Automated screening of control potential with spatially explicit results to support dialogue about sewer overflow reduction and beyond

For real-time control to become a standard measure for upgrading urban drainage systems, control potential screenings need to be easily integrated into the early planning processes that already take place. However, current screening methods are either not aligned with the present planning process, unrelatable for water managers or too time-consuming. We therefore developed an automated screening methodology through a co-design process with six Danish utilities. The process started out from a literature review, included interviews and workshops, and resulted in the control potential screening tool COPOTO. In the co-design process, utilities generally responded that indicators based solely on an assessment of static system attributes are insufficient. Thus, COPOTO instead post-processes the results of urban drainage simulation models that are commonly available. The decision context considered in initial planning phases was found to include environmental, economic, social and technical objectives that were highly case-dependent. When presenting CSO reduction potentials, the utilities therefore generally preferred interactive, spatially explicit visualisations that link the CSO reduction at a particular location to the storages and actuators that need to be activated. This enables water managers to discuss, for example, operational constraints of a considered control location. COPOTO provides such assessments with very limited manual and computational effort and thus facilitates the integration of real-time control into standard planning workflows of utilities.

Temporal variations in micropollutant inlet concentrations matter when planning the design and compliance assessment of stormwater control measures

Stormwater Control Measures (SCMs) contribute to reducing micropollutant emissions from separate sewer systems. SCM planning and design are often performed by looking at the hydrological performance. Assessment of pollutant removal and the ability to comply with discharge concentration limits is often simplified due to a lack of data and limited monitoring resources. This study analyses the impact of using different time resolutions of input stormwater concentrations when assessing the compliance of SCMs against water quality standards. The behaviour of three indicator micropollutants (MP - Copper, Diuron, Benzo[a]pyrene) was assessed in four SCM archetypes, which were defined to represent typical SCM removal processes. High resolution MP data were extrapolated by using high resolution (2 min) measurements of TSS over a long period (343 events). The compliance assessment showed that high resolution input concentrations can result in a different level of compliance with water quality standards, especially when discharged concentrations are close to the limit values. This study underlines the importance of considering the high temporal variability of stormwater micropollutants when planning and designing SCMs to identify the most effective solutions for stormwater pollution management and to ensure a thorough consideration of all the environmental implications.

A decade of monitoring micropollutants in urban wet-weather flows: What did we learn?

Urban wet-weather discharges from combined sewer overflows (CSO) and stormwater outlets (SWO) are a potential pathway for micropollutants (trace contaminants) to surface waters, posing a threat to the environment and possible water reuse applications. Despite large efforts to monitor micropollutants in the last decade, the gained information is still limited and scattered. In a metastudy we performed a data-driven analysis of measurements collected at 77 sites (683 events, 297 detected micropollutants) over the last decade to investigate which micropollutants are most relevant in terms of 1) occurrence and 2) potential risk for the aquatic environment, 3) estimate the minimum number of data to be collected in monitoring studies to reliably obtain concentration estimates, and 4) provide recommendations for future monitoring campaigns. We highlight micropollutants to be prioritized due to their high occurrence and critical concentration levels compared to environmental quality standards. These top-listed micropollutants include contaminants from all chemical classes (pesticides, heavy metals, polycyclic aromatic hydrocarbons, personal care products, pharmaceuticals, and industrial and household chemicals). Analysis of over 30,000 event mean concentrations shows a large fraction of measurements (> 50%) were below the limit of quantification, stressing the need for reliable, standard monitoring procedures. High variability was observed among events and sites, with differences between micropollutant classes. The number of events required for a reliable estimate of site mean concentrations (error bandwidth of 1 around the "true" value) depends on the individual micropollutant. The median minimum number of events is 7 for CSO (2 to 31, 80%-interquantile) and 6 for SWO (1 to 25 events, 80%-interquantile). Our analysis indicates the minimum number of sites needed to assess global pollution levels and our data collection and analysis can be used to estimate the required number of sites for an urban catchment. Our data-driven analysis demonstrates how future wet-weather monitoring programs will be more effective if the consequences of high variability inherent in urban wet-weather discharges are considered.

Classifying pollutant flush signals in stormwater using functional data analysis on TSS MV curves

Pollution levels in stormwater vary significantly during rain events, with pollutant flushes carrying a major fraction of an event pollutant load in a short period. Understanding these flushes is thus essential for stormwater management. However, current studies mainly focus on describing the first flush or are limited by predetermined flush categories. This study provides a new perspective on the topic by applying data-driven approaches to categorise Mass Volume (MV) curves for TSS into distinct classes of flush tailored to specific monitoring location. Functional Data Analysis (FDA) was used to investigate the dynamics of MV curves in two large data sets, consisting of 343 measured events and 915 modelled events, respectively. Potential links between classes of MV curves and combinations of rain characteristics were explored through a priori clustering. This yielded correct class assignments for 23-63% of the events using different combinations of MV curve clustering and rainfall characteristics. This suggests that while global rainfall characteristics influence flush, they are not sufficient as sole explanatory variables of different flush phenomena, and additional explanatory variables are needed to assign MV curves into classes with a predictive power that is suitable for e.g. design of stormwater control measures. Our results highlight the great potential of the FDA methodology as a new approach for classifying, describing, and understanding pollutant flush signals in stormwater.

Using multi-event hydrologic and hydraulic signatures from water level sensors to diagnose locations of uncertainty in integrated urban drainage models used in living digital twins

Digital twins of urban drainage systems require simulation models that can adequately replicate the physical system. All models have their limitations, and it is important to investigate when and where simulation results are acceptable and to communicate the level of performance transparently to end users. This paper first defines a classification of four possible 'locations of uncertainty' in integrated urban drainage models. It then develops a structured framework for identifying and diagnosing various types of errors. This framework compares model outputs with in-sewer water level observations based on hydrologic and hydraulic signatures. The approach is applied on a real case study in Odense, Denmark, with examples from three different system sites: a typical manhole, a small flushing chamber, and an internal overflow structure. This allows diagnosing different model errors ranging from issues in the underlying asset database and missing hydrologic processes to limitations in the model software implementation. Structured use of signatures is promising for continuous, iterative improvements of integrated urban drainage models. It also provides a transparent way to communicate the level of model adequacy to end users.

Prioritize effluent quality, operational costs or global warming? - Using predictive control of wastewater aeration for flexible management of objectives in WRRFs

This study presents a general model predictive control (MPC) algorithm for optimizing wastewater aeration in Water Resource Recovery Facilities (WRRF) under different management objectives. The flexibility of the MPC is demonstrated by controlling a WRRF under four management objectives, aiming at minimizing: (A) effluent concentrations, (B) electricity consumption, (C) total operations costs (sum electricity costs and discharge effluent tax) or (D) global warming potential (direct and indirect nitrous oxide emissions, and indirect from electricity production) . The MPC is tested with data from the alternating WRRF in Nørre Snede (Denmark) and from the Danish electricity grid. Results showed how the four control objectives resulted in important differences in aeration patterns and in the concentration dynamics over a day. Controls B and C showed similarities when looking at total costs, while similarities in global warming potential for controls A and D suggest that improving effluent quality also reduced greenhouse gasses emissions. The MPC flexibility in handling different objectives is shown by using a combined objective function, optimizing both cost and greenhouse emissions. This shows the trade-off between the two objectives, enabling the calculation of marginal costs and thus allowing WRRF operators to carefully evaluate prioritization of management objectives. The long-term MPC performance is evaluated over 51 days covering seasonal and inter-weekly variations. On a daily basis, control A was 9-30% cheaper on average compared to controls A, D and to the current rule-based control. Similarly, control D resulted on average in 35-43% lower greenhouse gasses daily emission compared to the other controls. Difference between control performance increased for days with greater inter-diurnal variations in electricity price or greenhouse emissions from electricity production, i.e. when MPC has greater possibilities for exploiting input variations. The flexibility of the proposed MPC can easily accommodate for additional control objectives, allowing WRRF operators to quickly adapt the plant operation to new management objectives and to face new performance requirements.

Integrated model predictive control of water resource recovery facilities and sewer systems in a smart grid: example of full-scale implementation in Kolding

An integrated model predictive control (MPC) strategy to control the power consumption and the effluent quality of a water resource recovery facility (WRRF) by utilizing the storage capacity from the sewer system was implemented and put into operation for a 7-day trial period. This price-based MPC reacted to electricity prices and forecasted pollutant loads 24 hours ahead. The large storage capacity available in the sewer system directly upstream from the plant was used to control the incoming loads and, indirectly, the power consumption of the WRRF during dry weather operations. The MPC balances electricity costs and treatment quality based on linear dynamical models and predictions of storage capacity and effluent concentrations. This article first shows the modelling results involved in the design of this MPC. Secondly, results from full-scale MPC operation of the WRRF are shown. The monetary savings of the MPC strategy for the specific plant were quantified around approximately 200 DKK per day when fully exploiting the allowed storage capacity. The developed MPC strategy provides a new option for linking WRRFs to smart grid electricity systems.

Evaluating the performance of a simple phenomenological model for online forecasting of ammonium concentrations at WWTP inlets

A simple model for online forecasting of ammonium (NH₄ ⁺) concentrations in sewer systems is proposed. The forecast model utilizes a simple representation of daily NH₄ ⁺ profiles and the dilution approach combined with information from online NH₄ ⁺ and flow sensors. The method utilizes an ensemble approach based on past observations to create model prediction bounds. The forecast model was tested against observations collected at the inlet of two wastewater treatment plants (WWTPs) over an 11-month period. NH₄ ⁺ data were collected with ion-selective sensors. The model performance evaluation focused on applications in relation to online control strategies. The results of the monitoring campaigns highlighted a high variability in daily NH₄ ⁺ profiles, stressing the importance of an uncertainty-based modelling approach. The maintenance of the NH₄ ⁺ sensors resulted in important variations of the sensor signal, affecting the evaluation of the model structure and its performance. The forecast model succeeded in providing outputs that potentially can be used for integrated control of wastewater systems. This study provides insights on full scale application of online water quality forecasting models in sewer systems. It also highlights several research gaps which - if further investigated - can lead to better forecasts and more effective real-time operations of sewer and WWTP systems.

Robust model for estimating pumping station characteristics and sewer flows from standard pumping station data

Flow data represent crucial input for reliable diagnostics of sewer functions and identification of potential problems such as unwanted inflow and infiltration. Flow estimates from pumping stations, which are an integral part of most separate sewer systems, might help in this regard. A robust model and an associated optimization procedure is proposed for estimating inflow to a pumping station using only registered water levels in the pump sump and power consumption. The model was successfully tested on one month of data from a single upstream station. The model is suitable for identification of pump capacity and volume thresholds for switching the pump on and off. These are parameters which are required for flow estimation during periods with high inflows or during periods with flow conditions triggering pump switching on and off at frequencies close to the temporal resolution of monitored data. The model is, however, sensitive within the transition states between emptying and filling to observation errors in volume and on inflow/outflow variability.

Towards model predictive control: online predictions of ammonium and nitrate removal by using a stochastic ASM

Online model predictive control (MPC) of water resource recovery facilities (WRRFs) requires simple and fast models to improve the operation of energy-demanding processes, such as aeration for nitrogen removal. Selected elements of the activated sludge model number 1 modelling framework for ammonium and nitrate removal were included in discretely observed stochastic differential equations in which online data are assimilated to update the model states. This allows us to produce model-based predictions including uncertainty in real time while it also reduces the number of parameters compared to many detailed models. It introduces only a small residual error when used to predict ammonium and nitrate concentrations in a small recirculating WRRF facility. The error when predicting 2 min ahead corresponds to the uncertainty from the sensors. When predicting 24 hours ahead the mean relative residual error increases to ∼10% and ∼20% for ammonium and nitrate concentrations respectively. Consequently this is considered a first step towards stochastic MPC of the aeration process. Ultimately this can reduce electricity demand and cost for water resource recovery, allowing the prioritization of aeration during periods of cheaper electricity.

Definitions of event magnitudes, spatial scales, and goals for climate change adaptation and their importance for innovation and implementation

We examine how core professional and institutional actors in the innovation system conceptualize climate change adaptation in regards to pluvial flooding-and how this influences innovation. We do this through a qualitative case study in Copenhagen with interconnected research rounds, including 32 semi-structured interviews, to strengthen the interpretation and analysis of qualitative data. We find that the term "climate change adaptation" currently has no clearly agreed definition in Copenhagen; instead, different actors use different conceptualizations of climate change adaptation according to the characteristics of their specific innovation and implementation projects. However, there is convergence among actors towards a new cognitive paradigm, whereby economic goals and multifunctionality are linked with cost-benefit analyses for adapting to extreme rain events on a surface water catchment scale. Differences in definitions can lead to both successful innovation and to conflict, and thus they affect the city's capacity for change. Our empirical work suggests that climate change adaptation can be characterized according to three attributes: event magnitudes (everyday, design, and extreme), spatial scales (small/local, medium/urban, and large/national-international), and (a wide range of) goals, thereby resulting in different technology choices.

Effect of climate change on stormwater runoff characteristics and treatment efficiencies of stormwater retention ponds: a case study from Denmark using TSS and Cu as indicator pollutants

This study investigated the potential effect of climate changes on stormwater pollution runoff characteristics and the treatment efficiency of a stormwater retention pond in a 95 ha catchment in Denmark. An integrated dynamic stormwater runoff quality and treatment model was used to simulate two scenarios: one representing the current climate and another representing a future climate scenario with increased intensity of extreme rainfall events and longer dry weather periods. 100-year long high-resolution rainfall time series downscaled from regional climate model projections were used as input. The collected data showed that total suspended solids (TSS) and total copper (Cu) concentrations in stormwater runoff were related to flow, rainfall intensity and antecedent dry period. Extreme peak intensities resulted in high particulate concentrations and high loads but did not affect dissolved Cu concentrations. The future climate simulations showed an increased frequency of higher flows and increased total concentrations discharged from the catchment. The effect on the outlet from the pond was an increase in the total concentrations (TSS and Cu), whereas no major effect was observed on dissolved Cu concentrations. Similar results are expected for other particle bound pollutants including metals and slowly biodegradable organic substances such as PAH. Acute toxicity impacts to downstream surface waters seem to be only slightly affected. A minor increase in yearly loads of sediments and particle-bound pollutants is expected, mainly caused by large events disrupting the settling process. This may be important to consider for the many stormwater retention ponds existing in Denmark and across the world.

Evaluation of stormwater micropollutant source control and end-of-pipe control strategies using an uncertainty-calibrated integrated dynamic simulation model

The estimation of micropollutant (MP) fluxes in stormwater systems is a fundamental prerequisite when preparing strategies to reduce stormwater MP discharges to natural waters. Dynamic integrated models can be important tools in this step, as they can be used to integrate the limited data provided by monitoring campaigns and to evaluate the performance of different strategies based on model simulation results. This study presents an example where six different control strategies, including both source-control and end-of-pipe treatment, were compared. The comparison focused on fluxes of heavy metals (copper, zinc) and organic compounds (fluoranthene). MP fluxes were estimated by using an integrated dynamic model, in combination with stormwater quality measurements. MP sources were identified by using GIS land usage data, runoff quality was simulated by using a conceptual accumulation/washoff model, and a stormwater retention pond was simulated by using a dynamic treatment model based on MP inherent properties. Uncertainty in the results was estimated with a pseudo-Bayesian method. Despite the great uncertainty in the MP fluxes estimated by the runoff quality model, it was possible to compare the six scenarios in terms of discharged MP fluxes, compliance with water quality criteria, and sediment accumulation. Source-control strategies obtained better results in terms of reduction of MP emissions, but all the simulated strategies failed in fulfilling the criteria based on emission limit values. The results presented in this study shows how the efficiency of MP pollution control strategies can be quantified by combining advanced modeling tools (integrated stormwater quality model, uncertainty calibration).

Modelling the impact of retention-detention units on sewer surcharge and peak and annual runoff reduction

Stormwater management using water sensitive urban design is expected to be part of future drainage systems. This paper aims to model the combination of local retention units, such as soakaways, with subsurface detention units. Soakaways are employed to reduce (by storage and infiltration) peak and volume stormwater runoff; however, large retention volumes are required for a significant peak reduction. Peak runoff can therefore be handled by combining detention units with soakaways. This paper models the impact of retrofitting retention-detention units for an existing urbanized catchment in Denmark. The impact of retrofitting a retention-detention unit of 3.3 m³/100 m² (volume/impervious area) was simulated for a small catchment in Copenhagen using MIKE URBAN. The retention-detention unit was shown to prevent flooding from the sewer for a 10-year rainfall event. Statistical analysis of continuous simulations covering 22 years showed that annual stormwater runoff was reduced by 68-87%, and that the retention volume was on average 53% full at the beginning of rain events. The effect of different retention-detention volume combinations was simulated, and results showed that allocating 20-40% of a soakaway volume to detention would significantly increase peak runoff reduction with a small reduction in the annual runoff.

A new settling velocity model to describe secondary sedimentation

Secondary settling tanks (SSTs) are the most hydraulically sensitive unit operations in biological wastewater treatment plants. The maximum permissible inflow to the plant depends on the efficiency of SSTs in separating and thickening the activated sludge. The flow conditions and solids distribution in SSTs can be predicted using computational fluid dynamics (CFD) tools. Despite extensive studies on the compression settling behaviour of activated sludge and the development of advanced settling velocity models for use in SST simulations, these models are not often used, due to the challenges associated with their calibration. In this study, we developed a new settling velocity model, including hindered, transient and compression settling, and showed that it can be calibrated to data from a simple, novel settling column experimental set-up using the Bayesian optimization method DREAM(ZS). In addition, correlations between the Herschel-Bulkley rheological model parameters and sludge concentration were identified with data from batch rheological experiments. A 2-D axisymmetric CFD model of a circular SST containing the new settling velocity and rheological model was validated with full-scale measurements. Finally, it was shown that the representation of compression settling in the CFD model can significantly influence the prediction of sludge distribution in the SSTs under dry- and wet-weather flow conditions.

Significance of settling model structures and parameter subsets in modelling WWTPs under wet-weather flow and filamentous bulking conditions

Current research focuses on predicting and mitigating the impacts of high hydraulic loadings on centralized wastewater treatment plants (WWTPs) under wet-weather conditions. The maximum permissible inflow to WWTPs depends not only on the settleability of activated sludge in secondary settling tanks (SSTs) but also on the hydraulic behaviour of SSTs. The present study investigates the impacts of ideal and non-ideal flow (dry and wet weather) and settling (good settling and bulking) boundary conditions on the sensitivity of WWTP model outputs to uncertainties intrinsic to the one-dimensional (1-D) SST model structures and parameters. We identify the critical sources of uncertainty in WWTP models through global sensitivity analysis (GSA) using the Benchmark simulation model No. 1 in combination with first- and second-order 1-D SST models. The results obtained illustrate that the contribution of settling parameters to the total variance of the key WWTP process outputs significantly depends on the influent flow and settling conditions. The magnitude of the impact is found to vary, depending on which type of 1-D SST model is used. Therefore, we identify and recommend potential parameter subsets for WWTP model calibration, and propose optimal choice of 1-D SST models under different flow and settling boundary conditions. Additionally, the hydraulic parameters in the second-order SST model are found significant under dynamic wet-weather flow conditions. These results highlight the importance of developing a more mechanistic based flow-dependent hydraulic sub-model in second-order 1-D SST models in the future.

Aeration tank settling and real time control as a tool to improve the hydraulic capacity and treatment efficiency during wet weather: results from 7 years' full-scale operational data

This paper investigates the aeration tank settling (ATS) operation in combination with real time control (RTC) as a tool for increasing the hydraulic capacity and improving the treatment efficiency of a wastewater treatment plant (WWTP) during wet weather flows. Results from 7 years' full-scale operational data at the Avedøre WWTP, Denmark, show that ATS operation in combination with RTC increases the hydraulic capacity of the treatment plant with up to 150 and 67% of the design capacity during winter and summer respectively. Compared to the conventional wet weather operation, the ATS in combination with RTC operation resulted in lower effluent concentrations for total phosphate (40-50%), suspended solids (30-60%) and chemical oxygen demand (30-50%), whereas no significant effect was observed on total nitrogen. Apart from the reduced effluent concentrations, the RTC resulted in economic savings in the form of reduced costs for electricity and green taxes. However, in very few cases the ATS operation in combination with RTC was not able to handle design capacity, and some overflows occurred at flows below the design capacity. The frequency of these overflows may increase in the future due to increased rain intensity resulting in shorter prediction time available for ATS.

Urban drainage models--simplifying uncertainty analysis for practitioners

There is increasing awareness about uncertainties in the modelling of urban drainage systems and, as such, many new methods for uncertainty analyses have been developed. Despite this, all available methods have limitations which restrict their widespread application among practitioners. Here, a modified Monte-Carlo based method is presented that reduces the subjectivity inherent in typical uncertainty approaches (e.g. cut-off thresholds), while using tangible concepts and providing practical outcomes for practitioners. The method compares the model's uncertainty bands to the uncertainty inherent in each measured/observed datapoint; an issue that is commonly overlooked in the uncertainty analysis of urban drainage models. This comparison allows the user to intuitively estimate the optimum number of simulations required to conduct uncertainty analyses. The output of the method includes parameter probability distributions (often used for sensitivity analyses) and prediction intervals. To demonstrate the new method, it is applied to a conceptual rainfall-runoff model (MOPUS) using a dataset collected from Melbourne, Australia.

Comparison of short-term rainfall forecasts for model-based flow prediction in urban drainage systems

Forecast-based flow prediction in drainage systems can be used to implement real-time control of drainage systems. This study compares two different types of rainfall forecast - a radar rainfall extrapolation-based nowcast model and a numerical weather prediction model. The models are applied as input to an urban runoff model predicting the inlet flow to a waste water treatment plant. The modelled flows are auto-calibrated against real-time flow observations in order to certify the best possible forecast. Results show that it is possible to forecast flows with a lead time of 24 h. The best performance of the system is found using the radar nowcast for the short lead times and the weather model for larger lead times.

Modelling and monitoring of integrated urban wastewater systems: review on status and perspectives

While the general principles and modelling approaches for integrated management/modelling of urban water systems already present a decade ago still hold, in recent years aspects like model interfacing and wastewater treatment plant (WWTP) influent generation as complements to sewer modelling have been investigated and several new or improved systems analysis methods have become available. New/improved software tools coupled with the current high computational capacity have enabled the application of integrated modelling to several practical cases, and advancements in monitoring water quantity and quality have been substantial and now allow the collecting of data in sufficient quality and quantity to permit using integrated models for real-time applications too. Further developments are warranted in the field of data quality assurance and efficient maintenance.

State-space adjustment of radar rainfall and skill score evaluation of stochastic volume forecasts in urban drainage systems

Merging of radar rainfall data with rain gauge measurements is a common approach to overcome problems in deriving rain intensities from radar measurements. We extend an existing approach for adjustment of C-band radar data using state-space models and use the resulting rainfall intensities as input for forecasting outflow from two catchments in the Copenhagen area. Stochastic grey-box models are applied to create the runoff forecasts, providing us with not only a point forecast but also a quantification of the forecast uncertainty. Evaluating the results, we can show that using the adjusted radar data improves runoff forecasts compared with using the original radar data and that rain gauge measurements as forecast input are also outperformed. Combining the data merging approach with short-term rainfall forecasting algorithms may result in further improved runoff forecasts that can be used in real time control.

Comparing the impact of time displaced and biased precipitation estimates for online updated urban runoff models

When an online runoff model is updated from system measurements, the requirements of the precipitation input change. Using rain gauge data as precipitation input there will be a displacement between the time when the rain hits the gauge and the time where the rain hits the actual catchment, due to the time it takes for the rain cell to travel from the rain gauge to the catchment. Since this time displacement is not present for system measurements the data assimilation scheme might already have updated the model to include the impact from the particular rain cell when the rain data is forced upon the model, which therefore will end up including the same rain twice in the model run. This paper compares forecast accuracy of updated models when using time displaced rain input to that of rain input with constant biases. This is done using a simple time-area model and historic rain series that are either displaced in time or affected with a bias. The results show that for a 10 minute forecast, time displacements of 5 and 10 minutes compare to biases of 60 and 100%, respectively, independent of the catchments time of concentration.

Model-based monitoring of stormwater runoff quality

Monitoring of micropollutants (MP) in stormwater is essential to evaluate the impacts of stormwater on the receiving aquatic environment. The aim of this study was to investigate how different strategies for monitoring of stormwater quality (combining a model with field sampling) affect the information obtained about MP discharged from the monitored system. A dynamic stormwater quality model was calibrated using MP data collected by automatic volume-proportional sampling and passive sampling in a storm drainage system on the outskirts of Copenhagen (Denmark) and a 10-year rain series was used to find annual average (AA) and maximum event mean concentrations. Use of this model reduced the uncertainty of predicted AA concentrations compared to a simple stochastic method based solely on data. The predicted AA concentration, obtained by using passive sampler measurements (1 month installation) for calibration of the model, resulted in the same predicted level but with narrower model prediction bounds than by using volume-proportional samples for calibration. This shows that passive sampling allows for a better exploitation of the resources allocated for stormwater quality monitoring.

Quantification of uncertainty in modelled partitioning and removal of heavy metals (Cu, Zn) in a stormwater retention pond and a biofilter

Strategies for reduction of micropollutant (MP) discharges from stormwater drainage systems require accurate estimation of the potential MP removal in stormwater treatment systems. However, the high uncertainty commonly affecting stormwater runoff quality modelling also influences stormwater treatment models. This study identified the major sources of uncertainty when estimating the removal of copper and zinc in a retention pond and a biofilter by using a conceptual dynamic model which estimates MP partitioning between the dissolved and particulate phases as well as environmental fate based on substance-inherent properties. The two systems differ in their main removal processes (settling and filtration/sorption, respectively) and in the time resolution of the available measurements (composite samples and pollutographs). The most sensitive model factors, identified by using Global Sensitivity Analysis (GSA), were related to the physical characteristics of the simulated systems (flow and water losses) and to the fate processes related to Total Suspended Solids (TSS). The model prediction bounds were estimated by using the Generalized Likelihood Uncertainty Estimation (GLUE) technique. Composite samples and pollutographs produced similar prediction bounds for the pond and the biofilter, suggesting a limited influence of the temporal resolution of samples on the model prediction bounds. GLUE highlighted model structural uncertainty when modelling the biofilter, due to disregard of plant-driven evapotranspiration, underestimation of sorption and neglect of oversaturation with respect to minerals/salts. The results of this study however illustrate the potential for the application of conceptual dynamic fate models base on substance-inherent properties, in combination with available datasets and statistical methods, to estimate the MP removal in different stormwater treatment systems and compare with environmental quality standards targeting the dissolved MP fraction.

Partitioning of fluoranthene between free and bound forms in stormwater runoff and other urban discharges using passive dosing

Partitioning of fluoranthene in stormwater runoff and other urban discharges was measured by a new analytical method based on passive dosing. Samples were collected at the inlet (n = 11) and outlet (n = 8) from a stormwater retention pond in Albertslund (Denmark), and for comparison samples were also obtained at a municipal wastewater treatment plant, a power plant, a contaminated site and a waste deposit in Copenhagen (n = 1 at each site). The freely dissolved concentration of (14)C-fluoranthene in the samples was controlled by equilibrium partitioning from a pre-loaded polymer and the total sample concentration measured. The measurements yielded free fractions of fluoranthene in stormwater in the range 0.04-0.15 in the inlet during the first part of the runoff events increasing to 0.3-0.5 at the end of the events and in the outlet from the retention pond. The enhanced capacity of the different stormwater samples for carrying fluoranthene was 2-23 relative to pure water and decreasing during rain events. The enhanced capacity of stormwater showed a different relationship with suspended solid concentrations than the other types of urban discharges. Partitioning of fluoranthene to dissolved organic carbon was lower than partitioning to particulate organic carbon. Partitioning of fluoranthene to particulate organic matter in the 19 stormwater samples yielded a log K(POM) of 5.18. The presented results can be used in stormwater quality modeling and assessment of efficiency of stormwater treatment systems. This work also shows the potential of the passive dosing method to obtain conversion factors between total concentrations, which are needed for comparison with water quality criteria, and freely dissolved concentrations, which are more related to toxicity and obtained by the use of most passive samplers.

A source classification framework supporting pollutant source mapping, pollutant release prediction, transport and load forecasting, and source control planning for urban environments

PURPOSE

Implementation of current European environmental legislation such as the Water Framework Directive requires access to comprehensive, well-structured pollutant source and release inventories. The aim of this work was to develop a Source Classification Framework (SCF) ideally suited for this purpose.

METHODS

Existing source classification systems were examined by a multidisciplinary research team, and an optimised SCF was developed. The performance and usability of the SCF were tested using a selection of 25 chemicals listed as priority pollutants in Europe.

RESULTS

The SCF is structured in the form of a relational database and incorporates both qualitative and quantitative source classification and release data. The system supports a wide range of pollution monitoring and management applications. The SCF functioned well in the performance test, which also revealed important gaps in priority pollutant release data.

CONCLUSIONS

The SCF provides a well-structured approach for European pollutant source and release classification and management. With further optimisation and demonstration testing, the SCF has the potential to be fully implemented throughout Europe.

A conceptual framework for addressing complexity and unfolding transition dynamics when developing sustainable adaptation strategies in urban water management

To achieve a successful and sustainable adaptation to climate change we need to transform the way we think about change. Much water management research has focused on technical innovation with a range of new solutions developed to achieve a 'more sustainable and integrated urban water management cycle'. But Danish municipalities and utility companies are struggling to bring such solutions into practice. 'Green infrastructure', for example, requires the consideration of a larger range of aspects related to the urban context than the traditional urban water system optimization. There is the need for standardized methods and guidelines to organize transdisciplinary processes where different types of knowledge and perspectives are taken into account. On the basis of the macro-meso-micro pattern inspired by complexity science and transition theory, we developed a conceptual framework to organize processes addressing the complexity characterizing urban water management in the context of climate change. In this paper the framework is used to organize a research process aiming at understanding and unfolding urban dynamics for sustainable transition. The final goal is to enable local authorities and utilities to create the basis for managing and catalysing the technical and organizational innovation necessary for a sustainable transition towards climate change adaptation in urban areas.

Uncertainty-based calibration and prediction with a stormwater surface accumulation-washoff model based on coverage of sampled Zn, Cu, Pb and Cd field data

A dynamic conceptual and lumped accumulation wash-off model (SEWSYS) is uncertainty-calibrated with Zn, Cu, Pb and Cd field data from an intensive, detailed monitoring campaign. We use the generalized linear uncertainty estimation (GLUE) technique in combination with the Metropolis algorithm, which allows identifying a range of behavioral model parameter sets. The small catchment size and nearness of the rain gauge justified excluding the hydrological model parameters from the uncertainty assessment. Uniform, closed prior distributions were heuristically specified for the dry and wet removal parameters, which allowed using an open not specified uniform prior for the dry deposition parameter. We used an exponential likelihood function based on the sum of squared errors between observed and simulated event masses and adjusted a scaling factor to cover 95% of the observations within the empirical 95% model prediction bounds. A positive correlation between the dry deposition and the dry (wind) removal rates was revealed as well as a negative correlation between the wet removal (wash-off) rate and the ratio between the dry deposition and wind removal rates, which determines the maximum pool of accumulated metal available on the conceptual catchment surface. Forward Monte Carlo analysis based on the posterior parameter sets covered 95% of the observed event mean concentrations, and 95% prediction quantiles for site mean concentrations were estimated to 470 μg/l ± 20% for Zn, 295 μg/l ± 40% for Cu, 20 μg/l ± 80% for Pb and 0.6 μg/l ± 35% for Cd. This uncertainty-based calibration procedure adequately describes the prediction uncertainty conditioned on the used model and data, but seasonal and site-to-site variation is not considered, i.e. predicting metal concentrations in stormwater runoff from gauged as well as ungauged catchments with the SEWSYS model is generally more uncertain than the indicated numbers.

Water management in cities of the future using emission control strategies for priority hazardous substances

Cities of the future face challenges with respect to the quantity and quality of water resources, and multiple managerial options need to be considered in order to safeguard urban surface water quality. In a recently completed project on 'Source control options for reducing emissions of Priority Pollutants' (ScorePP), seven emission control strategies (ECSs) were developed and tested within a semi-hypothetical case city (SHCC) to evaluate their potential to reduce the emission of selected European priority hazardous substances (PHSs) to surface waters. The ECSs included (1) business-as-usual, (2) full implementation of relevant European (EU) directives, (3) ECS2 in combination with voluntary options for household, municipalities and industry, (4) ECS2 combined with industrial treatment and best available technologies (BAT), (5) ECS2 in combination with stormwater and combined sewer overflow treatment, (6) ECS2 in combination with advanced wastewater treatment, and (7) combinations of ECS3-6. The SHCC approach was chosen to facilitate transparency, to allow compensating for data gaps and to decrease the level of uncertainty in the results. The selected PHSs: cadmium (Cd), hexachlorobenzene (HCB), nonylphenol (NP) and pentabromodiphenyl ether (PBDE) differ in their uses and environmental fate and therefore accumulate in surface waters to differing extents in response to the application of alternative ECS. To achieve the required reduction in PHS levels in urban waters the full implementation of existing EU regulation is prioritised and feasible combinations of managerial and technological options (source control and treatment) can be highly relevant for mitigating releases.

Evaluation of two stormwater infiltration trenches in central Copenhagen after 15 years of operation

Two stormwater infiltration trenches were installed in 1993 in an area in central Copenhagen. The system was monitored continuously for almost three years after establishment, and a small reduction in performance over that time, possibly due to clogging, was noted. A new study was conducted in 2009 to see whether the reduction in performance has continued and to determine how the system performs today. Water levels in the trenches were monitored for almost 4 months, and from this period seven events were selected to analyse the infiltration rate. A comparison with similar analyses on storm sequences from the first 3 years of operation shows that the infiltration has decreased since the establishment of the system 15 years ago. The decrease is statistically significant (p<0.01). A clogging model was fitted to the data and predictions were made for future performance. The results show that the system will discharge around 10 times more annual overflow to the sewers after 100 years of operation compared to the initial volumes, if clogging continues at current rates. This corresponds to 60% of the total runoff from the area. The results show that clogging and proper maintenance are important factors to consider when implementing stormwater infiltration trenches.

Micropollutants in stormwater runoff and combined sewer overflow in the Copenhagen area, Denmark

Stormwater runoff contains a broad range of micropollutants. In Europe a number of these substances are regulated through the Water Framework Directive, which establishes Environmental Quality Standards (EQSs) for surface waters. Knowledge about discharge of these substances through stormwater runoff and combined sewer overflows (CSOs) is essential to ensure compliance with the EQSs. Results from a screening campaign including more than 50 substances at four stormwater discharge locations and one CSO in Copenhagen are reported here. Heavy metal concentrations were detected at levels similar to earlier findings, e.g., with copper found at concentrations up to 13 times greater than the Danish standard for surface waters. The concentration of polyaromatic hydrocarbons (PAHs) exceeded the EQSs by factors up to 500 times for stormwater and 2,000 times for the CSO. Glyphosate was found in all samples whilst diuron, isoproturon, terbutylazine and MCPA were found only in some of the samples. Diethylhexylphthalate (DEHP) was also found at all five locations in concentrations exceeding the EQS. The results give a valuable background for designing further monitoring programmes focusing on the chemical status of surface waters in urban areas.

Combining multimedia models with integrated urban water system models for micropollutants

Integrated urban water system (IUWS) modeling aims at assessing the quality of the surface water receiving the urban emissions through sewage treatment plants, combined sewer overflows (CSOs) and stormwater drainage systems. However, some micropollutants tend to appear in more than one environmental medium (air, water, sediment, soil, groundwater, etc.). In this work, a multimedia fate and transport model (MFTM) is "wrapped around" a dynamic IUWS model for organic micropollutants to enable integrated environmental assessment. The combined model was tested on a hypothetical catchment using two scenarios: on the one hand a reference scenario with a combined sewerage system and on the other hand a stormwater infiltration pond scenario, as an example of a sustainable urban drainage system (SUDS). A case for Bis(2-ethylhexyl) phthalate (DEHP) was simulated and resulted in reduced surface water concentrations for the latter scenario. However, the model also showed that this was at the expense of increased fluxes to air, groundwater and infiltration pond soil. The latter effects are generally not included in IUWS models, whereas MTFMs usually do not consider dynamic surface water concentrations,; hence the combined model approach provides a better basis for integrated environmental assessment of micropollutants' fate in urban environments.

Dynamic stormwater treatment unit model for micropollutants (STUMP) based on substance inherent properties

Modelling the removal of micropollutants (MPs) in stormwater treatment systems is essential in a context that is characterized by a general lack of measurements. This paper presents an innovative dynamic model for the prediction of the removal of MPs in stormwater treatment systems (Stormwater Treatment Unit model for Micro Pollutants--STUMP). The model, based on a conceptual model of two-compartment (water and sediment) serial Continuous Stirred-Tank Reactors (CSTRs), can predict the fate of MPs based on their inherent properties, which are often the only information available regarding this kind of substances. The flexible structure of the model can be applied to a wide range of treatment units and substances. Based on the most relevant removal processes (settling, volatilization, sorption, biodegradation, and abiotic degradation), the model allows the dynamic simulation of the MP behaviour in the different compartments of stormwater treatment systems. The model was tested for heavy metals (copper and zinc) and organic substances (benzene and di(2-ethylhexyl)phthalate). The results show that volatilization plays a big role for removal of benzene while the removal of substances with high sorption capacity is mainly driven by settling. The model was proven to be able to predict the importance of the various fate processes for selected substances with different inherent properties. A thorough assessment of the influence of the various fate process parameters will allow a reliable assessment of the treatment performances for a wide range of MPs.

Potential future increase in extreme one-hour precipitation events over Europe due to climate change

In this study the potential increase of extreme precipitation in a future warmer European climate has been examined. Output from the regional climate model (RCM) HIRHAM4 covering Europe has been analysed for two periods, a control period 1961-1990 and a scenario 2071-2100, the latter following the IPCC scenario A2. The model has a resolution of about 12 km, which is unique compared with existing RCM studies that typically operate at 25-50 km scale, and make the results relevant to hydrological phenomena occurring at the spatial scale of the infrastructure designed to drain off rainfall in large urban areas. Extreme events with one- and 24-hour duration were extracted using the Partial Duration Series approach, a Generalized Pareto Distribution was fitted to the data and T-year events for return periods from 2 to 100 years were calculated for the control and scenario period in model cells across Europe. The analysis shows that there will be an increase of the intensity of extreme events generally in Europe; Scandinavia will experience the highest increase and southern Europe the lowest. A 20 year 1-hour precipitation event will for example become a 4 year event in Sweden and a 10 year event in Spain. Intensities for short durations and high return periods will increase the most, which implies that European urban drainage systems will be challenged in the future.

Selected stormwater priority pollutants: a European perspective

The chemical characteristics of stormwater are dependent on the nature of surfaces (roads, roofs etc.) with which it comes into contact during the runoff process as well as natural processes and anthropogenic activities in the catchments. The different types of pollutants may cause problems during utilisation, detention or discharge of stormwater to the environment and may pose specific demands to decentralised treatment. This paper proposes a scientifically justifiable list of selected stormwater priority pollutants (SSPP) to be used, e.g., for evaluation of the chemical risks occurring in different handling strategies. The SSPP-list consists of 25 pollutant parameters including eight of the priority pollutants currently identified in the European Water Framework Directive. It contains general water quality parameters (organic and suspended matter, nutrients and pH); metals (Cd, Cr, Cu, Ni, Pb, Pt and Zn); PAH (naphthalene, pyrene and benzo[a]pyrene); herbicides (pendimethalin, phenmedipham, glyphosate and terbutylazine); and other representative industrially derived compounds (nonylphenol ethoxylates, pentachlorophenol, di(2-ethylhexyl)phthalate, PCB-28 and methyl tert-butyl ether). Tools for flux modelling, enabling calculation of predicted environmental concentrations (PECs), and for ranking the susceptibility of a pollutant to removal within a range of structural stormwater treatment systems or best management practices (BMPs) have been developed, but further work is required to allow all SSPPs to be addressed in the development of future stormwater pollution control measures. In addition, the identified SSPPs should be considered for inclusion in stormwater related monitoring campaigns.

How uncertain is model-based prediction of copper loads in stormwater runoff?

In this paper, we conduct a systematic analysis of the uncertainty related with estimating the total load of pollution (copper) from a separate stormwater drainage system, conditioned on a specific combination of input data, a dynamic conceptual pollutant accumulation-washout model and measurements (runoff volumes and pollutant masses). We use the generalized likelihood uncertainty estimation (GLUE) methodology and generate posterior parameter distributions that result in model outputs encompassing a significant number of the highly variable measurements. Given the applied pollution accumulation-washout model and a total of 57 measurements during one month, the total predicted copper masses can be predicted within a range of +/-50% of the median value. The message is that this relatively large uncertainty should be acknowledged in connection with posting statements about micropollutant loads as estimated from dynamic models, even when calibrated with on-site concentration data.

Comparative uncertainty analysis of copper loads in stormwater systems using GLUE and grey-box modeling

In this paper two attempts to assess the uncertainty involved with model predictions of copper loads from stormwater systems are made. In the first attempt, the GLUE methodology is applied to derive model parameter sets that result in model outputs encompassing a significant number of the measurements. In the second attempt the conceptual model is reformulated to a grey-box model followed by parameter estimation. Given data from an extensive measurement campaign, the two methods suggest that the output of the stormwater pollution model is associated with significant uncertainty. With the proposed model and input data, the GLUE analysis show that the total sampled copper mass can be predicted within a range of +/-50% of the median value (385 g), whereas the grey-box analysis showed a prediction uncertainty of less than +/-30%. Future work will clarify the pros and cons of the two methods and furthermore explore to what extent the estimation can be improved by modifying the underlying accumulation-washout model.

A methodology for ranking and hazard identification of xenobiotic organic compounds in urban stormwater

The paper presents a novel methodology (RICH, Ranking and Identification of Chemical Hazards) for ranking and identification of xenobiotic organic compounds of environmental concern in stormwater discharged to surface water. The RICH method is illustrated as a funnel fitted with different filters that sort out problematic and hazardous compounds based on inherent physico-chemical and biological properties. The outcomes of the RICH procedure are separate lists for both water phase and solid phase associated compounds. These lists comprise: a justified list of compounds which can be disregarded in hazard/risk assessments, a justified list of stormwater priority pollutants which must be included in hazard/risk assessments, and a list of compounds which may be present in discharged stormwater, but cannot be evaluated due to lack of data. The procedure was applied to 233 xenobiotic organic chemicals (XOCs) of relevance for stormwater. Of these 233 compounds, 121 compounds were found to be priority pollutants with regard to solids phases (i.e. suspended solids, soil, or sediments) when stormwater is discharged to surface water and 56 compounds were found to be priority pollutants with regard to the water phase. For 11% of the potential stormwater priority pollutants the screening procedure could not be carried out due to lack of data on basic physico-chemical properties and/or data on bioaccumulation, resistance to biodegradation, and ecotoxicity. The tiered approach applied in the RICH procedure and the focus on the phases relevant for monitoring or risk assessment in the aquatic environment refines the list of "compounds of concern" when compared to the outcome of existing classification schemes. In this paper the RICH procedure is focused on effects in the aquatic environment exemplified with xenobiotic organic compounds (XOCs) found in urban stormwater, but it may be transferred to other environmental compartments and problems. Thus, the RICH procedure can be used as a stand-alone tool for selection of potential priority pollutants or it can be integrated in larger priority setting frameworks.

Indicators of hazard, vulnerability and risk in urban drainage

An alternative definition of risk is proposed as risk being a function of the hazard, which is related to the risk source and the vulnerability, which is related to the risk object. The same hazard will not cause the same effect on all risk objects. Therefore, vulnerability is introduced as a system-dependent property to be the link between the hazard and the effect so that the combination of the occurrence of a hazard and the vulnerability of an object results in the effect. In risk communication indicators are helpful since they help to simplify the message that has to be communicated. Three examples (pluvial flooding of sewers, dissolved oxygen depletion in streams and discharge of chemicals to receiving waters) show that dependent on the risk problem possibilities for risk reduction lies either at the risk source or at the risk object. Therefore, it is important to have indicators that can be used when the possibilities of risk reduction are analysed.

Integrated modelling of two xenobiotic organic compounds

This paper presents a dynamic mathematical model that describes the fate and transport of two selected xenobiotic organic compounds (XOCs) in a simplified representation of an integrated urban wastewater system. A simulation study, where the xenobiotics bisphenol A and pyrene are used as reference compounds, is carried out. Sorption and specific biological degradation processes are integrated with standardised water process models to model the fate of both compounds. Simulated mass flows of the two compounds during one dry weather day and one wet weather day are compared for realistic influent flow rate and concentration profiles. The wet weather day induces resuspension of stored sediments, which increases the pollutant load on the downstream system. The potential of the model to elucidate important phenomena related to origin and fate of the model compounds is demonstrated.

Transfer of hydrophobic contaminants in urban runoff particles to benthic organisms estimated by an in vitro bioaccessibility test

An in vitro bioaccessibility test was applied for assessing the transfer of polycyclic aromatic hydrocarbons (PAHs) present in road dust, into benthic organisms living in a receiving water body. The road dust is supposed to be urban runoff particles under wet weather conditions. Sodium dodecyl sulfate (SDS) solution was used as a hypothetical gut fluid. Pyrene, fluoranthene and phenanthrene were the main PAH species in the SDS extractable fraction of road dust, as well as the whole extract. Benzo(ghi)perylene showed relatively low concentrations in the SDS extract in spite of a high concentration in the original dust. The PAH composition in benthic organisms (polychaetes) did not correspond with that of the surrounding sediment and the PAHs detected were also detected in high concentrations in the SDS extract of road dust. When testing the toxicity of the extracted contaminants by a standardised algal toxicity test, SDS extracts of a detention pond sediment showed higher toxicity than the pore water of the corresponding sediment. Sediment suspension showed a comparative toxicity with 0.1% SDS extract. From the results, the in vitro bioaccessibility test seems more suitable to evaluate the exposed contaminants than the traditional organic solvent extraction method and the SDS extracted fraction is applicable to toxicity tests reflecting the digestive process.

Chemical hazard identification and assessment tool for evaluation of stormwater priority pollutants

Assessment of chemical hazards is a critical issue, which have to be dealt with when evaluating different strategies for sustainable handling of stormwater. In the present study, a methodology for identifying the most critical and representative chemical pollutants was developed. A list of selected stormwater priority pollutants (SSPP-list) is the out-put from the procedure. Two different strategies for handling of stormwater were considered; discharge into a surface water recipient and infiltration. However, the same methodology can be used for other types of wastewater and other strategies for handling and treatment. A literature survey revealed that at least 656 xenobiotic organic compounds (XOCs) could be present in stormwater. In the next step, 233 XOCs were evaluated with respect to the potential for being hazardous towards either aquatic living organisms or humans, or causing technical or aesthetical problems. 121 XOCs were found have at least one of these negative effects, while 26 XOCs could not be assessed due to the lack of data. The hazard assessment showed that 40 XOCs had a PEC/PNEC ratio above one., e.g. they should be considered as priority pollutants. The final step is the expert judgement, which resulted in a final SSPP-list containing 16 selected priority pollutants.

A novel method for evaluating bioavailability of polycyclic aromatic hydrocarbons in sediments of an urban stream

Hydrophobic organic pollutants in urban wet weather discharges can accumulate in the sediments of receiving waters and may have adverse effects on the ecological system, especially on benthic organisms. Here, a novel method is developed for evaluating the bioavailability of such hydrophobic organic pollutants by considering the digestive guts in deposit-feeding polychaetes. We compared the amount of polycyclic aromatic hydrocarbons (PAHs) extracted by an organic solvent and by sodium dodecyl sulfate (SDS) solution (as a hypothetical digestive gut fluid of polychaetes) and interpreted the ratio of the two values as bioavailability. The sediment extracts were applied to bacterial acute toxicity tests and algal growth inhibition tests. Sediment samples were collected from an urban stream system receiving wet weather discharges. The bioavailability of the total amount of 12 PAHs in the sediments was in the range 14-38% based on the results from the GC/MS determination of the two different extracts. Lower molecular PAHs showed higher bioavailability compared to the higher molecular ones. The sediment extracts were shown to be toxic towards both algae and bacteria. The SDS extracts showed similar or higher toxicity in the two biotests compared to the organic solvent extracts in spite of their lower PAHs content.

Cost benefit risk--a concept for management of integrated urban wastewater systems?

Urban wastewater systems should be evaluated and analysed from an integrated point of view, taking all parts of the system, that is sewer system, wastewater treatment plant and receiving waters into consideration. Risk and parameter uncertainties are aspects that hardly ever have been addressed in the evaluation and design of urban wastewater systems. In this paper we present and discuss a probabilistic approach for evaluation of the performance of urban wastewater systems. Risk analysis together with the traditional cost-benefit analysis is a special variant of multi-criteria analysis that seeks to find the most feasible improvement alternative for an urban wastewater system. The most feasible alternative in this context is the alternative that has the best performance, meaning that the alternative has the lowest sum of costs, benefits and risks. The sum is expressed as the Net Present Cost (NPC). To use NPC as a decision variable has the problematic effect, that two alternatives performing completely differently when focusing on environmental cost can have the same NPC. The extreme example is one alternative with high risk and low cost and another with low risk and high cost. In this example it is up to the decision-maker to decide whether she wants to spend the budget on preventive installations or cleaning up after failures in the environment.

Dissemination of regional rainfall analysis in design and analysis of urban drainage at un-gauged locations

A research program in Denmark on statistical modelling of rainfall has resulted in a model for regional distribution of rainfall extremes. The results show that extreme rainfalls critical to the hydraulic function of urban drainage systems and the pollution discharge are subject to a significant regional variation of extreme rainfalls throughout the country. This has implications for design and analysis of all practical problems related to urban drainage, since the rainfall data so far recommended as input to engineering analyses underestimates the problems. Consequently, the Danish Water Pollution Control Committee has issued a statement recommending a new engineering practice. The dissemination of the research results proved to be difficult due to lack of understanding of the concepts of the new paradigm by practitioners. The traditional means of communication was supplemented by user-friendly spreadsheets and easy access to rainfall data as well as giving courses on the new paradigm. This has eased the implementation of the new concepts greatly.