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Jain, Sanjay K.; Kumar, Sudhir; Varghese, Jose

doi:10.1023/a:1012246029263

Cited by 214 publications

(28 citation statements)

References 3 publications

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“…The C factor represents the impacts of cropping and related management practices on the erosion severity of a place [29,54], whereas the P factor is defined as the ratio of soil loss with particular support practice to the loss with row cultivation upslope and downslope [26]. The C and P values were assigned as per the land uses [26,55,56] (Table 3).…”

Section: Rusle Modelmentioning

confidence: 99%

Estimation of Sediment Yield and Maximum Outflow Using the IntErO Model in the Sarada River Basin of Nepal

Chalise

Kumar

Spalević

et al. 2019

Water

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Soil erosion is a severe environmental problem worldwide as it washes away the fertile topsoil and reduces agricultural production. Nepal, being a hilly country, has significant erosion disputes as well. It is important to cognise the soil erosion processes occurring in a river basin to manage the erosion severity and plan for better soil conservation programs. This paper seeks to calculate the sediment yield and maximum outflow from the Sarada river basin located in the western hills of Nepal using the computer-graphic Intensity of Erosion and Outflow (IntErO) model. Asymmetry coefficient of 0.63 was calculated, which suggests a possibility of large floods to come in the river basin in the future whereas the maximum outflow from the river basin was 1918 m³ s−1. An erosion coefficient value of 0.40 was obtained, which indicates surface erosion of medium strength prevails in the river basin. Similarly, the gross soil loss rate of 10.74 Mg ha−1 year−1 was obtained with the IntErO modeling which compares well with the soil loss from the erosion plot measurements. The IntErO model was used for the very first time to calculate soil erosion rates in the Nepalese hills and has a very good opportunity to be applied in similar river basins.

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Section: Rusle Modelmentioning

confidence: 99%

Estimation of Sediment Yield and Maximum Outflow Using the IntErO Model in the Sarada River Basin of Nepal

Chalise

Kumar

Spalević

et al. 2019

Water

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“…For a particular soil association, the soil erodibility factor is the rate of erosion per unit of the erosion index from a standard plot. In this study, K values are obtained from the published work conducted in and around of Nepal [50][51][52][53][54]. If there was two different researchers who had produced two different K values for the same soil type, we used the mean value of the two values (Figure 4).…”

Section: Soil Erodibility Factor (K)mentioning

confidence: 99%

Assessment of Land Cover Change and Its Impact on Changes in Soil Erosion Risk in Nepal

2018

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Land cover change is a critical driver for enhancing the soil erosion risk in Nepal. Loss of the topsoil has a direct and indirect effect on human life and livelihoods. The present study provides an assessment of the decadal land use and land cover (LULC) change and consequent changes in the distribution of soil erosion risk for the years, 1990, 2000, and 2010, for the entire country of Nepal. The study attempted to understand how different land cover types change over the three decades and how it has changed the distribution of soil erosion risks in Nepal that would help in the development of soil conservation priority. The land cover maps were produced using geographic object-based image analysis (GEOBIA) using Landsat images. Soil erosion patterns were assessed using the revised universal soil loss equation (RUSLE) with the land cover as the input. The study shows that the forest cover is the most dominant land cover in Nepal that comprises about 6,200,000 ha forest cover. The estimated annual erosion was 129.30 million tons in 1990 and 110.53 million tons in 2010. The assessment of soil erosion dynamics was presented at the national, provincial, and district level. District wise analysis revealed that Gulmi, Parbat, Syangja, and the Tanahu district require priority for soil conservation.

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“…where A is the computed spatial average soil loss over a period selected for R, (t ha -1 ); R, K, L, S, C and P are rainfall erosivity [(MJ mm) (ha h) -1 ], soil erodibility [(t ha h) (ha MJ mm) -1 ], slope length, slope steepness, land cover management, and conservation practices factors, respectively. All dimensionless factors were normalized with respect to the unit plot conditions as described in Jain et al (2001) and Dabral et al (2008), and has been validated by Ganasri et al (2016). To determine study factors, the RUSLE was integrated in GIS and Remote Sensing (RS) as successfully reported by many researchers (Millward and Mersey 1999;Prasannakumar et al 2011;Vijith et al 2012;Asadi et al 2017;Mohammadi et al 2018;Chatrsimab et al 2019) to improve the accuracy and expedite the estimation.…”

Section: Soil Erosion Estimationmentioning

confidence: 99%

Dynamic Analysis Of Soil Erosion-Based Watershed Health

Hazbavi

Sadeghi

Gholamalifard

2019

GES

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Accelerated soil erosion is one of the most important detrimental factors affecting the quality of the watershed health. Due to different environmental pressures and drivers, the effort is needed for ecological health and resilience assessment in regards to erosion changeability. However, this important subject has not been adequately studied yet. Towards this, in the present research, an innovative approach was developed for conceptualizing the watershed health dynamics in viewpoint of soil erosion. A risk-based study was conducted to quantitatively characterize the spatiotemporal variability of erosion-based health in an industrialized watershed i.e., the Shazand Watershed using the conceptual reliability, resilience and vulnerability (RelResVul) framework for four node years of 1986, 1998, 2008 and 2014. To this end, the soil erosion was estimated at monthly scale in 24 sub-watersheds by applying the Revised Universal Soil Loss Equation (RUSLE). The RelResVul indicators were then computed according to the threshold defined for the study watershed. A geometric mean was used to combine the three risk indicators and the erosion-based watershed health index was ultimately calculated for each study sub-watershed. Additionally, the change detection analysis was conducted over the years of 1986 to 2014. According to the results of erosion-based the RelResVul indices, very healthy, healthy, moderately healthy, unhealthy and very un-healthy conditions in the Shazand Watershed were respectively distributed over some 67, 25, zero, zero and eight percent for 1986; 50, 13, eight, zero and 29 % for 1998; 71, eight, 83, zero, zero and eight percent for 2008 and finally 71, zero, 17, zero and 12 % for 2014. The results of change detection revealed an oscillating trend of erosion-based watershed health index during the whole study period (1986 -2014). So that, during periods of 1986-1998, 1986-2008 and 1986-2014, the watershed health decreased at tune of 23, 13 and six percent, respectively. Whilst, the watershed health improved during study periods of 1998-2008 (13 %), 2008-2014 (eight percent) and 1998-2014 (22 %). The results also identified ‘hot spots’ of the most important index of land degradation and ‘bright spots’ of land improvement in the Shazand Watershed.The proposed approach would provide a sustainable framework supporting decision makers to comprehend health-related soil erosion targets according to the integrated watershed management plans.

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Untitled

Cited by 214 publications

References 3 publications

Estimation of Sediment Yield and Maximum Outflow Using the IntErO Model in the Sarada River Basin of Nepal

Estimation of Sediment Yield and Maximum Outflow Using the IntErO Model in the Sarada River Basin of Nepal

Assessment of Land Cover Change and Its Impact on Changes in Soil Erosion Risk in Nepal

Dynamic Analysis Of Soil Erosion-Based Watershed Health

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