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Article

A Study on Prediction Model of Gully Volume Based on Morphological Features in the JINSHA Dry-Hot Valley Region of Southwest China

by 1,2,†, 1,3,†, 1,2, 1,2,*, 1,2, 1,2, 1,2 and 1,2
1
School of Land and Resources, China West Normal University, Nanchong 637009, China
2
Sichuan Provincial Engineering Laboratory of Monitoring and Control for Soil Erosion on Dry Valleys, China West Normal University, Nanchong 637009, China
3
Sichuan Institute of Land and Space Ecological Restoration and Geohazards Prevention, Chengdu 610081, China
*
Author to whom correspondence should be addressed.
These authors contributed equally to this work and should be considered co-first authors.
Academic Editors: Wolfgang Kainz, Josef Strobl and Liyang Xiong
ISPRS Int. J. Geo-Inf. 2021, 10(5), 300; https://doi.org/10.3390/ijgi10050300
Received: 8 March 2021 / Revised: 27 April 2021 / Accepted: 2 May 2021 / Published: 5 May 2021
(This article belongs to the Special Issue Geomorphometry and Terrain Analysis)
Gully erosion is well-developed in the Jinsha dry-hot valley region, which has caused serious soil losses. Gully volume is regarded as an effective indicator that can reflect the development intensity of gully erosion, and the evolutionary processes of gullies can be predicted based on the dynamic variation in gully volume. Establishing an effective prediction model of gully volume is essential to determine gully volume accurately and conveniently. Therefore, in this work, an empirical prediction model of gully volume was constructed and verified based on detailed morphological features acquired by elaborate field investigations and measurements in 134 gullies. The results showed the mean value of gully length, width, depth, cross-section area, volume, and vertical gradient decreased with the weakness of the activity degree of the gully, although the decrease in processes of these parameters had some differences. Moreover, a series of empirical prediction models of gully volume was constructed, and gully length was demonstrated to be a better predictor than other morphological features. Lastly, the effectiveness test showed the model of V = aL^b was the most effective in predicting gully volume among the different models established in this study. Our results provide a useful approach to predict gully volume in dry-hot valley regions. View Full-Text
Keywords: soil erosion; gullies; prediction model; morphological features; sediment yield soil erosion; gullies; prediction model; morphological features; sediment yield
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MDPI and ACS Style

Yang, D.; Mu, K.; Yang, H.; Luo, M.; Lv, W.; Zhang, B.; Liu, H.; Wang, Z. A Study on Prediction Model of Gully Volume Based on Morphological Features in the JINSHA Dry-Hot Valley Region of Southwest China. ISPRS Int. J. Geo-Inf. 2021, 10, 300. https://doi.org/10.3390/ijgi10050300

AMA Style

Yang D, Mu K, Yang H, Luo M, Lv W, Zhang B, Liu H, Wang Z. A Study on Prediction Model of Gully Volume Based on Morphological Features in the JINSHA Dry-Hot Valley Region of Southwest China. ISPRS International Journal of Geo-Information. 2021; 10(5):300. https://doi.org/10.3390/ijgi10050300

Chicago/Turabian Style

Yang, Dan, Kai Mu, Hui Yang, Mingliang Luo, Wei Lv, Bin Zhang, Hui Liu, and Zhicheng Wang. 2021. "A Study on Prediction Model of Gully Volume Based on Morphological Features in the JINSHA Dry-Hot Valley Region of Southwest China" ISPRS International Journal of Geo-Information 10, no. 5: 300. https://doi.org/10.3390/ijgi10050300

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