Estimation of soil losses by USLE model using GIS at Mashhad plain, Northeast of Iran

Bagherzadeh, Ali

doi:10.1007/s12517-012-0730-3

Cited by 55 publications

(36 citation statements)

References 19 publications

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“…In terms of practicality, Desmet & Govers (1996) have reported studies of this method applied at a watershed scale with the disadvantages of it being time-consuming. Studies in Iran and the Philippines have implemented the R/USLE methods within a GIS environment by calculating the LS-factor for each raster cell in a DEM, essentially treating each pixel as its own segment of uniform slope (Bagherzadeh, 2014;Schmitt, 2009). …”

Section: Slope Length (L) and Steepness (S) Factormentioning

confidence: 99%

“…The P-factor accounts for management practices that affect soil erosion through modifying the flow pattern, such as contouring, strip-cropping, or terracing (Renard et al, 1997). The more effective the conservation practice is at mitigating soil erosion, the lower the P-5 factor (Bagherzadeh, 2014). Like the C-factor, values for P-factors can be taken from literature and if there are no support practices observed, the P-factor is 1.0 (Adornado et al, 2009).…”

Section: Support Practice Factor (P)mentioning

confidence: 99%

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A review of the (Revised) Universal Soil Loss Equation (R/USLE): with a view to increasing its global applicability and improving soil loss estimates

Benavidez¹,

Jackson²,

Maxwell³

et al. 2018

Preprint

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Abstract. Soil erosion is a major problem around the world because of its effects on soil productivity, nutrient loss, siltation in water bodies, and degradation of water quality. By understanding the driving forces behind soil erosion, we can more easily identify erosion-prone areas within a landscape and use land management and other strategies to effectively manage the problem. Soil erosion models have been used to assist in this task. One of the most commonly used soil erosion models is 10 the Universal Soil Loss Equation (USLE) and its family of models: the Revised Universal Soil Loss Equation (RUSLE), the Revised Universal Soil Loss Equation version 2 (RUSLE2), and the Modified Universal Soil Loss Equation (MUSLE). This paper reviewed the different components of USLE and RUSLE etc., and analysed how different studies around the world have adapted the equations to local conditions. We compiled these studies and equations to serve as a reference for other researchers working with R/USLE and related approaches. We investigate some of the limitations of R/USLE, such as issues 15 in data-sparse regions, its inability to account for soil loss from gully erosion or mass wasting events, and that it does not predict sediment pathways from hillslopes to water bodies. These limitations point to several future directions for R/USLE studies: incorporating soil loss from other types of soil erosion, estimating soil loss at sub-annual temporal scales, and using consistent units for future literature. These recommendations help to improve the applicability of the R/USLE in a range of geoclimatic regions with varying data availability, and at finer spatial and temporal scales for scenario analysis. 20

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Section: Slope Length (L) and Steepness (S) Factormentioning

confidence: 99%

Section: Support Practice Factor (P)mentioning

confidence: 99%

A review of the (Revised) Universal Soil Loss Equation (R/USLE): with a view to increasing its global applicability and improving soil loss estimates

Benavidez¹,

Jackson²,

Maxwell³

et al. 2018

Preprint

View full text Add to dashboard Cite

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“…"P i " is monthly average of rainfall for month i (mm) and "P" represents the annual average of rainfall (mm) (Bagherzadeh 2012;Demirci & Karaburun 2011;Pradhan et al 2012).…”

Section: Preparation Of Usle Layersmentioning

confidence: 99%

“…Recently, due to population and industrial growth, massive development in hilly areas can be observed especially in Penang Island and Kuala Lumpur city . Therefore, many hilly areas are under heavy pressure from agricultural and urban development (Akgun et al 2011;2012;Pradhan 2010b;2012;Pradhan et al 2012).…”

Section: Introductionmentioning

confidence: 99%

Spatio-temporal assessment of soil erosion at Kuala Lumpur metropolitan city using remote sensing data and GIS

Khosrokhani

Pradhan

2013

Geomatics, Natural Hazards and Risk

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The main purpose of this paper is to assess and predict soil erosion and its dynamism observation at Kuala Lumpur metropolitan city using universal soil loss equation (USLE). To acquire USLE factors, multi-source datasets such as rainfall data of the past 20 years, DEM map, SPOT5 image and geological map of the study area were used to calculate spatial soil erosion of Kuala Lumpur metropolitan city. Results indicated that the highest spatial coverage (61.9%) occurred in very low and the lowest spatial coverage (3.8%) in severe soil loss class. Furthermore, a landslide inventory map of the same area was overlaid on the resultant soil erosion layer to demonstrate their correlation. A frequency ratio (FR) method was applied to determine the relationship between occurred landslides and each soil erosion class. The results indicated that the highest and the lowest FR equal to 0.8 and 2.1 and observed in very low and severe soil loss classes, respectively. Temporal assessment of soil erosion indicated that there is a decrement of soil loss content in severe class from 2000 to 2010. The result of the prognosis analysis showed that the spatial coverage of the study area in severe soil loss class equals to 48%. This result proved the significance of land use/land cover to curb soil erosion. The resultant maps may help the planners and managers to take proper decision for the conservation of soil as a noteworthy natural resource.

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“…One of the most important characteristics of precipitation in arid and semi-arid regions as the case of the study area is thunderstorm which causes huge runoff in a short time which resulted in massive amount of soil losses. In an investigation by Bagherzadeh (2014) for estimating soil losses in Mashhad-Chenaran Plain, the values of soil losses varied between 0 and 0.25 t ha -1 yr -1 alongside the kashaf-rud river in the middle of the plain and 2-10 t ha -1 yr -1 at the edges of the plain. Conventional down-slope cultivation on 1-2% slopes of silty loam soils accelerated the erosion process and adversely influenced soil structure (Kurothe et al, 2014).…”

Section: Introductionmentioning

confidence: 99%

The Effect of Crops Cultivation on Soil Erosion Indices Based on Impelero Model in Northeast Iran

Afshar¹

2018

Appl. Ecol. Env. Res.

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Abstract. In the present study an integrated neural network based model named ImpelERO was applied to estimate the impact of conventional cropping system on erosion indices, including soil vulnerability index, erosion risk class and soil loss rates by potato, alfalfa and maize plantations. Our results revealed that the soil vulnerability indices ranged from 0.21 to 0.52, 0.15 to 0.41 and 0.2 to 0.5 by potato, alfalfa and maize cultivations, respectively. The values of erosion risk classes by potato and maize cultivation ranged from V1 to V4 in which categorize the region as non-sensitive to very sensitive to erosion and by alfalfa cultivation varied between V1 to V3 which classify the study area as non-sensitive to sensitive to erosion The values of soil losses varied between 7.1 to 59 t ha -1 yr -1 with an average of 15.11 t ha -1 yr -1 by potato, 4.9 to 32.4 t ha -1 yr -1 with an average of 8.42 t ha -1 yr -1 by alfalfa and 6.8 to 52.7 t ha -1 yr -1 with an average of 13.65 t ha -1 yr -1 by maize cultivation. It was concluded that planting perennial alfalfa compared to row planted potato and maize has a great effect on controlling soil erosion and its indices at the study area.

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Estimation of soil losses by USLE model using GIS at Mashhad plain, Northeast of Iran

Cited by 55 publications

References 19 publications

A review of the (Revised) Universal Soil Loss Equation (R/USLE): with a view to increasing its global applicability and improving soil loss estimates

A review of the (Revised) Universal Soil Loss Equation (R/USLE): with a view to increasing its global applicability and improving soil loss estimates

Spatio-temporal assessment of soil erosion at Kuala Lumpur metropolitan city using remote sensing data and GIS

The Effect of Crops Cultivation on Soil Erosion Indices Based on Impelero Model in Northeast Iran

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