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Urban stormwater, increasingly seen as a potential water resource for cities and towns, contains various trace organic chemicals (TrOCs). This study, conducted through a comprehensive literature review of 116 publications, provides a detailed report on the occurrence, concentration distribution, health, and ecological risks of TrOCs, as well as the impact of land use and rainfall characteristics on their concentrations. The review uncovers a total of 629 TrOCs detected at least once in urban stormwater, including 228 pesticides, 132 pharmaceutical and personal care products (PPCPs), 29 polycyclic aromatic hydrocarbons (PAHs), 30 per- and polyfluorinated substances (PFAS), 28 flame retardants, 24 plasticizers, 22 polychlorinated biphenyls (PCBs), nine corrosion inhibitors, and 127 other industrial chemicals/intermediates/solvents. Concentration distributions were explored, with the best fit being log-normal distribution. Risk assessment highlighted 82 TrOCs with high ecological risk quotients (ERQ > 1.0) and three with potential health risk quotients (HQ > 1.0). Notably, 14 TrOCs (including six PAHs, five pesticides, three flame-retardants, and one plasticizer) out of 68 analyzed were significantly influenced by land-use type. Relatively weak relationships were observed between rainfall characteristics and pollutant concentrations, warranting further investigation. This study provides essential information about the occurrence and risks of TrOCs in urban stormwater, offering valuable insights for managing these emerging chemicals of concern.

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The rapid development of the city leads to the continuous updating of the land use allocation ratio, particularly during the flood season, which will exacerbate the significant changes in the spatial and temporal patterns of urban flooding, increasing the difficulty of urban flood forecasting and early warning. In this study, the spatial and temporal evolution of flooding in a high-density urban area was analyzed based on the Mike Flood model, and the influence mechanisms of different rainfall peak locations and infiltration rate scenarios on the spatial and temporal characteristics of urban waterlogging were explored. The results revealed that under the same return period, the larger the rainfall peak coefficient, the larger the peak value of inundation volume and inundation area. When the rainfall peak coefficient is small, the higher the return period is, and the larger the peak lag time of the inundation volume is, in which P = 50a, r = 0.2, the peak lag time of the inundation volume reached 32 min and 45 min for the inundation depths H > 0.03 m and H > 0.15 m, respectively. There are also significant differences in the peak lag time of waterlogging inundation volume for different inundation depths. The greater the inundation depth, the longer the peak lag time of the inundation volume, and the higher the return period, the more significant the effect of lag time prolongation. It is worth noting that the increase in infiltration rate may lead to an advance in the peak time of inundation volume and inundation area, and the peak time of the inundation area is overall more obvious than that of inundation volume. The effect of infiltration rate on the peak time of inundation volume for larger inundation depths was relatively large; the peak times of inundation volume and inundation area were advanced by 4-6 min and 4-8 min for H > 0.03 m and H > 0.15 m, respectively, after the increase in infiltration rate, and the higher the rainfall return period, the longer the advance time. The spatial and temporal characteristics of waterlogging under different peak rainfall locations and infiltration capacities obtained in this study can help provide a new perspective for temporal forecasting and warning of urban waterlogging.

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Significant changes in rainfall patterns are critical to agriculture, and the dependency of cropping systems on rainfall variability would engender appropriate farming practices and agriculture policies for a climate-resilient agriculture system. This study analyses the significance of rainfall variability on agriculture productivity in the Wayanad district of Kerala (India) using time series data on rainfall (1989-2019) and crop yield (2000-2019). The spatial variability of rainfall patterns reveals a dichotomy between the rain gauge stations in the northern and southern parts of the region. Despite the absence of statistically significant trends in the monthly, seasonal and annual rainfall, based on the Mann-Kendall trend analysis, an increase in the yield of many crops (e.g., winter paddy, banana) is evident, which emphasises the critical role of irrigation in driving the crop productivity. As an adaptation strategy to changing rainfall patterns, irrigation would meet the additional crop water requirement for sustainable agricultural production under the varying rainfall distributions. However, the increase in the area under irrigation in recent years has had significant implications for both surface water and groundwater resources. The conclusive findings suggest that the region requires climate-resilient agriculture, focusing on optimising irrigation and developing sustainable agriculture and water conservation strategies.

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The relationship between rainfall characteristics and pollutant discharge has rarely been investigated in industrial sectors. To address this need, we investigated the pollutant concentrations of surface runoff and the correlation between pollutant discharge and rainfall characteristics using the self-reported stormwater quality data collected under the Tennessee Multi-Sector Permit program for two industrial facilities in West Tennessee. The variation of certain stormwater quality parameters over this period was utilized as an indicator to evaluate the effectiveness of control measures implemented at these two facilities. Furthermore, the Water Quality Index (WQI) as an indicator to assess the temporal changes in stormwater quality at industrial facilities was determined using the Weighted Sum (WSM) and Canadian Council of Ministers of the Environment (CCME) methods. The principal component analysis (PCA) and Pearson correlation coefficient were utilized to understand the correlation between runoff quality parameters, rainfall characteristics, and the sources of pollutants. The results demonstrated lower WQI indices using the WSM method compared to the CCME method. The data analysis revealed that 93.1%, 100%, 86.2%, and 48.3% of Al, Mg, Cu, and Fe experienced a concentration greater than the benchmark level, respectively. There was a significant relationship between Total suspended solids (TSS) and Al, Chemical Oxygen Demand (COD), Fe, oil and grease (O&G), and Zn concentrations. As a result, TSS could be a priority pollutant for designing various best management practices (BMPs) and low impact developments (LIDs). The result of the PCA and Pearson correlation coefficient showed that Al concentration made a significant correlation with the rainfall depth and rainfall duration. This analysis also illustrated that biochemical oxygen demand (BOD5), COD, and O&G concentrations were highly correlated with antecedent dry days (ADDs). However, pH was more related to rainfall depth and rainfall intensity. This study informs both regulatory agencies and industry stakeholders regarding the importance of evaluating self-reported stormwater quality data.

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Stormwater runoff is considered a major pathway for land-based microplastic transportation to aquatic environments. By applying time-weighted stormwater sampling at stormwater outlets from industrial and residential catchments, we investigated the emission characteristics and loads (number- and mass-based) of microplastics to aquatic environments through urban stormwater runoff during rainfall events. Microplastics were detected in stormwater runoff from industrial and residential areas in the concentration range of 68-568 n/L and 54-639 n/L, respectively. Polypropylene and polyethylene were found as major polymers accounting for around 60 % of total microplastics. The fragment was the dominant shape of microplastics, and the most common size class was 20-100 µm or 100-200 µm. The microplastic load emitted from industrial and residential areas were estimated to be 1.54-46.1 × 108 and 0.63-28.5 × 108 particles, respectively. The discharge characteristics of microplastics inter- and intra-event were affected by the land-use pattern and rainfall characteristics. The concentration of microplastics did not significantly differ between industrial and residential catchments, but the composition of polymer types reflected the land-use pattern. The microplastics in stormwater were more concentrated when the number of antecedent dry days (ADDs) was higher; the concentration of microplastics was generally peaked in the early stage of runoff and varied according to rainfall intensity during a rainfall event. The contamination level and load of microplastics were heavily affected by the total rainfall depth. Most microplastics were transported in the early stage of runoff (19-37 % of total runoff time), but the proportion of larger and heavier particles increased in the later period of runoff. The microplastic emission via stormwater runoff was significantly higher than that through the discharge of wastewater treatment plant effluent in the same area, implying that stormwater runoff is the dominant pathway for transporting microplastics to aquatic environments.

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Urban stormwater is a substantial source of non-point source pollution. Despite considerable monitoring efforts, little is known about stormwater quality in certain geographic regions. These spatial gaps induce uncertainty when extrapolating data and reduce model calibration capabilities, thereby limiting pollutant load reduction strategies. In this study, stormwater quality was monitored from 15 watersheds to characterize pollutant event mean concentrations (EMCs) and loads as a function of urban and forested (i.e., surrogates for pre-development) land use and land covers (LULCs) and rainfall patterns from a geographic region where these data are sparse. Residential and heavy industrial, heavy industrial, and industrial and commercial LULCs, respectively, were the primary generators of nutrients, total suspended solids (TSS), and heavy metals. Increased rainfall intensities (average and peak) significantly increased the EMCs of all particulate bound pollutants. Pollutant loads increased with rainfall depth and, in general, did not follow the same LULC trends as EMCs, suggesting loads were influenced substantially by watershed hydrologic responses. Mean annual urban loads of total phosphorus, total nitrogen, TSS, and zinc (Zn) ranged from 0.4 (low density residential [LDR]) to 1.5 (heavy industrial), 3.2 (single family residential [SFR]) to 11.5 (heavy industrial), 122.6 (SFR) to 1219.9 (heavy industrial), and 0.1 (LDR) to 0.7 (commercial) kg/ha/yr, respectively. Annual urban loads of TSS were 3.5 to 34 and - 1.5 to 6.8-fold greater than annual loads from forested and agricultural watersheds, respectively. Mean annual loads of heavy metals from urban LULCs were substantially greater than loads produced by forested and agricultural watersheds (e.g., 8.6 to 92 and 6.8 to 73-fold greater, respectively, for Zn), while loads of nutrients were generally similar between urban and agricultural watersheds. Findings herein suggest non-point source pollution will continue to threaten surface water quality as land is developed; results can help guide the development of cost-efficient stormwater management strategies.

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Influenced by global climate change, rainfall characteristics have changed in recent years, especially in arid regions. However, the actual response of the watersheds' hydrological indicators to erosive rainfalls has not been understood yet. Therefore, this study sought to investigate the changes in the watersheds' hydrological response due to the intra-rainfall indices of various events in the Dehgin paired watershed in Hormozgan, Iran, using the data collected from 2007 to 2019. To this end, first, all rainfall events which elicited the response of watersheds were identified concurrently based on the meteorological and flume data. Then, the qualitative and quantitative intra-storm variations associated with hydrological indicators (i.e., total runoff and discharge variables) were extracted for statistical analysis. The study's results revealed that (1) the increasing rates of the continuous discharge time of the control and treatment watershed's front position were about 2.25 and 4.76 times the rear position, respectively. (2) A strong linear relationship was found between total runoff volume and variables including precipitation of storm and time to storm peak in both control and treatment watersheds, with the R2 reported to be 67.7 and 63.6%, respectively. (3) It was also found that the watershed management operations reduced the variables' values including the maximum discharge, the discharge variation coefficient, continuity time of discharge, the peak of the time to discharge, the number of discharge peaks, and the total runoff volume by 3, 1.6, 2.25, 2.37, 2.42, and 3.27 times, respectively. Therefore, it could conceivably be argued that extreme rainfalls can be controlled by management practices in the watersheds.

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Nitrogen pollution in urban stormwater has led to serious quality issues in urban water. Nitrogen pollution mitigation requires fully understanding the transport process and major nitrogen sources in urban stormwater. In this study, the concentrations and flux of various nitrogen forms during urban stormwater transport were analyzed. It was found that the concentration and flux of NO3--N and NH3-N decreased in the order of roof runoff, road runoff, and drainage runoff, while the concentration and flux of dissolved organic nitrogen (DON) and particulate nitrogen (PN) were found to be the highest in road runoff. Source quantification found that roof runoff (34%) and rainwater (34%) were the main contributors to nitrate pollution during light and moderate rains (<25 mm), while road runoff was identified as the major source (49%) of nitrate pollution during heavy rains (>25 mm) due to the large road runoff volume. Regarding particulate organic nitrogen (PON), the road runoff in commercial areas contributed most (23%) to PON pollution during light and moderate rains, while the runoff generated from pervious surfaces and drainage sediments were the primary two sources (22%) of PON during heavy rains. Moreover, the influence of rainfall characteristics on nitrate and PON source contributions was identified. The results show that antecedent dry periods were an important factor influencing nitrogen source contributions during light and moderate rains, while rainfall amount and intensity were critical factors impacting the nitrogen source contributions during heavy rains. Taking various transport processes, source contributions, and rainfall characteristics into consideration, several recommendations were given for the mitigation of nitrogen pollution in urban stormwater. This study can provide a useful perspective to understand the transport and sources of nitrogen, thus developing constructive strategies to control urban nonpoint source pollution management.

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In this study, coal gangue (CG) was applied as media in bioretention system to remove runoff pollutant. CG modified bioretention systems show good removal efficiency towards runoff pollutant due to the high adsorption capacity of CG. The removal of total phosphorus (TP), total nitrogen (TN), ammonia (NH4+-N) and chemical oxygen demand (COD) by CG modified bioretention systems was influenced by diverse rainfall conditions including rainfall concentration, recurrence period and drying period, and their removal rate ranged 94-99%, 30-70%, 83-97% and 33-86%, respectively. The effluent concentration of Zn, Pb and Cu was as low as 3.14-10.99 µg/L, 0.66-2.56 µg/L and 0.60-3.15 µg/L, respectively. In addition, CG could promote the plant heavy metal uptake and thus decrease their accumulation in soil to a certain extent. Meanwhile, Malondialdehyde (MDA) content and peroxidases (POD) activities of plants in CG modified bioretention were lower than that in tradition bioretention, indicating that CG could help plants recovery and lessened the oxidative stress for the negative impact of high heavy metals accumulation. CG-based media alleviated the inhibitory effect of rainwater runoff pollutant accumulation (especially heavy metals) on microbial diversity and the enhancement of the dominant bacteria (such as Proteobacteria and Bacteroidota) could conduce the nutrients removal in the bioretention systems. In overall, this study demonstrated that the CG modified bioretention systems show an excellent removal performance combine with biological effects.

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An in-depth understanding of the rainfall-runoff process is essential for effective stormwater management. However, the understanding of the hierarchy of rainfall characteristics in terms of their importance in influencing runoff generation is limited. This paper investigates the influence of rainfall characteristics and catchment characteristics on runoff generation in urban catchments. The outcomes showed that there are 4 dominant factors affecting runoff generation: total precipitation TP and maximum 60-min rainfall intensity MAX60 are the two top-ranked factors while average rainfall intensity RI and maximum 5-min rainfall intensity MAX5 are ranked second. Additionally, compared to the moderate rainfall regime (MR), the heavy rainfall regime (HR) tends to produce higher peak flow rates, higher total inflow per unit area, and lower runoff control effect. Note that the antecedent precipitation has a more significant effect on runoff generation and is even the dominant factor when rainstorm events with daily rainfall larger than 50 mm are not considered. The results of analyzing the influence of catchment characteristics suggest that only under HR regime conditions do the catchment characteristics have an impact on runoff generation and behave as smaller catchment areas, and higher proportions of green landscapes always lead lower peak flow rates, lower total inflows per unit area, and higher runoff control effects.

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Based on the runoff and sediment yield data from 59 erosive rainfall plots with different slope lengths (5, 10, 15, 20, 25 m) in Shiqiao small watershed of Guizhou Province from 2012 to 2014, we analyzed the relationship between runoff and sediment yield and slope length under diffe-rent rainfall conditions. The results showed that, with the increases of slope length, the runoff yield of slope showed a 'V-shape' pattern, the sediment yield of slope increased first and then decreased. According to rainfall amount, rainfall duration, and average rainfall intensity, the 59 erosive rainfall in the study area could be divided into three types, including type A with short duration, heavy rain intensity and small rainfall, type B with medium duration, light rain intensity and medium rainfall, and type C with long duration, medium rain intensity and large rainfall. The relationships between runoff and sediment yield and slope length were different under different rainfall patterns. There was about 20 m critical slope length of sediment yield under type A and B. The sediment yield gradually increased with the increases of slope length under type C. There was a good cubic function relationship between slope length and runoff and sediment yield under different rainfall patterns. The variable amplitude of runoff and sediment yield was different among different slope lengths. Except the slope length of 15-20 m, the variable amplitude of runoff and sediment yield under type C was relatively large. The variation amplitude of sediment yield was significantly higher than that under other rainfall patterns. The total runoff yield under different rainfall patterns was type A>B>C. The sediment yield under type B was the smallest, that of type A at the slope length of 20 m was the largest and that of type C at other slope lengths was the largest. The correlation between compound rainfall factors and runoff and sediment yield was better than that of single rainfall factor under type A (common rainfall type in the study area). Rainfall amount (P), the pro-duct of rainfall duration and maximum 30 min rainfall intensity (TI30), product of rainfall duration and average rainfall intensity (TI), product of rainfall amount and rainfall duration (PT) were significantly correlated with the runoff and sediment yield. Among those factors, P and TI had the strongest correlation with runoff. Further, the relationship between them and runoff under different slope lengths could be expressed by linear equation and S-curve. There was a good cubic function relationship between the sediment yield and its corresponding rainfall factors under different slope lengths.

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Rainfall and runoff characteristics may influence off-site export of pesticides into downstream aquatic ecosystems. However, the relationship between rainfall characteristics and pesticide export from small headwater catchments remains elusive due to confounding factors including the application dose and timing and the variation of pesticide stocks in soil. Here we examined the impact of rainfall characteristics on the export of copper (Cu), zinc (Zn) and 12 legacy and currently used synthetic pesticides in surface runoff from a headwater vineyard catchment. Cluster analysis of rainfall intensity, depth and duration of 78 events revealed four distinct rainfall categories, i.e., Small, Long, Moderate and Intense (p < 0.001). Event mean concentrations of pesticides did not differ among rainfall categories (p > 0.05). In contrast, event loads of both dissolved and solid-bound Cu and Zn significantly differed among rainfall categories (p < 0.001). Rainfall depth and intensity significantly correlated with both Cu and Zn loads in runoff (ρs = 0.33 to 0.92, p < 0.002), and might be the main drivers of Cu and Zn export at the catchment scale. In contrast, rainfall depth, intensity or duration did not influence the loads of synthetic pesticides in runoff, even when weekly variations of pesticide stocks in the soil were accounted for. However, intense rainfall-runoff events, that can fragment soil, may control the export of persistent and hydrophobic legacy pesticides stocks in the soil, such as simazine and tetraconazole. Our results show that rainfall characteristics controlled the off-site export of Cu, Zn and legacy synthetic pesticides in a small headwater catchment, whereas the application timing drove the export of currently used synthetic pesticides in runoff. We anticipate our results to be a preliminary step to forecast the influence of regional rainfall patterns on the export of both metallic and synthetic pesticides by surface runoff from small agricultural headwater catchments.

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Globally, fluvial heavy metal (HM) pollution has recently become an increasingly severe problem. However, few studies have investigated the variational characteristics of fluvial HMs after rain over long periods (≥1 year). The Dakan River in Xili Reservoir watershed (China) was selected as a case study to investigate pollution levels, influencing factors, and sources of HMs under different rainfall conditions during 2015 and 2016. Fluvial HMs showed evident spatiotemporal variations attributable to the coupled effects of pollution generation and rainfall diffusion. Fluvial HM concentrations were significantly associated with rainfall characteristics (e.g., rainfall intensity, rainfall amount, and antecedent dry period) and river flow, which influenced the generation and the transmission of fluvial HMs in various ways. Moreover, this interrelationship depended considerably on the HM type and particle size distribution. Mn, Pb, Cr, and Ni were major contributors to high values of the comprehensive pollution index; therefore, they should be afforded special attention. Additionally, quantitative source apportionment of fluvial HMs was conducted by combining principal component analysis with multiple linear regression and chemical mass balance models to obtain comprehensive source profiles. Finally, an environment-friendly control strategy coupling "source elimination" and "transport barriers" was proposed for aquatic environment protection.

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Urban road runoff contains pollutants such as particulate matters, organic chemicals, heavy metals, nutrients, oil and grease that can cause significant degradation of receiving water quality. Eliminating the pollutant mass loading of road runoff and protecting the receiving water bodies have been the focuses in environmental field in recent years. To accomplish pollutant reduction and develop a cost-effective treatment method, knowledge of water quality characteristics, as well as the pollutant effluent characteristics of road runoff is required. In order to investigate the impacts of rainfall characteristics and occurrence of pollutant on the variation of pollutant concentrations during the duration of runoff events and pollutant load effluent characteristics of road runoff, 207 road runoff samples in the durations of 13 storm events occurred at Taibai Interchange of the south second-ring road in Xi'an, Shaanxi province from July 2014 to September 2015 were collected by the manual time-interval sampling method, and concentrations of SS, COD, dissolved COD, Cu, dissolved Cu, Pb, dissolved Pb, Cr, dissolved Cr, Cd and dissolved Cd of the samples were determined. The results indicated that, the road runoff of Xi'an city was seriously polluted by SS and COD, which were the main contaminants in road runoff. Meanwhile, concentrations of Pb and Cr in road runoff were also at a high level. The variation of pollutant concentrations during the duration of runoff was closely related to rainfall characteristics and occurrence states of the pollutants. Emission of the dissolved pollutants was not affected by the type of rainfall. The concentration of the dissolved pollutants in the runoff reached a peak in the initial duration of runoff, and then, decreased continuously. However, the peak concentration of particulate pollutants in the runoff only occurred after the peak of sufficiently large rainfall intensity. The concentration of particulate pollutants in the runoff fluctuated sharply with the variation of rainfall intensity, and impacted by the rainfall duration and rainfall depth as well. Rainfall characteristics didn't have a great impact on the load emission of the dissolved pollutants, therefore, had a significant influence on the load emission of the particulate pollutants. Compared with the rainfall type Ⅲ, first flush effects of pollutant loads of SS, COD, Cu, Pb, Cr, Cd in rainfall type Ⅰand type Ⅱ were more obvious. Besides, first flush effect of pollutant loads was not ubiquitous. All the pollutants in the monitoring 13 runoff events didn't exhibit an obvious first flush effect. The descending order of the first flush effect of those pollutants was COD, SS, dissolved COD, Cu, Pb, Cr, dissolved Cu, Cd, dissolved Pb, dissolved Cr, dissolved Cd.

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Understanding the particle size distribution (PSD) of sediment in urban runoff assists in the selection of appropriate treatment systems for sediment removal as systems vary in their ability to remove sediment across different particle size fractions. Variation in PSD in runoff from individual urban surfaces both during and across multiple rain events is not well understood and it may lead to performance uncertainty in treatment systems. Runoff PSDs in international literature were compiled to provide a comparative summary of PSDs from different urban surfaces. To further assess both intra-event and inter-event PSD variation, untreated runoff was collected from road, concrete roof, copper roof, and galvanized roof surfaces within an urban catchment exposed to the same rainfall conditions and analysed for PSD and total suspended solids (TSS). Road runoff had the highest TSS concentrations, while copper roofs had high initial TSS that reduced to very low levels under steady state conditions. Despite variation in TSS concentrations, the median particle diameter of the TSS was comparable across the surfaces. Intra-event variation was generally not significant, but substantial inter-event variation was observed, particularly for coarser road and concrete roof surfaces. PSD variation for each surface contributed to a wide range in predicted treatment performance and suggests that short-retention treatment devices carry a high performance risk of not being able to achieve adequate TSS removal across all rain events.

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Atmospheric pollutants deposited on impermeable surfaces can be an important source of pollutants to stormwater runoff; however, modelling atmospheric pollutant loads in runoff has rarely been done, because of the challenges and uncertainties in monitoring their contribution. To overcome this, impermeable concrete boards (≈ 1m(2)) were deployed for 11 months in different locations within an urban area (industrial, residential and airside) throughout Christchurch, New Zealand, to capture spatially distributed atmospheric deposition loads in runoff over varying meteorological conditions. Runoff was analysed for total and dissolved Cu, Zn, Pb, and total suspended solids (TSS). Mixed-effect regression models were developed to simulate atmospheric pollutant loads in stormwater runoff. In addition, the models were used to explain the influence of different meteorological characteristics (e.g. antecedent dry days and rain depth) on pollutant build-up and wash-off dynamics. The models predicted approximately 53% to 69% of the variation in pollutant loads and were successful in predicting pollutant-load trends over time which can be useful for general stormwater planning processes. Results from the models illustrated the importance of antecedent dry days on pollutant build-up. Furthermore, results indicated that peak rainfall intensity and rain duration had a significant relationship with TSS and total Pb, whereas, rain depth had a significant relationship with total Cu and total Zn. This suggested that the pollutant speciation phase plays an important role in surface wash-off. Rain intensity and duration had a greater influence when the pollutants were predominantly in their particulate phase. Conversely, rain depth exerted a greater influence when a high fraction of the pollutants were predominantly in their dissolved phase. For all pollutants, the models were represented by a log-arctan relationship for pollutant build-up and a log-log relationship for pollutant wash-off. The modelling approach enables the site-specific relationships between individual pollutants and rainfall characteristics to be investigated.

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Treatment performance of bioretention basins closely depends on hydrologic and hydraulic factors such as rainfall characteristics and inflow and outflow discharges. An in-depth understanding of the influence of these factors on water quality treatment performance can provide important guidance for effective bioretention basin design. In this paper, hydraulic and hydrologic factors impacting pollutant removal by a bioretention basin were assessed under field conditions. Outcomes of the study confirmed that the antecedent dry period plays an important role in influencing treatment performance. A relatively long antecedent dry period reduces nitrite and ammonium concentrations while increasing the nitrate concentration, which confirms that nitrification occurs within the bioretention basin. Additionally, pollutant leaching influences bioretention basin treatment performance, reducing the nutrients removal efficiency, which was lower for high rainfall events. These outcomes will contribute to a greater understanding of the treatment performance of bioretention basins, assisting in the design, operation and maintenance of these systems.

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The validity of using rainfall characteristics as lumped parameters for investigating the pollutant wash-off process such as first flush occurrence is questionable. This research study introduces an innovative concept of using sector parameters to investigate the relationship between the pollutant wash-off process and different sectors of the runoff hydrograph and rainfall hyetograph. The research outcomes indicated that rainfall depth and rainfall intensity are two key rainfall characteristics which influence the wash-off process compared to the antecedent dry period. Additionally, the rainfall pattern also plays a critical role in the wash-off process and is independent of the catchment characteristics. The knowledge created through this research study provides the ability to select appropriate rainfall events for stormwater quality treatment design based on the required treatment outcomes such as the need to target different sectors of the runoff hydrograph or pollutant species. The study outcomes can also contribute to enhancing stormwater quality modelling and prediction in view of the fact that conventional approaches to stormwater quality estimation is primarily based on rainfall intensity rather than considering other rainfall parameters or solely based on stochastic approaches irrespective of the characteristics of the rainfall event.

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