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Fingerprinting surficial sediment sources: Exploring some potential problems associated with the spatial variability
1International Research and Training Center on Erosion and Sedimentation (IRTCES), China Institute of Water Resources and Hydropower Research (IWHR), No. 20 Chegongzhuang Road West, Beijing, 100048, China.
Journal of Environmental Management
|July 25, 2016
Summary
Investigating spatial variability in soil properties is crucial for accurate sediment source fingerprinting. This study quanties geochemical variations within a field, offering guidelines for improved sediment tracing methods.
Area of Science:
- Environmental Science
- Soil Science
- Geochemistry
Background:
- Sediment source tracing relies on sediment properties for source discrimination.
- Spatial variability of these properties poses challenges for accurate source apportionment.
- Previous research has not fully explored the extent and implications of spatial variability in surface soils.
Purpose of the Study:
- To document the magnitude and nature of spatial variability in geochemical properties of surface soils.
- To explore the implications of this variability for sediment source fingerprinting.
- To provide guidelines for selecting sampling points in source fingerprinting investigations.
Main Methods:
- Collected 52 surface soil samples from a 7-hectare cultivated field.
- Analyzed 53 geochemical properties for potential fingerprinting.
- Utilized caesium-137 (137Cs) measurements to assess soil redistribution rates.
Main Results:
- Quantified the spatial variability of 53 geochemical properties within the field.
- Demonstrated the influence of soil redistribution rate on surface soil properties.
- Identified correlations between different soil properties and their impact on fingerprinting procedures.
Conclusions:
- Spatial variability of soil properties significantly impacts sediment source fingerprinting accuracy.
- Understanding soil redistribution is key to interpreting spatial variability.
- Guidelines for sampling point selection can improve the reliability of source apportionment results.

