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Watershed-Based Evaluation of Automatic Sensor Data: Water Quality and Hydroclimatic Relationships
Stockholm University, Faculty of Science, Department of Physical Geography.ORCID iD: 0000-0002-7611-5758
Stockholm University, Faculty of Science, Department of Physical Geography.ORCID iD: 0000-0002-7978-0040
Stockholm University, Faculty of Science, Department of Physical Geography.ORCID iD: 0000-0001-9408-4425
Number of Authors: 32020 (English)In: Sustainability, E-ISSN 2071-1050, Vol. 12, no 1, article id 396Article in journal (Refereed) Published
Abstract [en]

Water is a fundamental resource and, as such, the object of multiple environmental policies requiring systematic monitoring of its quality as a main management component. Automatic sensors, allowing for continuous monitoring of various water quality variables at high temporal resolution, offer new opportunities for enhancement of essential water quality data. This study investigates the potential of sensor-measured data to improve understanding and management of water quality at watershed level. Self-organizing data maps, non-linear canonical correlation analysis, and linear regressions are used to assess the relationships between multiple water quality and hydroclimatic variables for the case study of Lake Malaren in Sweden, and its total catchment and various watersheds. The results indicate water discharge from dominant watersheds into a lake, and lake water temperature as possible proxies for some key water quality variables in the lake, such as blue-green algae; the latter is, in turn, identified as a potential good proxy for lake concentration of total nitrogen. The relationships between water discharges into the lake and lake water quality dynamics identify the dominant contributing watersheds for different water quality variables. Seasonality also plays an important role in determining some possible proxy relationships and their usefulness for different parts of the year.

Place, publisher, year, edition, pages
2020. Vol. 12, no 1, article id 396
Keywords [en]
water quality, water discharge, hydroclimate, data mining, automatic sensor, monitoring, watershed, lake Malaren, Stockholm region, Green & Sustainable Science & Technology
National Category
Earth and Related Environmental Sciences
Identifiers
URN: urn:nbn:se:su:diva-181388DOI: 10.3390/su12010396ISI: 000521955600396OAI: oai:DiVA.org:su-181388DiVA, id: diva2:1428760
Available from: 2020-05-06 Created: 2020-05-06 Last updated: 2025-02-07Bibliographically approved
In thesis
1. Active and legacy source contributions to observed water quality: A data-driven approach to their distinction across spatiotemporal scales
Open this publication in new window or tab >>Active and legacy source contributions to observed water quality: A data-driven approach to their distinction across spatiotemporal scales
2024 (English)Doctoral thesis, comprehensive summary (Other academic)
Abstract [en]

Water is a fundamental resource for human society and natural ecosystems.  Ensuring good water quality in the natural waters that provide water for drinking and other uses around the world is of forefront importance for management of this resource. Even after implementing substantial management strategies and measures for mitigating water pollution, water quality still remains too deteriorated in many freshwater and coastal water environments. A possible reason for this lack of quality improvements may be the formation of legacy sources, due to various physical and biogeochemical processes that delay (up to several decades or more) the waterborne pollutant propagation through hydrological catchments and the effects of efforts to mitigate this propagation. The resulting legacy source contributions of pollutants after such delaying processes contrast to the contributions of active sources, characterized by considerably shorter times (of around a year) of waterborne pollutant transport and associated propagation of mitigation effects through catchments.

This thesis aims at quantitative differentiation of the contributions of active and legacy pollutant sources to currently measured stream water quality. The research uses different types of data for various spatial and temporal scales, to explore variations and their dependence on monitoring resolution both in space and time. To this end, the thesis considers different types of pollutants, including nutrients, metals, dissolved carbon, and chloride, as well as common water quality variables measured by automatic sensors.

The theoretical framework used in this thesis hypothesizes, on mechanistic grounds, a significant linear relationship between pollutant loads and water discharges, which is here tested against data. Based on the support that data provide for the hypothesis, the obtained linear relationships are further used to quantify and differentiate between active and legacy source contributions to observed water quality conditions.  A main result from this work is significant indication that today’s measured water quality is strongly influenced by pollution history, with legacy source contributions dominating current concentration and load levels for all investigated pollutants in different catchments, of various scales, around Sweden and the world. This result can explain why recent water quality improvement efforts have been relatively unsuccessful in improving water quality in natural water environments of various countries around the world, as such efforts so far have mainly considered and targeted active sources. Furthermore, the thesis has quantified important relationships between legacy nutrient contributions and agricultural land, with widely consistent relationship parameters for nitrogen and more location-specific ones for phosphorous. For shorter-term water quality monitoring with fine (sub-daily) time resolution, the thesis shows that and why legacy source contributions are most influential under high flow conditions, while the active contributions are increasingly important for lower flows, which in turn drives distinct seasonal variation patterns in the water quality dynamics.

The methodological and result contributions of this thesis provide valuable tools and insights for distinction and quantification of legacy and active source contributions to water quality in natural water environments. The contributions apply across various scales, and for different pollutants and water quality variables, as basis for improved and more efficient water quality management.

Place, publisher, year, edition, pages
Stockholm: Department of Physical Geography, Stockholm University, 2024. p. 45
Series
Dissertations in Physical Geography, ISSN 2003-2358 ; 39
Keywords
legacy sources, active sources, hydrology, water quality, groundwater, streams, data-driven, pollutants, source attribution
National Category
Oceanography, Hydrology and Water Resources
Research subject
Physical Geography
Identifiers
urn:nbn:se:su:diva-232843 (URN)978-91-8014-919-8 (ISBN)978-91-8014-920-4 (ISBN)
Public defence
2024-10-18, Högbomsalen, Geovetenskapens hus, Svante Arrhenius väg 12, and via Zoom: https://stockholmuniversity.zoom.us/j/66185088490, Stockholm, 13:00 (English)
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Supervisors
Available from: 2024-09-25 Created: 2024-08-29 Last updated: 2024-09-13Bibliographically approved

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Cantoni, JacopoKalantari, ZahraDestouni, Georgia

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