Study on the response mechanisms and evolution prediction of groundwater microbial-toxicological indicators.

IF 2.5 4区 环境科学与生态学 Q3 ENGINEERING, ENVIRONMENTAL Water Environment Research Pub Date : 2024-10-01 DOI:10.1002/wer.11131
Weichao Sun, Shuaiwei Wang, Junbo Bi, Zhuo Ning, Jingjing Wang, Haibo Hou
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Abstract

This study aims to investigate the response mechanisms of groundwater microbial-toxicological indicators, specifically total bacteria count (TBC) and total coliform count (TCC), to water quality indicators and environmental conditions. Using data from a water source in the western plateau of China, a predictive model focusing on TBC and TCC was developed. An orthogonal experimental design was employed to manipulate environmental conditions such as temperature, pH, and porosity, facilitating laboratory experiments. These experiments measured pH, chemical oxygen demand (COD), oxidation-reduction potential (ORP), TBC, and TCC at varying depths and environmental conditions. Principal component analysis elucidated the mechanisms by which water quality indicators and environmental conditions affect groundwater microbial-toxicological indicators. A prediction model for these indicators in plateau regions was established based on a backpropagation neural network (BP-NN), using TBC and TCC as target variables and the newly extracted principal components as influencing factors. The results demonstrate that environmental conditions and water quality indicators primarily influence the evolution of groundwater microbial-toxicological indicators by altering the ionic charge quantities, redox conditions, and temperature of the groundwater. The predictive model for groundwater microbial-toxicological indicators shows trends consistent with experimental outcomes, with an average relative error of less than 15%, meeting engineering requirements. PRACTITIONER POINTS: The values of total bacteria count (TBC) and total coliform count (TCC) under different conditions were obtained by column experiments. The influence mechanism of environmental conditions and groundwater indicators on TBC and TCC was elaborated by principal component analysis. TBC and TCC prediction models were established through the investigation of water sources in a plateau area and laboratory experiments.

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地下水微生物毒理学指标的响应机制和演化预测研究。
本研究旨在探讨地下水微生物毒理学指标(特别是细菌总数(TBC)和总大肠菌群数(TCC))对水质指标和环境条件的响应机制。利用中国西部高原水源地的数据,建立了以总细菌数和总大肠菌群为重点的预测模型。采用正交实验设计来控制温度、pH 值和孔隙度等环境条件,从而促进实验室实验。这些实验测量了不同深度和环境条件下的 pH 值、化学需氧量 (COD)、氧化还原电位 (ORP)、TBC 和 TCC。主成分分析阐明了水质指标和环境条件对地下水微生物毒理学指标的影响机制。以 TBC 和 TCC 为目标变量,以新提取的主成分为影响因素,基于反向传播神经网络(BP-NN)建立了高原地区这些指标的预测模型。结果表明,环境条件和水质指标主要通过改变地下水的离子电荷量、氧化还原条件和温度来影响地下水微生物毒理学指标的演变。地下水微生物毒理学指标预测模型显示的趋势与实验结果一致,平均相对误差小于 15%,符合工程要求。实践点:通过柱状实验得到了不同条件下细菌总数(TBC)和大肠菌群总数(TCC)的数值。通过主成分分析,阐述了环境条件和地下水指标对 TBC 和 TCC 的影响机理。通过对高原地区水源的调查和实验室实验,建立了 TBC 和 TCC 预测模型。
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来源期刊
Water Environment Research
Water Environment Research 环境科学-工程:环境
CiteScore
6.30
自引率
0.00%
发文量
138
审稿时长
11 months
期刊介绍: Published since 1928, Water Environment Research (WER) is an international multidisciplinary water resource management journal for the dissemination of fundamental and applied research in all scientific and technical areas related to water quality and resource recovery. WER''s goal is to foster communication and interdisciplinary research between water sciences and related fields such as environmental toxicology, agriculture, public and occupational health, microbiology, and ecology. In addition to original research articles, short communications, case studies, reviews, and perspectives are encouraged.
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