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Himan Shahabi

Himan Shahabi

Academic rank: Professor
ORCID:
Education: PhD.
ScopusId: 23670602300
HIndex: 0/00
Faculty: Faculty of Natural Resources
Address: Faculty of Natural Resources, University of Kurdistan, Sanandaj, Iran
Phone: 087-33664600-8 داخلی 4312

Research

Title
Soil erosion and degradation assessment integrating multi-parametric methods of RUSLE model, RS, and GIS in the Shaqlawa agricultural area, Kurdistan Region, Iraq
Type
JournalPaper
Keywords
Soil erosion · RUSLE · Topography · Shaqlawa · GIS · Remote sensing
Year
2023
Journal Environmental Monitoring and Assessment
DOI
Researchers Badeea Abdi ، Kamal Kolo ، Himan Shahabi

Abstract

This study evaluated soil erosion rates in the Shaqlawa district using the Geographical Information System (GIS)-based Revised Universal Soil Loss Equation (RUSLE) model. The primary objective was to identify areas within the district that are prone to significant erosion and develop appropriate soil conservation schemes accordingly. A combination of primary and secondary data from diverse sources was utilized to achieve this objective. The GIS-based RUSLE model used variables like soil erodibility (K), soil coverage (C), topographic effect (LS), rainfall runoff (R), and erosion control practices (P) to estimate the amount of soil that had been washed away in the study area. The study provided valuable information that can be used to plan and administer soil protection in the Shaqlawa district. The average yearly soil loss in the study region is estimated to be 65.66 t ha−1 year−1. The district is experiencing significant soil erosion rates, which may have detrimental effects on agricultural productivity, water quality, and environmental health. The analysis revealed that Balisan, Hiran, Shaqlawa center, and part of the Salahaddin subdistrict are the most affected areas, with high values of LS and R factors contributing to significant soil erosion rates. These results underscore the importance of soil protection and management efforts in the Shaqlawa district. The combination of the RUSLE with GIS and remote sensing techniques has been recognized as an essential, cost-effective, and highly accurate approach for estimating soil erosion.