Analysis of pollutant dispersion patterns in rivers under different rainfall based on an integrated water-land model.

In the context of rapid urban expansion, the interaction between humanity and nature has become more prominent. Urban land and rivers often exist as distinct entities with limited material exchange. However, during rainfall, these two systems interconnect, resulting in the transfer of land-derived pollutants into rivers. Such transfer significantly increases river pollutant levels, adversely affecting water quality. Therefore, developing a water quality simulation and prediction model is crucial. This model should effectively illustrate pollutant movement and dispersion during rain events. This study proposes a comprehensive model that merges the Storm Water Management Model (SWMM) with the Environmental Fluid Dynamics Code (EFDC). This integrated model assesses the spread and dispersion of pollutants, including Ammonia Nitrogen (NH3-N), Total Phosphorus (TP), Total Nitrogen (TN), and Chemical Oxygen Demand (COD), within urban water cycles for various rainfall conditions, thus offering critical theoretical support for managing the water environment. The application of this model under different rainfall intensities (light, moderate and heavy) provides vital insights. During light rainfall, the river's natural purification process can sustain surface water quality at Class IV. Moderate rainfall causes accumulation of pollutants, reducing water quality to Class V. Conversely, heavy rainfall rapidly increases pollutant concentrations due to higher inflow, pushing the river to a degraded Class V status, which is beyond its natural purification capacity, necessitating engineering solutions to reattain Class IV quality. Furthermore, pollutant accumulation in downstream river sections is more influenced by flow rate than by rainfall intensity. In summary, the SWMM-EFDC integrated model proves highly effective in predicting river water quality, thereby significantly aiding urban water pollution control.

An improved Back Propagation Neural Network framework and its application in the automatic calibration of Storm Water Management Model for an urban river watershed.

The use of the Storm Water Management Model (SWMM) to simulate flows in urban river watersheds necessitates the proper calibration of the various parameters involved in the process. Back Propagation Neural Network (BPNN) is often used to establish relationship between two sets of multivariate variables, such as parameters and simulation results of SWMM. The aim of this study is to establish an improved BPNN to calibrate SWMM. It was found that when using gauged flow data obtained from the urban river management system as calibration data, only using BPNN was not sufficient. An improved BPNN framework was proposed with integrating Principal Component Analysis (PCA) and Genetic Algorithm (GA) process, abbreviated as PCA-GA-BPNN. It was proved to be effective for calibration. The BPNN combined with GA process made 90 % of the predicted parameters within reasonable range, which was only 8 % using BPNN alone. The PCA process reduced the training time up to 64 %. Using a hydrograph of 196 h, compared with the nondominated sorting genetic algorithm (NSGA), PCA-GA-BPNN training time can be reduced from 18,142 s down to 4.5 s. Nash efficiency coefficients (NSE) of hydrographs fitting was 0.75. Including more rainfall events data in calibration achieved better fitting than including more gauging station data.

Simulation and investigation into the pluvial effect on peri-urban unsewered drainage basin of Kolkata due to rapid urbanization.

A pluvial effect is a geologic event caused by the action of water during excessive precipitation in a particular region, resulting in water logging, which affects the drainage system of that area, or it may be caused by the spill of a large amount of water beyond the normal limit from the water bodies. The pluvial effect is also referred to as a flood having highly devastating consequences when it affects a region's urban or peri-urban areas. It affects the day-to-day activities of people staying in those areas and causes various social and economic losses. This effect would even grow further if proper planning and management of land were not done in a given time. Therefore, through this paper, the authors try to address the issue of urban flooding along with its consequences and impacts. For this study, the peri-urban region of the Tollygunge-Panchannagram Basin in Kolkata, India, is considered. The zero inertia model, Triangular Irregular Network Flood (TINFLOOD), is employed for surface flow simulation, whereas the storm water management model (SWMM) is used to determine the lateral flow. The output of this study provides various hyetographic presentations, considering infiltration during advanced, intermediate, and delayed rainfall conditions. Here, the time of concentration is also examined for different rainfall intensities to observe the time for peak flow. The simulated data obtained from this model has been validated with the real-time data of a pumping station situated at Chowbhaga. Nevertheless, this study helps assess flood risk management upstream of a region's basin and peri-urban areas.

Quantifying and improving flood resilience of urban drainage systems based on socio-ecological criteria.

In this paper, a new framework is developed for evaluating the resilience of urban drainage systems (UDSs) under floods by proposing and quantifying some technical and socio-ecological (SE) criteria. The proposed criteria are used to quantify the seven principles of building resilience in socio-ecological systems. The criteria mainly focus on preserving diversity and multiplicity in a UDS, managing variables that gradually change over time (slow variables), improving structural and functional connectivity, maintaining system adaptability, encouraging learning, broadening participation, and promoting polycentric governance systems. For evaluating the efficiency of the proposed framework, it is applied to a real-world case study of improving resilience of the UDS in the eastern part of Tehran metropolitan area. Three scenarios for flood management are proposed based on the Low Impact Development (LID) practices which are simulated using the Storm Water Management Model (SWMM). The Entropy method is used to consider the uncertainty in the relative importance of different criteria in estimating the flood resilience. The estimated values for the proposed criteria regarding the current drainage system in the study area show its undesirable condition in many sub-catchments. The results also show that using around 2.3 km2 of LID practices in this urban watershed can significantly improve the resilience in many sub-catchments (nearly, 30%) and reduce the total volume of the overflow (about 50%). The results also show that using the flood management scenarios, improving connectivity is the most influential factor that enhances the general resilience of the system.

How to simulate future scenarios of urban stormwater management? A novel framework coupling climate change, urbanization, and green stormwater infrastructure development.

Climate change, urbanization, and green stormwater infrastructure (GSI) planning policies lead to uncertainties in future urban sustainability. Coupling multiple influencing factors such as climate change, urbanization, and GSI development, this study proposes a novel framework for simulating future scenarios of urban stormwater. Subsequently, the changes in annual surface runoff and runoff pollutants in Shanghai's new and old urban areas were compared and analyzed based on 35 typical future and seven baseline scenarios. The following results were obtained: 1) The runoff control rate of the new urban area was significantly higher than that of the old urban area before GSI construction. After GSI construction, both areas could control stormwater runoff and pollutants, while the decline in efficiency in GSI facilities enormously impacted the old area. 2) Surface runoff in the new urban area was mainly affected by urbanization, while climate change was a major factor in the old urban area; runoff pollutants in new and old urban areas were mainly affected by urbanization, and the change in pollutants in new areas was more pronounced. 3) GSI facilities were unlikely to guarantee the quantity and quality of water resources, especially in scenarios where the efficiency of GSI facilities decreases. In old urban areas, the more extreme climate change and urbanization were, the more significant the effect of improving stormwater management facilities. Our findings showed that future studies on stormwater management should specifically consider the different characteristics of new and old urban regions, pay attention to the maintenance and management of GSI facilities, and build adaptive strategies to cope with climate change, urbanization, and GSI facility destruction.

Spatial allocation of LID practices with a water footprint approach.

Urban water problems due to stormwater have been aggravated by the higher frequency of high-intensity precipitation events and the increase of paved surfaces. However, with appropriate stormwater management practices, such as low-impact development (LID), stormwater can provide an additional urban water resources rather than cause damage. This study aims to apply a water footprint to location determination of LID practices in the urban area. The LID planning procedure was demonstrated with the highest population density region in Taipei, Taiwan. In order to improve the spatial resolution of LID allocation, the "first-level dissemination area" with 450 residents was used as a spatial unit. The performance of LID practices was then evaluated with the simulation using the Storm Water Management Model (SWMM). Three LID practices, rainwater harvesting systems, permeable pavements, and bioretention systems, were selected. After the water footprint accounting, ten sites were suggested for LID implementation. The runoff reduction rate reached up to 65 % by rainwater harvesting systems or at least 3 % by permeable pavements. This study provides a simpler and more effective approach to ways of integrating an urban water footprint into LID planning and stormwater management in urban areas.

The optimization of Low Impact Development placement considering life cycle cost using Genetic Algorithm.

Low Impact Development (LID) is an effective measure in controlling the urban runoff and mitigating the non-point source pollution. The determination of LID facilities and layouts for a sub-catchment is important for designing stormwater management system. However, there are remain large uncertainty and challenge exist in determination of LID facilities when consider budget, land use, soil surface and groundwater as well as local climate etc. To address this issue, this study employed Genetic Algorithm (GA) for optimization of the selection and layout of LID. The urban runoff was simulated using Environmental Protection Agency (EPA) Storm Water Management Model (SWMM). The LID planning was encoded as 0 and 1 in GA algorithm. The multiple objectives which include runoff reduction, area of LID and life cycle cost were selected as optimization targets. To test the model performance, the Airport Economic Zone in Tianjin, China was chosen as the study area. The results demonstrate that the combination of LID approaches are most effective measures on runoff reduction through long-term simulation (10 years' rainfall events). The impact of different weights of land area and cost on LID selection were evaluated when considering life cycle cost. Bio-Retention is preferred when considering the area of LID and Green Roof is recommended when the cost is prioritized. The present research proved GA is feasible for LID planning in urban area. The proposed method can help the decision-makers to determine the LID plan more scientific based on SWMM model and GA.

Runoff control simulation and comprehensive benefit evaluation of low-impact development strategies in a typical cold climate area.

With the acceleration of urbanization, the proportion of surface imperviousness is increasing continuously in cities, resulting in frequent waterlogging disasters. In this context, storm water management, based on the low-impact development (LID) concept, offers an effective measure for the management of urban storm waters. First, the storm water management model (SWMM) was built for a typical cold climate city (Changchun) in China. Next, the two-stage calibrated model was employed to explore the surface runoff and storm sewer control effects of four LID combination plans. Finally, these plans were put through a "cost-benefit" evaluation through an analytic hierarchy process. According to the results, after using four LID plans, the reduction rates of peak runoff exceeded 40% and the problem of overflow load of the storm sewage was significantly mitigated. The infiltration-oriented Plan I proved to be the optimal plan, with the lowest proportions of the overflow nodes and full-load pipe sections in each return period, as well as with maximum overall performance. This study offers technical and conformed methodological support to cold cities for the prevention and control of waterlogging disasters and recycling of rainwater resources.

An online participatory system for SWMM-based flood modeling and simulation.

In the context of the continuous development of urbanization and global climate change, urban flooding risk has become a well-publicized research issue. The Storm Water Management Model (SWMM) performs very well in urban rain-runoff simulations and is widely used to build flood models in specific areas. Because of the complicated and tedious processing work for urban flood modeling and simulation, multifield participants' cooperation is becoming a trend. To promote the research and application of flood modeling and simulation, some resource sharing-oriented systems and platforms have been proposed with the advantages of network technology. However, they still require a participatory environment that can help modeling participants overcome the difficulties of distributed cooperation in the process of SWMM-based flood modeling and simulation. Therefore, we designed and implemented an online participatory system to coordinate the effective collaboration of modeling participants in this process. By referring to the scenarios and specific participatory demands in the modeling process, the system provides a guiding framework that consists of multiple participatory activities and prepares a series of online auxiliary tools designed for these activities. Using the main urban area of Lishui City as the study area, it was confirmed that the process of SWMM-based flood modeling and simulation can be demonstrated collaboratively on the online participatory system developed in this study.

CityGML urban model generation using national public datasets for flood damage simulations: A case study in Korea.

Managing information at city level has become increasingly important owing to the introduction of smart cities and the increasing severity of disasters due to climate change. A data collection framework, model construction, and information management must be established to systematically manage information at the city level. This study developed an urban model generation method using detailed attributes within the City Geography Markup Language (CityGML), a standard data schema for 3D representation of cities based on different types of publicly available information within Korea. The generated model was used to develop a method for simulating flooding status, degree of flooding, and level of building damage after heavy rainfall, in Korea. Furthermore, we developed a method to estimate the loss of human life and property damage by combining the results of the flood analysis with the city model. The proposed methodology supports the creation of standard-based models for flood analysis and exhibits strong interoperability for application to different areas of analysis.

Unit and regression tests of scientific software: A study on SWMM.

Testing helps assure software quality by executing a program and uncovering bugs. Scientific software developers often find it challenging to carry out systematic and automated testing due to reasons like inherent model uncertainties and complex floating-point computations. Extending the recent work on analyzing the unit tests written by the developers of the Storm Water Management Model (SWMM) [32], we report in this paper the investigation of both unit and regression tests of SWMM. The results show that the 2953 unit tests of SWMM have a 39.7% statement-level code coverage and a 82.4% user manual coverage. Meanwhile, an examination of 58 regression tests of SWMM shows a 44.9% statement-level code coverage and a near 100% user manual coverage. We also observe a "getter-setter-getter" testing pattern from the SWMM unit tests, and suggest a diversified way of executing regression tests.

Avaliação do emprego de técnicas compensatórias na sub-bacia urbana Ribeirão do Santa Rita do município de Fernandópolis, São Paulo / Evaluation of the use of compensatory techniques in the Ribeirão do Santa Rita urban sub-basin in the municipality of Fernandópolis, São Paulo

RESUMO Com o crescimento da população urbana e consequente alteração do uso e da ocupação do solo nas bacias hidrográficas, as inundações têm ficado cada vez mais frequentes. O presente trabalho teve como objetivo verificar os efeitos do emprego de técnicas compensatórias na sub-bacia hidrográfica Ribeirão do Santa Rita, localizada no município de Fernandópolis, São Paulo, Brasil. Foram analisados a vazão de pico e o tempo de resposta de diversos cenários, com o intuito de verificar o potencial de atenuação das inundações. A metodologia utilizada empregou o Storm Water Management Model (SWMM) para propagar o escoamento, e o software de Sistema de Informação Geográfica (SIG) para obter as características da bacia em estudo e os locais de potencial emprego das técnicas. Foi simulada a instalação de diversas técnicas compensatórias, isoladamente e em conjunto, para a configuração urbana de 2017. Mediante os hidrogramas gerados por cada cenário, constatou-se que os melhores resultados ocorreram em eventos com tempo de retorno menor. A atenuação da vazão de pico chegou a 33,72% utilizando-se trincheiras de infiltração, 31,38% para pavimentos permeáveis, 31,08% empregando jardins de chuva e 12,20% com telhados verdes. O aumento no tempo de resposta foi de até 16 minutos. No cenário com todas as técnicas compensatórias, a redução foi de até 37,29% da vazão de pico e o aumento do tempo de resposta foi de 18 minutos. Portanto, as técnicas compensatórias podem reduzir a vazão de pico e aumentar o tempo de resposta da sub-bacia, mitigando as ocorrências de inundações.

ABSTRACT With the growth of the urban population and the consequent alteration of land use and occupation in the watersheds, floods have become more frequent. This paper aimed to verify the effects of the use of compensatory techniques in the watershed Ribeirão do Santa Rita, located in the city of Fernandópolis, São Paulo, Brazil. Peak flow and response time of various scenarios were analyzed in order to verify the potential for flood mitigation. The methodology used Storm Water Management Model (SWMM) to propagate the flow, with the support of the Geographic Information Systems (GIS) to obtain the characteristics of the studied watersheed and the places of potential use of the techniques. The installation of several compensatory techniques was simulated, separately and together, for the 2017 urban configuration. Upon the hydrographs generated by each scenario, it was found that the best results occurred in events with shorter return time. Peak flow attenuation reached 33.72% using infiltration trenches, 31.38% for pours pavements, 31.08% using rain gardens, and 12.20% with green roofs. The increase in lag time was up to 16 minutes. In the scenario with all compensatory techniques, the reduction in peak flow was up to 37.29% and the response time increased by 18 minutes. Therefore, compensatory techniques can reduce peak flow and increase the response time of the sub-basin, consequently mitigating the occurrences of floods.

Not all SuDS are created equal: Impact of different approaches on combined sewer overflows.

Sustainable urban drainage systems (SuDS) help in stormwater management by reducing runoff volume, increasing runoff concentration time and thereby improving the drainage system capacity. This study investigated the potential and cost-effectiveness of SuDS in reducing combined sewer overflows (CSOs). We simulated the performance of four SuDS techniques (bioretention cell, permeable pavement, rain barrel and green roof) at incremental levels of spatial coverage for a small urban catchment with a combined sewer system. We also used an Analytic Hierarchy Process (AHP) considering end-point CSO, land use, imperviousness, slope and elevation criteria to identify priority areas for SuDS deployment. Results showed that CSO volume attenuation ranged a maximum of 50-99% for the catchment, depending on the deployment strategy and underlying mechanisms of each technology. We also found that deployment of SuDS in AHP-selected sub-catchments improved CSO reduction only for rain barrels and green roofs, but not for bioretention cells and permeable pavements. SuDS were also a cost-effective retrofit option: for a 40% volume reduction, the SuDS cost, at most, 25% of the equivalent cost required for a large CSO tank. Outcomes of this study demonstrate the efficacy of SuDS in controlling CSOs, adding yet another tangible benefit to their increasingly recognised multi-functionality.

Modelagem da qualidade da água em sistemas de macrodrenagem de bacias urbanas / Water quality modeling in urban basins macrodrainage systems

RESUMO A remoção da cobertura vegetal e a impermeabilização de grandes áreas somadas à ineficiência dos serviços básicos de saneamento, contribuem para o aumento das cargas poluidoras pontuais e difusas que são transportadas superficialmente pelas águas pluviais, causando impactos negativos ao sistema de drenagem. Como o despejo ilegal de efluentes domésticos em redes de drenagem é uma realidade observada em todo o país, principalmente no meio urbano, hoje, a maior preocupação dos gestores e estudiosos é voltada às fontes pontuais de poluição e, apesar da importância, as fontes difusas têm recebido pouca atenção. Este trabalho objetivou modelar, utilizando o programa Storm Water Management Model (SWMM), a qualidade das águas pluviais a partir da avaliação do acúmulo de poluentes na superfície do solo em períodos secos e da lavagem durante eventos de precipitação na Bacia Hidrográfica Riacho do Prado, inserida no perímetro urbano da cidade de Campina Grande, Paraíba. Oito pontos no canal de drenagem foram monitorados, analisando-se as variáveis demanda bioquímica de oxigênio (DBO), demanda química de oxigênio (DQO) e fósforo total (FT), além da determinação da vazão. Os resultados obtidos nas simulações do comportamento dos poluentes em escala temporal para o evento medido do dia 08 de junho de 2018 foram condizentes com os valores observados nas análises laboratoriais, confirmando a eficiência dos resultados para as outras simulações realizadas. Os dias antecedentes sem chuva e a intensidade da precipitação se mostraram importantes na análise da carga poluente.

ABSTRACT Removal of vegetation cover and the expansion of impermeable land, together with the inefficiency of basic sanitation services, contribute to the increase of point and diffuse pollutant loads drained by rainwater, causing negative impacts at drainage system. As the illegal discharging of domestic sewage in drainage canals is a reality observed throughout the country, especially in urban areas, today the main concern of managers and researchers is directed to the point sources of pollution and, despite the importance, diffuse sources have received little attention. This work aims to model the rainwater quality using the Storm Water Management Model (SWMM) from the evaluation of buildup pollutants on the soil surface in dry periods and the washoff during precipitation events in the Riacho do Prado watershed located in the urban area of Campina Grande, Paraíba. Eight points were monitored at the drainage canal, in which the variables BOD5, COD, and total phosphorus were analyzed, in addition to flow determination. The results obtained on the simulations of behavior of pollutants in time scale for the actual event of 06/08/2018 were in agreement with the values observed at laboratory analyses, confirming the efficiency of results for the other simulations. The previous days without rain and the intensity of precipitation were important in the analysis of the pollutant load.

Testing of the Storm Water Management Model Low Impact Development Modules.

Stormwater infrastructure designers and operators rely heavily on the United States Environmental Protection Agency's Storm Water Management Model (SWMM) to simulate stormwater and wastewater infrastructure performance. Since its inception in the late 1970s, improvements and extensions have been tested and evaluated rigorously to verify the accuracy of the model. As a continuation of this progress, the main objective of this study was to quantify how accurately SWMM simulates the hydrologic activity of low impact development (LID) storm control measures. Model performance was evaluated by quantitatively comparing empirical data to model results using a multievent, multiobjective calibration method. The calibration methodology utilized the PEST software, a Parameter ESTimation tool, to determine unmeasured hydrologic parameters for SWMM's LID modules. The calibrated LID modules' Nash-Sutcliffe efficiencies averaged 0.81; average percent bias (PBIAS) -9%; average ratio of root mean square error to standard deviation of measured values 0.485; average index of agreement 0.94; and the average volume error, simulated vs. observed, was +9%. SWMM accurately predicted the timing of peak flows, but usually underestimated their magnitudes by 10%. The average volume reduction, measured outflow volume divided by inflow volume, was 48%. We had more difficulty in calibrating one study, an infiltration trench, which identified a significant limitation of the current version of the SWMM LID module; it cannot simulate lateral exfiltration of water out of the storage layers of a LID storm control measure. This limitation is especially severe for a deep LIDs, such as infiltration trenches. Nevertheless, SWMM satisfactorily simulated the hydrologic performance of eight of the nine LID practices.

A robust approach for comparing conventional and sustainable flood mitigation measures in urban basins.

An integrated methodological framework for assessing different flood mitigation measures in urban catchments is presented. The framework comprises hydrologic, hydraulic and economic indices aiming at quantifying the effect of different alternatives regarding flood hazard mitigation. The alternatives evaluated include both conventional drainage solutions and low impact development measures. The conventional drainage solutions were: (i) off-line detention tanks; and (ii) sewer enlargement. The low impact development measures included: (i) green roofs (GR); and (ii) permeable surfaces (PS). Each solution was modeled using SWMM5 with respect to flood reduction effectiveness, and the results were compared to those of the existing condition (i.e., no flood mitigation measures). All the examined solutions were also compared based on their construction and operation and maintenance costs for a typical lifespan (i.e., 30 years). The results of the simulation revealed that both low impact development measures and conventional drainage solutions were highly effective even for storm events with low probability of occurrence. However, sewer enlargement was found to be the best alternative from an economic perspective. Nevertheless, peak at the sewer exit increased and time to peak remained unchanged; as a result, local flooding problems are resolved but downstream flooding problems may be introduced. If other criteria are considered, i.e., traffic obstruction, noise, construction easiness, co-benefits and downstream impacts, low impact development measures become more attractive compared to conventional drainage solutions.

Does the spatial location of green roofs affects runoff mitigation in small urbanized catchments?

Green roofs have been treated as practical low impact development (LID) strategies to retain stormwater runoff and alleviate the rainfall-induced flooding risks in urban regions. The purpose of this study was to analyze the hydrological effects of the spatial location of green roofs in urbanized catchments. In the built-up region of Beijing, 12 urbanized catchments with various architectural patterns were chosen as the study areas. To distinguish the spatial characteristics of roof surfaces, we defined the effective roof surfaces to distinguish from other types of roofs, which have more convenient or direct hydrological connections to drainage systems. A hydrological model was then used to simulate the stormwater mitigation performance of green roofs for the study catchments, which were assigned to different rainfall conditions. The simulation results confirmed the benefits of implementing green roofs for urban stormwater regulation. However, the spatial variability of green roofs showed inherent influences on the runoff mitigation capacity in urbanized catchments. Greening on effective roof surfaces would provide more effective stormwater regulation benefits, for reductions in both runoff volume and peak flow. In addition, the spatial arrangement characteristics of roof surfaces also influenced the hydrological efficiency of green roofs. The effect of the spatial location of green roofs on runoff mitigation was rainfall-dependent. These findings provide insights into the hydrological role of green roofs, and suggest that proper siting of LID facilities should be a consideration for urban stormwater management in order to fulfill the hydrological efficiency and cost-effectiveness planning target.

Assessment of a green roof practice using the coupled SWMM and HYDRUS models.

Green roof can mitigate urban stormwater and improve environmental, economic, and social conditions. Various modeling approaches have been effectively employed to implement a green roof, but previous models employed simplifications to simulate water movement in green roof systems. To address this issue, we developed a new modeling tool (SWMM-H) by coupling the stormwater management and HYDRUS-1D models to improve simulations of hydrological processes. We selected green roof systems to evaluate the coupled model. Rainfall-runoff experiments were conducted for a pilot-scale green roof and urban subbasin. Soil moisture in the green roof and runoff volume in the subbasin were simulated more accurately by using SWMM-H instead of SWMM. The scenario analysis showed that SWMM-H selected sandy loam for controlling runoff whereas SWMM recommended sand. In conclusion, SWMM-H could be a useful tool for accurately understanding hydrological processes in green roofs.

Cumulative effect of the disconnection of impervious areas within residential lots on runoff generation and temporal patterns in a small urban area.

This study sought to evaluate the cumulative effect of the implementation of green space depressions to promote disconnection of impervious areas within residential lots on runoff generation and temporal patterns in a small urban area characterized by high imperviousness. Three hypothetical scenarios were proposed with variations in the disconnection rate (α) within the lot, the soil infiltration conditions, and the rainfall patterns. Simulations were performed using the Storm Water Management Model (SWMM) with the implementation of a high spatial resolution model which allowed the explicit representation of the routing runoff between distinct surfaces. The results revealed a linear relationship trend between the total amount of rainfall (P) and total runoff (q), with identification of a possible precipitation threshold above the point at which a more critical condition of runoff generation is established. The value of this threshold was shown to be dependent on the degree of efficiency of the receptor permeable areas, which is associated with the disconnection rate and infiltrability of the soil. The results also showed that for a very high disconnection rate and lower infiltrability, runoff can increase substantially, with significant changes in the hydrographs simulated for longer storm events.

Hydrological modelling of green and grey roofs in cold climate with the SWMM model.

Rooftop retrofitting targets the largest land-use type available for reduction in impervious surfaces area in urban areas. Extensive green and grey roofs offer solution for retention and detention of stormwater in densely developed urban areas. Among the available green roof types, the extensive green roof has become a popular selection and commonly adopted choice. These solutions provide multiple benefits for stormwater and environmental management due to stormwater retention and detention capacities. The Storm Water Management Model (SWMM) 5.1.012 with Low Impact Development (LID) Controls was used to model the hydrological performance of a green and a grey (non-vegetated detention roof based on extruded lightweight aggregates) roof (located in the coastal area of Trondheim, Norway) by defining the physical parameters of individual layers in LID Control editor. High-resolution 1-min data from a previously monitored green and grey roof were used for calibration. Six parameters within the individual LID layers: soil (four parameters) and drainage mat (two parameters) were selected for calibration. After calibration, the SWMM model simulated runoff with a Nash-Sutcliffe model efficiency (NSME) of 0.94 (green roof) and 0.78 (grey roof) and a volume error of 3% for the green roof, and 10% for the grey roof. Validation of the calibrated model indicates good fit between observed and simulated runoff with a NSME of 0.88 (green roof) and 0.81 (grey roof) and with volume errors of 29% (green roof) and 11% (grey roof). Concerning the snowmelt modelling, the calibrated model showed a NSME of 0.56 (green roof) and 0.37 (grey roof) through the winter period. However, regarding volume errors, additional model development for winter conditions is needed; 30% (green roof) and 11% (grey roof). Optimal parameter sets were proposed within both the green and grey configurations. The results from calibration and especially validation indicated that SWMM could be used to simulate the performance of different rooftop solutions. The study provides insight for urban planners of how to target and focus the implementation of rooftop solutions as stormwater measures.