Stormwater Drainage Systems Research Articles

A 3D Spatial Model to integrate Stormwater Drainage Design into Public Space

Abstract. This paper explores the integration of water sensitive urban design within public space planning using integrated 3D digital technologies. In traditional design processes, drainage and public space design often utilise distinct software and are led by different professionals, which creates significant communication barriers.Although civil and hydraulic engineers have made significant strides in integrating hydrology analysis with multi-objective space design, the collaboration of conventional 2D hydrology with 3D landscape design still presents challenges. To address these challenges, this study proposes a novel approach that integrates drainage analysis and design within a 3D design model. This methodology is specifically designed to aid landscape and urban designers in incorporating stormwater management and drainage systems early in the design process. The approach involves three key steps: (1) identifying critical factors that impact, or are impacted by, drainage design; (2) translating these factors into specific spatial parameters; and (3) developing a workflow to integrate these parameters. This integration not only streamlines the design process, making it more cohesive and efficient but also mitigates potential conflicts between drainage requirements and spatial design, thereby reducing unnecessary revisions. Ultimately, this approach enhances the incorporation of essential drainage considerations into urban and landscape planning, leading to more sustainable and functional public spaces.

Predicting the urban stormwater drainage system state using the Graph-WaveNet

Graph Neural Networks (GNNs) have been applied to network data such as traffic flow and water distribution systems, yet their use in predicting the state of urban stormwater drainage systems remains rare. This study investigates the application of Graph-WaveNet (GWN), a type of GNN, in forecasting the states of stormwater systems in Kowloon, Hong Kong. Data was sourced from the Storm Water Management Model (SWMM) spanning 43 rainfall events from 2020 to 2023. Based on the preceding 30 to 60 min of network states and rainfall data, GWN predicted junction inflows, pipe flow rates, and relative water depths (fraction of full area filled by flow) for lead times up to 20, 20, and 30 min, with an R2 greater than 0.6, respectively. Prediction accuracy declines with longer forecast horizons. GWN predicts more time steps ahead for pipes’ flow rates and junctions’ inflows, but fewer for relative water depths during peak versus non-peak periods. It is also more effective at predicting states of large pipes and connected junctions downstream, compared to smaller upstream components. GWN's accuracy improves significantly with precise rainfall nowcasting inputs. This study establishes a significant baseline for GWN's performance in predicting urban stormwater systems during rainfall events.

Application of a microbial and pathogen source tracking toolbox to identify infrastructure problems in stormwater drainage networks: a case study.

Water scarcity and increasing urbanization are forcing municipalities to consider alternative water sources, such as stormwater, to fill in water supply gaps or address hydromodification of receiving urban streams. Mounting evidence suggests that stormwater is often contaminated with human feces, even in stormwater drainage systems separate from sanitary sewers. Pinpointing sources of human contamination in drainage networks is challenging given the diverse sources of fecal pollution that can impact these systems and the non-specificity of traditional fecal indicator bacteria (FIB) for identifying these host sources. As such, we used a toolbox approach that encompassed microbial source tracking (MST), FIB monitoring, and bacterial pathogen monitoring to investigate microbial contamination of stormwater in an urban municipality. We demonstrate that human sewage frequently contaminated stormwater (in >50% of routine samples), based on the presence of the human fecal marker HF183, and often exceeded microbial water quality criteria. Arcobacter butzleri, a pathogen of emerging concern, was also detected in >50% of routine samples, with 75% of these pathogen-positive samples also being positive for the human fecal marker HF183, suggesting human municipal sewage as the likely source for this pathogen. MST and FIB were used to track human fecal pollution in the drainage network to the most likely point source of contamination, for which a sewage cross-connection was identified and confirmed using tracer dyes. These results point to the ubiquitous presence of human sewage in stormwater and also provide municipalities with the tools to identify sources of anthropogenic contamination in storm drainage networks.IMPORTANCEWater scarcity, increased urbanization, and population growth are driving municipalities worldwide to consider stormwater as an alternative water source in urban environments. However, many studies suggest that stormwater is relatively poor in terms of microbial water quality, is frequently contaminated with human sewage, and therefore could represent a potential health risk depending on the type of exposure (e.g., irrigation of community gardens). Traditional monitoring of water quality based on fecal bacteria does not provide any information about the sources of fecal pollution contaminating stormwater (i.e., animals/human feces). Herein, we present a case study that uses fecal bacterial monitoring, microbial source tracking, and bacterial pathogen analysis to identify a cross-connection that contributed to human fecal intrusion into an urban stormwater network. This microbial toolbox approach can be useful for municipalities in identifying infrastructure problems in stormwater drainage networks to reduce risks associated with water reuse.

Perceived Quality of Basic Sanitation: an Analysis From the Four Components

Objective: The study aims to identify users' perceptions regarding the quality of public basic sanitation services based on its four components. Theoretical Framework: Based on existing legislation and the quality of public services, this study focuses on the four components of basic sanitation services and their problems, aiming to investigate users' perceptions. Method: Survey research encompassing 1,114 residents in the state of Rio Grande do Sul. The instrument covered the four components of sanitation (potable water supply, sanitary sewage, urban cleaning and solid waste management, and urban stormwater drainage and management). Descriptive statistics and multiple linear regression analysis were used as analysis techniques. Results and Discussion: The quality of basic sanitation services in all its components is considered satisfactory by users, but improvements are still needed. The frequency of observed problems negatively impacts the perception of service quality. Those who reuse water, separate waste, and whose residences have sewage collection and treatment and stormwater drainage systems attribute higher quality to the service. Research Implications: There is a need to implement a continuous quality evaluation model for sanitation services, as without evaluation, end-user feedback does not exist. Originality/Value: Identification of users' perceptions regarding the quality of basic sanitation services, as no research with this theme covering the entire state has been found so far.

Automatic topology and capacity generation framework for urban drainage systems with deep learning-based land use segmentation and hydrological characterization

This paper proposed a comprehensive and automated framework that integrates the entire urban drainage design process, from refined land use segmentation, to catchment subdivision and characterization, to network topology generation, and finally to hydraulic estimation of pipeline capacity, based on multiple open-source datasets. The method incorporated deep learning-based semantic segmentation, GIS-based hydrological characterization, topology generation and hydraulic calculation algorithms. The performance and applicability of the method were validated through case studies of two cities. The results showed that the deep learning model with prior knowledge could accurately segment urban land use to obtain the detailed shape and boundary description, and achieved higher detection accuracy for water bodies, buildings, and roads. The stormwater drainage topology and conveyance capacity were automatically generated based on subcatchment division and hydrological characterization under a set of topological parameter conditions. In the optimal Critical Success Index (CSI) scenario, only 8% and 21% of the generated pipelines were inconsistent with the expert-designed networks. Compared to the traditional manual design process, the automated approach can save significant time and resources and reduce the reliance on field surveys and empirical/expert work. At the same time, the tool can be employed for system layout and capacity optimization, providing important support for the automation, design, and rehabilitation of stormwater drainage systems.

Modeling nonstationary intensity-duration-frequency curves for urban areas of India under changing climate

Enhancing stormwater drainage systems is paramount amid evolving climate dynamics, necessitating robust design and continual upgrades to address changing environmental conditions. The present work constructs the nonstationary Intensity-Duration-Frequency (IDF) curves for prominent urban areas of India. It develops 2313 nonstationary Generalized Extreme Value (GEV) models in annual and seasonal timeframes by integrating the influence of local and global climate-informed covariates, including time covariates. The work involves analyzing 1, 2, 3, 4, 6, 12, 24, 36, and 48 hourly maximum rainfall series with return periods of 2, 5, 10, 25, 50, and 100 years. Among the 16 urban areas examined, there's a significant shift from stationary to nonstationary extreme rainfall intensities, marked by a 38.7% increase in shorter duration series with a 5-year return period in New Delhi and Visakhapatnam. AMO, DMI, GTA, and LTA in New Delhi play significant roles. Similarly, in Visakhapatnam, SST in Niño 3.4 and DMI are significant covariates influencing nonstationarity. Recently, in the 2023 monsoon, the 25-year flood wreaked havoc in New Delhi, Rajkot, Surat, and Visakhapatnam. Generating nonstationary IDF curves for the annual and seasonal timeframes offers a comprehensive approach to stormwater design and infrastructure upgradation and effective adaptation strategies across sixteen Indian cities.

Geospatial Assessment of the Occurrence of Flooding In Informal Settlements in Ilala Municipality, Tanzania

This article assesses the occurrence of flooding in informal settlements of Ilala Municipality using quantitative and qualitative approaches. Non-probability sampling technique was used to select participants for participatory mapping. Data collection was done through participatory mapping, remote sensing, document review, and field observation. The weighted sum tool in ArcGIS was used to combine flood factors layers and create flood-prone area maps. Participatory mapping was used to map flood depth before data was converted for map visualization. Results indicated that areas with high to very high risk of flooding are generally decreasing over time. From 1990–2000 areas with high risk of flooding covered 31.1% of the study area, decreasing to 21.1% from 2001–2010, while from 2011–2020 it covered 21.6%. However, flood depths increased over time. From 1990–2000 the highest flood depth was 5ft decreasing to 4ft between 2011–2020. Hence, people living in informal settlements are more vulnerable and mostly affected by floods because of disposing of solid wastes into the river valley, which blocks drainage systems, thereby causing overflow of water. Therefore, regulations guiding human development near the river valleys should be improved and unlawful activities in the river valley be discouraged. Again, storm water drainage systems should be protected and well managed as the levels of storm water have become very high over time. Waste collection contracts should be given to private companies which are flexible and able to use alternative means of accessing unplanned streets to easily collect wastes.

The compound impact of rainfall, river flow and sea level on a watercourse through a coastal city: Methodology in making

Due to climate change, future weather conditions will become more extreme. During recent years, several severe damages have been caused by heavy rainfalls in combination with riverine events. Even though the effects of compound events are known to be influential for flood hazard, the method for investigating these types of events is a novel area of expertise. In this study, a methodology was developed to investigate a watercourse, acting as a part of a stormwater drainage system in an urban coastal area, in a hydrodynamic model to find areas prone to flooding. The method was applied for Ståstorpsån in Trelleborg, Sweden. The model was a unified model for seasonal variability and compound events with scenarios developed based on series of data representing normal values of the boundary conditions rainfall, river flow and sea level. The result was analysed graphically and statistically as a flood hazard. The data used was based on data collected during the past 10 years for rain and sea level and 16 years of simulated river flow. The constructed rain events from gauge data all had a return time of less than 10 years. Therefore, the chosen events are considered to represent normal levels. For Trelleborg, the results from the hydrodynamic model indicate that compound events will increase the flood hazard with anincreasing time horizon. The visual analysis converges with earlier flood events, and hotspots are generally seen around bridges and culverts. For the studied area, there is a large seasonal variation in the flood hazard and with climate change, all seasons will cause more severe flood hazards. The effects experienced during a summer event, which is the most severe event today, are to be expected for all seasons in 2100. The effect seen during summer eventsis a combination of all three drivers. However, rain intensity is likely to be more influential for normal events. When a certain threshold value for sea level is reached, sea level becomes the most influential driver, overtaking the other drivers in importance.

Preparing Vulnerable Communities: Disaster Mitigation Strategies for Economically Depressed Areas in Oklahoma

When disasters strike, vulnerable areas that are economically disadvantaged are adversely affected economically, culturally, and healthily, as the lack of resources and vulnerabilities amplify their problems. This research focuses on the population specifics of disaster vulnerabilities and targeted policies for economically depressed neighborhoods in Oklahoma. Relative to less susceptible entities, poor people are likelier to take damage from tornados, winter storms, wildland fires, and flooding because they lack the resources required for preparation, response, and recovery. Through an equity-focused lens, the study examines four key factors amplifying disaster risk: those due to aging critical infrastructure, lack of insurance and savings, health disparities, or the failure to plan adequately. Collapsed stormwater drainage systems, roads, bridges, and water pipes in financially deprived communities experience cracks in a hurry during duresses. With little or no funds, families earning every paycheck cannot afford to purchase rescue insurance or, in the case of names, save money to build an emergency fund, including money to cover repair costs, temporary housing, and other costs. This is, of course, made even worse by any previously existing medical, disability, or mental health issues as well, with poorer health outcomes than might usually be expected since access to healthcare services, treatments, and medications is also disrupted. Lastly, language and education barriers lead to the lower development of disaster plans; the delays include access to early warning systems and a need for more awareness of risks among vulnerable groups. Given these weaknesses, the study offers policymakers, funders, and resilience practitioner’s implementable policy, investment, and community-oriented intervention recommendations. The hazards can be lessened by prioritizing infrastructure upgrades, insurance reduction, and commitment to spread-out shelters and relief supplies. Long-term recovery programs financed specifically by equal aid promote program equity of rebuilding. Regarding inclusive messaging on public preparation and early warnings, local trusted institutions should be appropriated to reach a diverse population. Collaborative networks among government agencies, relief organizations, businesses, and grassroots associations can bolster response capacity. Their unified efforts on localized resilience initiatives advance strategic plans for the state's most economically fragile neighborhoods. Implementation should focus on those with the highest vulnerability markers and the least ability to prepare, respond, and recover independently— metrics assessing community functionality, equity factors, and recovering spending offer evidence-based progress milestones. With climate change projected to increase disaster severity in Oklahoma, research-driven and equitable resilience policies for marginalized communities can reduce prolonged suffering. Tailored preparation, outreach, critical system backups, and financial support lessen acute shocks and accelerate recovery. However, sustainable policy change relies on addressing root socioeconomic inequalities through systemic interventions beyond immediate disaster management.

Hydraulic-based optimization algorithm for the design of stormwater drainage networks

Stormwater drainage networks are designed to reduce the risk of rainwater damage to the served area. The purpose of optimizing a stormwater drainage system is to reduce overall construction costs and to meet hydraulic design requirements. Currently, designs that rely on software or manual calculations are limited by the available time and the designer’s capabilities. In fact, manual optimization for large networks consumes a lot of time and effort, and there is no guarantee that the optimal design is reached, also it is subject to human errors. In recent years, several researchers have focused on creating optimization design algorithms specifically for sewer and storm networks, such as genetic algorithm (GA), linear programming (LP), heuristic programming (HP),…etc. However, these studies were limited to covering one or two design parameters and constraints. Additionally, in some studies, the hydraulic performance of the designed network was not treated in a proper way, especially the water surface profile effects. So, the main objective of the study is to develop an effective hydraulic-based optimization algorithm (HBOA) that can dynamically get the optimal design with minimum total cost for a given storm network layout and meet all hydraulic requirements. To achieve this, a MATLAB code is created and coupled with SewerGEMS software that automatically simulates all expected optimization scenarios based on network hydraulic performance. The HBOA is validated economically and hydraulically using two benchmark examples from the literature. According to the economic validation, the total network cost generated by HBOA was the lowest when compared to the optimization methods found in the literature. During the hydraulic evaluation, it was observed that the optimization algorithm (GA-HP) used in the literature for the benchmark examples does not meet the hydraulic requirements where the networks are flooded, whereas HBOA meets the hydraulic requirements with minimal overall network cost. Also, the HBOA is applied to four real stormwater drainage networks that were already designed, constructed, and optimized manually. The four redesigned real cases using HBOA revealed a cost reduction of about 15% compared to the original designs, while consuming a few hours for the design and optimization processes. Finally, the developed HBOA is a robust, time-efficient, and cost-effective optimization and hydraulic design tool which could be used in the design of stormwater drainage networks with different design constraints with minimal human interference.

Analysis of rainwater utilization technology and current situation in the roof garden

The urban water environment has been deteriorating over the last decade due to land development and climate change, increasing the pressure on urban stormwater drainage systems. With economic development, the value of buildings has also been challenged at a higher level. Roof garden, as a new form of roof treatment, can effectively increase the urban greening area and compensate for the ecological and water environments that have been damaged by building development and utilization. This paper analyzes the advancement of roof garden by comparing it with the traditional sloped roof. The analysis finds that roof gardens can store water and control drainage, and have significant advantages in reducing rainwater discharge, reducing building water demand, and improving the urban water cycle. Roof gardens not only have the ability to utilize rainwater efficiently, but also come with a series of economic, ecological, and social benefits, such as improving the urban heat island effect, saving the amount of water demanded by buildings, and energy consumption. By analyzing domestic and international cases of roof gardens, it is verified that roof gardens are designed as a combination of utility and aesthetics.

Operation Risk Simulation and Interaction Impact of Stormwater and Sewage Systems Based on Storm Water Management Model

With the increasing urbanization rate, higher demand is placed on drainage systems, necessitating analysis of their risk profiles. While many studies focus on the individual hydraulic modeling of stormwater and wastewater systems when considering operational risks, they often overlook the exacerbating effects of combined stormwater and wastewater flows on each other’s risks. In this study, we constructed a model of the combined stormwater and wastewater drainage system in Lijiao, Guangdong Province. We analyzed the operational risks of both stormwater and sewage networks in different scenarios, focusing on full-load pipes, overload pipes, node overflows, and minimum flow velocities. Furthermore, we compared the exacerbating effects of sewage and stormwater on each other’s network operational risks. Simulation results indicated that, for sewage networks with combined sewer sections, the lengths of full-load pipes and overload pipes increased by an average of 27.4% and 16.3%, respectively, during rainy weather scenarios compared to dry weather. After considering the inflow of sewage into combined sewer sections, the average length of full-load pipes increased by 3.8 km, overload pipe length increased by 1.1 km, and overflow volume increased by 2.26 × 104 m3. As the return period of rainfall events increases, these inter-system impacts gradually diminish. Therefore, when modeling drainage systems and assessing operational risks, particularly during low return period rainfall events, the inclusion of both stormwater and sewage in combined sewer networks should be comprehensively considered.

Prevention of flash floods in the town of Kokrajhar through efficient drainage network design

Flash floods are common in the town of Kokrajhar in north-eastern Indian state of Assam. Many areas in the town of Kokrajhar are submerged in water almost every year due to floods during rainy season. These floods cause heavy damage to roads, agricultural production and halt the progress of major infrastructural development projects. Hence, prevention of floods has become an important concern in the town of Kokrajhar. This study investigated the causes of floods and offered a solution for their elimination. The investigation showed that inadequate and inefficient network of storm drains was the reason for the flash floods. A new drainage network for the town of Kokrajhar has resulted from studying the shortcomings of the existing network of storm drains. The new network is designed in accordance with the recommendations stated in the “Manual on storm water drainage systems” prepared by the Central Public Health and Environmental Engineering Organization in 2019.

Improving precipitation estimates for Turkey with multimodel ensemble: a comparison of nonlinear artificial neural network method with linear methods

AbstractEnsemble analysis is proven to provide advantages in climate change impact assessment based on outputs from climate models. Ensembled series are shown to outperform single-model assessments through increased consistency and stability. This study aims to test the improvement of precipitation estimates through the use of ensemble analysis for south and southwestern Turkey which is known to have complex climatic features due to varying topography and interacting climate forcings. The analysis covers an evaluation of the performance of eight regional climate models (RCMs) from the EUR-11 domain available from the CORDEX database. The historical outputs are evaluated for their representativeness of the current climate of the Mediterranean region and its surroundings in Turkey through a comparison with long-term monthly precipitation time series obtained from ground-based precipitation observations by the use of statistical performance indicators and Taylor diagrams. This is followed by a comparative evaluation of three ensemble methodologies, simple average of the models, multiple linear regression for superensemble, and artificial neural networks (ANN). The analysis results show that the overall performance of ensembled time series is better compared to individual RCMs. ANN generally provided the best performance when all RCMs are used as inputs. Improvement in the performance of ensembling due to the use of nonlinear models is further confirmed by fuzzy inference systems (FIS). Both ANN and FIS generated monthly precipitation time series with higher correlations with those of observations. However, extreme events are poorly represented in the ensembled time series, and this may result in inefficiency in the design of various water structures such as spillways and storm water drainage systems that are based on high return period events.

Resilient Stormwater Management of a Coastal Catchment

Designing stormwater drainage systems considering deep uncertainty is a task that has no correct solution, rather, it can only be addressed by managing the system in a smart, robust way. Over recent decades, robust decision-making has been promoted as a solution to planning systems that are vulnerable to deep uncertainty. In this paper, we adopt a robust decision-making methodology to propose a stormwater drainage system in a coastal catchment in an arid region which is vulnerable to sea-level rise and increased precipitation intensity. We used bias-corrected precipitation and sea-level rise projections from a regional climate model, in addition to analyzing observed data. The decision-making methodology adopted is the Dynamic Adaptive Policy Pathways (DAPP). It involves building a decision tree with probable actions to consider when the stormwater system is expected to fail. The success of DAPP relies on continuous and extensive monitoring of the system and all components/factors that form risk or add to the vulnerability of the system, in addition to extensive simulations of the pre-identified actions that enable quick implementation of the solutions preceding failure of the system. This gives an early warning and aids the proactive execution of actions, hence making the system resilient to deep uncertainty. The DAPP for the study site is presented, and the advantages of relying on robust decision-making for arid regions are discussed.

Study rainfall intensity duration frequency relationships under climate change for design of efficient urban stormwater drainage systems in Dodola town, Ethiopia

Study rainfall intensity duration frequency relationships under climate change for design of efficient urban stormwater drainage systems in Dodola town, Ethiopia

Analysis of Stormwater and Rainwater Harvesting Potential Based on a Daily Water Balance Model: A Case Study of Korea

The increasing intensity of rainfall resulting from climate change is projected to worsen the inundation of urban areas by floods. As a viable alternative, stormwater harvesting presents an opportunity to enhance water supply reliability while reducing pressure on both water resources and urban stormwater drainage systems. The stored rainwater can be supplied with a radius of one kilometer around the storage facility, so less pumping energy is consumed compared to supplying the stored rainwater far away from the storage facilities. To visually depict the characteristics of the selected storage facility, land cover maps were created using ArcGIS. These maps were created for a circular region with a radius of one kilometer around each studied storage facility. In this study, a daily water balance model was formulated using spreadsheets to assess the potential of harvesting stormwater and rainwater for various pre-existing storage facilities. Five different types of storage facilities were selected for this study. The term “SRWH facility evaluation criteria” as a whole is used for the storm or rain (SR) water supply satisfaction rate, the SR guarantee rate, and the SR utilization rate. The results provide evidence that, for each selected studied storage facility, the SR water guarantee rate can potentially surpass 70% under conditions of low water demand. Moreover, we investigated the potential of the existing storage facilities to work as multifunctional resources, while the original purpose for which each facility was constructed remains un-affected.

Analysis of suspended solids emissions from a combined sewage system using the Stormwater Management Model (SWMM)

The protection of water bodies requires the reduction of pollutant emissions from all major sources. In urbanized areas, these include: wastewater treatment plants (WWTPs) and (depending on the type of sewage system) combined sewer overflows (CSOs) and stormwater drainage outlets. WWTPs are usually monitored and emitted pollutant loads are known, but it is more difficult to assess the pollutant load discharged by CSOs and stormwater drainage systems. The article attempts to use the Stormwater Management Model (SWMM) to assess emissions of suspended solids from a large urban combined catchment. Suspended solids are the main pollutant of stormwater runoff in urban areas, and the dynamics of their emission from catchments is very diverse. The amount of suspended solids discharged by CSOs functioning in the given city was assessed in comparison with emissions from a wastewater treatment plant. The results show that CSOs discharge a pollutant load to the receiver which is comparable to WWTPs, but in a much shorter time and in a violent manner which can lead to the severe deterioration of receiving water quality. The modelling took into account the quality of dry weather sewage, the build-up of suspended solids, wash-off processes in the catchment area, and local precipitation characteristics. Factors affecting the quality of the obtained model and the accuracy of the emission level assessment were analysed.

Exposure of the US population to extreme precipitation risk has increased due to climate change

The magnitude and frequency of extreme precipitation events in the early twenty-first century have already proven to be increasing at a rate more quickly than previously anticipated. Currently, the biggest consequence of the change in extreme precipitation is the lack of a climate-adjusted national standard taking into account these recent increases that could be used to prevent life and property loss from catastrophic precipitation-driven floods. Here, we address how severe the change in extreme precipitation compares against the current national standard for precipitation climatology (NOAA Atlas 14) and how much of the population is affected by the underestimation of this risk in the contiguous United States (CONUS). As a result, extreme precipitation in the early twenty-first century has outpaced our current national standard in half of CONUS, and the heavy precipitation events experienced recently are quickly becoming a “new normal”, which will increase in severity and frequency in a continually changing climate. Over three-quarters of the U.S. population will likely experience this new normal occurrence of extreme precipitation. As much as one-third of the population is expected to experience the current definition of a 1-in-100-year storm as often as three times in their lifetime. Additionally, the current precipitation standards for designing transportation infrastructure and urban stormwater drainage systems that are built upon Atlas 14 may be insufficient to protect the public's safety and personal/community property from severe flooding. Areas where flood risk is mitigated by operating hydraulic and adaptation structures urgently need to assess the impact of the increased-hourly extreme precipitation and reevaluate their applicable operation rules. Understanding and predicting patterns and the likelihood of short-duration heavy precipitation would be beneficial in preparing for severe precipitation-driven disasters, such as flash floods and landslides, which would happen more frequently in a changing climate. Following the results of this analysis, accelerating the development and dissemination of the next generation of the national standard that has been climatically adjusted to adapt to the new normal is strongly recommended.

Reuse of Wastewater and Hydrogeneration: Sustainable Land Division Project

Abstract The present case study - Sustainable Cerrado Subdivision Project in Arouca (Portugal) - proposes the implementation of a design solution that promotes ‘sustainable neighborhoods’, expanding the concept of ‘sustainable homes’. This type of project results from the application of established construction methodologies and innovative solutions, aiming to meet society’s needs with the least possible mobilization of resources (natural, energy, and financial), considering water and energy efficiency as central elements. More specifically, the goal is to reduce the inflows into public wastewater and stormwater drainage systems by changing the consumption habits of the population and collecting rainwater in impermeable areas, as well as treating greywater for non-potable reuse. In water supply systems, there is potential for energy production through microturbines that can harness the energy required for pressure control - hydrogeneration.