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Appl. Sci. 2015, 5(3), 157-173;

Prediction of Experimental Rainfall-Eroded Soil Area Based on S-Shaped Growth Curve Model Framework

1,2,* , 2,†
State Key Laboratory of Coal Mine Disaster Dynamics and Control, Chongqing University, Chongqing 400044, China
State Key Laboratory of Geo-hazard Prevention and Geo-environment Protection, Chengdu University of Technology, Chengdu 610059, Sichuan, China
State Key Laboratory of Oil and Gas Reservoir Geology and Exploitation, Southwest Petroleum University, Chengdu, 610500, Sichuan, China
School of Aeronautics & Astronautics, Shanghai Jiao Tong University, Shanghai 200240, China
School of Science, Southwest Petroleum University, Chengdu 610500, Sichuan, China
These authors contributed equally to this work.
Author to whom correspondence should be addressed.
Academic Editor: Takayoshi Kobayashi
Received: 10 May 2015 / Revised: 3 July 2015 / Accepted: 7 July 2015 / Published: 14 July 2015
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Rainfall-induced soil erosion of a mountain area plays a significant role in supplying sediment and shaping the landscape. The related area of soil erosion, as an index of the changed landscape, is easier to calculate visually using some popular imaging tools. By image analysis, our work shows that the changing of the soil erosion area admits the structure of an S-growth curve. Therefore, we propose to establish an S-curve model, based on incremental learning, to predict the soil erosion area. In the process of incremental learning, we dynamically update the accumulative rainfall and rainfall intensity to train the parameters of our S-curve model. In order to verify our prediction model, the index of area is utilized to express the output of eroded soil in a series of experiments. The results show that the proposed S-growth curve model can be used to estimate the growth of the soil erosion area (average relative error 3%–9.7%) according to variable soil material and rainfall intensity. The original S-growth curve model can calculate the erosion areas of just one soil material and one rainfall condition whose average relative error is 7.5%–12.2%; compared to the simple time series analysis-moving average method (average relative error 5.7%–12.1%), our proposed S-growth curve model can reveal the physical mechanism and evolution of the research object. View Full-Text
Keywords: eroded soil area; S-shaped growth curve; time series analysis; incremental learning eroded soil area; S-shaped growth curve; time series analysis; incremental learning

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Nie, W.; Huang, R.-Q.; Zhang, Q.-G.; Xian, W.; Xu, F.-L.; Chen, L. Prediction of Experimental Rainfall-Eroded Soil Area Based on S-Shaped Growth Curve Model Framework. Appl. Sci. 2015, 5, 157-173.

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