Water Quality Of Urban Stream Research Articles

Spatiotemporal Dynamics of Carbon and Nitrogen in Subtropical Urban Streams (Santo André, SP, Brazil)

Urban sprawl poses a significant threat to urban stream water quality due to impermeabilization, reduced vegetation cover, and the release of diffuse pollutants. This study evaluates water quality in seven catchments in Santo André, SP, considering seasonality. Nutrient concentrations and in situ measurements were taken during both dry and rainy seasons. Comparisons were made using Kruskal–Wallis and Mann–Whitney tests. Streams showed significant differences in relation to water quality parameters. The Carapetuba, Jundiaí, and Apiaí streams were most adversely affected, underscoring the need for urgent water quality intervention (water conductivity above 500 μS/cm, dissolved oxygen below 2 mg/L, total dissolved carbon above 50 mg/L, and total dissolved nitrogen above 25 mg/L). Significant differences were observed across seasons. The dry season showed elevated temperatures (above 25 °C) and increased total dissolved carbon (above 50 mg/L) and nitrogen concentrations (above 30 mg/L), indicating reduced dilution effects from rainfall and heightened organic contamination. Conversely, the wet season demonstrated lower nutrient concentrations, emphasizing seasonal dynamics. Sustained, long-term monitoring of urban streams in Santo André and the implementation of sewage collection and treatment in irregular settlements are recommended. These measures are essential to mitigate the adverse impacts of urban expansion on water quality.

Assessing impacts of cemeteries on water quality in an urban headwater watershed with mixed human‐built infrastructure

AbstractCemeteries are understudied integral components to urban watersheds, which provide ecosystem services but can also export nutrients, trace elements, and other contaminants to nearby water bodies. In this study, we focus on Meadowbrook Creek, an urban headwater stream in Syracuse, New York (USA), which has shown significant nitrate contributions from a local cemetery. We collected biweekly surface water samples over the course of 1 year from 2022 to 2023 for analysis of major and trace elemental concentrations including Na, Ca, Mg, K, F, Cl, sulfate, and nitrate. Here, we aim to assess the impact of various human infrastructures on urban stream water quality with a particular focus on the cemetery and nitrate. A comparison between the new dataset in this study and previously reported water chemistry data in Meadowbrook in 2012 suggests a decade‐long impact of road salting and the cemetery on water quality particularly with respect to Na, Cl, and nitrate. Sulfate, Mg, Ca, and K are likely mainly geogenic. Stable nitrogen isotope data, the usage of concrete or steel vaults in the cemetery in the past 50 years, and the lack of correlation between nitrate and fluoride concentrations in stream water argue against burial decay products being a major source of nitrate to the stream. Instead, other nitrate sources that exist in the cemetery such as, fertilizer, decaying plant material, and wastewater, are more viable dominant nitrate sources. In addition, nitrate loading calculations indicate that the groundwater‐connected reach, including the cemetery, acts as an annual net sink for nitrate despite the seasonally varying sink‐source patterns.

Effects of urbanization and accessibility to sanitation services on water quality in urban streams in Uruguay.

The world's urban population is growing rapidly, and threatening natural ecosystems, especially streams. Urbanization leads to stream alterations, increased peak flow frequencies, and reduced water quality due to pollutants, morphological changes, and biodiversity loss, known as the urban stream syndrome. However, a shift towards recognizing urban streams as valuable natural systems is occurring, emphasizing green infrastructure and nature-based solutions. This study in Uruguay examined water quality in various watersheds with different urbanization levels and socio-environmental characteristics along a precipitation gradient. Using Geographic Information Systems (GIS) and in situ data, we assessed physicochemical parameters, generated territorial variables, and identified key predictors of water quality. We found that urbanization, particularly urban areas, paved areas, and populations without sanitation, significantly influenced water quality parameters. These factors explained over 50% of the variation in water quality indicators. However, the relationship between urbanization and water quality was non-linear, with abrupt declines after specific urban intensity thresholds. Our results illustrate that ensuring sanitation networks and managing green areas effectively are essential for preserving urban stream water quality. This research underscores the importance of interdisciplinary teams and localized data for informed freshwater resource management.

Graph-Based Deep Learning Model for Forecasting Chloride Concentration in Urban Streams to Protect Salt-Vulnerable Areas

In cold-climate regions, road salt is used as a deicer for winter road maintenance. The applied road salt melts ice and snow on roads and can be washed off through storm sewer systems into nearby urban streams, harming the freshwater ecosystem. Therefore, aiming to develop a precise and accurate model to determine future chloride concentration in the Credit River in Ontario, Canada, the present work makes use of a “Graph Neural Network”–“Sample and Aggregate” (GNN-SAGE). The proposed GNN-SAGE is compared to other models, including a Deep Neural Network-based transformer (DNN-Transformer) and a benchmarking persistence model for a 6 h forecasting horizon. The proposed GNN-SAGE surpassed both the benchmarking persistence model and the DNN-Transformer model, achieving RMSE and R2 values of 51.16 ppb and 0.88, respectively. Additionally, a SHAP analysis provides insight into the variables that influence the model’s forecasting, showing the impact of the spatiotemporal neighboring data from the network and the seasonality variables on the model’s result. The GNN-SAGE model shows potential for use in the real-time forecasting of water quality in urban streams, aiding in the development of regulatory policies to protect vulnerable freshwater ecosystems in urban areas.

Stream Water Quality Control and Odor Reduction through a Multistage Vortex Aerator: A Novel In Situ Remediation Technology

In this work, we report the restoration of a polluted urban stream by employing the multistage vortex aerator (MVA), an in-line mixer device that improves the dissolved oxygen concentration of polluted streams and accelerates the water purification rate. It was observed during the field experiment that the dissolved oxygen was enhanced up to 7.05 mg/L and the water quality was improved to a good grade. As a result, the complex odor was successfully eliminated and reduced by up to 71.9%, while the water quality grade was also improved by more than two grades on average. Stream water quality indicators monitored for twelve months revealed high removal rates of total phosphorous (56.4%) and suspended solids (61%). The study demonstrated MVA as a promising eco-friendly technology for significant improvement in urban stream water quality. Moreover, the MVA process creates no secondary pollution and is believed to be a sustainable treatment option for odorous water bodies. Overall, the MVA process is technically feasible for implementation, and this study provides a specific reference as a basis for the treatment of polluted water bodies in urban settings.

Effects of Antecedent Precipitation Amount and COVID-19 Lockdown on Water Quality along an Urban Gradient

Water quality is affected by multiple spatial and temporal factors, including the surrounding land characteristics, human activities, and antecedent precipitation amounts. However, identifying the relationships between water quality and spatially and temporally varying environmental variables with a machine learning technique in a heterogeneous urban landscape has been understudied. We explore how seasonal and variable precipitation amounts and other small-scale landscape variables affect E. coli, total suspended solids (TSS), nitrogen-nitrate, orthophosphate, lead, and zinc concentrations in Portland, Oregon, USA. Mann–Whitney tests were used to detect differences in water quality between seasons and COVID-19 periods. Spearman’s rank correlation analysis was used to identify the relationship between water quality and explanatory variables. A Random Forest (RF) model was used to predict water quality using antecedent precipitation amounts and landscape variables as inputs. The performance of RF was compared with that of ordinary least squares (OLS). Mann–Whitney tests identified statistically significant differences in all pollutant concentrations (except TSS) between the wet and dry seasons. Nitrate was the only pollutant to display statistically significant reductions in median concentrations (from 1.5 mg/L to 1.04 mg/L) during the COVID-19 lockdown period, likely associated with reduced traffic volumes. Spearman’s correlation analysis identified the highest correlation coefficients between one-day precipitation amounts and E. coli, lead, zinc, and TSS concentrations. Road length is positively associated with E. coli and zinc. The Random Forest (RF) model best predicts orthophosphate concentrations (R2 = 0.58), followed by TSS (R2 = 0.54) and nitrate (R2 = 0.46). E. coli was the most difficult to model and had the highest RMSE, MAE, and MAPE values. Overall, the Random Forest model outperformed OLS, as evaluated by RMSE, MAE, MAPE, and R2. The Random Forest was an effective approach to modeling pollutant concentrations using both categorical seasonal and COVID data along with continuous rain and landscape variables to predict water quality in urban streams. Implementing optimization techniques can further improve the model’s performance and allow researchers to use a machine learning approach for water quality modeling.

Development of water quality index as a tool for urban water resources management.

Urban stream monitoring programs rarely consider the daily cycle of water quality. Furthermore, water quality indexes (WQIs) often rely on an excessive number of correlated parameters. To the best of our knowledge, no previous study used both the principal component analysis (PCA) and the daily cycle of the water quality of urban streams to create better WQIs. In this context, the present study aimed to develop a novel urban WQI (WQIurban) considering these two factors. Moreover, the main WQI in Brazil for water quality assessment for public supply (WQIcetesb) was used as a starting point (parameters: total solids (TS), temperature, turbidity, biochemical oxygen demand, pH, dissolved oxygen (DO), total nitrogen, total phosphorus, and thermotolerant coliforms (Escherichia coli)). The selected parameters to integrate the WQIurban received weights according to their importance for the conformation of water quality and a quality value was assigned to each parameter as a function of its concentration or measure. The developed WQIurban (parameters: pH, TS, E. coli, and DO) was able to maintain the seasonal and daily patterns of the urban stream water quality compared to the WQIcetesb. Nevertheless, the spatial relationship among the sampling sites was somewhat lacking. Our findings can help environmental managers, policy planners, and local researchers to improve their urban stream monitoring programs, saving money, time, and resources. Moreover, the WQIurban can be helpful during exceptional circumstances in which the water quality of urban streams must be quickly assessed.

Prediction of water quality based on SVR by fluorescence excitation-emission matrix and UV–Vis absorption spectrum

As a result of economic development, the pollution of freshwater resources in urban areas of China is becoming more and more serious. Therefore, it is urgent and necessary to develop a real-time monitoring method for the water quality of urban streams and rivers. In this study, a novel method (CFFA) Combined by peak-picking method, Fluorescence spectral indexes, Fluorescence regional integration, and Absorption spectral indexes were designed to extract wide-ranging information from the combination of the excitation-emission matrix (EEM) and absorption spectrum (Abs) of water samples. More than 600 freshwater samples were collected at 180 sections of 60 rivers in the Yangzhou urban region from April 2018 and May 2019. The CFFA inputs form was applied to establish the prediction models of water quality indexes (CODCr, CODMn, NH3-N, TP, TN, and BOD5) based on ε-Support Vector Regression (ε-SVR). To examine the performance of the prediction models, contrastive analysis among CFFA and the other three input models was carried out. Results show that CFFA input models have shorter modeling time, lower RMSE and MAPE, and higher R2 in both training and testing sets, and each constituent part of CFFA is important to the precise prediction on the basis of the ablating analysis. Our study highlights that SVR models with the CFFA input trained by numerous and various water samples could effectively predict multiple indexes for real-time water quality monitoring.

Anthropogenic impacts on isotopic and geochemical characteristics of urban streams: a case study in Wuhan, China.

Urbanization and human activities have significantly modified the geochemical signatures of urban streams worldwide. However, the geochemical characteristics of urban streams in Wuhan, one of the core cities in the Yangtze River Economic Belt in China, remain largely unstudied. Here, we examined the stable isotopes and geochemistry of urban streams at 73 locations in the central districts in Wuhan during May 2019. Maps of isotopic signatures reflected a non-free-flowing state in part of the urban stream system in Wuhan. A lower DO and a higher EC level were found in urban streams relative to the adjacent Yangtze River. The Na+, K+, and Cl- concentrations in urban streams were > 3.0 times as high as those in the Yangtze River, and there was a slight increasing trend between 1.1 and 1.4 times for other major ions. The mildly elevated Fe concentration (1.3 times) and markedly elevated Mn concentration (> 5.0 times) were observed in urban streams. Spearman's correlation analysis indicated strong positive bivariate correlations among Na+, K+, and Cl- in urban streams, and an urban geochemical principal component was identified by principal component analysis. Plotting Na/(Na + Ca) versus total dissolved solids (TDS) indicated a potential risk of "urban stream syndrome." These findings can enhance the knowledge of anthropogenic impacts on current urban stream water quality and provide reference for the restoration and improvement of water ecology functions of the urban stream system in Wuhan.

Analysis of physicochemical water quality parameters for streams under agricultural, urban and forest land-use types: in the case of gilgel Gibe catchment, Southwest Ethiopia

Streams draining to Gilgel Gibe catchment cross agricultural and urban land uses receiving a different pollutant that challenges water quality. A total of 21 sampling sites were selected from seven streams of agricultural (n = 3), urban (n = 3) and forest (n = 1) land-use types. Composite samples were collected from upstream, middle and downstream of all land-use types. Twenty-three physicochemical parameters were measured from each sampling site. Temperature, DO, pH, EC, turbidity, width, depth, current velocity and discharge were measured onsite. Two milliliters of unfiltered water samples was collected from every site for laboratory analysis. Mean of NO3-N was highest in agricultural streams than forested and urban streams. In contrast, mean of SRP, NH4-N and COD and BOD5 concentration was greater in urban streams followed by agricultural streams, whereas forest streams are lowest. Concentrations of nutrients, EC and turbidity were recorded in increasing manner across land-use gradient from forested to agricultural and urban streams. The analysis of one-way ANOVA showed that all physicochemical parameters were significantly different among all sites with different land-use types (P < 0.05), except for water temperature (one-way ANOVA: F = 0.987, P = 0.494). NMDS and cluster analyses have discriminated the sites into three groups of land-use types. Then, we conclude that water quality of urban stream is highly impaired than agricultural streams, whereas forested streams have better water quality. Therefore, stream restoration projects, reforestation, conservation of riparian vegetation appropriate waste disposal need to be encouraged in the study area for sustainable management of freshwater resources.

Water quality evaluation of two urban streams in Northwest Uruguay: are national regulations for urban stream quality sufficient?

Poor water quality in urban streams places at risk the health of urban residents and the integrity of urban environments, ultimately leading to the "urban stream syndrome." In response to growing concerns regarding urban streams in Uruguay, we evaluated the spatiotemporal variation in water quality parameters in two urban streams, the Ceibal and La Curtiembre streams, over 12-18months. A proposal for an Urban Water Quality Index (UWQI) was developed based on national water quality standards for two stream classes to assess variability in overall stream condition over time. Both streams displayed extremely high levels of fecal coliform concentrations in mid-downstream sites and relatively high levels of total dissolved phosphorus and ammonia well above the national standards of 0.025mg/L and 0.02mg/L, respectively. Nitrate was consistently below the national maximum of 44.3mg/L, calling to question the adequacy of this standard for designated uses. Over 40% of samples had oxygen levels below the national standard of 5mg/L, and a dead zone (average 1.5mg/L) was detected in the downstream reach of the La Curtiembre stream. Despite differences in land use and urban context, monthly observations of nutrients and coliforms indicated high levels of contamination in mid-downstream reaches, which could present a health risk for the populations in Paysandú and Salto. This study highlights the degradation of urban streams in two major cities in Uruguay and the need for a comparative diagnosis of stream condition as a basis for decision-making regarding urban development and water resources.

Considerations on the monitoring of water quality in urban streams: a case study in Portugal

Monitoring water quality in urban stream is of utmost importance for water resources managers, who are pressured to optimize monitoring schemes in order to reduce costs. The present study aims to use the results of a 2-year-long water quality monitoring program of an urban stream in Portugal to identify improvement opportunities. The urban stream under study was subjected to wastewater treatment plants effluent discharges, leachates from a major sealed landfill, low-class housing effluents, and nonpoint sources of pollution. Contributing watersheds are mostly artificial surfaces and agricultural land, which irrigate directly from the river. River water quality was evaluated on 11 sampling locations for 24months from October 2013 to September 2015. The present paper describes statistical analysis of the results obtained for 12 physicochemical parameters in order to optimize the monitoring scheme. Cluster analysis detected a seasonal variation in the water quality and a spatial pattern based on the major point sources of pollution. A factor analysis showed that the parameters that mostly contribute to water quality assessment in this urban river are alkalinity, ammonia, electrical conductivity, pH, temperature, and dissolved oxygen. Results suggest that the monitoring efforts-and associated costs-may be reduced by decreasing monitoring frequency, sampling points, and monitored parameters. The statistical analysis described in this study may be replicated in other water quality monitoring programs, providing useful and important information for the systematic and iterative assessment of the adequacy of water quality sampling programs towards a sustainable management of water quality surveillance.

Impact of Combined Sewer Systems on the Quality of Urban Streams: Frequency and Duration of Elevated Micropollutant Concentrations

Water quality in urban streams is highly influenced by emissions from WWTP and from sewer systems particularly by overflows from combined systems. During storm events, this causes random fluctuations in discharge and pollutant concentrations over a wide range. The aim of this study is an appraisal of the environmental impact of micropollutant loads emitted from combined sewer systems. For this purpose, high-resolution time series of river concentrations were generated by combining a detailed calibrated model of a sewer system with measured discharge of a small natural river to a virtual urban catchment. This river base flow represents the remains of the natural hydrological system in the urban catchment. River concentrations downstream of the outlets are simulated based on mixing ratios of base flow, WWTP effluent, and CSO discharge. The results show that the standard method of time proportional sampling of rivers does not capture the risk of critical stress on aquatic organisms. The ratio between average and peak concentrations and the duration of elevated concentrations strongly depends on the source and the properties of the particular substance. The design of sampling campaigns and evaluation of data should consider these characteristics and account for their effects.

Understanding spatiotemporal variability of in-stream water quality in urban environments – A case study of Melbourne, Australia

To support sustainable urban planning and the design of water pollution mitigation strategies, the spatial and temporal trends of water quality in urban streams needs to be further understood. This study analyses over ten years of surface water quality data from 53 upstream catchments (20 of them predominated by a single type of land use) and two lowland sites across Greater Melbourne, Australia. We evaluated the impact of various catchment characteristics, especially urban land uses, on spatial and temporal urban water quality trends. Here, we focused on common urban pollutants: total suspended solids (TSS), total phosphorous (TP), total nitrogen (TN), zinc (Zn), copper (Cu) and nickel (Ni). Site median nutrient and heavy metal concentrations were negatively correlated with the catchment's elevation and its average annual rainfall. Further analysis shows that such trends were driven by the geographical pattern of Melbourne – i.e. low-laying sites tend to have less rainfall and be more urbanised. Only median concentrations of heavy metals (Zn and Cu) were correlated to catchment imperviousness. Further characterising of the urban environment was done into specific land uses (residential, industrial and commercial), yet median concentrations of all pollutants were not significantly correlated with land uses. This is because simple metrics, such as land use proportions, do not adequately reflect the significant variability in pollution sources that can exist even within the same land use type. Indeed, our temporal analysis found that the water quality difference between catchments with similar land uses is likely caused by their site-specific pollutant sources (construction and illegal discharge) and environmental management actions (wastewater management actions) regardless of similarities in land use. A 3-stage urbanisation cycle (development, operation and renewal) is suggested to further explain the urban water quality variance, but more data from small areas of an urban catchment is required to directly understand the unique impact of each urbanisation stage on water quality.

High spatial resolution landscape indicators show promise in explaining water quality in urban streams

Urban streams are subject to a myriad of complex stressors associated with impervious surfaces, which impact delivery of pollutants. Landscape indicators (e.g. the amount and arrangement of land cover) are widely used to help monitor water quality, yet their application in highly urbanized settings remains poorly understood. Here, we explored the utility of landscape indicators for explaining water chemistry and bacterial concentrations in streams throughout the Greater Vancouver Regional District, British Columbia, Canada. First, we compared high and moderate spatial resolution imagery to evaluate their relative efficacy in characterizing impervious surfaces. Second, we linked a suite of landscape indicators to major chemical properties and pollutants (e.g. dissolved oxygen, nitrate, turbidity, fecal coliform, E. Coli.) using a series of comparative statistical models. Land cover at 30-m resolution often over-estimated the proportional area of impervious surface by 0.10–0.30, sometimes doubling the amount detected using finer resolution imagery. Finer 5- and 2-m resolution imagery demonstrated little difference in estimating impervious cover. Therefore, 5-m resolution imagery was adopted for spatial analysis in the study region. Watershed-level landscape indicators explained nearly 50% of the variability in wet season concentrations of dissolved oxygen and fecal coliform. When considering the spatial configuration of impervious areas, edge density within the riparian zone explained more than 30% of the variability in fecal coliform and E. Coli. Our approach is potentially transferable to many cities worldwide facing similar challenges in monitoring urban streams.

Quantifying the Relative Contributions of Environmental Sources to the Microbial Community in an Urban Stream under Dry and Wet Weather Conditions

Investigating sources of microbial contamination in urban streams, especially when there are no contributions from combined sewer overflows or sewage effluent discharges, can be challenging. The objectives of this study were to identify the sources of microbes in an urban stream and quantify their relative contributions to the microbial community in the stream under dry and wet weather conditions. A microbial source tracking method relying on the 16S rRNA gene was used to investigate the microbial communities in water samples of an urban stream (i.e., from 11 dry and 6 wet weather events), as well as in streambed sediment, soils, street sweepings, sanitary sewage, an upstream lake, and feces of animals and birds collected between 2013 and 2015. The results showed that the Escherichia coli levels in the stream were significantly higher in wet weather flow than in dry weather flow. The upstream lake contributed approximately 93% of the microbes in dry weather flows. Water discharged from storm drain outfalls was the biggest source of microbes in wet weather flows, with a median contribution of approximately 90% in the rising limb and peak flow and about 75% in the declining limb of storms. Furthermore, about 70 to 75% of the microbes in the storm drain outfall water came from materials washed off from the street surfaces in the watershed. Fecal samples did not appear to contribute substantially to the microbes in environmental samples. The results highlight the significance of street surfaces in contributing microbial loads to urban streams under wet weather conditions.IMPORTANCE Identifying the sources of microbial contamination is important for developing best management practices to protect the water quality of urban streams for recreational uses. This study collected a large number of water samples from an urban stream under both dry and wet weather conditions and provided quantitative information on the relative contributions of various environmental compartments to the overall microbial contamination in the stream under the two weather conditions. The watershed in this study represents urban watersheds where no dominant fecal sources are consistently present. The findings highlight the importance of reducing the direct contribution of microbes from street surfaces in the watershed to urban streams under wet weather conditions. The methods and findings from this study are expected to be useful to stormwater managers and regulatory agencies.

Are Odonata nymph adversely affected by impaired water quality in urban streams

AbstractGlobally 10% of all dragonfly species are threatened by extinction that can be primarily attributed to a loss of natural habitat. Urban expansion and the associated urban stream syndrome has established that the extent and intensity of urban development is directly linked to a range of adverse physical, chemical and ecological changes. Urban waterways typically experience degraded water quality and are occupied by impaired communities of aquatic invertebrates which are mostly dominated by rapid colonizing insects. Odonata are a diverse insect group and their tolerance or sensitivity to urban waterway degradation is unclear. This research examined the response of aquatic macroinvertebrate communities and specifically the Odonata nymph community to impaired water quality and degraded riparian vegetation condition in streams of the Georges River catchment, Sydney, across an urban development gradient. Unlike the overall macroinvertebrate community, Odonata nymph species assemblages were not strongly linked to the urban development gradient nor the degree of degradation in water quality. This result diverges from many aquatic macroinvertebrate studies that have reported a correlation between the response of Odonata taxa to degraded water quality. Our findings conclude that Odonata nymph community alone are not a suitable indictor of urban stream degradation as measured by water quality or catchment imperviousness and that the conservation of urban dragonflies should place a greater focus on the conservation and creation of suitable habitats.

Engineered headwaters can act as sources of dissolved organic matter and nitrogen to urban stream networks

AbstractImproved management of urban stream water quality requires identification of sources contributing excess nutrients and organic matter. While soils and lawns are potential nonpoint sources characterized by large pools of carbon (C) and nitrogen (N), their hydrologic connectivity to streams is often low relative to impervious surfaces. In contrast, engineered headwaters (gutters and pipes) retain smaller pools of C and N, but efficiently process litter into dissolved organic matter and are highly connected to streams during storms. We found that engineered headwaters have the potential to provide more than enough dissolved C and N to account for streamflow fluxes during storms. This finding suggests that engineered headwaters can act not only as stormwater conveyances, but as important proximate sources of dissolved carbon and nutrients to streams during storms. A nested mass balance approach like the one used here can further understanding of the contributions of previously overlooked subsystems, such as engineered headwaters, to biogeochemistry and element flux in urban catchments.

An urban observatory for quantifying phosphorus and suspended solid loads in combined natural and stormwater conveyances

Water quality in urban streams and stormwater systems is highly dynamic, both spatially and temporally, and can change drastically during storm events. Infrequent grab samples commonly collected for estimating pollutant loadings are insufficient to characterize water quality in many urban water systems. In situ water quality measurements are being used as surrogates for continuous pollutant load estimates; however, relatively few studies have tested the validity of surrogate indicators in urban stormwater conveyances. In this paper, we describe an observatory aimed at demonstrating the infrastructure required for surrogate monitoring in urban water systems and for capturing the dynamic behavior of stormwater-driven pollutant loads. We describe the instrumentation of multiple, autonomous water quality and quantity monitoring sites within an urban observatory. We also describe smart and adaptive sampling procedures implemented to improve data collection for developing surrogate relationships and for capturing the temporal and spatial variability of pollutant loading events in urban watersheds. Results show that the observatory is able to capture short-duration storm events within multiple catchments and, through inter-site communication, sampling efforts can be synchronized across multiple monitoring sites.

Spatial modelling of stream water quality along an urban–rural gradient

It is widely known that intensive land use generally decreases stream water quality, but the influence of watershed physiography is relatively poorly understood. Since management planning has to take into account the protection of water quality, the current status of stream water must be identified. The potential effects of land use and watershed physiography variables on water quality were studied in an extensive set of 83 watersheds in the Helsinki region, Finland, covering wide land‐use intensity gradient. The aims of this study were to test if the geographical information of watershed land‐use data can be used to model the stream water quality, and to examine whether the spatial water quality models are improved after including predictors of watershed physiography to the land‐use model. Water quality variables were related to watershed predictors by utilizing generalized additive models and linear mixed models, and the independent effect of the variables was investigated using a hierarchical partitioning approach. While land use turned out to be the most influential factor explaining water quality, all models improved significantly after incorporating the watershed characteristics, such as topography and soil. These results were consistent across three modelling techniques. This study, with its novel approach to examine the impacts of several watershed physiographic characteristics on urban stream water quality in northern Europe, demonstrates that spatial land use and watershed physiography data can be used as cost‐efficient predictors in stream water quality models.