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  5. Modeling of driving factors and headcut rates of ephemeral gullies in the loess plateau of China using high-resolution remote sensing images

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Article
en
2024

Modeling of driving factors and headcut rates of ephemeral gullies in the loess plateau of China using high-resolution remote sensing images

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0 Files

en
2024
Vol 17 (1)
Vol. 17
DOI: 10.1080/17538947.2024.2369632

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Kadambot Siddique
Kadambot Siddique

University of Western Australia

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Boyang Liu
Ziyu Chen
Ли Бин
+4 more

Abstract

Ephemeral gully headcut erosion contributes significantly to global land degradation and increased sediment yields, but the underlying driving factors and prediction models remain poorly understood. We conduct a comprehensive quantitative analysis of ephemeral gully headcut erosion in the Loess Plateau using an optimal parameters-based geographical detector (OPGD) model, leveraging high-resolution remote sensing images. Our findings reveal a varied ephemeral gully head advance rate spanning 0.04–5.54 m yr−1 between 2009 and 2021 (average 1.37 m yr−1), with over 58% of the erosion rates falling between 0.50 and 2.00 m yr−1. Catchment area emerges as the primary driving factor, with an explanatory power of 61%. Moreover, the interactions between catchment area and slope degree, rainfall erosivity, and fractional vegetation coverage (FVC) had explanatory powers exceeding 80%. Furthermore, we developed a robust prediction model for ephemeral gully head advance rates based on the results from the OPGD model, incorporating the FVC factor. The validation of our model yielded a high coefficient of determination (R2 = 0.92 m yr−1) and low root mean square error (RMSE = 0.31 m yr−1). Our study offers new insights into ephemeral gully headcut erosion control in the Loess Plateau and serves as a valuable reference for loess regions worldwide.

How to cite this publication

Boyang Liu, Ziyu Chen, Ли Бин, Shufang Wu, Hao Feng, Xiaodong Gao, Kadambot Siddique (2024). Modeling of driving factors and headcut rates of ephemeral gullies in the loess plateau of China using high-resolution remote sensing images. , 17(1), DOI: https://doi.org/10.1080/17538947.2024.2369632.

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Publication Details

Type

Article

Year

2024

Authors

7

Datasets

0

Total Files

0

Language

en

DOI

https://doi.org/10.1080/17538947.2024.2369632

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