JOURNAL ARTICLE
Sedimentary Characteristics, Ages, and Environmental Significance of Gravel Deposits and Loess in Shandong, Eastern China: Regional Response to Global Change Since the Last Glacial Period.
Published In: Acta Geologica Sinica (English Edition), 2024, v. 98, n. 2. P. 491 1 of 3
Database: Academic Search Ultimate 2 of 3
Authored By: Wang, Min; KONG, Fanbiao; KONG, Xianglun; Chen, Haitao; Wang, Jiawei; MIAO, Xiaodong; JIA, Guangju; HAN, Mei; XU, Shujian 3 of 3
Abstract
Investigation of rarely studied gravel layers found in the loess in Shandong Province, eastern China, reveals the fabric characteristics of two gravel layers (G1, G2) and the sedimentary characteristics of loess at the typical and well‐preserved Heiyu section (HY), where, to determine the paleoclimatic changes during Marine Isotope Stage 3a. Optically stimulated luminescence dates of the HY formation range from 0.26 ± 0.02 ka to 39.00 ± 2.00 ka. In addition, the ages of G1 and G2 were estimated using the Bayesian model to be 39.60–40.50 and 29.00–29.50 ka. G1 and G2 are mainly composed of fine and medium gravel, both of which were subangular to subrounded limestone, with gravel directions to NE and E. The average flow velocity, average depth, and flood peak flow of G1 are 1.10 m/s, 0.49 m, and 37.04 m3/s, respectively, calculated using the flow energy method, whereas those of G2 are 0.98 m/s, 0.38 m, and 18.38 m3/s, respectively. Analysis of climate proxy indices show that the sedimentary environment of the gravel and loess in HY might be a regional response to global change. [ABSTRACT FROM AUTHOR]
Additional Information
- Source:Acta Geologica Sinica (English Edition). 2024/04, Vol. 98, Issue 2, p491
- Document Type:Article
- Subject Area:Earth and Atmospheric Sciences
- Publication Date:2024
- ISSN:1000-9515
- DOI:10.1111/1755-6724.15152
- Accession Number:176866543
- Copyright Statement:Copyright of Acta Geologica Sinica (English Edition) is the property of Wiley-Blackwell and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
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