A Bayesian approach to model the trends and variability in urban stormwater quality associated with catchment and hydrologic parameters

Modeling the effect of land use change to design a suitable low impact development (LID) system to control surface water pollutants

Growth in urbanization has led to increased impervious surfaces, exacerbating flood risks and water quality degradation. This study investigated the impact of land use change and Low-Impact Development (LID) systems on urban runoff quality and quantity in the second region of Tehran. Pioneering an innovative approach, the integration of the Land Change Modeler (LCM) with the Stormwater Management Model (SWMM) signifies a paradigm shift in urban water management. Combined with other hydrological models, this new approach provides a comprehensive method for assessing the future effectiveness of LID practices. The Event Mean Concentration Method (EMC) was used in this study to measure Total Suspended Solids (TSS), Chemical Oxygen Demand (COD), Total Phosphorus (TP), and Zinc (Zn) in urban runoff from five land uses. Results pinpointed transportation land uses as the primary source of pollutants. Using LCM, the study forecasted a surge in urban runoff pollutants by 2030, particularly in the Northwest area of the region due to anticipated land use shifts towards commercial and residential land uses. Model results showed an 11 % increase in TSS over a decade, highlighting the importance of land use change in runoff quality. The study used three types of LIDs to reduce contaminants in dense urban areas. Assessing the impact of LID scenarios on runoff pollutants using SWMM revealed that the bio-retention cell had the best performance, reducing TSS by 20.92 %, and the vegetative swale had the worst performance, reducing TSS by 8.43 %. The study also concluded that combining LIDs would be more effective than using them separately. The results of this study suggest that LID systems can be an effective way to reduce urban runoff pollutants and improve water quality in the second region of Tehran. However, more research is needed to optimize the design and placement of LID systems in different urban areas.

Understanding the role of land use for urban stormwater management in coastal waterways

A holistic understanding of the quality and quantity of stormwater in the context of catchment land use plays a crucial role in stormwater management. This study investigated the quality and quantity of stormwater from forested, residential, industrial, and mixed land use areas. Water samples were collected from seven sites over two years at different stages of the runoff hydrograph using fixed sampling stations. Analysis of physicochemical and hydrological variables showed different patterns across the four land use types at various flow conditions highlighting the complex nature of stormwater quality influenced by catchment and rainfall characteristics. Mean concentrations of dissolved organic and oxidised nitrogen (DON and NOx-N) and dissolved organic and filterable reactive phosphorus (DOP and FRP) in stormwater from industrial, mixed-use and residential catchment types were statistically different from stormwater originating from a forested catchment. On average, residential, mixed-use and industrial catchments transported over 50 times more NOx-N to the receiving waters compared to forested catchments. Under high flow conditions, total phosphorus, FRP and total suspended solids (TSS) were mobilised, indicating that phosphorous export is directly related to sediment export regardless of the land use. The study outcomes contribute to the formulation of more effective stormwater management strategies to deal with the drivers of nutrients and TSS inputs resulting from modified land use types to minimise the urbanisation impacts on aquatic biota. In particular, the elevated dissolved nitrogen fractions from all the catchment types other than the forested catchment is a concern for receiving waters, as these can potentially impair water quality and impact the ecosystem health of downstream water bodies such as Intermittently Closed and Open Lakes or Lagoons (ICOLL). The stochastic nature of hydrology and corresponding nutrient loads should be prioritised in stormwater management action plans. However, as space limitations hinder the expansion of vegetation cover and retrofitting stormwater management devices, a paradigm shift in stormwater management is required to achieve the desired outcomes. The study outcomes further indicate that a one-size-fits-all approach to stormwater management may not deliver the desired outcomes, and a suite of tailor-made approaches targeting various flow conditions and catchment surface types is needed.

What are the relevant sources and factors affecting event mean concentrations (EMCs) of nutrients and sediment in stormwater?

Urbanization increases runoff, sediment, and nutrient loadings downstream, causing flooding, eutrophication, and harmful algal blooms. Stormwater control measures (SCMs) are used to address these concerns and are designed based on inflow loads. Thus, estimating nutrient and sediment loads is important for meeting restoration objectives. Pollutants accumulate on surfaces during dry periods, making Event Mean Concentration (EMC) a function of antecedent dry period (ADP). An EMC results from wash-off of accumulated pollutants from catchment surface during runoff events. However, several studies found little to no correlation between constituent concentrations in stormwater and ADP. The objective of this study is to verify this finding and discover which climatological or catchment characteristics most significantly affect stormwater quality. Stormwater quality data were obtained from the National Stormwater Quality Database (NSQD), which is the largest data repository of stormwater quality data in the U.S. Bayesian Network Structure Learner (BNSL) was used to assess the relationships between catchment characteristics, climatological information, and stormwater quality for selected land uses. Given the optimal BN structure, it was determined which parameters most affect stormwater quality EMCs. The results demonstrate that both catchment and rain characteristics affected stormwater quality EMCs. Among catchment characteristics, land use (LU) was the most important factor and catchment size was the least. Precipitation depth (P) and duration (D) affected Total Phosphorus (TP), Total Nitrogen (TN), and Total Suspended Solids (TSS). This indicated that it is likely that P and D had a greater influence on stormwater quality more than ADP. P, D, and ADP affected the dissolved constituents of TN (i.e. NO₂-N/NO₃-N) and TP (i.e. Ortho-P). Compared to other factors (i.e. P and D), the effect of ADP on TSS was negligible. Stormwater quality EMCs related to nitrogen were not affected by catchment slope (S). However, TSS and Ortho-P were influenced by S.

Study on the Water Quality Characteristics of the Baoan Lake Basin in China under Different Land Use and Landscape Pattern Distributions

Land use and landscape pattern highly affect water quality. Their relationship can assist in land-use management and improve land-use efficiency. In this study, a water quality survey of rivers and lakes was performed in 2020 to analyze the effects of land use and the landscape pattern on the water quality of the rivers and lakes in the Baoan Lake basin and is expected to provide a reference for land use planning. The results demonstrated that the effects of land use on water quality were generally higher during the dry season than during the wet season; however, the opposite was demonstrated for the landscape pattern index. Cropland and urban land were closely correlated with deteriorating water quality, with contributions to total nitrogen, total phosphorous, and ammonia nitrogen in the basin. The impact of the landscape pattern of the basin on water quality was controlled by the original land-use type. In addition, the landscape configuration formed different land-use types to produce different effects on water quality. The basin scale better explained the changes in water quality, especially for construction land, followed by the 250 m and 500 m scales in the buffer zone.

Ranking Three Water Sensitive Urban Design (WSUD) Practices Based on Hydraulic and Water Quality Treatment Performance: Implications for Effective Stormwater Treatment Design

Bioretention basins, constructed wetlands and roadside swales are among the most common Water-Sensitive Urban Design (WSUD) or stormwater quality treatment systems. Although these systems can reduce stormwater quantity and improve quality, their hydraulic and water quality treatment performances are different. The aim of this study was to investigate the hydraulic and water quality performance of a bioretention basin, a constructed wetland and a roadside swale by analyzing monitored water quantity and quality data from a range of rainfall events using a ranking approach. The study outcomes showed that a bioretention basin performed better in relation to peak flow and runoff volume reduction while the constructed wetland tended to produce better outflow water quality. The roadside swale had a relatively lower capacity for treating stormwater. These results suggest that a bioretention basin could be the preferred option when the primary requirement is water quantity improvement. However, if water quality improvement is the primary consideration, a constructed wetland could be more efficient. Additionally, when designing a treatment train, it appears to be preferable to place a bioretention basin prior to a constructed wetland. Further, a swale appears to be more appropriate for use as a pretreatment device. The research study outcomes will contribute to effective stormwater treatment design.

Integrating Tank Model and adsorption/desorption characteristics of filter media to simulate outflow water quantity and quality of a bioretention basin: A case study of biochar-based bioretention basin

Reliable approaches for accurately assessing the performance of stormwater treatment systems is essential for their effective design, including filter media selection which can be a significant constituent in stormwater treatment systems. This study presents an innovative modelling approach integrating the Tank Model with the adsorption-desorption characteristics of the filter media. The resulting modelling approach was applied to simulate a field-scale bioretention basin where biochar was used as filter media with over ten years of rainfall records. The resulting outflow and overflow volumes were compared with observed data for calibration. The Stormwater Treatment Tank Model (STTM) was validated using the Leave-One-Out-Cross-Validation (LOOCV) method. The simulation outcomes include water outflow and overflow (quantity) from the bioretention basin as well as outflow water quality represented by three heavy metals (Pb, Cu, and Zn). The modelling approach developed was found to be capable of accurately simulating outflow and overflow volumes, with outlet water quantity being significantly influenced by the total rainfall depth. The modeling results also suggested that a sole treatment system would not be adequate, particularly for large rainfall events (>100 mm) and a treatment train would be more effective. Simulating long-term (over ten years) pollutant removal performance in the bioretention basin indicated that heavy metals outflow event mean concentration (EMCs) values calculated using simulated results of 30% biochar application rate generated the best pollutant removal with consistent values (2.7 μg/L, 3.0 μg/L, 17.2 μg/L for Pb, Cu, and Zn, respectively). These results confirm that the modelling approach is reliable for assessing long-term treatment performance, as well as a robust tool able to contribute to more effective treatment system design, particularly filter media selection and evaluation.

Water pollution characteristics of inflowing rivers under different land-use patterns in the Daye Lake basin: pollution mode and management suggestions

Land use/land cover (LULC) conditions can have a profound impact on the water quality of rivers, lakes, and other water bodies within a basin. Land use status of Daye Lake basin in 2019 has been shown by Landsat 8 OLI image, water quality of Daye Lake, and 12 inflowing rivers have been investigated once a month; this study provides a comprehensive analysis of the water pollution characteristics of the inflowing rivers and lake in the basin under different LULC patterns, and providing a reference for the scientific planning of land-use types in the basin and land use research in lake basins in subtropical areas. Pollutants are mainly introduced to Daye Lake from the west (such as Da Gang) and north (such as Linjiaju Gang), with concentrations gradually decreasing within the lake from west to east. Construction land is closely associated with the total nitrogen (TN), total phosphorus (TP), permanganate index (COD_Mn), and ammonia nitrogen (NH₃-N) inputs to the basin, which can be trapped by vegetation. Agricultural dryland can contribute acid and dissolved oxygen (DO) to water. Precipitation can influence the input of pollutants, with a stronger effect on TN and weaker effect on TP. Pollutants accumulate from the inlets to the centre of the lake, with longer retention times during the dry season.