Dangerous degree forecast of soil loss on highway slopes in mountainous areas of the Yunnan–Guizhou Plateau (China) using the Revised Universal Soil Loss Equation

Li, Yue; Qi, Shi; Liang, Bin; Ma, Junming; Cheng, Baihan; Ma, Cong; Qiu, Yidan; Chen, Qinyan

doi:10.5194/nhess-19-757-2019

Articles | Volume 19, issue 4

https://doi.org/10.5194/nhess-19-757-2019

© Author(s) 2019. This work is distributed under
the Creative Commons Attribution 4.0 License.

Special issue:

Landslide–transport network interactions

https://doi.org/10.5194/nhess-19-757-2019

© Author(s) 2019. This work is distributed under
the Creative Commons Attribution 4.0 License.

Articles | Volume 19, issue 4

Research article

|

12 Apr 2019

Research article |

| 12 Apr 2019

Dangerous degree forecast of soil loss on highway slopes in mountainous areas of the Yunnan–Guizhou Plateau (China) using the Revised Universal Soil Loss Equation

Yue Li, Shi Qi, Bin Liang, Junming Ma, Baihan Cheng, Cong Ma, Yidan Qiu, and Qinyan Chen

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Feb 2018	26	6	7	39
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Apr 2018	36	8	1	45
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Jun 2018	30	4	0	34
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Jun 2019	71	17	1	89
Jul 2019	12	24	1	37
Aug 2019	13	12	1	26
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Oct 2019	20	21	1	42
Nov 2019	16	13	0	29
Dec 2019	22	14	1	37
Jan 2020	18	15	4	37
Feb 2020	18	14	1	33
Mar 2020	9	7	2	18
Apr 2020	23	7	0	30
May 2020	27	4	1	32
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Mar 2021	17	9	0	26
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Oct 2021	29	39	1	69
Nov 2021	21	29	0	50
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Jan 2022	26	18	0	44
Feb 2022	16	10	1	27
Mar 2022	16	13	0	29
Apr 2022	23	7	2	32
May 2022	23	16	2	41
Jun 2022	12	7	2	21
Jul 2022	23	5	0	28
Aug 2022	22	14	0	36
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Oct 2022	40	4	1	45
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Feb 2023	27	12	1	40
Mar 2023	25	13	1	39
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May 2023	23	14	4	41
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Jan 2024	36	17	0	53
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Apr 2024	22	6	2	30
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Jul 2024	27	11	2	40
Aug 2024	27	6	2	35
Sep 2024	26	16	1	43
Oct 2024	18	6	1	25
Nov 2024	6	1	7
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Jan 2025	22	8	2	32
Feb 2025	25	5	4	34
Mar 2025	29	10	4	43
Apr 2025	21	25	1	47
May 2025	28	5	1	34
Jun 2025	52	22	1	75
Jul 2025	20	36	2	58
Aug 2025	18	12	0	30
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Oct 2025	29	30	3	62
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Cumulative views and downloads (calculated since 21 Nov 2017)

Month	HTML	PDF	XML	Total
Nov 2017	76	18	2	96
Dec 2017	87	12	1	100
Jan 2018	43	7	1	51
Feb 2018	26	6	7	39
Mar 2018	35	5	0	40
Apr 2018	36	8	1	45
May 2018	22	5	0	27
Jun 2018	30	4	0	34
Jul 2018	17	3	0	20
Aug 2018	15	4	0	19
Sep 2018	26	7	0	33
Oct 2018	19	8	0	27
Nov 2018	18	4	2	24
Dec 2018	22	9	0	31
Jan 2019	22	5	0	27
Feb 2019	9	6	0	15
Mar 2019	20	5	0	25
Apr 2019	183	55	4	242
May 2019	127	23	4	154
Jun 2019	71	17	1	89
Jul 2019	12	24	1	37
Aug 2019	13	12	1	26
Sep 2019	14	14	1	29
Oct 2019	20	21	1	42
Nov 2019	16	13	0	29
Dec 2019	22	14	1	37
Jan 2020	18	15	4	37
Feb 2020	18	14	1	33
Mar 2020	9	7	2	18
Apr 2020	23	7	0	30
May 2020	27	4	1	32
Jun 2020	26	13	0	39
Jul 2020	15	17	1	33
Aug 2020	23	25	1	49
Sep 2020	15	11	0	26
Oct 2020	17	6	0	23
Nov 2020	14	12	2	28
Dec 2020	13	6	0	19
Jan 2021	23	8	1	32
Feb 2021	12	9	0	21
Mar 2021	17	9	0	26
Apr 2021	21	4	0	25
May 2021	27	10	0	37
Jun 2021	25	9	0	34
Jul 2021	28	8	0	36
Aug 2021	20	18	0	38
Sep 2021	30	15	0	45
Oct 2021	29	39	1	69
Nov 2021	21	29	0	50
Dec 2021	26	8	2	36
Jan 2022	26	18	0	44
Feb 2022	16	10	1	27
Mar 2022	16	13	0	29
Apr 2022	23	7	2	32
May 2022	23	16	2	41
Jun 2022	12	7	2	21
Jul 2022	23	5	0	28
Aug 2022	22	14	0	36
Sep 2022	23	10	1	34
Oct 2022	40	4	1	45
Nov 2022	34	16	1	51
Dec 2022	17	10	0	27
Jan 2023	17	13	1	31
Feb 2023	27	12	1	40
Mar 2023	25	13	1	39
Apr 2023	16	9	0	25
May 2023	23	14	4	41
Jun 2023	21	7	2	30
Jul 2023	13	6	1	20
Aug 2023	16	5	2	23
Sep 2023	9	9	0	18
Oct 2023	13	6	0	19
Nov 2023	10	4	0	14
Dec 2023	25	7	0	32
Jan 2024	36	17	0	53
Feb 2024	117	13	3	133
Mar 2024	34	16	1	51
Apr 2024	22	6	2	30
May 2024	23	5	3	31
Jun 2024	52	11	1	64
Jul 2024	27	11	2	40
Aug 2024	27	6	2	35
Sep 2024	26	16	1	43
Oct 2024	18	6	1	25
Nov 2024	6	1	7
Dec 2024	20	6	2	28
Jan 2025	22	8	2	32
Feb 2025	25	5	4	34
Mar 2025	29	10	4	43
Apr 2025	21	25	1	47
May 2025	28	5	1	34
Jun 2025	52	22	1	75
Jul 2025	20	36	2	58
Aug 2025	18	12	0	30
Sep 2025	44	17	0	61
Oct 2025	29	30	3	62
Nov 2025	26	27	2	55

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Short summary

This study fully considers the characteristics of expressways in mountain areas. The catchment area is considered a prediction unit. The method of slope division is improved, and a method of improving the parameters in the model is proposed. Comparison and analysis with actual observation data show that the method of soil and water loss prediction adopted in this paper has less error and higher prediction accuracy than other models and can satisfy prediction requirements.


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