Controls on Spatial Variability in Mean Concentrations and Export Patterns of River Chemistry Across the Australian Continent

被引:9
|
作者
Liu, Shuci [1 ]
Dupas, Remi [2 ]
Guo, Danlu [3 ]
Lintern, Anna [4 ]
Minaudo, Camille [5 ]
Bende-Michl, Ulrike [6 ,7 ]
Zhang, Kefeng [8 ]
Duvert, Clement [9 ,10 ]
机构
[1] Queensland Govt, Dept Environm & Sci, Brisbane, Qld, Australia
[2] INRAE, Inst Agro, UMR SAS 1069, Rennes, France
[3] Australian Natl Univ, ANU Coll Engn Comp & Cybernet, Sch Engn, Canberra, ACT, Australia
[4] Monash Univ, Dept Civil Engn, Melbourne, Vic, Australia
[5] Univ Barcelona, Dept Evolutionary Biol Ecol & Environm Sci, Barcelona, Spain
[6] Bur Meteorol, Sci & Innovat Grp Hydrol Res, Canberra, ACT, Australia
[7] Univ Melbourne, Dept Infrastructure Engn, Melbourne, Vic, Australia
[8] UNSW Sydney, Water Res Ctr, Sch Civil & Environm Engn, Sydney, NSW, Australia
[9] Charles Darwin Univ, Res Inst Environm & Livelihoods, Darwin, NT, Australia
[10] Natl Ctr Groundwater Res & Training NCGRT, Adelaide, SA, Australia
关键词
water quality; concentration-discharge relationship; spatial variability; catchment characteristics; Bayesian model averaging; Bayesian hierarchical modeling; BAYESIAN VARIABLE SELECTION; GREAT-BARRIER-REEF; STREAM WATER-QUALITY; LAND-USE; SEDIMENT TRANSPORT; TIME DISTRIBUTIONS; SUSPENDED SEDIMENT; LINEAR-REGRESSION; RESIDENCE TIME; DISCHARGE;
D O I
10.1029/2022WR032365
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
The state and dynamics of river chemistry are influenced by both anthropogenic and natural catchment characteristics. However, understanding key controls on catchment mean concentrations and export patterns comprehensively across a wide range of climate zones is still lacking, as most of this research is focused on temperate regions. In this study, we investigate the catchment controls on mean concentrations and export patterns (concentration-discharge relationship, C-Q slope) of river chemistry, using a long-term data set of up to 507 sites spanning five climate zones (i.e., arid, Mediterranean, temperate, subtropical, tropical) across the Australian continent. We use Bayesian model averaging (BMA) and hierarchical modeling (BHM) approaches to predict the mean concentrations and export patterns and compare the relative importance of 26 catchment characteristics (e.g., topography, climate, land use, land cover, soil properties and hydrology). Our results demonstrate that mean concentrations result from the interaction of catchment indicators and anthropogenic factors (i.e., land use, topography and soil), while export patterns are influenced by topography. We also found that incorporating the effects of climate zones in a BHM framework improved the predictability of both mean concentrations and C-Q slopes, suggesting the importance of climatic controls on hydrological and biogeochemical processes. Our study provides insights into the contrasting effects of catchment controls across different climate zones. Investigating those controls can inform sustainable water quality management strategies that consider the potential changes in river chemistry state and export behavior.
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收藏
页数:26
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