Results 181 to 190 of about 9,641 (227)

Mapping potential soil erosion in East Africa using the Universal Soil Loss Equation and secondary data [PDF]

Breugel, P., van, Claessens, L., Herrero, M., Notenbaert, A., Steeg, J., van de   +4 more
core   +1 more source

The promotion of sustainable land use planning for the enhancement of ecosystem service capacity: Based on the FLUS-INVEST-RUSLE-CASA model. [PDF]

PLoS One
Li G, Wu Z, He Y, Chen C, Long Y.
europepmc   +1 more source

A new approach to estimate cover-management factor of RUSLE and validation of RUSLE model in the watershed of Kartalkaya Dam

Journal of Hydrology, 2015
RUSLE is one of the most widely used soil erosion model worldwide. However, some of the input parameters of RUSLE may require extensive field and laboratory studies, and therefore in most of the cases these parameters are estimated according to some alternative approaches. In this context, cover-management factor (C) has significant importance since it
Håkan Tanyas, Mehmet Lutfi Suzen
exaly   +3 more sources

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A Review of RUSLE Model

Journal of the Indian Society of Remote Sensing, 2020
In this paper, we attempted to review the soil erosion studies conducted throughout the globe using Revised Universal Soil Loss Equation (RUSLE). We searched the SCI, Scopus, Web of Science, Google Scholar database and various theses for this study. Though RUSLE is the most widely used model for estimation of soil erosion, the factors, namely rainfall ...
Kaushik Ghosal, Santasmita Das Bhattacharya   +1 more
exaly   +2 more sources

Global-scale application of the RUSLE model: a comprehensive review

Hydrological Sciences Journal, 2022
Sonam Sandeep Dash, S K Raúl
exaly   +2 more sources

Adaptation of RUSLE in the Eastern Part of the Mediterranean Region

Environmental Management, 2004
Empirically based models are used worldwide to estimate soil erosion. The Revised Universal Soil Loss Equation (RUSLE) is one such model that has been intensively tested and validated under conditions in the United States. RUSLE estimates average soil loss as a function of five main factors: rainfall erosivity (R), soil erodibility (K), crop management
A Abu, Hammad, H, Lundekvam, T, Børresen   +2 more
exaly   +3 more sources

RUSLE Model Description and Database Sensitivity

Journal of Environmental Quality, 1993
AbstractWater quality modeling generally requires estimates of the amount of eroded material entering water courses. This information is necessary because sediment often transports adsorbed chemicals. Numerous models have been developed to assist with assessment of this problem.
K. G. Renard, V. A. Ferreira
openaire   +1 more source

An overview of soil erosion modelling compatible with RUSLE approach

Rendiconti Lincei, 2012
Different approaches were used to model soil losses in the Sele River basin (southern Italy) characterized by data scarcity. The suitability of models interpolating different sources of data was evaluated with the aim to suggest similar methodologies in other regions where data availability is not sufficient to use the more complex and detailed models.
FAGNANO, MASSIMO, Diodato N., ALBERICO, INES, FIORENTINO, NUNZIO   +3 more
openaire   +3 more sources

An integrated method for calculating DEM-based RUSLE LS

Earth Science Informatics, 2018
The improvement of resolution of digital elevation models (DEMs) and the increasing application of the Revised Universal Soil Loss Equation (RUSLE) over large areas have created problems for the efficiency of calculating the LS factor for large data sets.
Wang, Meng, Baartman, Jantiene E.M., Zhang, Hongming, Yang, Qinke, Li, Shuqin, Yang, Jiangtao, Cai, Cheng, Wang, Meili, Ritsema, Coen J., Geissen, Violette   +9 more
openaire   +1 more source

Extension of a GIS procedure for calculating the RUSLE equation LS factor

Computers and Geosciences, 2013
The Universal Soil Loss Equation (USLE) and revised USLE (RUSLE) are often used to estimate soil erosion at regional landscape scales, however a major limitation is the difficulty in extracting the LS factor. The geographic information system-based (GIS-based) methods which have been developed for estimating the LS factor for USLE and RUSLE also have ...
Hongming Zhang, Qinke Yang, D Moore
exaly   +2 more sources