The Experts below are selected from a list of 327 Experts worldwide ranked by ideXlab platform
Nicholas P Webb - One of the best experts on this subject based on the ideXlab platform.
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soil Erodibility dynamics and its representation for wind erosion and dust emission models
Aeolian Research, 2011Co-Authors: Nicholas P Webb, Craig L StrongAbstract:The susceptibility of a land surface to wind erosion is highly sensitive to changes in soil Erodibility. Nonetheless, the performance of wind erosion models continues to be affected by the accuracy of their Erodibility representations. There is thus an ongoing need for robust approaches for assessing and modelling soil Erodibility dynamics. This paper provides a critical review of research into the controls on soil Erodibility dynamics. The review focuses on progress in understanding temporal changes in soil aggregation and crusting as they influence the Erodibility of agricultural and rangeland soils, and identifies deficiencies in approaches for resolving the nature and causes of spatio-temporal patterns of Erodibility change. A conceptual model of soil Erodibility dynamics is developed to represent Erodibility changes within a single Erodibility continuum. The model is used to identify ongoing research questions that are central to developing new measures and a deeper understanding of soil Erodibility dynamics, and representations of soil Erodibility for wind erosion and dust emission models. Finally, available soil Erodibility metrics are evaluated in the context of their application in addressing these research needs, and new and alternate approaches for reducing the complexity of soil Erodibility assessments and models are identified.
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approaches to modelling land Erodibility by wind
Progress in Physical Geography, 2009Co-Authors: Nicholas P Webb, Hamish A McgowanAbstract:Land susceptibility to wind erosion is governed by complex multiscale interactions between soil Erodibility and non-erodible roughness elements populating the land surface. Numerous wind erosion modelling systems have been developed to quantify soil loss and dust emissions at the field, regional and global scales. All of these models require some component that defines the susceptibility of the land surface to erosion, ie, land Erodibility. The approaches taken to characterizing land Erodibility have advanced through time, following developments in empirical and process-based research into erosion mechanics, and the growing availability of moderate to high-resolution spatial data that can be used as model inputs. Most importantly, the performance of individual models is highly dependent on the means by which soil Erodibility and surface roughness effects are represented in their land Erodibility characterizations. This paper presents a systematic review of a selection of wind erosion models developed over the last 50 years. The review evaluates how land Erodibility has been modelled at different spatial and temporal scales, and in doing this the paper identifies concepts behind parameterizations of land Erodibility, trends in model development, and recent progress in the representation of soil, vegetation and land management effects on the susceptibility of landscapes to wind erosion. The paper provides a synthesis of the capabilities of the models in assessing dynamic patterns of land Erodibility change, and concludes by identifying key areas that require research attention to enhance our capacity to achieve this task.
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Visual assessment of the Australian land Erodibility model
Journal of Arid Environments, 2009Co-Authors: Nicholas P Webb, Stuart R. Phinn, Hamish A McgowanAbstract:Abstract There is a growing requirement for techniques to assess land susceptibility to wind erosion, i.e. land Erodibility, over large geographic areas (>10 4 km 2 ). This requirement stems from a lack of wind erosion research between the field (10 1 km 2 ) and regional scales, and a need to evaluate the performance of spatially explicit wind erosion models across these scales. This paper addresses this issue by presenting a methodology for monitoring land Erodibility at the landscape scale (10 3 km 2 ). First, we define criteria suitable for evaluating land Erodibility based on empirical relationships between soil texture, vegetation cover, geomorphology, and wind erosion. The criteria were used to visually assess land Erodibility over long distances (10 3 km) using vehicle-based transects run through the rangelands of western Queensland, Australia. Application of the data for testing the performance of a spatially explicit land Erodibility model (AUSLEM) is then demonstrated by comparing the visual assessments of land Erodibility with the model output. The model performed best in the west of the study area in the open rangelands. In regions with higher woody shrub and tree cover the model performance decreases. This highlights the need for research to better parameterise controls on Erodibility in semi-arid landscapes consisting of forested and rangeland mosaics.
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auslem australian land Erodibility model a tool for identifying wind erosion hazard in australia
Geomorphology, 2006Co-Authors: Nicholas P Webb, Hamish A Mcgowan, Stuart R. Phinn, Grant Harvey MctainshAbstract:We present AUSLEM (AUStralian Land Erodibility Model), a land Erodibility modelling system that utilizes a rule-set of surficial and climatic thresholds applied through a Geographic Information System (GIs) modelling framework to predict landscape susceptibility to wind erosion. AUSLEM is distinctive in that it quantitatively assesses landscape susceptibility to wind erosion at a 5 x 5 km. spatial resolution on a monthly time-step across Australia. The system was implemented for representative wet (1984), dry (1994), and average rainfall (1997) years with corresponding low, high and moderate dust storm day frequencies. Results demonstrate that AUSLEM can identify landscape Erodibility, and provide an interpretation of the physical nature and distribution of erodible landscapes in Australia. Further, results offer an assessment of the dynamic tendencies of Erodibility in space and time in response to the El Nino Southern Oscillation (ENSO) and seasonal synoptic scale climate variability. A comparative analysis of AUSLEM output with independent national and international wind erosion, atmospheric aerosol and dust event records indicates a high level of model competency. (c) 2006 Elsevier B.V. All rights reserved.
Hamish A Mcgowan - One of the best experts on this subject based on the ideXlab platform.
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approaches to modelling land Erodibility by wind
Progress in Physical Geography, 2009Co-Authors: Nicholas P Webb, Hamish A McgowanAbstract:Land susceptibility to wind erosion is governed by complex multiscale interactions between soil Erodibility and non-erodible roughness elements populating the land surface. Numerous wind erosion modelling systems have been developed to quantify soil loss and dust emissions at the field, regional and global scales. All of these models require some component that defines the susceptibility of the land surface to erosion, ie, land Erodibility. The approaches taken to characterizing land Erodibility have advanced through time, following developments in empirical and process-based research into erosion mechanics, and the growing availability of moderate to high-resolution spatial data that can be used as model inputs. Most importantly, the performance of individual models is highly dependent on the means by which soil Erodibility and surface roughness effects are represented in their land Erodibility characterizations. This paper presents a systematic review of a selection of wind erosion models developed over the last 50 years. The review evaluates how land Erodibility has been modelled at different spatial and temporal scales, and in doing this the paper identifies concepts behind parameterizations of land Erodibility, trends in model development, and recent progress in the representation of soil, vegetation and land management effects on the susceptibility of landscapes to wind erosion. The paper provides a synthesis of the capabilities of the models in assessing dynamic patterns of land Erodibility change, and concludes by identifying key areas that require research attention to enhance our capacity to achieve this task.
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Visual assessment of the Australian land Erodibility model
Journal of Arid Environments, 2009Co-Authors: Nicholas P Webb, Stuart R. Phinn, Hamish A McgowanAbstract:Abstract There is a growing requirement for techniques to assess land susceptibility to wind erosion, i.e. land Erodibility, over large geographic areas (>10 4 km 2 ). This requirement stems from a lack of wind erosion research between the field (10 1 km 2 ) and regional scales, and a need to evaluate the performance of spatially explicit wind erosion models across these scales. This paper addresses this issue by presenting a methodology for monitoring land Erodibility at the landscape scale (10 3 km 2 ). First, we define criteria suitable for evaluating land Erodibility based on empirical relationships between soil texture, vegetation cover, geomorphology, and wind erosion. The criteria were used to visually assess land Erodibility over long distances (10 3 km) using vehicle-based transects run through the rangelands of western Queensland, Australia. Application of the data for testing the performance of a spatially explicit land Erodibility model (AUSLEM) is then demonstrated by comparing the visual assessments of land Erodibility with the model output. The model performed best in the west of the study area in the open rangelands. In regions with higher woody shrub and tree cover the model performance decreases. This highlights the need for research to better parameterise controls on Erodibility in semi-arid landscapes consisting of forested and rangeland mosaics.
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auslem australian land Erodibility model a tool for identifying wind erosion hazard in australia
Geomorphology, 2006Co-Authors: Nicholas P Webb, Hamish A Mcgowan, Stuart R. Phinn, Grant Harvey MctainshAbstract:We present AUSLEM (AUStralian Land Erodibility Model), a land Erodibility modelling system that utilizes a rule-set of surficial and climatic thresholds applied through a Geographic Information System (GIs) modelling framework to predict landscape susceptibility to wind erosion. AUSLEM is distinctive in that it quantitatively assesses landscape susceptibility to wind erosion at a 5 x 5 km. spatial resolution on a monthly time-step across Australia. The system was implemented for representative wet (1984), dry (1994), and average rainfall (1997) years with corresponding low, high and moderate dust storm day frequencies. Results demonstrate that AUSLEM can identify landscape Erodibility, and provide an interpretation of the physical nature and distribution of erodible landscapes in Australia. Further, results offer an assessment of the dynamic tendencies of Erodibility in space and time in response to the El Nino Southern Oscillation (ENSO) and seasonal synoptic scale climate variability. A comparative analysis of AUSLEM output with independent national and international wind erosion, atmospheric aerosol and dust event records indicates a high level of model competency. (c) 2006 Elsevier B.V. All rights reserved.
Artemi Cerda - One of the best experts on this subject based on the ideXlab platform.
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assessment of soil particle Erodibility and sediment trapping using check dams in small semi arid catchments
Catena, 2017Co-Authors: A R Vaezi, Mohammad Abbasi, Saskia Keesstra, Artemi CerdaAbstract:Check dams can be used as a source of information for studies on sediment characteristics and soil particle Erodibility. In this study, sediment yield and grain size distribution (GSD) were measured in twenty small catchments draining into a rock check dam in NW Iran for different runoffs during 2010–2011. Significant correlations were found between sediment yield and slope steepness, vegetation cover and soil Erodibility factor (K) of the catchments. The Erodibility of soil particles was determined using the comparison of GSD between sediment and original soil. Clay was the most erodible soil particle which showed 2.05 times more percentage in sediment than the original soil. The Erodibility of soil particles were strongly affected by the rainfall erosivity (EI30). Check dams showed more effectiveness in trapping coarse particles (sand and gravel). The effectiveness of check dams in trapping coarse particles enhanced with increase in the remaining capacity of check dams.
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developing an Erodibility triangle for soil textures in semi arid regions nw iran
Catena, 2016Co-Authors: A R Vaezi, Heidar Hasanzadeh, Artemi CerdaAbstract:Abstract There is a strong need to develop a simple method for rapid estimation of Erodibility using readily available data. In this study, soil Erodibility was measured using eleven soil textures at the plot scale (60 cm × 80 cm) on a slope of 9% in a semi-arid region. A total of 110 soil erosion experiments were conducted using ten simulated rainfalls (50 mm h − 1 for 30 min). A regression model was developed based on silt and clay content (R 2 = 0.82, p
Grant Harvey Mctainsh - One of the best experts on this subject based on the ideXlab platform.
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auslem australian land Erodibility model a tool for identifying wind erosion hazard in australia
Geomorphology, 2006Co-Authors: Nicholas P Webb, Hamish A Mcgowan, Stuart R. Phinn, Grant Harvey MctainshAbstract:We present AUSLEM (AUStralian Land Erodibility Model), a land Erodibility modelling system that utilizes a rule-set of surficial and climatic thresholds applied through a Geographic Information System (GIs) modelling framework to predict landscape susceptibility to wind erosion. AUSLEM is distinctive in that it quantitatively assesses landscape susceptibility to wind erosion at a 5 x 5 km. spatial resolution on a monthly time-step across Australia. The system was implemented for representative wet (1984), dry (1994), and average rainfall (1997) years with corresponding low, high and moderate dust storm day frequencies. Results demonstrate that AUSLEM can identify landscape Erodibility, and provide an interpretation of the physical nature and distribution of erodible landscapes in Australia. Further, results offer an assessment of the dynamic tendencies of Erodibility in space and time in response to the El Nino Southern Oscillation (ENSO) and seasonal synoptic scale climate variability. A comparative analysis of AUSLEM output with independent national and international wind erosion, atmospheric aerosol and dust event records indicates a high level of model competency. (c) 2006 Elsevier B.V. All rights reserved.
Guanghui Zhang - One of the best experts on this subject based on the ideXlab platform.
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temporal variations in soil Erodibility indicators of vegetation restored steep gully slopes on the loess plateau of china
Agriculture Ecosystems & Environment, 2019Co-Authors: Baojun Zhang, Guanghui Zhang, Hanyue YangAbstract:Abstract Near soil-surface characteristics change considerably with vegetation growth during one growing season, and thus likely induce the temporal variations in soil Erodibility indicators. This study was performed to investigate the temporal variations in soil Erodibility indicators under different vegetation-restored gully slope lands on the Loess Plateau of China. Soil Erodibility indicators included the K factor, mean weight diameter (MWD), mean number of drop impacts (MND), saturated conductivity (Ks), cohesion (Coh), penetration resistance (PR), and one comprehensive soil Erodibility index (CSEI). One slope cropland (as the control) and seven vegetation-restored gully slope lands were selected to measure soil Erodibility indicators for seven times from April 23 to October 10, 2018. Near soil-surface characteristics were also measured to explain the temporal variations in soil Erodibility indicators. The results showed that the temporal variations in soil Erodibility indicators of different vegetation lands were similar. The K factor fluctuated considerably, while the MWD, MND, Ks, Coh, and PR gradually increased over time. However, all Erodibility indicators of the control cropland fluctuated over time with no distinctive trend. The CSEI of all sites fluctuated significantly over time. Compared to the control cropland, the mean K factors of different vegetation lands decreased by 2%–24%, but the mean values of MWD, MND, Ks, Coh, and PR increased by 108%–217%, 152%–343%, 94%–306%, 73%–175%, and 30%–199%, respectively. Consequently, the mean CSEI of different vegetation lands was reduced by 41% to 86%. The temporal variations in soil Erodibility indicators were closely related to the seasonal changes in root mass density. Bothriochloa ischaemum (Linn.) Keng was considered the most effective restoration community to reduce soil Erodibility of steep gully slope lands. The results contribute to improving the eco-environment on the Chinese Loess Plateau.
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soil Erodibility affected by vegetation restoration on steep gully slopes on the loess plateau of china
Soil Research, 2018Co-Authors: Baojun Zhang, Guanghui Zhang, Hanyue Yang, Hao Wang, Ningning LiAbstract:Vegetation restoration influences near soil-surface characteristics and thus likely affects soil Erodibility. This study was performed to quantify the effects of vegetation restoration on soil Erodibility on steep gully slopes, and to identify the potential influencing factors on the Loess Plateau. Three shrub and four grass types distributed on different gully slopes were selected, and six Erodibility indicators and an integrated Erodibility index (IEI) were applied to indirectly evaluate the effects of vegetation restoration on soil Erodibility. The former included the soil Erodibility K factor, aggregate stability (the mean weight diameter, MWD, and the mean number of drop impacts, MND), saturated hydraulic conductivity (Ks), cohesion (Coh), and penetration resistance (PR), and the latter was calculated using these indicators and a weighted integration method. The results showed that vegetation restoration on steep gully slopes was effective in reducing soil Erodibility on the Loess Plateau, and grasses seemed more effective than shrubs. Compared with the control, the K of vegetation-restored gully slopes decreased by 4.1–24.0%, and MWD, MND, Ks, Coh, and PR increased by 64.0–284.3, 51.4–269.5, 100.5–417.4, 10.1–172.2, and 63.3–278.9% respectively. Consequently, the IEI of the vegetation-restored gully slopes declined by 33.1–81.9%, and the mean reduction percentage of the four grasses was 1.5 times that of the three shrubs. The variation in soil Erodibility was closely related to the changes in the soil organic matter content and root mass density with vegetation restoration. The results will help in understanding the soil conservation mechanisms of vegetation restoration on steep gully slopes.
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soil Erodibility influenced by natural restoration time of abandoned farmland on the loess plateau of china
Geoderma, 2018Co-Authors: Hao Wang, Guanghui Zhang, Baojun Zhang, Ningning Li, Hanyue YangAbstract:Abstract Natural restoration age of abandoned farmlands has significant effects on near soil surface characteristics and thus affects soil Erodibility. However, few studies have been conducted to investigate the potential effects of natural restoration age on soil Erodibility on the Loess Plateau where many slope farmlands have been abandoned for soil erosion control in the past decades. This study was performed to quantify the effects of natural restoration age on soil Erodibility reflected by soil cohesion ( Coh ), saturated conductivity ( K s ), the number of drop impact ( NDI ), the mean weight diameter of soil aggregates ( MWD ), soil penetration resistance ( PR ), and soil Erodibility K factor. One slope farmland (as the control) and six abandoned farmlands restored for 3 to 33 years were selected for soil indicators measurements. A weighted summation method was used to produce one comprehensive soil Erodibility index ( CSEI ) to demonstrate comprehensively the temporal variation in soil Erodibility with natural restoration age. The results showed that Coh , K s , NDI , and MWD increased generally when the restoration age PR and K decreased gradually with restoration age, and tended to stabilize after 19 years abandonment. CSEI decreased generally with natural restoration age and gradually leveled off after restored for 25 years. Compared to the control, soil Erodibility (reflected by CSEI ) of abandoned farmlands restored for 3, 6, 12, 19, 25, and 33 years decreased on average by 15.9%, 44.6%, 59.4%, 82.7%, 96.5%, and 100%, respectively. The temporal variation in soil Erodibility was controlled greatly by the changes in biological soil crust thickness, plant litter density, root mass density, bulk density, texture and organic matter content driven by natural restoration. The natural restoration is an effective measure for decreasing soil Erodibility on the Loess Plateau.
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temporal variability in rill Erodibility for two types of grasslands
Soil Research, 2014Co-Authors: Guanghui Zhang, Keming Tang, X C ZhangAbstract:The temporal variability in rill Erodibility (Kr) and its influencing factors are not fully quantified in grasslands. This study was conducted to detect temporal variation and quantify the potential factors causing changes in rill Erodibility by using natural, undisturbed soil samples collected from two grasslands and one bare soil near Beijing, China. Sampling was at ~20-day intervals from April to October 2011. Soil detachment capacity by concentrated flow was measured in a hydraulic flume with the fixed bed under six different flow shear stresses to determine rill Erodibility. Root mass density was measured to analyse potential effects on temporal variability in rill Erodibility. Mean rill Erodibility of bare soil was 13.2 and 19.6 times greater than under switchgrass (Panicum virgatum) and smooth bromegrass (Bromus inermis). The temporal variability in rill Erodibility under grasslands differed significantly from that of bare soil. Distinctive temporal variation patterns were found throughout the growing season. Rill Erodibility declined as root density increased, and the rill Erodibility of grassland could be well estimated from the measured Erodibility of bare soil and root density (R2 ≥ 0.92). The results of this study aid understanding of soil erosion mechanisms and development of process-based erosion models to simulate the seasonal variation in soil detachment by concentrated flow for grassland.