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优化低地透水流域的多站点传感器网络,以在基流条件下进行全面水质监测和氮质量平衡分析。

Optimising multi-site sensor networks in lowland permeable catchments for comprehensive water quality monitoring and nitrogen mass balancing during baseflow conditions.

作者信息

Homan Thomas, Bryant Lee, Howden Nicholas J K, Barden Ruth, Kasprzyk-Hordern Barbara, Hofman Jan

机构信息

Department of Chemical Engineering, University of Bath, Claverton Down, Bath, BA2 7AY, UK; Water Innovation and Research Centre (WIRC), University of Bath, Bath, BA2 7AY, UK.

Water Innovation and Research Centre (WIRC), University of Bath, Bath, BA2 7AY, UK; Department of Architecture & Civil Engineering, University of Bath, Bath, BA2 7AY, UK.

出版信息

Water Res. 2025 Sep 1;283:123874. doi: 10.1016/j.watres.2025.123874. Epub 2025 May 20.

DOI:10.1016/j.watres.2025.123874
PMID:40449313
Abstract

High-frequency data are essential to elucidate intricate fluvial water quality dynamics, but current understanding is often limited by measurements taken solely at the catchment outlet. In densely populated and agriculturally intensive lowland permeable catchments, such as Chalk streams in southern England, the spatial heterogeneity of processes driving solute mobilisation, transport, and fate can only be unravelled through monitoring at high spatio-temporal resolutions. In this study, we deployed a network of in-situ sensors in the lower section (ca. 18 km third-order reach) of a chalk stream during baseflow conditions to address this limitation. We focused particularly on reach-scale processing of reactive nitrogen (N), using a mass-balance approach based on high-frequency measurements, to quantify the relative importance of different sources (springs, sewage effluent) and sinks (microbiological processes in the river). Continuous in-situ measurements revealed important event-based influences that grab sampling would likely fail to capture, such as rainfall disturbance of metabolic activity and polluted discharges from combined sewer overflows. Mass balances showed the majority of fluvial nitrate load originates in the first half (ca. 8 km) of the study reach, where it increased by a factor of 2.8 from 324 kg d to 914 kg d. This was mainly attributed to a sewage treatment discharge (37% of accreted load), and chalk spring discharges (55%) carrying loads primarily from agricultural inputs. Nitrate assimilation (overall for the study reach 80 mg m d) by autotrophs was estimated to be the main retention pathway but accounted for only 2.6% ± 0.6% of total loading to the stream reach. Despite the short study duration (5 weeks) and extreme low-flow conditions, we concluded that the river has limited capacity to attenuate gross N loads, causing detrimental ecological impacts to the downstream marine conservation area. Our findings underscore the management imperative of reducing catchment N loading to nitrate-enriched streams as the most effective way of controlling N exports and restoring the removal efficacy of natural stream ecosystems. Our novel mass-balance sensor-network approach is effective at quantifying the relative importance of solute sources and sinks in heterogenous catchments. But, to maximise the data value of multi-station networks, we recommend recording measurements over long durations and in unison with other sampling strategies e.g. tracer studies, terrestrial and ecological monitoring, sediment-core sampling, and longitudinal profiling.

摘要

高频数据对于阐明复杂的河流水质动态至关重要,但目前的认识往往受限于仅在集水区出口处进行的测量。在人口密集且农业集约化程度高的低地透水集水区,如英格兰南部的白垩溪流,驱动溶质动员、运输和归宿的过程的空间异质性只能通过高时空分辨率的监测来揭示。在本研究中,我们在基流条件下于一条白垩溪流的下游段(约18公里的三级河段)部署了一个原位传感器网络,以解决这一限制。我们特别关注活性氮(N)的河段尺度处理,使用基于高频测量的质量平衡方法,来量化不同来源(泉水、污水排放)和汇(河流中的微生物过程)的相对重要性。连续的原位测量揭示了基于事件的重要影响,而抓取采样可能无法捕捉到这些影响,例如代谢活动的降雨干扰和来自合流制下水道溢流的污染排放。质量平衡表明,大部分河流硝酸盐负荷起源于研究河段的前半段(约8公里),在那里它从324千克/天增加到914千克/天,增长了2.8倍。这主要归因于污水处理排放(增加负荷的37%)和携带主要来自农业输入负荷的白垩泉水排放(55%)。自养生物的硝酸盐同化作用(研究河段总体为80毫克/平方米·天)被估计为主要的保留途径,但仅占流入该河段总负荷的2.6%±0.6%。尽管研究持续时间较短(5周)且流量极低,但我们得出结论,该河流减少总氮负荷的能力有限,对下游海洋保护区造成了有害的生态影响。我们的研究结果强调了减少集水区向富含硝酸盐的溪流的氮负荷的管理必要性,这是控制氮输出和恢复天然溪流生态系统去除功效的最有效方法。我们新颖的质量平衡传感器网络方法在量化异质集水区中溶质来源和汇的相对重要性方面是有效的。但是,为了最大化多站点网络的数据价值,我们建议长时间记录测量数据,并与其他采样策略(如示踪剂研究、陆地和生态监测、沉积物芯采样以及纵向剖面分析)同步进行。

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