Quantitative analysis of soil erosion causative factors for susceptibility assessment in a complex watershed

Sholagberu, Abdulkadir Taofeeq; Mustafa, Muhammad Raza Ul; Yusof, Khamaruzaman Wan; Ahmad, Mustafa Hashim; Aremu, Saheed Adeniyi; Gohari, Adel; Abdurrasheed, Abdurrasheed S.

doi:10.1080/23311916.2019.1594506

Cited by 23 publications

(17 citation statements)

References 56 publications

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“…The rainfall erosivity factor (R) describes the relationship between the rainfall intensity and the soil responses to it (Prasannakumar et al, 2012) (Abdulkadir et al, 2019). In this catchment, the spatial variability of the intensity of the rainfall varies from 1353.65 mm to 2030.93mm.…”

Section: Rainfall Erosivity Factor (R)mentioning

confidence: 99%

“…The length of the slope and slope steepness of the area in the study area was generated using Digital Elevation Model (DEM) of 12.5 x 12.5m spatial resolution and LS-factor was generated in ArcGIS version 10.4. Flow accumulation and slope (%) are commonly used input parameters with a fixed cell size with regression equation (Abdulkadir et al, 2019) Where LS Slope length and steepness factor (dimensionless)…”

Section: Topographic Factor (Ls)mentioning

confidence: 99%

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RUSLE Model Based Annual Soil Loss Quantification for Soil Erosion Protection in Fincha Catchment, Abay River Basin, Ethiopia.

Tamiru¹,

Wagari²

2021

Preprint

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The quantity of soil loss as a result of soil erosion is dramatically increasing in catchment where land resources management is very weak. In this paper, a RUSLE model-based soil loss quanti-fication technique is presented to estimate the annual soil loss and identify the severity of the erosion in the catchment. This study uses Fincha catchment in Abay river basin as the study area to quantify the annual soil loss by implementing Revised Universal Soil Loss Equation (RUSLE) model developed in ArcGIS version 10.4. Digital Elevation Model (12.5 x 12.5), LANDSAT 8 of Operational Land Imager (OLI) and Thermal Infrared Sensor (TIRS), Annual Rainfall of 10 stations and soil maps of the catchment were used as input parameters to generate the significant factors. Rainfall erosivity factor (R), soil erodibility factor (K), cover and management factor (C), slope length and steepness factor (LS) and support practice factor (P) were used as soil loss quantification significant factors. A model builder for the RUSLE model was developed and raster map calcula-tion algebra was applied in ArcGIS version 10.4 to quantify the total annual soil loss. It was found that the quantified average annual soil loss ranges from 0.0 to 76.5 t ha-1 yr-1 was obtained in the catchment. The area coverage of soil erosion severity with 55%, 35% and 10% as low to moderate, high and very high respectively were identified. The information about the spatial variation of soil loss severity map generated in RUSLE model has a paramount role to alert land resources man-agers and all stakeholders in controlling the effects via implementation of both structural and non-structural mitigations. The results of the RUSLE model can also be further considered along with the catchment for practical soil loss quantification that can help for protection practices.

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Section: Rainfall Erosivity Factor (R)mentioning

confidence: 99%

Section: Topographic Factor (Ls)mentioning

confidence: 99%

RUSLE Model Based Annual Soil Loss Quantification for Soil Erosion Protection in Fincha Catchment, Abay River Basin, Ethiopia.

Tamiru¹,

Wagari²

2021

Preprint

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“…There are plenty of potential factors affecting the soil susceptibility to erosion, the contribution of which is site-specific and differ between regions, leaving no general method to evaluate erosion susceptibility (Abdulkadir et al, 2019). Regarding this matter and the region's characteristics, three factors were identified as important for estimating the soil susceptibility: slope, runoff curve number, and normalized difference vegetation index (NDVI) derived from a Landsat image in July 2015.…”

Section: Luim Input Preparation Susceptibilitymentioning

confidence: 99%

Measuring the Land Use Based Risk of Soil Erosion in a Mining-Dominated landscape in Northern Iran

Javadi¹,

layeghi²,

Jafari³

et al. 2020

J. Ecol. Eng.

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This study assessed the occurrence risk of soil erosion in a mining-dominated landscape in Qazvin Province, northern Iran using the Land Use Impact Model (LUIM) and MPSIAC model. The LUIM employs two concepts for estimating the soil erosion risk: Likelihood and Consequence. Likelihood was estimated spatially by integrating the maps of soil susceptibility to erosion, derived from a simultaneous analysis of slope, runoff curve number, and NDVI maps, and current land use management practices. In turn, Consequence was measured by combining soil sensitivity to erosion (according to soil depth), and the socioeconomic and environmental value of different land uses. Likelihood was found to be high over abandoned rainfed and mining lands and low in rangelands. All mining areas and parts of rainfed lands and rangelands, covering 35% of the region, were classified as high in terms of Consequence. According to the final soil risk map, over 60% of the region distributed across all mining areas and parts of rangelands as well as the rainfed and irrigated lands, was found to have a moderate risk of soil erosion. The results showed that the ratio of mining sizes to their relevant hydrological basins size had a significant correlation with specific erosion, and special sediment (p < 0.01). Overall, extensive surface mining activities were found to be a major soil erosion driver requiring effective post-mining rehabilitation plans.

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“…People-environment relations caused land-use changes triggering alleviating watersheds services for humans living downstream (Abdulkadir et al 2019). When watershed runs into deprivation, all elements to shape and reliant on the watershed, in short, were endured.…”

Section: Introductionmentioning

confidence: 99%

Assessment of Air Bengkulu (Indonesia) watershed based on agroecosystem landscape quality and sustainable land use plan

et al. 2020

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Abstract. Barchia MF, Sulistyo B, Hindarto KS, Suhartoyo H. 2020. Assessment of Air Bengkulu (Indonesia) watershed based on agroecosystem landscape quality and sustainable land use plan. Biodiversitas 21: 5422-5430. This study purposes to assess agro-ecosystem landscape based on land quality values and current land use and assess agro-ecosystem matrices with agricultural conservation practices in Air Bengkulu Watershed conducted from August to December 2019. Spatial analysis used some map and Landsat 8 OLI satellite imagery and ArcGIS version 10.1. The analysis depicted spatial distribution of soil and land quality, land uses, agricultural landscape matrices, and sustainable agro-ecosystems. The assessments revealed soil quality covered Air Bengkulu Watershed categorized moderate 33.1% to good 14.4% suitable for sustainable agroecosystems while in marginal quality 38.9% mostly lying on the upstream. This unique landscape formed a land quality prone to degradation because of intensive agriculture for oil palm covering 60% and coffee plantation about 17%. Actually, only about 61.1% of the Air Bengkulu Watershed is categorized as moderate to good quality matrix of sustainable agroecosystems. Improper agricultural cultivation with monoculture system without implemented conservation practices drove landscape filled with degradation landscapes. With sustainable agro-ecosystem scenarios implementing physical conservation terraces and restored with multi-purposes tree species such as candlenut, kapok tree, betel nut, durian, good quality of the landscape matrix of 82% Air Bengkulu Watershed.

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Quantitative analysis of soil erosion causative factors for susceptibility assessment in a complex watershed

Cited by 23 publications

References 56 publications

RUSLE Model Based Annual Soil Loss Quantification for Soil Erosion Protection in Fincha Catchment, Abay River Basin, Ethiopia.

RUSLE Model Based Annual Soil Loss Quantification for Soil Erosion Protection in Fincha Catchment, Abay River Basin, Ethiopia.

Measuring the Land Use Based Risk of Soil Erosion in a Mining-Dominated landscape in Northern Iran

Assessment of Air Bengkulu (Indonesia) watershed based on agroecosystem landscape quality and sustainable land use plan

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