Soil loss estimation and prioritization of sub-watersheds of Kali River basin, Karnataka, India, using RUSLE and GIS

2016 ◽  
Vol 188 (4) ◽  
Author(s):  
Vipin Joseph Markose ◽  
K. S. Jayappa
Keyword(s):  
River Basin ◽  
Soil Loss ◽  
Loss Estimation ◽  
Kali River

scholarly journals Soil loss estimation using rusle model to prioritize erosion control in KELANI river basin in Sri Lanka

2019 ◽  
Vol 7 (2) ◽  
pp. 130-137 ◽  
Author(s):  
Cassim Mohamed Fayas ◽  
Nimal Shantha Abeysingha ◽  
Korotta Gamage Shyamala Nirmanee ◽  
Dinithi Samaratunga ◽  
Ananda Mallawatantri
Keyword(s):  
Sri Lanka ◽  
River Basin ◽  
Soil Loss ◽  
Erosion Control ◽  
Loss Estimation ◽  
Rusle Model ◽  
Kelani River

scholarly journals SOIL LOSS ESTIMATION OF S7-2 CATCHMENT OF THE SHIRINDAREH WATERSHED, IRAN USING THE RIVER BASIN MODEL

AGROFOR ◽  
2016 ◽  
Vol 1 (1) ◽  
Author(s):  
Velibor Spalević ◽  
Atefeh Behzadfar ◽  
Andre Silva Tavares ◽  
Milena Moteva ◽  
Vjekoslav Tanaskovik
Keyword(s):  
Decision Making ◽  
River Basin ◽  
Policy Development ◽  
Soil Loss ◽  
Rapid Assessment ◽  
Loss Estimation ◽  
Peak Discharge ◽  
Good Tool ◽  
Support Decision Making ◽  
Potential Peak

This study aims to estimate the soil loss of S7-2 Watershed of Shirindareh RiverBasin in Iran, using a simple but comprehensive “River Basin” model for erosionclassification and prediction of erosion potential. Peak discharge from the S7-2Watershed was calculated on 65 m3s-1 for the incidence of 100 years; the net soilloss on 4397 m³km-², specific 178 m³ km-² per year. The results of the research andearlier application of the “River Basin” model in the studied area of the ShirindarehRiver Basin in Iran shown that this approach is a good tool for rapid assessment oferosion risk to support decision-making and policy development.

GIS-based soil loss estimation using RUSLE model: a case of Kirindi Oya river basin, Sri Lanka

2018 ◽  
Vol 4 (1) ◽  
pp. 251-262 ◽  
Author(s):  
N. C. Wijesundara ◽  
N. S. Abeysingha ◽  
D. M. S. L. B. Dissanayake
Keyword(s):  
Sri Lanka ◽  
River Basin ◽  
Soil Loss ◽  
Loss Estimation ◽  
Rusle Model

scholarly journals Use of satellite and modeled soil moisture data for predicting event soil loss at plot scale

2015 ◽  
Vol 19 (9) ◽  
pp. 3845-3856 ◽  
Author(s):  
F. Todisco ◽  
L. Brocca ◽  
L. F. Termite ◽  
W. Wagner
Keyword(s):  
Soil Moisture ◽  
Soil Loss ◽  
Large Scale ◽  
Central Italy ◽  
Remote Sensing Data ◽  
Loss Estimation ◽  
Balance Model ◽  
Estimation Accuracy ◽  
Soil Losses

Abstract. The potential of coupling soil moisture and a Universal Soil Loss Equation-based (USLE-based) model for event soil loss estimation at plot scale is carefully investigated at the Masse area, in central Italy. The derived model, named Soil Moisture for Erosion (SM4E), is applied by considering the unavailability of in situ soil moisture measurements, by using the data predicted by a soil water balance model (SWBM) and derived from satellite sensors, i.e., the Advanced SCATterometer (ASCAT). The soil loss estimation accuracy is validated using in situ measurements in which event observations at plot scale are available for the period 2008–2013. The results showed that including soil moisture observations in the event rainfall–runoff erosivity factor of the USLE enhances the capability of the model to account for variations in event soil losses, the soil moisture being an effective alternative to the estimated runoff, in the prediction of the event soil loss at Masse. The agreement between observed and estimated soil losses (through SM4E) is fairly satisfactory with a determination coefficient (log-scale) equal to ~ 0.35 and a root mean square error (RMSE) of ~ 2.8 Mg ha−1. These results are particularly significant for the operational estimation of soil losses. Indeed, currently, soil moisture is a relatively simple measurement at the field scale and remote sensing data are also widely available on a global scale. Through satellite data, there is the potential of applying the SM4E model for large-scale monitoring and quantification of the soil erosion process.

scholarly journals Soil loss risk and habitat quality in streams of a meso-scale river basin

2007 ◽  
Vol 64 (4) ◽  
pp. 336-343 ◽  
Author(s):  
Alexandre Marco da Silva ◽  
Lilian Casatti ◽  
Clayton Alcarde Alvares ◽  
Aline Maria Leite ◽  
Luiz Antonio Martinelli ◽  
...  
Keyword(s):  
River Basin ◽  
Habitat Quality ◽  
Urban Areas ◽  
Riparian Vegetation ◽  
Soil Loss ◽  
Buffer Strips ◽  
Physical Damage ◽  
High Chemical ◽  
Sediment Delivery ◽  
Chemical Purity

Soil loss expectation and possible relationships among soil erosion, riparian vegetation and water quality were studied in the São José dos Dourados River basin, State of São Paulo, Brazil. Through Geographic Information System (GIS) resources and technology, Soil Loss Expectation (SLE) data obtained using the Universal Soil Loss Equation (USLE) model were analyzed. For the whole catchment area and for the 30 m buffer strips of the streams of 22 randomly selected catchments, the predominant land use and habitat quality were studied. Owing mainly to the high soil erodibility, the river basin is highly susceptible to erosive processes. Habitat quality analyses revealed that the superficial water from the catchments is not chemically impacted but suffers physical damage. A high chemical purity is observed since there are no urban areas along the catchments. The water is physically poor because of high rates of sediment delivery and the almost nonexistence of riparian vegetation.

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

2021 ◽  
Author(s):  
Habtamu Tamiru ◽  
Meseret Wagari
Keyword(s):  
Soil Erosion ◽  
River Basin ◽  
Soil Loss ◽  
Annual Rainfall ◽  
Rainfall Erosivity ◽  
Landsat 8 ◽  
Land Resources ◽  
Rusle Model ◽  
Factor C ◽  
Significant Factors

Abstract Background: The quantity of soil loss as a result of soil erosion is dramatically increasing in catchment where land resources management is very weak. The annual dramatic increment of the depletion of very important soil nutrients exposes the residents of this catchment to high expenses of money to use artificial fertilizers to increase the yield. This paper was conducted in Fincha Catchment where the soil is highly vulnerable to erosion, however, where such studies are not undertaken. This study uses Fincha catchment in Abay river basin as the study area to quantify the annual soil loss, where such studies are not undertaken, by implementing Revised Universal Soil Loss Equation (RUSLE) model developed in ArcGIS version 10.4. Results: 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 (2010-2019) 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. 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. Conclusion: Finally, it was concluded that having information about the spatial variability of soil loss severity map generated in the RUSLE model has a paramount role to alert land resources managers and all stakeholders in controlling the effects via the 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.

RUSLE Model based Assessment of Soil Erosion in Parbati River Basin, Central India using Google Earth Engine and GIS

2021 ◽  
Author(s):  
Rohit Kumar ◽  
Benidhar Deshmukh ◽  
Kiran Sathunuri
Keyword(s):  
Land Use ◽  
Soil Erosion ◽  
Spatial Pattern ◽  
River Basin ◽  
Soil Loss ◽  
Google Earth ◽  
Rusle Model ◽  
High Soil ◽  
Basin Scale ◽  
Google Earth Engine

<p>Land degradation is a global concern posing significant threat to sustainable development. One of its major aspects is soil erosion, which is recognised as one of the critical geomorphic processes controlling sediment budget and landscape evolution. Natural rate of soil erosion is exacerbated due to anthropogenic activities that may lead to soil infertility. Therefore, assessment of soil erosion at basin scale is needed to understand its spatial pattern so as to effectively plan for soil conservation. This study focuses on Parbati river basin, a major north flowing cratonic river and a tributary of river Chambal to identify erosion prone areas using RUSLE model. Soil erodibility (K), Rainfall erosivity (R), and Topographic (LS) factors were derived from National Bureau of Soil Survey and Land Use Planning, Nagpur (NBSS-LUP) soil maps, India Meteorological Department (IMD) datasets, and SRTM30m DEM, respectively in GIS environment. The crop management (C) and support practice (P) factors were calculated by assigning appropriate values to Land use /land cover (LULC) classes derived by random forest based supervised classification of Sentinel-2 level-1C satellite remote sensing data in Google Earth Engine platform. High and very high soil erosion were observed in NE and NW parts of the basin, respectively, which may be attributed to the presence of barren land, fallow areas and rugged topography. The result reveals that annual rate of soil loss for the Parbati river basin is ~319 tons/ha/yr (with the mean of 1.2 tons/ha/yr). Lowest rate of soil loss (i.e. ~36 tons/ha/yr with mean of 0.22 tons/ha/yr) has been observed in the open forest class whereas highest rate of soil loss (i.e. ~316 tons/ha/yr with mean of 32.08 tons/ha/yr) have been observed in gullied area class. The study indicates that gullied areas are contributing most to the high soil erosion rate in the basin. Further, the rate of soil loss in the gullied areas is much higher than the permissible value of 4.5–11 tons/ha/yr recognized for India. The study helps in understanding spatial pattern of soil loss in the study area and is therefore useful in identifying and prioritising erosion prone areas so as to plan for their conservation.</p>

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