A - Papers appearing in refereed journals
Nosrati, K., Haddadchi, A., Collins, A. L., Jalali, S. and Reza Zare, M. 2018. Tracing sediment sources in a mountainous forest catchment under road construction in northern Iran: comparison of Bayesian and frequentist approaches. Environmental Science and Pollution Research. 25, pp. 30979-30999. https://doi.org/10.1007/s11356-018-3097-5
Authors | Nosrati, K., Haddadchi, A., Collins, A. L., Jalali, S. and Reza Zare, M. |
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Abstract | Development and land use change lead to accelerated soil erosion as a serious environmental problem in river catchments in Iran. Reliable information about the sources of sediment in catchments is therefore necessary to design effective control strategies. This study used a composite sediment source tracing procedure to determine the importance of forest road cuttings as a sediment source in a mountainous catchment located in northern Iran. A fallout radionuclide (137Cs) and 12 geochemical tracers (Ca, Cu, Fe, K, Mg, Mn, Na, Ni, OC, Pb, Sr and TN) were used to determine the relative contributions of three sediment source types |
Keywords | Sediment tracing; Sub-surface erosion; Geochemical tracers; 137Cs ; MixSIR Bayesian model |
Year of Publication | 2018 |
Journal | Environmental Science and Pollution Research |
Journal citation | 25, pp. 30979-30999 |
Digital Object Identifier (DOI) | https://doi.org/10.1007/s11356-018-3097-5 |
Open access | Published as non-open access |
Funder | Biotechnology and Biological Sciences Research Council |
Funder project or code | S2N - Soil to Nutrition - Work package 3 (WP3) - Sustainable intensification - optimisation at multiple scales |
Output status | Published |
Publication dates | |
Online | 04 Sep 2018 |
Publication process dates | |
Accepted | 28 Aug 2018 |
Publisher | Springer Heidelberg |
Copyright license | CC BY |
ISSN | 0944-1344 |
Permalink - https://repository.rothamsted.ac.uk/item/84v0q/tracing-sediment-sources-in-a-mountainous-forest-catchment-under-road-construction-in-northern-iran-comparison-of-bayesian-and-frequentist-approaches
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