A new method to evaluate the accuracy of the sediment source mixing model. (September 2022)
- Record Type:
- Journal Article
- Title:
- A new method to evaluate the accuracy of the sediment source mixing model. (September 2022)
- Main Title:
- A new method to evaluate the accuracy of the sediment source mixing model
- Authors:
- Bai, Lulu
Shi, Peng
Yu, Kunxia
Li, Peng
Li, Zhanbin
Xu, Guoce
Wang, Dejun
Sun, Jingmei
Min, Zhiqiang
Man, Zhiqiang
Cui, Lingzhou - Abstract:
- Graphical abstract: Highlights: A new method for the applicability of sediment source model is established. M-H Mixing Model had a higher comprehensive score compared with C Mixing Model. Mg, Cr, Ni, TOC were the optimum composite fingerprints with 97.2% contribution. The contribution rate followed as: gully > farmland > grassland > branch ditch. Abstract: Soil erosion is the worldly environmental and ecological problems. How to accurately identify the source of the sediment is important for soil and water conservation. Fingerprint identification technology has been widely used in the extraction of sediment source proportion, but currently most of the methods used to evaluate the accuracy of the results are a-good-fit (GOF) or a mean absolute error (MAE). We propose a new method to evaluate the accuracy of the sediment source mixing model and quantitatively evaluate the two sediment source mixing models. A typical check dam in the Loess Plateau was used to evaluate the new method by combining field sampling and numerical simulation. Collins (C) and Modified Hughes mixing (M-H) models were used to quantitatively analyze the sediment sources in the dam-control watershed. The results showed that the optimum composite fingerprints were Mg, Cr, Ni, and TOC, and they had 97.2% discrimination ability. The contribution rates of sediment source from gully, farmland, grassland and branch ditch were 54%, 24%, 15% and 7%, respectively. The M-H mixing model had a higher comprehensiveGraphical abstract: Highlights: A new method for the applicability of sediment source model is established. M-H Mixing Model had a higher comprehensive score compared with C Mixing Model. Mg, Cr, Ni, TOC were the optimum composite fingerprints with 97.2% contribution. The contribution rate followed as: gully > farmland > grassland > branch ditch. Abstract: Soil erosion is the worldly environmental and ecological problems. How to accurately identify the source of the sediment is important for soil and water conservation. Fingerprint identification technology has been widely used in the extraction of sediment source proportion, but currently most of the methods used to evaluate the accuracy of the results are a-good-fit (GOF) or a mean absolute error (MAE). We propose a new method to evaluate the accuracy of the sediment source mixing model and quantitatively evaluate the two sediment source mixing models. A typical check dam in the Loess Plateau was used to evaluate the new method by combining field sampling and numerical simulation. Collins (C) and Modified Hughes mixing (M-H) models were used to quantitatively analyze the sediment sources in the dam-control watershed. The results showed that the optimum composite fingerprints were Mg, Cr, Ni, and TOC, and they had 97.2% discrimination ability. The contribution rates of sediment source from gully, farmland, grassland and branch ditch were 54%, 24%, 15% and 7%, respectively. The M-H mixing model had a higher comprehensive score (2.26) when compared with the C mixing model (2.20). The comprehensive evaluation method could provide an effective scientific theoretical basis for optimal allocations of water and soil conservation in small watersheds. … (more)
- Is Part Of:
- Ecological indicators. Volume 142(2022)
- Journal:
- Ecological indicators
- Issue:
- Volume 142(2022)
- Issue Display:
- Volume 142, Issue 2022 (2022)
- Year:
- 2022
- Volume:
- 142
- Issue:
- 2022
- Issue Sort Value:
- 2022-0142-2022-0000
- Page Start:
- Page End:
- Publication Date:
- 2022-09
- Subjects:
- Check dam -- Sediment sources -- Model accuracy -- Comprehensive evaluation
Environmental monitoring -- Periodicals
Environmental management -- Periodicals
Environmental impact analysis -- Periodicals
Environmental risk assessment -- Periodicals
Sustainable development -- Periodicals
333.71405 - Journal URLs:
- http://www.sciencedirect.com/science/journal/1470160X/ ↗
http://www.elsevier.com/journals ↗ - DOI:
- 10.1016/j.ecolind.2022.109304 ↗
- Languages:
- English
- ISSNs:
- 1470-160X
- Deposit Type:
- Legaldeposit
- View Content:
- Available online (eLD content is only available in our Reading Rooms) ↗
- Physical Locations:
- British Library DSC - 3648.877200
British Library DSC - BLDSS-3PM
British Library HMNTS - ELD Digital store - Ingest File:
- 23048.xml