Application of quantitative composite fingerprinting technique to identify the main sediment sources in two small catchments of Iran

Abstract

Abstract. The targeting of sediment management strategies is a key requirement in developing countries including Iran because of the limited resources available. These targeting is, however hampered by the lack of reliable information on catchment sediment sources. This paper reports the results of using a quantitative composite fingerprinting technique to estimate the relative importance of the primary potential sources within the Amrovan and Royan catchments in Semnan Province, Iran. Fifteen tracers were first selected for tracing and samples were analyzed in the laboratory for these parameters. Statistical methods were applied to the data including nonparametric Kruskal-Wallis test and Differentiation Function Analysis (DFA). For Amrovan catchment three parameters (N, Cr and Co) were found to be not significant in making the discrimination. The optimum fingerprint, comprising Oc, PH, Kaolinite and K was able to distinguish correctly 100% of the source material samples. For the Royan catchment, all of the 15 properties were able to distinguish between the six source types and the optimum fingerprint provided by stepwise DFA (Cholorite, XFD, N and C) correctly classifies 92.9% of the source material samples. The mean contributions from each sediment source obtained by multivariate mixing model varied at two catchments. For Amrovan catchment Upper Red formation is the main sediment sources as this sediment source approximately supplies 36% of the reservoir sediment whereas the dominant sediment source for the Royan catchment is from Karaj formation that supplies 33% of the reservoir sediments. Results indicate that the source fingerprinting approach appears to work well in the study catchments and to generate reliable results.