Importance of Monitoring Frequency for Representation of Dissolved Organic Matter Dynamics in Urban Rivers

IF 4.6 1区 地球科学 Q2 ENVIRONMENTAL SCIENCES Water Resources Research Pub Date : 2024-12-04 DOI:10.1029/2024wr037254
Hongzheng Zhu, Kieran Khamis, David M. Hannah, Stefan Krause
{"title":"Importance of Monitoring Frequency for Representation of Dissolved Organic Matter Dynamics in Urban Rivers","authors":"Hongzheng Zhu, Kieran Khamis, David M. Hannah, Stefan Krause","doi":"10.1029/2024wr037254","DOIUrl":null,"url":null,"abstract":"In-situ dissolved organic matter (DOM) monitoring frequencies have often been chosen for convenience or based on perceived wisdom, without fully assessing their impact on representation of DOM dynamics. To address this gap, we collected 5-min fluorescence data in an urban headwater and resampled it at coarser intervals to investigate the impact of monitoring frequencies on the detectability of DOM dynamics during storms. Expecting hydrometeorological conditions to modify the impact of monitoring frequency, we categorized 85 storm events into groups: Group A (low intensity, short duration), Group B (high intensity, short duration), and Group C (low intensity, long duration). Surprisingly, our analysis indicated that monitoring frequency has minimal influence on commonly used biogeochemical indexes (e.g., maximum, hysteresis and flushing index), which are employed to characterize solute behavior, regardless of storm type. To facilitate a direct comparison between monitoring frequencies, we back-interpolated coarser data into 5-min intervals and calculated mean squared errors by comparing them with original high-resolution data. Our findings indicated that in colder periods with predominately Type A and C storms, a coarser monitoring frequency (>30 min) can capture DOM dynamics. Conversely, in warmer periods when Type B storms dominate, a finer frequency (≤15 min) is necessary to capture key solute chemograph processes (e.g., first flush and dilution). Generally, we suggest a 15-min monitoring frequency as optimal for similar urban headwater systems, and advocate an adaptive approach based on seasonal variations to improve efficiency, especially when power, data transfer, and storage are constraints.","PeriodicalId":23799,"journal":{"name":"Water Resources Research","volume":"46 1","pages":""},"PeriodicalIF":4.6000,"publicationDate":"2024-12-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Water Resources Research","FirstCategoryId":"89","ListUrlMain":"https://doi.org/10.1029/2024wr037254","RegionNum":1,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"ENVIRONMENTAL SCIENCES","Score":null,"Total":0}
引用次数: 0

Abstract

In-situ dissolved organic matter (DOM) monitoring frequencies have often been chosen for convenience or based on perceived wisdom, without fully assessing their impact on representation of DOM dynamics. To address this gap, we collected 5-min fluorescence data in an urban headwater and resampled it at coarser intervals to investigate the impact of monitoring frequencies on the detectability of DOM dynamics during storms. Expecting hydrometeorological conditions to modify the impact of monitoring frequency, we categorized 85 storm events into groups: Group A (low intensity, short duration), Group B (high intensity, short duration), and Group C (low intensity, long duration). Surprisingly, our analysis indicated that monitoring frequency has minimal influence on commonly used biogeochemical indexes (e.g., maximum, hysteresis and flushing index), which are employed to characterize solute behavior, regardless of storm type. To facilitate a direct comparison between monitoring frequencies, we back-interpolated coarser data into 5-min intervals and calculated mean squared errors by comparing them with original high-resolution data. Our findings indicated that in colder periods with predominately Type A and C storms, a coarser monitoring frequency (>30 min) can capture DOM dynamics. Conversely, in warmer periods when Type B storms dominate, a finer frequency (≤15 min) is necessary to capture key solute chemograph processes (e.g., first flush and dilution). Generally, we suggest a 15-min monitoring frequency as optimal for similar urban headwater systems, and advocate an adaptive approach based on seasonal variations to improve efficiency, especially when power, data transfer, and storage are constraints.
查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
监测频率对城市河流溶解有机质动态表征的重要性
原位溶解有机物(DOM)监测频率的选择通常是为了方便或基于感知的智慧,而没有充分评估它们对DOM动态表示的影响。为了解决这一差距,我们收集了城市水源的5分钟荧光数据,并以更粗的间隔重新采样,以研究监测频率对风暴期间DOM动态可探测性的影响。预计水文气象条件会改变监测频率的影响,我们将85次风暴事件分为:A组(低强度,持续时间短),B组(高强度,持续时间短)和C组(低强度,持续时间长)。令人惊讶的是,我们的分析表明,监测频率对用于表征溶质行为的常用生物地球化学指数(例如最大值、滞后和冲刷指数)的影响最小,而与风暴类型无关。为了便于监测频率之间的直接比较,我们将较粗的数据反插值为5分钟的间隔,并通过与原始高分辨率数据进行比较来计算均方误差。我们的研究结果表明,在以A型和C型风暴为主的较冷时期,较粗的监测频率(>;30分钟)可以捕获DOM动态。相反,在B型风暴占主导地位的温暖时期,需要更细的频率(≤15分钟)来捕捉关键的溶质化学照相过程(例如,第一次冲洗和稀释)。一般来说,我们建议对于类似的城市水源系统,15分钟的监测频率是最佳的,并提倡基于季节变化的自适应方法来提高效率,特别是在电力、数据传输和存储受限的情况下。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 去求助
来源期刊
Water Resources Research
Water Resources Research 环境科学-湖沼学
CiteScore
8.80
自引率
13.00%
发文量
599
审稿时长
3.5 months
期刊介绍: Water Resources Research (WRR) is an interdisciplinary journal that focuses on hydrology and water resources. It publishes original research in the natural and social sciences of water. It emphasizes the role of water in the Earth system, including physical, chemical, biological, and ecological processes in water resources research and management, including social, policy, and public health implications. It encompasses observational, experimental, theoretical, analytical, numerical, and data-driven approaches that advance the science of water and its management. Submissions are evaluated for their novelty, accuracy, significance, and broader implications of the findings.
期刊最新文献
Unraveling the Distinct Roles of Snowmelt and Glacier-Melt on Agricultural Water Availability: A Novel Indicator and Its Application in a Glacierized Basin of China’s Arid Region Machine Learning Prediction of Tritium-Helium Groundwater Ages in the Central Valley, California, USA Control of Groundwater-Lake Interaction Zone Structure on Spatial Variability of Lacustrine Groundwater Discharge in Oxbow Lake A Cluster-Based Data Assimilation Approach to Generate New Daily Gridded Time Series Precipitation Data in the Himalayan River Basins Physics-Guided Deep Learning Model for Daily Groundwater Table Maps Estimation Using Passive Surface-Wave Dispersion
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 联系我们:info@booksci.cn
Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。
Copyright © 2023 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1