Urbanizing watersheds face challenges from both human and nature systems. Our research group focuses on urbanization and its impacts on human-nature systems at the watershed scale. First, we measured the built-up area expansion across global watersheds. Then, we investigated the supply and demand of ecosystem services (e.g., soil conservation, water provision and cultural services) based on the SWAT (Soil and Water Assessment Tool) model, Solves model and online big data, in Guanting Reservoir Basin, a transitional ecosystem from semi-arid areas to arid areas. Then, we examined how urbanization affect the ecosystem services received and realized by local urban and rural residents of this Basin, in the context of Ecological Civilizaton, and Poverty Alleviation Relocation (PAR) Initiative in China. Our results exhibted unique characteristics of ecosystem services and human well-beings in rapidly urbanizing watersheds and can provide policy implications for similar basins
How to cite: Huang, Q., Zhou, Y., Wu, P., Zhou, Y., and Bai, Y.: Urbanization and its impacts on ecosystem services and human well-beings in rapidly urbanizing watersheds, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-5605, https://doi.org/10.5194/egusphere-egu25-5605, 2025.
Urban streams climate change adaptation
Müller Helene, Kleiner Jürgen, Philipp Stern, Rauch Hans Peter
Urban water courses are a system under pressure. Either they have been modified in the past, banned in the underground or even inundated in the sewage system. Within the north western part of the city of Vienna (research area: city of Vienna in the north of Wien river + in the west of Donaukanal) the runoff of a riparian catchment area of 20.8 km² arrives at the waste water treatment plant. The ecological pressure, heavily modified water bodies are bothered with, is intensified by climate change. Despite these circumstances, the urban water courses should provide flood security as well as low flow security. In order to derive resilient systems restoration is essential. Within an urban context the spectrum reaches from water quality improvements, morphological restoration to reactivation of water courses in the underground or in the sewage system. The list of benefits is long, it covers the generation of urban blue green infrastructure (BGI), which can help with urban heat island (UIH) mitigation and leads to additional recreational areas, the availability of an additional water source in the urban area and many other ecosystem services. Regarding climate change and low flow situations the thermal regime of rivers is addressed. To restrict the warming of the water temperature shading via vegetation is an important factor. Within the research project ProBach a testfield of three artificial and temporal limited waterbodies (two running waters one stagnant waterbody) was installed in spring 2024 at an asphalted spot at the Klimabiennale in Vienna. In the context of installing BGI elements via urban river reactivation for UHI mitigation microclimatic, social, technical and river ecology related questions have been addressed. Regarding the latter, physio-chemical and biological water quality parameters were observed. The focus of the work presented in the poster is water temperature as a major factor for cooling the effects of water bodies. The interrelationship between water body, its riparian vegetation and the associated shading effects were observed. The water temperature was monitored in a testbed, 7.8 m long and 80 cm broad, and a discharge of 1 l/s within a circular system. Natural riparian vegetation was simulated by shading nets with UV permeability of 60%. The water temperature was recorded by nine HOBO sensors at different positions of the riverbed (on the sediment, in the sediment, in the sump), air temperature was collected by eight TOMST sensors in 1.5 m height. During a heat period in July 2024 shaded and unshaded measuring campaigns were carried out repeatedly. The artificial shading of the water bodies impacts the water temperature significantly. The findings highlight the importance of riparian vegetation while restoring and reactivating water courses within an urban context in order to generate resilient, vital and climate change resistant river systems.
How to cite: Mueller, H., Kleiner, J., Stern, P., and Rauch, H. P.: Water temperature of urban streams - climate change adaptation, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-11755, https://doi.org/10.5194/egusphere-egu25-11755, 2025.
Pharmaceutical pollution in urban water poses a significant threat to coastal ecosystems, particularly in regions with rapid urbanization. This study investigates the source, occurrence, and distribution of pharmaceutical compounds (PCs) in agriculture runoff and treated wastewater (TWW) used for irrigation within urban coastal zones in eastern Saudi Arabia. Water samples were collected from TWW irrigation (2 samples) and agriculture runoff channels (10 samples) to identify and quantify the pharmaceutical pollution. The agricultural runoff samples were collected from fields irrigated with TWW and fields irrigated by groundwater (GW) for comparative study. Water samples were analyzed for 50 PCs using Liquid Chromatography-Mass Spectrometry with Direct Injection (LCMS–DI) and followed the US EPA Method 1694. The results show that 12 PCs were detected in both water sources, including caffeine, carbamazepine, iohexol, sulfamethazine, valsartan, atenolol, diclofenac, furosemide, gabapentin, hydrochlorothiazide, naproxen, and paracetamol. Among those compounds, caffeine, iohexol, valsartan, sulfamethazine, and gabapentin were detected with frequencies of 100%, 60%, 50%, 30%, and 20%, respectively. The remaining compounds were detected with a frequency of <20%. The results reveal that the highest concentration of PCs was observed in the main agricultural drainage channel in downstream regions. This probably reflects the cumulative input of PCs from upstream tributaries. Additionally, agricultural runoff from fields irrigated with GW contains only caffeine and sulfamethazine pollutants. However, in regions irrigated with TWW, twelve PCs were detected. The potential source for PCs in agriculture runoff from fields irrigated with GW is the manure fertilizer, which is commonly used in the study area. However, in regions irrigated with TWW, the PCs were most probably sourced from TWW irrigation. The study findings suggest enhancing wastewater treatment with advanced techniques to remove emerging pollutants and to protect the aquatic ecosystem. In addition, the study contributed to a better understanding of the urban watershed dynamics and provides insights that can inform sustainable urban water management practices, especially in urban agricultural regions where TWW is utilized for irrigation.
How to cite: Benaafi, M.: Pharmaceutical Pollution in Urban Coastal Watersheds of Eastern Saudi Arabia: Implications for Sustainable Water Resource Management , EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-2030, https://doi.org/10.5194/egusphere-egu25-2030, 2025.
Semi-formal neighbourhoods face complex social, economic and environmental challenges, of which many are related to poorly coordinated land and water management. Reduced vegetation and surface sealing combined with the lack of a sewage system lead to high surface water runoff, which results in increasing pluvial flooding, erosion, and landslides. Mitigation measures are often implemented by individual residents in the form of low-cost Nature-based Solutions (NbS), but implemented measures frequently lead to negative impacts further downhill. The effects of climate change are increasing hazard intensities and therefore, hydro-meteorological risks.
The aim of this study is to support the design of NbS by coupling pluvial flood modelling with participatory methods. The use of numerical models to describe surface water runoff and to analyse the effects of NbS has been applied often. Nevertheless, the calibration and validation of urban surface runoff models and the choice of appropriate solutions remains challenging.
This study uses the coupled hydrological-hydrodynamic model HEC-RAS to simulate pluvial flooding in selected precipitation events by utilizing Rain-on-Grid modelling, and to quantify the potential effects of selected NbS. The validation and calibration of the model is supported by flow paths, identified problem sites and flooding depths during historical precipitation events, which were determined during a participatory mapping workshop.
To find appropriate solutions interviews and transect walks were conducted along with the participatory mapping workshop as a basis to discuss, design, and locate low-cost, self-implementable NbS. These were implemented in the model to evaluate the effectiveness of potential solutions.
The results are expected to demonstrate the ability of this conceptual approach to utilize local knowledge to design implementable and effective NbS to reduce hydro-meteorological risks. Furthermore, this study shows how local knowledge and participatory mapping can be used to validate urban surface runoff models. The quantification of proposed NbS effects can support the implementation of suggested measures.
How to cite: Pyerin, C., Hörbinger, S., Grande-Ayala, C. E., Rauch, H. P., and Gutiérrez Poizat, S.: Designing Nature-based Solutions for hydro-meteorological risk reduction by coupling surface water modelling with participatory sciences in a peri-urban neighbourhood in El Salvador, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-5228, https://doi.org/10.5194/egusphere-egu25-5228, 2025.
Key Points:
- Affordable sensors allow continuous monitoring of soil moisture and hydrological performance in rain gardens.
- Using sensors for predictive maintenance lowers expenses and increases the longevity of rain gardens.
Rain gardens (RG) are essential for sustainable stormwater management, but their effectiveness relies on consistent maintenance, which is both critical and costly. This study explores the use of low-cost electronic sensors to monitor biofilter conditions and enable predictive maintenance, reducing manual inspections and improving operational efficiency.The experiment involved 15 laboratory-scale columns, replicating the typical structure of rain gardens, with stratified layers: a ponding zone, fine sand filter, coarse sand with mulch transition layer and a gravel drainage layer. The columns were divided into three groups to simulate different conditions: a control group (C) representing optimal performance, a group with preferential flow paths (P) simulating surface erosion, and one with surface clogging (S) due to sediment accumulation. Each column had five sensors to monitor soil moisture and temperature: two Chameleon Soil Water Sensors, two temperature probes, and one Truebner SMT 100 sensors. Data were collected in real time and transmitted to a cloud-based system. To evaluate the columns, simulated rainfall events, reflecting varying intensities and antecedent dry periods based on Melbourne’s historical weather patterns, were applied. The SMT sensor effectively tracked volumetric water content (VWC), identifying peaks from simulated rainfall events and showing variability across different antecedent dry days (ADD). However, Chameleon sensors exhibited performance degradation over time due to soil drying, root growth, and temperature variations. Inflow, outflow, and infiltration rates were measured to assess hydrological behavior, but these data alone were insufficient to differentiate healthy from malfunctioning systems. Consequently, indices were developed to differentiate the hydraulic performance of each group. Parameters such as peak time, peak span, and delay time were identified as notable in diagnosing operational states. For instance, the clogging group exhibited delayed response times and retained less water. In contrast, preferential flow columns displayed immediate responses to rainfall. Post-experimentation, the columns were disassembled to analyze physical changes in soil stratigraphy and assess root development, providing additional insights into the impact of hydraulic malfunctions on overall system health. In conclusion, this research underscores the potential of integrating low-cost sensor technologies into the management of rain gardens. Real-time monitoring not only enhances the reliability and longevity of these systems but also reduces operational costs, contributing to the broader goal of fostering resilient and sustainable urban environments. Future research should refine sensor applications and expand testing under diverse environmental conditions.
How to cite: Marella, C., Dada, A., Winfrey, B., and Grossi, G.: Low-cost electronic sensors for continuous performance monitoring of raingardens, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-13735, https://doi.org/10.5194/egusphere-egu25-13735, 2025.
Stormwater management has emerged as one of the main issues, especially in urban areas. When cities expand, urbanization increases with the result of more impermeable areas. In this way, there is a modification of some pre-development hydrological cycle's functions like infiltration and evapotranspiration with direct consequences in increasing pluvial urban flood phenomena.
In addition, the increase in extreme events due to climate change makes the traditional urban drainage systems inadequate to manage stormwater, and this increases the cities' vulnerability to pluvial urban flooding.
Recently, to mitigate the cited issues, the scientific community has concentrated on a series of "green" facilities known as Nature-based Solutions (NBS). Among NBS the most popular are green systems such as Green Roofs and Walls.
The aim of this work is to propose a comprehensive approach to assess the hydrological/hydraulic benefit of a GW cascade system using experimental investigation on the soil substrate coupled with a physically based approach applying the HYDRUS-1D model.
The GW investigated in this work consists of a cascade of five boxes. Each box contains a seepage face layer (to permit the water flux from one box to the other); a drainage layer of 5 cm composed of natural gravel material; a highly permeable geotextile to avoid fine particle migration into the underneath layer; a substrate of 10 cm; a surface layer with vegetation. The mixture of the soil substrate is made up of 40% mediterranean soil, 40% compost, and 20% glass sand while the drainage layer consists of fine gravel. To assess the hydraulic properties of the soil substrate the evaporation method simplified by Schindler has been performed using the HYPROP device applying the unimodal van Genuchten-Mualem model.
To carry out the modeling analysis with the HYDRUS-1D model, a one-year data set (2022) gathered from a meteorological station located in Cosenza was taken into consideration.
The potential effect of the GW cascade on a building has shown promising results in reducing runoff volume. It should be noted, however, that this study considers only the rainfall falling on the first box of the GW cascade as the first precipitation input. Further investigation on inflow coming from an adjacent roof surface should improve the knowledge about the GW cascade runoff reduction.
How to cite: Turco, M., Brusco, A. C., Brunetti, G., Pirouz, B., and Piro, P.: Experimental investigation and numerical analysis of a green wall system, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-18107, https://doi.org/10.5194/egusphere-egu25-18107, 2025.
Climate change, inter-annual precipitation variability, recurrent droughts, and flash flooding, combined with increasing water demands, are influencing the evolution of socioeconomic and cultural structures, water laws, and equitable access to drinking water worldwide. To address the need for strategies to ensure drinking water availability in urban areas, the Isotope Hydrology Section of the International Atomic Energy Agency (IAEA) conducted a comprehensive global assessment titled ‘Use of Isotope Techniques for the Evaluation of Water Sources for Domestic Supply in Urban Areas (2018–2023)’. This initiative aimed to evaluate water sources and the distribution of drinking water supply in urban centres using isotopic tools.
The project successfully covered (a) current research trends in studying urban drinking water systems over the past two decades and (b) the development, testing, and integration of new methodologies for better assessment, mapping, and management of water resources used for drinking water supply in urban settings. Examples of water isotope applications from countries such as Canada, USA, Costa Rica, Ecuador, Morocco, Botswana, Romania, Slovenia, India, and Nepal provide context to the insights and recommendations presented, demonstrating the versatility of water isotopes in capturing seasonal and temporal variations across different environmental and climate scenarios.
The study found that urban areas rely on a diverse range of water sources, including mountain recharge, extensive local groundwater extraction, and water transfer from nearby or distant river basins. This diversity is reflected in the spatial isotope snapshot variability. High-resolution monitoring (hourly and sub-hourly) revealed significant diurnal variations in the wet tropics (Costa Rica) (up to 1.5‰ in δ18O) and more uniform diurnal variations in urban centres supplied by groundwater sources (0.08‰ in δ18O) (Ljubljana, Slovenia). Additionally, while d-excess values were generally close to the global mean (+10‰) across all urban centres (10‰–15‰), reservoir-based drinking water systems showed lower values (up to ~ −20‰) (Arlington, TX, USA and Gaborone, Botswana) due to strong evapoconcentration processes. δ18O time series and depth-integrated sampling highlighted the influence of the catchment damping ratio on the final intake water composition.
By introducing new, traceable spatial and temporal tools that span from the water source to the end-user and are linked to the engineered and socioeconomic structure of the water distribution system, governmental, regional, or community-based water operators and practitioners can enhance drinking water treatment strategies (including more accurate surface water blending estimations) and improve urban water management and conservation plans in the context of global warming.
How to cite: Ortega, L. and the CRP team members: Tracing urban Drinking water sources using isotope techniques: insights and applications, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-5807, https://doi.org/10.5194/egusphere-egu25-5807, 2025.
Accelerating urbanization development has a great impact on water environment with altered hydrological cycle process, deteriorating water quality and redistributed water quantity. In addition, urban river-lake networks have emerged as a blend of natural and engineered water environment under artificial transformation. However, water exchange relationships and pollution patterns in such water networks are complicated and poorly understood due to various disturbances from both nature and social activities. This study investigated water chemistry and stable isotopic tracers in the Dongsha River-Lake Networks (DRLN) in Wuhan, China, to enhance the understanding of hydrological connectivity and controlling factors of urban water pollution. The results indicated that domestic wastewater was the main pollution source in DRLN, significantly contributing to high nutrient levels, particularly in urban streams. Point sources such as domestic wastewater and industrial effluents exerted a more considerable influence on water quality in dry season with lower discharge. In contrast, during the wet season, non-point pollution increased due to rainfall-runoff carrying various pollutants on the landscape. Taking urban streams as the research object and considering precipitation, tap water, Yangtze River water and East Lake as water sources, the MIXSIAR model was adopted to analyze the differences in water sources of urban streams in different months and locations. Moreover, the variation of stable isotopes suggested that pollution patterns in river-lake networks were also shaped by interactions between waterbodies, and water exchanges were more frequent in summer. The water diversion from the Yangtze River (YR) effectively enhanced water quality in urban streams, but the improvement on East Lake was insufficient to affect the water quality in central areas. Therefore, more rational water management strategies in DRLN were urgently needed considering the impact of hydrological connectivity on water pollution distribution. Integration analysis of water chemistry and stable isotopes contributes to understanding the mechanisms of pollutant generation and transportation in complex urban water networks, and provides insights into anthropogenic impacts on urban water networks.
How to cite: Zhang, H., Zhang, X., Xu, J., Tao, S., Li, C., and Yang, Y.: Coupling stable isotopes and river networks connectivity to identify the linking between hydrology and water quality in a urban river-lake water system, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-14450, https://doi.org/10.5194/egusphere-egu25-14450, 2025.
Combined sewer spills are a significant environmental concern in the United Kingdom and other countries where rain and wastewater are not separated during storms. In recent years, the pollutant impacts of sewer spills on water bodies have received increasing scrutiny. Public awareness and monitoring efforts have consequently grown due to extensive media coverage, highlighting the scale of the issue. The UK Storm Overflows Discharge Reduction Plan sets strict targets for water companies to reduce the number of spills per year. Traditionally, the water industry has relied on grey infrastructure, such as storm tanks, to mitigate storm overflow impacts. However, there is growing recognition of the benefits of green infrastructure, particularly nature-based solutions. While urban-focused Sustainable Drainage Systems (SuDS) and end-of-pipe treatments are common, permeable runoff contributions to combined sewer networks are often overlooked, representing a gap in current approaches. Permeable areas, like parkland or agricultural fields, are often large and, although permeable, overland flow can still occur and reach the sewer networks. Therefore, it is crucial to identify permeable areas that have potential to contribute to surface runoff entering the combined sewer and ideally, put in place solutions to mitigate this risk.
To address this, a Geographic Information System (GIS) tool set within ArcGIS Pro environment, and an equivalent R-based open-source tool has been developed to support water companies in identifying permeable areas with potential for nature-based solutions to reduce overland flow into combined sewer systems. The tool uses spatial layers as inputs and incorporates multiple options to allow for customisation, whilst also accounting for barriers (e.g. hedges and walls) that may interrupt overland flow. Overall, these features help address the topographic complexities of the urban fringe. The final output from the toolbox provides a layer that consists of any potential permeable areas that could drain to the inlets for the combined sewer network and consequently contribute to combined sewer overflows.
The output from the tool identifies permeable areas draining to the combined sewer, as well as areas for potential sites for nature-based solutions. This geospatial data can be further evaluated through desktop and field surveys to confirm a locations suitability for nature-based solutions. Integration with UK Industry standard hydraulic models such as InfoWorks, enables a comprehensive assessment of the potential benefits of solutions. The tool has currently been applied in the 1,800 km2 Tamar catchment, UK, demonstrating a pathway for the water industry to spatially prioritise green infrastructure, reduce storm overflows, and transition away from conventional grey solutions, aligning with a green first approach. And in turn, provide additional benefits such as ecosystem services, as well as being less costly than grey infrastructure solutions.
How to cite: Kitch, J., Robinson, M., Jackson, B., Waly, M., Peng, Z., Panici, D., and Brazier, R.: A GIS-based tool for identifying areas for nature-based solutions to aid water companies in a green first approach to reduce combined sewer overflows, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-6663, https://doi.org/10.5194/egusphere-egu25-6663, 2025.
This paper presents the complex interactions between river systems and Vienna’s urban development through historical, infrastructural, and contemporary perspectives, with a particular focus on the role of water infrastructure in shaping spatial planning and urban dynamics. By analyzing historical maps, georeferenced data, and archaeological findings, the study reconstructs the changes in the Danube River and its tributaries during key phases of the city's development, including major interventions in river regulation and the urbanization of riverbanks.
A particular emphasis is placed on the 19th-century channelization of the Danube, which was implemented to reduce flood risks, improve navigation, and enable industrial growth. These processes significantly impacted natural hydrological characteristics, ecosystems, and the urban landscape. The regulation involved straightening the river’s course, and constructing protective embankments. These were important elements of Vienna’s transformation into an industrial and economic hub of Central Europe. Additionally, the channelization of streams in the urban area contributed to public health improvements but also led to further fragmentation of natural watercourses.
In the contemporary context, the paper addresses renaturation projects and the reintegration of water systems into urban spaces to achieve sustainable development and improve human quality of life. These initiatives aim to balance ecological, social, and economic aspects by creating multifunctional spaces that integrate natural processes with urban needs.
The findings highlight the importance of a historical and interdisciplinary approach to understanding the relationship between river systems and urban development. Integrating these insights into contemporary planning provides a framework for effective water resource management, preservation of natural heritage, and promotion of sustainable urban development.
How to cite: Vranešević, M., Knežević, M., and Haidvogl, G.: From Flood Control to Ecological Balance through The Evolution of Vienna’s Relationship with the Danube and Its Tributaries, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-1848, https://doi.org/10.5194/egusphere-egu25-1848, 2025.
Climate change and anthropogenic activities are profoundly disrupting regional hydrological cycles, altering precipitation regimes, intensifying temperature variations, and accelerating sea-level rise. These factors collectively exacerbate flood events and elevate associated risks, particularly for vulnerable urban communities. Although the hydrological impacts of floods are extensively documented, their role in propagating waterborne diseases and escalating public health risks remains inadequately explored. In Delhi, the national capital of India, urban flooding has inflicted substantial damage and numerous health challenges. Its location along the Yamuna River, dense population, unregulated urbanization, deficient drainage infrastructure, and increasingly extreme rainfall patterns driven by climate change are the key contributors to this dismal situation. This study, for the first time, develops an integrated framework to quantify human health risks associated with contaminated urban floodwaters in a flood-prone region under current and projected future scenarios by coupling climate and socio-economic dynamics. High-resolution hydro-meteorological data, including rainfall, streamflow, sewer flow, and water quality parameters, were analyzed alongside statistically downscaled NEX-GDDP-CMIP6 data under SSP2-4.5 and SSP5-8.5 scenarios to evaluate future flood extremes. A multi-model framework was employed, combining a semi-distributed hydrological model, a three-way coupled hydrodynamic model, and a water quality model. The SWAT hydrological model simulated rainfall-runoff processes to estimate runoff, which served as input for the 3-way coupled MIKE+ hydrodynamic model. Outputs from the hydrodynamic simulations were integrated into the MIKE EcoLAB module to simulate the transport and fate of faecal indicator bacteria (FIB) under varying flood conditions. Human health risks associated with FIB exposure were quantified using the β-Poisson dose-response model. The proposed framework, which synergizes climate and socio-economic factors within a multi-model environment, is adaptable and can be applied to other flood-prone regions globally. By providing actionable insights, this study seeks to inform the development of resilience strategies to protect at-risk populations, addressing the critical need for sustainable flood risk management in developing and underdeveloped nations increasingly affected by climate change and socio-economic pressures.
How to cite: Deopa, R., Mishra, D., Kumar Shahi, N., Tripathi, V., and Prakash Mohanty, M.: Quantifying human health risks from contaminated urban floodwaters using a multi-model framework under climate and socio-economic scenarios, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-15444, https://doi.org/10.5194/egusphere-egu25-15444, 2025.
Stormwater drainage generally flows untreated into receiving waters, such as rivers, groundwater, and the sea. Stormwater networks can serve as pathways for contamination to enter receiving waters. Misconnections, illicit connections and discharges, overflows, and leaks from damaged sewers are the primary causes of such contamination. These issues not only degrade water quality, posing public health and environmental risks, but also create a range of expensive operational challenges for water and wastewater companies.
Detecting wastewater contamination and tracing its entry points into stormwater systems remains a significant challenge predominantly due to various potential sources of incoming wastewater, dilution and dispersion of contaminants by tributary stormwater flows, and significant differences in consistency, regularity, and flow rate of inflows.
We conducted an investigation on an urban stormwater pipeline in the UK suspected of receiving wastewater from multiple misconnections. The aim of the investigation was to determine whether the stormwater system was being impacted so that the statutory undertaker could address the contamination issues and improve the quality of the receiving water environment. The source of the misconnections was uncertain prior to the investigation but it was suspected that they may have been inputs from domestic households, small to medium-sized businesses, or both. The study employed a comprehensive approach combining water sampling for microbiological indicators (total coliforms and E. coli) and an array of chemical analyses, including trace elements, organics, nutrients, petroleum hydrocarbons, and volatile and semi-volatile organic compounds. The collection of grab samples was complemented by the use of a Proteus multi-sensor sonde (Proteus Instruments, UK), which measured parameters such as tryptophan-like fluorescence (TLF), chromophoric / fluorescent dissolved organic matter (CDOM/fDOM), electrical conductivity, pH, ORP, turbidity, temperature, ammonium (NH4), and dissolved oxygen (DO). Moreover, data collected with the multi-sensor sonde was used to model microbial parameter concentrations over a period of approximately three weeks. Two modelling approaches were tested: one following the methodology recommended by Proteus Instruments, and another employing the machine learning Random Forest method. The latter approach offers potential advantages in addressing challenges commonly associated with fluorescence-based sensors. The findings demonstrate the potential for enhanced detection of wastewater misconnections, providing a more efficient and accurate method for identifying sources of contamination within stormwater systems.
How to cite: Vucinic, L., Lydon, C., Mezali, H., McConvey, P., McIntyre, T., Ajia, F., Freitas da Silva Vucinic, M. I., O'Connell, D., Coxon, C., and Gill, L.: Combining multi-sensor data and machine learning for improved wastewater contamination detection in stormwater systems, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-13955, https://doi.org/10.5194/egusphere-egu25-13955, 2025.
Catchment morphology and river network structure greatly condition hydrological response to flooding. While scaling laws have been established for natural catchments and Optimal Channel Networks (OCNs) (Rinaldo and Rodriguez-Iturbe, 1997; Moussa, 2003 & 2009), fewer works have looked into artificial urban water networks, namely stormwater and sewer networks. Optimal Channel Networks (OCNs) are defined based on a generative geomorphological mechanism minimizing the total energy dissipation. However, man-made networks are conceived based on engineering efficiency taking governed by local optimizations, both in time and space, for minimal costs. Hence questions arise regarding the applicability of OCN scaling laws to sewer networks and their potential impact on the shape of the Geomorphological Instantaneous Unit Hydrograph (GIUH).
This work addresses these issues through a case study on twelve nested subcatchments of the Greater Paris combined sewer system (France). A two-step methodology is used. First, the morphometric properties are analysed using the reference Horton-Strahler, Rodríguez-Iturbe and Moussa-Bocquillon scaling laws. They are used in the second step to calculate four GIUHs: the reference Width Function (GWF), the Nash unit hydrograph (GN) using Horton-Strahler ratios, the Nash Unit Hydrograph equivalent (GNe) using Moussa- Bocquillon descriptors, and the Hayami function (GH) solution of the diffusive wave equation (Achour et al., 2023).
In an effort to generalize the methodology to smaller catchments and Separate Sewer System (SSS), a case study is presented on a sub-network of the city of Montpellier (Southern France). The preliminary results show the need to adapt catchment delimitation methods. Indeed, while hillslopes are the main contributing areas to water flow in natural rivers, the flow in sewer networks is generated by individual production units such as residential, industrial and commercial units. Hence the methods traditionally used to automatically extract hydrographic networks from digital terrain models (DTMs) and delimit catchment boundaries lead to an overestimation of contributing areas. Thus, the geomorphological properties of Moussa and the power law of Rodriguez-Iturbe were not verified.
How to cite: Chahinian, N., Achour, M., Mbayang Thiam, M., Chancibault, K., Andrieu, H., and Moussa, R.: Morphometric properties and hydrological responses of sewer networks: cases studies from France., EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-6745, https://doi.org/10.5194/egusphere-egu25-6745, 2025.
The catchment areas of the Lippeverband (and Emschergenossenschaft, EGLV) in Western Germany are characterized by former coal mining activities. In consequence extensive subsidence areas without drainage have developed. These often densely populated polder areas are dependent on artificial drainage systems such as pumping stations that are crucial for flood protection. If the capacity of the pumping station is exceeded or if the pumping station (partially) fails, the water floods the drainage-free subsidence area. The consequences are life-threatening situations for the population and monetary losses of several billion euros.
The BMBF (Federal Ministry of Education and Research) joint project PuwaSTAR aims to develop a real-time forecasting system for potential flooded areas and their water depth in subsidence areas around pumping stations. Based on artificial intelligence (AI), time-consuming hydraulic simulations are replaced in the event of an incident. In addition to the hydrological forecast the operating status of the pumping station is considered during simulations, and failure scenarios are respected. The AI-model is based on a convolutional neural network (CNN) and designed to generate maximum water depth and inundation areas for the upcoming 24 h using discharge and rainfall data as input data. As part of this project, EGLV's existing flood forecasting system is extended to the forecast of flooded areas including details of the pumping stations status.
Although existing hazard and risk studies provide an overview of the potentially affected flood areas, a dynamic system allows for strategic disaster management. Thus, resulting options of targeted population warnings and initiation of prioritized measures reduce potential damage and protect the population. This enhances flood-resilience. The current operating status of the pumping station as well as a potential failure significantly contributes to the risk of flooding and must be considered likewise.
The real-time prediction based on AI will be demonstrated using the example of the Dorsten-Hammbach pumping station in the Hammbach catchment of the Lippeverband. According to an existing risk study, in the event of a pumping station failure and resulting flooding, the expected damage would amount to around €75 million, about 1,800 people and critical infrastructure would be affected. In collaboration with local authorities and first responders, the opportunities for improved forecasts for practical disaster management are derived. A participatory approach to elaborate and define requirements jointly with the stakeholders is a key aspect of the project. This enables targeted measures in the event of an incident and improves preparedness of the densely populated area around the pumping station.
The results of the project are intended to serve as a basis to transfer the methodology to further pumping stations and other controlling drainage elements, both in the EGLV catchment as well as those of other operators.
How to cite: Eckers, H., Buchholz, O., Falter, D., Johann, G., Leandro, J., Nafo, I., Nijzink, J., Pfister, A., Ramsauer, S., and Schmid, F.: Flood forecasting and pumping station warning in urban areas to improve flood-resilience: The project PuwaSTAR, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-16233, https://doi.org/10.5194/egusphere-egu25-16233, 2025.
Flood resilience assessment has become increasingly important for effective stormwater management in the context of frequent and severe urban flooding disasters. The severity of flooding in riverine cities is influenced by various factors, such as rainfall and river levels, but resilience assessments usually only consider the impact of heavy rainfall. Given the lack of urban flood resilience assessment under compounding risks, this study proposes a performance-based resilience assessment method considering the joint impacts of precipitation and river level, using a lake basin in Wuhan City as an example. Based on urban water system theory, the resilience assessment framework considered three subsystems’ resilience, i.e. the performance of the pipe network, the residual storage capacity of lakes, and the available discharge capacity of pumps. The Copula function was used to quantitatively assess the joint distribution characteristics of daily rainfall and the Yangtze River water level in Wuhan. A SWMM model was developed for hydrological simulation and resilience assessment under composite scenarios. Considering only the impact of precipitation would underestimate flooding risk relative to the joint effects of precipitation and river water level. The resilience index of the pipe network was the highest among the three subsystems, whereas that of the lake system was the most variable. For the same return period rainfall, the decrease in resilience of the pump system was the most pronounced as the river water level rose from 22.06 m to 29.25 m. In addition, the higher the rainfall magnitude, the more important it is to consider the jacking effects of the Yangtze River level on urban flooding. The proposed method evaluated the resilience-enhancing capacity of grey-green-blue infrastructures, and their combined effects were found to be non-linear. This research proposed a resilience assessment method founded upon joint risk and provided valuable feedback for developing effective flood resilient management strategies in riverine cities.
How to cite: Gong, L., Zhang, X., Guo, Z., Winston, R., Tao, S., and Smith, J.: Urban flood resilience assessment under compounding risk: joint impacts of precipitation and river level, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-15166, https://doi.org/10.5194/egusphere-egu25-15166, 2025.
Urban floods have become a pressing concern as cities worldwide face unprecedented flooding events that severely impact the lives and livelihoods of millions in densely populated areas. This issue is particularly alarming in developing countries, where rapid, unplanned urbanization often outpaces the development of adequate infrastructure. Climate change exacerbates this challenge by intensifying the frequency and severity of extreme rainfall events, further straining fragile urban systems. Given the growing vulnerability of urban areas to flooding, it is crucial to develop targeted mitigation strategies grounded in comprehensive urban flood risk assessment. The present study aims to quantify flood risk and leverage Global Climate Models (GCMs) for predicting future flood scenarios. A sensitivity analysis is performed on spatial layers, including land use/land cover (LULC), elevation, slope, rainfall, stream density, distance to roads, distance to rivers, population, population density, literacy rates, and building footprint, to evaluate their influence on flood risk. Machine learning (ML) algorithms—support vector machine (SVM), random forest (RF), gradient boosting (GB), and artificial neural networks (ANN)—are employed to generate urban flood risk zones (UFRZ). The UFRZs derived from these algorithms are validated using the area under the curve – receiver operating characteristic (AUC-ROC) metric to ensure accuracy. The optimal UFRZ model is then used to predict future urban flood risks based on GCM outputs. Fifteen downscaled, bias-corrected GCMs are evaluated against observed rainfall data for the historical period (1985–2020) to identify the best-performing model for the region. Future flood risk predictions are made for three time periods: 2025–2050, 2051–2075, and 2076–2100. Identifying high-risk flood zones will aid in formulating effective mitigation strategies, providing a roadmap for flood resilience that can be adapted for similar regions globally.
How to cite: Rashiq, A., Prakash, O., Roy, S. K., and Kumar, A.: Comprehensive urban flood risk assessment using machine learning algorithms and GCM projections, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-21883, https://doi.org/10.5194/egusphere-egu25-21883, 2025.
Urban floods are one of the major challenges in the sustainable management of urban areas, which have intensified due to climate change and the rapid expansion of urbanization. These floods, especially in coastal and low-lying areas, create significant risks for infrastructure and human settlements and have extensive economic and social consequences. With the increase in heavy and short-term rains, the necessity of surface runoff management and accurate prediction of flood patterns in urban areas is felt more than ever.
Hydraulic modeling is critical as one of the basic tools in predicting flood behavior and reducing its effects in urban environments. Using the HEC-RAS 2D model and supporting QGIS software, this research examines the hydraulic modeling of urban runoff caused by floods in the coastal city of Catania. This method allows accurate flood flow simulation and dynamic water movement analysis in complex urban environments.
The main goal of this study is to evaluate the effectiveness and capability of hydraulic models as a tool for analyzing the vulnerability caused by heavy rainfall runoff in urban environments. Also, flood maps are reviewed to identify high-risk points and prioritize vulnerable areas.
Finally, this research highlights the importance of accurate modeling and integration of hydrological and hydraulic approaches, along with attention to detail, to provide sustainable and practical solutions to reduce the risks of urban floods.
How to cite: Yousefi, F., Ester Musumeci, R., and Cavallaro, L.: Assessing the Impact of Urban Flooding on Cities through Hydraulic Modelling, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-19480, https://doi.org/10.5194/egusphere-egu25-19480, 2025.
Urban pluvial flooding is increasingly recognized as a critical issue due to its rising frequency and severity in many cities worldwide. This study aims to develop dynamic maps at suburban scales for flood risk assessment in the city of Rome, Italy, focusing on the impacts on critical transport linear infrastructures, such as roads. Dynamic mapping incorporates temporal changes in environmental conditions (such as rainfall intensity, water levels, and storm surges), human activities (like population movements and daily routines), infrastructure status (e.g., drainage capacity and road networks), and other socio-economic variables (such as adaptive capacity and community resilience) to capture how flood risk evolves over time. For this case study, dynamic pluvial flood hazard maps are developed by using the rain-on-grid model from HEC-RAS, i.e. a 2D hydrodynamic model designed to simulate surface water flow over a grid-based terrain. In this setup, rainfall is applied directly onto each cell of a high-resolution digital DSM, creating a rain-on-grid scenario where precipitation generates surface runoff that flows across the landscape. This approach captures detailed interactions between rainfall intensity, topography, and surface flow dynamics, making it suitable for urban areas. The analyzed data includes series of synthetic precipitation hyetographs that are estimated using Intensity-Duration-Frequency (IDF) curves derived from rain gage data located in the study area. These synthetic hyetographs represent return periods of 2, 5, 25, 50, and 100 years, with durations of 5, 10, 20, 30, 40, 50, and 60 minutes, which represent different precipitation intensities to produce a sensitivity analysis under different return periods and rainfall durations. Also, observed storm events are assessed to calibrate and validate the model. It is worth to mention that this model does not consider the drainage system, thus results are in favour of safety.
How to cite: Wilches Kochinski, E. J., Lanciotti, S., Ridolfi, E., Moccia, B., Russo, F., and Napolitano, F.: Pluvial flooding Dynamic Mapping under Historical Climatic Conditions in Rome, Italy , EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-12433, https://doi.org/10.5194/egusphere-egu25-12433, 2025.
Urban trees play a significant role in reducing surface runoff through crown interception loss and root-enhanced infiltration. However, the effects of tree crown and roots on surface runoff are often simplified in the Storm Water Management Model (SWMM). This study aims to evaluate stormwater benefits of an urban isolated tree combined with different ground covers through interception-infiltration-runoff processes using SWMM. The crown interception process during 15 rainfall events was measured using a weighing lysimeter and used to obtain the net rainfall (i.e., the rainfall amount reaching the ground surface beneath tree crown) that was input into the rain gauge for simulations. Additionally, the optimization of key hydrological parameters in the bio-retention cell was performed to determine an optimal set of parameters to represent the effect of target tree roots on the infiltration process. This optimal set of parameters was validated using experimental results from two irrigation-drainage events, and the results showed that the coefficient of determination (R2) between simulated and measured results exceeded 0.9. According to the proposed simulation method that considers the effects of tree crown and roots on surface runoff, the interception-infiltration-runoff processes for different combinations of an isolated tree with tree pits, permeable pavement, and water-retaining pavement were analyzed during 15 rainfall events. The results revealed that the total surface runoff reduction from the isolated tree was 11.5%. Meanwhile, the simulation results for different combinations were compared to quantify stormwater benefits, including reductions in total and peak surface runoff. Based on rainfall characteristics (total rainfall amount and rainfall intensity) and surface runoff reduction, this study recommends optimal combination of the tree and ground covers to support urban greening design in stormwater management.
How to cite: Zhao, X. and Asawa, T.: Evaluating stormwater benefits of an urban isolated tree with different ground covers through interception-infiltration-runoff processes using Storm Water Management Model , EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-14318, https://doi.org/10.5194/egusphere-egu25-14318, 2025.
Urbanization has increased impervious surfaces, intensifying disaster risks in urban areas, particularly with climate change. Rainwater pumping stations and stormwater drainage systems are crucial for mitigating internal flooding, but their independent operation limits overall effectiveness. While integrated management of drainage facilities, including pumping stations, has been suggested, the development of systems to maximize existing technologies remains insufficient. Additionally, discharging stormwater into rivers to mitigate internal flooding can exacerbate external flooding by raising river water levels.
This study aims to integrate XP-SWMM and HEC-RAS to simulate internal runoff and surface flooding, model flood mitigation facility operations, and analyze river water level changes caused by lateral inflows in urban watersheds. The XP-SWMM model enables comprehensive runoff and 2D flood analyses, accounting for stormwater networks and hydraulic structures. Calibration and validation using water level data from Sebyeong Bridge in the Oncheoncheon watershed demonstrated good agreement between observed and simulated levels.
Lateral inflows for HEC-RAS were estimated by dividing the Oncheoncheon watershed using the Euclidean Allocation method. Initially divided into 133 sub-watersheds based on pipe connections, refinements led to 37 sub-watersheds by considering tributaries and further to 26 using contour data. Runoff hydrographs for the 26 sub-watersheds were generated using a 100-year return period 1-hour rainfall distributed via Huff's third quartile distribution.
These hydrographs were applied to HEC-RAS as lateral inflows. Terrain data were based on the ⌜Oncheoncheon River Master Plan (Busan Metropolitan City, 2017)⌟. Due to instability in upstream steep slope areas, these sections were excluded from simulations, focusing on watersheds with stormwater runoff reduction facilities. The upstream boundary condition utilized runoff from watershed 1, and the downstream boundary condition applied the 100-year base flood level. Stability was verified by assessing bridge cross-section water levels and time-step consistency.
Through HEC-RAS simulations incorporating lateral inflows, this study provides insights into optimizing operational rules for flood mitigation facilities, aiming to reduce both internal and external flooding via SWMM and HEC-RAS integration.
How to cite: Kang, J., Kim, K., Kim, J., Lee, S. I., and Jun, H.: Analysis of River Water Level Variability Based on Discharge Rates from Flood Mitigation Facilities Using SWMM+RAS for Preventing Internal and External Flooding in Urban Watersheds, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-4005, https://doi.org/10.5194/egusphere-egu25-4005, 2025.
The contribution of trees in altering the hydrological cycle necessitates evaluating the effects of meteorological conditions, leaf cover, seasonal variations, and rainfall magnitude on throughfall beneath pine tree canopy across different climates. Understanding trees' rainfall interception characteristics is essential for effective urban greenery planning and stormwater management. Thus, this study aimed to examine the influencing factors that are responsible for the variation in the throughfall rate of black pine trees (Pinus nigra Arnold) in diverse urban climates. To achieve the aim of this study, we analyzed gross rainfall and throughfall at two research experimental sites in the city of Ljubljana, Slovenia, and the city of Sopron, Hungary. The measurement period spanned from September 2023 to September 2024, with 42 and 51 rainfall events recorded at the sites, respectively. Both manual and automatic meteorological measurements were conducted at each site.
The mean throughfall over the measurement period was 45% in Ljubljana and 50% in Sopron, with average rainfall intensities of 2.02 mm/h and 1.96 mm/h, respectively. Throughfall patterns were analyzed across phenological and calendar seasons and rainfall magnitude. Both sites exhibited similar seasonal trends, but Sopron consistently had higher throughfall than Ljubljana in both phenological periods, with throughfall percentages increasing as rainfall magnitude increased. Throughfall was higher in Sopron during autumn, winter, and spring, whereas Ljubljana had higher throughfall in summer. The difference between the leafed and leafless seasons was 2.0% in Ljubljana and 1.9% in Sopron, with higher throughfall recorded during the leafless period at both sites.
The impact of the meteorological variables and canopy characteristics on throughfall across the year, leafed, and leafless periods was investigated using the regression tree (RT) and boosted regression tree (BRT) models. Rainfall amount was the primary predictor in all cases, but secondary factors varied by site and season. RT analysis showed that relative humidity and leaf area index (LAI) impacted throughfall in Ljubljana, while relative humidity, LAI, and rainfall duration were significant in Sopron during the year. Seasonal variations affected these influences, with rainfall amount impacting throughfall only during the leafless period, while wind speed and relative humidity played key roles in the leafed season for Ljubljana and Sopron, respectively. BRT analysis further confirmed that relative humidity influenced throughfall year-round at both sites. Furthermore, rainfall intensity and wind speed became critical during the leafed season in Ljubljana and the leafless season in Sopron.
The 5% variance in the mean throughfall observed between the two locations underscores the effect of microclimatic conditions and canopy attributes on the interception of rainfall by a pine tree canopy. These findings strengthen the need for site-specific hydrological assessments to enhance tree-based stormwater management practices in urban environments.
Acknowledgment: This study is part of ongoing research entitled "Microscale influence on runoff" supported by the Slovenian Research and Innovation Agency (N2-0313) and National Research, Development, and Innovation Office (OTKA project grant number SNN143972). The work was also supported through the Ph.D. grant of the first author which is financially supported by the Slovenian Research and Innovation Agency.
How to cite: Ogunfolaji, Y. O., Alivio, M. B., Orosz, K., Herceg, A., Kalicz, P., Zagyvai-Kiss, K. A., Gribovszki, Z., and Bezak, N.: Assessing the impacting factors responsible for the variation in the throughfall rate of black pine trees in diverse urban climates, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-4363, https://doi.org/10.5194/egusphere-egu25-4363, 2025.
Due to the rapid changes in precipitation patterns resulting from ongoing climate change, urban watercycle problem associated with extreme rainfall events are becoming increasingly severe. In response, the Ministry of Environment of Korea introduced the concept of Low Impact Development (LID) in the 2000s and has implemented stormwater runoff reduction facilities nationwide. This study investigates the impact of permeable block performance, one of the most widely adopted LID facilities, on the water cycle in urban drainage.
Initially, experimental analyses were conducted to assess the fundamental performance and clogging-induced degradation of various types of permeable blocks. These evaluations focused on examining the basic functionality of the blocks and the impact of clogging on their performance. Based on the experimental findings, the SWMM model was employed to investigate the effects of permeable block performance on hydrological processes across watersheds of varying scales.
The results indicated that the application of permeable pavement significantly improved the water cycle regardless of watershed size, with the extent of improvement dependent on the coverage area of permeable pavement. Notably, infiltration showed the largest increase across all watersheds, followed by increased evaporation and reduced surface runoff. In terms of peak runoff, significant reductions were observed in watersheds where permeable pavement covered more than 10% of the total area, although the reduction effects were marginal in most regions.
An investigation into the effects of clogging revealed that, compared to the initial installation phase, infiltration decreased by up to 34.2%, evaporation by up to 3.2%, and surface runoff increased by 0.7%. Furthermore, the study confirmed that clogging had the most substantial impact on the performance of permeable blocks, with performance degradation becoming more pronounced as block porosity increased.
These findings highlight the necessity for future research to establish correlations between porosity and clogging and to identify optimal porosity levels. Moreover, effective policy interventions are required to mitigate the impact of clogging by preventing the ingress of debris from the surrounding environment.
Accknowledgement
This work was supported by Korea Environment Industry & Technology Institute(KEITI) through R&D program for innovative flood protection technologies against climate crisis, funded by Korea Ministry of Environment(MOE)(RS-2023-00218973)
How to cite: Lee, H., Kim, J., and Shin, H.: Effect of Permeable Block Performance on the Urban Water Cycle, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-5277, https://doi.org/10.5194/egusphere-egu25-5277, 2025.
In this study, we present a probabilistic urban inundation modeling framework that combines high-resolution process-based modeling with observed information via ensemble data assimilation (DA). We investigate the impact of multivariate flood observations on improving urban inundation prediction accuracy through synthetic experiments. The framework leverages diverse flood observations from both the urban surface and sewer system, integrating them into the modeling process using non-Gaussian sequential DA methods, such as particle filtering. The modeling framework employs the H12 model for integrated 1D sewer network and 2D surface inundation analyses, with synthetic experiments conducted in an urban catchment in Osaka, Japan. Prior to implementing DA, a sensitivity analysis is performed to assess the effects of uncertainties in inundation modeling. Major uncertainty components, such as input forcings and storm drain box efficiency, are perturbed to evaluate their influence. The synthetic DA experiments analyze the influence of various types of flood observations, including urban surface inundation depths and sewer water levels, on the posterior distributions of the model ensemble. Additionally, the impact of observation location and density on DA performance is evaluated. This study demonstrates the potential of utilizing diverse flood observations in data assimilation to enhance the accuracy and reliability of urban flood predictions.
How to cite: Kim, B., Lee, Y., Lee, S., and Noh, S. J.: Exploring the Role of Multivariate Observations in Urban Flood Prediction: A Data Assimilation Approach, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-8211, https://doi.org/10.5194/egusphere-egu25-8211, 2025.
In the past, urban floods were primarily caused by river overflow due to insufficient conveyance capacity and inadequate infrastructure. However, in recent years, domestic flooding resulting from unplanned urban development has been identified as a major cause. To defend against and prevent urban floods, effective monitoring of urban infrastructure is essential, along with real-time analysis of monitoring data. However, current standards and methodologies for implementing such monitoring systems are insufficient.
This study aims to develop monitoring techniques for obtaining accurate flow data from key urban flood defense infrastructure and to establish methods for real-time evaluation of urban flow rates using data collected from various infrastructure components. The major urban flood defense infrastructure addressed in this study includes in-city elements, such as sewage pipes, rainwater pipes, sidewalks, underground reservoirs, and pump facilities, as well as out-of-city features like natural reservoirs. The experimental facility is designed to allow all infrastructure components to operate both organically and independently, depending on the experimental purpose. This study focuses on the construction and design of these facilities.
The experimental facilities are broadly categorized into urban floodplains, underground infrastructure, and out-of-city infrastructure. The urban floodplain replicates in-city infrastructure with a width of 35 meters and a length of 25 meters. It includes classified rainwater pipes, sidewalks, and a surface area designed to incorporate Low-Impact Development (LID) techniques in future experiments. The underground infrastructure features a network of rainwater pipes, underground reservoirs, collection systems, and pumping stations, designed to handle a maximum flow of 2 m³/s. The entire site is equipped to apply various monitoring techniques, with the construction of the experimental facilities planned in three phases, to be completed by 2026.
Acknowledgements
This work was supported by Korea Environment Industry & Technology Institute(KEITI) through R&D program for innovative flood protection technologies against climate crisis, funded by Korea Ministry of Environment(MOE)(RS-2023-00218973)
How to cite: Jung, S. and Kim, J.: Development of Experimental Facilities for Urban Flood Monitoring and Evaluation Method., EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-8838, https://doi.org/10.5194/egusphere-egu25-8838, 2025.
Urban flash floods have become increasingly frequent and severe, resulting in significant damage to lives, infrastructure, and the economy. A major contributor to urban flooding is the inability of stormwater drainage (SWD) systems to efficiently convey excess runoff, which often leads to localized failures and cascading disruptions across the network. Assessing the vulnerability of such systems becomes crucial for developing effective flood risk mitigation strategies. While conventional hydrodynamic models (e.g., SWMM, MIKE) are essential for predicting flood-related characteristics (e.g., peak flow/depth, duration) and inundation extents, they are limited in their ability to evaluate vulnerabilities within the system under rapidly changing rainfall patterns and account for uncertainties in decision-making processes. These limitations highlight the need for alternative approaches to analyze and address network vulnerabilities under dynamic conditions. The present study explores the potential of the Bayesian Belief Network (BBN) approach to evaluate vulnerabilities within the SWD system. This approach leverages the topological structure of drainage systems to assess interdependencies among components and flood-causing factors to better understand the cascading impacts of localized failures on the system-wide performance of a SWD network. The proposed BBN approach is tested on the Bangalore SWD network to identify critical zones under varying hydraulic loads. By providing probabilistic insights, BBNs enable a more comprehensive understanding of flood risk and improve decision-making under uncertainty. The findings of the study demonstrate the potential of BBN as a powerful tool for urban flood risk assessment and offer a comprehensive framework to strengthen flood resilience and guide infrastructural rehabilitation, planning, and management.
How to cite: Pandey, J., Sudhikumar, K., and Srinivas, V. V.: Vulnerability Assessment of Storm Water Drains using Bayesian Belief Network , EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-14978, https://doi.org/10.5194/egusphere-egu25-14978, 2025.
Rapid population growth and urbanization in India have significantly increased the discharge of untreated effluents into rivers, resulting in deteriorating water quality. Hydraulic structures, such as weirs, offer an effective solution to improve water quality in urban drains and streams by enhancing oxygen transfer and minimizing pollution loads. While natural streams often require several kilometers to re-oxygenate, weirs can achieve substantial oxygenation within shorter distances. This study investigates the oxygen transfer efficiency of contracted and uncontracted rectangular weirs through laboratory experiments conducted in a flume measuring 15 m in length, 0.5 m in width, and 0.75 m in depth. Dissolved oxygen concentrations were measured upstream and downstream of the weirs to evaluate oxygen transfer efficiency. The results show that contracted rectangular weirs outperform uncontracted weirs in oxygen transfer efficiency, with increased contraction leading to higher efficiency. Furthermore, the efficiency was found to increase with head loss over the weir and with the downstream Froude number. Hydraulic jumps formed downstream of the weir further contributed to oxygen transfer by entraining air bubbles into the flow. Using a phase detection probe, air concentration measurements revealed that the highest air concentration occurred near the jump toe, with depth-averaged air concentration decreasing with distance from the toe.
How to cite: Tiwari, A., Ojha, C. S. P., and Hari Prasad, K.: A Comparative Study of Oxygen Transfer Over Contracted and Uncontracted Weirs, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-20638, https://doi.org/10.5194/egusphere-egu25-20638, 2025.
The growing flood risk in urban areas, driven by urbanization and climate change, underscores the need for accurate building representation in flood hydrodynamic models. This study examines the effects of three representation methods—Building Block (BB), Building Hole (BH), and Building Resistance (BR)—on flood modeling during the 2021 Ahr Valley flood, analyzing their impact on flood extent, water depths, and flow velocities across different model resolutions.
Our findings reveal that building representation significantly influences flood dynamics. The BB and BH methods generally result in larger flooded areas, deeper water, and faster flows, while increased resistance or omitting buildings leads to smaller extents, shallower water, and slower flows. The choice of representation is especially critical at coarser resolutions, where the BH method yields the most accurate flood extents, while increased resistance performs better at finer scales. Although all methods achieve reasonable flood extent predictions, variations in water depths and velocities emphasize the importance of selecting the right approach for accurate flood impact assessments, particularly in dense urban areas. Finally our results highlight that tailoring building representation to model resolution is crucial for improving urban flood modeling and impact accuracy.
How to cite: Khosh Bin Ghomash, S., Devi Nallasamy, N., and Apel, H.: Evaluating the Role of Building Representation in Flood Dynamics: Insights from the 2021 Ahr Valley Flood, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-3124, https://doi.org/10.5194/egusphere-egu25-3124, 2025.
Urbanization exacerbates runoff, peak flow unpredictability, deterioration of water quality, and the Urban Heat Island Effect. Low-income, flood-prone areas are disproportionately impacted by weak governance and inadequate infrastructure. All of which influence water, energy, and equality balance. As preventing urban development is unfeasible, Low Impact Development (LID) provides a viable alternative. We offer a multi-scale framework that incorporates LID solutions for stormwater management in Ankara, Türkiye; therefore, filling the gap in holistic, multidisciplinary, and multiscale approaches via engineering and urban planner perspectives. Our framework contains: (i) Multi-Criteria Decision Making (MCDM)-Driven Pixel Scale Analysis of WorldView-4 images to create Land Use Land Cover (LULC) data using Random Forest (81.34% accuracy) on Google Earth Engine and SRTM-based slope and flow accumulation data. Using expert opinion and literature, we created and scored criteria matrices for LULC, slope, flow accumulation, and cost. This resulted in detailed LID suitability maps via the MCDM algorithm by the R programming language. (ii) Expert-Driven Neighborhood Scale Analysis for prioritization of LID based on urban parameters such as slope, surface morphology, population density, impervious surfaces, road networks, and runoff hotspots by the junction areas that emerge from the overlapping of the areas. Bioretention cells are suggested for 42.9% of the research area, rain barrels for 19.6%, and vegetative filter strips for 1.4%. Expert-Driven analysis facilitates prioritizing, whereas MCDM-Driven analysis gives pixel-level LID placement recommendations. This scalable, multidisciplinary framework provides a solid model for urban water management that may influence urban planners and policymakers in Ankara and other cities throughout the world.
How to cite: Şenocak, İ., Şimşek, G., Afshar, M. H., Tuna, A., Çakıcı Alp, S., Bektaş, H. O., and Alp, E.: Assessment of Low Impact Development Strategies with Multi-Scale, Multi-Criteria Decision Making Approaches for Urban Flood Resilience, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-513, https://doi.org/10.5194/egusphere-egu25-513, 2025.
Posters virtual: Mon, 28 Apr, 14:00–15:45 | vPoster spot A
EGU25-2656 | ECS | Posters virtual | VPS8
Developing Practical Green-Grey Solutions Based on Critical Node Identification for Stormwater ManagementMon, 28 Apr, 14:00–15:45 (CEST) | vPA.7
Urbanization has exacerbated challenges faced by urban watersheds, including increased impervious surfaces, deteriorating water quality, and heightened flood risks. Previous research has extensively employed the Genetic Algorithm (GA) to optimize urban grey-green infrastructure (GGI), primarily focusing on preventing system-wide overflow during design storm events. However, the high costs associated with these solutions have often hindered their implementation. This study proposes a practical approach to enhance urban stormwater management by prioritizing interventions at critical locations within watersheds. A multi-index fuzzy comprehensive evaluation (MFCE) model was developed to identify critical nodes in the drainage network based on hazard (overflow volume and duration), topological characteristics (degree and Katz centrality), and vulnerability (peak hour traffic flow). Problematic segments within the drainage network, including those with adverse slopes, mismatched pipe diameters, and ground depressions, were identified using a combination of SWMM simulations and graph-based analyses. Subsequently, the Genetic Algorithm (GA) was employed to optimize the design and placement of grey-green infrastructure solutions, subject to the constraint of preventing overflow at these critical nodes during design storm events. A case study in Guangzhou, China, demonstrated the efficacy of this approach. The optimized grey-green infrastructure system significantly reduced budgetary costs and peak flow compared to traditional grey infrastructure systems, while enhancing flood control and improving the overall resilience of the urban watershed.
How to cite: Yang, G., Huang, G., and Zeng, B.: Developing Practical Green-Grey Solutions Based on Critical Node Identification for Stormwater Management, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-2656, https://doi.org/10.5194/egusphere-egu25-2656, 2025.
