Skip to main content

Lund University Publications

LUND UNIVERSITY LIBRARIES

Increasing riverine export of dissolved organic carbon from China

Yan, Yanzi ; Lauerwald, Ronny ; Wang, Xuhui ; Regnier, Pierre ; Ciais, Philippe ; Ran, Lishan ; Gao, Yuanyi ; Huang, Ling ; Zhang, Yao and Duan, Zheng LU , et al. (2023) In Global Change Biology 29(17). p.5014-5032
Abstract

River transport of dissolved organic carbon (DOC) to the ocean is a crucial but poorly quantified regional carbon cycle component. Large uncertainties remaining on the riverine DOC export from China, as well as its trend and drivers of change, have challenged the reconciliation between atmosphere-based and land-based estimates of China's land carbon sink. Here, we harmonized a large database of riverine in-situ measurements and applied a random forest model, to quantify riverine DOC fluxes (FDOC) and DOC concentrations (CDOC) in rivers across China. This study proposes the first DOC modeling effort capable of reproducing well the magnitude of riverine CDOC and FDOC, as well as its trends, on a... (More)

River transport of dissolved organic carbon (DOC) to the ocean is a crucial but poorly quantified regional carbon cycle component. Large uncertainties remaining on the riverine DOC export from China, as well as its trend and drivers of change, have challenged the reconciliation between atmosphere-based and land-based estimates of China's land carbon sink. Here, we harmonized a large database of riverine in-situ measurements and applied a random forest model, to quantify riverine DOC fluxes (FDOC) and DOC concentrations (CDOC) in rivers across China. This study proposes the first DOC modeling effort capable of reproducing well the magnitude of riverine CDOC and FDOC, as well as its trends, on a monthly scale and with a much wider spatial distribution over China compared to previous studies that mainly focused on annual-scale estimates and large rivers. Results show that over the period 2001–2015, the average CDOC was 2.25 ± 0.45 mg/L and average FDOC was 4.04 ± 1.02 Tg/year. Simultaneously, we found a significant increase in FDOC (+0.044 Tg/year2, p =.01), but little change in CDOC (−0.001 mg/L/year, p >.10). Although the trend in CDOC is not significant at the country scale, it is significantly increasing in the Yangtze River Basin and Huaihe River Basin (0.005 and 0.013 mg/L/year, p <.05) while significantly decreasing in the Yellow River Basin and Southwest Rivers Basin (−0.043 and −0.014 mg/L/year, p =.01). Changes in hydrology, play a stronger role than direct impacts of anthropogenic activities in determining the spatio-temporal variability of FDOC and CDOC across China. However, and in contrast with other basins, the significant increase in CDOC in the Yangtze River Basin and Huaihe River Basin is attributable to direct anthropogenic activities. Given the dominance of hydrology in driving FDOC, the increase in FDOC is likely to continue under the projected increase in river discharge over China resulting from a future wetter climate.

(Less)
Please use this url to cite or link to this publication:
author
; ; ; ; ; ; ; ; and , et al. (More)
; ; ; ; ; ; ; ; ; ; ; and (Less)
organization
publishing date
type
Contribution to journal
publication status
published
subject
keywords
China, climate change, dissolved organic carbon, land cover, machine learning method, net primary production, river chemistry, soil organic carbon
in
Global Change Biology
volume
29
issue
17
pages
19 pages
publisher
Wiley-Blackwell
external identifiers
  • pmid:37332159
  • scopus:85161983255
ISSN
1354-1013
DOI
10.1111/gcb.16819
language
English
LU publication?
yes
id
f7158118-0940-4806-9314-2159fbcda119
date added to LUP
2023-10-17 14:56:15
date last changed
2024-04-19 03:27:57
@article{f7158118-0940-4806-9314-2159fbcda119,
  abstract     = {{<p>River transport of dissolved organic carbon (DOC) to the ocean is a crucial but poorly quantified regional carbon cycle component. Large uncertainties remaining on the riverine DOC export from China, as well as its trend and drivers of change, have challenged the reconciliation between atmosphere-based and land-based estimates of China's land carbon sink. Here, we harmonized a large database of riverine in-situ measurements and applied a random forest model, to quantify riverine DOC fluxes (F<sub>DOC</sub>) and DOC concentrations (C<sub>DOC</sub>) in rivers across China. This study proposes the first DOC modeling effort capable of reproducing well the magnitude of riverine C<sub>DOC</sub> and F<sub>DOC</sub>, as well as its trends, on a monthly scale and with a much wider spatial distribution over China compared to previous studies that mainly focused on annual-scale estimates and large rivers. Results show that over the period 2001–2015, the average C<sub>DOC</sub> was 2.25 ± 0.45 mg/L and average F<sub>DOC</sub> was 4.04 ± 1.02 Tg/year. Simultaneously, we found a significant increase in F<sub>DOC</sub> (+0.044 Tg/year<sup>2</sup>, p =.01), but little change in C<sub>DOC</sub> (−0.001 mg/L/year, p &gt;.10). Although the trend in C<sub>DOC</sub> is not significant at the country scale, it is significantly increasing in the Yangtze River Basin and Huaihe River Basin (0.005 and 0.013 mg/L/year, p &lt;.05) while significantly decreasing in the Yellow River Basin and Southwest Rivers Basin (−0.043 and −0.014 mg/L/year, p =.01). Changes in hydrology, play a stronger role than direct impacts of anthropogenic activities in determining the spatio-temporal variability of F<sub>DOC</sub> and C<sub>DOC</sub> across China. However, and in contrast with other basins, the significant increase in C<sub>DOC</sub> in the Yangtze River Basin and Huaihe River Basin is attributable to direct anthropogenic activities. Given the dominance of hydrology in driving F<sub>DOC</sub>, the increase in F<sub>DOC</sub> is likely to continue under the projected increase in river discharge over China resulting from a future wetter climate.</p>}},
  author       = {{Yan, Yanzi and Lauerwald, Ronny and Wang, Xuhui and Regnier, Pierre and Ciais, Philippe and Ran, Lishan and Gao, Yuanyi and Huang, Ling and Zhang, Yao and Duan, Zheng and Papa, Fabrice and Yu, Bing and Piao, Shilong}},
  issn         = {{1354-1013}},
  keywords     = {{China; climate change; dissolved organic carbon; land cover; machine learning method; net primary production; river chemistry; soil organic carbon}},
  language     = {{eng}},
  number       = {{17}},
  pages        = {{5014--5032}},
  publisher    = {{Wiley-Blackwell}},
  series       = {{Global Change Biology}},
  title        = {{Increasing riverine export of dissolved organic carbon from China}},
  url          = {{http://dx.doi.org/10.1111/gcb.16819}},
  doi          = {{10.1111/gcb.16819}},
  volume       = {{29}},
  year         = {{2023}},
}