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A GIS-RS Approach for RUSLE-Based Method of Mean Estimation of Mean Annual Soil Loss of the Tagoloan River Basin, Philippines

Authors :
B. W. A. L. Salino
K. J. T. Medrano
M. G. L. Mosquito
V. X. P. B. Dagaraga
J. Jr. R. Vallente
Source :
The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, Vol XLVIII-5-2024, Pp 97-103 (2024)
Publication Year :
2024
Publisher :
Copernicus Publications, 2024.

Abstract

Soil erosion is a serious environmental concern in Tagoloan River Basin (TRB), a major watershed in Northern Mindanao, Philippines. It leads to soil loss causing detrimental impacts such as decreased soil productivity, nutrient loss, siltation, and water quality degradation among others. These impacts are better understood by estimating the degree of soil loss in the watershed and visualized in a GIS-based and factor-based approach using the Revised Universal Soil Loss Equation (RUSLE) model. Thematic maps of soil loss were generated with factors for rainfall erosivity (R), soil erodibility (K), topographic (LS) consisting of slope length (L) and slope steepness (S), cover management (C), and support practice (P). Factors were calculated separately and multiplied together to develop combined soil loss maps. Results show that TRB has an actual mean annual soil loss of 153.20 tons/hectare/year with 47.15% of the study area having very high to very severe susceptibility to soil loss. Further, a comparison of the potential (RKLS) and actual (RKLSCP) soil loss maps indicates the significance of cover management and support practices to the resulting mean annual soil loss. The present characterized soil loss level maps and its understanding driving forces of soil erosion for the planning of management practices and mitigating environmental hazards in the watershed.

Details

Language :
English
ISSN :
16821750 and 21949034
Volume :
XLVIII-5-2024
Database :
Directory of Open Access Journals
Journal :
The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences
Publication Type :
Academic Journal
Accession number :
edsdoj.fe05162cd7644408807b7373acc3b54
Document Type :
article
Full Text :
https://doi.org/10.5194/isprs-archives-XLVIII-5-2024-97-2024