Soil erosion risk assessment and spatial mapping using LANDSAT-7 ETM+, RUSLE, and GIS—a case study

Rawat, Kishan Singh; Mishra, A. K.; Bhattacharyya, Ranjan

doi:10.1007/s12517-015-2157-0

Cited by 46 publications

(19 citation statements)

References 56 publications

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“…Overall accuracy was >86.79% and Kappa statistics (0.80) [43]. LULC map of the watershed was classified into four classes namely; vegetation, fallow, barren and water bodies (Fig.…”

Section: Resultsmentioning

confidence: 99%

“…47.81%) comes under vegetation condition. This is a sign of a model setting where the area exposed for erosion and have probability for water erosion [43]. Several studies have been conducted to demonstrate the feasibility of interpreting the land use categories from EO data and further used as input data in a hydrologic modeling for estimating the runoff [1,38,58].…”

Section: Resultsmentioning

confidence: 99%

“…The slope of area shows a nearly flat to a gentle undulating topography with occasionally small hillocks. The elevation ranges from 90-180 m above mean sea level [43].…”

Section: Study Areamentioning

confidence: 99%

“…LULC types namely fallow land, barren land, vegetation and water bodies/ wetlands were identified and their co-ordinates were logged with a hand held Global Positioning System (GPS) device (Garmin (eTrexH), with ±15 m horizontal locational accuracy. These data were used in supervised classification method [43]. For 'salt and pepper' noise correction from classified image, a majority filter with a 3 × 3 window size was used.…”

Section: Data Sets Used and Methdologymentioning

confidence: 99%

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Estimation of Surface Runoff from Semi-arid Ungauged Agricultural Watershed Using SCS-CN Method and Earth Observation Data Sets

Rawat

Singh

2017

Water Conserv Sci Eng

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In the present study, Soil Conservation ServiceCurve Number (SCS-CN) method, Earth Observation (EO) data sets and Geographic Information System (GIS) have been used in order to estimate the surface runoff from Jhagrabaria an agricultural watershed of Allahabad district, Uttar Pradesh (India). LANDSAT-7ETM+, NOAA data and hydrologic soil groups have been used to prepare land use/land cover, rainfall and soil map. The traditional SCS-CN method for calculating the composite CN is very tedious and time demanding process of the hydrologic modeling. Therefore, GIS is now being used in combination with the SCS-CN method. The outcome of work showed 79.35 (CN II ) of normal condition, of dry condition 61.76 (CN I ) and of wet condition 89.84 (CN III ), respectively. This investigation outline that ungauged watershed exhibits an annual average of 14 years runoff volume as 3.58 × 10 6 m 3 from an average annual rainfall of 14 years 110.77 cm and the average annual surface runoff of 14 years was 23.83 cm and annual average runoff coefficient of 14 years was 0.22. The correlation analysis suggests that the strong correlation as R 2 (0.91) was observed between satellite drive rainfall and runoff from SCS-CN method. The developed rainfall-runoff model for the region will be useful to understand the watershed and its runoff flow characteristics.

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“…Overall accuracy was >86.79% and Kappa statistics (0.80) [43]. LULC map of the watershed was classified into four classes namely; vegetation, fallow, barren and water bodies (Fig.…”

Section: Resultsmentioning

confidence: 99%

Section: Resultsmentioning

confidence: 99%

“…The slope of area shows a nearly flat to a gentle undulating topography with occasionally small hillocks. The elevation ranges from 90-180 m above mean sea level [43].…”

Section: Study Areamentioning

confidence: 99%

Section: Data Sets Used and Methdologymentioning

confidence: 99%

See 2 more Smart Citations

Estimation of Surface Runoff from Semi-arid Ungauged Agricultural Watershed Using SCS-CN Method and Earth Observation Data Sets

Rawat

Singh

2017

Water Conserv Sci Eng

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“…Universal Soil Loss Equation (USLE) is considered as the best model and is being used worldwide for the estimation of surface erosion (e.g., Zhang et al 2008;Alexakis et al 2013;Perović et al 2013;Chatterjee et al 2014;Kourgialas et al 2016). Its revised version, RUSLE (Renard et al 1997), became mostly used to provide estimates of soil loss (Demirci and Karaburun 2012;Kumar et al 2014;Ganasri and Ramesh 2015;Napoli et al 2016;Rawat et al 2016). Other studies (Baumgardner et al 1986;Yesou et al 1993;Escadafal et al 1994;Hill et al 1994;Haboudane et al 2002) have shown the interest of spectral indices based on soil reflectance, such as form index (FI), coloration index (CI), brightness index (BI), and normalized difference vegetation index (NDVI), for characterizing soil surface state, especially in arid and semi-arid lands.…”

Section: Introductionmentioning

confidence: 99%

Soil erosion modeled with USLE, GIS, and remote sensing: a case study of Ikkour watershed in Middle Atlas (Morocco)

et al. 2017

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The Ikkour watershed located in the Middle Atlas Mountain (Morocco) has been a subject of serious soil erosion problems. This study aimed to assess the soil erosion susceptibility in this mountainous watershed using Universal Soil Loss Equation (USLE) and spectral indices integrated with Geographic Information System (GIS) environment. The USLE model required the integration of thematic factors' maps which are rainfall aggressiveness, length and steepness of the slope, vegetation cover, soil erodibility, and erosion control practices. These factors were calculated using remote sensing data and GIS. The USLE-based assessment showed that the estimated total annual potential soil loss was about 70.66 ton ha. This soil loss is favored by the steep slopes and degraded vegetation cover. The spectral index method, offering a qualitative evaluation of water erosion, showed different degrees of soil degradation in the study watershed according to FI, BI, CI, and NDVI. The results of this study displayed an agreement between the USLE model and spectral index approach, and indicated that the predicted soil erosion rate can be due to the most rugged land topography and an increase in agricultural areas. Indeed, these results can further assist the decision makers in implementation of suitable conservation program to reduce soil erosion.

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A Review of Remote Sensing andGIS‐Based Soil Loss Models With a Comparative Study From the Upper and Marginal Ganga River Basin

Kumar

Devrani

Deshmukh

2022

Advances in Remote Sensing Technology and the Three Poles

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Soil erosion risk assessment and spatial mapping using LANDSAT-7 ETM+, RUSLE, and GIS—a case study

Cited by 46 publications

References 56 publications

Estimation of Surface Runoff from Semi-arid Ungauged Agricultural Watershed Using SCS-CN Method and Earth Observation Data Sets

Estimation of Surface Runoff from Semi-arid Ungauged Agricultural Watershed Using SCS-CN Method and Earth Observation Data Sets

Soil erosion modeled with USLE, GIS, and remote sensing: a case study of Ikkour watershed in Middle Atlas (Morocco)

A Review of Remote Sensing andGIS‐Based Soil Loss Models With a Comparative Study From the Upper and Marginal Ganga River Basin

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