Runoff and soil loss from bare fallow plots at Inverell, New-South-Wales

Soil Research ◽  
1990 ◽  
Vol 28 (4) ◽  
pp. 659 ◽  
Author(s):  
JL Armstrong
Keyword(s):  
Soil Loss ◽  
New South ◽  
Soil Erodibility ◽  
Energy Component ◽  
South Wales ◽  
K Factor ◽  
Bare Fallow ◽  
Runoff And Soil Loss ◽  
Soil Losses ◽  
Runoff Component

Three 41 m long bare fallow plots were established on a chocolate soil (Mollisol) at Inverell in late 1976 to determine the soil erodibility (K) factor for use in the Universal Soil Loss Equation (USLE). The K-factor was estimated as 0.018 tonne hectare hour per hectare megajoule millimetre, indicating a soil of low to moderate erodibility. This value was close to that predicted from the soil erodibility nomograph used in the USLE. The average annual soil loss over the eight year period was 51 t/ha, while the largest individual storm soil loss from the plots was 47 t/ha. The two largest soil losses in each year accounted for 60-99% of the annual soil loss. Various erosivity indices were examined for their ability to predict runoff and soil loss from individual erosive storms. Indices which had separate variables for soil particle detachment (energy component) and particle transport (runoff component) were superior, although a large proportion of the variation in runoff and soil loss remained unaccounted for, and the possible reasons for this are examined. The highest correlation was obtained between soil loss and runoff amount.

scholarly journals Digital mapping of soil erodibility for water erosion in New South Wales, Australia

Soil Research ◽  
2018 ◽  
Vol 56 (2) ◽  
pp. 158 ◽  
Author(s):  
Xihua Yang ◽  
Jonathan Gray ◽  
Greg Chapman ◽  
Qinggaozi Zhu ◽  
Mitch Tulau ◽  
...  
Keyword(s):  
Soil Erosion ◽  
Soil Properties ◽  
Soil Loss ◽  
New South ◽  
New South Wales ◽  
Field Measurements ◽  
Soil Erodibility ◽  
South Wales ◽  
Australian Continent ◽  
K Factor

Soil erodibility represents the soil’s response to rainfall and run-off erosivity and is related to soil properties such as organic matter content, texture, structure, permeability and aggregate stability. Soil erodibility is an important factor in soil erosion modelling, such as the Revised Universal Soil Loss Equation (RUSLE), in which it is represented by the soil erodibility factor (K-factor). However, determination of soil erodibility at larger spatial scales is often problematic because of the lack of spatial data on soil properties and field measurements for model validation. Recently, a major national project has resulted in the release of digital soil maps (DSMs) for a wide range of key soil properties over the entire Australian continent at approximately 90-m spatial resolution. In the present study we used the DSMs and New South Wales (NSW) Soil and Land Information System to map and validate soil erodibility for soil depths up to 100 cm. We assessed eight empirical methods or existing maps on erodibility estimation and produced a harmonised high-resolution soil erodibility map for the entire state of NSW with improvements based on studies in NSW. The modelled erodibility values were compared with those from field measurements at soil plots for NSW soils and revealed good agreement. The erodibility map shows similar patterns as that of the parent material lithology classes, but no obvious trend with any single soil property. Most of the modelled erodibility values range from 0.02 to 0.07 t ha h ha–1 MJ–1 mm–1 with a mean (± s.d.) of 0.035 ± 0.007 t ha h ha–1 MJ–1 mm–1. The validated K-factor map was further used along with other RUSLE factors to assess soil loss across NSW for preventing and managing soil erosion.

Soil erodibility (Km) values for some Australian soils

Soil Research ◽  
1998 ◽  
Vol 36 (6) ◽  
pp. 1045 ◽  
Author(s):  
R. J. Loch ◽  
B. K. Slater ◽  
C. Devoil
Keyword(s):  
Soil Loss ◽  
Clay Soil ◽  
New South ◽  
Soil Surface ◽  
Field Studies ◽  
Soil Erodibility ◽  
Laboratory Measurements ◽  
Soil Factors ◽  
South Wales ◽  
Soil Loss Equation

This paper reports calculated soil erodibility (Km) values for the universal soil loss equation (USLE) for a range of surface soils, and for some subsoils. The calculation of erodibility values was based on laboratory measurements of water-stable sizes at the soil surface following wetting by rain and on the wet density of coarse sediment. Also included are erodibility data derived from field studies of erosion for 5 soils from New South Wales and Queensland. The erodibility values obtained indicate reasonable consistency in erodibility values for Vertosols and Ferrosols, but considerable variation in the erodibility of soils lower in clay. Soil factors best correlated with the calculated Km factors were identified, and the potential to use such information to estimate Km factors was evaluated.

Seasonal distribution of runoff and soil loss under four tillage treatments in the upper St. John River valley New Brunswick, Canada

2000 ◽  
Vol 80 (4) ◽  
pp. 649-660 ◽  
Author(s):  
T. L. Chow ◽  
H. W. Rees ◽  
J. Monteith
Keyword(s):  
New Brunswick ◽  
Soil Loss ◽  
Potato Production ◽  
Seasonal Distribution ◽  
Soil Erodibility ◽  
Hordeum Vulgare L ◽  
Cropping Season ◽  
The Difference ◽  
Runoff And Soil Loss ◽  
Soil Losses

The effect of four different tillage treatments on surface runoff and soil loss, their seasonal distribution and temporal variation in soil erodibility were examined using runoff-erosion plots (10 m wide × 30 m long), on a Holmesville gravelly loam soil, a major soil type used for potato production in New Brunswick. Fall moldboard plowing, fall chisel plowing, spring moldboard plowing and subsoiling followed by fall moldboard plowing were evaluated under barley and fallow conditions on 8 and 11% slopes between 1989 and 1993. With exception of one year, annual precipitation was lower than normal. However, due to higher rainfall during the cropping season, the calculated erosivities were higher than those typically used for conservation planning in this region. Runoff data revealed that fall moldboard plowing generated the highest runoff. Either performing subsoiling prior to fall moldboard plowing or delaying moldboard plowing until the next spring, reduced runoff by approximately 10%. Chisel plowing, which loosens the soil without inverting it and leaves a large amount of residues on the surface, provided by far the greatest benefit in reducing runoff (20% reduction over fall moldboard plowing). Soil loss from fall moldboard plowing on the 11% slope under fallow was 2.8 and 2.6 times greater than from spring moldboard plowing and fall chisel plowing, respectively. The majority of the difference in soil loss occurred during the summer months. The benefit of spring moldboard and fall chisel plowing was considerably less on the 8% slope in which soil loss from the fall moldboard plowing was only 24 and 19% higher than spring moldboard and fall chisel plowing, respectively, indicating that the benefits are slope dependent and increase with increasing slope from 8 to 11%. When the plots were planted in Chapais barley (Hordeum vulgare L.), soil losses were negligible. Tillage treatments, and particularly cropping practices, play a major role in seasonal distribution of runoff and soil loss. Under fallow, approximately 79% of runoff and 8.1% of soil loss occurred during the non-cropping season whereas 96% of runoff and 68% of soil loss were found when the plots were planted in barley. The soil erodibility factor was two to three times higher during March and April, which coincide with the winter-spring thaw period, than during the rest of the year. This seasonal variation must be considered when using event-based models to predict soil losses. Key words: Moldboard plow, chisel plow, subsoiling, erodibility, erosivity, universal soil loss equation, crop residue

scholarly journals Identifying erosive periods by using RUSLE factors in mountain fields of the Central Spanish Pyrenees

2008 ◽  
Vol 12 (2) ◽  
pp. 523-535 ◽  
Author(s):  
M. López-Vicente ◽  
A. Navas ◽  
J. Machín
Keyword(s):  
Soil Moisture ◽  
Moisture Content ◽  
Soil Loss ◽  
Rainfall Intensity ◽  
Soil Moisture Content ◽  
Rainfall Erosivity ◽  
Soil Erodibility ◽  
Maximum Rainfall ◽  
Freeze Thaw ◽  
Soil Losses

Abstract. The Mediterranean environment is characterized by strong temporal variations in rainfall volume and intensity, soil moisture and vegetation cover along the year. These factors play a key role on soil erosion. The aim of this work is to identify different erosive periods in function of the temporal changes in rainfall and runoff characteristics (erosivity, maximum intensity and number of erosive events), soil properties (soil erodibility in relation to freeze-thaw processes and soil moisture content) and current tillage practices in a set of agricultural fields in a mountainous area of the Central Pyrenees in NE Spain. To this purpose the rainfall and runoff erosivity (R), the soil erodibility (K) and the cover-management (C) factors of the empirical RUSLE soil loss model were used. The R, K and C factors were calculated at monthly scale. The first erosive period extends from July to October and presents the highest values of erosivity (87.8 MJ mm ha−1 h−1), maximum rainfall intensity (22.3 mm h−1) and monthly soil erosion (0.25 Mg ha−1 month−1) with the minimum values of duration of erosive storms, freeze-thaw cycles, soil moisture content and soil erodibility (0.007 Mg h MJ−1 mm−1). This period includes the harvesting and the plowing tillage practices. The second erosive period has a duration of two months, from May to June, and presents the lowest total and monthly soil losses (0.10 Mg ha−1 month−1) that correspond to the maximum protection of the soil by the crop-cover ($C$ factor = 0.05) due to the maximum stage of the growing season and intermediate values of rainfall and runoff erosivity, maximum rainfall intensity and soil erodibility. The third erosive period extends from November to April and has the minimum values of rainfall erosivity (17.5 MJ mm ha−1 h−1) and maximum rainfall intensity (6.0 mm h−1) with the highest number of freeze-thaw cycles, soil moisture content and soil erodibility (0.021 Mg h MJ−1 mm−1) that explain the high value of monthly soil loss (0.24 Mg ha−1 month−1). The interactions between the rainfall erosivity, soil erodibility, and cover-management factors explain the similar predicted soil losses for the first and the third erosive periods in spite of the strong temporal differences in the values of the three RUSLE factors. The estimated value of annual soil loss with the RUSLE model (3.34 Mg ha−1 yr−1) was lower than the measured value with 137Cs (5.38 Mg ha−1 yr−1) due to the low values of precipitation recorded during the studied period. To optimize agricultural practices and to promote sustainable strategies for the preservation of fragile Mediterranean agrosystems it is necessary to delay plowing till October, especially in dryland agriculture regions. Thus, the protective role of the crop residues will extend until September when the greatest rainfall occurs together with the highest runoff erosivity and soil losses.

Effects of two crop rotations on seasonal runoff and soil loss in the Peace River region

1991 ◽  
Vol 71 (4) ◽  
pp. 533-543 ◽  
Author(s):  
L. J. P. Van Vliet ◽  
J. W. Hall
Keyword(s):  
Soil Loss ◽  
Crop Rotations ◽  
Snowmelt Runoff ◽  
Hordeum Vulgare L ◽  
Peace River ◽  
Residual Variation ◽  
River Region ◽  
Seasonal Runoff ◽  
Runoff And Soil Loss ◽  
Soil Losses

Four erosion plots were monitored from 1983 to 1989 (6 yr) to evaluate the effects of two crop rotations and their constituent crops on runoff and soil loss under natural precipitation near Fort St. John in the Peace River region of British Columbia. Rotation 1 consisted of two cycles of summerfallow — canola (Brassica rapa)-barley (Hordeum vulgare L.), and Rotation 2 included summerfallow — canola-barley-barley underseed to red fescue (Festuca rubra L.)-fescue-fescue. Rainfall and snowmelt runoff were collected and sampled throughout the year to determine seasonal runoff and soil losses. Over the 6 yr, the cumulative runoff and soil losses were consistently greater under Rotation 1 than under Rotation 2. There was a greater than fourfold difference in total soil loss, and 33–35% more total runoff. Rainfall-induced runoff and soil losses were significantly higher for Rotation 1 than for Rotation 2. Snowmelt runoff accounted for 90 and 96% of the total annual runoff and for 39 and 80% of the total annual soil loss from Rotations 1 and 2, respectively. Two large rainfall events during 1983 and 1987, each causing a soil loss in excess of 2000 kg ha−1, accounted for between 85 and 91% of the 6-yr total rainfall-induced erosion from Rotation 1. No differences in runoff or soil loss were detected among crops but the comparisons were insensitive because of high residual variation. Key words: Runoff, soil loss, erosion plots, crop rotations

Alternative production systems' effects on the K-factor of the Revised Universal Soil Loss Equation

1997 ◽  
Vol 12 (2) ◽  
pp. 55-58 ◽  
Author(s):  
Kim L. Fleming ◽  
William L. Powers ◽  
Alice J. Jones ◽  
Glenn A. Helmers
Keyword(s):  
Organic Matter ◽  
Soil Loss ◽  
Production Systems ◽  
Sandy Loam ◽  
Organic Matter Content ◽  
Universal Soil Loss Equation ◽  
Soil Erodibility ◽  
Silty Clay ◽  
K Factor ◽  
Soil Loss Equation

AbstractThe soil erodibility factor (K) of the Revised Universal Soil Loss Equation is currently considered a constant for all soils in the same type, regardless of production practice. To examine the effect of alternative production systems on the K-factor we compared pairs of alternatively and conventionally farmed fields on a Judson silt loam (Fine-silty, mixed, mesic Cumulic Hapludolls), a Yutan silty clay loam (Fine-silty, mixed, mesic Mollic Hapludalf), and a Wann fine sandy loam (Coarse-loamy, mixed, mesic Fluvaquentic Haplustolls). Soil cores were taken from the surface 10 cm and analyzed for organic matter, permeability, structure, and texture. These data were used to estimate K-factors from a nomograph. All soils in the study had a fine granular structure. Organic matter content and permeability were significantly higher for the alternatively managed field at every location, except for no difference in permeability on the Judson soil. However, the K-factor was significantly lower for the alternative system on the Judson soil. Of all the parameters, texture has the greatest influence in determining K-factors within the nomograph, with soils higher in silt being more erodible than soils higher in sand or clay. Thus, the influences of alternative production systems affected the Judson soil to a greater degree than other textures because of its higher inherent susceptibility to erosion. This study shows that alternative production systems affect the K-factor of some soil types and can reduce soil erodibility, and therefore should be considered when developing conservation plans.

Digital mapping of RUSLE slope length and steepness factor across New South Wales, Australia

Soil Research ◽  
2015 ◽  
Vol 53 (2) ◽  
pp. 216 ◽  
Author(s):  
Xihua Yang
Keyword(s):  
Land Use Planning ◽  
Soil Loss ◽  
Overland Flow ◽  
New South ◽  
New South Wales ◽  
Slope Angle ◽  
Universal Soil Loss Equation ◽  
Slope Length ◽  
South Wales ◽  
Soil Loss Equation

The Universal Soil Loss Equation (USLE) and its main derivate, the Revised Universal Soil Loss Equation (RUSLE), are widely used in estimating hillslope erosion. The effects of topography on hillslope erosion are estimated through the product of slope length (L) and slope steepness (S) subfactors, or LS factor, which often contains the highest detail and plays the most influential role in RUSLE. However, current LS maps in New South Wales (NSW) are either incomplete (e.g. point-based) or too coarse (e.g. 250 m), limiting RUSLE-based applications. The aim of this study was to develop automated procedures in a geographic information system (GIS) to estimate and map the LS factor across NSW. The method was based on RUSLE specifications and it incorporated a variable cutoff slope angle, which improves the detection of the beginning and end of each slope length. An overland-flow length algorithm for L subfactor calculation was applied through iterative slope-length cumulation and maximum downhill slope angle. Automated GIS scripts have been developed for LS factor calculation so that the only required input data are digital elevation models (DEMs). Hydrologically corrected DEMs were used for LS factor calculation on a catchment basis, then merged to form a seamless LS-factor digital map for NSW with a spatial resolution ~30 m (or 1 s). The modelled LS values were compared with the reference LS values, and the coefficient of efficiency reached 0.97. The high-resolution digital LS map produced is now being used along with other RUSLE factors in hillslope erosion modelling and land-use planning at local and regional scales across NSW.

Reducing denitrification loss with nitrification inhibitors following presowing applications of urea to a cottonfield

1994 ◽  
Vol 34 (1) ◽  
pp. 75 ◽  
Author(s):  
DL Chen ◽  
JR Freney ◽  
AR Mosier ◽  
PM Chalk
Keyword(s):  
Soil Loss ◽  
New South ◽  
New South Wales ◽  
Calcium Carbide ◽  
Nitrification Inhibitors ◽  
N Loss ◽  
Mineral N ◽  
N Transformations ◽  
South Wales ◽  
Denitrification Loss

The effects of the nitrification inhibitors nitrapyrin, acetylene (provided by wax-coated calcium carbide), and phenylacetylene on nitrogen (N) transformations and denitrification losses following presowing applications of urea were determined in a cottonfield in the Namoi Valley of New South Wales. The study used 0.05-m-diameter microplots to follow the changes in mineral N, and 0.15-m-diameter microplots fertilised with 15N-labelled urea (6 g N/ m2; 5 atom % 15N) to assess losses of applied N. When urea was applied in February (34 weeks before sowing), 84% of applied N was lost from the soil. Loss of applied N was reduced by addition of nitrapyrin and phenylacetylene, to 53 and 57%, respectively. In the absence of nitrification inhibitors, less N was lost (72% of that applied) from an application in May than from the February application. Addition of acetylene, phenylacetylene, and nitrapyrin reduced losses over the 24 weeks to sowing to 57, 52, and 48%, respectively. These experiments show that N loss from presowing applications of urea can be significantly reduced by the use of nitrification inhibitors, but that the losses of N are still substantial.

The effect of kinetic energy of excess rainfall on soil loss from non-vegetated plots

Soil Research ◽  
1983 ◽  
Vol 21 (4) ◽  
pp. 445 ◽  
Author(s):  
PIA Kinnell
Keyword(s):  
Kinetic Energy ◽  
Soil Loss ◽  
Rainfall Intensity ◽  
Acceptance Rate ◽  
Slope Gradient ◽  
The Difference ◽  
Bare Fallow ◽  
Runoff And Soil Loss ◽  
Sheet Erosion

Data obtained from three 0.01 ha runoff and soil-loss plots, established with a bare fallow treatment on a yellow podzolic (Albaqualf) soil and slope gradient of 4.2%, were analysed in terms of the kinetic energy of raindrops and the efficiency of the use of that energy in generating soil loss. The results indicate that the difference between rainfall intensity and the average infiltration (acceptance) rate of the soil during an event can be used to estimate variations in the efficiency of use of rainfall energy in generating sheet erosion.

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