Beschreibung:
Fingerprinting methods are widely used to quantify sediment provenance at a watershed scale. However, different fingerprinting methods often yield different results for the same watershed. The objectives are to discuss in detail the performance of five fingerprinting approaches, compare the efficiency of various solutions, and investigate the effects of the number of composite fingerprints and the number of tracers in a composite fingerprint on the estimation accuracy. Source samples were collected from three typical geomorphic areas of the dune, gobi, and mountain in the Danghe Reservoir watershed in Northwest China, and sediment from the Danghe reservoir. Overall results suggest that the multiple composite fingerprints approach was superior to the single or fewer composite fingerprints approach. Generally, increasing the number of composite fingerprints tended to improve the estimation accuracy. Secondly, the preferred methods of solving the mixing model should depend upon the number of composite fingerprints. When the number of composite fingerprints is large, analytical solutions, compared to numerical solutions, are preferred as the computation is simple while providing exact solution and better estimation by eliminating fitting errors. For a single composite fingerprint or fewer composite fingerprints, Monte Carlo (MC) simulation, which can statistically increase sample number, is favored to obtain a reliable estimation. However, for a moderate number of composite fingerprints, direct optimization using average tracer concentrations without MC simulation may be desirable, because it tends to yield similar accuracy to a full MC simulation while avoiding intensive computation. There was no clear relationship between the number of tracers in a composite fingerprint and the estimation accuracy, as the optimal number of tracers is situation dependent. Results also indicate that a composite fingerprint with higher discriminant ability may not necessarily translate to better estimation, as affected by tracers’ conservatism and measurement errors