Integrating climate forecasts and geospatial systems to enhance grazing management in Northern Australia
Queensland Department of Primary Industries, Queensland Centre for Climate Applications, PO Box 519, Longreach, Qld, 4730
Phone 07 46584455, Fax 07 46584433
Email address parkj@dpi.qld.gov.au
Abstract
Geospatial systems were a useful tool to assess climate variability and the impacts of climate variability on grazing management. They provided a mechanism for simplifying interpretation of highly variable and complex information, they provided a regional overview of spatial variability and useful interpolation between locations where no data was available. In this study we analyse daily rainfall data to determine the impacts of El Niño Southern Oscillation (ENSO) on the timing of break-of-season rain, follow-up rain and effective rain. In addition we use models to identify the impacts of ENSO on grazing management and we suggest how pastoralists can use the Southern Oscillation Index to increase profit, induce native pasture recovery, reduce the risk of overgrazing and reduce animal mortalities.
Introduction
The grazing industry in northern Australian is important from a resource and economic viewpoint and one of its greatest challenges is the management of climate variability. Native pastures occupy about 85% of Queensland and the majority of the $1.9B produced annually from beef and sheep come from these pastures. Thirty-three percent of the total gross value of Queenslands agricultural products comes from sheep and beef cattle (1997/98). The mitchell grasslands are an important part of the northern Australian landscape occupying about 19% of Queensland. The nine shires in this case study represent nearly 25 Mha or 15% of Queensland and they consist predominantly of mitchell grass (>70%).
The region in central-west and north-west Queensland has summer dominant rainfall followed by a long and variable dry season (6 8 months). The length of the dry season, the high variability of annual rainfall (Coefficient of variation at Longreach is 45%, Clewett et al. 1999), extreme temperatures (maximum temperatures exceed 37oC for 6 months at Julia Creek, Moule 1950) and high evaporation rates (3.3 m/year at Longreach, Clewett et al. 1999) are some climatic variables that challenge pastoral managers. The timing of the dry season break, and follow-up rain, and the amount of effective summer rain are important considerations in managing climate variability in northern Australia.
The strategies and tactics pastoralists use to manage climate variability are numerous, however, they largely involve the number of livestock run (Buxton and Stafford Smith 1996, Johnston et al. 2000). One approach called safe carrying capacity is to run low numbers of stock so that in most droughts there is enough feed without needing to destock. It is implemented by adopting a safe level of utilisation of long-term pasture growth (Johnston et al. 1996 a,b). It is an objective process of assessing the safe carrying capacity of specific paddocks/properties. The process involves the use of geospatial software, land system maps, a digital cadastral database (DCDB) of property boundaries, and maps showing internal fences and other physical features of the property. Using this technology and the software to calculate carrying capacity (Cobon and Clewett 1999) maps are produced of the carrying capacity of each paddock on the property. Although over 200 individual properties have been assessed using this method, no attempt has been made to assess the climatic impacts on carrying capacity over regional scales.
Other approaches to managing climate variability in pastoral systems usually involve adjusting stock numbers more regularly, depending on feed availability (Cobon 2001), market prices, output targets, plant cover and palatable plant production (Stafford Smith 1992). Decision support packages such as WinGrasp, GrazeOn (Cobon and Clewett 1999) and GrassCheck (Forge 1994) are available to calculate sustainable stocking rates commensurate with feed availability at the paddock level, but they are not designed to demonstrate the spatial variability on regional scales. AussieGrass simulates pasture growth, feed shortages and total standing dry matter on a 5 km2 grid at the state and national level (Carter et al. 2000, Hall et al. 1999) and maps are produced to demonstrate spatial variation. These are ‘big picture’ products and are used mainly by policy makers.
State and national maps showing the probability of receiving rainfall in different phases of the Southern Oscillation Index (SOI) have been produced (Stone et al. 1996). These maps are generated from probability distributions of monthly rainfall. Australian Rainman has daily rainfall records back 80-110 years for about 3700 locations in Australia (Clewett et al. 1999). Australian Rainman provides analyses of this data to calculate the timing of rainfall events (first and second), the number of rainfall events and the amount of effective rainfall. Definitions of an event and effective rainfall are provided by the user. The analysis of these parameters to define the timing of break of dry season rains, follow-up rain and effective rain has not been completed for northern Australian regions.
El Niño Southern Oscillation (ENSO) has an impact on the seasonal rainfall, pasture growth and profit in western Queensland pastoral enterprises (Cobon 1999). The extent of these impacts however varies spatially and geospatial systems can be useful tools to demonstrate these differences to pastoralists.
In this paper we define what pastoralists in western Queensland regard as useful break-of-season rain, useful follow-up rain and effective summer rain, and calculate either when these events can be expected or the chance of receiving them between 1 September to 30 April. This paper also reports the impact of climate on: the carrying capacity of a major mitchell grass land system, pasture growth, total standing dry matter and on the safe stocking rate of a typical mitchell grass system. We use geospatial technology to demonstrate results.
Materials and methods
Daily rainfall analysis
Analysis of the timing of the break of the dry season (BSR) and follow-up rain (FUR) was completed using Australian Rainman. Daily rainfall records averaging nearly 100 years (range 80-109 years) from 12 western Queensland locations were analysed for time to first (break-of-season) and second (follow-up rain) events. A break-of-season rainfall event was classed as the amount of rain over a given period of time required to break the seasonal dry period (June to December). A group of pastoralists from the Richmond area agreed that 40 mm of rain falling within a 3 day time period would provide adequate relief to break the dry period. This paper examines 30 and 40 mm rainfall events in 3 days (referred to as BSR30 and BSR40 respectively). For each location the median date for the first and second events was calculated for all years, years when the SOI (June – August) was less than –5, between –5 and +5 and greater than +5. In terms of the analysis, the start and end of the rainfall period were 1 September and 30 April respectively. The median number of days from 1 September for the event to occur was calculated for all categories. The percentage effect of ENSO was calculated as:
% ENSO = (P – N) * 100 / 2 / M
where (P - N) is an absolute value and,
P = Median number of days from 1 September to event in years when the SOI is >+5
N = Median number of days from 1 September to event in years when the SOI is <-5
M = Median number of days from 1 September to event over all years.
The chance of a 30 or 40 mm event occurring before the 1 October, 1 November and 1 December was determined using Australian Rainman. The chance of 250 mm of effective rainfall occurring during the rainfall period (1 September to 30 April) was also examined using Australian Rainman. Effective rainfall was defined as all rainfall greater than either 30 (250Ef30) or 40 mm (250Ef40) in 3 days.
Carrying capacity
Carrying capacity was calculated for a typical mitchell grass land system (F3 on Western Arid Region Land Use System - WARLUS) in western Queensland using the process of Johnston et al. (1996a) and the Carrying Capacity evaluator (CCe) model (Cobon and Clewett 1999). To study the impact of ENSO on carrying capacity, treeless/scrubless landscapes were modelled in 18 locations using median rainfall from all years, and years when the was SOI<-5, SOI between –5 and 5 and SOI>5. CCe calculated carrying capacity at a ‘safe’ level of utilisation. The spatial analyst extension for Arc View GIS® was used to show the impacts of ENSO on carrying capacity.
Annual rainfall, pasture growth, total standing dry matter and stocking rate
Annual rainfall was analysed in WinGrasp (McKeon et al. 1990, Cobon and Clewett 1999) from climate files. Pasture growth, total standing dry matter (TSDM) and stocking rate were modelled in WinGrasp using a calibrated and validated parameter set for mitchell grasslands without trees (Day 1997). Simulations were completed for 15 locations (Blackall, Isisford, Barcaldine, Longreach, Aramac, Muttaburra, Morella, Winton, Kynuna, Corfield, Toorak Research Station, Julia Creek, Nelia, Maxwelton and Richmond) using climate data from 1957-1999. Output from simulations were grouped for all years, years when the SOI<-5, SOI between –5 and 5 and SOI>5. Stocking rate was calculated using 20% utilisation of TSDM on 1 June. ArcView GIS® was used to show the impacts of ENSO.
Results
Daily rainfall analysis
Break-of-season rainfall (BSR) - The median date for BSR, or the first event, in western Queensland was 15 December (>30 mm in 3 days) and 28 December (>40 mm in 3 days) (Table 1). Within the region median occurrence varied widely between the locations (Appendix 1). For example, the earliest occurrence was at Blackall (30 mm, 22 November; 40 mm, 21 December) which was up to 5 weeks before the latest occurrence at Winton (30 mm, 29 December; 40 mm, 15 January).
The median impact of ENSO on the timing of BSR was 12-14% (Table 1). Compared to all years, this translated to the break-of-season coming 9 days earlier in years when the SOI (June August) was greater than 5, and 21 days later in years when the SOI was less than –5. However the impact of ENSO varied widely between locations, the range being zero (Isisford and Julia Creek) to 26% (Tangorin) (Figure 1a, Appendix 1). At Tangorin, the median timing of BSR (40 mm in 3 days) was 2 months later in SOI<-5 years compared to SOI>5 years, however in western Queensland the average was about one month later.
The mean chance of BSR30 and BSR40 occurring in western Queensland before 1 October was 8% and 5% respectively (Table 1). By 1 November the respective chances were 23% and 15% and by 1 December were 39% and 28% respectively (Appendix 2).
Follow-up rainfall (FUR) - The median date for FUR, or the second event, was 4 weeks (30 mm, 15 January) and 5 weeks (40 mm, 8 February) after the BSR (Table 1). The timing of the FUR varied across the region with the earliest occurring on 31 December (Blackall 30 mm) and 18 January (Richmond 40 mm). This was 4 and 7 weeks earlier than the last FUR which occurred on 30 January (30 mm Winton) and on 9 March (Arrilalah 40 mm).
The median impact of ENSO on the timing of FUR was 12-15% (Table 1). Compared to all years, this translated to the FUR coming about 2 weeks earlier in years when the SOI (June-August) was greater than 5, and 2 weeks later in years when the SOI was less than –5.
At Arrilalah, Isisford and Muttaburra the median time of FUR did not occur within 12 months in the years when the SOI was less than 5, which resulted in elevated % ENSO (46, 54 and 66% respectively) (Figure 1b, Appendix 1).
Effective rainfall – The average chance of receiving 250Ef30 and 250Ef40 in western Queensland between 1 September and 30 April was 42 and 33% respectively (Table 1). The respective ranges were 28-55% (Arrilalah and Richmond) and 19-45% (Arrilalah and Richmond). In years when the SOI was >5 the average chance of 250Ef30 and 250Ef40 in western Queensland was 10 and 8% units respectively higher than all years. However, the SOI influence was greater in north-eastern locations (Muttaburra, Richmond, Tangorin) with a 16-23% units greater chance of receiving either 250EF30 or 250Ef40 in SOI >5 years compared to all years (Appendix 3).
Carrying capacity
The mean carrying capacity for the treeless mitchell grasslands (F3 land system WARLUS) in all years was 53 DSE/km2 (Table 1). The potential carrying capacity was 74 DSE/km2 (years when SOI>5) or about 40% higher than all years. The impact of ENSO on carrying capacity was 25% and much of this impact was generated by greater discrimination in years when the SOI>5 (% increase in SOI>5 years compared to all years > % decrease in years when the SOI<-5 compared to all years) (Appendix 4).
Annual rainfall, pasture growth, total standing dry matter and stocking rate
The average annual rainfall, pasture growth, TSDM and stocking rate was 435 mm, 1940 kg/ha, 1693 kg/ha and 84 DSE/km2 respectively (Table 1).
ENSO had a significant but variable impact on mean rainfall (27%), pasture growth (35%), TSDM (32%) and stocking rates (10%) in western Queensland (Table 1, Figures 1d-g, Appendix 5). This impact was generated mainly because the SOI was relatively more efficient at discriminating the better years (SOI>5) than the poorer years (SOI<-5) compared to all years. For example, the percent increase in SOI>5 years compared to all years for rainfall, pasture growth and TSDM was 40, 48 and 47% respectively. As a comparison, the percent decrease in SOI<-5 years, compared to all years, was 15, 21 and 17% respectively.
Discussion
In northern Australia climate has a large impact on vegetation and animal production. This paper examines the impact ENSO has on break-of-season rainfall, follow-up rain, effective rain, potential long-term safe carrying capacity, growth of native grasses and stocking rate. However, as Lou Gerstner (IBM, CEO) once said ‘You do not get points for predicting rain - you get points for building arks,’ and so packaging the outcomes of climate applications research so it can be applied for some benefit is as important as knowing the climate impacts. Spatial representation of research outcomes is a way of helping people better interpret complex and highly variable information. The geospatial maps in this paper provide a colourful and readily interpretable overview of the regional impacts of ENSO on a range of parameters important in on-property decision making. Examples of some decisions that can be altered depending on the SOI and possible outcomes can be summarised as:
Decisions |
Outcomes | |
Right decision is made and forecast was correct |
Right decision is made but the forecast was wrong | |
adjusting stock numbers |
improve profits |
reduce profit |
sending to or taking on agistment stock |
reduce risk of overgrazing |
increase risk of overgrazing |
altering joining dates |
reduce stock mortalities |
increase risk of higher mortalities |
native seed harvesting |
stimulate native grass recovery |
increase drought risk |
pasture establishment |
reduce drought risk |
increase risk of low grass cover and soil loss |
woody weed control |
pests and weeds controlled |
|
burning |
||
pest and disease control |
||
supplement |
Break-of-season rain occurred in most years in mid to late December in western Queensland. In most centres there was less than 25% chance of it occurring before 1 November. The SOI forecast provided a one month buffer for break-of-season and follow-up rain and therefore provided a small window of opportunity for adjusting stock numbers, burning and supplementation. Centres like Tangorin had a two month buffer and a wider window of opportunity but at Julia Creek the SOI had little impact on the timing of break-of-season rains, which offers little opportunity for changing decisions.
Follow-up rain occurred on average 4-5 weeks after break-of-season rains in mid January to early February. This rain is important for continued grass growth and the initiation of forb growth. Forbs are selectively grazed by stock, are highly palatable and nutritious and contribute significantly to livestock production. Pastoralists breeding sheep can alter the time of joining ewes in order to take advantage of the high nutrient content of forbs at a time when pregnant/lactating ewes are in most need of nutrients.
250 mm of effective rain between September and April should provide adequate pasture of sufficient quality to produce a good year for animal production. This rainfall occurred on average at least once every three years but the chance was significantly higher when the SOI was >5. Knowing this information by the 1 September provides an opportunity for graziers to increase stock numbers (purchase stock, take-on agistment stock) or undergo pasture regeneration activities.
By definition safe carrying capacity is a low level of grazing pressure to avoid the need to destock in 80% of years. It is a strategy designed to help manage the variability in pasture production caused by climate variability. Maps showing carrying capacity at regional scales provide a useful overview of the impacts of climate variability.
Annual rainfall, pasture growth and TSDM were about 50% greater in SOI>5 years compared to all years. The variation in pasture availability at the end of the growing season (1 June) provides an opportunity to purchase animals to fully utilise feed supplies in good years, and sell animals in poor years to rest pasture and restore resource condition. The concept and timing of flexible grazing management means that seasonal forecasting can be readily incorporated. With existing forecast skill and lead-times the value of a forecast for a western Queensland sheep enterprise averages about $1 per hectare/year (Cobon and McKeon 2000).
This paper has shown how geospatial technology has been used to show the extent of climate variability and the impacts of climate on pastoral enterprises. It has been a useful tool to simplify the interpretation of large and complex data sets and provide an overview of climate variability and climate impacts on a regional scale.
References
Buxton, R. and Stafford Smith, M. (1996). Managing drought in Australia’s rangelands: four weddings and a funeral. Rangeland Journal, 18 (2), 292-308.
Carter, J.O., Hall, W.B., Brook, K.D., McKeon, G.M., Day, K.A. and Paull, C.J. (2000). AussieGrass: Australian Grassland and Rangeland Assessment by Spatial Simulation. In Applications of seasonal climate forecasting in agricultural and natural ecosystems – The Australian Experience. (Ed. G.L. Hammer, N Nicholls and C. Mitchell), Kluwer Academic , The Netherlands. pp. 329-49.
Clewett, J.F., Smith, P.G., Partridge, I.J., George, D.A. and Peacock, A. (1999). Australian Rainman Version 3: An integrated package of rainfall information for better management. QI98071, Department of Primary Industries Queensland.
Cobon, D.H. (1999). Use of seasonal climate forecasts for managing grazing systems in western Queensland. In Proceedings of the VI th International Rangelands Congress, July 1999, Townsville. pp. 855-57.
Cobon, D.H. (2001). Safe stocking rates based on pasture supply and demand for the mitchell grasslands in central and north-west Queensland. I. Development and evaluation of a model. Rangeland Journal (submitted for publication)
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Day, K.A., McKeon, G.M. and Carter, J.O. (1997). Evaluating the risks of pasture and land degradation in native pasture in Queensland. Final report to Rural Industries and Research Development Corporation project DAQ124A.
Forge, K. (1994). GrassCheck – Grazier Rangeland Assessment for Self Sustainablity. Department of Primary Industries Queensland, Information Series QI94005.
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Johnston, P.W., McKeon, G.M., Buxton, R., Cobon, D.H., Day, K., Hall, W. and Scanlan, J. (2000). Managing climate variability in Queenslands grazing lands: New approaches. In Applications of seasonal climate forecasting in agricultural and natural ecosystems – The Australian Experience. (Ed. G.L. Hammer, N Nicholls and C. Mitchell), Kluwer Academic, The Netherlands. pp. 197-226.
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Johnston, P.W., Tannock, P.R. and Beale, I.F. (1996b). Objective ‘safe’ grazing capacities for south west Queensland Australia: Model application and evaluation. Rangeland Journal, 18 (2), 259-69.
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Moule, G.R. (1950). Some problems of sheep breeding in semi arid tropical Queensland. Australian Veterinary Journal 26, 29-37.
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Table 1. Median date of break-of-season rainfall (BSR), follow-up rainfall (FUR) and percent chance of BSR, 250 mm effective rain (September-April). Mean carrying capacity of a typical mitchell grass land system and rainfall, pasture growth, total standing dry matter (TSDM) and stocking rate (20% utilisation) on the 1 June for locations in nine shires of western Queensland in different categories of the Southern Oscillation Index (SOI). The percent impact of El Niño Southern Oscillation (ENSO) is shown for some parameters
Parameter |
SOI<-5 |
SOI Neutral |
SOI>5 |
All Years |
% ENSO |
BSR 30mm |
27 Dec |
13 Dec |
29 Nov |
15 Dec |
14 |
BSR 40 mm |
17 Jan |
27 Dec |
19 Dec |
28 Dec |
12 |
FUR 30mm |
1 Feb |
14 Jan |
30 Dec |
15 Jan |
12 |
FUR 40mm |
23 Feb |
7 Feb |
28 Jan |
8 Feb |
15 |
Chance BSR 30mm (%) |
|||||
1 October |
4 |
8 |
12 |
8 |
|
1 November |
9 |
26 |
29 |
23 |
|
1 December |
25 |
40 |
51 |
39 |
|
Chance BSR 40mm (%) |
|||||
1 October |
2 |
4 |
8 |
5 |
|
1 November |
6 |
16 |
23 |
15 |
|
1 December |
16 |
26 |
43 |
28 |
|
Chance of effective rain (%) |
|||||
250 effective 30mm |
35 |
41 |
52 |
42 |
|
250 effective 40mm |
33 |
30 |
40 |
33 |
|
Carrying capacity (DSE/km2) |
48 |
50 |
74 |
53 |
25 |
Annual rainfall (mm) |
371 |
426 |
610 |
435 |
27 |
Pasture growth (kg/ha/yr) |
1531 |
1960 |
2872 |
1940 |
35 |
TSDM (kg/ha) |
1414 |
1708 |
2489 |
1693 |
32 |
Stocking rate (DSE/km2) |
79 |
83 |
96 |
84 |
10 |
Figure 1. Geospatial maps showing the percent impact of El Niño Southern Oscillation (ENSO) in western Queensland for a) median of break-season-rain b) median date of follow-up rain c) carrying capacity d) annual rainfall e) pasture growth f) total standing dry matter and f) stocking rate.
Appendix 1. Median date of break-of-season and follow-up rainfall events in 12 western Queensland locations with the rainfall period from 1 September to 30 April and SOI from June to August. Median values for all locations in western Queensland (WQld) are shown
Location |
First event 30 mm in 3 days |
Second event 30 mm in 3 days | ||||||||
SOI |
SOI Zero |
SOI |
All years |
% |
SOI |
SOI Zero |
SOI |
All years |
% | |
Aramac |
26 Dec |
12 Dec |
13 Nov |
12 Dec |
21 |
04 Feb |
13 Jan |
30 Dec |
15 Jan |
13 |
Arrilalah |
31 Dec |
17 Dec |
10 Dec |
19 Dec |
10 |
11 Feb |
04 Feb |
29 Dec |
28 Jan |
15 |
Barcaldine |
27 Dec |
02 Dec |
13 Nov |
07 Dec |
23 |
03 Feb |
05 Jan |
27 Dec |
08 Jan |
15 |
Blackall |
01 Dec |
19 Nov |
11 Nov |
22 Nov |
12 |
09 Jan |
02 Jan |
03 Dec |
31 Dec |
15 |
Isisford |
18 Dec |
09 Dec |
27 Nov |
10 Dec |
11 |
27 Jan |
11 Jan |
13 Jan |
15 Jan |
5 |
Julia Creek |
17 Dec |
17 Dec |
07 Dec |
14 Dec |
5 |
04 Jan |
14 Jan |
30 Dec |
11 Jan |
2 |
Kynuna |
07 Jan |
25 Dec |
21 Dec |
27 Dec |
7 |
09 Feb |
23 Jan |
13 Jan |
27 Jan |
9 |
Longreach |
04 Jan |
08 Dec |
22 Dec |
15 Dec |
6 |
25 Jan |
14 Jan |
14 Jan |
16 Jan |
4 |
Muttaburra |
07 Jan |
20 Dec |
09 Dec |
21 Dec |
17 |
11 Feb |
15 Jan |
09 Jan |
21 Jan |
12 |
Richmond |
25 Dec |
14 Dec |
23 Nov |
16 Dec |
15 |
25 Jan |
09 Jan |
18 Dec |
06 Jan |
15 |
Tangorin |
22 Dec |
09 Dec |
20 Nov |
13 Dec |
16 |
29 Jan |
12 Jan |
25 Dec |
11 Jan |
13 |
Winton |
18 Jan |
28 Dec |
05 Dec |
29 Dec |
18 |
11 Feb |
30 Jan |
07 Jan |
30 Jan |
12 |
W Qld |
27 Dec |
13 Dec |
29 Nov |
15 Dec |
14 |
01 Feb |
14 Jan |
30 Dec |
15 Jan |
12 |
First event 40 mm in 3 days |
Second event 40 mm in 3 days | |||||||||
Aramac |
06 Jan |
20 Dec |
15 Dec |
26 Dec |
9 |
19 Mar |
06 Feb |
17 Jan |
06 Feb |
20 |
Arrilalah |
31 Jan |
01 Jan |
27 Dec |
03 Jan |
14 |
1 year + |
23 Feb |
10 Mar |
09 Mar |
46 |
Barcaldine |
18 Jan |
20 Dec |
08 Dec |
25 Dec |
18 |
23 Apr |
03 Feb |
31 Jan |
08 Feb |
26 |
Blackall |
31 Dec |
22 Dec |
24 Nov |
21 Dec |
17 |
31 Jan |
30 Jan |
12 Jan |
26 Jan |
6 |
Isisford |
28 Dec |
18 Dec |
27 Dec |
22 Dec |
0 |
1 year + |
07 Feb |
04 Mar |
14 Feb |
54 |
Julia Creek |
27 Dec |
30 Dec |
28 Dec |
29 Dec |
0 |
25 Jan |
27 Jan |
13 Jan |
25 Jan |
4 |
Kynuna |
15 Jan |
06 Jan |
27 Dec |
03 Jan |
8 |
16 Feb |
07 Feb |
29 Jan |
07 Feb |
6 |
Longreach |
18 Jan |
24 Dec |
28 Dec |
29 Dec |
9 |
26 Feb |
08 Feb |
25 Feb |
15 Feb |
0 |
Muttaburra |
01 Feb |
06 Jan |
14 Dec |
07 Jan |
19 |
1 year + |
10 Feb |
26 Jan |
13 Feb |
66 |
Richmond |
06 Jan |
30 Dec |
06 Dec |
27 Dec |
13 |
11 Feb |
31 Jan |
24 Dec |
18 Jan |
18 |
Tangorin |
19 Jan |
22 Dec |
21 Nov |
22 Dec |
26 |
15 Feb |
12 Feb |
05 Jan |
07 Feb |
13 |
Winton |
21 Jan |
15 Jan |
22 Dec |
15 Jan |
11 |
19 Feb |
25 Feb |
30 Jan |
18 Feb |
6 |
W Qld |
17 Jan |
27 Dec |
19 Dec |
28 Dec |
12 |
23 Feb |
07 Feb |
28 Jan |
08 Feb |
15 |
Appendix 2. Chance of receiving break-of-season rain by the first of October, November and December in 12 western Queensland locations. The rainfall period was from 1 September to 30 April and SOI from June to August. An average for western Queensland is shown.
Location |
% chance of 30 mm in 3 days by |
% chance of 40 mm 3 days by | ||||||||
SOI < 5 |
SOI Zero |
SOI > 5 |
All years |
SOI < 5 |
SOI Zero |
SOI > 5 |
All years | |||
Aramac |
1 Oct |
0 |
14 |
14 |
10 |
0 |
10 |
10 |
8 | |
1 Nov |
15 |
29 |
38 |
28 |
8 |
24 |
31 |
22 | ||
1 Dec |
27 |
41 |
59 |
42 |
15 |
33 |
48 |
33 | ||
Arrilalah |
1 Oct |
5 |
4 |
12 |
6 |
5 |
0 |
12 |
4 | |
1 Nov |
9 |
22 |
31 |
22 |
9 |
11 |
23 |
14 | ||
1 Dec |
23 |
33 |
46 |
34 |
18 |
18 |
42 |
25 | ||
Barcaldine |
1 Oct |
7 |
10 |
17 |
11 |
4 |
8 |
10 |
7 | |
1 Nov |
14 |
35 |
38 |
30 |
7 |
19 |
31 |
19 | ||
1 Dec |
29 |
48 |
62 |
47 |
14 |
29 |
45 |
29 | ||
Blackall |
1 Oct |
7 |
13 |
24 |
15 |
4 |
8 |
14 |
8 | |
1 Nov |
14 |
40 |
48 |
36 |
7 |
21 |
34 |
21 | ||
1 Dec |
46 |
54 |
62 |
54 |
29 |
29 |
55 |
36 | ||
Isisford |
1 Oct |
11 |
12 |
21 |
14 |
4 |
6 |
14 |
7 | |
1 Nov |
11 |
29 |
38 |
27 |
7 |
21 |
24 |
18 | ||
1 Dec |
29 |
44 |
52 |
42 |
21 |
35 |
38 |
32 | ||
Julia Creek |
1 Oct |
0 |
5 |
5 |
4 |
0 |
0 |
5 |
1 | |
1 Nov |
5 |
18 |
19 |
15 |
5 |
13 |
10 |
10 | ||
1 Dec |
35 |
31 |
38 |
34 |
30 |
21 |
33 |
26 | ||
Kynuna |
1 Oct |
0 |
2 |
7 |
3 |
0 |
0 |
7 |
2 | |
1 Nov |
8 |
22 |
18 |
18 |
4 |
12 |
18 |
12 | ||
1 Dec |
16 |
31 |
46 |
31 |
8 |
20 |
43 |
24 | ||
Longreach |
1 Oct |
8 |
4 |
11 |
7 |
4 |
4 |
7 |
5 | |
1 Nov |
12 |
24 |
19 |
19 |
8 |
18 |
15 |
15 | ||
1 Dec |
23 |
46 |
41 |
39 |
12 |
32 |
26 |
25 | ||
Muttaburra |
1 Oct |
4 |
7 |
13 |
8 |
4 |
5 |
8 |
6 | |
1 Nov |
4 |
19 |
33 |
19 |
4 |
9 |
25 |
12 | ||
1 Dec |
17 |
40 |
46 |
36 |
9 |
21 |
42 |
23 | ||
Richmond |
1 Oct |
0 |
4 |
0 |
2 |
0 |
4 |
0 |
2 | |
1 Nov |
5 |
20 |
17 |
15 |
0 |
16 |
17 |
12 | ||
1 Dec |
14 |
31 |
58 |
34 |
9 |
20 |
50 |
25 | ||
Tangorin |
1 Oct |
0 |
9 |
8 |
7 |
0 |
5 |
4 |
3 | |
1 Nov |
5 |
33 |
29 |
25 |
5 |
19 |
25 |
17 | ||
1 Dec |
27 |
44 |
58 |
44 |
18 |
30 |
54 |
34 | ||
Winton |
1 Oct |
4 |
6 |
10 |
6 |
4 |
2 |
7 |
4 | |
1 Nov |
11 |
17 |
21 |
17 |
7 |
10 |
17 |
11 | ||
1 Dec |
18 |
37 |
48 |
35 |
14 |
23 |
34 |
24 | ||
W Qld |
1 Oct |
4 |
8 |
12 |
8 |
2 |
4 |
8 |
5 | |
1 Nov |
9 |
26 |
29 |
23 |
6 |
16 |
23 |
15 | ||
1 Dec |
25 |
40 |
51 |
39 |
16 |
26 |
43 |
28 |
Appendix 3. Percentage chance of receiving 250 mm of effective rain (all rainfall greater than either 30 or 40 mm in 3 days) at 12 different locations in western Queensland. Average values for western Queensland are shown. The difference between years with SOI>5 and all years indicates the locations where ENSO is having greatest impact
Location |
250Ef30 |
250Ef40 | ||||||
SOI < 5 |
SOI > 5 |
All years |
Difference (SOI>5 All years) |
SOI < 5 |
SOI > 5 |
All years |
Difference (SOI>5 All years) | |
Aramac |
31 |
45 |
41 |
4 |
27 |
34 |
30 |
4 |
Arrilalah |
32 |
31 |
28 |
3 |
32 |
15 |
19 |
4 |
Barcaldine |
28 |
48 |
41 |
7 |
18 |
31 |
25 |
6 |
Blackall |
46 |
55 |
49 |
6 |
36 |
45 |
36 |
9 |
Isisford |
29 |
41 |
33 |
8 |
29 |
24 |
27 |
3 |
Julia Creek |
45 |
53 |
54 |
1 |
45 |
43 |
46 |
3 |
Kynuna |
30 |
50 |
45 |
5 |
32 |
43 |
37 |
6 |
Longreach |
27 |
52 |
37 |
15 |
27 |
37 |
30 |
7 |
Muttaburra |
32 |
59 |
38 |
21 |
30 |
46 |
29 |
17 |
Richmond |
47 |
73 |
55 |
18 |
44 |
65 |
48 |
17 |
Tangorin |
43 |
64 |
48 |
16 |
41 |
63 |
40 |
23 |
Winton |
33 |
47 |
39 |
8 |
29 |
34 |
29 |
5 |
W Qld |
35 |
52 |
42 |
10 |
33 |
40 |
33 |
7 |
Appendix 4. Average carrying capacity (DSE/km2) of mitchell grasslands without trees in years when the SOI<-5, SOI neutral, SOI>5 and all years. The percentage impact of El Nino Southern Oscillation (% ENSO) is shown for locations in nine western Queensland shires
Location |
SOI<-5 |
SOI Neutral |
SOI>5 |
All Years |
% ENSO |
Aramac |
54 |
61 |
85 |
64 |
24 |
Barcaldine |
55 |
62 |
90 |
67 |
26 |
Blackall |
61 |
66 |
102 |
69 |
29 |
Isisford |
55 |
51 |
81 |
57 |
23 |
Kynuna |
42 |
44 |
68 |
46 |
29 |
Richmond |
52 |
53 |
81 |
55 |
27 |
Tangorin |
51 |
54 |
75 |
54 |
22 |
Winton |
40 |
45 |
75 |
48 |
36 |
Property A |
56 |
51 |
68 |
58 |
10 |
Property B |
39 |
43 |
66 |
44 |
30 |
Property C |
48 |
48 |
73 |
51 |
24 |
Property K |
64 |
48 |
76 |
53 |
11 |
Property L |
39 |
43 |
66 |
44 |
30 |
Property Lo |
38 |
42 |
65 |
43 |
30 |
Property R |
43 |
53 |
70 |
54 |
25 |
Property T |
43 |
38 |
62 |
44 |
21 |
Property V |
46 |
53 |
75 |
55 |
26 |
Property W |
38 |
42 |
64 |
43 |
31 |
Appendix 5. Average rainfall, pasture growth, total standing dry matter (TSDM) and stocking rate in years when the SOI<-5, SOI near zero, SOI>5 and all years. The percentage impact of El Nino Southern Oscillation (% ENSO) is shown for locations in nine western Queensland shires