Tracking the origin of tracemetals in a watershed by identifying fingerprints of soils, landscape and river sediments

被引:14
|
作者
Derakhshan-Babaei, Farzaneh [1 ]
Mirchooli, Fahimeh [2 ]
Mohammadi, Maziar [2 ]
Nosrati, Kazem [1 ]
Egli, Markus [3 ]
机构
[1] Shahid Beheshti Univ, Dept Phys Geog, Fac Earth Sci, Tehran 1983969411, Iran
[2] Tarbiat Modares Univ, Fac Nat Resources, Dept Watershed Management & Engn, Tehran 46414356, Iran
[3] Univ Zurich, Dept Geog, Winterthurerstr 190, CH-8057 Zurich, Switzerland
基金
美国国家科学基金会;
关键词
Soil trace-elements; Machine learning; Sediment fingerprinting; Landforms; Kan River watershed; FLUVIAL SUSPENDED SEDIMENT; HEAVY-METAL POLLUTION; LAND-USE; SPATIAL-DISTRIBUTION; BANK EROSION; QUALITY; PREDICTION; CATCHMENT; INDEX; QUANTIFICATION;
D O I
10.1016/j.scitotenv.2022.155583
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
The identification of the spatial distribution of soil trace-elements and the contribution of different sources to the sediment yield is necessary for a better watershed and river water quality management. Until now, less attention has been paid to comprehensive assessments of sediment sources and soil trace-elements with respect to the suspended sediment production. The present study aimed at modelling the spatial distribution of soil trace-elements, quantifying the sediment sources apportionment and relating the landforms to polluted soils. Different techniques and approaches such as the Nemerow pollution index, machine learning algorithms (Random Forest (RF), generalised boosting methods (GBM), generalised linear models (GLM) and sediment fingerprinting were applied to the Kan watershed. A total of 79 soil samples having different Nemerow index values were considered for spatial modelling. Using statistical methods (Range test, Kruskal-Wallis and discrimination function analysis), an optimal set of tracers was selected. An unmixing model was applied to calculate the relative contribution of landforms for eight rainfall events. The results of the soil trace-element mapping showed that RF had the best performance with an accuracy of 83%. The evaluation of polluted soil areas showed that the landforms `steep hills' and `valley' contributed the most with 51% and 27% in the riparian zone, respectively. In addition, these landforms give a high contribution to sediment production in late-winter -spring events (29%) with a GOF (goodness of fit) of 0.65. The landform `plain' had the highest contribution (28%) in sediment yield with a GOF of 0.72 in early-winter events. This means that the valley and steep hill landforms accelerate the transport of trace-elements across the watershed. Interestingly, the contribution of landforms varies during the year. Overall, the new proposed approach enables to better trace the origin of suspended sediments and traceelements discharge into the river environment.
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页数:15
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