Fingerprinting analysis for delineation of sediment source areas in the headwater of the Volta basin, Burkina Faso (WASCAL)

Summary

A main problem for understanding, quantifying and modelling the budgets of suspended sediments, especially in developing countries, is the lack of information about its origin and its mobilisation and transfer dynamics (Walling et al 2001). Since the 1970s, however, new methods based on sediment fingerprinting were developed and tested that are able to determine the source of sediments in rivers (Wallbrink 2004). Sediment fingerprinting analysis is based on the assumption that sediments from different areas in a catchment can be distinguished due to their different chemical, physical, or even biogenic properties, and that by comparing these properties with the properties of suspended sediments it is possible to determine the relative contribution of each source area to the total load (Collins & Walling 2002). The specific fingerprint sediment from an area is assigned and its fraction in the suspended sediment load is calculated with the help of mixing models. Though it has often been tried to find one specific property to distinguish source areas, Collins & Walling 2002 suggest that composite fingerprinting - where a range of approx. 20 different properties is analysed and the best ones are used for discrimination – leads to better source area delineation. Most commonly used properties are the concentrations of a range of trace metals, base cations, organic matter, N, P, as well as concentrations of radionuclides as Caesium-137 or Lead-210 (Theuring et al. 2013).
Another factor to keep in mind is variability in time of the contribution of the different sediment sources. Especially in larger catchments rainfall is often not homogeneously distributed leading to different contributions in time. Therefore either a time integrated sampling as e.g. in Walling et al 2008, or a time series of samples covering the rainfall season, or at least main runoff events will actually be needed to estimate the annual contribution of the different sediment sources. With the knowledge of the origin of the load it is possible to combine this knowledge with quantitative data on river transported material that can be easily monitored by e.g. turbidity and discharge measurements to estimate river catchment budgets. This information can then be used as a further parameter in the sediment transport models to simulate and predict soil erosion with a higher accuracy.
Two field campaigns along the study river after the rainy season will be conducted and samples from soils, stream banks and river water will be taken from different sites within the selected catchment and river system. All sediment samples will be analysed for soil texture smaller than 10μm. Elements (26 compounds) and the radionuclides 137 Cs, 210 Pb and 7Be will be analysed in all samples. The use of mixing models will allow to distinguishing different sources of sediments.

References

• Collins, A.L. & D. E. Walling (2002): Selecting fingerprint properties for discriminating potential suspended sediment sources in river basins. In: Journal of Hydrology 261 (1-4): 218-244.

• Theuring, P., A. Jha, G. Kirchner, S. Behrens, M. Rode (2013) Identification of fluvial sediment sources in a meso-scale catchment, Northern Mongolia. Hydrological Processes, 27 (6), 845 – 856.

• Wallbrink PJ 2004. Quantifying the erosion processes and land-uses which dominate fine sediment supply to Moreton Bay, Southeast Queensland, Australia. Journal of Environmental Radioactivity 76(1-2)67-80.

• Walling, D.E., Collins, A.L. & R.W. Stroud (2008): Tracing suspended sediment and particulate phosphorus sources in catchments. Journal of Hydrology 350 (3-4): 274-289.

• Walling DE, Collins AL, Sichingabula HM, Leeks GJL 2001. Integrated assessment of catchment suspended sediment budgets: A Zambian example. Land Degradation & Development 12(5) 387-415