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Traditional fingerprinting methods are limited in their ability to identify soil erosion sources where geologic variations are small or where different land uses span geological boundaries. In this study, a new biomarker for fingerprinting, specifically, n -alkanes, was used in a small catchment to identify sediment sources. The n -alkanes were based on land uses, could provide vegetation information, and were relatively resistant to diagenetic modifications and decomposition. This study used a composite fingerprinting method that was based on two types of fingerprint factors (27 biomarker properties and 45 geochemical properties) with 60 source samples (i.e., gully, grassland, forest, and cropland) and nine soil profiles. Genetic algorithm (GA) optimization has been deployed to find the optimal source contribution to sediments. The biomarker results demonstrated that young forest is the main sediment source in this catchment, contributing 50.5%, whereas cropland, grassland and gully contributed 25.6%, 14.4% and 9.5%, respectively; the geochemistry results were similar to the biomarkers. The forest and grassland contributions gradually increased from upstream to downstream, and the sediment contributions of cropland gradually decreased in the direction of the runoff pathway at the check dam. In a comparison of biomarker and geochemical fingerprinting data, the latter may have overestimated the forest inputs to the catchment sediment yields because of a mixed land use history (i.e., forest and grassland). The geochemical fingerprint approach limits its ability to fully discriminate sources based on land management regimes, but the biomarker (individual n -alkanes) displayed the potential to discriminate between a greater number and different types of sediment sources and to provide greater detail regarding sediment sources. [ABSTRACT FROM AUTHOR]

The frequency of harmful algal blooms caused by eutrophication is increasing globally, posing serious threats to human health and economic development. Reservoir bays, affected by water environment and local watershed landscape, are more prone to eutrophication and algal blooms. The chlorophyll a (Chl a) concentration is an important indicator for the degree of eutrophication and algal bloom. Exploring the complex relationships between water environment and landscape background, and Chl a concentration in the reservoir bays are crucial for ensuring high-quality drinking water from reservoirs. In this study, we monitored Chl a concentrations of 66 bays in Danjiangkou Reservoir and the related water quality parameters (e.g., water temperature, turbidity, nutrients) in waterbodies of these reservoir bays in the storage and discharge periods from 2015 to 2018. Partial least squares-structural equation modeling (PLS-SEM) was used to quantify the relationship between water environmental factors and watershed landscapes, and Chl a concentrations in reservoir bays. The results showed that mean Chl a concentration was higher in storage period than that in discharge period. Two optimal PLS-SEMs explained 66.8% and 53.6% of Chl a concentration variation in the storage and discharge periods, respectively. The net effect of water chemistry on Chl a concentration was more pronounced during the discharge period (total effect = 0.61, 37% of the total effect on Chl a), while the net effect of land-use composition on Chl a concentration was more significant during the storage period (total effect = 0.57, 30% of the total effect on Chl a). The landscape pattern had significant indirect effects on Chl a concentration, especially during the discharge period (indirect effect = −0.31, 19% of the total effect on Chl a). Our results provide valuable information for managers to make rational decisions, thereby contributing to the prevention of eutrophication and algal blooms in reservoir bays. Unlabelled Image • The relationships between water environment and local watershed landscape and Chl a in reservoir bays were investigated. • The Chl a concentration had significant variations between the storage and discharge periods. • Water chemistry had greater positive effects on Chl a concentration in the discharge period. • The positive effect of land use on the Chl a concentration was greater in the storage period. [ABSTRACT FROM AUTHOR]