Wind Erosion in Western Queensland Australia
Modelling Land Susceptibility to Wind Erosion in Western ... - Ninti One Modelling Land Susceptibility to Wind Erosion in Western ... - Ninti One
Chapter 5 – Land Erodibility Model DevelopmentTable 5.1 Dust-event frequencies at stations used for model validation. Dust event classes listed foreach station include dust-event frequencies for all event types (All); events with hazes removed(NoHz); events with hazes and dust whirls removed (NoHzWr); and Dust Storm Index (DSI) valuesStation* Class 1980 1981 1982 1983 1984 1985 1986 1987 1988 1989 1990Birds All 9 2 33 51 22 35 30 47 64 74 42NoHz 7 1 32 49 21 32 25 44 64 69 33NoHzWr 5 1 32 46 21 29 24 42 62 66 33DSI 0.3 0.05 13 11.7 6.85 1.35 1.1 15.1 2 13.45 8.05Boul All 4 0 10 12 3 5 12 20 11 20 16NoHz 3 0 8 3 0 2 10 10 7 14 10NoHzWr 3 0 8 3 0 2 10 10 7 14 10DSI 5.05 0 1.3 1.1 0 0.1 7.2 8.1 5.3 5.25 2.15Char All 436 369 271 93 38 36 28 9 18 11 38NoHz 118 94 65 35 14 20 20 2 5 9 20NoHzWr 8 11 8 6 5 7 13 0 1 5 5DSI 4.75 8.4 3.95 4 2.55 0.9 5.5 0.1 1.2 0.35 0.85Thargo All 11 3 5 6 1 3 11 14 6 14 8NoHz 10 1 2 2 1 3 8 14 6 13 2NoHzWr 10 1 1 2 1 3 8 13 6 13 2DSI 11.3 1 0.05 1.05 0.05 5.05 3.15 3.2 1.2 1.4 0.1Uran All 9 3 8 4 0 17 11 17 25 70 63NoHz 9 3 6 4 0 16 11 14 24 69 63NoHzWr 9 3 5 3 0 16 10 12 23 67 34DSI 0.45 0.15 6.2 1.1 0 3.45 4.25 7.45 2 13.75 13Wind All 35 10 20 10 15 26 44 55 75 15 12NoHz 28 3 12 7 15 26 44 54 75 15 12NoHzWr 23 3 12 6 12 20 27 42 69 15 11DSI 1.3 0.15 0.55 0.3 0.65 2.2 4.85 8.45 14.35 12.4 0.4Long All 5 2 130 63 27 8 5 8 6 8 56NoHz 0 2 14 16 13 8 4 1 5 0 14NoHzWr 0 2 3 3 0 7 3 0 3 0 11DSI 0 0.05 1.45 0.6 0.5 0.2 1.1 0 1.15 0 0.45Quil All 6 5 7 0 2 3 3 5 5 3 7NoHz 6 5 5 0 2 2 3 4 5 2 5NoHzWr 6 5 5 0 2 2 3 4 5 2 10DSI 1.2 6.1 0.2 0 0.1 0.1 0.1 1.15 2.15 5.05 3.05* Birds (Birdsville); Boul (Boulia); Char (Charleville); Thargo (Thargomindah); Uran (Urandangie); Wind(Windorah); Long (Longreach); Quil (Quilpie).The range of land surface characteristics (soil, vegetation types), management and climatevariability between the stations means that they have distinct dust-event frequency timeseriestrajectories (Table 5.1). The data also show that the types of dust events comprising thefrequencies varied between stations. The western stations (Birdsville, Urandangie, Boulia,Windorah) show little difference in frequencies between event classes. On the other hand, theeastern stations (Longreach, Charleville) have larger differences between class frequencies.146
Chapter 5 – Land Erodibility Model DevelopmentRemoving dust hazes and whirls from the western stations records has little effect on thefrequencies, indicating that the majority of events recorded at these stations are dust storms(i.e. Synop Codes 09, 30-35) or locally blowing dust (Code 07). At the eastern stationsremoving hazes and whirls significantly reduces the remaining event frequencies, indicatingthat the majority of events recorded at these stations are non-local (i.e. hazes) or are notrepresentative of lateral wind erosion activity (i.e. dust whirls).Figure 5.5 presents examples of time-series trajectories of mean annual land erodibility forQuilpie, Thargomindah and Windorah. Figure 5.5a presents trajectories for the circular AOIsat scales from 25 to 150 km. Figure 5.5b presents trajectories extracted from the directionalhalf-circle AOIs with a radius of 100 km. The patterns in trajectory changes between scales inFigure 5.5a are typical of those found across all stations. Differences were found between themagnitude of output values between scales, but no consistent differences were found betweenthe trends in the trajectories. Data for the year 1980 at the 150 km scale for Quilpie andThargomindah (5.5a), for example, indicate that land further from these stations had lowerodibility during that year. Variations in mean annual output values for the directional halfcircleAOIs also exhibit significant differences in magnitude and not trajectory. The trends inmean annual land erodibility extracted from model output on one side of a station (i.e. to thewest) were found to be similar to those extracted from other areas around the stations (i.e. tothe north, east or south). This outcome is interesting as the BoM stations are surrounded bymultiple soil and vegetation types so the land erodibility trajectories could be expected tohave different trends.147
- Page 119 and 120: Chapter 3 - Modelling Land Erodibil
- Page 121: Chapter 3 - Modelling Land Erodibil
- Page 124 and 125: Chapter 4 -Modelling Soil Erodibili
- Page 126 and 127: Chapter 4 -Modelling Soil Erodibili
- Page 128 and 129: Chapter 4 -Modelling Soil Erodibili
- Page 130 and 131: Chapter 4 -Modelling Soil Erodibili
- Page 132 and 133: Chapter 4 -Modelling Soil Erodibili
- Page 134 and 135: Chapter 4 -Modelling Soil Erodibili
- Page 136 and 137: Chapter 4 -Modelling Soil Erodibili
- Page 138 and 139: Chapter 4 -Modelling Soil Erodibili
- Page 140 and 141: Chapter 4 -Modelling Soil Erodibili
- Page 142 and 143: Chapter 4 -Modelling Soil Erodibili
- Page 144 and 145: Chapter 4 -Modelling Soil Erodibili
- Page 146 and 147: Chapter 4 -Modelling Soil Erodibili
- Page 148 and 149: Chapter 4 -Modelling Soil Erodibili
- Page 150 and 151: Chapter 4 -Modelling Soil Erodibili
- Page 152 and 153: Chapter 4 -Modelling Soil Erodibili
- Page 154 and 155: Chapter 5 - Land Erodibility Model
- Page 156 and 157: Chapter 5 - Land Erodibility Model
- Page 158 and 159: Chapter 5 - Land Erodibility Model
- Page 160 and 161: Chapter 5 - Land Erodibility Model
- Page 162 and 163: Chapter 5 - Land Erodibility Model
- Page 164 and 165: Chapter 5 - Land Erodibility Model
- Page 166 and 167: Chapter 5 - Land Erodibility Model
- Page 168 and 169: Chapter 5 - Land Erodibility Model
- Page 172 and 173: Chapter 5 - Land Erodibility Model
- Page 174 and 175: Chapter 5 - Land Erodibility Model
- Page 176 and 177: Chapter 5 - Land Erodibility Model
- Page 178 and 179: Chapter 5 - Land Erodibility Model
- Page 180 and 181: Chapter 5 - Land Erodibility Model
- Page 182 and 183: Chapter 6 - Field Assessments and M
- Page 184 and 185: Chapter 6 - Field Assessments and M
- Page 186 and 187: Chapter 6 - Field Assessments and M
- Page 188 and 189: Chapter 6 - Field Assessments and M
- Page 190 and 191: Chapter 6 - Field Assessments and M
- Page 192 and 193: Chapter 7 - Land Erodibility Dynami
- Page 194 and 195: Chapter 7 - Land Erodibility Dynami
- Page 196 and 197: Chapter 7 - Land Erodibility Dynami
- Page 198 and 199: Chapter 7 - Land Erodibility Dynami
- Page 200 and 201: Chapter 7 - Land Erodibility Dynami
- Page 202 and 203: Chapter 7 - Land Erodibility Dynami
- Page 204 and 205: Chapter 7 - Land Erodibility Dynami
- Page 206 and 207: Chapter 7 - Land Erodibility Dynami
- Page 208 and 209: Chapter 7 - Land Erodibility Dynami
- Page 210 and 211: Chapter 7 - Land Erodibility Dynami
- Page 212 and 213: Chapter 7 - Land Erodibility Dynami
- Page 214 and 215: Chapter 8 - Conclusions• There is
- Page 216 and 217: Chapter 8 - ConclusionsThe third ai
- Page 218 and 219: Chapter 8 - Conclusionswas shown to
Chapter 5 – Land Erodibility Model DevelopmentRemov<strong>in</strong>g dust hazes and whirls from the western stations records has little effect on thefrequencies, <strong>in</strong>dicat<strong>in</strong>g that the majority of events recorded at these stations are dust storms(i.e. Synop Codes 09, 30-35) or locally blow<strong>in</strong>g dust (Code 07). At the eastern stationsremov<strong>in</strong>g hazes and whirls significantly reduces the rema<strong>in</strong><strong>in</strong>g event frequencies, <strong>in</strong>dicat<strong>in</strong>gthat the majority of events recorded at these stations are non-local (i.e. hazes) or are notrepresentative of lateral w<strong>in</strong>d erosion activity (i.e. dust whirls).Figure 5.5 presents examples of time-series trajectories of mean annual land erodibility forQuilpie, Thargom<strong>in</strong>dah and <strong>W<strong>in</strong>d</strong>orah. Figure 5.5a presents trajectories for the circular AOIsat scales from 25 to 150 km. Figure 5.5b presents trajectories extracted from the directionalhalf-circle AOIs with a radius of 100 km. The patterns <strong>in</strong> trajectory changes between scales <strong>in</strong>Figure 5.5a are typical of those found across all stations. Differences were found between themagnitude of output values between scales, but no consistent differences were found betweenthe trends <strong>in</strong> the trajectories. Data for the year 1980 at the 150 km scale for Quilpie andThargom<strong>in</strong>dah (5.5a), for example, <strong>in</strong>dicate that land further from these stations had lowerodibility dur<strong>in</strong>g that year. Variations <strong>in</strong> mean annual output values for the directional halfcircleAOIs also exhibit significant differences <strong>in</strong> magnitude and not trajectory. The trends <strong>in</strong>mean annual land erodibility extracted from model output on one side of a station (i.e. to thewest) were found to be similar to those extracted from other areas around the stations (i.e. tothe north, east or south). This outcome is <strong>in</strong>terest<strong>in</strong>g as the BoM stations are surrounded bymultiple soil and vegetation types so the land erodibility trajectories could be expected tohave different trends.147