Pollution Assessment and Source Analysis of Heavy Metals and Nutrients in Sediments of Liujiaxia Reservoir, Upper Yellow River, China
Abstract
Liujiaxia Reservoir is a critical drinking-water source on the upper Yellow River; sediment pollution directly threatens downstream water supply security and watershed ecological health. Sediment samples were collected from 21 sites spanning the entire reservoir and its major tributary inlets in November 2025. This study evaluated total nitrogen (TN), total phosphorus (TP), and eight heavy metals (Cd, Cr, Cu, Zn, Pb, Hg, As, Ni) using an improved geo-accumulation index, potential ecological risk index, comprehensive pollution index, Pearson correlation, and PCA for pollution assessment and source apportionment.TN averaged 544.62 mg/kg and TP 585.33 mg/kg, indicating clean to slight pollution, with TP as the dominant contributor and enrichment at river inlets and deep-water zones due to terrestrial inputs and hydrodynamic trapping. All heavy metals remained below GB 15618 − 2018 screening values (pH > 7.5); only Hg showed localized slight enrichment above the Gansu background value (Im1 = 0.14). Composite assessment confirmed low ecological risk (RI mean = 95.86). Source analysis revealed three independent factors: natural Loess Plateau weathering (PC1, 44.0%), anthropogenic atmospheric/agricultural inputs dominated by Hg and Pb (PC2, 16.3%), and terrestrial runoff plus localized aquaculture for nutrients (PC3, 13.9%).The improved geo-accumulation index outperformed conventional methods. These findings fill key research gaps and provide a scientific basis for targeted pollution control and sustainable management of this vital drinking-water source.
Keywords
Citation Information
@article{beibeiwang2026,
title={Pollution Assessment and Source Analysis of Heavy Metals and Nutrients in Sediments of Liujiaxia Reservoir, Upper Yellow River, China},
author={Beibei Wang and Dili Li and Long Yan and Yanhang Hu and Zifeng Hong and Long Shi and Pengxin Cao},
journal={Scientific Reports},
year={2026},
doi={https://doi.org/10.21203/rs.3.rs-9239803/v1}
}
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