This session invites research that focuses on all aspects of urban hydrological research, with a particular focus on urban hydrological processes and related water challenges, including:
- Urban catchment characterization and functioning.
- Runoff and pollution in urban watersheds.
- Flood management and drought risks in urban or urbanized regions.
- Urban stormwater management solutions, including green infrastructure and other nature-based solutions.
- Surface-groundwater interactions in urban areas.
- Exploring inter-linkages between hydrometeorology/hydroclimate, surface and subsurface water resources, urbanization and extreme weather in the context of urban water management.
- Integrated approaches for studying/monitoring urban watersheds
- Community engagement and climate adaptation and management strategies in urban areas.
We particularly encourage submissions focusing on urban water challenges in the Global South.
Orals: Wed, 6 May, 08:30–12:25 | Room 2.44
Urban water scarcity is increasingly recognized as one of the most pressing challenges facing urban watershed management, driven by the compounding effects of climate change and rapid urbanization. Day Zero events, in which municipal taps run dry, have exposed critical vulnerabilities not only in physical infrastructure but in urban governance and social equity. While hydrological research often focuses on physical scarcity, this research argues that understanding urban watershed dynamics requires a systematic integration of social and institutional dimensions. This study presents a systematic literature review of three decades (1995–2025) of peer-reviewed social science research on urban water shortages involving rationing and emergency measures. Analyzing 69 articles from 1,295 records, the study tracks the evolution in research focus. Findings show shifts in disciplinary and methodological approaches, proposed coping strategies (technocratic versus sociocratic), levels of analysis, and water crisis framing. The review highlights that research is heavily clustered around several highly publicized water crises, notably Cape Town’s “Day Zero” (2015-2018), Australia’s Millennium Drought (2000s), and the Brazilian Drought (2014-2017). By synthesizing insights, the review identifies key gaps in integrated approaches for studying urban watersheds. It concludes that advancing urban water management research requires connecting hydrological processes with social-political drivers, to inform policy approaches that address scarcity not only as a technical challenge but as a fundamentally social and political issue.
How to cite: Laauwen, M., Koehler, J., and Greene, M.: Cities under pressure: a global review of urban water scarcity governance, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-10107, https://doi.org/10.5194/egusphere-egu26-10107, 2026.
High nutrient loads, coming from urban sewage water and agricultural land use affect ecosystem functioning of surface water bodies. Urban lakes are special cases due to the anthropogenic use as storm water reservoir and the pollution caused by nutrients such as phosphorus and nitrate. Especially, the pollution by high nutrient loads causes the aquatic ecosystem to change in the trophic state to eutrophic or even worse hypertrophic, which influences the availability of oxygen and by this the occurrence of fishes, insects, plants and other aquatic beings. Moreover, the release of hydrogen sulfide due to anoxic conditions at the bottom of a lake causes odor in the surroundings of the lake. Improving the water quality of urban lakes is both a benefit for the ecosystem, and for the socio-ecological value of the waterbody. While reducing nutrient loads from inflowing water is crucial to achieve a healthy aquatic ecosystem, an in-depth understanding of transport and reaction processes in connected urban lakes is needed to guide restauration measures and water quality management. An example for connected water bodies is the Grunewald chain of lakes in Berlin, Germany, where ten lakes are connected one after the other, directly, via pumps or canals. The lakes are located at the southwest of Berlin and are surrounded by urban areas. The lakes serve as storm water reservoirs collecting rain water from urban and traffic areas. Phosphorus and other pollutants are accumulated in the lakes. To better understand the exchange between the lakes and how they affect each other, a monitoring campaign was conducted over a period of 13 months, where monthly water samples were taken at 17 sampling stations at the inlets, outlets and at the connections of the lakes. During the monitoring campaign (07/2024 - 07/2025), a heavy rain event with more than 20 mm per day was captured providing insights into nutrient transport along the chain of lakes. A feature selection algorithm (Boruta) was applied to identify the key parameters that affect the limiting nutrient in the Grunewald chain of lakes. The limiting nutrient is described by the TN:TP ratio, also known as Redfield ratio, and categorized as phosphorus limited, nitrogen limited and co-limited. In this study, an investigation about the variation of the measured parameters as well as the TN:TP ratio along the chain of lakes and the dependency of the season is conducted in addition to the Boruta feature selection. This study reveals the relevance of temperature, volume ratio, depth and phosphorus concentrations affecting the TN:TP ratio of the lakes and how water quality of the lakes are affected by each other. The study gives insights to cascading effects on nutrient accumulation along a chain of lakes, providing guidance for further management practices.
How to cite: Radtke, C., Heinemann, N., Höring, A., and Schröter, K.: Identification of Key Water Quality Drivers in the Grunewald Chain of Lakes, Berlin, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-2779, https://doi.org/10.5194/egusphere-egu26-2779, 2026.
Marsh Creek in Oakley, CA was once a naturally, intermittent creek that ran from the foothills of Mt. Diablo to Dutch Slough and into the San Francisco Estuary (Contra Costa Resource Conservation District, n.d.). It contained several native fish species, whose ranges were dispersed across varying aquatic habitats. Over time, the creek has been dammed and diverted for agricultural and recreational purposes. Today, only a few sections of intermittent and small, perennial streams remain in the foothills. The lower section of the creek has become channelized, receives perennial flow from a wastewater treatment plant, and the Marsh Creek Reservoir. These anthropogenic modifications have facilitated the creation of a novel ecosystem, where the remaining native aquatic community assembly blends with introduced, non-native species.
Despite being modified, we detected regional species of concern such as Sacramento Hitch (Lavinia exilicauda) and Chinook Salmon (Oncorhynchus tshawytscha) using Marsh Creek as habitat. To determine how Marsh Creek serves as habitat for these native fish, we plan to utilize GoPro video surveys and clover/minnow traps to assess species abundance and habitat heterogeneity at sample sites. Macroinvertebrate and YSI samples will be collected to characterize water quality and identify invertebrate community assemblage. Visual observations are planned to be used to observe breeding behavior and abundances of chinook salmon and Sacramento hitch adults. This study seeks to provide insight into the persistence of native fish in novel ecosystems and the influence stream modification can have on aquatic communities in Central California.
How to cite: Long, C. and Durand, J.: Trends of Native & Non-Native Fish Communities in an Urban Creek (Marsh Creek, California) , EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-15672, https://doi.org/10.5194/egusphere-egu26-15672, 2026.
In urban areas, a high groundwater table can cause problems such as groundwater flooding, unintended infiltration into sewer and drainage systems, and infrastructure damage. These challenges are further intensified by climate change, underscoring the need for improved water management in low-elevation urban areas. Developing solutions depends on a detailed understanding of groundwater‑level dynamics, which constitute the core of this research.
Recent research based on urban groundwater monitoring sites in Denmark has shown that shallow groundwater varies seasonally far more than deeper groundwater. Furthermore, it is shown that shallow groundwater levels may abruptly rise by 50–150 cm as an immediate response to rainfall. The explanation for the extreme dynamics is identified as the capillary fringe zone, which becomes fully saturated in response to infiltrating rain. In the capillary fringe zone just above the normal groundwater level, the capillary forces are stronger than the gravitational forces, leaving this transition zone nearly saturated. Under the impact of infiltrating rain, the saturation of the capillary fringe zone results in a change in pore water pressure from negative to positive and thus an observable change in the groundwater table.
In areas with shallow groundwater, the magnitude of these significant groundwater level increments can be critical for triggering groundwater flooding or unintended infiltration into sewer systems and drainage infrastructure. Moreover, observations have shown that in clayey soil types, the groundwater level can remain elevated for days to weeks after rainfall, whereas in sandy soils, the groundwater levels return to their original state much more quickly.
Understanding these dynamics requires greater knowledge of infiltration processes, the unsaturated zone, and, in particular, the capillary fringe zone, which in many cases is neglected in the estimation of groundwater level variability.
In this work, we present analyses of time series of groundwater head, soil moisture, and rainfall, and link observed rainfall-response to physical and hydraulic soil properties. Furthermore, we propose the development of a one-dimensional modelling concept of the vadose zone based on the Darcy flow equation integrated with respect to soil depth and combined with an explicit finite-difference solution of the continuity equation. The model is demonstrated to simulate the dynamics of groundwater head as a response to rainfall for different soil types. Accordingly, the study aims to model potential groundwater variability as a function of multiple soil‑properties, providing a basis for subsequent risk assessment related to shallow groundwater in urban areas.
How to cite: Thorndahl, S., Vester, I. K., Nielsen, J. E., and Møldrup, P.: Shallow Groundwater Dynamics in Urban Environments: The Crucial Role of Capillary Forces, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-18223, https://doi.org/10.5194/egusphere-egu26-18223, 2026.
There is growing concern about the impact of wastewater discharges from combined sewer overflows (CSOs) on the quality of surface waters and their vulnerability to a wetter and stormier climate. The UK is already experiencing increased wet weather, and will continue to have more intense and frequent storms with climate change. Stronger and more frequent storms will increase pressure on sewer networks, likely compromising treatment capabilities and increasing discharges via CSOs. Consequently, reduced wastewater treatment means more faecal pollution and further degradation of surface water quality through increased loads of solids, faecal microbes, phosphorus, organics, microplastics, and pharmaceuticals.
Using a 12-month dataset from >1500 overflow monitors across Scottish Water’s Wastewater Intelligence Network (WWIN), the authors will present a novel analysis of real-time monitoring of CSO discharges at the nationwide level. Preliminary analysis involving the WWIN monitoring data and daily regional rainfall intensities show how high intensity storm events were the main driver of significant CSO discharges across Scotland in 2025. This research reveals for the first time that monitoring data has been analysed at a national scale to evaluate the impacts of weather on network performance. The results demonstrate that the intensity of rainfall, rather than total rainfall volume, is the main driver in causing significant CSO discharge events. This presentation will showcase how real-time CSO monitoring can improve climate-informed decisions in prioritising and evaluating asset performance at a catchment level to ensure maximum return on investment to relation protecting public and environmental health.
How to cite: Rusk, B., Hunter, P., Oliver, D., Quilliam, R., and Tyler, A.: Extreme Storms and Sewer Overflows, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-1270, https://doi.org/10.5194/egusphere-egu26-1270, 2026.
Climate change can significantly affect the effectiveness and resilience of Stormwater Control Measures (SCMs) in urban environments, as changes in rainfall intensity and depth can impact SCMs' capacity to mitigate flooding and reduce pollutant loads in water bodies. Thus, increasingly adaptive and robust SCM designs need to be informed by a continued understanding of changing precipitation patterns. In this study we evaluate SCMs precipitation thresholds based on two main methods: 90% rainfall capture depth and 90th percentile rank of daily precipitation over the period 1980-2023 in North Carolina, USA. We sought to address the questions of whether changes in daily precipitation are detected over time and, if so, whether these changes result in different thresholds depending on the method of choice. Our results indicate over the entire timeseries (1980-2023) both methods result in thresholds consistent with the current North Carolina Department of Environmental Quality SCM standard of 25.4 mm/day in central and western North Carolina and 38.1 mm/day in the eastern coastal plains. However, when the data is sliced in four 11-year periods the evolution of precipitation thresholds show a positive trend in both methods. We also find that the capture depth method is considerably more sensitive to extreme precipitation events than the 90th percentile method. Our results indicate that current water quality event standards in North Carolina may underestimate pollutant load treatment due to observed precipitation changes in recent years, suggesting a need for decadal adjustments. Defined SCM threshold need also to account for differences arising from the choice of calculation method, and practitioners using the capture depth methodology in particular, may want to revisit established thresholds.
How to cite: Fernandes, K., Sañudo, L., Hunt, W., and Bowden, J.: Evaluating the impacts of climate variability and change versus methodological approaches on stormwater control measures rainfall thresholds. A case study from North Carolina, USA, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-1576, https://doi.org/10.5194/egusphere-egu26-1576, 2026.
Trees are found ubiquitously in urban environments and are appreciated for a range of ecosystem services. However, their ability to reduce stormwater runoff volumes – and any tradeoffs involved with nutrients and other pollutants typically carried by stormwater runoff – are largely overlooked in stormwater management practices due to lack of robust data. We undertook a three-year project to monitor tree-scale water quantity and quality fluxes and examine how these local measurements and patterns related to the watershed observations across the city of Saint Paul, Minnesota. In this conference paper, we report on our multi-year effort to quantify the effects of trees on the urban hydrologic cycle, which included measuring the stormwater interception capacity of urban trees and their contributions to coarse organic matter, nitrogen, and phosphorus fluxes, using a series of watersheds in the Saint Paul, Minnesota, USA. At the tree scale, we quantified patterns in canopy throughfall amount, transpiration, and nutrient fluxes in canopy throughfall, which relates directly to stormwater runoff generated under deciduous trees. Under most species at most sites, canopy throughfall was statistically lower than open precipitation. Transpiration rates, determined by the sapflux method, differed across individual trees, with tree health and canopy defoliation explaining some of the differences between individual trees. Canopy interception also altered throughfall nutrient concentrations and fluxes relative to open precipitation. In spring and summer seasons between 2023-2024 mean soluble reactive phosphorus (SRP) and total organic carbon (TOC) fluxes were significantly higher under ash and maple trees than in open precipitation despite lower overall water fluxes under the canopy. With this process, deciduous trees potentially contribute increased phosphorus fluxes to stormwater while leaves remain on the tree canopy. Beyond the individual tree scale, stormwater fluxes, as monitored at the watershed level, showed variation with landcover. The presence of deciduous street tree canopy in watersheds corresponded to patterns in nutrient concentrations in stormwater at the storm-event and seasonal time scales.
How to cite: Karwan, D., Feng, X., Rose, L., and Chen, X.: Urban trees influence stormwater quantity and quality from site to watershed scales, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-22168, https://doi.org/10.5194/egusphere-egu26-22168, 2026.
Urban flooding and water-logging have become recurring problems in Guwahati, Assam, India, primarily due to rapid and unplanned urbanization, high monsoonal rainfall, and degradation of natural drainage systems. The Maligaon Railway Colony, one of the most flood-prone areas of the city, frequently experiences surface inundation caused by inadequate stormwater conveyance, encroachment on natural drains, and runoff from the surrounding Kamakhya and Gotanagar hills. This study evaluates the performance of the existing stormwater drainage system of the Maligaon Railway Colony and proposes improvement measures to mitigate flooding. A detailed assessment was carried out using topographic data and hydraulic modeling in SWMM to simulate rainfall–runoff processes and drainage network behaviour under peak rainfall conditions. Initial simulations identified critical deficiencies in the existing system, particularly poor connectivity among several drainage nodes on the northern side of the railway line, leading to localized flooding. These issues were addressed through network modification and re-simulation. Two improvement scenarios were analysed, a proposed drainage system without wetland interaction and a system incorporating wetland storage effects linked to Deepor Beel. Simulation results indicate that, in the absence of wetland influence, the proposed outfall system conveys peak discharges of approximately 34 m³/s during a 2-hour rainfall event with a 5-year return period. When wetland storage is considered, the peak outflow is reduced to about 20 m³/s, demonstrating a substantial attenuation of flood peaks. The findings highlight the importance of preserving and integrating wetlands into urban drainage planning. The study provides practical design recommendations for improving drainage efficiency, reducing flood risk, and promoting sustainable stormwater management in the Maligaon Railway Colony.
How to cite: Luxmi, K., Jyoti Sarmah, D., and Kumar Bhattacharjya, R.: Improvement of the Stormwater Drainage System in the Maligaon Railway Colony, Guwahati, Assam: A Case Study, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-18594, https://doi.org/10.5194/egusphere-egu26-18594, 2026.
In many snow-affected regions, road salt application (primarily sodium chloride) has caused long-term chloride increases in streams, lakes and groundwater, negatively impacting freshwater biodiversity and drinking water quality. While regional-scale studies in Ontario, Canada have documented strong relationships between chloride concentrations and urban land use, local drivers of longitudinal stream chloride patterns within individual watersheds remain poorly understood. In Toronto’s highly urbanized Black Creek catchment, in-stream sensors reveal spatial variability in chloride, but insufficient groundwater monitoring wells prevent similar high-resolution mapping of subsurface concentrations.
Here, we leveraged leaking stormwater sewers as sampling points for shallow groundwater throughout the watershed. Water samples collected during inter-event periods in summer 2025 from storm sewer outfalls (n = 111) were analyzed for stable isotopes of oxygen and hydrogen in water and major ions. Using historical isotope signatures for groundwater, municipal water, and precipitation, we identified 70 % of the samples as likely groundwater. Among these, chloride concentrations ranged from 126 to 4,241 mg/L, all exceeding Canada’s chronic guideline (120 mg/L). Spatial patterns indicate highest concentrations near multi-lane highways crossing the catchment, corroborating previous modelling studies. This demonstrates that leaky sewer sampling offers a novel, accessible approach for mapping shallow groundwater chloride, which is critical for understanding surface water patterns and identifying areas that are vulnerable to elevated salinity.
How to cite: Oswald, C., Atwal, G., Holmes, G., and Ross, C.: Using leaky sewers to map urban groundwater chloride contamination, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-21752, https://doi.org/10.5194/egusphere-egu26-21752, 2026.
Groundwater recharge in urban areas is generally accepted to differ from that in natural landscapes. However, due to numerous artificial influences on groundwater recharge, it is often difficult to predict the groundwater recharge without proper monitoring. Meanwhile, data from urban areas is scarce because most built-up sites consist of private property where data collection is challenging. This is particularly problematic for settlements with individual water supply in hardrock regions, as they are highly dependent on local groundwater resources. Furthermore, the availability of groundwater in those areas is often threatened by the ongoing climate change.
We evaluated the impact of localized infiltration of rainwater from impervious surfaces on groundwater recharge in a small settlement in Czechia. As the settlement has no public water supply or wastewater collection, the only artificial influences on water balance are withdrawal from domestic wells, irrigation and rainwater discharge on individual estates. Therefore, localized infiltration can be observed with as little disturbance as possible. We monitored water table level in a well, and installed a piezometer next to an outlet from rainwater drainage of a house roof to observe the localized infiltration independently. Two lysimeters were installed at the site – one 35 cm deep with cut grass and one 94 cm deep with shrubs. They confirmed that evapotranspiration significantly reduces the amount of groundwater recharge in gardens. The profiles with grass and shrubs consumed 68% and 95% of precipitation, respectively. During a 2-year monitoring period, water percolated to the bottom of the deeper lysimeter very few times – only in winter or after extreme rainfall. Despite that, water table in the well rose even when there was no recharge through the soil profile with vegetation. As the water table rises corresponded to peaks in the piezometer, it is evident that they were caused by the localized infiltration from the rainwater drainage. We estimated groundwater recharge inside and outside the settlement using Water table fluctuation method and Soil moisture deficit model (Šabatová et al., 2025), and also compared it to an existing regional study of groundwater recharge. Our results suggest that groundwater recharge enhanced by the localized infiltration can be up to 4 times higher than natural recharge. Thus, localized infiltration from impervious surfaces can substantially improve the water balance in built-up areas. This is especially valuable in dry periods, because the localized infiltration appears to percolate rapidly, avoiding capture for evapotranspiration. Therefore, allowing the rainwater from impervious surfaces to infiltrate can contribute significantly to counter the increasing drought related to the climate change, especially in hardrock areas where groundwater is of local origin.
References
Šabatová, K., Bruthans, J., Weiss, T., 2025. New groundwater recharge model for water table fluctuation method calibration using easily available data. Journal of Hydrology 661, 133685. https://doi.org/10.1016/j.jhydrol.2025.133685
Acknowledgements
Contribution was supported by project SS02030040 "PERUN - Prediction, Evaluation and Research for Understanding National sensitivity and impacts of drought and climate change for Czechia", co-financed with state support of the Technology Agency of the Czech Republic as part of the Program Environment for Life.
How to cite: Šabatová, K. and Bruthans, J.: Increased groundwater recharge due to localized infiltration from impervious surfaces in an urban area, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-6353, https://doi.org/10.5194/egusphere-egu26-6353, 2026.
The design of urban neighbourhoods involves addressing a multitude of interrelated factors, which makes decision-making increasingly challenging. This complex task is further exacerbated by the steady expansion of urban areas, the increasing frequency and intensity of meteorological extremes, and the growing interest in sustainable urban drainage systems and the Nature-based Solutions (NBS). Within this context, and as part of the Water Smart Cities (WSC) European project funded by the European Regional Development Fund (ERDF), a modular software tool has been developed to rapidly assess the performance of NBS and conventional grey infrastructure for stormwater management in relatively small urban catchments. The tool is intended to support urban planners, decision-makers, and civil engineering consultancies by offering an intermediate level of modelling complexity that bridges the gap between simple spreadsheet-based approaches and highly detailed hydraulic-hydrological simulation platforms.
The software architecture is based on nodal modelling and organised into interconnected modules that address various aspects of urban water management. Hydraulic and hydrological components provide quantitative assessments, while ecosystem services and water quality aspects are represented by a combination of quantitative outputs and qualitative indicators. This modular structure enables the flexible testing and comparison of alternative urban drainage strategies, including both NBS and grey solutions, within a consistent modelling framework.
This contribution focuses on the hydraulic-hydrological solver and its applications. The solver is implemented in Python using the JAX library, and is based on an implicit numerical formulation. JAX enables just-in-time compilation, automatic differentiation for efficient Jacobian evaluation, and parallel computation on CPU and GPU architectures provided one adopts a pure functional programming paradigm using continuously differentiable model formulations. The implicit formulation improves numerical stability and ensures synchronous coupling between interacting system components, thereby avoiding artificial numerical delays.
Unlike spreadsheet-based tools, which are generally limited to volume-based evaluations, the proposed solver explicitly represents the dynamic interactions between structures and their spatial organisation. It allows the assessment of outlet regulations, pipe characteristics, spillway geometries, soil properties and . This provides design-relevant information to communicate modelling uncertainties and support planning and decision-making. Several applied case studies will be presented to showcase the implications of modelling choices and the range of design possibilities in the context of water-sensitive urban development.
Acknowledgments: The project Water Smart Cities is part of the projects portfolio SWaM@Sc, cofunded by the European Union and by the Walloon Region (ERDF)
How to cite: Dessers, C., Champailler, S., Renard, A.-C., Sadrijaj, D., Dellieu, A., Paulus de Chatelet, P., Gritten, F., Erpicum, S., Pirotton, M., Degré, A., Dewals, B., and Archambeau, P.: Water Smart Cities: a Modular Modelling Framework for Nature-Based Stormwater Management in Urban Areas , EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-18804, https://doi.org/10.5194/egusphere-egu26-18804, 2026.
Bengaluru, the “Silicon Valley of India”, faces environmental pressures, with degradation of its urban lakes among the most visible. Historically, three interconnected catchments with cascades of manmade reservoirs supported irrigation, domestic use and groundwater recharge. Rapid urbanisation and a shift from agriculture to the service sector led the city to import water from the Cauvery River, about 100 km away, reducing reliance on local lakes. Wastewater infrastructure did not keep pace with expanding water supply, and many lakes became sinks for untreated or partially treated sewage, resulting in fish kills, algal blooms and odour problems.
In response, public agencies, corporate social responsibility initiatives and citizen groups undertook lake restoration projects, but most interventions focused on civil works such as stone pitching, desilting, deepening of basins and planting of exotic species, with limited ecological rationale. Restoration success has typically been assessed against national “Class B” bathing water standards. Because most lakes fail to meet these norms, restoration is often portrayed as unsuccessful.
This study presents a context specific framework to benchmark lake health and guide restoration in rapidly developing catchments. We evaluated 32 lakes during critical season (Feb to May 2025), randomly selected from about 180 across Bengaluru, representing diverse intervention types, such as sewage treatment plants, sedimentation ponds and constructed wetlands, and different levels of community stewardship. Lake condition was assessed along three dimensions: water quality and hydrology (Secchi depth, total phosphorus, dissolved oxygen), biodiversity (plant and bird diversity) and community engagement.
To develop an operational benchmark, we focused on three indicators with strong ecological relevance: water clarity (Secchi depth), nutrient status (total phosphorus) and plant species richness. These were weighted to reflect their relative importance (0.5, 0.3 and 0.2 respectively). Indicators were normalised across lakes; beneficial values were scored positively and detrimental values inversely. Composite scores were calculated for each lake, and a benchmark threshold of 0.6 was proposed.
Fewer than 20 percent of lakes exceeded this benchmark. Higher scoring lakes had Secchi depth greater than 0.4 m, total phosphorus less than 0.8 mg/L, well maintained shoreline vegetation and received treated wastewater through sedimentation zones or in lake constructed wetlands, together with strong community stewardship. Lower scoring lakes were characterised by total phosphorus greater than 1.2 mg/L, Secchi depth less than 0.25 m and degraded shorelines, reflecting inflows of untreated or partially treated sewage and weak local engagement.
The framework helps establish restoration targets that are achievable in rapidly urbanising catchments. Rather than focusing solely on bathing water standards, agencies can use the benchmark to design interventions (type and scale) that help lakes achieve threshold 0.6 and above. Additionally also help identify catchment and in lake factors associated with higher water clarity and better ecological condition. Well performing lakes can serve as reference systems, and the benchmark can act as a performance indicator. These lakes can also be developed as living laboratories where schools and communities monitor simple indicators such as Secchi depth, total phosphorus and plant diversity, helping to sustain lake health and the effectiveness of interventions.
How to cite: Jamwal, P.: Innovative approach to restoring urban water bodies in rapidly developing catchments, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-183, https://doi.org/10.5194/egusphere-egu26-183, 2026.
As climate change intensifies, urban areas are increasingly exposed to compound hydro-climatological extremes, including heat waves, pluvial flooding, droughts, and associated thermal and health stresses. These hazards are interconnected, and their impacts are modulated by socio-demographic factors (e.g. age structure, population density), urban form (e.g. imperviousness, ventilation corridors), and pre-existing environmental burdens such as air pollution and noise. Understanding these impact chains is essential for identifying where adaptation measures can most effectively reduce vulnerability.
Nature-based Solutions (NbS), including unsealing, green infrastructure, and decentralized stormwater retention, have demonstrated substantial potential to simultaneously mitigate heat and flood impacts. Despite their proven benefits, implementation in Berlin remains fragmented and spatially limited, with measures typically realized as isolated projects rather than strategically located where their effectiveness would be highest.
This study identifies priority locations for NbS implementation by integrating multi-criteria indicators: pluvial flood risk, environmental burdens (air pollution, noise, thermal stress), and socio-demographic development. Using population projections for Berlin until 2040 combined with the Environmental Justice Atlas, the Friedrichshain district was identified as exhibiting elevated vulnerability to hydro-climatological extremes.
The district is characterized by continued population growth (+2.1 % by 2040), the highest projected increase in average age across Berlin (from 38.9 to 41.6 years), high surface sealing (~70 %), limited green infrastructure, and pronounced thermal load. These characteristics make the district particularly susceptible to compound flood and heat hazards and a representative case for highly built-up environments.
Building-scale pluvial flood risk was assessed using the 2D shallow water model hms++, simulating a 100-year precipitation event (48.8 mm in 1 hour). Mesh resolutions of 2×2 m, 4×4 m, and 8×8 m were compared to analyze flood extent and volumes while balancing model precision and computational efficiency. Flooding hotspots were identified using the unsupervised clustering algorithm DBSCAN, enabling robust detection of clusters with varying shapes and densities. Results reveal major flooding clusters in the south-western study area, particularly at sealed crossroads with limited infiltration capacity and high cumulative environmental burdens. Initial scenario analyses demonstrate that selective unsealing of public spaces (schoolyards, parking areas) can substantially reduce total flood volume (-6 % at 8×8 m; -44 % at 2×2 m) and inundated area (-4 % at 8×8 m; -35 % at 2×2 m) in the largest clusters.
Future work will incorporate time-varying infiltration and evapotranspiration schemes to capture wetting-drying cycles, vegetation dynamics, cooling effects of blue-green infrastructure, and potential drought stress. The proposed framework supports integrated assessment of flood-heat-drought interactions and provides evidence-based guidance for climate adaptation strategies in vulnerable urban districts.
How to cite: Ölmez, C. and Hinkelmann, R.: Perspectives on Target-Oriented NbS/BGI Interventions through Integrated Hydrodynamic Modeling and Social Indicators, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-7198, https://doi.org/10.5194/egusphere-egu26-7198, 2026.
The phenomenon of urban flooding has evolved into a critical challenge in contemporary urban environments. Urban floods can occur due to rapid unplanned urbanization, frequent climatic extremes, and poor urban drainage infrastructure (URDAN). Incidents of urban flooding have become frequent in recent history. Hence, it is imperative to strengthen the flood resilience of cities. The present study proposes a holistic, multi-faceted flood resilience framework that integrates the critical elements of past urban floods, simulates existing URDAN using present and future climate extremes, and evaluates the integration of Low Impact Development (LID) in enhancing resilience of cities. Historically, landuse change and climate variability are quantified along with a dedicated assessment of previous urban floods. For the present, urban flood risk zonation and hotspot identification (UFRZHI) ascertain areas at higher flood risk. Performance of URDAN in a high flood risk zone is then evaluated using Stormwater Management Model (SWMM). The URDAN is optimized for performance using LID elements, while General Circulation Models (GCMs) integrate future rainfall projections.
The study analyzed the 2019 urban flood and found that climate change was the immediate cause of the floods, as intense rainfall overwhelmed the existing URDAN, while the week-long inundation resulted from poor management. The builtup area increased from 29.9 to 48.5 sq. km., while vegetation declined from 64.5 to 48.7 sq. km. between 1990 and 2020. The long-term historical (1950–2020) climate variability assessed using Modified Mann-Kendall and Centroidal Day (CD) shifts shows a forward shift in monsoonal and annual rainfall in recent decades. The variability in total rainfall is more pronounced post-1985, while rainfall during monsoons has intensified. An increase of 64.53 mm (18.9%) in surface runoff is observed despite decreasing rainfall trends.
A normalized multivariate approach ranks the performance of downscaled and bias-corrected GCMs. The ensemble of the top three optimal GCMs is used for future predictions for Shared Socioeconomic Pathways (SSP) (SSP245, SSP370, and SSP585) scenarios. The historical annual maximum hourly rainfall series was fitted to Generalized Extreme Value distribution and alternating block method develops design storm hyetographs. The UFRZHI analysis identifies the most flood-prone areas, the existing URDAN of which is comprehensively evaluated using SWMM for 2- (baseline), 5-, 10-, and 25-year return periods. Simulation results show that the baseline URDAN fails and the time to peak ( Tp) is 59 minutes for 2-year return period. The peak outlet discharge (Qpeak ) increases and remains constant with higher return periods and warmer climate forcings.
Permeable pavement, bioretention cells, and green roofs included URDAN shows a sharp decrease in Qpeak and a 22-minute delay in Tp. The inclusion of LID eliminates URDAN failure and reduces the runoff in subcatchments by 40-45%. The performance of LIDs saturates under higher return periods and warmer climatic scenarios. The framework in the present study can model risk prone URDAN and alleviate the failure stress through the inclusion of LID and climate uncertainty. The proposed framework can be used to develop an urban flood resilient city under climatic extremes.
How to cite: Rashiq, A. and Prakash, O.: Climate-Adaptive Urban Flood Hazard Framework: Risk Evaluation and Resilience Optimization, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-808, https://doi.org/10.5194/egusphere-egu26-808, 2026.
Recent precipitation extremes have shattered historical records over the Beijing-Tianjin-Hebei (BTH) region, causing devastating losses of life and property. While climate change is expected to increase the probability of precipitation extremes, how the frequency and intensity of rarest events will change remains unclear. Here, we develop an integrated framework combining long-term observations, large-ensemble Earth system simulations, and convection-permitting regional modeling to project the likelihood and magnitude of such “rareness” precipitation events. Using the Community Earth System Model Large Ensemble (CESM2-LE), we find that the likelihood of regional events comparable to the July 2023 BTH extreme precipitation event (“23.7 BTH” event) increase by 159% under the SSP3-7.0 scenario, primarily driven by thermodynamic intensification linked to more frequent moisture-abundant conditions. We further find that the local intensity of the most extreme future storms may increase by approximately 30%, with hourly precipitation rate nearly doubling. Our framework provides a robust pathway to quantify the frequency and magnitude of unprecedented regional extremes, offering critical implications for flood management, hazard mitigation, and climate adaptation planning.
How to cite: Pei, L., Miao, S., Zhao, L., and Chen, D.: Intensified future regional record-shattering precipitation events from convection-permitting ensemble downscaling, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-3709, https://doi.org/10.5194/egusphere-egu26-3709, 2026.
Aggregated sewershed models provide simulations of sewer system behaviour with relatively low computational cost and limited structural complexity. In contrast, fully distributed models, such as SWMM and Infoworks, provide detailed representations of flows within individual pipes and network infrastructure, but require extensive data for model construction and substantially greater computational resources. Sewersheds are also embedded within wider integrated water systems, interacting with hydrological processes through both inputs and outputs. Capturing these interactions introduces additional modelling complexity and motivates the use of integrated modelling approaches. Across all model types, uncertainty is inherent. In particular, structural uncertainty (arising from choices related to model formulation, process representation, and model component configuration) remains a significant challenge and is especially difficult to quantify. In this study, we examine three urban case studies in the Greater Manchester region, developing aggregated integrated models using the WSIMOD integrated modelling framework. WSIMOD enables the simultaneous representation of urban infrastructure, hydrological processes, and land use within a flexible model structure, making it well suited to integrated sewershed modelling and the exploration of alternative model configurations. We introduce and apply a novel framework to systematically explore the impacts of key modelling decisions on both model behaviour (simulated system dynamics) and performance (simulation-observation metrics). Alternative model structures were constructed to represent different modelling choices, and a series of sensitivity analyses was conducted to assess parameter sensitivities and to group model processes according to their influence on model behaviour and performance. The results provide insights into how structural modelling decisions affect aggregated sewershed model outcomes and highlight implications for integrated urban water system modelling.
How to cite: Maes-Prior, R., Dobson, B., and Mijic, A.: Evaluating integrated model structural uncertainty of aggregated urban sewershed models, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-20194, https://doi.org/10.5194/egusphere-egu26-20194, 2026.
Evaporation from rainfall intercepted by the urban canopy layer (Ei) is a key but highly uncertain component of urban water and energy balances, with important implications for runoff generation and stormwater management. Quantifying Ei remains challenging due to the strong spatial heterogeneity of urban vegetation and impervious surfaces, as well as the difficulty in separating interception evaporation from other evaporation components during wet periods. In this study, we develop and validate a Reference-based Urban Evaporation Partitioning (RUEP) framework to quantify urban canopy interception evaporation by integrating multi-source observations with data-driven modeling. The proposed framework combines a hybrid machine learning model (HM_Ets) and a deep learning model (ML_Ei). HM_Ets is trained using dry-period observations to estimate total non-interception evaporation, including transpiration and soil evaporation (Ets), and is subsequently applied to wet periods. Interception evaporation (Ei) is derived as the residual between observed wet-period evaporation and modeled Ets, and is further simulated using ML_Ei. The framework is evaluated using multi-source datasets from an urban flux site in Vancouver, Canada, including eddy covariance flux measurements, meteorological observations, remote sensing products, and GIS-derived urban morphology data. Results demonstrate that the RUEP framework effectively reproduces both Ets and Ei dynamics, with R² values of 0.80 and 0.90 and Nash–Sutcliffe efficiencies of 0.55 and 0.81 for dry and wet periods, respectively. Event-based interception ratios (Ei/P) exhibit pronounced seasonal variability, peaking in autumn (0.47) and reaching minimum values in spring (0.09), while Ei/E ratios peak in spring (0.14) and are lowest in autumn (0.08). At the street-block scale, Ei shows strong spatial heterogeneity and a non-monotonic “high–low–high” pattern along the combined normalized difference vegetation index (NDVI) and impervious surface fraction (ISF) gradient. Areas with either high vegetation cover or large impervious fractions exhibit elevated Ei, with vegetation height further modulating Ei under high-NDVI conditions. Random forest analysis identifies wind speed, vegetation structure (NDVI and vegetation height), and precipitation characteristics as the dominant controls on urban interception evaporation. Overall, the proposed RUEP framework provides a practical approach for quantifying interception evaporation in heterogeneous urban environments, offering new insights for improving urban hydrological modeling and supporting vegetation-informed stormwater management and urban design.
How to cite: Zhou, L. and Cheng, L.: A Reference-based Urban Evaporation Partitioning framework for urban interception estimation using multi-source observations, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-9159, https://doi.org/10.5194/egusphere-egu26-9159, 2026.
Urban pluvial flooding has emerged as a critical challenge for contemporary cities, driven by rapid urbanization, ageing drainage infrastructure, and increasingly intense rainfall events. Reliable modelling of such floods is essential for risk assessment, urban planning, and mitigation strategies’ design. However, model performance is highly sensitive to input data quality, particularly topographic information governing overland flow and the description of drainage system. Despite their recognized importance, those kinds of input data are frequently selected based on availability rather than systematic evaluation, resulting in potential inaccuracies in flood predictions.
This research examines the influence of input data quality and preprocessing on urban pluvial flood simulations, with a specific focus on 1D-2D coupled modelling. An integrated modelling framework combining IBER for surface flow (2D) and SWMM for drainage dynamics (1D) is adopted to explicitly represent the interactions between overland runoff and underground drainage systems. Particular attention is given to how terrain representation affects surface–subsurface exchanges, including flow concentration, inlet efficiency, and drainage surcharge behaviour, while the drainage network system is analysed focusing solely on the primary stormwater drainage network, modelled as 137 conduit links, 3 outfall and 137 junction nodes.
The study is conducted in the densely urbanized portion of Sampierdarena district of Genoa, Italy (1.43km2), an area frequently affected by pluvial flooding. Initial simulations are performed using the 2D IBER model under controlled conditions, applying a synthetic Chicago hyetograph with a duration of 1 hour, a time-to-peak ratio of 0.5, and a return period of 10 years. This preliminary phase allows the isolation of terrain-related effects by comparing model results obtained from different digital terrain models (DTMs).
High-resolution LiDAR-derived DTMs were compared with coarser photogrammetric products and derivative datasets commonly employed in practice. Model outputs, including water depth, flow velocity, inundation extent, and overland flow pathways, are analysed both qualitatively and quantitatively. Results show that reduced terrain resolution and excessive smoothing of micro-topographic features significantly alter surface flow patterns, shift flood extents, and modify peak water depths. These effects are particularly critical in urban environments, where small-scale topographic features control flow routing toward drainage inlets and strongly influence surface–drainage interactions.
To overcome limitations inherent to purely 2D simulations, this study has advanced to a fully coupled 1D-2D IBER-SWMM approach enabling a dynamic and bidirectional exchange of water between the surface and the drainage network. This integrated framework explicitly accounts for inlet capacity, drainage surcharge, overflow locations, and the timing of interactions between streets and the underground system. As a result, the coupled model provides a more realistic representation of flood dynamics, improves identification of vulnerable infrastructure, and supports the assessment of adaptation measures such as green infrastructure, detention systems, and drainage network upgrades.
Overall, the research highlights the critical role of systematic terrain data selection and preprocessing within 1D-2D coupled urban flood models. The IBER-SWMM coupling constitutes the core methodological contribution, enhancing the physical consistency and predictive reliability of pluvial flood simulations and supporting more informed decision-making toward resilient urban flood management.
How to cite: Acquilino, M., Gnecco, I., Palla, A., Sanz-Ramos, M., Russo, B., and Boni, G.: Towards Accurate Urban Pluvial Flood Predictions: IBER–SWMM Application in Sampierdarena, Italy, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-12147, https://doi.org/10.5194/egusphere-egu26-12147, 2026.
Urban underground spaces are highly vulnerable to flooding due to their complex, multi-level configurations and limited drainage capacity. Although numerous numerical models have been proposed to simulate inundation processes in underground environments, their reliable development and application remain constrained by the lack of reference data for validating model structure and reproducibility. In particular, few studies have systematically investigated inundation behavior within the same underground space under varying inflow locations, numbers of inlets, and discharge conditions. This study presents the development of a two-dimensional surface–underground integrated flood model based on the shallow water equations, with the aim of reproducing inundation processes in complex underground spaces. The model was formulated to represent inflow, internal propagation, and drainage processes within underground spaces in a unified computational framework. Unlike conventional approaches that treat underground spaces as lumped storage elements or simplified links, the proposed model resolves underground spaces as two-dimensional hydraulic domains, allowing lateral flow propagation and spatial water-depth distributions to be explicitly simulated. Physical hydraulic experiments were employed to support model verification and to provide controlled reference conditions for quantitative evaluation. Model validation was conducted using laboratory-scale hydraulic experiments performed with the Kyoto Oike underground space facility (1/30 scale) at the Disaster Prevention Research Institute, Kyoto University. Steady-state inflow conditions were considered at 16 surface–underground connection points, including both single-inlet and sequential multi-inlet configurations. A total of 93 experimental cases were designed by applying constant inflow rates of 100, 200, and 400 mL/s while progressively increasing the number of active inlets. Final water depths, inundation extents, and dominant outflow pathways were measured after steady conditions were reached and were directly compared with numerical results under identical geometrical and boundary conditions. The comparison results demonstrate that the developed model can reasonably reproduce inundation propagation and drainage behavior within complex underground spaces under varying inflow locations, inlet numbers, and discharge levels. Through this study, a numerical model for analyzing inundation processes in complex underground spaces was developed, and the proposed model is expected to support future underground flood risk assessment and evacuation planning in urban environments.
How to cite: Song, I. and Lee, S.: Development of Complex Underground Space Inundation Model based on Laboratory Scale Experimental Data, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-3245, https://doi.org/10.5194/egusphere-egu26-3245, 2026.
Intensive groundwater extraction in Central Mexico, driven by the increasing demand from population growth, exerts significant pressure on the hydrogeological system. This has led to sustained declines in piezometric levels and a deterioration of the chemical quality of the water produced by wells all around the entire watershed. Adequate watershed management requires comprehensive information to understand its behavior.
In this regard, the objective of this work is to compile hydrogeological data for a volcanic watershed that hosts one of the world's largest cities: the Basin of Mexico. The methodology consisted of consulting, collecting, and processing various databases from the National Water Commission (CONAGUA), the National Autonomous University of Mexico (UNAM), and various technical studies.
The result is a groundwater compendium with data from 1960 to 2022, providing a technical analysis of changes in water levels and chemical composition associated with groundwater use. Additionally, it contains physiographic, edaphological, geological, and climatological information, along with lithological columns, isotopic, hydrogeological, and hydrogeochemical data. It also includes the locations of wastewater discharge sites, treatment and drinking water plants, deep wells, protected natural areas, the piezometric monitoring network, the delimitation of hydrological-administrative regions, administrative aquifer boundaries, and the delimitation of the regional flow system. Furthermore, all the data is available for visualization with a Geographic Information System (GIS).
Finally, establishing a database and a subsequent diagnosis of hydrogeological information is of vital importance. It allows for the identification of areas of opportunity to improve our knowledge of the watershed and enables the proposal and definition of necessary works, such as the construction of piezometers, water level monitoring, and chemical and isotopic analyses, among others. All these elements are highly valuable for decision-making regarding management, infrastructure construction, and monitoring.
How to cite: Martinez Casas, Z., Escolero Fuentes, O., Morales Casique, E., Olea Olea, S., Montaño Caro, J. C., Ortega Medina, P., and Blanco Gaona, S.: Strategic database for the diagnosis and prognosis of hydrogeological conditions in a highly populated volcanic watershed in Central Mexico, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-15941, https://doi.org/10.5194/egusphere-egu26-15941, 2026.
Urbanisation and climate change are driving an increase in impervious surfaces and extreme weather events, leading to water scarcity, flooding, pollution, and significant threats to river health in cities and downstream watersheds. Stormwater management and blue-green infrastructure further influence urban hydrology, while offering opportunities for mitigation and adaptation to enhance ecosystem and societal resilience in a rapidly changing world. Advancing hydrological research on the spatial and temporal dynamics of urban water quantity and quality is critical for identifying multi-scale patterns, understanding underlying processes, and providing the evidence base for targeted, scalable, and sustainable management interventions.
Against this backdrop, the NERC-NSFGEO SMARTWATER project seeks to diagnose and manage watershed-wide pollution “hotspots” (locations) and “hot moments” (times). This interdisciplinary initiative combines environmental sensing, data science, and numerical modelling to uncover the dynamic drivers of multi-contaminant pollution. Our focus here is on findings from the Birmingham Urban River Observatory, a UNESCO Intergovernmental Hydrology Programme Ecohydrology Demonstration Site within a global network applying ecohydrology principles for sustainable watershed management. The observatory employs high-frequency, in-situ water quality monitoring across low- to mid-order streams along an urban-to-peri-urban gradient.
This overview aims to reflect on five key objectives: (1) identifying and characterising pollution dynamics using scalable field diagnostic technologies, (2) developing smart water quality monitoring networks, (3) applying data science innovations (including AI) for pollution tracking, (4) leveraging high-frequency, distributed observations to improve pollution models and predictions, and (5) collaborating with stakeholders - such as citizen scientists through Birmingham River Champion - to implement practical solutions for water quality management and planetary health.
By sharing these experiences, we aim to transform how urban water challenges are diagnosed, understood, predicted, and managed.
How to cite: Hannah, D., Kelleher, L., Khamis, K., Lynch, I., White, J., Yasmin, T., Buytaert, W., Howard, B., and Krause, S. and the SMARTWATER: Urban hydrology challenges and solutions: insights from the Birmingham Urban River Observatory, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-18477, https://doi.org/10.5194/egusphere-egu26-18477, 2026.
Deep drainage tunnels face significant limitations in field-scale experimentation and high-resolution monitoring due to their structural characteristics, such as large diameters, long distances, and extreme depths. Consequently, the importance of numerical simulations for precisely evaluating sediment behavior within these tunnels is increasing. In this study, we numerically reproduced the processes of sediment transport and deposition under free-surface flow conditions using sedInterFoam, an OpenFOAM-based three-phase flow solver. Initially, the validity of the vertical-velocity and sediment-concentration profiles was established by comparison with prior hydraulic experimental data. Subsequently, the model was applied to a numerical domain based on a conceptual schematic that simplifies the overall structure of the deep drainage tunnel system. For the simulation, a representative cross-section was established with a top width (B) of 0.60 m and a depth-to-width ratio (H/B) of 4. A total of 27 scenarios were configured, using flow rate, inflow sediment concentration, and invert cross-sectional shapes (U-shaped, trapezoidal, and base-type) as design variables, to perform a sensitivity analysis of their impact on sediment management efficiency (η manage). The efficiency index (η manage) was defined as the ratio of the sum of the mass discharged at the tunnel outlet (M outlet) and the mass captured in the sump (M sump) to the total sediment mass entering the system (M inflow). The results indicated that, compared with the base section, both the U-shaped and trapezoidal sections facilitated the formation of a continuous low-velocity zone at the center of the invert, resulting in a thick central sediment bed and stable capture performance. Furthermore, the sensitivity analysis revealed that the cross-sectional shape is the most dominant factor influencing variations in sediment management efficiency. These findings provide a quantitative basis for selecting optimal cross-sectional geometries and dimensions during the design phase of deep drainage tunnels. They are expected to contribute to the establishment of proactive maintenance strategies during the operational phase.
Keywords: Deep stormwater drainage tunnel, Sediment management efficiency, SedInterFOAM, Multiphase flow
Acknowledgement: This work is financially supported by Korea Ministry of Climate, Energy, Environment(MCEE) as 「Technology development project to optimize planning, operation, and maintenance of urban flood control facilities)(RS-2024-00397821)」.
How to cite: Lee, Y., Jeong, C., Kim, K., and Lee, S.: Sensitivity Analysis of Sediment Deposition Characteristics and Management Efficiency in Deep Drainage Tunnels Based on Invert Geometries Using OpenFOAM , EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-15097, https://doi.org/10.5194/egusphere-egu26-15097, 2026.
In contemporary urban planning, infrastructure plays a decisive role in shaping the resilience, sustainability, and economic performance of cities. However, the urban planning discipline has conventionally lacked optimization-based frameworks for analyzing and operating these infrastructures. Instead, many studies have relied predominantly on AI or statistical pattern-recognition approaches that capture observable phenomena but often fail to reveal the underlying causal mechanisms. With the increasing diversity of operational data and the rapid evolution of computational capabilities, research that relies solely on empirical patterns is no longer sufficient for addressing the complexities of modern urban systems.
Water resource infrastructure is a prime example representing one of the largest electricity consumers in the public sector, yet much of the existing literature continues to depend on management of the conventional resources. In modern era, the scope of operable resources is far broader than pumps and treatment facilities alone. Renewable energy sources, battery energy storage, and even emerging hydrogen-based power systems increasingly interact with water infrastructure operations.
Given these expanded resource portfolios and the growing importance of electricity markets, urban infrastructure systems must be planned and operated through integrated, optimization-driven frameworks that recognize cross-sectoral coupling. Moreover, the scheduling horizon and operational logic of water and energy systems should be aligned with the temporal structures of electricity markets, enabling cities to capitalize on price signals, reduce operational costs, and enhance flexibility. Such a paradigm shift from isolated empirical decision-making to comprehensive optimization based on physics, economics, and system interactions, is essential for building next-generation climate-resilient and energy-efficient urban environments.
The study focuses on cost-optimization of a reconstructed water resource network of the city of Seongnam, developed using publicly available municipal data. The system serves a population of 943,676 and is supplied through an integrated metropolitan–local water network comprising 17 distribution reservoirs, 31 pumping stations, 140 pumps, 2 small hydropower generators, 2 photovoltaic generators, 1 battery energy storage system postulated, multiple intake stations and treatment facilities equipped with Oz-GAC and rapid filtration. Distances among facilities, stations and reservoirs were measured as straight-line distances using Google Earth, based on publicly provided GIS coordinates. The operational framework incorporates a MILP-based optimization model that explicitly accounts for operational delays through piecewise-linear flow representations, enabling time-dependent scheduling in the system.
How to cite: Lee, J.: Integrated Optimization of Urban Water–Energy Infrastructure Operations in a Metropolitan-Scale Network, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-1405, https://doi.org/10.5194/egusphere-egu26-1405, 2026.
Combined sewer overflows (CSOs) are a major source of untreated wastewater discharge into urban water bodies during periods of excess flow, posing significant environmental and public health risks. Using approximately four million CSO spill events recorded by Event Duration Monitors across England (2020-2024), we analyze the statistical distribution of spill durations to better understand the stresses applied to urban watersheds from CSOs. Our results reveal a strongly heavy-tailed distribution: while spills exceeding two hours represent only ~10% of events, they account for ~85% of total spill time, indicating potentially disproportionate ecological impact from long-duration spills. Likelihood ratio tests confirm that this distribution is best described by a stretched exponential (Weibull) model with a shape parameter of 0.15, a finding consistent across multiple subsettings of our dataset. Periodic deviations from this trend correspond to diurnal water-use cycles, with elevated probabilities of a spill lasting near integer multiples of 24 hours. Hydraulic modeling reproduces the observed heavy tail only when groundwater infiltration is included, suggesting that prolonged spills are primarily driven by infiltration into sewer networks rather than extreme precipitation. Furthermore, we show that the observed scaling can be approximated statistically by first passage times of a sewer head modeled as fractional Brownian motion. Given the outsized environmental impact of long-duration spills, we recommend incorporating tail behavior explicitly into hydraulic model calibration and propose using stretched exponential parameters as robust metrics for CSO performance assessment.
How to cite: Lipp, A. and Dobson, B.: A heavy tailed distribution for Combined Sewer Overflow spill durations driven by infilitration, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-8016, https://doi.org/10.5194/egusphere-egu26-8016, 2026.
Urban areas are characterised by continuous emissions of particulate matter from multiple anthropogenic sources, which accumulate mainly on impervious surfaces such as roads, parking areas, and rooftops. During precipitation events, especially extreme rainfall, these accumulated contaminants can be mobilised and redistributed throughout the urban water cycle. This study examines contaminant mass balance and redistribution during extreme precipitation at the scale of the urban water cycle in the regional pilot-case aquifer. Understanding these processes is essential for evaluating the effectiveness and long-term risks of infiltration-based stormwater management.
A multi-compartment sampling strategy is being implemented within an urban catchment to capture the key reservoirs and fluxes governing contaminant transfer within the system. Precipitation is sampled to characterise atmospheric washout, while street dust serves as an integrated record of contaminant accumulation on impervious surfaces. Surface runoff from sealed areas is monitored at gully pots, followed by sampling of water percolating through infiltration and filtration layers of the stormwater retention system. Groundwater quality is statistically evaluated at selected monitoring wells to assess aquifer response. In parallel, recharge inputs from the aquifer hinterland, including river infiltration, are characterised to constrain background groundwater conditions.
Water samples are being analysed for physicochemical parameters and dissolved contaminants, while solid phases from precipitation, runoff, and dust are chemically, mineralogically, and morphologically characterised to identify dominant particulate contaminant carriers. These datasets provide the basis for developing a conceptual mass-balance model describing contaminant transfer across the air–surface–soil–groundwater continuum.
Preliminary results indicate that a substantial fraction of contaminants mobilised during rainfall events is initially retained within soils and filtration media, thus limiting direct transfer to groundwater. However, this retention capacity is finite and strongly depends on contaminant loads, soil properties, and hydrological conditions. In areas affected by spatially localised industrial hotspots, extreme precipitation and associated leaching processes may act as effective triggers for contaminant release and downward transport once storage capacities are exceeded. These findings highlight the need to determine when soils and infiltration systems serve as effective buffers and when they facilitate contaminant transfer. This distinction is critical for evaluating the long-term performance of infiltration-based urban water management strategies and assessing groundwater vulnerability under climate change–related extreme precipitation regimes.
How to cite: Svetina, J., Prestor, J., Gaberšek, M., and Gosar, M.: Urban Water Cycle Responses to Extreme Precipitation: Contaminant Mass Balance, Redistribution, and Transfer to Groundwater, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-8995, https://doi.org/10.5194/egusphere-egu26-8995, 2026.
The Hsintien River is a major watershed for water supply in Northern Taiwan, where high population density and urbanization have led to a complex water environment. Therefore, this study aims to develop a water environment resilience assessment framework applicable to Taiwan by integrating "Water Quality–Quantity–Social Nexus" to examine long-term resilience changes. The results show that upstream resilience is mainly influenced by flow conditions, whereas downstream resilience is constrained by high population density and pollution base loads, leading to insufficient dilution effects. Using the extreme drought event of 2020–2021 as a case study, shows that while the upstream reach maintained a stable recovery of resilience, the downstream reach failed to exhibit resilience due to increased ammonia nitrogen (NH₃–N) concentrations resulting from diminished self-purification. In highly urbanized river reaches, observed resilience patterns are not fully explained by flow conditions alone but are also influenced by pollution pressures associated with urbanization.
How to cite: Chang, L.-W., Chang, C.-L., and Chen, S.-T.: Assessment of Urban Water Environment Resilience and Vulnerability: Hsintien River Watershed in Taiwan, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-10622, https://doi.org/10.5194/egusphere-egu26-10622, 2026.
Urban pluvial flood prediction demands rapid operational response while maintaining street-scale realism amid strong urban heterogeneity and uncertain forcings. We present a suite of hybrid physics–AI developments that address this trade-off through complementary components designed for flexible coupling and discussion. First, multi-GPU-accelerated hydrodynamic modeling reduces latency, enabling city-scale, high-resolution scenario exploration. Second, to exploit sparse and heterogeneous observations (e.g., gauges and camera-derived depths), we introduce real-time data assimilation methodologies, such as particle filtering, and multivariate geostatistical data fusion via co-kriging. The latter translates limited measurements and auxiliary covariates into spatially distributed, uncertainty-aware inundation updates. In parallel, we introduce AI surrogates to complement physical modeling: a rapid emulator trained on high-fidelity physics simulations and deep-learning super-resolution methods that bridge the scale gap between coarse forcings and street-level impacts. We conclude by discussing alternative deployment pathways for these components, evaluating key trade-offs among speed, physical consistency, observational influence, and robustness under extreme events.
How to cite: Noh, S. J., Kim, B., Choi, H., Woo, H., Lee, Y., and Choi, J.: Hybrid Physics-AI Approaches for Urban Flood Prediction: GPU Hydrodynamics, Data Assimilation, and AI Surrogates, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-19955, https://doi.org/10.5194/egusphere-egu26-19955, 2026.
Water scarcity has emerged as one of the most pressing issues in Central Asia, driven by climate change, transboundary water issues, rapid population growth, and escalating demands on limited water resources. For the Republic of Kazakhstan, water security has become a critical aspect of national security, recognised as early as 2003 and becoming more urgent from year to year. Despite an estimated renewable water resource potential, Kazakhstan faces significant water scarcity, particularly in the southern regions, due to uneven distribution, excessive water withdrawal for irrigation, and climatic variability. This research aims to assess the challenges in water resources management in Almaty, the primate city of Kazakhstan, using the DPSIR-MCDA approach. The DPSIR assessment of Almaty’s urban water system indicates that climate change, rapid demographic expansion, urbanization, and infrastructure underinvestment are primary drivers, generating pressures such as altered glacial runoff, variable groundwater recharge, rising consumption, and severe infrastructure deterioration. These pressures have degraded the system’s state, resulting in unstable water availability, high distribution losses, and unequal access to centralized services in peri-urban areas. The analysis indicates that effective responses must include adaptive abstraction strategies, large-scale infrastructure rehabilitation, expansion of water reuse and circular systems, and targeted PPP-based development for underserved districts. To prioritise these measures from the perspective of sustainability factors (economic, environmental, social, and technological), two respective questionnaires were developed and distributed among twenty-six experts: experienced academicians in the urban water management and local representatives. The outcomes were assessed using the hybridised versions of DEMATEL-ANP as a tool for MCDA. The results showed that the measure focusing on the implementation of Circular Economy principles received the highest total weighted score, demonstrating strong performance, particularly in the technological dimension, and a relatively balanced influence across the others. The measure of tariffs' modification and strengthening control mechanisms for water users followed closely, primarily driven by its dominant performance in the economic dimension. Awareness-raising initiatives ranked third, demonstrating particular strength in the social dimension, whereas water use diversification ranked fourth with a more even distribution across dimensions. The engaging independent private enterprises received the lowest composite score, suggesting weaker alignment with environmental and social sustainability. The study concludes that delivering water supply and sanitation services in a more sustainable, inclusive, efficient, and resilient manner requires technologically advanced solutions and proper governance response.
How to cite: Baubekova, A., Radelyuk, I., and Khaibullina, Z.: Sustainability assessment of Almaty urban water management using DPSIR-MCDA approach , EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-545, https://doi.org/10.5194/egusphere-egu26-545, 2026.
Urban and industrial wastewater often contains high concentrations of heavy metals, which are among the most harmful pollutants due to their toxicity, persistence, and negative effects on both biological systems and human health. This study investigates the efficiency of Co and Ni removal from aqueous solutions using synthetic Mg-carbonates produced through a CO₂-mineralization process, in which anthropogenic CO₂ reacts with MgCl₂ solutions. The open-high reactive structure of amorphous magnesium carbonates (AMCs) promotes rapid Co/Ni uptake through adsorption and ion-exchange mechanisms, offering a low-energy and sustainable remediation strategy for contaminated urban and industrial effluents. Batch experiments were conducted using Co and Ni solutions from 50 to 1000 mg/L, reacted with 0.1 g of AMCs for interaction times ranging from 20 minutes to 4 weeks at ambient pressure and temperature. The residual solutions were analyzed by ICP-AES to quantify removal efficiency and Mg release, whereas solid products were examined using SEM-EDS and XRPD to assess morphological and mineralogical transformations. The Co removal experiments provided a coherent dataset across analytical techniques and revealed a critical threshold of ~250 mg/L, marking the transition between two distinct removal regimes. Below the concentration 50–150 mg/L, morphological transformation is rapid and highly efficient, with AMC dissolution and reprecipitation as Co-carbonates occurring within a few hours and removal efficiencies reaching up to ~99% after four weeks. At concentrations ≥250 mg/L, removal remained significant (up to ~75%) but was characterised by slower kinetics and incomplete equilibrium within the experimental time. The correlation between the moles of Co removed and Mg released showed that at short times (0–3 h) the process was dominated by adsorption on AMC surfaces, whereas at longer times (24 h–4 w) ion exchange progressively prevailed, leading to nearly 1:1 Co–Mg stoichiometry. The transition between these mechanisms occurred earlier at higher Co concentrations. XRPD data confirmed structural reorganisation and the precipitation of new Co-bearing carbonate phases throughout the process. Preliminary Ni experiments indicate comparable trends, confirming that AMCs exhibit similar reactivity and removal mechanisms toward both metals. Overall, these results show that CO₂-derived synthetic Mg-carbonates offer an effective, low-energy and scalable solution for Co and Ni removal from contaminated waters, with clear relevance for urban and industrial water management. Their reactivity and sustainability, combined with the strategic value of Co and Ni as critical raw materials, highlight the potential of this approach for future resource-recovery applications.
How to cite: Sbardella, G., De Vito, C., Ballirano, P., Paciucci, M., and Mignardi, S.: Cobalt and nickel removal from urban and industrial wastewaters using sustainable synthetic carbonates, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-9068, https://doi.org/10.5194/egusphere-egu26-9068, 2026.
Due to recent climate change, urban flood damage is increasing. Current urban flood prediction has been mainly conducted by performing numerical simulations for various return period scenarios and producing inundation maps based on the results. However, this method has disadvantages in that it is difficult to predict arbitrary rainfall events or intermediate frequencies that can occur other than the fixed scenarios, and it is difficult to respond in real-time because the computation time of numerical simulations is significantly long. Therefore, to overcome these challenges, this study developed a 'scientific interpolation method' to estimate urban inundation maps for arbitrary frequencies by leveraging pre-constructed flood scenario data. We utilized simulation results from a self-developed Python-based urban flood model as a benchmark to derive the fundamental governing equations and related parameters. An Inverse Analysis technique was applied to mathematically reconstruct the non-linear relationship between rainfall frequency and inundation depth. Consequently, the inundation depths and extents for arbitrary frequencies interpolated through the derived equations showed a high spatial correlation with the physics-based model results with R2= 0.9. By integrating discrete scenario maps through this interpolation scheme, the proposed method enables rapid flood prediction without the need for repetitive numerical simulations. This approach is expected to significantly enhance the capability for immediate decision-making and response against sudden urban flood disasters.
How to cite: Kim, J., Song, S., Kim, K., and Lee, S.: Development of Scientific Interpolation Method for Urban Inundation Maps of Arbitrary Return Periods Based on Pre-Simulated Scenarios, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-15412, https://doi.org/10.5194/egusphere-egu26-15412, 2026.
Urbanization is a vital catalyst for socio-economic development in developing countries, such as India. However, rapid and poorly planned urban expansion has resulted in increased vulnerability to flooding during heavy rainfall. Stormwater drainage (SWD) systems emerge as cost-effective solutions to mitigate these challenges. Many major Indian cities, including Chennai, are situated in coastal and riverbank areas. During intense rainfall in upstream catchments, rivers carry significant water to the coastal areas of the city, challenging SWD systems to efficiently discharge water at outlet points. Complicating matters, the occurrence of surges from cyclonic effects in the sea further impedes river water transport. Consequently, urban areas experience prolonged flooding due to the compound effects of multiple drivers. This study evaluates the performance of the SWD system subjected to multiple flood drivers in the coastal part of Chennai city using the freely downloadable HEC-RAS model. The assessment encompasses pluvial, fluvial, and storm surge-induced flooding scenarios. The hydrological component of the model computes runoff from the watershed, which is then input into a one-dimensional (1D) stormwater model. To address compound flooding, the 1D model is coupled with a two-dimensional (2D) hydraulic routing model, enabling the management of junction overflows onto urbanized floodplains and simulating overland flows from floodplains into junctions. The comprehensive investigation not only enhances our understanding of the effectiveness of SWD during flooding but also provides valuable insights for decision makers. The study informs decisions related to resizing or expanding the proposed SWD infrastructure, ultimately contributing to improved flood preparedness and resilience in the urban landscape.
How to cite: Pradhan, P. R. and Kuiry, S. N.: Performance Evaluation of Stormwater Drainage System Subjected to Multiple Flood Drivers, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-13132, https://doi.org/10.5194/egusphere-egu26-13132, 2026.
Urbanization leads to the conversion of pervious surfaces into impervious surfaces, significantly altering the hydrological conditions of urban catchments. These changes adversely affect the conveying capacity of urban drainage systems, resulting in increased overflow and eventually increase urban flooding risk. This study aims to assess the impact of imperviousness on rain induced urban flooding and to evaluate the effectiveness of (NbS) in improving runoff management using advanced modeling techniques for a neighborhood of the Trento Municipality (Italy). To achieve these objectives, 1D/2D hydrodynamic modeling approaches was applied to simulate the runoff generation, its routing within the designed drainage system and the flooding propagation on the study area. Within the 19 sub-catchments experiencing flooding under existing conditions and extreme rainfall events, NbS, specifically green roof and bio-retention cell were applied to manage runoff.Results demonstrate the capability of the proposed NbS to reduce flooded areas, runoff volume by mimicking natural processes (i.e., delaying runoff time and promoting infiltration). Reducing the imperviousness of the study area by 6% provides a reduction of the flooded area and runoff volume by 40% and 50%, respectively.Overall, the findings confirm that increasing NbS coverage significantly enhances urban drainage efficiency and mitigates urban flooding, highlighting the importance of sustainable urban planning and green infrastructure strategies for effective flood management.
How to cite: Abbas, G., Marzadri, A., and Formetta, G.: Evaluating the Influence of Imperviousness on Urban Runoff and Drainage System Efficiency, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-14413, https://doi.org/10.5194/egusphere-egu26-14413, 2026.
Posters virtual: Fri, 8 May, 14:00–18:00 | vPoster spot A
EGU26-8965 | ECS | Posters virtual | VPS11
Impact of Organoclay Content on Hydraulic Performance of Filter Strips to Treat Urban RunoffFri, 08 May, 14:42–14:45 (CEST) vPoster spot A
Impact of Organoclay Content on Hydraulic Performance of Filter Strips to Treat Urban Runoff
Yaren Ozturk 1, Derya Ayral Cınar 2
1 Marmara University, Istanbul, Turkiye
2 Gebze Technical University, Kocaeli, Turkiye
Abstract.
Due to urbanization and climate change, it has become common for urban runoff to carry pollutants to surface water bodies, wastewater treatment plants, infrastructure systems and groundwater. Pollutants transported include heavy metals, solids, nutrients, pathogens and various organic substances such as pesticides and polycyclic aromatic hydrocarbons (PAH). It is proposed to manage this pollutant load at source before it reaches receiving environments. Nature-based solutions such as filter ditches, infiltration ponds or rain gardens are considered more efficient to manage urban runoff. Among these methods, filter ditches have the highest potential to treat pollutants. It is thought that the use of organoclays, synthesized by the integration of surfactants into the clay mineral structure, as filter material may increase a common contaminant in urban runoff -PAH- removal compared to conventional clay minerals. In addition to treatment efficiency, another important parameter in designing filter ditches is the hydraulic permeability of the filter material. It is desirable that the infiltration rate of the surface flow is slow enough to allow time for pollutant removal and fast enough to prevent ponding on the filter. This study investigated how organoclays, which are proposed to enhance PAH removal from urban runoff, affect the hydraulic permeability of the filter material. Organoclay synthesized by Ca-montmorillonite and HDTMA is used at different percentages in the filter material mixture and hydraulic permeability was determined. Hydraulic conductivity of sand was 4.5x10-4 cm/s and it dropped to 2.4x10-5 cm/s and 2.3x10-5 cm/s when 10% and 20% clay was used, respectively. On the contrary, organoclay at 10% and 20% did not decrease the hydraulic conductivity significantly (to 1.5x10-4 cm/s and 1.4x10-4 cm/s, respectively). As hydraulic conductivity is suggested to be 0.3-1.4 x 10-4 cm/s for surface runoff treatment systems, it appeared that using 20% organoclay is promising to treat emerging pollutants such as PAHs without comprimising the hydraulic performance of the filter system.
Keywords: Nature based solutions, urban runoff, climate change, filter strips, organoclay
How to cite: Ozturk, Y. and Ayral Cınar, D.: Impact of Organoclay Content on Hydraulic Performance of Filter Strips to Treat Urban Runoff, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-8965, https://doi.org/10.5194/egusphere-egu26-8965, 2026.
EGU26-15359 | ECS | Posters virtual | VPS11
Applicability of distributed thermal sensing for identifying illicit sewage connections in urban drainage networks under tropical climatesFri, 08 May, 14:45–14:48 (CEST) vPoster spot A
Urban water pollution remains a major challenge for sanitation management in Brazil and other tropical regions. In areas served by separate sewer systems, illicit domestic sewage connections to stormwater drainage networks represent a significant source of contamination of urban runoff and receiving water bodies. Conventional inspection techniques for identifying such contributions are often operationally complex, spatially limited, and therefore rarely applied. Distributed temperature sensing techniques have been successfully used in temperate regions to detect sewage inputs based on thermal contrasts; however, their applicability under tropical conditions remains poorly explored.
This study investigates the thermal signature of domestic sewage in a tropical urban environment and evaluates the detectability of illicit sewage discharges in stormwater systems using a simplified thermal mixing model. Sewage temperature was monitored using thermocouples connected to a data logger with 1-minute temporal resolution in a sewer interceptor located at the São Carlos School of Engineering, University of São Paulo, Brazil, in an area characterized by student housing and food service facilities. Two monitoring campaigns were conducted. Mean sewage temperatures of 27.45 ± 0.45 °C (November 2024–April 2025) and 24.21 ± 0.54 °C (September–November 2025) were observed. A moderate Pearson correlation between sewage temperature and local air temperature (r = 0.58, p < 0.05, n = 140) indicates that atmospheric conditions partially influence sewage thermal variability.
Based on the monitored sewage temperatures (T₂) and stormwater temperature data (T₁) from the literature, a preliminary theoretical model was developed using an instantaneous energy balance approach. The model relates the detectable temperature variation (ΔT) to the sewage fraction (f), defined as the ratio between sewage discharge (Q₂) and stormwater flow (Q₁). Results indicate an exponential relationship between f and ΔT for different thermal contrasts (T₂ − T₁). The minimum detectable sewage discharge was found to be highly sensitive to ΔT, associated with the thermal resolution of the sensing system, while showing direct proportionality to stormwater flow and inverse proportionality to the thermal contrast between sewage and runoff. Future work will focus on model validation under field conditions and its extension to non-stationary flow regimes.
How to cite: de lima neto, E., Bertotto, L. E., and Wendland, E. C.: Applicability of distributed thermal sensing for identifying illicit sewage connections in urban drainage networks under tropical climates, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-15359, https://doi.org/10.5194/egusphere-egu26-15359, 2026.
