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In this paper, the capability of selected sustainable drainage systems (SuDS) to accomplish hydraulic hydrological invariance (HHI) was analyzed. The HHI principle is achieved if both the peak flow and the volume runoff of the urbanized catchment remain equal after any increase of impervious surfaces. In particular, the hydraulic performance of green roofs and permeable pavements was evaluated by considering a standard case study frequently encountered in design practices. The numerical simulations were conducted using Storm Water Management Model (SWMM) software. The efficiency of SuDS was assessed by varying the effective impervious area (EIA) along with the main rainfall characteristics. The findings of this research show that the global performance of a SuDS-retrofitted catchment improves with the EIA reduction. Moreover, the rainfall characteristics, namely the rainfall duration and the return period, influence the hydrologic efficiency moderately. The experimental results confirm the positive impact of SuDS in mitigating the effect of the escalating urbanization on the existing urban drainage system. This effect was evaluated by quantifying the reduction of the choking occurrence in the sewer pipe and structures downstream the urban lot. However, the HHI principle is barely achievable with the standard implementation of SuDS, as also proved in a design graph to appraise how close SuDS are to HHI compliance. [ABSTRACT FROM AUTHOR]

Featured Application: Hydrological modelling using HEC-HMS to model runoff changes associated with different nature-based solutions. The solutions implemented into the model were green roofs, permeable paving and retention ponds. Many regions in Europe face increasing issues with flooding and droughts due to changing rainfall patterns caused by climate change. For example, higher rainfall intensities increase urban flooding. Nature-based solutions (NbS) are suggested as a key mitigation strategy for floods. This study aims to address and mitigate the challenges faced in Tivoli natural park in Ljubljana regarding high peak discharges and low-flow issues in the creek entering the sewer system. The study involves setting up, calibrating and validating a Hydrologic Engineering Centre–Hydrologic Modelling System (HEC-HMS) model using available data. This study analyses NbS, such as small ponds, green roofs and permeable paving, to reduce peak discharge. Runoff was reduced by an average of 32.4% with all NbS implemented and peak discharge by 20 L/s. Permeable parking performed best, with an average runoff reduction of 6.4%, compared to 4.8% for permeable streets and 5.9% for green roofs. The ponds reduced peak discharge, although their effectiveness varied between rainfall events. Rainfall events with higher volumes and durations tended to overwhelm the proposed solutions, reducing their effectiveness. The ability of HEC-HMS to model NbS is also discussed. The curve number (CN) parameter and impervious % alterations to simulate NbS provided quantitative data on changes in runoff and discharge. [ABSTRACT FROM AUTHOR]

Jeddah is the most important port city in the Kingdom of Saudi Arabia. The climate of Jeddah is mostly dry; however, events of intensive rainfall followed by urban flooding have been reported in recent history. These floods interrupt the logistics and lifelines of the city. In this study runoff analysis and Flash Flood management by the green roof low impact development (LID) control system, was performed using United States Environmental Protection Agency (EPA)'s Stormwater Management Model (SWMM). Six middle districts of Jeddah city had been selected and modeled in five sub-catchment areas. The local soil and geographic conditions were incorporated into the model. The effect of the soil-based, rooftop, LID system has been emphasized in the analysis. In flood simulations, 30–70% of the impervious area of each sub-catchment has been treated with LID. It has been observed that the LID application can significantly reduce the overall flood flow. Thus, simple but well-planned LID control systems can be effectively utilized for the flood management of heavily urbanized regions. [ABSTRACT FROM AUTHOR]

The use of green roofs, a low-impact development practice, can be an effective means of reducing direct runoff in urban centers. Green roof modeling can enable efficient design by preliminarily grasping the behavior of the green roof system according to specific configurations. In this study, we aimed to find appropriate evapotranspiration and parameter optimization schemes for HYDRUS-1D, a commonly used modeling tool for green roofs. Comparative studies of this sort in the context of green roof runoff modeling have not been conducted previously and are important in guiding users to overcome the difficulties of choosing the right numerical schemes for an accurate prediction of runoff from a green roof. As a study site, the Portland Building Ecoroof in Portland, Oregon, USA, was chosen, as green roof configurations and observed data for climate and runoff were available. From the simulation results of the runoff volume, the Blaney–Criddle method, which was considered an alternative, was found to be appropriate for calculating evapotranspiration from a green roof (R2 = 0.82) relative to the Hargreaves method built in HYDRUS-1D (R2 = 0.46). In addition, this study showed that the optimization method using the harmony search algorithm, which was proposed as an alternative optimizer, was better (R2 = 0.95) than that of the HYDRUS-1D's own optimization module (R2 = 0.82) in calibrating HYDRUS-1D for green roof runoff. The findings are thought to be useful in guiding modelers who are considering using HYDRUS-1D for green roof runoff simulations. [ABSTRACT FROM AUTHOR]

Green roofs (GRs) are a widely recognized green infrastructure (GI) strategy that helps reduce runoff volume and runoff pollution caused by the significant increase in impervious urban areas. However, the leaching of several nutrients from GR substrates is a growing concern. Biochar, a carbon-rich material, possesses advantageous properties that can help address such environmental challenges associated with GRs. Therefore, this paper aimed to undertake a field study to investigate the impacts of various biochar application methods, particle sizes, and amendment rates on the quality of runoff from GRs. Observational data of runoff quality were collected over a two-month period from five newly established 1 m × 1 m biochar-amended GR test beds and a control test bed without biochar, with all test beds subjected to artificially simulated rainfall. The results indicated that the addition of biochar did not result in a significant improvement in runoff pH, whereas the electrical conductivity (EC) was higher in runoff from GRs with biochar-amended substrates. When comparing the total nitrogen (TN) concentration in runoff from the non-biochar GR (ranging from 3.7 to 31 mg/L), all biochar test beds exhibited higher TN release (4.8 to 58 mg/L), except for the bed where medium biochar particles were applied at the bottom of the substrate (ranging from 2.2 to 21 mg/L). Additionally, all biochar-amended GRs exhibited higher TP concentrations in runoff (0.81 to 2.41 mg/L) when compared to the control GR (0.35 to 0.67 mg/L). Among the different biochar setups, GR with fine biochar particles applied to the surface of the substrate had the poorest performance in improving runoff water quality. Despite these mixed results, biochar holds significant potential to improve runoff quality by significantly increasing water retention, thereby reducing pollutant loads. [ABSTRACT FROM AUTHOR]

While green roofs have gained widespread popularity as a measure to detain and retain runoff in urban areas, their performance during extreme events is not well studied. In this study 15 years of runoff and precipitation observations from a small extensive green roof in Norway are analysed. GEV‐distributions were fitted to the annual max values for precipitation and runoff in order to develop intensity‐duration‐frequency (IDF) and runoff‐duration‐frequency (RDF) data. Using the IDF and RDF data a total of 31 extreme events were identified (containing precipitation or runoff values with return period greater than 2 years for one or more durations). While nearly all extreme runoff events were caused by extreme precipitation, only 69% of the extreme precipitation events resulted in extreme runoff. The assumption of 1:1 equivalency of return periods did not hold true, and deviations were mainly explained by variations in substrate water content prior to the extreme event. Moreover, in 50% of the events, the runoff duration with the greatest return period was shorter than the precipitation duration with the greatest return period. Hence, the results indicate that the use of design storms to predict runoff from green roofs may be inappropriate. The potential of having IDF and RDF data available was demonstrated by the development of simple empirical equations, which ensure conservations of both return period and duration. To generate reliable green roof RDF data, future research should prioritize evaluating various continuous models with the aim of accurately describing extreme events. [ABSTRACT FROM AUTHOR]

A one-year study was conducted to evaluate the impact of air pollution and roof coating on runoff quality. An existing 440 sq meter bitumen roof of a single-story building was coated with an extensive green roof layer on one half. Rainfall and runoff samples from both roofs were collected during 11 rainfall events after the separation of the first flush. The study monitored several key parameters, including pH, electrical conductivity (EC), turbidity, chemical oxygen demand (COD), ammonium nitrogen, nitrate nitrogen, and phosphates. The study revealed that both types of roofs altered the rainfall quality, but the changes caused by the green roof were more substantial. Although the retention of runoff from green roofs has a widely acknowledged positive impact on collecting systems, our study shows that green roofs also result in a 7.5- fold increase in COD concentrations, a 5.4-fold increase in the sum of ammonium and nitrate nitrogen, and a 2.3-fold increase in phosphates compared to bitumen roofs. A clear link between the quality of rainwater/runoff and air pollution was not established. The study's findings will aid in the development and management of local rainwater harvesting systems and enhance global understanding of the primary quality parameters of various roof types, particularly in regions with air pollution. [ABSTRACT FROM AUTHOR]

Space availability is one of the largest barriers to urban agriculture. One way around this issue that urban farmers in some parts of the world are exploring is moving their farming activities to building rooftops. One method of rooftop farming in use is row agriculture using green roof technology. Vegetable crop plants, which typically require more water and more nutrients than the ornamental species found on green roofs, require irrigation and the use of fertilizers. One nutrient management practice that some rooftop farmers are using is the addition of compost, which could lead to changes over time in the water-holding capacity, organic matter content, and weight of green roof media. This practice and its long-term implications have not been well-studied. Green roof platforms were created to examine how the annual additions of compost in quantities of 0, 0.33, 0.66, and 1 kg/m2 affect runoff water quality and green roof media properties. Runoff water samples were collected and analyzed for pH, conductivity, color, turbidity, and nitrate nitrogen, ammonia nitrogen, total phosphorus, and potassium contents. Compost treatment had no effect on any water quality metric except for color, which had slightly different changes over time in the different compost treatments. The lack of difference among the treatments may be attributed to the low nutrient content of the compost and continued use of fertilizers to provide nutrients. Most samples observed in this study exceeded the US Environmental Protection Agency water quality guidelines for nitrate nitrogen and phosphorus and were similar to values observed in the green roof literature regarding agricultural and ornamental green roofs. This has potential implications for surface water quality and eutrophication, especially as green roof agriculture increases. [ABSTRACT FROM AUTHOR]

Green roofs (GRs) have been researched for decades, yet their implementation remains constrained due to several reasons, including their limited appeal to policymakers and the public. Biochar, a carbon-rich material, has been recently introduced as an amendment to GR substrate to enhance the performance of GRs through reduced runoff volume, improved runoff quality, and increased soil fertility. This paper aims to investigate the impact of biochar amendment on the hydrological performance of newly established GRs. Six 1 m × 1 m GR test beds were constructed, comprising of five biochar-amended GR test beds, and one conventional test bed (without any biochar in its substrate). The water retention capacity and runoff outflow delay of the six test beds were studied with the application of artificial rainfall using a nozzle-based simulator. Biochar was found to increase the water retention capacity and effectively delay runoff outflow in the biochar-amended GRs. After nine artificial rainfall events of 110.7 mm rainfall in total, 39.7 to 58.9 L of runoff was retained by the biochar-amended GRs as compared to 37.9 L of runoff retained by the conventional GR. Additionally, the test bed without biochar quickly started releasing runoff after 300 to 750 s, whereas test beds with fine biochar particles could delay runoff outflow by 700 to 1100 s. The performance of the non-biochar and biochar-amended test beds varies according to the values of biochar-related variables such as biochar particle sizes, amendment rates, and application methods. The observational data illustrated that the GR test bed with medium biochar particles applied to the bottom layer of the GR substrate was the optimal biochar-GR design. This selection was determined by the combined performance of high retention rates, long runoff outflow delays, and few other factors, such as lesser loss of biochar caused by wind and/or water. [ABSTRACT FROM AUTHOR]

The urban growth leads cities to adopt sustainable strategies in order to mitigate the relevant hydrological effects. In this study, the use of synthetic aperture radar SAR imagery has allowed us to demonstrate a 70% increase of the built-up area in Sarno River basin between 1995 and 2016. This increase is linked to the statistical temporal increase of the damaging hydrological events occurring during the same period. To restore the pre-development hydrological condition, a scenario analysis was undertaken where SWMM was used to simulate the hydrological effect of green roof retrofitting landscape design. SAR imagery was furthermore used to explore the potential retrofitting surfaces, leading to defining three different conversion scenarios with 5%, 30% and 100% of potential retrofitting surfaces. The study demonstrated that the pre-development hydrological condition can be never fully restored. Indeed, this scenario is partially equaled only by a 100% green conversion of the existing traditional roofs, with average runoff and peak flow reduction of 41% and 25%, respectively. Such conditions are clearly not feasible, provided the obvious retrofitting limitation for existing buildings. The use of additional nature-based techniques, beyond green roofs conversion, should be explored in the perspective of a balance for urban growth. HIGHLIGHTS In Sarno River basin, a correlation between the increase of built-up areas and damaging hydrological effects exists.; Radar images help to identify the potential areas for green roof retrofit.; Green roofs applied at a basin scale allow substantial mitigation of urban runoff.;

To renovate an ordinary building roof into an extensive green roof (GR), on the basis of optimizing the runoff process, the total runoff control rate (TR-CR) and peak runoff control rate (PR-CR) were analyzed with the SWMM model under parameter sensitivity analysis. The response surface method (RSM) was used to investigate the effect of area ratio (GR area to total roof area), width (surface width per unit), and soil hydraulic conductivity on TR-CR and PR-CR. The optimal test conditions were obtained through the establishment of quadratic regression equations. The results showed that the effects of the three factors on TR-CR were in the order of area ratio>hydraulic conductivity>width, and on PR-CR was area ratio>width>hydraulic conductivity. Considering the volume capture ratio (80%) of annual rainfall and construction cost of the GR, under the optimal conditions of the area ratio of 0.79, width of 2.21 m, and hydraulic conductivity of 55.59 mm/h, the average values of TR-CR and PR-CR for this optimization scheme were 80.2% and 80.9%, respectively. This result show that the multiple quadratic regression model established is reliable. Therefore, the RSM can effectively optimize the simulation parameters, and provide some theoretical and practical basis for the renovation or construction of GRs. [ABSTRACT FROM AUTHOR]

Green roofs have been used to reduce rainfall runoff by altering hydrological processes through plant interception and retention as well as detention within the green roof system. Green roof media depth, substrate type, plant type and density, regional climatic conditions, rainfall patterns, and roof slope all impact runoff retention. To better understand the impacts of media depth (10, 15, and 20 cm), plant (planted and non-planted), and rainfall pattern (low, medium, and high) on rainfall retention, we analyzed data collected between September 2005 and June 2008 from 24 green roof models (61 cm × 61 cm) for growing and non-growing seasons. Our results showed that a planted green roof has greater rainfall retention capability than a non-planted green roof for all media depths. Interestingly, a non-planted green roof system with a 10 cm media depth retained greater rainfall than a planted green roof during both growing and non-growing periods. Retention capability decreased with increasing rainfall amounts for both planted and non-planted green roofs and seasons (growing and non-growing). The 15 cm media depth green roof retained significantly greater rainfall depth than the 20 cm models during medium (0.64 to 2.54 cm) and high (>2.54 cm) rainfall events for the growing season but not during the non-growing season. The study provides insight into the interactive effects of media depth, rainfall amount, plant presence, and seasons on green roof performance. The results will be helpful for designing economical and effective green roof systems. [ABSTRACT FROM AUTHOR]

Stormwater runoff in green roofs (GRs) is represented by the runoff coefficient, which is fundamental to assess their hydraulic performance and to design the drainage systems downstream. Runoff coefficient values in newly installed GR systems should be estimated by models that must be feasible and reproduce the retention behavior as realistically as possible, being thus adjusted to each season and climate region. In this study, the suitability of a previously developed model for runoff coefficient determination is assessed using experimental data, and registered over a 1 year period. Results showed that the previously developed model does not quite fit the experimental data obtained in the present study, which was developed in a distinct year with different climate conditions, revealing the need to develop a new model with a better adjustment, and taking into consideration other variables besides temperature and precipitation (e.g., early-stage moisture conditions of the GR matrix and climate of the study area). Runoff coefficient values were also determined with different time periods (monthly, weekly, and per rain event) to assess the most adequate approach, considering the practical uses of this coefficient. The monthly determination approach resulted in lower runoff coefficient values (0–0.46) than the weekly or per rain event (0.017–0.764) determination. When applied to a long-term performance analysis, this study showed no significant differences when using the monthly, weekly, or per rain event runoff, resulting on a variation of only 0.9 m3 of annual runoff. This indicates that the use of monthly values for runoff coefficient, although not suitable for sizing drainage systems, might be used to estimate their long-term performance. Overall, this pilot extensive GR of 0.4 m2 presented an annual retention volume of 469.3 L, corresponding to a retention rate of 89.6%, in a year with a total precipitation of 1089 mm. The assessment of different time scales for runoff coefficient determination is a major contribution for future GR performance assessments, and a fundamental decision support tool. [ABSTRACT FROM AUTHOR]

The soil layer is the most important structure for green roof runoff reduction and vegetation growth. The mechanisms of runoff reduction and water content of green roofs with varying soil depth and saturated water content (θs) under dry–wet cycles are not well understood. Field and numerical methodologies were adopted for investigation in this study. The green roof drainage and water content were observed for a given period (i.e., August 2020 to July 2021). A numerical model was calibrated and validated for the analysis of annual runoff reduction and water stress with different θs and soil depths. Based on climate in southern China, the green roof's annual runoff reduction rate (ARR) (100 mm soil) was 33%, and the annual water stress was 168 days. With an increase in θs by 0.1 mm3/mm3, the ARR of green roofs increased by an average of 5% while the water stress was reduced by an average of 32 days. With an increase in soil depth by 100 mm, the average ARR increased by 4%, whereas the average water stress was reduced by 6 days. It was shown that the runoff reduction is enhanced with an increasing θs and soil depth during a longer antecedent dry weather period, but it had no significant effect on runoff reduction during back-to-back rainfall events. Increasing soil depth had no significant improvement in runoff reduction and water stress beyond a certain point. Consequently, the optimal structural configuration of green roofs was considered as a soil depth of 200 mm (θs of 0.5 mm3/mm3). [ABSTRACT FROM AUTHOR]

The urban growth leads cities to adopt sustainable strategies in order to mitigate the relevant hydrological effects. In this study, the use of synthetic aperture radar SAR imagery has allowed us to demonstrate a 70% increase of the built-up area in Sarno River basin between 1995 and 2016. This increase is linked to the statistical temporal increase of the damaging hydrological events occurring during the same period. To restore the pre-development hydrological condition, a scenario analysis was undertaken where SWMM was used to simulate the hydrological effect of green roof retrofitting landscape design. SAR imagery was furthermore used to explore the potential retrofitting surfaces, leading to defining three different conversion scenarios with 5%, 30% and 100% of potential retrofitting surfaces. The study demonstrated that the predevelopment hydrological condition can be never fully restored. Indeed, this scenario is partially equaled only by a 100% green conversion of the existing traditional roofs, with average runoff and peak flow reduction of 41% and 25%, respectively. Such conditions are clearly not feasible, provided the obvious retrofitting limitation for existing buildings. The use of additional nature-based techniques, beyond green roofs conversion, should be explored in the perspective of a balance for urban growth. [ABSTRACT FROM AUTHOR]

Increased urbanization combined with the intensification of short rainfall events has worsened the urban flood issue. Among the different blue-green solutions to mitigate pluvial floods, green roofs (GR) and rainwater harvesting (RWH) have been investigated as sustainable systems to reduce runoff from rooftops. Their flood mitigation capacity, however, has been estimated mostly at building-scale. Following the need to estimate discharge reduction at large scale over entire cities, we simulated the installation of (extensive, intensive and multilayer blue) GRs on flat roofs and RWH systems for sloped ones. Performances of such systems were investigated in selected cities, representing different climate regimes. Although at building-scale GRs showed higher retention capacity, the cost-efficiency analysis highlights that at large-scale RWH tanks ensure higher retention with lower costs, due to rooftop distribution. The coupled system of multilayer blue-GRs and RWH tanks guarantees a discharge reduction of 5% even during extreme events. [ABSTRACT FROM AUTHOR]

Green roofs (GR) are known as one of the most effective water-sensitive urban design (WSUD) strategies to deal with numerous environmental and social issues that urbanized cities face today. The overall quality of research on GRs has significantly improved and an increasing trend is observed in the amount of research over the last decade. Among several approaches, the application of modeling tools is observed to be an effective method to simulate and evaluate the performance of GRs. Given that studies on GRs at a catchment scale are limited, this paper aims to provide a simple but effective framework for estimating the catchment-scale impacts of GR on runoff quantity and quality. MUSICX, an Australian-developed software that possesses the advantages of a conceptual model, is chosen as the modeling tool in this study. While MUSICX has built-in meteorological templates for Australian regions, this tool also supports several climate input file formats for application by modelers in other parts of the world. This paper presents two different modeling approaches using the Land Use node and Bioretention node in MUSICX. The steps used for model calibration are also provided in this paper. The modeling results present the annual reductions in runoff volume, total suspended solid (TSS), total phosphate (TP), and total nitrogen (TN) load. The largest reductions of roughly 30% per year were observed in runoff volume and TN load. The annual runoff reduction rate reported in this study is close to that of other published results. Similar research outcomes quantifying the benefits of GRs play a major role in facilitating the widespread implementation of GRs due to the awareness of both positive and negative impacts of GRs. Future studies are recommended to concentrate on modeling the impacts of implementing GRs at a large scale (i.e., scales exceeding the single-building scale) to fill the research gaps and enhance the modeling accuracy. [ABSTRACT FROM AUTHOR]

Green roofs provide multiple benefits to households and urban neighbourhoods by lowering temperatures, reducing energy costs, and reducing stormwater runoff. However, green roofs are expensive and may not be available to all residents, which raises questions about who benefits from green roofs and urban policies that support this technology. Policies to support different social groups' access to this green infrastructure is important for achieving equity. This study aims to identify and analyze to what extent existing different rooftop greening incentives and mandatory policies in three American cities, including New York, Chicago, and Philadelphia, address environmental justice. Nine policies were analyzed from three cities based on three dimensions of environmental justice. The results show that all policies have neglected a degree of distributional, recognitional, and procedural environmental justice in their policies. Although incentives try to advance distributional justice by implementing green roofs in different parts of the city, these policies do not pay enough attention to support themes such as zoning, size, rental status, land value, and affordability in all urban areas. [ABSTRACT FROM AUTHOR]

The paper proposes a spreadsheet-based model to simulate the hydrological response of a pilot installation of modular tray-based blue roof (BR). The BR is installed on the roof terrace of a building in the Campus of the University of Catania (Italy). The paper firstly describes the results of preliminary field experiments on the pilot aimed at evaluating hydrological parameters used in the model, i.e. the runoff coefficient and the initial abstraction of the terrace, and the evaporation from the BR. Then, the model was applied to 26 precipitation events recorded in the period from 2018 to 2020. Results of the application show a good ability of the model to reproduce the hydrological behaviour of the BR during precipitation events. Finally, the paper discusses limitations of the results obtained and potential for model improvement. [ABSTRACT FROM AUTHOR]

Urban floods caused by expanding impervious areas due to urban development and short-term heavy precipitation adversely affect many coastal cities. Notably, Seoul, one of the coastal cities that experiences acute urban floods, suffers annually from urban floods during the rainfall season. Consequently, to mitigate the impacts of urban floods in Seoul, we established flood-vulnerable areas as target areas where green infrastructure planning was applied using the Stormwater Runoff Reduction Module (SRRM). We selected the Gangdong, Gangbuk, and Dobong districts in Seoul, Korea, all of which demonstrate high flood vulnerability. Analyses in reducing the runoff amount and peak time delay effect were estimated by model simulation using the SRRM. The reduction in peak discharge for the whole area occurred in the following order: Gangdong district, then Gangbuk district, and lastly Dobong district. In contrast, the reduction in peak discharge per unit area was most prominent in Gangbuk district, followed by Dobong and Gangdong districts. However, the delay effect was almost identical in all target areas. Based on the simulation results in this study, we planned green infrastructure, including green roofs, infiltration storage facilities, and porous pavement. We believe that the results of this study can significantly enhance the efficiency of urban flood restoration and green infrastructure planning in coastal cities. [ABSTRACT FROM AUTHOR]

Runoff modelling is a crucial element in hydrologic sciences. However, a global runoff database is not currently available at a resolution higher than 0.1°. We use the recently developed Global Curve Number dataset (GCN250) to develop a dynamic runoff application (2015 – present) and that can be accessed via a Google Earth Engine application. We also provide a global mean monthly runoff dataset for April 2015-2021 in GeoTIFF format at a 250-meter resolution. We utilize soil moisture and GPM rainfall to dynamically retrieve the appropriate curve number and generate the corresponding runoff anywhere on Earth. Mean annual global runoff ratio results for 2021 were comparable to the runoff ratio from the Global Land Data Assimilation System (0.079 vs. 0.077, respectively). Mean annual global runoff from GCN and GLDAS were within 11% each other for 2020–2021 (0.18 vs. 0.16 mm/day, respectively). The GCN250 runoff application and the dataset are useful for many water applications such hydrologic design, land management, water resources management, and flood risk assessment. Measurement(s) runoff Technology Type(s) Natural Resources Conservation Service Curve Number Method Factor Type(s) Curve Number • Soil Moisture • Rainfall Sample Characteristic - Environment land [ABSTRACT FROM AUTHOR]

A precise rainfall-runoff prediction is crucial for hydrology and the management of water resources. Rainfall-runoff prediction is a nonlinear method influenced by simulation model inputs. Previously employed methods have some limitations in predicting rainfall-runoff, such as low learning speed, overfitting issues, stopping criteria, and back-propagation issues. Therefore, this study uses distinctive soft computing approaches to overcome these issues for modeling rainfall-runoff for the Mangla watershed in Pakistan. Rainfall-runoff data for 29 years from 1978–2007 is used in the study to estimate runoff. The soft computing approaches used in the study are Tree Boost (TB), decision tree forests (DTFs), and single decision trees (SDTs). Using various combinations of past rainfall datasets, these soft computing techniques are validated and tested for the security of efficient results. The evaluation criteria for the models are some statistical measures consisting of root means square error (RMSE), mean absolute error (MAE), coefficient of determination (R2), and Nash–Sutcliffe efficiency (NSE). The outcomes of these computing techniques were evaluated with the multilayer perceptron (MLP). DTF was found to be a more accurate soft computing approach with the average evaluation parameters R2, NSE, RMSE, and MAE being 0.9, 0.8, 1000, and 7000 cumecs. Regarding R2 and RMSE, there are about 57% and 17% of improvement in the results of DTF compared to other techniques. Flow duration curves (FDCs) were employed and revealed that DTF performed better than other techniques. This assessment revealed that DTF has potential; researchers may consider it an alternative approach for rainfall-runoff estimations in the Mangla watershed. [ABSTRACT FROM AUTHOR]

Using local sources (roof runoff, stormwater, graywater, and onsite wastewater) to meet non-potable water demands can minimize potable water use in buildings and increase supply reliability. In 2017, an Independent Advisory Panel developed a risk-based framework to identify pathogen log reduction targets (LRTs) for onsite non-potable water systems (ONWSs). Subsequently, California's legislature mandated the development and adoption of regulations--including risk-based LRTs--for use in multifamily residential, commercial, and mixed-use buildings. A California Expert Panel was convened in 2021 to (1) update the LRT requirements using new, quantitative pathogen data and (2) propose treatment trains capable of meeting the updated LRTs. This paper presents the updated risk-based LRTs for multiple pathogens (viruses, protozoa, and bacteria) and an expanded set of end-uses including toilet flushing, clothes washing, irrigation, dust and fire suppression, car washing, and decorative fountains. The updated 95th percentile LRTs required for each source water, pathogen, and end-use were typically within 1-log10 of the 2017 LRTs regardless of the approach used to estimate pathogen concentrations. LRT requirements decreased with influent pathogen concentrations from wastewater to graywater to stormwater to roof runoff. Cost and footprint estimates provide details on the capital, operations and maintenance, and siting requirements for ONWS implementation. [ABSTRACT FROM AUTHOR]

Green roof technology can partially mitigate the adverse effects of urbanization by controlling stormwater runoff, pre-filtering water, minimizing climate change outcomes and reducing heat island effects. However, improvements to current green roof systems and innovative approaches are paramount to advancing environmental benefits and consumer acceptance of this technology. Regular green roofs are hindered by high cost and mass, as well as the incorporation of large amounts of polymers. Hydroponic green roofs (HGRs) require specific setups, maintenance and frequent replacement of plant-growing substrate, with limited energy savings in the heating and cooling load of the building due to the space between the roof surface and the hydroponic setup. In this review, a comparison of regular and HGRs is provided, and research into the environmental benefits of these technologies, including stormwater control, water purification and lifecycle assessment, is summarized. Following this, the prospect of porous concrete (PC), as a combined plant-growth substrate and structural layer in a novel extensive hydroponic green roof (EHGR) design is proposed, through a compilation and analysis of recent studies reporting the feasibility of this construction material for different applications. The mechanical, hydrological and vegetative properties of PC are discussed. Finally, a new green roof system that incorporates both PC and hydroponics, termed the EHGR system, is presented. This new green roof system may help offset the effects of urbanization by providing stormwater and pollution control, runoff delay and physical and thermal benefits, while concurrently producing biomass from a reusable substrate. [ABSTRACT FROM AUTHOR]

Green roof systems (GRs) are effective tools for urban stormwater management. However, there is limited documentation of the long-term hydrological performance of GRs to support decision-making. This study evaluated long-term field monitoring records (7 years) from a 12-year-old GR, situated in a Moist Subtropical Mid-Latitude Climate, to analyze seasonality in and evolution of hydrological performance. The monitoring system was built within a pan lysimeter buried under substrate layers matching the surrounding GR. The monitoring results highlight the efficacy of this GR in long-term stormwater runoff control. The GR can retain 87% of the annual precipitation and return 54% of the precipitation to the atmosphere through evapotranspiration (ET) and sustain long-term event-based mean runoff volume reductions, peak flow reductions, and flow delays of 82%, 93%, and 4.3 h, respectively. The initial moisture content prior to events was highly correlated with hydrological performance, with a seasonal mean Spearman correlation coefficient of 0.47, suggesting the potential of enhancing ET from the GR to improve performance. Substrate water holding capacity increased over time, but no obvious changes in water retention performance were observed. These monitoring results from the aging GR demonstrate the effectiveness of GR systems for long-term stormwater management. [Display omitted] • A GR was monitored using a sensor network for >10 years. • The GR presented a long-term mean event retention of 82%. • The GR retention was more sensitive to initial moisture content than precipitation. • Evolution of soil water properties did not obviously decrease water retention. [ABSTRACT FROM AUTHOR]

The quantity and quality of runoff from green roofs have so far been studied using an extensive vegetated roof (substrate depth > 150 mm). However, studies on various substrate depths and vegetation for runoff and phytoremediation in temperate and monsoon climates, where heavy rain is concentrated in a specific season, are limited. Therefore, the purpose of this study was to investigate combined effects of substrate depth and vegetation of an unfertilized green roof on runoff reduction and airborne pollutant purification based on rainfall intensity. A total of 21 plots were implemented on a roof top with three substrate depths (100, 200, and 400 mm), two vegetation s (vegetated or non-vegetated), and control (plot with standard frame only). The runoff reduction increased significantly (p < 0.05) with increasing substrate depth. Vegetated plots had a slightly higher runoff reduction than plots without vegetation. Compared to controls, turbidity and pH tended to increase regardless of vegetation or substrate depth, with the exception of electrical conductivity (EC). However, concentrations of heavy metals (Cu, Zn, Mn, and Cd) in the runoff of vegetated plots were all significantly (p < 0.05) lower than those of un-vegetated plots and controls. These results suggest that as the rainfall intensity increases, the depth of the substrate is more important than vegetation for runoff reduction. In addition, the vegetation can be an effective tool to neutralize acid rain to stabilize pH and effectively reduce EC and heavy metals in the runoff by remediating dissolved air pollutants from rainwater. [ABSTRACT FROM AUTHOR]

Hydrometeorological observations of small watersheds of the northeast Pacific coastal temperate rainforest (NPCTR) of North America are important to understand land to ocean ecological connections and to provide the scientific basis for regional environmental management decisions. The Hakai Institute operates a densely networked and long-term hydrometeorological monitoring observatory that fills a spatial data gap in the remote and sparsely gauged outer coast of the NPCTR. Here we present the first 5 water years (October 2013–October 2019) of high-resolution streamflow and weather data from seven small (< 13 km 2) coastal watersheds. Measuring rainfall and streamflow in remote and topographically complex rainforest environments is challenging; hence, advanced and novel automated measurement methods were used. These methods, specifically for streamflow measurement, allowed us to quantify uncertainty and identify key sources of error, which varied by gauging location. Average yearly rainfall was 3267 mm, resulting in 2317 mm of runoff and 0.1087 km 3 of freshwater exports from all seven watersheds per year. However, rainfall and runoff were highly variable, depending on the location and elevation. The seven watersheds have rainfall-dominated (pluvial) streamflow regimes, streamflow responses are rapid, and most water exports are driven by high-intensity fall and winter storm events. The complete hourly and 5 min interval datasets can be accessed at 10.21966/J99C-9C14 (Korver et al., 2021), and accompanying watershed delineations with metrics can be found at 10.21966/1.15311 (Gonzalez Arriola et al., 2015). [ABSTRACT FROM AUTHOR]

As an impact of climate change, water-related disasters, such as floods, are becoming more frequent. In this context, there is an increasing demand to improve the resiliency of urban settlements, using multiple approaches and techniques. This paper assesses one of those techniques, by developing an algorithmic-parametric tool to quantify how urban forestry reduces flood impacts from rainfall runoff. The assessment was comprised by three main methodological steps: (#1) observing the scientific literature on "the sponge effect" observed in green infrastructures; (#2) developing an algorithmic-parametric tool using the Grasshopper application to estimate rainfall runoff, considering the influence of urban forestry design factors; and (#3) performing digital simulations with this parametric tool using a Rhinoceros-Grasshopper interface. Results indicate this method is effective in assessing the efficacy of green interventions to mitigate urban flood damage and also in foreseeing how different design strategies impact urban hydrological dynamics. [ABSTRACT FROM AUTHOR]

This study proposes the technology of "runoff storage and seepage utilization" for achieving purification of road rainfall–runoff and presents a multi-level series purification system (PBT-GR) comprising porous asphalt pavement (PAP), a bioretention system (BS), a storage tank (T) and a hydroponic green roof (GR). The operation parameters of each component unit were optimized and the contribution of each unit to pollution was analyzed. The results showed that under typical simulated rainfall, the suspended solids (SS), total nitrogen (TN), total phosphorus (TP), Pb, Zn and Cu removal rates by filtration and interception of porous pavement were 62.26 ± 3.19%, 16.29 ± 1.74%, 29.27 ± 1.37%, 37.61 ± 2.58%, 35.57 ± 4.64% and 31.17 ± 3.27%, respectively. The average concentrations of SS, TN, TP, Pb, Zn and Cu in the effluent of the PBT-GR system were 14.70 ± 2.21 mg/L, 1.52 ± 0.24 mg/L, 0.14 ± 0.04 mg/L, 0.09 ± 0.04 mg/L, 0.11 ± 0.03 mg/L and 0.04 ± 0.01mg/L, respectively, which met the water quality standards recommended in the Chinese guidelines and showed a high adaptability to pollution load. The contents of pesticide residues and heavy metals in cultivated vegetables met the national standards. The period required to recoup the investment in the system was approximately 3 years, indicating its good economic feasibility. The present study can provide a valuable reference of the construction of an efficient, low consumption and sustainable urban stormwater treatment system and can contribute to the improvement in the quality of the urban water environment. [ABSTRACT FROM AUTHOR]

Increasing urbanization related to land pressure and the soil arising from it are aggravating factors of flood risk in urban areas, including storm water runoff. Therefore, urban sanitation networks face an excess of water that exceeds their absorption capacity. This article deals with the effect of impermeability in densely populated urban areas and the function of a combined sewer system under higher rainfall intensities using the Storm Water Management Model (SWMM). The objective is to simulate a possible increase in rainfall intensities for reducing overflow points in the combined sewage system at the study area, which was the city of Ahmed Rachdi, Mila in Algeria. The excessive rainfall intensities were modeled using the SWMM software program to estimate maximum water volumes inside the combined sewage system of the study area. To evaluate the model's performance, a comparison process was used between the values of the flow rates of the pipelines of the sewerage system combined with the design flow rates in the current state and the flow rates of a single modeling of future events available during the study interval. The comparison results showed a good and convergent performance for these models. The results of the flooding volumes using different values of rainfall intensities and different return periods, which were 2, 5, 10 and 25 years, in the modeling of the combined sewage system are 3626, 6888, 8636 and 12676m³, respectively. The suggested scenario included increasing diameters of some pipes in the combined sewage system pipelines. The results using this scenario showed reductions in the total percentage of overflow points from the integrated sewage system of 52.42%, 40.63%, 31.83% and 20.51% using the rainfall intensities for the return periods of 2, 5, 10 and 25 years, respectively. The present study can provide technical support for using software in the planning, controlling and tests of the sewer systems, which contribute to solving the sewer systems' problems. [ABSTRACT FROM AUTHOR]

The 1D sewer - 2D surface coupled hydrodynamic model has increasingly become an essential tool for simulating and predicting the flood process and is widely used in the study of urban rainfall-runoff simulation. The current method of using the smaller time step of the sub model in the coupled model as the synchronization time greatly limits the computational efficiency, especially in the case of the large data amount or models executed in different platforms and in various types of codes. To evaluate the impact of time synchronization on the rainfall-runoff process in a coupled hydrodynamic model, a new model that couples the 2D GPU accelerated shallow water model and the 1D SWMM is applied to two urban catchments to simulate the rainfall-runoff-drainage processes, the fixed time step (5 s, 10 s, 30 s, 60 s, 120 s, 180 s and 300 s) is adopted to ensure the calculation efficiency and precision of the model. The results show that the time computational efficiency can be improved by 7.27%–27.37% in different scenarios compared with the method applying 2D model time step as the synchronization time; the surface runoff process is hardly affected as the synchronization time changes; and the relative error of the drainage process is less than 2.5% when the synchronization time is less than 60 s. Therefore, the fixed synchronization time method is recommended in the 1D-2D coupled model to improve the computational efficiency for flood and inundation simulation. Based on the advantage that the fixed synchronization time is easy to realize in the programming of the model and the high efficiency of the fixed synchronization time method concluded above, this work is expected to provide a reference for model coupling applications. [ABSTRACT FROM AUTHOR]

This study evaluated the potential of transforming nonvegetated (grey) roofs into vegetated (green) roofs to increase their water retention capacity and the retention of surface runoff in Taipei City. Of the total area of Taipei City (26 855 ha), we found that 304.5 ha of grey roof could be converted to green roof. Residential areas with higher living standards had a greater potential for grey roof to green roof transformation. The sampled substrate had an average porosity of 59.2% and a bulk density of 1.00 g/cm3. Surface runoff is likely to occur when the level of precipitation exceeds the field capacity of the green roof (13.3 mm/day). The highest percentage of runoff reduction (59.0%) occurred in the cold season. During the rainy months, the runoff reduction ranged from 14% to 28%. The water retention capacity of the green roof was higher during low‐intensity rainfall events than during high‐intensity rainfall events. [ABSTRACT FROM AUTHOR]

This study quantified how a smart rainwater harvesting cistern that collected stormwater runoff from a green roof reduced stormwater flow into a combined sewer system (CSS) during wet-weather flow. The studied smart rainwater harvesting cistern collected runoff from a green roof located in Bronx, New York City; it used the Continuous Monitoring and Adaptive Control (CMAC) smart sensor provided by OptiRTC, Inc., to regulate the water flow from the cistern. The cistern collected stormwater runoff from the roof, usually draining completely after 24 h of dry weather. However, the smart sensor used weather forecasting data, and if additional rainfall was predicted immediately following another storm, the cistern only drained a specific amount, calibrated to mitigate the CSO. Five years of data from the cistern system were used to understand the role of the cistern's smart sensor in reducing stormwater flow into the CSS during storms. The study results demonstrate that connecting the smart cistern system to the green-roof maximized stormwater collection (compared with the green roof alone) for storm sizes between 2 mm and 25 mm and for antecedent dry-weather periods greater than 2 days. The total of 65.2% of rainfall retained over the monitoring period by the green roof alone increased to 75.6% when considering the total stormwater retained and detained together by the green roof and cistern, thus yielding a 10% improvement. The study results also demonstrate that the smart sensor's use of weather forecasting data failed to improve system performance. [ABSTRACT FROM AUTHOR]

Urban flooding is increasing due to climate change and the expansion of impervious land surfaces. Green roofs have recently been identified as effective solutions for mitigating urban stormwater. However, discharge routes that involve receiving catchments of stormwater runoff from roofs to mitigate high flows have been limited. Thus, a hydrological model was constructed to investigate the effects of changing discharge routes on stormwater flow. Three hypothetical scenarios were assessed using various combinations of discharge routes and roof types. The reduction effects on outflow and overflow were identified and evaluated across six return periods of designed rainstorms in the Tai Hung Tulip House community in Beijing. The results showed that green roofs, together with the discharge routes connecting to pervious catchments, were effective in reducing peak flow (13.9–17.3%), outflow volume (16.3–27.3%), drainage overflow frequency, and flood duration. Although mitigation can be improved by considering discharge routes, it is limited compared to that achieved by the effects of green roofs. However, integrating green roofs and discharge routes can improve community resilience to rainstorms with longer return periods. These results provide useful information for effective design of future stormwater mitigation and management strategies in small-scale urban areas. [ABSTRACT FROM AUTHOR]

Green roofs have become increasingly common in urban areas to slow and reduce stormwater runoff from buildings. However, phosphorus has been found to leach from green roofs. Water treatment residuals (WTRs), a waste product in the water treatment process, may help reduce leaching of phosphorus from green roofs. This study evaluated a green roof retrofit that consisted of a WTR filter at the green roof drain to reduce phosphorus in runoff. Samples of rainfall, runoff from a green roof, and runoff from a regular roof were collected every time it rained and analyzed for total phosphorus (TP), phosphate (PO43-), copper (Cu) and zinc (Zn). Samples were taken January-March 2020 and September 2020-March 2021. Phosphate and TP concentrations were significantly lower (p<0.05) with the retrofit during the winter (Jan-March 2020 and 2021) but not during the fall (Sept-December 2020). The change in WTR efficacy may be due to the WTRs drying out during the summer months, although it appears the WTRs are effective once they have been resaturated during the fall wetting period. This study shows that the WTR retrofit may reduce phosphorus leaching as long as the WTRs do not dry out. The WTRs should be replaced each fall in regions that experience dry summer months to maximize efficacy. [ABSTRACT FROM AUTHOR]

The campus is facing the problems of waterlogging and runoff pollution. To mitigate these phenomena, this study constructs a SWMM model using a campus as the study area. The reduction effects of runoff volume and pollutant load under four LID facility combination scenarios were simulated. Eleven evaluation indicators were selected from environmental, economic and social aspects, and the weights of each indicator were calculated by applying the CRITIC method. The relative percentage of different rainfall recurrence periods under the same evaluation indicator was obtained. The composite index method is used to calculate the composite index for each scenario. The combination of rain garden, permeable pavement, bioretention and green roof is determined as the optimal scenario. The Fuzzy pattern recognition method is used to select three representative rainfall events and simulate the reduction effect of runoff volume and pollutant load under four scenarios to further verify the optimal scenario. The results show that the reduction rates of runoff volume and pollutant load under scenario 4 are 2.7%, 4.2% and 4.7% higher than those under scenarios 1, 2 and 3. Based on the above study, the optimal LID facility combination selected in this paper will provide a reference for the construction of sponge facilities similar to this study area. [ABSTRACT FROM AUTHOR]

A study was undertaken to identify differences in the performance of low-impact development (LID) measures in arid and humid cities. Yinchuan and Guangzhou in China were selected as a representative of each type. A stormwater management model was constructed with the aid of a geographic information system and LID measures of permeable pavements (PP), rain gardens (RG), green roofs (GR) and combinations of these were then designed. The results showed that a combination of PP, RG and GR provided the largest reduction in total runoff, peak runoff and runoff coefficient in both cities. Paired measures also delivered a significantly higher performance than single measures, with PP plus GR better than other paired combinations. The results of this work could guide the construction of sponge cities in both arid and humid areas. [ABSTRACT FROM AUTHOR]

The mijration law of runoff pollutants in bic-retention tank was studied through the experimentaO research, containing calculation formulo of poOutantr reduction coefficient. After ihat, the technolooy of reducing and controlling runoff pollution by bio-retention ink was demonstrated. The result showed that bio-retention tank can reduce runoff by 15% -85%, and the pollutant emissions can be cut by 35% -95%. At the same time, it had good ecolooical landscape effect. The study can provide a referencc for the desion method of road bio-retention tank in sponge city construct ion, and basio technical methods and parametere for ihe subsequent construction of comprehensivv control platform foe urban rainwatee runoff and the layout optimization of comprehensivv measures of watee quality and quantity. [ABSTRACT FROM AUTHOR]

In the recent years natural phenomena such as flood have cost billions of euros and numerous losses of human life. In this context, accurate modelling of storm runoff from urban catchments is very important, but it is difficult to achieve because of the complexity of modelling green areas. Depending on the local practice, the available software, the data availability, the possibility of data processing, computation time, and even the experience of the modeller, storm runoff from urban catchments can be analysed using different modelling approaches. Choosing the modelling approach, the rainfall loads to the model and the model parameters are very important steps that must be made with caution, and there is thus a need to establish more precise guidelines to help modellers in choosing the most suitable modelling approach. The overall objective of the research project is to investigate the possibilities of managing the storm water to cope with climate change in a sustainable way. The storm water can be used as a resource, as an element in urban recreational activities. This initiative is supported by the key principles of sustainability: water recycling, minimizing pollutants in storm water and urban environmental protection against flood events. [ABSTRACT FROM AUTHOR]

Due to substrate layers with different substrate configurations, extensive green roofs (EGRs) exhibit different rainfall runoff retention and pollution interception effects. In the rainfall runoff scouring process, nutrient leaching often occurs in the substrate layer, which becomes a pollution source for rainwater runoff. In this study, six EGR devices with different substrate layer configurations were fabricated. Then, the cumulative leaching quantity (CLQ) and total leaching rate (TLR) of NH4+, TN, and TP in the outflow of nine different depth simulated rainfall events under local rainfall characteristics were evaluated and recorded. Furthermore, the impact of different substrate configurations on the pollution interception effects of EGRs for rainfall runoff was studied. Results show that a mixed adsorption substrate in the EGR substrate layer has a more significant rainfall runoff pollution interception capacity than a single adsorption substrate. PVL and PVGL, as EGRs with layered configuration substrate layers, exhibited good NH4+-N interception capacity. The CLQ and TLR of NH4+-N for PVL and PVGL were − 114.613 mg and − 63.43%, − 121.364 mg, and − 67.16%, respectively. Further, the addition of biochar as a modifier significantly slowed down the substrate layer TP leaching effect and improved the interception effect of NH4+-N and TN. Moreover, although polyacrylamide addition in the substrate layer aggravated the nitrogen leaching phenomenon in the EGRs' outflow, but the granular structure substrate layer constructed by it exhibited a significantly inhibited TP leaching effect. [ABSTRACT FROM AUTHOR]

The objective of this study was to compare the hydrological performance of an irrigated, 127 mm deep green roof, planted with vegetation native to the New York City area, to a conventional, non-irrigated, 100 mm deep green roof, planted with drought-tolerant Sedum spp. Four years of climate and runoff data from both green roofs were analyzed to determine seasonal stormwater retention. Empirical relationships between rainfall and runoff were developed for both roofs, and applied to historical rainfall data in order to compare stormwater retention values for different rainfall depths. Crop coefficients for the vegetation on each green roof were estimated using the soil moisture extraction function. This function was also used to estimate monthly evapotranspiration. Despite being irrigated, the green roof with native vegetation retained more stormwater per annum (64%) than the non-irrigated green roof planted with Sedum spp. (54%). The green roof planted with native vegetation also had approximately twice the crop coefficient (1.13) than the green roof planted with Sedum spp. (0.57), indicating that the New York City native plants transpire more stormwater than the Sedum spp. plants given certain climate and substrate moisture conditions. Overall, the results of the study indicate that, for the New York City climate region, irrigated green roofs of native vegetation have the capacity to better manage stormwater than non-irrigated green roofs planted with drought-tolerant succulents. [ABSTRACT FROM AUTHOR]

Precise and reliable runoff forecasting is crucial for water resources planning and management. The present study was conducted to test the applicability of different data-driven techniques including artificial neural networks (ANN), support vector machine (SVM), random forest (RF) and M5P models for runoff forecasting for the lead time of 1 day and 2 days in the Koyna River basin, India. The best input variables for the development of the models were selected by applying the Gamma test (GT). Two different scenarios were considered to select the input variables for 2 days ahead runoff forecasting. In the first scenario, the output of 1 day ahead runoff (t + 1) was not used as an input while it was also used as an input along with other input variables for the development of the models in the second scenario. For 2 days ahead runoff forecasting, the models developed by adopting the second scenario performed more accurately than that of the first scenario. The RF model performed the best for 1 day ahead runoff forecasting with root mean square error (RMSE), coefficient of efficiency (CE), correlation coefficient (r) and coefficient of determination (R2) values of 168.94 m3/s, 0.67, 0.84 and 0.704, respectively, during the test period. For 2 days ahead runoff forecasting, RF and ANN models performed the best in the first and second scenario, respectively. In 2 days ahead runoff forecasting, RMSE, CE, r and R2 values were observed to be 169.72 m3/s, 0.67, 0.84, 0.7023 and 148.55 m3/s, 0.74, 0.87, 0.76 in the first and second scenarios, respectively, during the test period. Finally, the results revealed that the addition of 1 day ahead runoff forecast increased the forecast accuracy of 2 days ahead runoff forecasts. In addition, the dependability of the various models was determined using the uncertainty analysis. [ABSTRACT FROM AUTHOR]

Recent studies have provided explicit analytical equations that can be used to quantify directly the hydrologic performance statistics of green roofs, such as runoff-reduction ratios. These equations were obtained based on simplified representations of the hydrologic and hydraulic processes occurring on and inside green roofs, as well as stochastic models describing local rainfall characteristics. To simplify derivations, these studies considered only saturation-excess runoff and neglected infiltration-excess runoff that may be generated from green roofs. We develop a method for considering both saturation- and infiltration-excess runoff; the proposed analytical equations can be used to directly quantify the performance statistics of any type of green roof. Systematic comparisons of analytical and numerical simulation results were also conducted to demonstrate the accuracy of the analytical equations. As an alternative to numerical simulations, the analytical equations can be used by engineers to more conveniently quantify the performances of alternative green roof configurations. [ABSTRACT FROM AUTHOR]

This article aims to analyse the performance of green roof in runoff reduction. A case study has been conducted through a deployed green roof at the custom house quay building in Dublin, Ireland. Modular green roofs have been deployed which have IoT scales associated to it for measuring the effective reduction in runoff. Hydro-meteorological variables such as rainfall, temperature, relative humidity and wind speed values were corresponded to the amount of runoff reduction by means of a regression-based relationship. Comparison of the observed runoff reduction from a modular green roof and that estimated based on the developed regression relationship yielded a R2 value of 0.874. Through this research, a pattern was identified which established that longer records and better weather variables data have the potential to improve the performance of the regression model in predicting the amount of runoff reduction corresponding to different rainfall and weather patterns. In general, performance of green roof was found to be highly positively correlated to the amount of rainfall received; however, low correlation between rainfall and the percentage of runoff reduction indicate that saturated soil in green roofs considerably deteriorates the performance in runoff reduction. Overall, this study can help in identification of locations where installation of green roofs can help mitigate floods at a city scale. [ABSTRACT FROM AUTHOR]

Urbanization and population growth result in an increase of insufficient groundwater recharge. In order to overcome the adverse effects of urbanization, low impact development (LID) best management practices (BMPs) are introduced. LIDs are nature-based solutions, also called green infrastructures, that have the ability to control both the amount and the quality of stormwater runoff. Rain barrels, vegetative swale, green roofs, bioretention, permeable pavement, and detention ponds are among the examples of LIDs. Within this context, the infiltration trench is also one of the important LID types and is widely implemented in settlement areas. Field-scale experiments may not be sufficient in determining the design criteria of infiltration trenches. Controlled experiments should be conducted in order to identify the optimum design criteria of infiltration trenches for best practices. In this study, the hydrological performance of the infiltration trench is investigated by conducting experiments using an open-lab large-scale rainfall-watershed-infiltration trench (RWI) experimental setup. The RWI experimental setup is built at the Avcılar Campus of Istanbul University-Cerrahpaşa and consists of an artificial rainfall system, an impermeable drainage area, and an infiltration trench. The effect of gravel size, berm height, and rainfall type on the hydrological behavior of the infiltration trench is tested by conducting several experiments. During these experiments, the overflow rate and the drainage rate are measured at the exit of the pipes, located on the front wall and on the base of the infiltration trench, respectively. Results show that the magnitude and lag time of the overflow rate hydrograph are affected by rainfall intensity, gravel size, and berm height significantly. On the other hand, minor changes on the drainage rate hydrograph are observed under different rainfall intensities, gravel sizes, and berm heights. Based on the outcomes of this study, the engineering design guidelines of infiltration trenches are elaborated. [ABSTRACT FROM AUTHOR]

Rainfall retention and runoff detention are likely the most important ecosystem services provided by extensive green roofs (EGRs) that contribute to urban stormwater mitigation and management. However, the hydrological performance and runoff generation mechanisms of mature, well‐established EGRs in tropical regions remain poorly understood. This study evaluated the rainfall retention, discharge detention times and processes of runoff generation in two neighbouring 20‐year‐old EGRs with different slopes (2° and 14° for EGRns and EGRws, respectively) and management practices in Mexico City; results were compared with those obtained in a conventional roof (CR, 2° slope). Precipitation, substrate moisture and storm runoff were continuously measured during the 2017 and 2018 rainy seasons (May–November). Results showed spatial differences in substrate properties and moisture within and between green roofs. In general, higher bulk densities and a wide range of variation in water content characterized the bare substrate areas compared to those below vegetation. Greatest increases in substrate moisture and storm runoff were observed in the steeper green roof. Subsurface flow was the dominant process controlling the amount and timing of stormflow in the EGRs. The occurrence of saturation excess overland flow was small and detected when large rain events were preceded by high wetness conditions. The main factors influencing the hydrological responses of the green roofs were their substrate hydrophysical properties, related mostly to vegetation cover, management and age, and to much lesser extent to slope and substrate depth. On average, rainfall retention was ~60% in the EGRs with significantly longer delays and prolonged runoff times (100 and 340 min, respectively) compared to CR (3%, 20 min, and 258 min, respectively). Overall, these findings highlight the potential of EGRs in reducing stormflow and peak discharges for most rainfall in Mexico City, and thus mitigating the risk of saturation and overflow of urban drainages. [ABSTRACT FROM AUTHOR]