Antecedent Dry Period Research Articles

Fingerprinting to trace sources of suspended solids in the transport of heavy metals in urban stormwater runoff

Suspended solids are an important pollutant in urban stormwater runoff. Past studies have mainly focused on a single transport stage of pollutants, constraining source identification of suspended solids at the catchment scale. Therefore, identifying the sources of suspended solids in stormwater runoff for the formulation of effective pollution mitigation measures is an effective way to manage suspended solids pollution in receiving waters. Sediment source fingerprinting is a widely used technique to trace the sources of river sediments, which can accurately identify the source of sediment through widely used tracers. This study used six heavy metals including Cd, Cr, Ni, Cu, Zn and Pb as tracers to quantify the sources of suspended solids in stormwater runoff from urban catchments. The spatial and temporal distribution characteristics of suspended solids during stormwater transport were investigated. The study results showed that the concentration of suspended solids was the highest in road runoff and sewer flow, especially particles <44 μm. In addition, relatively large rainfall depth, high rainfall intensity and long antecedent dry periods can lead to higher concentrations of suspended solids in roof and road runoff whereas longer rainfall duration can result in more suspended solids in sewer runoff. Sediment source fingerprinting and principal component analysis confirmed that coarse (>105 μm) particles primarily originate from road deposited sediments (63.80%), while fine (<105 μm) particles primarily originate from stormwater grate sediments and soil. The outcomes derived can help to comprehensively understand the sources of suspended solids and provide guidance for the management of urban stormwater particulate pollution, as well as being a technical reference for pollutant source traceability in urban stormwater runoff.

Potentially hazardous elements in atmospheric precipitation during the warm season (May–September) of 2019 in Moscow

Atmospheric precipitation acts as a significant pathway for pollutants from the atmosphere to the Earth’s surface, and analyzing urban precipitation data on intensity, fallout regime, transfer patterns, and solid particle content helps identify pollution sources. For the first time in the Moscow megacity, the levels of soluble forms of potentially hazardous elements (PHEs) in atmospheric precipitation were studied during the whole summer season of May–September 2019. The concentrations of Al, As, B, Ba, Be, Bi, Cd, Ce, Co, Cu, Fe, La, Li, Mn, Ni, P, Pb, Rb, Sb, Sn, Sr, and Zn were determined using inductively coupled plasma mass spectrometry and atomic emission spectroscopy methods. The research underscores the crucial role of atmospheric precipitation in washing PHEs out of the atmosphere. In May and September, concentrations of PHEs surpass the warm-season average. Notable contamination in May stems from elevated traffic during vacations, extensive burning of plant debris and wood, and pollen transport. Summer months are characterized by reduced forest and agricultural fires, traffic, and increased vegetation, leading to lower PHE concentrations, especially in July, with typical amount of precipitation contributing to pollutant dispersion. Elevated PHE levels in September are observed due to increased traffic load, biomass burning, and the expansion of unvegetated soil areas. Rainwater is enriched with Sb, Pb, Cd, Zn, Cu, B, Bi, P, and Sr, sourced from vehicle emissions, soil particles, industry, construction dust, biomass burning, and forest fires. Moderate enrichment with Ba, Mn, Ni, Co, and Sn also occurs episodically. Regression analysis highlights solid particles’ role as a major PHE source in rainwater, with the longer antecedent dry periods and the higher acidity level of rain intensifying the accumulation of PHEs. Long-range transport plays a lesser role, with Southern and Northern Europe, Western Siberia, and the central part of European Russia contributing meaningfully.

Modeling the influences of rainfall conditions on nitrogen removal effects of a permeable pavement system

Permeable pavement systems are important facilities for alleviating runoff pollution. However, few studies have focused on outflow nitrogen processes under varying rainfall conditions. In this study, we proposed a permeable pavement system model that can simulate the nitrogen transformation processes. The model was verified with data on outflow rates and outflow nitrogen concentrations (ammonia nitrogen (NH4-N), nitrate nitrogen (NO3-N), and total nitrogen (TN)) processes for six consecutive rainfall events of a permeable pavement system in Shenzhen, China. Based on the validated model, scenarios were designed to simulate the influences of rainfall conditions on nitrogen removal effects at the single rainfall event and annual scale, respectively. The results indicate that: (i) the model can explicitly describe hydrological and nitrogen processes of the system, and the Nash Sutcliffe Efficiency and percent bias of outflow rates and outflow nitrogen concentrations range from 0.5 to 0.9 and from −22.4% to 24.9%, respectively; (ii) the sensitivity analysis reveals that the empirical coefficient (C) related to evaporation in the gravel layer is sensitive at the annual scale but not at rainfall events scale. Parameters related to mineralization and microbial assimilation (i.e., mineralization rate constant in the gravel layer (k3N,mine), microbial assimilation rate constant of NH4-N, NO3-N, and ON (k1N,bio, k2N,bio, k3N,bio)) are sensitive annually but not at rainfall events scale; (iii) in the single rainfall event simulations, nitrogen removal efficiencies decrease with increasing rainfall return periods but is not significantly affected by rainfall peak coefficients. Nitrogen removal efficiencies improve notably with antecedent dry period extension for single rainfall event with antecedent dry period less than 2 days. In addition, we found that the outflow process significantly affects the outflow nitrogen concentrations process. In annual-scale simulations, extending the antecedent dry period only significantly boosts runoff reduction efficiency and nitrogen removal efficiencies for rainfall events with less than 10 mm.

Particle size distribution of total suspended sediments in urban stormwater runoff: Effect of land uses, precipitation conditions, and seasonal variations

Understanding particle size distribution (PSD) of total suspended sediments in urban runoff is essential for pollutant fate and designing effective stormwater treatment measures. However, the PSDs from different land uses under different weather conditions have yet to be sufficiently studied. This research conducted a six-year water sampling program in 15 study sites to analyze the PSD of total suspended sediments in runoff. The results revealed that the median particle size decreased in the order: paved residential, commercial, gravel lane residential, mixed land use, industrial, and roads. Fine particles less than 125 μm are the dominant particles (over 75%) of total suspended sediments in runoff in Calgary, Alberta, Canada. Roads have the largest percentage of particles finer than 32 μm (49%). Gravel lane residential areas have finer particle sizes than paved residential areas. The results of PSD were compared with previous literature to provide more comprehensive information about PSD from different land uses. The impact of rainfall event types can vary depending on land use types. A long antecedent dry period tends to result in the accumulation of fine particles on urban surfaces. High rainfall intensity and long duration can wash off more coarse particles. The PSD in spring exhibits the finest particles, while fall has the largest percentage of coarse particles. Snowmelt particles are finer for the same land use than that during rainfall events because the rainfall-runoff flows are usually larger than the snowmelt flows.

Tracking the nitrogen leaching from different sources in bioretention systems with a process-based model

Bioretention systems are a typical stormwater management technology intended to reduce runoff and non-point source pollution. Multiple sources can contribute to nitrogen (N) leaching from bioretention systems, including the current rainfall-runoff (i.e., immediate leaching), recent rainfall-runoffs (i.e., fast leaching) and long-ago legacy N (i.e., slow leaching), however, there is a lack of methods to quantify these contributions. Here, a process-based Bioretention System (BRS) model for N leaching simulations was verified with artificially-labeled 15N data besides N data to reduce predictive uncertainties. The BRS model was then coupled with an Nitrogen Source Apportionment (NSA) module for N leaching tracking to quantify the contributions from different sources. Results from a bioretention system showed that additional 15N data reduced the predictive uncertainty of total N (TN) concentrations by 23 %. Immediate leaching, fast leaching and slow leaching increased, decreased and remained steady during the leaching process and accounted for 79.54 ± 5.08 %, 2.80 ± 1.74 % and 17.66 ± 4.11 % of N leaching, respectively. The dominant immediate leaching can be significantly weakened by a submerged zone, a shorter antecedent dry period (ADP), a lower rainfall intensity or influent concentration. This study provides a framework to quantify N leaching from multiple sources with implications for long-term N leaching management.

Investigating First Flush Occurrence in Agro-Urban Environments in Northern Italy

The first flush (FF) phenomenon is commonly associated with a relevant load of pollutants, raising concerns about water quality and environmental management in agro-urban areas. An FF event can potentially transport contaminated water into a receiving water body by activating combined sewer overflow (CSO) systems present in the drainage urban network. Therefore, accurately characterizing FF events is crucial for the effective management of sewer systems and for limiting environmental degradation. Given the ongoing controversy in the literature regarding the delineation of FF event occurrences, there is an unavoidable necessity for further investigations, especially experimental-based ones. This study presents the outcomes of an almost two-year field campaign focused on assessing the water quantity and quality of two combined sewer systems in Northern Italy. For this purpose, various hydro-meteorological variables, including precipitation, flow rate, temperature, and solar radiation, in addition to water quality analytics, were measured continuously to capture stormwater events. Throughout the monitoring period, sixteen stormwater events were identified and analyzed using five indices usually adopted in the literature to identify FF occurrences. The results indicate that there is a strong positive correlation between the mass first flush ratios calculated for nutrients and three factors, including maximum rainfall intensity, maximum flow rate, and antecedent dry weather period. Furthermore, rainfall duration was found to possess a strong negative correlation with the mass first flush ratios calculated for nutrients. However, for the same rainfall event, the occurrence of FF has never been unanimously confirmed by the indices examined in this study. Moreover, different macro-groups of pollutants can behave differently. Thus, it becomes apparent that relying solely on a priori analyses, without the support of data from experimental monitoring campaigns, poses a risk when designing actions for the mitigation of FF occurrences.

Using a Laboratory Column Experiment to Explore the Influence of an Antecedent Dry Period on the Nutrient Removal of a Bioretention Filter

Using a Laboratory Column Experiment to Explore the Influence of an Antecedent Dry Period on the Nutrient Removal of a Bioretention Filter

Time-varying characteristics of saturated hydraulic conductivity in grassed swales based on the ensemble Kalman filter algorithm —A case study of two long-running swales in Netherlands

Saturated hydraulic conductivity (Ks) of the filler layer in grassed swales are varying in the changing environment. In most of the hydrological models, Ks is assumed as constant or decrease with a clogging factor. However, the Ks measured on site cannot be the input of the hydrological model directly. Therefore, in this study, an Ensemble Kalman Filter (EnKF) based approach was carried out to estimate the Ks of the whole systems in two monitored grassed swales at Enschede and Utrecht, the Netherlands. The relationship between Ks and possible influencing factors (antecedent dry period, temperature, rainfall, rainfall duration, total rainfall and seasonal factors) were studied and a Multivariate nonlinear function was established to optimize the hydrological model. The results revealed that the EnKF method was satisfying in the Ks estimation, which showed a notable decrease after long-term operation, but revealed a recovery in summer and winter. After the addition of Multivariate nonlinear function of the Ks into hydrological model, 63.8% of the predicted results were optimized among the validation events, and compared with constant Ks. A sensitivity analysis revealed that the effect of each influencing factors on the Ks varies depending on the type of grassed swale. However, these findings require further investigation and data support.

Evaluation of sorbent amendments used with stormwater management practices to remove contaminants: Impacts of rainfall intensity and antecedent dry periods

For a comprehensive evaluation of the suitability and efficiency of soil amendments in bioretention systems, it is crucial to investigate the capability of amendments for simultaneously serving three important functions under intermittent and variable flow conditions: removing a wide range of contaminants, supporting plant health, and maintaining media infiltration rate. However, most studies have not considered these important factors and conditions simultaneously, which may overestimate or underestimate the bioretention performance. In this study, a long-term vegetated column study was conducted to investigate the ability of various sorbent amendments– coconut coir fiber (CCF), blast furnace slag (BFS), and waste tire crumb rubber (WTCR) –for removal of metals, nutrients, and polycyclic aromatic hydrocarbons (PAHs) from stormwater. The experiments were performed under intermittent flow conditions considering different runoff intensities and antecedent dry periods (ADP). The long-term effect of bioretention usage on plant health and media infiltration rate was also investigated.All amended and unamended columns were able to remove >99 % of influent metals, except Cu, over the 7-month experiment period with different rain intensities and dry periods; modest effluent Cu concentrations occurred with higher rainfall. The performance of different media for removing PAHs such as naphthalene and acenaphthylene varied with the rain intensity. The BFS-amended media had high phosphate removal capacity (>90 %) under tested conditions. In all columns, nitrate removal was notably affected by changes in stormwater intensity and ADP, with high nitrate removal during heavy rainfall. Over the entire experiment, all media had good infiltration rate within the locally acceptable range (1–25 cm/h). The high iron and aluminum contents of BFS adversely affected the plant health in BFS-amended media. Overall, this study identifies the opportunities and challenges associated with the usage of bioretention amendments, and improves awareness among bioretention designers to consider seasonal effect on the performance of bioretention systems.

Substrate moisture variations of extensive green roofs with different structural configurations in a semi-arid region: Observational data and dynamic simulation

Substrate moisture condition is crucial for hydrological performance, water management and plant survival of green roofs. To date, the behaviour of long-term substrate moisture of green roofs in various climate regions has not been well understood. In this study, 24 months continuous field monitoring of substrate moisture content within nine extensive green roof modules with varies structural configurations was conducted to investigate the impacts of structural configurations and meteorological factors on substrate moisture content, and identify the key parameters for simulating the long-term substrate moisture dynamics. Results showed that green roofs planted with SedumSpectabilehave the highest mean volumetricwater content (VWC) (0.12–0.15 m3/m3) compared to other plant species considered. Green roofs with 5-cm substrate depth had lower mean VWC (0.07–0.08 m3/m3) than other substrate depths. The average substrate moisture loss rate of green roofs in summer and autumn seasons was 1.35 and 1.22 mm/day, respectively, which was higher than the spring (0.73 mm/day) and winter (0.64 mm/day) seasons for 2021. There were significant differences in mean VWC of green roofs among substrate material types. The mean VWC of green roofs was gradually enhanced from 0.12 to 0.14 m3/m3 as the substrate depth increased from 5 cm to 15 cm. The differences of mean VWC among vegetation types were all extremely significant (p < 0.001). The relative humidity was the most significant influencing factor on the average VWC level (correlation coefficient r = 0.42), with antecedent dry weather period (ADWP) had less significant effects on substrate VWC (r = 0.33), and followed by precipitation depth (r = 0.27). However, there was no significant relationship between air temperature and average VWC level of green roofs as well as total solar radiation. Nash-Sutcliffe efficient (NSE) values of the model simulations ranged from 0.70 to 0.81, and the mean absolute relative error (MAE) values ranged from 1.25 to 2.36, which indicated the model can adequately simulate the long-term substrate moisture content dynamics of green roofs. The crop coefficient and maximum water holding capacity of the substrate were the key parameters affecting long-term moisture content simulation of green roofs. These results could provide scientific suggestions for selecting suitable structural configuration to enhance water holding capacity of extensive green roofs in arid climates.

Measuring sediment loads and particle size distribution in road runoff: Implications for sediment removal by stormwater control measures

Road runoff contributes an array of pollutants which degrade the quality of receiving waters. Sediment conveyed in runoff results in loss of habitat and loss of reservoir capacity, among other undesirable impacts. To select and design stormwater control measures (SCMs), the sediment particle size distribution (PSD) is needed to quantify the required hydraulic retention time for particle settling and to understand what other treatment processes (e.g., filtration) are needed to meet sediment removal targets. A two-year field monitoring study was undertaken across the state of Ohio, USA, to evaluate the PSD of sediment in runoff at twelve roads. The highest TSS concentrations were observed on interstate highways (highest annual average daily traffic [AADT]) and minor arterials (low AADT), suggesting factors beyond AADT, such as antecedent dry period, rainfall intensity, and windborne dust and particulates, contribute to the varied sediment characteristics in runoff. The median TSS load across all samples collected was 2.7 kg/ha per storm event, while annual TSS loads for the monitoring sites varied from 98 kg/(ha·yr) to 519 kg/(ha·yr), with a mean value of 271 kg/(ha·yr). Particle size distributions varied across the monitoring sites, with mean and median d50 of 48.6 μm and 52.5 μm, respectively. Interstate highways (highest AADT) had significantly finer PSDs than other functional classes, while roads in low density residential areas had coarser PSDs than other land uses. Observed differences in PSD across road characteristics may guide SCM selection; dry detention basins and wet ponds/wetlands were predicted to provide effective removal across a variety of PSDs, while TSS reductions provided by hydrodynamic separators and high-flow media filters (which effectively remove larger particles) may be maximized in areas with coarser PSDs (e.g., roads surrounded by low density residential areas studied herein).

Modeling the effect of the submerged zone on nitrogen removal efficiency of a bioretention system under dry-wet alterations

Bioretention systems are effective stormwater treatment systems. Many studies have been conducted on the nitrogen regulation effects of bioretention systems. However, few studies had investigated the variation of nitrogen concentration in the submerged zone during dry periods and evaluated the effect of the submerged zone on nitrogen removal efficiency under dry-wet alterations. Furthermore, existing models cannot fully consider the impact of the submerged zone on nitrogen removal. This paper presents the validation, prediction uncertainty, parameter sensitivity analysis, and scenario simulations with different submerged zone depths of a proposed model. We conducted 13 consecutive rainfall events for model validation under dry-wet alternations in a mesocosm bioretention system with a submerged zone. The collected data mainly includes outflow rates, outflow nitrogen concentrations (NH4-N, NO3-N, and TN) in wet periods, and submerged zone nitrogen concentrations (NH4-N, NO3-N, and TN) in dry periods. The results show that (1) the Nash efficiency coefficients in the wet and dry periods were all above 0.5 during calibration and validation phases; (2) the prediction uncertainty of outflow/submerged zone nitrogen concentration (NH4-N, NO3-N, and TN) can be significantly reduced by using NSE values of the wet and dry periods as likelihood objective functions than only using NSE values of the wet periods; (3) the sensitivity analysis shows that outflow nitrogen concentrations (NH4-N, NO3-N, or TN) are sensitive to most of nitrogen module parameters in the submerged zone; (4) in the long-term dry-wet alterations simulation, the increase of submerged zone depth can improve the annual average nitrogen removal rate, while it does not always improve nitrogen removal rates in single rainfall event. If a rainfall event with a short antecedent dry period (<1.5 d) and the inflow nitrogen concentration in the current event is less than that in the previous event, the increase of the submerged zone depth will even reduce the nitrogen removal rate.

In situ monitoring of internal water storage reveals nitrogen first flush phenomena, intermittent denitrification, and seasonal ammonium flushing

Internal water storage (IWS) can be included in bioretention practices to increase storage capacity or promote denitrification—the microbial reduction of nitrate to nitrogen gas. IWS and nitrate dynamics are well studied in laboratory systems. However, the investigation of field environments, consideration of multiple nitrogen species, and determination between mixing versus denitrification is lacking. This study employs in situ monitoring (∼24 h duration) of water level, dissolved oxygen (DO), conductivity, nitrogen species, and dual isotopes of a field bioretention IWS system for nine storms events over a year period. Rapid peaks in IWS conductivity, DO, and total nitrogen (TN) concentrations occurred along the rising limb of the IWS water level and indicated a first flush effect. TN concentrations generally peaked during the first ∼0.33 h of sampling and the average peak IWS TN concentration (Cmax = 4.82 ± 2.46 mg-N/L) was 38% and 64% greater than the average TN along the IWS rising and falling limb, respectively. Dissolved organic nitrogen (DON) and nitrate plus nitrite (NOx) were the dominant nitrogen species of IWS samples. However, average IWS peak ammonium (NH4+) concentrations August through November (0.28 ± 0.47 mg-N/L) demonstrated statistically significant shifts compared to February through May (2.72 ± 0.95 mg-N/L). Average lysimeter conductivity measurements were more than ten times higher February through May. The sustained presence of sodium observed in lysimeters, from road salt application, contributed to NH4+ flushing from the unsaturated media layer. Dual isotope analysis showed denitrification occurred for discrete time intervals along the tail of the NOx concentration profile and the hydrologic falling limb. Longer antecedent dry periods (17 days) did not correlate to enhanced denitrification but did correspond to more leaching of soil organic nitrogen. Results from field monitoring highlight the complexities of nitrogen management in bioretention systems. First flush behavior into the IWS suggests management to prevent TN export is most critical during the onset of a storm.

Spatio‐temporal variability and intra‐event variation of throughfall ammonium and nitrate in a pine plantation

AbstractForest canopies are the functional interface between ecosystem and the atmospheric nitrogen (N) deposition. However, the sources of spatio‐temporal variability and intra‐event variation of N deposition via throughfall (TF) remain ambiguous. Here, we analysed TF samples for concentrations and fluxes of ammonium (NH4+) and nitrate (NO3−) using an array of 20 fixed‐position collectors on an event and within event basis throughout the 2019 growing season in a Chinese pine plantation, Northern China. Results showed that the volume weighted mean concentrations of NH4+ and NO3− in TF were significantly higher than those in bulk precipitation (BP) during the study period. A canopy budget model indicated that canopy uptake was more dominant than dry deposition for NH4+, while the reverse was true for NO3−. This caused a comparable TF NH4+ flux but an enhanced TF NO3− fluxes compared to BP. The intra‐event trend and magnitude of TF NH4+ and NO3− concentrations were influenced by the antecedent dry period and rainfall intensity, and indicated that biological nitrification may occur in the canopies. In addition, due to the larger of canopy NH4+ uptake that counteracted the amplifying effect of dry deposition, the spatial variability of TF NH4+ concentration was significantly lower than that of TF NO3− concentration, and exhibited more temporal persistence. No relationship was found between the spatial distribution of TF NH4+ concentration and the TF amount, the distance to the nearest trunk, nor the canopy cover, whereas the TF NO3− concentration was significantly related to the TF amount and the canopy cover. These findings can enhance our understanding of N processes within canopies, and have important implications for evaluating the impacts of N deposition in forest ecosystems.

Characterization of micropollutants in urban stormwater using high-resolution monitoring and machine learning

Urban rainfall events can lead to the runoff of pollutants, including industrial, pesticide, and pharmaceutical chemicals. Transporting micropollutants (MPs) into water systems can harm both human health and aquatic species. Therefore, it is necessary to investigate the dynamics of MPs during rainfall events. However, few studies have examined MPs during rainfall events due to the high analytical expenses and extensive spatiotemporal variability. Few studies have investigated the occurrence patterns of MPs and factors that influence their transport, such as rainfall duration, antecedent dry periods, and variations in streamflow. Moreover, while there have been many analyses of nutrients, suspended solids, and heavy metals during the first flush effect (FFE), studies on the transport of MPs during FFE are insufficient. This study aimed to identify the dynamics of MPs and FFE in an urban catchment, using high-resolution monitoring and machine learning methods. Hierarchical clustering analysis and partial least squares regression (PLSR) were implemented to estimate the similarity between each MP and identify the factors influencing their transport during rainfall events. Eleven dominant MPs comprised 75% of the total MP concentration and had a 100% detection frequency. During rainfall events, pesticides and pharmaceutical MPs showed a higher FFE than industrial MPs. Moreover, the initial 30% of the runoff volume contained 78.0% of pesticide and 50.1% of pharmaceutical substances for events W1 (July 5 to July 6, 2021) and W6 (August 31 to September 1, 2021), respectively. The PLSR model suggested that stormflow (m3/s) and the duration of antecedent dry hours (h) significantly influenced MP dynamics, yielding the variable importance on projection scores greater than 1.0. Hence, our findings indicate that MPs in urban waters should be managed by considering FFE.

The control efficiency and mechanism of heavy metals by permeable pavement system in runoff based on enhanced infiltration materials

As one of the commonly used stormwater management measures, permeable pavement system (PPS) played a prominent role in controlling runoff pollution and alleviating urban waterlogging. In this study, new enhanced infiltration materials (construction waste brick, coal gangue, activated carbon, multi-walled carbon nanotube, multi-layer graphene) were applied in PPS and the control efficiency and mechanism of typical heavy metals (HMs, Mn2+, Pb2+, Zn2+, Cu2+, Cd2+, Ni2+) was investigated in runoff. Furthermore, the influences of different rainfall intensities and antecedent dry periods on HMs removal by PPS were evaluated. The results showed that all PPS with enhanced infiltration materials have little leaching effect on HMs (＜3 μg/L). All the selected enhanced infiltration materials meet the requirements of PPS. The concentration of HMs in the effluent of PPS dropped sharply first, followed rebounded and then maintained at a stable range. Activated carbon PPS (AC), Multi-walled carbon nanotube PPS (MCN), and Multi-layer graphene PPS (MG) could significantly improve the control effect of PPS on nearly all selected HMs. The average removal rates of AC, MCN and MG for six HMs were 75.48%–99.35%, 81.30%–97.59%, and 73.03%–99.33%, respectively. Compared with Traditional PPS (TR), the effluent concentrations of HMs in construction waste brick PPS (CW) and coal gangue PPS (CG) were relatively higher and unstable. AC, CN and MG could adapt to different rainfall conditions and the maximum removal rates of most HMs exceed to 99%. With antecedent dry periods increased, the control effect of HMs was significantly improved. The influences of the antecedent drying period on HMs removal followed as: CW＞CG＞TR＞MG＞CN＞AC. This study provided novel methods to eliminating HMs in runoff and provides implications for the design of PPS.

The uncertainity in stormwater quality modelling for temperate and tropical catchments

More research has been done on the uncertainty of stormwater quantity as compared to quality modelling. Although the washoff model has been in use for decades, there is a general lack of studies on the uncertainty associated with washoff modelling and how this uncertainty varies between catchments in different climate zones due to differences in rainfall conditions. This study investigated model structure uncertainty, in addition to gaining knowledge on model parameter uncertainty in water quality modelling of urban catchments located in two climate zones. Such a study not only adds to the body of knowledge but highlights the importance of distinguishing the difference in washoff behaviour, and their results, between catchments in different climate zones. Following an exhaustive search and assessment of data quality, the rainfall, discharge and water quality data sourced from 11 residential catchments, which include 72 events from temperate catchments and 59 from tropical catchments were analysed. Comparison of uncertainty between buildup-washoff model (BW) and washoff model (WO) results for particulate (Total Suspended Solids (TSS)), mixed (Total Phosphorus (TP), Total Nitrogen (TN)) and dissolved (ortho-Phosphate (OP), Ammonium (NH4-N)) phase water quality parameters were carried by using the Generalized Likelihood Uncertainty Estimation (GLUE) method. Higher Average Relative Interval Length (ARIL) values obtained for tropical catchments showed that uncertainty in model prediction is higher than temperate catchments. This result is confirmed for both the BW and WO modelling approaches. The threshold criteria for obtaining behavioural set chosen as likelihood measure of Tr = 0.7 (based on the Nash-Sutcliffe coefficient) and η ≥ 70 % (proportion of observed data falling within the 90 % uncertainty band of the simulated data distribution over the total number of observations) are mostly satisfied for the particulate phase and least by the dissolved phase water quality parameters, providing further evidence that the structure of the models are not universally applicable, and that model results should be understood in the light of this difference. Comparisons between the BW and WO approaches showed similar levels of uncertainty, irrespective of climate. Although this is consistent with other studies reported in the literature, the antecedent dry period (ADP), a key parameter in the buildup process, was not significantly (p =.07) different between the temperate and tropical datasets. This is likely an artifact of sampling, especially for temperate catchments, where field data is collected during the rainy season, when ADP is limited and similar with catchment in the tropics.

An improved nonnegative matrix factorization with the imputation method model for pollution source apportionment during rainstorm events

Data scarcity caused by extreme conditions during storms adds difficulties in performing pollution source apportionment. This study integrated nonnegative matrix factorization with the imputation method (NMF-IM) to fill in missing data (NAs) and conduct source apportionment. A total of 367 river samples and 35 runoff samples were taken from the Banqiao and Nanfei River basins located in Hefei, China, during four rainfall events from June to August 2020. Sixteen indicators were quantified and used for source diagnostics using NMF-IM. The results showed that total phosphorus (TP) had higher concentrations and more violent fluctuations than total nitrogen (TN) in river samples taken from rain. NMF-IM was shown to recover the value distribution of NAs approximately. The source profiles and contribution rates calculated by NMF-IM with NAs were close to the original results calculated by NMF without NAs, with root mean square error of less than 2.3% and differences less than 9.5%. Multiple forms of nitrogen and phosphorus indicators benefit reaching reasonable source diagnostics results. At least four indicators were needed to reach the same contribution rates as 16 indicator diagnostics. The two good indicator combination groups are nitrate (NO3–N), nitrite (NO2–N), ammonia nitrogen (NH3–N), and total suspended solids (TSS) and NO3–N, NO2–N, phosphorus (PO4–P), and TSS. The pollution source contributions changed with the Antecedent dry period (ADPs) of rain events. Treated tailwater and untreated sewage were major sources, contributing more than 80% of the total pollution of the rainstorm events with short ADPs. Dust wash became the dominant contributor after 60 min and contributed 36% of the total pollution of rainstorm events with long ADPs. The average source contribution rates for rainfall events in the Banqiao River were treated tailwater (41%) > untreated sewage (27%) > dust wash (19%) > other sources (16%). The pollution source diagnostics results were verified to be reasonable by simulation using tested run-off data and literature results.

Evaluating the impact of climate change on future bioretention performance across the contiguous United States

In light of shifting precipitation patterns induced by climate change, communities are seeking to build resiliency in urban drainage systems through interventions such as green stormwater infrastructure (GSI). Bioretention cells are one of the most commonly implemented forms of GSI for their ability to reduce peak discharge, retain runoff, and filter pollutants. However, they may be at risk of reduced function in the future due to deviations from historic precipitation frequency and intensity patterns which are essential to their design. Further, changes in future function are likely to vary regionally as the magnitude of future climate changes will differ across the globe. To explore the range of impacts to future bioretention function, an ensemble of 10 regional climate models at 17 locations across the contiguous United States were evaluated to provide the widest range of potential future outcomes using a probabilistic approach to capture the uncertain nature of climate change. Bioretention cells were modeled using USEPA’s Storm Water Management Model (SWMM) to compare existing and future performance under a range of climate change projections. Median annual rainfall and 99th percentile rainfall event depths and intensities were projected to increase across all 17 locations while antecedent dry period (i.e., the time between consecutive rain events) was projected to increase for 11 locations. Correspondingly, bioretention cell hydrologic performance decreased across all 17 locations under future scenarios: relative to performance under current climate conditions, annual volumes of infiltration decreased between 4.0 and 24.0% across all 17 locations while overflow increased between 0.4 and 19.6% for 15 locations. Results suggest that bioretention cells in the southern United States are at significant risk of reduced function in the future while those in the Midwest and Northeast are at moderate risk. Bioretention cells in the Northwest/West performed the best under future climate scenarios; that is, they showed similar function in the future to that of the present. Findings demonstrate that most, if not all, bioretention cells across the contiguous United States will require some degree of modification to maintain existing function under future conditions.

Estimating dry deposition of atmospheric aerosols to urban surfaces by rain washoff

Atmospheric aerosols accumulate onto urban surfaces by dry deposition and are subsequently washed off by rain. If there is a sufficiently long period of dry weather, it may be possible to estimate the dry deposition rate of a chemical species by measuring its concentration in runoff from the surface and its concentration in fresh rain. This hypothesis was tested for horizontal surrogate surfaces exposed to the atmosphere in Syracuse, New York. In each experiment, two flat disks 1 m diameter with 2.54 cm rims and two disks of similar size but without rims were exposed to the atmosphere on the roof of Hinds Hall at Syracuse University to collect dry deposition of aerosol fluoride, chloride, sulfate, potassium, calcium, and strontium. Airborne concentrations were measured simultaneously to calculate dry deposition velocities. Dry deposited material on the flat disks was removed using a Teflon scraper after a few days of exposure, just prior to a rainstorm. In the subsequent storm, sequential samples of runoff from the rimmed disks and fresh rain were collected. The concentrations in fresh rain were subtracted from the concentrations in the runoff to calculate dry deposition fluxes, which were compared to fluxes measured by scraping the flat disks prior to rain. Results showed that sufficient removal of dry deposited material was possible to estimate dry deposition fluxes. Ratios of the mean dry deposition flux onto the rimmed disks to the mean dry deposition flux onto the flat disks had an overall average of 0.89 for all chemical species. This ratio mean and standard deviation was 0.94±0.30 for fluoride, 0.59±0.54 for chloride, 1.0±0.10 for sulfate, 0.80±0.28 for potassium, 1.0±0.03 for calcium, and 0.93±0.12 for strontium. However, some dry deposition fluxes to the rimmed disks were smaller than those to the flat disks in cases where the wet deposition flux was at least one half of the contribution to the total flux. This suggests the importance of having antecedent dry periods of at least several days to use this method to estimate dry deposition of aerosols and to minimize the role of contaminants in the fresh rain contributing significantly to the total concentration in the runoff samples. Future work includes testing this method on rooftops and other horizontal urban surfaces, which may enable reliable estimates of dry deposition rates to urban areas.