高山峡谷区地球化学普查采样点协同优化布设与现场微调方法

doi:10.11720/wtyht.2025.0085

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Abstract

Stream sediment survey is the most widely applied method in regional geological surveys due to its simplicity, efficiency, low cost, and proven effectiveness in mineral exploration. This method shows promising application potential in Southwest China, characterized by well-developed hydrographic nets. Sampling quality directly determines the representativeness and accuracy of geochemical exploration data. However, sampling point arrangements in alpine gorge areas remain challenged by insufficient coverage of lower-order streams, omission of coarse-grained clastics in high-energy zones, and interference from human-induced contamination. To address these challenges, this study innovatively proposed an optimization strategy combining synergistic optimization and the on-site fine-tuning method for the 1∶50 000 stream sediment survey in the Fanshen Village area, Huize County, Yunnan Province. This strategy integrates critical technologies, including two-level dynamic grids (a 1 km×1 km basic grid and a 500 m infill grid), dynamic channel alignment offset (50 m to 100 m), and pre-set contamination buffer zones (200 m), for fieldwork. The results indicate that compared to traditional fixed-grid methods, the optimization strategy achieved a significantly increased coverage rate of 72% for tertiary tributaries, a capture rate of 82 % for coarse-grained clastics (>2 mm), and a reduced occurrence rate of 5% for human-induced pseudo-anomalies, with the overall cost increase controlled within 12%. Overall, the optimization strategy can effectively enhance the reliability of sampling data and the accuracy of anomaly delineation in complex topographic areas, providing an optimized solution for geochemical surveys in alpine gorge areas, Southwest China.

Key words： stream sediment survey sampling optimization synergistic optimization on-site fine-tuning method

Received: 18 March 2025 Published: 30 December 2025

ZTFLH:

P632

Corresponding Authors: YANG Ming-Long E-mail: zengliang3332022@163.com;351008671@qq.com

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	Liang ZENG
	Ming-Long YANG
	Yong PANG
	Jia-Zhong HUANG
	Ping-Yan BAI
	Bing-Jun WANG

Cite this article:

Liang ZENG,Ming-Long YANG,Yong PANG, et al. Synergistic optimization and on-site fine-tuning methods for sampling point arrangement for geochemical survey in an alpine gorge area, Southwest China[J]. Geophysical and Geochemical Exploration, 2025, 49(6): 1343-1352.

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https://www.wutanyuhuatan.com/EN/10.11720/wtyht.2025.0085 OR https://www.wutanyuhuatan.com/EN/Y2025/V49/I6/1343

Geological sketch map of the Fanshen Village area
1—Holocene; 2—Xiaolongtan Formation; 3—Ziliujing Formation; 4—Jialingjiang Formation; 5—Feixianguan Formation; 6—Xuanwei Formation; 7—Emeishan basalt Formation; 8—Maokou Formation; 9—Liangshan Formation; 10—Wanshoushan Formation; 11—Zaijieshan Formation; 12—Hongshiya Formation; 13—Loushanguan Formation; 14—Longwangmiao Formation; 15—Meishucun Formation; 16—Dengying Formation; 17—measured unconformity boundary; 18—main fault; 19—measured fault of unknown nature; 20—phosphate deposit; 21—copper mineralization point; 22—lead-zinc mineralization point; 23—bauxite mineralization point; 24—anthracite mineralization point; 25—hematite mineralization point; 26—barite mineralization point; 27—rare earth mineralization point; 28—calcite mineralization point; 29—agate mineralization point; 30—place name

Water system distribution in the Fenshen Village area
1—village; 2—watercourse line; 3—lower limit of F anomaly (1000×10^-6) delineation range; 4—lower limit of Ba anomaly (600×10^-6) delineation range; 5—lower limit of Cd anomaly (1×10^-6) delineation range; 6—lower limit of Pb anomaly (60×10^-6) delineation range; 7—lower limit of Ag anomaly (0.12×10^-6) delineation range; 8—lower limit of Zn anomaly (200×10^-6) delineation range; 9—lower limit of Mo anomaly (3×10^-6) delineation range; 10—lower limit of Sb anomaly (2×10^-6) delineation range; 11—elevation contour line

Reference network for soil geochemical measurements

S>15% and α>35° indicates a high=energy transport zone, and an offset ≤100 m ensures the represent-ativeness of the medium (RD<20%)
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Schematic diagram of the theoretical model of sampling bias in steep slope areas
note: according to A.N. Strahler's "Principles of Physical Geography", S>15% and α>35° indicates a high=energy transport zone, and an offset ≤100 m ensures the represent-ativeness of the medium (RD<20%)

Decision guidelines for sampling offsets in steep slope areas

Methodological system technical processes

Layout of specimen points for typical geomorphological units in the study area

Comparison between the traditional method(a) and the “Co-optimisation-field fine-tuning method” (b) for the deployment of sample points of typical geomorphological units in the study area
1—different sampling medium zone ranges; 2—encryption zone ranges; 3—dilution zone ranges; 4—repeated sample large grid; 5—repeated sample large grid number; 6—small grid number annotation; 7—sampling point; 8—large grid number; 9—water system line; 10—elevation line

Typical geomorphological unit method adaptation strategies

Comparison of key indicators

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