title: Variation of dissolved organic carbon transported by two Chinese rivers: The Changjiang River and Yellow River.
abstract: Real-time monitoring of riverine dissolved organic carbon (DOC) and the associated controlling factors is essential to coastal ocean management. This study was the first to simulate the monthly DOC concentrations at the Datong Hydrometric Station for the Changjiang River and at the Lijin Hydrometric Station for the Yellow River from 2000 to 2013 using a multilayer back-propagation neural network (MBPNN), along with basin remote-sensing products and river in situ data. The average absolute error between the modeled values and in situ values was 9.98% for the Changjiang River and 10.84% for the Yellow River. As an effect of water dilution, the variations of DOC concentrations in the two rivers were significantly negatively affected by discharge, with lower values reported during the wet season. Moreover, vegetation growth status and agricultural activities, represented by the gross primary product (GPP) and cropland area percent (CropPer) in the river basin, respectively, also significantly affected the DOC concentration in the Changjiang River, but not the Yellow River. The monthly riverine DOC flux was calculated using modeled DOC concentrations. In particular, the riverine DOC fluxes were affected by discharge, with 71.06% being reported for the Changjiang River and 90.71% for the Yellow River. Over the past decade, both DOC concentration and flux in the two rivers have not shown significant changes.
authors.affiliation: School of Earth Sciences, Zhejiang University, Hangzhou 310027, China; State Key Laboratory of Satellite Ocean Environment Dynamics, Second Institute of Oceanography, State Oceanic Administration, Hangzhou 310012, China.
authors.forename: Dong
authors.initials: D
authors.lastname: Liu
authors.affiliation: School of Earth Sciences, Zhejiang University, Hangzhou 310027, China; State Key Laboratory of Satellite Ocean Environment Dynamics, Second Institute of Oceanography, State Oceanic Administration, Hangzhou 310012, China. Electronic address: pandelu@sio.org.cn.
authors.forename: Delu
authors.initials: D
authors.lastname: Pan
authors.affiliation: State Key Laboratory of Satellite Ocean Environment Dynamics, Second Institute of Oceanography, State Oceanic Administration, Hangzhou 310012, China.
authors.forename: Yan
authors.initials: Y
authors.lastname: Bai
authors.affiliation: State Key Laboratory of Satellite Ocean Environment Dynamics, Second Institute of Oceanography, State Oceanic Administration, Hangzhou 310012, China.
authors.forename: Xianqiang
authors.initials: X
authors.lastname: He
authors.affiliation: State Key Laboratory of Satellite Ocean Environment Dynamics, Second Institute of Oceanography, State Oceanic Administration, Hangzhou 310012, China.
authors.forename: Difeng
authors.initials: D
authors.lastname: Wang
authors.affiliation: State Key Laboratory of Satellite Ocean Environment Dynamics, Second Institute of Oceanography, State Oceanic Administration, Hangzhou 310012, China.
authors.forename: Lin
authors.initials: L
authors.lastname: Zhang
mesh_terms: D002244:Carbon / Q000032:analysis* / Q000737:chemistry; D004784:Environmental Monitoring; D008962:Models, Theoretical; D045483:Rivers / Q000737:chemistry*; D012621:Seasons
chemical_list: D002244:Carbon
keywords: Dissolved organic carbon; Multilayer back-propagation neural network; The Changjiang River; The Yellow River; Variation