Uncertainty Assessment in Soil Erosion Modelling Using RUSLE, Multisource and Multiresolution DEMs

Pandey, Ashish; Gautam, Amar Kant; Chowdary, V. M.; Jha, C. S.; Cerdà, Artemi

doi:10.1007/s12524-021-01351-4

Cited by 16 publications

(5 citation statements)

References 74 publications

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“…GIS provides a platform to prepare and analyze the spatial layers of each of these factors to estimate the average annual soil loss rate (Dabral et al 2008). Subsequently, researchers across the globe have employed the Revised Universal Soil Loss Equation (RUSLE) to assess the soil loss status (Pandey et al 2021b).…”

Section: Methodology Development In Land Resources Managementmentioning

confidence: 99%

Overview of Geospatial Technologies for Land and Water Resources Management

Pandey

Singh

Chowdary

et al. 2021

Geospatial Technologies for Land and Water Resources Management

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Land and water resources management are essential for the future sustainability of the environment. The studies on land and water resources require basic geo-referenced data, such as land use-land cover (LULC), soil maps, and digital elevation models (DEMs) for capturing the spatio-temporal variations of thematic layers. These data can be easily obtained from remote sensing images and limited ground truth. Hydro-meteorological data, such as precipitation, air, land surface temperature, solar radiation, evapotranspiration, soil moisture, river and lakes water levels, river discharge, and terrestrial water storage, can also be derived from remote sensing as well as from point-based ground instruments. Then, studies can be carried out at various spatio-temporal scales.

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Section: Methodology Development In Land Resources Managementmentioning

confidence: 99%

Overview of Geospatial Technologies for Land and Water Resources Management

Pandey

Singh

Chowdary

et al. 2021

Geospatial Technologies for Land and Water Resources Management

Self Cite

View full text Add to dashboard Cite

show abstract

“…Moreover, the cropland area was overestimated from the CGLS-LC100 land cover dataset over Africa (Nabil et al, 2020;Xu et al, 2019), leading to underestimating the soil loss rate because of the lower P-factor assigned for cropland. The elevation data source and its resolution may also affect RUSLE-GEE estimates (e.g., Chidi et al, 2021;Mondal et al, 2017;Pandey et al, 2021;Zhang et al, 2008). Other errors may result from the parameters that determine the shape of the NDVI-C curve (Eq.…”

Section: Limitations and Uncertaintiesmentioning

confidence: 99%

Soil erosion assessment in the Blue Nile Basin driven by a novel RUSLE-GEE framework

Elnashar

Zeng

et al. 2021

Science of The Total Environment

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“…However, the sampling methods, sampling density, and result extrapolation methods have a significant impact on the regional soil erosion evaluation [20,21]. The accuracy of soil erosion evaluation results based on coarse resolution requires quantitative evaluation to explore whether they can provide decision-makers with good soil and water conservation planning services [22]. Further research needs to be conducted to evaluate whether the spatial distribution characteristics of the regional soil erosion assessment results are consistent between the grid method and sampling survey, and which of those results are more feasible.…”

Section: Introductionmentioning

confidence: 99%

Comparison of Sampling and Grid Methods for Regional Soil Erosion Assessment

Gu,

Cao,

et al. 2023

Land

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To control soil erosion, the intensity, area, and distribution of regional soil erosion must be determined to accurately plan and implement corresponding soil conservation measures. Therefore, regional soil erosion assessment has received extensive attention worldwide. At present, a sampling survey approach and full-coverage grid-based calculation are mainly applied in regional soil erosion assessment. The quantitative evaluation of the entire region depends on the quality of the data source. Furthermore, owing to the greatness of the evaluation object, the difficulty of data acquisition, the high cost, and poor usability, the present approach is bound to be at the expense of data accuracy, spatial resolution, time resolution, etc. The sampling survey approach can obtain high-precision data of soil erosion factors. Therefore, it can accurately quantify soil erosion in a field investigation unit. However, the sampling method, sampling density, and extrapolation methods have a significant impact on regional soil erosion assessments. This study considers the case of Baiquan County in the rolling hills of Northeast China as an example. Regional soil erosion evaluation using sampling survey and grid computing were compared. The impact of the data source accuracy on the soil erosion assessment was also quantitatively evaluated. The results of grid method showed a phenomenon of large rates of soil erosion and the ratio of the soil erosion area (the share of areas above the mild level), which were overestimated by 20% and 6%, respectively. A digital elevation model (DEM) with a resolution of 30 m can be used for soil erosion evaluation in plain areas, but that with the same resolution in hilly areas has insufficient calculation accuracy and provides large errors. The grid method can be adopted when land use and soil conservation measures are accurate. Otherwise, the sampling method is recommended. Interpolation of the ratio of the soil erosion area in the survey unit based on land use can better evaluate regional soil erosion.

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Uncertainty Assessment in Soil Erosion Modelling Using RUSLE, Multisource and Multiresolution DEMs

Cited by 16 publications

References 74 publications

Overview of Geospatial Technologies for Land and Water Resources Management

Overview of Geospatial Technologies for Land and Water Resources Management

Soil erosion assessment in the Blue Nile Basin driven by a novel RUSLE-GEE framework

Comparison of Sampling and Grid Methods for Regional Soil Erosion Assessment

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