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  5. Estimation of soil erosion rate in the Democratic People's Republic of Korea using the RUSLE model

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Article
English
2017

Estimation of soil erosion rate in the Democratic People's Republic of Korea using the RUSLE model

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English
2017
Forest Science and Technology
Vol 13 (3)
DOI: 10.1080/21580103.2017.1341435

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Eunjai Lee
Eunjai Lee

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Eunjai Lee
Sujung Ahn
Sangjun Im

Abstract

Forests are well known to control soil erosion and severe flooding. In the Democratic People's Republic of Korea (North Korea), deforestation was estimated at 20% between 1997 and 2014. This decline was mainly reflective of improper land use practices on steep slopes. Intensive deforestation and inappropriate land management can lead to severe soil erosion. The objective of this study was to describe the regional soil erosion severity in North Korea using the Revised Universal Soil Loss Equation (RUSLE) model coupled with a GIS technique. This model is widely being used to assess the potential mean annual soil erosion under different rainfall, soil characteristics, slope, and land use conditions. The results showed that the average annual rate of soil loss was estimated to be 15.8 tonnes ha−1 yr−1. Regionally, Nampo city is the most vulnerable region to soil erosion (55.1 tonnes ha−1 yr−1), followed by Hwanghaebuk-do (30.5 tonnes ha−1 yr−1), due to rapid land development. Denuded lands, which are estimated at around 6.5% of the total area, are predicted to have contributed 192.1 million tonnes yr−1 to the country's soil erosion. Participatory agroforestry and reforestation were found to be practical solutions to reduce soil erosion, particularly on degraded landscapes, and improve people's farm-based livelihoods.

How to cite this publication

Eunjai Lee, Sujung Ahn, Sangjun Im (2017). Estimation of soil erosion rate in the Democratic People's Republic of Korea using the RUSLE model. Forest Science and Technology, 13(3), pp. 100-108, DOI: 10.1080/21580103.2017.1341435.

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Publication Details

Type

Article

Year

2017

Authors

3

Datasets

0

Total Files

0

Language

English

Journal

Forest Science and Technology

DOI

10.1080/21580103.2017.1341435

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