Hillslope runoff and erosion on duplex soils in grazing lands in semi-arid central Queensland. III. USLE erodibility (K factors) and cover - soil loss relationships

Soil Research ◽  
2011 ◽  
Vol 49 (2) ◽  
pp. 127 ◽  
Author(s):  
D. M. Silburn
Keyword(s):  
Soil Loss ◽  
Soil Classification ◽  
Bare Soil ◽  
Classification Systems ◽  
Tree Canopy ◽  
Undisturbed Soil ◽  
Tree Canopy Cover ◽  
Basin Scale ◽  
Factor C ◽  
Grazing Lands

Measured Universal Soil Loss Equation (USLE) soil erodibility (K) values are not available for soils in grazing lands in northern Australia. The K values extrapolated from croplands are used in national and river-basin scale assessments of hillslope erosion, using an assumption that the cover factor (C) equals 0.45 for undisturbed (uncultivated) bare soil. Thus, the K needed for input into the models is the measured K for undisturbed soil (KU) divided by 0.45. Runoff and erosion data were available for 7 years on 12 hillslope plots with cover of 10–80%, with and without grazing, with and without tree canopy cover, on a variety of soils according to various soil classification systems. Soils were grouped into those derived from sandstone (SS), mudstone (MS), and eroded mudstone (MSe). These data were used to determine USLE KU, K, and C factor–cover relationships. Methods used to fit the parameters affected the results; minimising the sum of squares of errors in soil losses gave better results than fitting an exponential equation. The USLE LS (length–slope) factor explained the increase in measured average annual soil loss with slope, for plots with low cover. Erodibility (K) was 0.042 for SS and MS soils, irrespective of Australian Soil Classification (Chromosol, Kandosol, Rudosol, Sodosol, Tenosol); K was 0.062 for exposed, decomposing mudstone (MSe Leptic Rudosol). The measured K factor for SS and MS soils was close to that used in catchment-wide soil loss estimation for the site (0.039). This indicates that the method used for estimating K from soil properties (derived from cultivated soils) gave a reasonable estimate of K for the main duplex soils at the study site, as long as the correction for undisturbed soil is used in deriving K from measured data and in applying the USLE model. A 20% increase in K (0.050) for SS and MS soils may be warranted for heavy grazing by cattle. The C factor–cover relationship was different from the standard revised USLE (RUSLE) relationship, requiring a greater exponent (‘bcov’) of 0.075, rather than the default for cropland of 0.035. Increasing cover is therefore more effective at the site than suggested by the USLE. Parameters of USLE were also derived for bedload, allowing suspended load to be calculated by subtracting bedload from total soil loss.

Experimental assessment of soil protection by vegetation for current crops and for up-coming EU glyphosate ban

2021 ◽  
Author(s):  
Jakub Stašek ◽  
Josef Krása ◽  
Adela Roudnická ◽  
Tomáš Dostál ◽  
Martin Mistr ◽  
...  
Keyword(s):  
Sediment Transport ◽  
Soil Loss ◽  
Management Practices ◽  
Field Experiments ◽  
Cropping Systems ◽  
Bare Soil ◽  
Soil Protection ◽  
Local Conditions ◽  
Reference Plot ◽  
Factor C

<p>There is still uncertainty in determining vegetation cover and management factor (C factor) for Universal Soil Loss Equation (USLE). Data we use today are often outdated, not specific and not representing local conditions. Current technologies in agriculture and recent crop varieties substantially vary from processes known during USLE (RUSLE) development.</p><p>Use of a rainfall simulator on a defined field crop is one way to obtain data for vegetation protection effect. Simulated rainfall is applied on experimental field with crop and bare soil as a reference. Plot size is 8x2 m and runoff and sediment transport is measured. Soil loss ratios are measured for three crop-development stages. Pre-sowing and post-harvest phases are measured as well. All measured data give information about soil protection for the whole season. In the span of 5 years, we have conducted over 340 field experiments on 15 typical, but also newly used crops and various management practices. The results are used in soil erosion and sediment transport analyses or models’ calibration. Metadata of experiments and results are added into a complex and public available database.</p><p>The contribution was prepared in the frame of projects No. QK1920224 (Possibilities of anti-erosion protection on farms to avoid the use of glyphosate), and H2020 SHUi (Soil Hydrology research platform underpinning innovation to manage water scarcity in European and Chinese cropping systems).</p>

Hillslope runoff and erosion on duplex soils in grazing lands in semi-arid central Queensland. I. Influences of cover, slope, and soil

Soil Research ◽  
2011 ◽  
Vol 49 (2) ◽  
pp. 105 ◽  
Author(s):  
D. M. Silburn ◽  
C. Carroll ◽  
C. A. A. Ciesiolka ◽  
R. C. deVoil ◽  
P. Burger
Keyword(s):  
Soil Erosion ◽  
Suspended Sediment ◽  
Surface Soil ◽  
Bare Soil ◽  
Suspended Load ◽  
Total Soil ◽  
Tree Canopy Cover ◽  
Grazing Lands ◽  
Semi Arid ◽  
Soil Losses

Many soils in semi-arid grazing lands develop low pasture cover or bare areas (scalds) under heavy grazing and have a low tolerance to soil erosion, due to low total water-holding capacity and concentration of nutrients in the soil surface. Runoff and erosion was measured for 7 years on 12 hillslope plots with cover (pasture plus litter) ranging from 10 to 80%, slopes from 4 to 8%, with and without grazing, with and without tree canopy cover, on a variety of soils. Soils were grouped into those derived from sandstone (SS), mudstone (MS), and eroded mudstone (MSe). One plot with low cover had a grass filter at the outlet. Runoff was strongly influenced by surface cover and was high with low cover (200–300 mm/year or 30–50% of rainfall). Runoff averaged 35 mm/year or 5.9% of rainfall with >50% cover. All soils fitted the same runoff–cover relationship. The grass filter had no effect on runoff and suspended load, but did reduce bedload. Grass pasture cover and tree litter cover were equally effective in controlling runoff and erosion. Total, bedload, and suspended load sediment concentrations increased linearly with slope in the range 4–8% for plots with low cover, and decreased exponentially with greater cover. Total and bedload sediment–cover relationships were similar for SS, MS, and MSe. However, plots on MSe had higher suspended sediment losses and thus slightly higher total soil losses. For all soils, erosion resulted in low sediment concentrations due to the hard-set surface soil, but total soil losses were high due to the large volumes of runoff generated. Concentration–cover relationships were different for bedload and suspended sediment. Consequently, suspended sediment was 20–40% of total soil loss for bare soil, and increased with cover to about 80% with cover >80%. The proportion of suspended sediment for bare soil was similar to the proportion of dispersed silt plus clay in the surface soil. About 90% of suspended sediment was fine-sized (<0.053 mm). Bedload was mainly coarse and fine sands, which were enriched compared with the surface soil. Grazing in semi-arid pastures should be managed to maintain >50% ground cover to avoid excessive runoff and soil erosion, and degradation of soil productivity, and to maintain good off-site water quality.

scholarly journals Analyzing Potential Tree-Planting Sites and Tree Coverage in Mexico City Using Satellite Imagery

Forests ◽  
2020 ◽  
Vol 11 (4) ◽  
pp. 423 ◽  
Author(s):  
Juan C. Bravo-Bello ◽  
Tomas Martinez-Trinidad ◽  
J. Rene Valdez-Lazalde ◽  
Martin E. Romero-Sanchez ◽  
Sergio Martinez-Trinidad
Keyword(s):  
Mexico City ◽  
Satellite Images ◽  
Canopy Cover ◽  
Impervious Surface ◽  
Bare Soil ◽  
Tree Canopy ◽  
Tree Planting ◽  
Classification Approach ◽  
Tree Canopy Cover ◽  
Tree Coverage

Locating potential tree-planting sites and analyzing tree canopy cover is important in the planning and management of urban forests. This paper reports the quantification of potential planting sites as well as tree canopy cover in the urban area of Mexico City, estimated by means of SPOT (Satellite Pour l’Observation de la Terre) 6 satellite images and a supervised pixel-based classification approach. Results showed an estimated area of 3100.7 ha of potentially useful sites, including places with bare soil and grass-covered areas such as median strips, roundabouts and parks. An average tree canopy cover of 10.6% and an average impervious surface of 79.2% for the 15 boroughs were also analyzed. The area of potential planting sites would represent a 5% gain for the current tree canopy cover if it were to be planted. With an overall accuracy of 92.4%, the use of both images from the SPOT 6 sensor and the classification approach proved to be appropriate for obtaining thematic covers in the urban environment of Mexico City.

Zoning, land use, and urban tree canopy cover: The importance of scale

2013 ◽  
Vol 12 (2) ◽  
pp. 191-199 ◽  
Author(s):  
Sarah K. Mincey ◽  
Mikaela Schmitt-Harsh ◽  
Richard Thurau
Keyword(s):  
Land Use ◽  
Canopy Cover ◽  
Tree Canopy ◽  
Urban Tree ◽  
Tree Canopy Cover ◽  
Urban Tree Canopy

scholarly journals Diversity of Medicinal Plants among Different Tree Canopies

2021 ◽  
Vol 13 (5) ◽  
pp. 2640
Author(s):  
Muhammad Zubair ◽  
Akash Jamil ◽  
Syed Bilal Hussain ◽  
Ahsan Ul Haq ◽  
Ahmad Hussain ◽  
...  
Keyword(s):  
Medicinal Plants ◽  
Coniferous Forest ◽  
Canopy Cover ◽  
Local Communities ◽  
Tree Canopy ◽  
Tree Cover ◽  
Open Spaces ◽  
Floral Diversity ◽  
Tree Canopy Cover ◽  
Closed Canopy

The moist temperate forests in Northern Pakistan are home to a variety of flora and fauna that are pivotal in sustaining the livelihoods of the local communities. In these forests, distribution and richness of vegetation, especially that of medicinal plants, is rarely reported. In this study, we carried out a vegetation survey in District Balakot, located in Northeastern Pakistan, to characterize the diversity of medicinal plants under different canopies of coniferous forest. The experimental site was divided into three major categories (viz., closed canopy, open spaces, and partial tree cover). A sampling plot of 100 m2 was established on each site to measure species diversity, dominance, and evenness. To observe richness and abundance, the rarefaction and rank abundance curves were plotted. Results revealed that a total of 45 species representing 34 families were available in the study site. Medicinal plants were the most abundant (45%) followed by edible plants (26%). Tree canopy cover affected the overall growth of medicinal plants on the basis of abundance and richness. The site with partial canopy exhibited the highest diversity, dominance, and abundance compared to open spaces and closed canopy. These findings are instrumental in identifying the wealth of the medicinal floral diversity in the northeastern temperate forest of Balakot and the opportunity to sustain the livelihoods of local communities with the help of public/private partnership.

scholarly journals Estimating Forest Canopy Cover by Multiscale Remote Sensing in Northeast Jiangxi, China

Land ◽  
2021 ◽  
Vol 10 (4) ◽  
pp. 433
Author(s):  
Xiaolan Huang ◽  
Weicheng Wu ◽  
Tingting Shen ◽  
Lifeng Xie ◽  
Yaozu Qin ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Large Scale ◽  
Forest Canopy ◽  
Canopy Cover ◽  
Google Earth ◽  
Tree Canopy ◽  
Landsat Data ◽  
High Resolution Data ◽  
Modis Ndvi ◽  
Tree Canopy Cover

This research was focused on estimation of tree canopy cover (CC) by multiscale remote sensing in south China. The key aim is to establish the relationship between CC and woody NDVI (NDVIW) or to build a CC-NDVIW model taking northeast Jiangxi as an example. Based on field CC measurements, this research used Google Earth as a complementary source to measure CC. In total, 63 sample plots of CC were created, among which 45 were applied for modeling and the remaining 18 were employed for verification. In order to ascertain the ratio R of NDVIW to the satellite observed NDVI, a 20-year time-series MODIS NDVI dataset was utilized for decomposition to obtain the NDVIW component, and then the ratio R was calculated with the equation R = (NDVIW/NDVI) *100%, respectively, for forest (CC >60%), medium woodland (CC = 25–60%) and sparse woodland (CC 1–25%). Landsat TM and OLI images that had been orthorectified by the provider USGS were atmospherically corrected using the COST model and used to derive NDVIL. R was multiplied for the NDVIL image to extract the woody NDVI (NDVIWL) from Landsat data for each of these plots. The 45 plots of CC data were linearly fitted to the NDVIWL, and a model with CC = 103.843 NDVIW + 6.157 (R2 = 0.881) was obtained. This equation was applied to predict CC at the 18 verification plots and a good agreement was found (R2 = 0.897). This validated CC-NDVIW model was further applied to the woody NDVI of forest, medium woodland and sparse woodland derived from Landsat data for regional CC estimation. An independent group of 24 measured plots was utilized for validation of the results, and an accuracy of 83.0% was obtained. Thence, the developed model has high predictivity and is suitable for large-scale estimation of CC using high-resolution data.

Straw mulch impact on soil properties and initial soil erosion processes in the maize field

2021 ◽  
Author(s):  
Ivan Dugan ◽  
Leon Josip Telak ◽  
Iva Hrelja ◽  
Ivica Kisić ◽  
Igor Bogunović
Keyword(s):  
Soil Erosion ◽  
Soil Water ◽  
Soil Loss ◽  
Bare Soil ◽  
Water Erosion ◽  
Straw Mulch ◽  
Erosion Processes ◽  
Maize Field ◽  
Sediment Loss ◽  
Initial Soil

&lt;p&gt;&lt;strong&gt;Straw mulch impact on soil properties and initial soil erosion processes in the maize field&lt;/strong&gt;&lt;/p&gt;&lt;p&gt;Ivan Dugan*, Leon Josip Telak, Iva Hrelja, Ivica Kisic, Igor Bogunovic&lt;/p&gt;&lt;p&gt;University of Zagreb, Faculty of Agriculture, Department of General Agronomy, Zagreb, Croatia&lt;/p&gt;&lt;p&gt;(*correspondence to Ivan Dugan: [email protected])&lt;/p&gt;&lt;p&gt;Soil erosion by water is the most important cause of land degradation. Previous studies reveal high soil loss in conventionally managed croplands, with recorded soil losses high as 30 t ha&lt;sup&gt;-1&lt;/sup&gt; under wide row cover crop like maize (Kisic et al., 2017; Bogunovic et al., 2018). Therefore, it is necessary to test environmentally-friendly soil conservation practices to mitigate soil erosion. This research aims to define the impacts of mulch and bare soil on soil water erosion in the maize (Zea mays&amp;#160;L.) field in Blagorodovac, Croatia (45&amp;#176;33&amp;#8217;N; 17&amp;#176;01&amp;#8217;E; 132 m a.s.l.). For this research, two treatments on conventionally tilled silty clay loam Stagnosols were established, one was straw mulch (2 t ha&lt;sup&gt;-1&lt;/sup&gt;), while other was bare soil. For purpose of research, ten rainfall simulations and ten sampling points were conducted per each treatment. Simulations were carried out with a rainfall simulator, simulating a rainfall at an intensity of 58 mm h&lt;sup&gt;-1&lt;/sup&gt;, for 30 min, over 0.785 m&lt;sup&gt;2&lt;/sup&gt; plots, to determine runoff and sediment loss. Soil core samples and undisturbed samples were taken in the close vicinity of each plot. The results showed that straw mulch mitigated water runoff (by 192%), sediment loss (by 288%), and sediment concentration (by 560%) in addition to bare treatment. The bare treatment showed a 55% lower infiltration rate. Ponding time was higher (p &lt; 0.05) on mulched plots (102 sec), compared to bare (35 sec), despite the fact that bulk density, water-stable aggregates, water holding capacity, and mean weight diameter did not show any difference (p &gt; 0.05) between treatments. The study results indicate that straw mulch mitigates soil water erosion, because it immediately reduces runoff, and enhances infiltration. On the other side, soil water erosion on bare soil under simulated rainstorms could be high as 5.07 t ha&lt;sup&gt;-1&lt;/sup&gt;, when extrapolated, reached as high as 5.07 t ha&lt;sup&gt;-1 &lt;/sup&gt;in this study. The conventional tillage, without residue cover, was proven as unsustainable agro-technical practice in the study area.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Key words: straw mulch, &lt;/strong&gt;rainfall simulation, soil water erosion&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Acknowledgment&lt;/strong&gt;&lt;/p&gt;&lt;p&gt;This work was supported by Croatian Science Foundation through the project &quot;Soil erosion and degradation in Croatia&quot; (UIP-2017-05-7834) (SEDCRO).&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Literature&lt;/strong&gt;&lt;/p&gt;&lt;p&gt;Bogunovic, I., Pereira, P., Kisic, I., Sajko, K., Sraka, M. (2018). Tillage management impacts on soil compaction, erosion and crop yield in Stagnosols (Croatia). Catena, 160, 376-384.&lt;/p&gt;&lt;p&gt;Kisic, I., Bogunovic, I., Birk&amp;#225;s, M., Jurisic, A., Spalevic, V. (2017). The role of tillage and crops on a soil loss of an arable Stagnic Luvisol. Archives of Agronomy and Soil Science, 63(3), 403-413.&lt;/p&gt;

COMPUTER ASSISTED MAPPING OF SOIL EROSION POTENTIAL

1985 ◽  
Vol 65 (3) ◽  
pp. 411-418 ◽  
Author(s):  
T. VOLD ◽  
M. W. SONDHEIM ◽  
N. K. NAGPAL
Keyword(s):  
Soil Erosion ◽  
Soil Loss ◽  
Surface Soil ◽  
Mineral Soil ◽  
Weighted Average ◽  
Bare Soil ◽  
Computer Assisted ◽  
Additional Information ◽  
Potential Map ◽  
Fraser Valley

Soil erosion potential maps and summary statistics can be produced from existing information with relative ease with the aid of computers. Soil maps are digitized and survey information is stored as attributes for each soil. Algorithms are then prepared which evaluate the appropriate data base attributes (e.g. texture, slope) for each interpretation. Forty surface soil erosion potential maps were produced for the Lower Fraser Valley which identify the most erosion-prone areas and indicate average potential soil losses to be expected under assumed conditions. The algorithm developed follows the universal soil loss equation. Differences across the landscape in the R, K, and S factors are taken into account whereas the L factor is considered as a constant equal to 1.0. Worst conditions of bare soil (no crop cover, i.e. C = 1.0) and no erosion control practices (i.e. P = 1.0) are assumed. The five surface soil erosion potential classes are determined by a weighted average annual soil loss value based both on the upper 20 cm of mineral soil and on the proportion of the various soils in the polygon. A unique polygon number shown on the erosion potential map provides a link to computer tables which give additional information for each individual soil within that polygon. Key words: Erosion, computer mapping, USLE

Computerized Cone Penetration Test for Soil Classification

2008 ◽  
Vol 2053 (1) ◽  
pp. 47-64 ◽  
Author(s):  
Murad Y. Abu-Farsakh ◽  
Zhongjie Zhang ◽  
Mehmet Tumay ◽  
Mark Morvant
Keyword(s):  
Classification System ◽  
Soil Classification ◽  
Cone Penetration Test ◽  
Classification Systems ◽  
Fuzzy Classification ◽  
Classification Methods ◽  
Penetration Test ◽  
Cone Penetration ◽  
Cone Tip Resistance ◽  
Tip Resistance

Computerized MS-Windows Visual Basic software of a cone penetration test (CPT) for soil classification was developed as part of an extensive effort to facilitate the implementation of CPT technology in many geotechnical engineering applications. Five CPT soil engineering classification systems were implemented as a handy, user-friendly, software tool for geotechnical engineers. In the probabilistic region estimation and fuzzy classification methods, a conformal transformation is first applied to determine the profile of soil classification index (U) with depth from cone tip resistance (qc) and friction ratio (Rf). A statistical correlation was established in the probabilistic region estimation method between the U index and the compositional soil type given by the Unified Soil Classification System. Conversely, the CPT fuzzy classification emphasizes the certainty of soil behavior. The Schmertmann and Douglas and Olsen methods provide soil classification charts based on cone tip resistance and friction ratio. However, Robertson et al. proposed a three-dimensional classification system that is presented in two charts: one chart uses corrected tip resistance (qt) and friction ratio (Rf); the other chart uses qt and pore pressure parameter (Bq) as input data. Five sites in Louisiana were selected for this study. For each site, CPT tests and the corresponding soil boring results were correlated. The soil classification results obtained using the five different CPT soil classification methods were compared.

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