Search Results (20)

Microplastics (MPs) have been extensively studied in the marine environment, but reliable data on their sources and pathways in freshwater ecosystems, which are the main sources of such pollutants, are still limited. In this study, we investigated the spatiotemporal variations, characteristics, and sources of MPs in Nakivubo catchment, which drains waste and stormwater from Kampala city (Uganda) and empties it into Lake Victoria through the Nakivubo channel. Surface water samples (n = 117) were collected from thirteen sites in the Nakivubo catchment (S1 to S13) during the dry and wet seasons in 2022. The MPs were recovered by wet peroxide oxidation protocol, followed by salinity-based density separation, stereomicroscopy, and micro-attenuated total reflectance Fourier-transform infrared spectroscopy. All the samples had MPs, with mean concentrations ranging from 1568.6 ± 1473.8 particles/m³ during the dry season to 2140.4 ± 3670.1 particles/m³ in the wet season. Nakivubo catchment discharges an estimated 293.957 million particles/day into Lake Victoria. A Two-Way ANOVA revealed significant interactive effects of seasons and sampling sites on MPs abundance (p < 0.05). Spatially, the highest mean concentrations of MPs (5466.67 ± 6441.70 particles/m³) were in samples from site S3, which is characterized by poor solid waste and wastewater management practices. Filaments (79.7%) and fragments (17.9%) made of polyethylene (75.4%) and polyethylene/polypropylene co-polymer (16.0%) were the most common MPs. These are likely from single-use polyethylene and polypropylene packaging bags, water bottles, and filaments shed from textiles during washing. These results highlight the ubiquity of MPs in urban drainage systems feeding into Lake Victoria. To mitigate this pollution, urban authorities need to implement strict waste management policies to prevent plastic debris from entering drainage networks. Full article

In Africa, the urban population and informal settlements are increasing, resulting in additional public health and environmental risks and challenges related to the need for basic and sustainable infrastructures and services. In Maputo, the capital of Mozambique, at least 80% of the city is composed of informal settlements, and although some areas are regularized and have approved urbanization plans, the municipality has major deficiencies in meeting current demands in terms of basic infrastructures, such as water supply, sewerage, solid wastes, energy, roads, and communications. Most of the peri-urban areas are occupied by small but overcrowded houses, mostly self-built, served by unpaved roads, and with access limitations. The water pipe network is almost non-existent, and the same occurs with stormwater drainage, sanitation, waste collection, and public illumination services. Despite the improvements made in the last few years, some households still do not have safe sanitation, and in some neighborhoods, open defecation still prevails. In this study, the authors try to understand and explore the interdependences among the infrastructures of the different sectors and how they may jointly contribute to adequate services and a better life for the urban poor. And how to identify the combination of infrastructures to be implemented in the short term in the face of limited budgets for investments. For that purpose, a simplified conceptual approach is proposed and applied to an informal neighborhood in Maputo. Full article

High-quality rainfall data are essential in many water management problems, including stormwater management, water resources management, and more. Due to the high spatial–temporal variations, rainfall measurement could be challenging and costly, especially in urban areas. This could be even more challenging in tropical regions with their typical short-duration and high-intensity rainfall events, as some of the undeveloped or developing countries in those regions lack a dense rain gauge network and have limited resources to use radar and satellite readings. Thus, exploring alternative rainfall estimation methods could be helpful to back up some shortcomings. Recently, a few studies have examined the utilisation of citizen science methods to collect rainfall data as a complement to the existing rain gauge networks. However, these attempts are in the early stages, and limited works have been published on improving the quality of such data. Therefore, this study focuses on image-based rainfall estimation with potential usage in citizen science. For this, a novel convolutional neural network (CNN) model is developed to predict rainfall intensity by processing the images captured by citizens (e.g., by smartphones or security cameras) in an urban area. The developed model is merely a complementary sensing tool (e.g., better spatial coverage) to the existing rain gauge network in an urban area and is not meant to replace it. This study also presents one of the most extensive datasets of rain image data ever published in the literature. The estimated rainfall data by the proposed CNN model of this study using images captured by surveillance cameras and smartphone cameras are compared with observed rainfall by a weather station and exhibit strong R² values of 0.955 and 0.840, respectively. Full article

Optimizing the management of hydraulic infrastructures that support water supply, wastewater, and stormwater drainage can increase the efficiency of these systems. A framework for operational management of urban water systems allows for robust management, which contributes to the system’s overall resilience. A methodology has been structured to support the decision-making process of managing entities. The methodology for the operational management of hydraulic infrastructures incorporates concepts of asset management, risk management, and technical management. It is organized into three operational areas (assessment, operation, and intervention) and aims to increase the efficiency of managing entities. Two cases were used to implement the aforementioned methodology—the Arouca Water Supply System (SAA-Arouca) and the Trofa Wastewater Drainage System (SAR-Trofa), both under the responsibility of Águas do Norte, S.A. In SAA-Arouca. There was a particularly significant reduction in the system input volume (purchased the first level) and the number of pipe busts observed in the subsequent period after the implementation of the methodology. Regarding the SAR-Trofa, the application of the methodology focused particularly on improper inflows (rainwater and others). The proposals for this system mainly aim at reducing the volumes collected by the drainage networks (in low-level infrastructures) and delivering them to different high-level infrastructures. Full article

Urban stormwater drainage systems, which include many personholes to collect and discharge precipitation within a city, are extensively constructed to prevent streets and buildings from flooding. This research intends to build a machine learning model to predict whether a personhole will overflow soon, which is crucial to alleviate the damage caused by floods. To address the challenges posed by many diverse personholes, we proposed segmenting the personholes into several groups and have designed two methods employing different personhole features. The first, the geography-based method, uses the geographical locations of the personholes for the grouping. The second, the hydrology-based method, uses the characteristics that are directly related to the overflowing situation, such as the depth of the personhole, and the average and the maximum water level of the personholes. We also investigated several machine learning techniques, such as the multilayer perceptron (MLP) model and a fine-tuning architecture. The study area was located in the new Taipei city and the experimental results have shown the impressive predictive ability of the proposed approaches. Particularly, by applying the hydrology-based grouping method, and using a hybrid model combining the machine learning model prediction results with heuristic rules, we can obtain the best prediction result, and the accuracy is over 99%. We have also noticed the influence of the activation function used in the neural network and the number of frozen layers in the fine-tuning architecture. Particularly, using the tanh function with one frozen layer is good in some cases. However, since it is not general enough, we suggest the readers perform empirical studies before choosing the best setting in their own environment. Full article

Semi-arid and arid regions are characterized by their water scarcity, which leads territories to seek ways of increasing the water resources available to meet their demands (urban, agricultural, industrial, leisure and tourism, etc.). For this reason, this article proposes the term “wastewater use basin”; the concept of the “wastewater use basin” is presented as a working unit of a smaller scale than traditional river basins, which allows for a better management of the water collected in the sewerage network and rainwater of urban agglomerations. It is a geographically-focused proposal for the integrated management of wastewater and stormwater that ends up in a wastewater treatment plant for treatment and reuse. The study area is located in the southeast of the Iberian Peninsula, Spain; specifically, the Campo of Cartagena-Mar Menor district (Murcia) and Vega Baja district (Alicante). The results show the trend behaviour of rainfall in the Segura river basin in recent episodes of torrential rainfall. There is a clear tendency for these episodes to occur in the coastal and pre-coastal areas, so that the water does not reach the headwaters where the reservoirs are located. For this reason, the proposed concept includes the area of the basin that would be formed by the wastewater and rainwater collectors which, in short, are intended to be treated in a treatment plant for subsequent reuse. The calculations made on the basis of the capacity of the environmental tanks executed and projected amount to four cubic hectometers which could be added to the hydrological planning of the Segura basin. In conclusion, the collection of rainwater allows the incorporation of an additional volume of water that complements and increases the resources offered by the treatment plants in the hydrological planning. It also serves as a measure of adaptation to climatic extremes (droughts and floods) and to the effects of climate change, supporting a circular management of the use of resources. Full article

Flooding risk is a threat to many sea-level cities and residential areas in the world. In the city Kristianstad in southern Sweden, a large number of sensors of different types have been deployed to monitor rain and other weather conditions, water levels at sea and lakes, ground water levels, and water flows in the city’s storm-water and sewage systems. All the sensors are enabled by battery and wireless communication, and allow real-time data to be transferred and visualized on a cloud-based Internet of Things (IoT) portal. To better enable the system with capacity of foreseeing upcoming flooding threats and to allow early response from decision-makers, it is desired to build a real-time flood forecast system by utilizing the massive sensor data collected at the IoT portal and data from 3rd party weather forecast service. In this article, we have developed a smart flood forecast system using machine learning and artificial neural networks. The developed forecast system has successfully integrated data from multiple sources and can make accurate flood forecast at distributed locations for the coming days. After being successfully implemented as software product and integrated with the city’s IoT portal, our developed flood forecast system has significantly extended the basic monitoring functions of the city’s IoT infrastructure. This article presents the context of this work, the challenges that have been encountered during our development, our solutions and performance evaluation results. To the best of our knowledge, this is the first large-scale IoT-based real-time flood forecast system that has been enabled by artificial intelligence (AI) and deployed in real world. Full article

Climate change is a significant problem that many countries are currently facing, and green roofs (GRs) are one of the suitable choices to confront it and decrease its impacts. The advantages of GRs are numerous, such as stormwater management, thermal need reduction, runoff quality, and life quality improvement. However, there are some limitations, including the weight, limits in water retention, irrigation in the drought period, suitability of harvested water for building usages, installation on sloped roofs, and high cost. Therefore, developing a novel system and design for GRs with higher efficiency and fewer negative points seems necessary and is the main scope of this research. In this regard, a novel multipurpose self-irrigated green roof with an innovative drainage layer combined with specific multilayer filters has been developed. The application of the proposed system in terms of water retention capacity, water storage volume, runoff treatment performance, irrigation system, drainage layer, application of the harvested water for domestic purposes, and some other aspects has been analyzed and compared with the conventional systems with a focus on extensive green roofs. The results demonstrate that this novel green roof would have many advantages including less weight due to the replacement of the gravel drainage layer with a pipeline network for water storage, higher water retention capacity due to the specific design, higher impacts on runoff treatment due to the existence of multilayer filters that can be changed periodically, easier installation on flat and sloped roofs, the possibility of using the collected rainfall for domestic use, and fewer irrigation water demands due to the sub-surface self-irrigation system. Full article

This paper describes an innovative Decentralized Technical Sustainable Drainage System (SuDS) concept, which is based on technical devices, such as sieves, sedimentation barriers, floating barriers and a magnetic module, which addresses, mainly, the fine matter. The SuDS is designed as a retrofit system so that no costly and time-consuming conversion measures are necessary. Due to the possibility of free configurability of individual modules in the three levels, road, gully and drain, a novel solution approach is presented, which is not available on the market, for a reduction in solids in general and microplastics in particular. The retention performance of selected modules and their combinations is demonstrated by means of bench tests according to the test procedure of the German Institute for Construction Engineering (DIBt) for the evaluation of decentralized treatment systems. Four different rain intensities, from light to medium up to heavy rain, are charged to the filter modules. Collected and fractionated road-deposited sediment (RDS) was selected as the test substance (10 kg). Additional tests with tyre powder, PE pellets, cigarette butts and candy wrappers helped to make clear the filter process of the particulate matter. The retention performance was determined by the mass balance between the defined dosage and at the outlet. For this purpose, the total volume flow of the effluent was passed over a stainless-steel sieve with a diameter of 600 mm and a mesh size of 20 µm. For the test substance, RDS retention rates up to 97% were measured. Very fine matter, particularly, was technically challenging to obtain; <63 µm up to 66% could be retained by the filter modules. Modules in the road space, such as porous asphalt or additional retention spaces, in the area of the curb as well as direct infiltration in the road drainage shaft are theoretically described and discussed. The outlook also addresses the potential of an intelligent network to reduce the input of pollution from urban stormwater runoff. Full article

Modelling of stormwater networks and the related object (combined sewer overflows, diversion chambers, retention tanks) is a complex task requiring colleting of data with appropriate time and spatial resolution as well as application of adequate models. Often there is a need to find balance between the costs of conducting measurement (period, resolution) and the uncertainty of the model results. This paper presents an overview of simulation tools for sewerage networks modelling, related objects, as well as low-impact development (LID) systems in relation to the hydrodynamic and statistical models. Consecutive stages of data collection, sources of data uncertainty, limitations resulting from the adopted measurement methodology, as well as their influence on the simulation results and possible decision-making using the developed hydrodynamic or statistical model, are discussed. Attention is drawn to the optimization methods enabling reduction in the uncertainty of statistical models. The methods enabling the analysis of model uncertainty, as well as evaluation of its influence on the calculation results pertaining to stormwater hydrographs, retention tank capacity and combined sewers overflows, are also discussed. This is a very important aspect in terms of optimizing construction works in the sewerage network and designing their appropriate dimensions to achieve the assumed hydraulic effects. Full article

First flush is a phenomenon in stormwater runoff that has been considered a topic of great interest in the field of nonpoint source pollution. Despite several attempts to define the first flush quantitively, the specified characteristics of the phenomenon vary among sources. To address these uncertainties, a bibliometric and comprehensive review on published articles related to first flush was conducted. A corpus of 403 research articles was obtained from the Scopus database, which was then parsed using the CorText Manager for the bibliometric analysis. The study examined quantitative definitions of first flush from various sources; climate and topographic characteristics of monitoring and experimental sites where the studies on first flush were performed; the sample collection methods applied; the first flush values obtained on the studies and how it influenced the nonpoint source pollution in urban watersheds. A network map, two contingency matrices, and a Sankey diagram were created to visualize the relationship of significant keywords related to first flush, as well as their co-occurrences with journals, countries, and years. It was found that the strength of the first flush effect could vary depending on the geographical location of the site, climatic conditions, and the pollutants being analyzed. Therefore, initial rainfall monitoring, runoff sampling, and water quality testing were seen as critical steps in characterizing the first flush in urban catchments. Furthermore, the characterization of first flush was found to be significant to the selection of best management practices and design of low-impact development (LID) technologies for stormwater runoff management and nonpoint source pollution control. Full article

Public acceptance is the basic premise for the implementation of stormwater reuse projects anywhere in the world. Based on the theory of planned behaviour, this study constructed a hypothesized model of urban residents’ intention to use recycled stormwater for non-potable residential purposes. Having received 669 valid questionnaires from urban residents in Taiyuan City, a Structural Equation Model was used to analyze their acceptance intention to use recycled stormwater. Results of the study showed that the degree of human contact with recycled stormwater influenced respondents’ acceptance intention to use it for that purpose, which is consistent with previous studies. The impact of factors, including valuation of stormwater, emotions, perceived health risks, or trust in government, on respondents’ acceptance intention to use recycled stormwater was found to be not significant, which adds to the inconsistent literature. The unique contributions of the study to literature include that altruism and social and cultural norms were found to have significantly positive impacts on residents’ acceptance intention to use the water, while social and cultural norms demonstrated a more significant impact. This finding is perceived to relate to the collectivism of Chinese culture; however, to what extent the relation could be requires further research to verify. The study also makes contributions to methodology by using social networking (WeChat Moments) to collect data in social science studies. Full article

Urban stormwater runoff is an important source of pollution in receiving water bodies, mainly in cities in development. However, strategies to deal with the impacts caused by the runoff discharges, such as implementing a sustainable urban drainage system (SUDS) with optimized management, need information usually obtained through monitoring studies. Brasília is a city that has one of the highest urban growth rates in Brazil, with significant impacts on urban water resources, including diffuse pollution, generated by new unregulated urban developments that initially start being built with precarious sanitation infrastructure. The Vicente Pires (VP) watershed is highly urbanized and comprises two areas that have been intensively occupied more recently, at a fast pace, and do not have yet basic sanitation systems fully implemented. Stormwater quality at the outlet of the VP watershed was analyzed by monitoring the rainfall, runoff flows, and pollutant concentration. Event Mean Concentration (EMC) and first-flush (FF) phenomenon were calculated, and hydrologic characteristics were compared for different events through correlation analysis. During dry periods the flow varied between 0.5 and 1.29 m³/s, while in flood periods the maximum value was 72.17 m³/s, forming floods with great volume. Nitrate during dry periods stands out with its high concentration; the maximum was 1.49 mg/L, while the maximum concentration during the flood events was 0.43 mg/L, probably due to dilution. Ammonia results showed very low values, probably because nitrification is occurring up to the collection point. The EMC values of solids in flood events were higher and can be attributed to river bed scour along the VP watershed. The EMC SS values for the VP watershed are also similar to areas in the initial stages of building development. The EMC values in the dry season indicate strong correlations between some water quality parameters such as NH⁺³-N and SS, TS and NO₋₃-N; NO₋₃-N, and COD. These correlations indicate that these pollutants are probably being generated by the same source, probably sewage discharges. During flood events, the correlation between pollutant loads and peak flow can be associated with the scouring during surface washing off, because greater concentrations of solids and organic matter occur in events with greater flow rates. For the first 30% of the initial runoff volume, about 29% of SS, 38% of NH⁺³-N, and 35% of reactive P were carried during flood events. It was verified that large values of maximum or mean rainfall intensity are related to the occurrence of First Flush (FF) for most pollutants. Antecedent dry days (ADD) did not influence build-up processes in this watershed; however, they are related to FF occurrence. Data indicate that the sewage and stormwater collection networks were being installed caused a high impact on observed water quality, with high concentrations of solids during flood events. On the other hand, the wastewater collection after the sewer network installation led to a decrease in COD concentrations over time. For sustainable management of diffuse pollution, the adoption of distributed SUDS to enhance runoff volume reduction is a recommended solution for the case. Full article

High-resolution data collection of the urban stormwater network is crucial for future asset management and illicit discharge detection, but often too expensive as sensors and ongoing frequent maintenance works are not affordable. We developed an integrated water depth, electrical conductivity (EC), and temperature sensor that is inexpensive (USD 25), low power, and easily implemented in urban drainage networks. Our low-cost sensor reliably measures the rate-of-change of water level without any re-calibration by comparing with industry-standard instruments such as HACH and HORIBA’s probes. To overcome the observed drift of level sensors, we developed an automated re-calibration approach, which significantly improved its accuracy. For applications like monitoring stormwater drains, such an approach will make higher-resolution sensing feasible from the budget control considerations, since the regular sensor re-calibration will no longer be required. For other applications like monitoring wetlands or wastewater networks, a manual re-calibration every two weeks is required to limit the sensor’s inaccuracies to ±10 mm. Apart from only being used as a calibrator for the level sensor, the conductivity sensor in this study adequately monitored EC between 0 and 10 mS/cm with a 17% relative uncertainty, which is sufficient for stormwater monitoring, especially for real-time detection of poor stormwater quality inputs. Overall, our proposed sensor can be rapidly and densely deployed in the urban drainage network for revolutionised high-density monitoring that cannot be achieved before with high-end loggers and sensors. Full article

Properties of constructed soils determine the functioning of nature-based solutions, such as stormwater bioretention beds. Water infiltration, colloid transport and heat transport in the soil layer are affected by changes in pore system geometry of the biofilter layer particularly due to the development of macropores and by clogging of pores by particles. The rate of alterations is often faster than in natural soils due to higher loads of particles as well due to frequent variations of the water content. In the presented study we assess the temporal changes of soil structure of biofilter layer of the experimental bioretention beds by conducting field-scale experiments and noninvasive diagnostics of soil cores. The aim is to relate changes in bioretention cell performance to the structural changes of biofilter soil. Two identical experimental bioretention cells were constructed in December 2017. The first bioretention cell collects the stormwater from the roof of the nearby experimental building (roof area 38 m²). The second bioretention cell is supplied from a tank using a controlled pump system, which allows generating of artificial rainfall-runoff episodes. The bioretention were planted in July 2018 by four perennial plants (Aster novae-angliae “Purple Dome”; Hemerocallis ‘Lemon Bells’; Euphorbia amygdaloides; Molinia caerulea). Bioretention cells are instrumented with water content probes, tensiometers, water potential meters. Outflow from the bioretention cell is monitored by tipping buckets. Small undisturbed samples were collected from the biofilter layer before and after the first vegetation season and examined by X-ray micro computed tomography (CT). Image analysis involved segmentation of the macropore network and calculation of the properties of the pore system. The analysis of X-ray CT imaging demonstrates the significant decrease of macroporosity during the first vegetation season. The outcomes of the research will lead to improved design and management procedures for and bioretention beds. Full article