523.0 2011) for each year.
3.2.2. I
221
: water affordability for high-income households
The indicator of water affordability for high-income
households (I
221
) was also calculated in the same way,
except that the high-income value was used. For high-
income households, water consumption was estimated to
be 10% above average water use, i.e. 326 kL/year (Loh &
Coghlan 2003;WC2012).
Both indicators were normalised so that the indicator
resulted in full functionality (I
2j1
= 1), dyfunctionality
(I
2ji
= 0) or a linear interpolation in between these bounds
(0 < I
2j1
< 1). Water expenses that were 5% or more of
household income were considered dysfunctional, and
zero water expenses were considered functional:
I2j1¼0:05 WERHIj
0:05 for 0 WERHI 0:05;
else I2j1¼0 for WERHI 0:05:
(8)
3.2.3. I
231:
water supply environmental impact from the
water organisations perspective
Figure 3A showed that seven major dams were built after
1902 to supply the SWWA population and industry with
fresh water. After rainfall and streamflow declined in the
1970s, the major alternative water sources used to meet
demand were groundwater, and then desalination after
2005, both of which consume more energy and produce
higher carbon emissions than gravity fed water from dams.
Figure 6A shows the time series carbon emissions
from water production from 1902 onwards. It was
assumed that water demand for any one year above stream
flow was made up by groundwater, requiring 0.4 kwh/m
3
(Leslie 2004) and desalination that requires 3.4 kwh/m
3
(IRENA 2010) and that electricity is supplied using 45%
coal, 50% natural gas and 5% renewable energy at an
average emission rate of 0.683 tCO2-e/MWh (Evans
et al. 2009; Andrich et al. 2013). It was further assumed
that gravity feeding surface water from the escarpment
reservoirs was effectively carbon neutral as the pumping
costs are minimal and reservoirs may be operated to
sequester carbon (Tranvik et al. 2009). The annual stream
flow, water demand and water sources were supplied by
the Department of Water (DoW 2007,2009b), the Water
Corporation (WC 2010b,2012), Petrone et al. (2010) and
Berti et al. (2004).
I122 ¼Percentage of farm owners with incomes above $2000=week
Percentage of SWWA population with incomes at high income level :(6)
I131 ¼Wheat production per hectare Peak area under wheat production
Original production per hectare Actual area of production :(7)
International Journal of Sustainable Development & World Ecology 9
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The carbon emissions for the water environmental
indicator (I
231
) was normalised so that the functional
bound (I
231
= 1) occurred when net carbon emissions
were zero, and the dysfunctional bound (I
231
= 1) occurred
when carbon emissions from water production were equal
or greater than Western Australias average level of carbon
emissions production inefficiency (CEPI) (72.4mtCO2-e/
$162B GDP !4.52e-4 tCO2/$GDP) as provided by the
Department of Climate Change and Energy Efficiency
(DCCEE) (2010). Values from 2010 were chosen as the
dysfunctional bound, as at this time Western Australia had
one of the worlds highest per capita carbon emissions
(DCCEE 2010). The value of water was assumed to be
$1.50/kL (WC 2010a):
I231 ¼1
Carbon emissions from water production tCO2½
Value of water produced $½
CEPI tCO2
$GDP
 ;
(9)
where I
231
= 0, for any value of I
231
0.
The water production efficiency indicator values are
shown in Figure 6B. It is important to recognise that
Western Australias Water Corporation offsets its energy
use for desalinated water production via purchases of wind
and solar energy from the state electricity utility (WC
2012).
3.3. Summary of key ISF results
Figure 7 shows the results for the Agriculture System,
based on the data described in Section 3.1. The indicator
value representing the agricultural income potential for
low-income households (I
111
) has declined from functional
indicator values ranging between 0.95 and 0.8 in the early
1990s, to mostly semi-functional values of between 0.5
and 0.6 from 2001 onwards, with the exception of 2007
(when commodity prices were abnormally high).
As seen in Figure 7A, the affordability of food indi-
cator (I
112
) for low-income households decreased from
1987 to 1993, but remained largely stationary and semi-
functional at a value of approximately 0.6 to 0.75 from
1994 to 2010. The indicator representing food
(A)
(B)
tCO2-e emissions
Indicator value
1.00
0.90
0.80
0.70
0.60
0.50
0.40
0.30
0.20
0.10
0.00
450,000
400,000
350,000
300,000
250,000
200,000
150,000
100,000
50,000
0
1900 1910
tCO2 from surface water
tCO2 from groundwater
tCO2 from desalination
1920 1930 1940 1950 1960 1970 1980 1990 2000 2010 2020
1900 1910
I211 – Water affodability for low income households
I222 – Water affordability for high income households
I231 – Environmental impact of water supply
1920 1930 1940 1950 1960 1970 1980 1990 2000 2010 2020
Figure 6. Water system results showing carbon emissions from water production using the same energy sources (A). Note that in
Western Australia desalinated water uses wind and solar power, and therefore, the carbon emissions are lower than those shown.
(B) Water system results for households and the water organisations environmental impact.
10 M.A. Andrich and J. Imberger
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affordability for high-income households (I
121
) remained
high (0.9 or greater) and stationary across the entire
period.
By contrast the indicator representing the number of
high-income farmers as a proportion of the high-income
earners across the population is marginally functional
in 2001 (0.55), and dysfunctional (0.35) in 2006.
Figure 7B shows that agricultural productivity and effi-
ciency was consistently functional with I
131
=1forall
years (18762011), but experienced a major overall
decline. The un-normalised indicator shows that agricul-
ture production efficiency up until around 1960 was very
high, a factor of two to 500 times higher than post-1960s
production.
Figure 6A shows the downside of using renewable
energy for desalination. The large amount of energy
required for desalination is clearly seen, relative to the
energy requirements for either groundwater or surface
water supply. For the 110 years of surface water produc-
tion between 1902 and 2012, surface water supply was
effectively carbon neutral, groundwater pumping produced
10,000 to 50,000 tCO
2
-e per year, and without the use of
renewable energy desalination would have produced up to
410,000 tCO
2
-e per year.
Figure 6B showed that the indicator representing
water affordability for poor households (I
211
)was
semi-functional during the 1990s, with values trending
downwards from 0.63 to 0.55. The trend continued and
by 2012 the water affordability indicator for low-income
households was dysfunctional (0.4). By contrast for
high-income households, the water affordability indica-
tor (I
222
) was both functional and stationary across the
same period. The indicator of water production effi-
ciency (I
231
) shows largely functional but inconsistent
values (0.8 < I
231
< 1) from 1902 up until the 1940s and
1950s, when new reservoirs were built to supply surface
water (Figure 3A, Canning and Stirling reservoirs) and
the indicator from that time onwards up until 1970 was
fully function (I
231
= 1). After 1970, the indicator
showed large variability, dropping below 0.5 in 2010.
The indicator was completely dysfunctional (I
231
=0)
in 2012.
1
0.9
(A)
(B)
0.8
0.7
0.6
0.5
0.4
Indicator value
0.3
0.2
0.1
0
1000
100
Indicator value
10
1
1987
1876
1882
1888
1894
1900
1906
1912
1918
1924
1930
1936
1942
1948
1954
1960
1966
1972
1978
1984
1990
1996
2002
2008
1990
I111 – Agriculture income potential for low-income households
I112 – Food affordability for low-income households
I121 – Food affordability for high-income households
I122 – Percentage of high-income farming households relative to all high-income
households
1993 1995 1998 2001
Un-normalised I131: Productivity and
efficiency of agriculture system
Normalised I131 indicator value (I131
1 Fully Functional)
2004 2006 2009 2012
Figure 7. Agriculture system results from household perspectives (A) and from farm organisationsperspective (B).
International Journal of Sustainable Development & World Ecology 11
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4. Discussion
Pielke et al. (2011) showed that land-use change has been
under-studied and under-estimated in terms of its impor-
tance on climate and rainfall worldwide the dominant
scientific perspective on climate change is carbon dioxide
centric (Pielke et al. 2012). Mahmood et al. (Forthcoming
2013) have described land-cover change as being of pri-
mary concern in any assessment of climate processes. In
Section 2.2, we showed that deforestation was a major
cause of winter rainfall decline in SWWA. The only
research to date that has put forward an estimate of the
impact of land-use change on rainfall and fresh surface
water resources in SWWA was Pitman et al. (2004), who
suggested from numerical modelling that up to half of the
rainfall decline observed was caused by land clearing. Our
empirical analysis of rainfall data separated the region into
two distinct sub-regions to show that around 62% of the
1525% rainfall decline in the wheatbelt may be attributed
to land clearing, and 55% of the 1525% rainfall decline
in the escarpment, where the bulk water reservoirs are
located may be attributable to deforestation. The larger
decline and earlier change of rainfall (around 1950
1960) in the wheatbelt compared with the coastal strip
rainfall change (around 19601970) is consistent with
clearing data that showed a larger, earlier reduction in
native vegetation in the wheatbelt compared with the
heavily forested southwestern coast that opened to large
amounts of development in the 1960s when the southern
freeway was built, and when forestry activity intensified.
Lastly, the further rainfall decline commencing at all sta-
tions, both coastal and inland, after 2000, was hypothe-
sised to be caused by the rain bearing cold fronts
progressively moving south caused by other human cli-
mate forcings and a biotic pump effect.
The ISF indicator results showed that agriculture pro-
duction in the wheatbelt has not been able to support low-
income farmers, who have had declining opportunities to
earn income from the early 1990s, as well as highly vari-
able production efficiency from around 2000 onwards.
The price of food remained affordable, most likely a result
of the size of the wheatbelt relative to the small population
in Western Australia, and also due to the introduction of
new wheat varieties that tolerate low rainfall (Siddique
et al. 1989).
The effect of declining rainfall on the water system
was a reduction in water affordability for low-income
households. Water is a household necessity with poor
households water use only 10% less and high-income
familieswater use 10% more than water use by aver-
age-wealth households (Loh & Coghlan 2003). By com-
parison the income of the low-income households has not
increased at the same rate as those of the wealth house-
holds (Andrich et al. 2010,2013), so that rising water
prices resulting from reduced water supply caused by
deforestation have led to an increased income and wealth
gap between poor and rich households.
From an environmental perspective, the major negative
consequences of declining rainfall and streamflow salini-
sation have been on the biodiverse and unique flora and
fauna that have no ability to replace lost rainfall and
streamflow with ground or desalinated water; instead rely-
ing almost entirely on the impaired levels of rainfall and
some groundwater that flows into streams (Department of
Environment 2004). While this impact was recognised as
being important, no quantification indicator could be for-
mulated. Instead carbon emissions associated with desali-
nated water were quantified and shown to be substantially
higher than those emitted by using ground or surface
water. This highlighted the need to couple the introduction
of desalination technologies with renewable energy if the
functionality of water supply is to be maintained. The
results suggested that, in order to increase the sustainable
development indicator values, a combination of factors
need to be considered:
(1) To minimise carbon emissions, desalinated and
ground water both require renewable energy
sources.
(2) Using renewable energy and ground and desali-
nated water will increase the price of water, the
effect on society is to increase the gap between
rich and poor subsidies and/or increased charges
for high-volume/wealthy users are required, to
retain functionality.
(3) The case of SWWA clearly shows the need to
mitigate the effects of variations and long-term
changes in climate with regional reforestation
using large native trees thereby reducing the
cost of supply water, helping agriculture in the
wheatbelt to retain its functionality, as well as
increasing water supply to the natural environ-
ment. Reforestation for water productionshould
be seriously considered.
5. Limitations
There are two limitations to these analyses that are as
follows:
(1) Income data: Income data were not available at the
same income levels prior to 1994, and therefore,
income related indicators were not shown prior to
1994.
(2) Rainfall data: Much of the coastal rainfall data avail-
able were before 2000, with a small loss of rainfall
data also occurring at inland monitoring stations
after 2000 compared with the period 18902000.
Additionally few coastal rainfall stations had contin-
uous rainfall data. Rainfall data at Cape Naturaliste
and Cape Leeuwin showed a non-stationary
decrease in rainfall at the coast after 2000; however,
these data were not quality controlled after 1997.
12 M.A. Andrich and J. Imberger
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6. Conclusion
Correlating land-use change with rainfall reduction estab-
lished a causal relationship. It was found that reducing native
vegetation from 60% to 30% of the land area in the wheatbelt,
between 1950 and 1970, coincided with an average 21%
reduction in inland rainfall relative to coastal rainfall that
was independent of land-use change and stationary over the
same period. It was found that for the forested coastal strip
region south of Perth, land clearing that removed 50% of the
native forests between 1960 and 1980 coincided with a 16%
reduction in rainfall relative to stationary coastal rainfall.
A multidimensional sustainability index, the ISF, showed
that this water loss has increased the wealth gap between rich
and poor and has reduced the income earning potential for
low-income farmers; both of which are contrary to the objec-
tives of sustainable development. While high-income house-
holds were shown to be able to afford desalinated water, as
rainfall declined low-income households were significantly
less able to afford water. This means that as well as causing
dryland salinity and streamflow salinisation in SWWA, exces-
sive deforestation has also significantly reduced water avail-
ability and in part led to desalination plants being built at a cost
of more than $1 billion. The case of SWWA clearly shows the
need to mitigate the effects of variations and long-term
changes in climate with regional reforestation using large
native trees.
Acknowledgements
The authors would like to thank the many reviewers for com-
ments that were gratefully received. In particular, the authors
would like to acknowledge the significant contribution of Lord
Ron Oxburgh at Cambridge University for his assistance with
early edits, rainfall trend observations and other contributions to
the paper; as well as Professor Nazim Khan in the Mathematics
Department at the University of Western Australia for suggesting
the most effective way to analyse rainfall data. Funding for the
study was provided by the Centre for Water Research, the
University of Western Australia and the Water Corporation of
Western Australia. The conclusions are the authorsalone. This
paper forms CWR Reference # MA-2390.
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... The sites for which we have the longest rainfall records are the Cape Leeuwin lighthouse from 1897 and Cape Naturaliste from 1902 to the present. Surprisingly, a recent publication suggested that they show no obvious decline when winter rainfall at Cape Leeuwin and Cape Naturaliste is compared with the average rainfall for the first 5-year period (Andrich and Imberger 2013). George Seddon's 'Sense of Place' has a plot of Perth's rainfall from 1877 to 1970, from which it is also difficult to detect any obvious trend. ...
... George Seddon's 'Sense of Place' has a plot of Perth's rainfall from 1877 to 1970, from which it is also difficult to detect any obvious trend. The manipulation of the data in Andrich and Imberger (2013), however, shows the dangers inherent in choosing a baseline. Rainfall at the two Capes was low over the first 10 years of recording, and this in effect has skewed the analysis. ...
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This essay is based on my George Seddon Memorial Lecture at the University of Western Australia and documents the changes in the city of Perth since George's seminal book, 'Sense of Place', that was published in 1972. In 1972 the population of Perth was 642 000. It is now just over 2 million, but predicted to reach 3.5 million by 2050, growing by 45% from 2005. This increase in population, driven by the mining boom, has brought with it numerous problems. These include housing affordability, traffic congestion, increasing pollution and diminishing water supply. The environmental footprint of the average Perth home is a staggering 14.3 ha and it seems obvious that future growth must be accommodated vertically, rather than horizontally. Infill, however, is vigorously opposed in the affluent suburbs where the quarter- acre block still rules. Western Australians need to face up to Perth’s urban sprawl and its disastrous impact on the few remaining tracts of bushland on the Swan coastal plain. We also need to realise that our health, both physical and psychological, depends upon the health of the environment in which we live and work.
... The decline in autumn-winter rainfall over SWWA since the 1970s appears unusual in the context of instrumental records (since ~ 1900 CE) and several studies indicate that anthropogenic climate change (Cai and Cowan 2006;Hope 2006;Nicholls 2010;Cai et al. 2011;Raut et al. 2014) and possibly land clearing (Pitman et al. 2004;Nair et al. 2011;Andrich and Imberger 2013) have contributed to the decline. Importantly, southwest Australia is one of the few places in the world where the majority of climate models agree (> 90% in both CMIP5 and CMIP6) that further declines in autumn-winter rainfall are likely in the next century with increasing anthropogenic greenhouse gas concentrations (Hope et al. 2015;Grose et al. 2020). ...
... However, these declining trends are also consistent with model-based predictions of the impact of increasing greenhouse gas concentrations on rainfall in southwest Australia (Hope 2006;Delworth and Zeng 2014;Andrys et al. 2016). In particular, the post-1970 CE rainfall decline in SWWA has been attributed to anthropogenically-driven changes in sea level pressure and the increasingly positive behaviour of the SAM over the same period, (Cai and Cowan 2006;Hope 2006;Nicholls 2010;Cai et al. 2011;Raut et al. 2014) as well as changes in land cover in the region (Pitman et al. 2004;Nair et al. 2011;Andrich and Imberger 2013). Both natural variability and anthropogenic-driven changes likely contributed to the recent rainfall declines and their combined impacts could potentially lead to even greater reductions in rainfall in southwest Australia in the future (Cai and Cowan 2006). ...
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Declining winter rainfall coupled with recent prolonged drought poses significant risks to water resources and agriculture across southern Australia. While rainfall declines over recent decades are largely consistent with modelled climate change scenarios, particularly for southwest Australia, the significance of these declines is yet to be assessed within the context of long-term hydroclimatic variability. Here, we present a new 668-year (1350–2017 CE) tree-ring reconstruction of autumn–winter rainfall over inland southwest Australia. This record reveals that a recent decline in rainfall over inland southwest Australia (since 2000 CE) is not unusual in terms of either magnitude or duration relative to rainfall variability over the last seven centuries. Drought periods of greater magnitude and duration than those in the instrumental record occurred prior to 1900 CE, including two ‘megadroughts’ of > 30 years duration in the eighteenth and nineteenth centuries. By contrast, the wettest > decadal periods of the last seven centuries occurred after 1900 CE, making the twentieth century the wettest of the last seven centuries. We conclude that the instrumental rainfall record (since ~ 1900 CE) does not capture the full scale of natural hydroclimatic variability for inland southwest Australia and that the risk of prolonged droughts in the region is likely much higher than currently estimated.
... Freshwater biodiversity is considered one of the most threatened groups globally (Collen et al. 2014;Lintermans et al. 2020). Within the SWWA, freshwater species are currently threatened by several convergent issues, including ongoing aridification since the midlast century (Smith and Power 2014), habitat clearing primarily for agricultural development (Andrich and Imberger 2013), secondary salinization of rivers (Allen et al. 2020; Morgan et al. 2003) and invasive species Morgan et al. 2004). These threats will likely be exacerbated by anthropogenic climate change and their own interactive effects (Beatty et al. 2014;Stewart et al. 2022): projections of climate change alterations alone predict a 40-50% decrease in plant ranges and 10-44% loss of endemic plant diversity (294-1293 species) in the SWWA (Habel et al. 2019). ...
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Anthropogenic climate change is forecast to drive regional climate disruption and instability across the globe. These impacts are likely to be exacerbated within biodiversity hotspots, both due to the greater potential for species loss but also to the possibility that endemic lineages might not have experienced significant climatic variation in the past, limiting their evolutionary potential to respond to rapid climate change. We assessed the role of climatic stability on the accumulation and persistence of lineages in an obligate freshwater fish group endemic to the southwest Western Australia (SWWA) biodiversity hotspot. Using 19,426 genomic (ddRAD-seq) markers and species distribution modelling, we explored the phylogeographic history of western ( Nannoperca vittata ) and little ( Nannoperca pygmaea ) pygmy perches, assessing population divergence and phylogenetic relationships, delimiting species and estimating changes in species distributions from the Pliocene to 2100. We identified two deep phylogroups comprising three divergent clusters, which showed no historical connectivity since the Pliocene. We conservatively suggest these represent three isolated species with additional intraspecific structure within one widespread species. All lineages showed long-term patterns of isolation and persistence owing to climatic stability but with significant range contractions likely under future climate change. Our results highlighted the role of climatic stability in allowing the persistence of isolated lineages in the SWWA. This biodiversity hotspot is under compounding threat from ongoing climate change and habitat modification, which may further threaten previously undetected cryptic diversity across the region.
... The intensification and position of the sub-tropical ridge (STR) -the belt of surface high pressure associated with the descending branch of the Hadley Cell that dominates the southern mid-latitudes at mean sea level -has also been implicated in recently observed rainfall declines in southern Australia since the 1970s (Drosdowsky 2005;Hope et al. 2006;Pook et al. 2006;Pepler et al. 2019Pepler et al. , 2021. Lastly, modelling studies have shown that local land clearing has exacerbated the rainfall decline and increased temperatures in SWA (Pitman et al. 2004;Nair et al. 2011;Andrich and Imberger 2013). ...
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Human-induced climate change has resulted in long-term drying trends across southern Australia, particularly during the cool season, with the most pronounced impacts observed in the southwest since the 1970s. Although these trends have been linked to changes in large-scale atmospheric circulation features, the limited number of daily weather datasets that extend into the pre-industrial period have so far prevented an assessment of the long-term context of synoptic-level changes associated with global warming. To address this need, we present the development of the longest sub-daily atmospheric pressure, temperature and rainfall records for Australia beginning in 1830. We first consolidate a range of historical observations from the two southern Australian cities of Perth and Adelaide. After assessing the quality and homogeneity of these records, we verify their ability to capture the weather and climate features produced by the Southern Hemisphere’s key climate modes of variability. Our analysis shows the historical observations are sensitive to the influence of large-scale dynamical drivers of Australian climate, as well as the relationship between southwestern and southeastern Australia. Finally, we demonstrate the ability of the dataset to resolve daily weather extremes by examining three severe storms that occurred in the nineteenth century associated with westerly storm tracks that influence southern Australia. The historical dataset introduced here provides a foundation for investigating pre-industrial weather and climate variability in southern Australia, extending the potential for attribution studies of anthropogenically-influenced weather and climate extremes.
... Here we will consider the concepts of biotic pump (Makarieva and Gorshkov, 2007) and the associated condensation-induced atmospheric dynamics (CIAD). These concepts were invoked to explain spatial and temporal precipitation patterns in various regions (e.g., Andrich and Imberger, 2013;Poveda et al., 2014;Molina et al., 2019). These triggered multiple discussions (Meesters et al., 2009;Angelini et al., 2011;Makarieva et al., 2013a;Jaramillo et al., 2018Jaramillo et al., , 2019Makarieva et al., 2019;Pearce, 2020). ...
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Destabilization of the water cycle threatens human lives and livelihoods. Meanwhile our understanding of whether and how changes in vegetation cover could trigger transitions in moisture availability remains incomplete. This challenge calls for better evidence as well as for the theoretical concepts to describe it. Here we briefly summarize the theoretical questions surrounding the role of vegetation cover in the dynamics of a moist atmosphere. We discuss the previously unrecognized sensitivity of local wind power to condensation rate as revealed by our analysis of the continuity equation for a gas mixture. Using the framework of condensation-induced atmospheric dynamics, we then show that with the temperature contrast between land and ocean increasing up to a critical threshold, ocean-to-land moisture transport reaches a tipping point where it can stop or even reverse. Land-ocean temperature contrasts are affected by both global and regional processes, in particular, by the surface fluxes of sensible and latent heat that are strongly influenced by vegetation. Our results clarify how a disturbance of natural vegetation cover, e.g., by deforestation, can disrupt large-scale atmospheric circulation and moisture transport: an increase of sensible heat flux upon deforestation raises land surface temperature and this can elevate the temperature difference between land and ocean beyond the threshold. In view of the Heliyon 8 (2022) e11173 increasing pressure on natural ecosystems, successful strategies of mitigating climate change require taking into account the impact of vegetation on moist atmospheric dynamics. Our analysis provides a theoretical framework to assess this impact. The available data for the Northern Hemisphere indicate that the observed climatological land-ocean temperature contrasts are close to the threshold. This can explain the increasing fluctuations in the continental water cycle including droughts and floods and signifies a yet greater potential importance for large-scale forest conservation.
... Here we provide some insights from biotic pump (Makarieva and Gorshkov, 2007) and the associated condensation-induced atmospheric dynamics (CIAD). These concepts were invoked to explain spatial and temporal precipitation patterns in various regions (e.g., Andrich and Imberger, 2013;Poveda et al., 2014;Molina et al., 2019). These triggered multiple discussions (Meesters et al., 2009;Makarieva and Gorshkov, 2009;Angelini et al., 2011;Makarieva et al., 2013a;Jaramillo et al., 2018Jaramillo et al., , 2019Makarieva et al., 2019;Pearce, 2020). ...
... A growing body of evidence suggests that many threats to biodiversity are having increasingly negative impacts on other land uses as well as human livelihoods and well-being. For example, widespread land clearing in many areas has had significant impact on local weather and climate in Australia (Andrich & Imberger, 2013;Pitman et al., 2004) and elsewhere (McAlpine et al., 2018;Salazar et al., 2016), impacting agricultural productivity and water sources for human settlements. Similarly, widespread land clearing across large parts of Australia has resulted in major salinity issues, rendering these areas inhospitable for agriculture and biodiversity alike (Murray-Darling Basin Authority, 2015). ...
Article
Full-text available
The main effort to secure threatened species globally is to set aside land and sea for their conservation via governance arrangements such as protected areas. But not even the biggest protected area estate will cover enough area to halt most species declines. Consequently, there is a need for assessments of how species habitats are distributed across the tenure landscape, to guide policy and conservation opportunities. Using Australia as a case study, we assess the relationship between land tenure coverage and the distributions of nationally listed threatened species. We discover that on average, nearly half (48%) of Australian threatened species' distributions occur on privately owned (freehold) lands, despite this tenure covering only 29% of the continent. In contrast, leasehold lands, which cover 38% of Australia, overlap with only 6% of species' distributions while protected area lands (which cover 20%) have an average of 35% of species' distributions. We found the majority (75%; n = 1199) of species occur across multiple land tenures, and those species that are confined to a single tenure were mostly on freehold lands (13%; n = 201) and protected areas (9%; n = 139). Our findings display the opportunity to reverse the current trend of species decline with increased coordination of threat management across land tenures. We quantify the overlap of threatened species with land tenure across Australia. On average, half of threatened species' distributions occur on freehold lands and three‐quarter of the species occur across multiple land tenures.
... Here we provide some insights from biotic pump (Makarieva and Gorshkov, 2007) and the associated condensation-induced atmospheric dynamics (CIAD). These concepts were invoked to explain spatial and temporal precipitation patterns in various regions (e.g., Andrich and Imberger, 2013;Poveda et al., 2014;Molina et al., 2019). These triggered multiple discussions (Meesters et al., 2009;Makarieva and Gorshkov, 2009;Angelini et al., 2011;Makarieva et al., 2013a;Jaramillo et al., 2018Jaramillo et al., , 2019Makarieva et al., 2019;Pearce, 2020). ...
Preprint
Full-text available
Destabilization of the water cycle threatens human lives and livelihoods. Meanwhile our understanding of whether and how changes in vegetation cover could trigger abrupt transitions in moisture regimes remains incomplete. This challenge calls for better evidence as well as for the theoretical concepts to describe it. Here we briefly summarise the theoretical questions surrounding the role of vegetation cover in the dynamics of a moist atmosphere. We discuss the previously unrecognized sensitivity of local wind power to condensation rate as revealed by our analysis of the continuity equation for a gas mixture. Using the framework of condensation-induced atmospheric dynamics, we then show that with the temperature contrast between land and ocean increasing up to a critical threshold, ocean-to-land moisture transport reaches a tipping point where it can stop or even reverse. Land-ocean temperature contrasts are affected by both global and regional processes, in particular, by the surface fluxes of sensible and latent heat that are strongly influenced by vegetation. Our results clarify how a disturbance of natural vegetation cover, e.g., by deforestation, can disrupt large-scale atmospheric circulation and moisture transport. In view of the increasing pressure on natural ecosystems, successful strategies of mitigating climate change require taking into account the impact of vegetation on moist atmospheric dynamics. Our analysis provides a theoretical framework to assess this impact. The available data for Eurasia indicate that the observed climatological land-ocean temperature contrasts are close to the threshold. This can explain the increasing fluctuations in the continental water cycle including droughts and floods and signifies a yet greater potential importance for large-scale forest conservation.
... Consistent with earlier studies, our analysis shows that more arid landscapes are more variable (both rainfall and streamflow) from one year to the next. For rainfall, this variability is primarily a function of climate and weather, although possible feedbacks with land-use and ecohydrology have been proposed (Andrich & Imberger, 2013;Junkermann et al., 2009). For streamflow, with a much higher interannual variability, this variation is a function of the rainfall, but more importantly, the catchment processes that govern the water balance (Jothityangkoon et al., 2001;Ning et al., 2017;Tian et al., 2017). ...
Article
Full-text available
Links between climate variability modes, rainfall, and streamflow are important for understanding the trajectories of change and dynamics in water availability. In this study, we examined the influence of the El Nino Southern Oscillation, Indian Ocean Dipole, Southern Annular Mode, and Interdecadal Pacific Oscillation modes on interannual variations in rainfall and streamflow in four hydroclimate regions. We also explored the link between climate variability modes and extreme rainfall and streamflow years. Climate mode indices, rainfall, and streamflow data from 1975 to 2018 were analyzed for 92 predominately forested catchments located across temperate Australia. Climate modes had divergent influences on streamflow and rainfall between and within regions. Across temperate Australia, a higher proportion of interannual variation in rainfall was explained by climate modes than for streamflow, indicating factors other than atmosphere‐ocean phenomena are important in determining interannual streamflow variability. Extremes in rainfall and streamflow across regions were related to the co‐occurrence of climate modes, with a stronger relationship between teleconnections and low rainfall/streamflow years than high rainfall/streamflow years. The study provides new insights into the regional drivers of hydrological extremes and consolidates our understanding of the role of teleconnections on water availability in the temperate zone of Australia.
... Larvae are cued to hatch by flooding, and develop aquatically thereafter, reaching metamorphosis in around three months 84 . The winter rainfalls that promote breeding in this species have declined markedly in recent decades (19% reduction since the 1970s) [85][86][87] , and are projected to further decline by up to 30% by 2090 85 . Additionally, many P. guentheri populations are now isolated due to extensive clearing of habitat 88,89 , and significant declines in genetic diversity (expected heterozygosity and allelic richness) associated with repeated drought have been revealed through genomic analysis 39 . ...
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Human Impacts on Weather and Climate is a nonmathematical presentation of the basic physical concepts of how human activity may affect weather and climate. This book assesses the current hypotheses and examines whether the impacts are measurable. It critically evaluates the scientific status of weather modification by cloud seeding, human impacts on regional weather and climate, and human impacts on global climate, including the greenhouse gas hypothesis. Human Impacts on Weather and Climate will be valuable for upper-division undergraduate courses or graduate courses in meteorology, geophysics, earth and atmospheric science, as well as for policy makers and readers with an interest in how humans are affecting the atmosphere.