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Frost risk in New South Wales wheat belt

De Li Liu1, Brendan J Scott1, U.C. Pradhan2, Peter Martin1 and Chris Cole2

1NSW Agriculture, Wagga Wagga Agricultural Institute, PMB, Wagga Wagga, NSW 2650, Australia
de.li.liu@agric.nsw.gov.au
brendan.scott@agric.nsw.gov.au peter.martin@agric.nsw.gov.au
2
NSW Agriculture, LMB 21, 161 Kite St, Orange, NSW 2800, Australia udai.pradhan@agric.nsw.gov.au chris.cole@agric.nsw.gov.au

Abstract

Frost damage to wheat crops is a major climatic risk for farmers in NSW. Farmers are faced with decisions on choice of sowing date and variety to minimise the frost risk at the critical time of flowering. We analysed frost risk in the NSW wheat belt using 2C in the Stevenson screen as the critical temperature for frost damage to flowering wheat. The dates with a probability of a frost event less than or equal to 20%, 10% and 5% were estimated. The average dates for last frost were positively related to latitude and altitude. The dates for frost risk probability of 20%, 10% and 5% may be delayed by a week if the latitude is increased by 1.5, 1.4 and 1.2S, respectively. Every 76 m increase in altitude delayed the dates of frost risk by one week. The information may be used as an aid by farmers and advisers.

Key Words

Frost probability, frost temperature, wheat, climate variability

Introduction

Frost damage to wheat crops is one of main climatic risks for farmers in NSW. Farmers are faced with decisions on choice of sowing date and variety to minimise the frost risk at the critical crop stage around flowering. However, if the crop is sown late, crop yield is generally low (6). Early flowering in the absence of frosts produces higher yields as the grain filling occurs during more favourable temperatures and potentially less drought stress. Therefore, sowing time and variety choice are the variables farmers have to optimise flowering time with a minimum risk of frost and high yield potential.

The critical temperature for frost damage to a wheat crop varies with stage of crop development (4, 8). During vegetative stages, plants are not affected by frost in the Australian wheat belt (8). Before stem elongation, the critical temperature for frost damage to wheat can be as low as -8C, while the critical temperature for frost damage to the crop at stem elongation is -4C (4). The most susceptible stage for frost damage is at flowering. At this stage, critical temperature is reported as -2 to -2.5C (4). In this study, we analysed the historical climatic data and estimated the frost risk in the NSW wheat belt.

Methods

Minimum temperature data were obtained from MetAccess (2). Sites with a minimum of 30 years of records for minimum temperature were selected. A total of 38 sites were selected within the NSW wheat belt. The minimum temperature causing damage was taken as -2C (4). Because air temperature recorded at meteorology stations can be greater than those of crops in the field (temperature sensors are often located at post offices) minimum temperature below 2.0C recorded in the Stevenson screen is often used as critical temperature for frost (3, 5). However, minimum temperature of ≤1.3C (9) or ≤2.2C (4) have been used as critical frost temperatures. Thus, the critical temperature for a frost event is defined as a temperature of ≤2C in the screen in this study. Because the frequency is calculated based on mostly 30-40 years of records, fluctuations in frequency curves are often observed. In order to reduce the impact of the fluctuations, the initial frost probability is smoothed by a 14 day moving average. This technique makes long term trends of a time series clearer. The 20%, 10% and 5% frost risk means that occurrence of a frost event after that day is 1 in 5 years, 1 in 10 years and 1 in 20 years, respectively.

Table 1.The dates of last frost for probability that is less or equate to 20%, 10% and 5% in NSW wheat belt.

Site no & Name

Lat (oS)

Alt
(m)

No years

FRP 20%

FRP
10%

FRP
5%

Northern

           

1 Mungidi

28.98

160

31

18-Aug

31-Aug

08-Sep

2 Moree

29.48

212

38

28-Aug

13-Sep

28-Sep

3 Collarenabri

29.55

145

34

30-Aug

10-Sep

28-Sep

4 Brewarrina

29.97

115

37

08-Aug

29-Aug

01-Sep

5 Walgett

30.02

131

36

12-Aug

31-Aug

08-Sep

6 Narrabri

30.33

212

40

31-Aug

20-Sep

01-Oct

7 Barraba

30.38

500

36

06-Oct

18-Oct

31-Oct

8 Coonamble

30.98

180

37

25-Aug

07-Sep

16-Sep

9 Gunnedah

30.98

306

37

04-Aug

28-Aug

08-Sep

10 Tamworth

31.08

400

45

03-Sep

24-Sep

04-Oct

11 Coonabarabran

31.25

505

45

03-Oct

18-Oct

29-Oct

12 Quiridi

31.50

390

37

27-Sep

06-Oct

12-Oct

Mean

     

31-Aug

16-Sep

27-Sep

Central

           

13 Nyngan

31.53

13

32

24-Aug

02-Sep

12-Sep

14 Trangie1

32.00

215

33

12-Sep

01-Oct

07-Oct

15 Dundoo

32.02

388

37

28-Sep

09-Oct

25-Oct

16 Dubbo

32.22

275

43

05-Sep

28-Sep

06-Oct

17 Wellington

32.52

394

36

30-Aug

21-Sep

05-Oct

18 Mudgee

32.55

471

40

01-Oct

12-Oct

30-Oct

19 Peak hill

32.72

267

37

19-Aug

31-Aug

27-Sep

20 Condobolin

33.08

199

35

28-Sep

06-Oct

12-Oct

21 Parkes

33.13

330

32

23-Aug

04-Sep

21-Sep

22 L Cargelligo

33.27

169

34

30-Aug

10-Sep

30-Sep

23 Forbes

33.38

240

45

20-Sep

04-Oct

12-Oct

24 Cowra

33.80

380

37

24-Aug

03-Sep

04-Oct

25 Hillston

33.83

122

45

27-Aug

19-Sep

26-Sep

26 Grenfell

33.90

384

34

02-Sep

28-Sep

05-Oct

27 West Wyalong

33.93

245

37

02-Sep

29-Sep

05-Oct

Mean

     

05-Sep

21-Sep

05-Oct

Southern

           

28 Young

34.25

380

34

10-Oct

01-Nov

14-Nov

29 Griffith

34.30

126

37

05-Sep

30-Sep

12-Oct

30 Temora

34.40

270

37

03-Oct

15-Oct

30-Oct

31 Hay

34.52

93

45

09-Aug

05-Sep

22-Sep

32 Balranald

34.63

61

33

26-Aug

17-Sep

26-Sep

33 Cootamundra

34.63

318

39

01-Oct

12-Oct

25-Oct

34 Narranddera

34.72

160

32

12-Sep

05-Oct

11-Oct

35 Wagga Wagga

35.12

220

60

26-Sep

09-Oct

29-Oct

36 Deniliqu

35.55

93

39

23-Aug

22-Sep

03-Oct

37 Tocumwal

35.80

114

31

26-Aug

11-Sep

27-Sep

38 Albury

36.10

184

37

09-Aug

30-Aug

26-Sep

Mean

07-Sep

27-Sep

12-Oct

Linear regression was used to quantify the effect of latitude and altitude on the date at various frost risk probabilities. In order to allow the model to be applied at low latitude and high altitude that are not covered by the selected sites in NSW wheat belt, a few lower latitude and higher altitude sites other than in the NSW wheat belt are included. They are St George, (lat. 28.02S , alt. 201 m), Dalby (lat. 27.17S, alt. 344 m) and Toowoomba (24.58S, alt. 675 m) from Queensland, and Tumut (35.33S, alt. 305 m) and Yass (34.83S, alt. 520 m) from New South Wales. The NSW wheat belt sites are listed in Table 1. The model was also presented by estimating frost risk from the model for points on a GIS map with known location and altitude

Results

Table 1 shows the dates for the occurrence of last frost for the 20%, 10% and 5% probabilities. NSW wheat belt was arbitrarily divided into three regions with a latitude range: northern ≤ 31.5S; 31.5S < central ≤ 34S; southern > 34.0S. The dates of frost probability in northern region, at 20%, 10% and 5% were 31 August, 16 September and 27 September, respectively. This compares with the southern region where the respective dates were 7 September, 27 September and 12 October. There was about one week delay for each frost probability from northern to central and from central to southern region.

Altitude had a large effect on the frost occurrence. Within the same region, the latest frost risk dates all corresponded with the highest altitude. The highest altitude was 500 m at Barraba in northern, 471 m at Mudgee in central and 380 m at Young in the southern region. They had 5% frost probability of 31 October, 30 October and 14 November, respectively. The site with the lowest altitude had the earliest dates for 5% frost probability in northern and central regions. However, in southern region, the lowest altitude was 61 m at Balranald, which had a 5% frost risk date of 26 September. The earliest date for this event in this region is 22 September at Hay

To quantify the effect of latitude and altitude, we used the linear regression of day of year (DOY) at a defined frost risk probability as a function of latitude and

altitude:

(1)

Where Dα is the DOY at α % FRP, Λ is the latitude (S), and Δ is the altitude (m). The results were

R2=0.45, (2)

R2=0.54, (3)

R2=0.65, (4)

All coefficients were significantly different from zero (p<0.001).

The model was compared with dates of frost risk probability, which were estimated from climatic data, to examine the agreement of the regression (Figure 1). The latitude and altitude account for the 45%, 54% and 65% of total variation. This suggested a large proportion of variation is due to other local factors. There was a greater dispersion between fitted values and measured values at 20%, indicating the model performed worse in the high frost risk probability than low risk probability. This also can be seen from the coefficient of determination (R2): the lower the frost risk probability, the higher the value of R2.

The reasons for these big deviations are unknown. The unknown factors may include rainfall, position in the landscape and the position of weather station relative to buildings etc. Loss (1989) reported that for two recording sites about 400 m apart, 4C differences in minimum temperatures were recorded. In our studies, using the combined data of three Albury sites (Albury Airport, lat. 36.07 S, alt.165 m; Albury Grammar School, 36.07 S, 183 m and Albury Pumping Station, 36.08 S, 182 m), the dates for 20%, 10%, and 5% risk were 31, 35, 18 days later than the reported in Table 1 (for Hume Reservoir, 36.1oS, alt. 184 m). The dates for the respective frost risk probability were 5 days earlier, the same and 5 days later than that predicted by Eqs, 2, 3, and 4, respectively. This was compared with 38 days, 36 days and 24 days overestimated, using the data of Hume Reservoir, for 20%, 10% and 5% risk, respectively. The temperature data recorded at Hume Reservoir may be warmer than nearby recording stations as the micro-environment may be different due to the body of water in the reservoir. Estimation using data from Hume reservoir gave earlier dates than other sites nearby. Simulating two sites near Wagga Wagga shows that Soil Con. Services (lat. 35.13, alt. 222 m) were, respectively, 7, 11 and 17 days’ earlier than that at Wagga Wagga AMO. The differences at Wagga Wagga and the Albury example show the importance that locality can have on frost. Users should be aware of the limitations of the model.

Figure 1. Comparison of day of year (DOY) at 20%, 10% and 5% frost risk probability (FRP) determined by climatic data (measured DOY) and calculated DOY by Eqs. 2, 3 and 4 (fitted DOY)

One-degree of latitude increase delayed the dates for frost risk by 4.7, 5.0 and 5.9 days at 20%, 10% and 5%, respectively. Increase in latitude of 1.5, 1.4, 1.2S delayed frost risk date by a week for 20%, 10% and 5% frost probability. Every 100 m increase in altitude will gave a delay of about 9 days for all three frost risk probabilities. Thus, if the altitude has 76 m higher than a reference location, the expected date for a frost risk will be a week later. The frost risk we have defined is present in Figs 2, 3, and 4 by interpreting the models (Eqs 2, 3, and 4) using a digitised map with known altitude. The figures give an overview of the general frost risk in the NSW wheat belt. DOY is presented as a date on a line and towns are numbered as for Table 1. Variation in dates for any frost risk probability is much greater in the eastern than in western part of the wheat belt indicated by dense lines alone the eastern side of the wheat belt.

The date for 10% frost risk was 9 October at Wagga Wagga. Plant breeders have traditionally used a targeted flowering date of 10 October for selecting varieties for this region.

Conclusion

Frost risk for flowering wheat crops in NSW has been broadly described; altitude and latitude have a major effect on the probability of frost. Local effects can be important but are not included in the model

References

(1) Boer, R., Campbell, L.C. and Fletcher, D.J. (1993) Aust. J. Agric. Res. 44:1731-43.

(2) Donnelly, J.R., Moore, A.D., Freer, M. (1997). Agric. Syst. 54:57-76.

(3) Kelleher, F.M. Rollings, N.M., Poulton, D.M. and Cornish, P.S. (2001). 10th Aust Agron Conf, Horbart.

(4) Loss, S. (1989) W.A. J. Agric. 30:32-34.

(5) Linacre, E. and Hobbs, J. (1997). The Australian Climatic Environment. John Wiley & suns, Brisbane.

(6) McDonald, G.K., Sutton, B.G. and Ellison, F.W. (1983). Aust. J. Agric. Res. 34: 229-240.

(7) Single, W.V. (1975) in ‘Australian Field Crops. I. Wheat and other Temperate Cereals’, Ed. A. Lazenby and E.M. Matheson, p364., Angus and Robertson, Sydney.

(8) Single, W.V. (1985) J. Aust. Inst. Agric. Sci. 51:128-134.

(9) Stapper, M. Crispin, C.J. Davies, C. and Angus, J.F. (1998). 9th Aust Agron Conf, Wagga Wagga.

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