Estimation of Spatial and Seasonal Variability of Soil Erosion in a Cold Arid River Basin in Hindu Kush Mountainous Region Using Remote Sensing

Ziauddin Safari, Sayed Tamim Rahimi, Kamal Ahmed, Ahmad Sharafati, Ghaith Falah Ziarh, Shamsuddin Shahid, Tarmizi Ismail, Nadhir Al-Ansari, Eun-Sung Chung and Xiaojun Wang
Additional contact information
Ziauddin Safari: School of Civil Engineering, Faculty of Engineering, Universiti Teknologi Malaysia, Johor Bahru 81310, Malaysia
Sayed Tamim Rahimi: School of Civil Engineering, Faculty of Engineering, Universiti Teknologi Malaysia, Johor Bahru 81310, Malaysia
Kamal Ahmed: Department of Water Resource Management, Lasbela University of Agriculture, Water and Marine Sciences, Uthal, Lasbela, Balochistan 90150, Pakistan
Ahmad Sharafati: Department of Civil Engineering, Science and Research Branch, Islamic Azad University, Tehran, Iran
Ghaith Falah Ziarh: School of Civil Engineering, Faculty of Engineering, Universiti Teknologi Malaysia, Johor Bahru 81310, Malaysia
Shamsuddin Shahid: School of Civil Engineering, Faculty of Engineering, Universiti Teknologi Malaysia, Johor Bahru 81310, Malaysia
Tarmizi Ismail: School of Civil Engineering, Faculty of Engineering, Universiti Teknologi Malaysia, Johor Bahru 81310, Malaysia
Nadhir Al-Ansari: Civil, Environmental and Natural Resources Engineering, Lulea University of Technology, 97187 Lulea, Sweden
Eun-Sung Chung: Department of Civil Engineering, Seoul National University of Science and Technology, Seoul, Korea
Xiaojun Wang: State Key Laboratory of Hydrology-Water Resources and Hydraulic Engineering, Nanjing Hydraulic Research Institute, Nanjing 210029, China

Sustainability, 2021, vol. 13, issue 3, 1-14

Abstract: An approach is proposed in the present study to estimate the soil erosion in data-scarce Kokcha subbasin in Afghanistan. The Revised Universal Soil Loss Equation (RUSLE) model is used to estimate soil erosion. The satellite-based data are used to obtain the RUSLE factors. The results show that the slight (71.34%) and moderate (25.46%) erosion are dominated in the basin. In contrast, the high erosion (0.01%) is insignificant in the study area. The highest amount of erosion is observed in Rangeland (52.2%) followed by rainfed agriculture (15.1%) and barren land (9.8%) while a little or no erosion is found in areas with fruit trees, forest and shrubs, and irrigated agriculture land. The highest soil erosion was observed in summer (June–August) due to snow melting from high mountains. The spatial distribution of soil erosion revealed higher risk in foothills and degraded lands. It is expected that the methodology presented in this study for estimation of spatial and seasonal variability soil erosion in a remote mountainous river basin can be replicated in other similar regions for management of soil, agriculture, and water resources.

Keywords: Fluvisol; RUSLE; data scarcity; remote sensing; Afghanistan (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2021
References: View references in EconPapers View complete reference list from CitEc
Citations:

Downloads: (external link)
https://www.mdpi.com/2071-1050/13/3/1549/pdf (application/pdf)
https://www.mdpi.com/2071-1050/13/3/1549/ (text/html)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:gam:jsusta:v:13:y:2021:i:3:p:1549-:d:491433

Access Statistics for this article

Sustainability is currently edited by Ms. Alexandra Wu

More articles in Sustainability from MDPI
Bibliographic data for series maintained by MDPI Indexing Manager ().