Urban Hydrology Research Articles

Performance of low impact development on peak flow reduction in an urban system

AbstractThis study proposes an approach to evaluate the efficiency of low impact development (LID) in reducing urban runoff using a rainfall generator to disaggregate daily rainfall into sub‐hourly rainfall data, which are used as input of a hydrological model at the urban watershed scale. Twelve scenarios are analyzed combining four percentages of impervious area retrofitted with LIDs (25%, 50%, 75% and 100%), and three LID combinations of green roofs (GRs) and rain gardens (RGs). The rainfall generator Rainsim V.3 is used to generate 500 years of rainfall data with a 15‐min time step to analyze the performance of LIDs in the long‐term with the LID module of the Soil and Water Assessment Tool hydrological model. An urban watershed of 3 km2 located in Florence (Italy) is selected as a case study. Results show the performances of GRs and RG on peak flow reduction, highlighting a maximum flow reduction of single facilities ranging between 15% and 60% that can improve in case of their combination. The hydrological performances of LID combinations are very sensitive to the intensity of rainfall events, as well as percentages of area treated underlining the importance of simulating multiple scenarios of intervention to determine the most efficient combination of LIDs for a given case study and support their proper design from a urban water hydrology perspective.

The δ18O and δ2H fingerprint of the Scioto River: A detailed look into seasonal and spatial variations in the context of Ohio rivers

The global expansion and increased intensity of the human footprint causes modification of natural freshwater systems, particularly in densely populated areas. This poses a challenge for society where the water systems that humans rely on for domestic, industrial, and agricultural water are also the most physically and chemically disturbed. There is an urgent need to study hydrologic processes in surface water systems that flow through human-altered landscapes to better manage freshwater resources. Stable water isotopes (δ18O and δ2H) can be used as natural tracers to study the hydrologic patterns of rivers as they flow through these agricultural and urban landscapes. In this work, we investigate the seasonal and spatial hydrologic patterns of the Scioto River in Ohio, USA by analyzing stable water isotopes. Samples were collected over the course of one year (2021) from five locations that transition from intense agriculture to the metropolitan area of Columbus, Ohio. Results show that the Scioto River isotopic composition reflects a dampened seasonal precipitation pattern, where δ18O and δ2H are enriched in summer and depleted in winter. Scioto River transect patterns show that there was greater variability in stable isotopic composition in the upstream, agricultural reaches of the river. As the river flowed through the metropolitan Columbus area two “river-like” reservoirs generated isotopic homogenization along the Scioto without inducing isotopic enrichment, which is commonly observed from evaporation in river-reservoir systems. The Scioto River was put in context with other major Ohio river systems, to show the variability across the state. Isotopic composition differences among and within river systems across the state were induced by a combination of different environmental factors, like precipitation and river baseflow contribution. They were further affected by humans through land use modification and the constructions of dams and reservoirs. Overall, this study underlines the influence that urbanization and intensive agriculture have on rivers. In the context of the current hydrologic changes induced by climate change, this work emphasizes the importance of studying urban river hydrology in the context of joint climatic and human influences.

Stormwater reuse for water-sensitive city - Integrated analysis of urban hydrology for efficient alternatives of Amaravati city, India.

In the present study, Amaravati, a proposed city of Andhra Pradesh, India, is identified for stormwater reuse analysis and for various efficient options for reuse. Peak runoff from the entire catchment is determined for the management of stormwater using different models such as soil and water assessment tool (SWAT), stormwater management model, and intensity-duration-frequency curves by the log Pearson Type III method. Further, the bio-retention cell low-impact development option with 60% impervious area, 60% zero depression impervious area, bio-retention cell for 40% area for each sub-catchment, and the underground stormwater network system, for part of peak runoff reduction, remaining peak runoff is considered for reuse. The remaining peak runoff is proposed to be reused for irrigation purposes (option 1), and storage retention ponds as extended detention ponds (option 2). Also, in situ storage/percolation is recommended for unaccounted stormwater within or around each premise. The findings can help to propose, implement, and maintain various stormwater reuse measures and/or practices for any city.

Detection of Urban Flood Inundation from Traffic Images Using Deep Learning Methods

Urban hydrological monitoring is essential for analyzing urban hydrology and controlling storm floods. However, runoff monitoring in urban areas, including flood inundation depth, is often inadequate. This inadequacy hampers the calibration of hydrological models and limits their capacity for early flood warning. To address this limitation, this study established a method for evaluating the depth of urban floods using image recognition and deep learning. This method utilizes the object recognition model YOLOv4 to identify submerged objects in images, such as the legs of pedestrians or the exhaust pipes of vehicles. In a dataset of 1,177 flood images, the mean average precision for water depth recognition reached 89.29%. The study also found that the accuracy of flood depth recognition by YOLOv4 is influenced by the type of reference object submerged by the flood; the use of a vehicle as the reference object yielded higher accuracy than using a person. Furthermore, image augmentation with Mosaic technology effectively enhanced the accuracy of recognition. The developed method extracts on-site, real-time, and continuous water depth data from images or video data provided by existing traffic cameras. This system eliminates the need for installing additional water gauges, offering a cost-effective and immediately deployable solution.

Integrating the Spatial Configurations of Green and Gray Infrastructure in Urban Stormwater Networks

AbstractGreen infrastructure (GI) practices improve stormwater quality and reduce urban flooding, but as urban hydrology is highly controlled by its associated gray infrastructure (e.g., stormwater pipe network), GI's watershed‐scale performance depends on its siting within its associated watershed. Although many stormwater practitioners have begun considering GI's spatial configuration within a larger watershed, few approaches allow for flexible scenario exploration, which can untangle GI's interaction with gray infrastructure network and assess its effects on watershed hydrology. To address the gap in integrated gray‐green infrastructure planning, we used an exploratory model to examine gray‐green infrastructure performance using synthetic stormwater networks with varying degrees of flow path meandering, informed by analysis on stormwater networks from the Minneapolis‐St. Paul Metropolitan Area, MN, USA. Superimposed with different coverage and placements of GI (e.g., bioretention cells), these gray‐green stormwater networks are then subjected to different rainfall intensities within Environmental Protection Agency's Storm Water Management Model to simulate their hydrological benefits (e.g., peak flow reduction, flood reduction). Although only limited choices of green and gray infrastructure were explored, the results show that the gray infrastructure's spatial configuration can introduce tradeoffs between increased peak flow and increased flooding, and further interacts with GI coverage and placement to reduce peak flow and flooding at low rainfall intensity. However, as rainfall intensifies, GI ceases to reduce peak flow. For integrated gray‐green infrastructure planning, our results suggest that physical constraints of the stormwater networks and the range of rainfall intensities must be considered when implementing GI.

Infiltration performance evaluation of a 15-year-old concrete grid paver parking area (Italy)

Abstract The management of urban stormwater needs a wide array of environmentally friendly solutions to safeguard water resources and improve the quality of the urban environment. In that, permeable pavements, a type of sustainable drainage system, are designed to reduce the volume and peak flow of stormwater on-site, improve infiltrating water quality, and combat the urban heat island phenomena. In this study, we tested the infiltration capacity of 15-year-old concrete grid pavers (CGPs) using single ring infiltrometer tests. We investigated how various factors, including location within the parking space, affect infiltration rates. Despite no maintenance and 15 years of operation, the infiltration capacity of the CGPs still exceeds the minimum infiltration capacity of 1.62 mm/min as required in many European regions. This may be due to the presence of soil cracks and the development of plant roots and insect/microorganism activities within the pavement voids. Indeed, this ‘living soil system’ continuously develops and counteracts the formation of clogging, interacting with the compaction process. Our study demonstrates that incorporating CGPs is effective in addressing emerging challenges associated with urban hydrology. Due to effectiveness and limited maintenance requirements, CGPs could be successfully included in long term climate adaptation measures.

Improved urban runoff prediction using high-resolution land-use, imperviousness, and stormwater infrastructure data applied to a process-based ecohydrological model.

Modeling large-scale hydrological impacts brought about by site-level green and gray stormwater remediation actions is difficult because urbanized areas are extremely complex dynamic landscapes that include engineered features that, by design, expedite urban runoff to streams, creeks, and other water bodies to reduce urban flooding during storm events. Many urban communities use heavily engineered gray infrastructure to achieve that goal, along with more recent additions of green infrastructure such as rain gardens, bioswales, and riparian corridors. Therefore, successfully characterizing those design details and associated management practices, interactions, and impacts requires a detailed understanding of how fine and course-scale hydrologic processes and routing are altered and managed in urban watersheds. To enhance hydrologic modeling capabilities of urban watersheds, we implemented a number of improvements to an existing ecohydrology model called VELMA-Visualizing Ecosystem Land Management Assessments-including the addition of spatially explicit engineered features that impact urban hydrology (e.g., impervious surfaces, curbed roadways, stormwater routing) and refinement to the computational representations of evapotranspiration by adding impervious surface evaporation. We demonstrate improved capabilities for modeling within complex urbanized watersheds by simulating stream runoff within the Longfellow Creek watershed, City of Seattle, Washington (WA), United States (US) with and without these added urban watershed characteristics. The results demonstrate that the newly improved VELMA model allows for more accurate modeling of hydrology within urban watersheds. Being a fate and transport ecohydrology model, the improved hydrologic flow enhances VELMA's current capacity for modeling nutrient, contaminant, and thermal loadings.

Stronger control of surface conductance by soil water content than vapor pressure deficit regulates evapotranspiration in an urban forest in Beijing, 2012–2022

With urbanization rapidly increasing, evapotranspiration (ET) in urban forests plays an increasingly important role in urban hydrology and climate. However, large uncertainty remains regarding the regulating factors of ET in urban area. Using the eddy-covariance technique, we investigated the temporal variations of ET in an urban forest park in Beijing for 2012–2022. Daily ET was close to zero during winter and reached 3–6 mm day−1 in summer. Daily ET increased with vapor pressure deficit (VPD) and soil water content (SWC). When binning daily data into 10 bins according to percentiles of either SWC or VPD, surface conductance (gs) increased with SWC for all VPD bins, but showed weak responses to VPD for SWC bins. Monthly ET increased linearly with normalized difference vegetation index, showed a strong correlation with gs, and exhibited saturated responses to increasing monthly precipitation (PPT). Annual ET ranged from 326 to 566 mm (with the eleven-year mean of 428.66 ± 83.83 mm; mean±SD), and varied from 55 % to 148 % of annual PPT. Aggregated ET over the eleven years (4715 mm) accounted for 82 % of the aggregated PPT. Soil water replenishment through PPT from mid-summer to late autumn of the previous year was responsible for the generally higher monthly ET in spring relative to PPT, resulting in a weak correlation between annual ET and PPT in the same calendar year (R2= 0.28). The PPT in the early growing season partly promoted annual ET through its effect on summer gs. Our results suggest that biotic factors and PPT seasonality played an essential role in regulating ET at the seasonal and interannual scales, respectively. Soil dryness imposed additional constraints on gs at the finer timescale (i.e., days). Urban land-surface models should adequately address the soil moisture carryover effect to improve simulations.

Changes in the Urban Hydrological Cycle of the Future Using Low-Impact Development Based on Shared Socioeconomic Pathway Scenarios

Representative Concentration Pathway (RCP) scenarios have been used for various studies in the field of climate change. In this regard, the Shared Socioeconomic Pathway (SSP) scenario has been newly introduced to examine climate change impacts, but relevant research is still insufficient. For this reason, new SSP scenarios with a combination of Low-Impact Development (LID) techniques are applied to predict rainfall-runoff efficiency and hydrological variation. The inter-model variability in the monthly average precipitation for each GCM according to new SSP scenarios under future climate was investigated. Based on the RCP 4.5 and RCP 8.5 scenarios, the results show precipitation changes with an increase of 4.8% and 12.3%, respectively. Furthermore, precipitation projections under SSP2-4.5 and SSP5-8.5 scenarios are predicted to increase by 13.9% and 20.6%, respectively, indicating that the magnitude of precipitation increases with new climate change scenarios. The Storm Water Management Model (SWMM) during the future period indicated that LID applications will reduce runoff compared with scenarios with no LID application. In particular, the introduction of permeable pavement and infiltration trenches revealed the best runoff reduction performance among the combinations of LID techniques considered. In addition, this study projected changes in the urban hydrological cycle for the climate over the next 30 years to reflect the implementation of urban hydrological cycle plans, which take approximately 10 years. Overall, it was found that, in the future, LID applications will contribute to improving the sustainability of the urban hydrological cycle of the study area. The results of our study can provide future directions for water management strategies in Korea.

The heat is on: Predicting urban stream temperature responses to summer storms

AbstractShort‐term increases in stream temperature in response to storm events have frequently been observed in urban areas, highlighting the need for improved understanding of the factors influencing urban stream temperature. Urban land cover complexity and infrastructure designed for rapid water routing to the sewer system create a direct link between storm events and water release processes, influencing urban stream temperature responses. This study aims to identify predictors of diverse stream temperature response patterns to summer storms. We analysed 403 storm events from six urban and semi‐urban catchments along the US East Coast using dynamic time warping to identify archetype patterns of stream temperature responses. We further disentangled observed stream temperature increase patterns to reveal the drivers associated with ‘heat pulses’, which are characterized by a rapid but high‐magnitude temperature increase followed by a sharp temperature drop at the start of the hydrograph increase. Our results show that stream temperature patterns were event‐specific and linked to pre‐event conditions and rainfall–runoff characteristics, with the shape of the hydrograph and rainfall–runoff response identified as the most important determinators of the observed temperature response patterns. Ponded surface waters and storm drains, as well as cooler water from the shallow subsurface, were identified as potential sources contributing to temperature patterns. These findings have important implications for understanding urban hydrology and the contributions of different source zones in urban catchments. Specifically, our results suggest that stream temperature may serve as a cost‐effective tracer providing information about urban water sources and pathways, thus aiding in the understanding of complex urban hydrology.

Impact of greenspaces and water bodies on hydrological processes in an urbanizing area: A case study of the Liuxi River Basin in the Pearl River Delta, China

The rapid shifts in landuse and the frequency of flooding events brought by urbanization significantly impact the urban basins, which means that optimizing landscape patterns is crucial for improving urban hydrology. Therefore, the Liuxi River Basin (LRB), an important river in the Pearl River Delta region, was utilized as an example in the study to examine how the landscape configuration of greenspaces and water bodies influences the hydrological components. However, there are few studies on landscape hydrology in the Pearl River Delta (PRD) and the spatial linkages between landscape metrics and hydrological components are not clear. Based on this, this paper aims to explore the mathematical and spatial associations between landscape configuration and hydrological variables in the PRD region. The SWAT model was constructed to simulate hydrological components based on landuse changes from 1980 to 2018, and regressions were established for landscape pattern indices, water morphology parameters, and hydrological components using stepwise multiple linear regression and geographically weighted regression (GWR). According to the results, the LRB continued to develop, although the greenspaces spread out and changed shape considerably. The influence of water bodies on the hydrological component is mainly in evapotranspiration, and some three-dimensional parameters such as relief ratio favor surface runoff. In the case of greenspace, the runoff is less in connected and wide farmland areas. Irregular forest land will promote water yield but suppress evapotranspiration, and the effect of forest’s shape on hydrological components is more obvious in upstream areas because the regression coefficients in this range are higher, such as 90.27. Methodologically, we found that for water yield, the accuracy of GWR was significantly higher (R2 = 0.814) than that of multiple linear regression (R2 = 0.243). In addition, understanding land use changes before conducting landscape hydrology studies can help make the results more interpretable. We supplemented the relevant research gaps in the PRD region and revealed the spatial correlation between landscape metrics and the hydrological cycle. These findings can aid urban planners in improving their comprehension of hydrological processes and landscape design, leading to more sustainable management of the urban basins.

Interplay of Engineering Skills, Aesthetic Creativity, and Ethical Judgement in the Creation of Sustainable Urban Transformations

This paper examines a PBL project module “Sustainable Urban Transformation” in an Urban Design master’s education. The module combines urban design and hydrology engineering. Within the module, students are supported by lectures and study circles on various dimensions of sustainability, especially vis-a-vis climate change. However, they are left with the freedom to choose how they balance between design and engineering approaches when they give a physical form for sustainability in the site transformation projects with which they work through the semester. This paper discusses the development of their skills building on three Aristotelean concepts: techne (engineering), poiesis (aesthetic form-giving), and phronesis (making of ethical judgments). The last two concepts, the paper argues, are especially important when at issue is design education. Based on an analysis of the student projects in Fall 2022, the paper examines whether and how the students manage to find a balance between engineering skills, on the one hand, and aesthetic creativity and ethical judgement, on the other hand, in their project work.

A spatially distributed hydrodynamic model framework for urban flood hydrological and hydraulic processes involving drainage flow quantification

Two-dimensional hydrodynamic models are increasingly used to predict overland surface water flooding in urban catchments. The complexity of urban surfaces and subsurface drainage systems poses great challenges to modelling urban rainfall-runoff and flood hydraulics. This work develops a spatially distributed hydrodynamic model framework incorporating both hydrological and hydraulic processes of surface and subsurface drainage processes during urban flooding. The model is built upon 2D full shallow water equations solved by a Godunov-type finite volume method with robust treatments of the bed source term. To properly involve drainage flow effects, we present three methods to quantify the drainage flow discharge and its delay time which affect both urban hydrology and surface inundation. Besides, a simple OpenMPI-based parallel algorithm is applied to accelerate the model and ensure computational efficiency when applied to real-world events. The model framework is justified through the validations with five benchmark cases. Benchmark results indicate that the well-balanced treatment of bed source term ensures the model applicability in irregular urban surfaces, the model can predict both urban surface inundation and flood hydrograph, and the proposed drainage flow treatments can well reproduce drainage flow hydrograph. The model framework is successfully applied to simulate rainstorm-induced flood events in a rural–urban catchment, the upper Shenzhen River catchment. Results further demonstrate the robust capability of the model in the quantification of flow exchange between surface and subsurface systems to some extent even in the absence of drainage information. Our framework provides a practical solution for urban flood simulation even when pipe data are scarce.

The influence of stormwater infiltration on downslope groundwater chemistry

Stormwater infiltration basins have been used extensively around the world to restore urban hydrology towards more natural flow and water quality regimes. There is, however, significant uncertainty in the fate of infiltrated water and accompanying contaminants that depends on multiple factors including media characteristics, interactions with downslope vegetation, legacy contaminants, and presence of underground infrastructure. Understanding the influence of such factors is thus central to the design and siting of infiltration basins. An extensive field program was established to collect monthly data on ground water quality, including nutrients and major ion concentrations, in a bore network downstream of a stormwater infiltration basin in Victoria, Australia. The groundwater samples were analysed for temperature, pH, EC, turbidity, major ions (Na+, Ca2+, K+, Mg2+, Cl−, SO42−, NO3−, CO32−, HCO3−), NOx and heavy metals. The collected data were used to understand the origin and fate of water and solutes in the subsurface and their interactions with the soil matrix. The results revealed that Ca–HCO3, Na–Cl water types predominate in the study area, grouped in 3 clusters; shallow fresh groundwater in the vicinity of the basin (near basin), deep saline groundwater further downstream of the basin (near-stream) and a mid-section where rock-water interaction (Na–HCO3 water) through cation exchange control the chemistry of groundwater. The results also suggest that as the water moves downstream of the basin, it experiences significant evapotranspiration and concentration due to the presence of deep-rooted vegetation. The results suggest that while infiltration basins can remove infiltrated contaminants, the infiltrated stormwater can mobilise legacy contaminants such as nitrate. Overall, the efficacy of infiltration basins in urban regions depends substantially on the downstream vegetation, urban underground infrastructure and the presence of legacy contaminants in the soils. These all need to be considered in the design of stormwater infiltration basins.

Bayesian parameter inference in hydrological modelling using a Hamiltonian Monte Carlo approach with a stochastic rain model

Abstract. Stochastic models in hydrology are very useful and widespread tools for making reliable probabilistic predictions. However, such models are only accurate at making predictions if model parameters are first of all calibrated to measured data in a consistent framework such as the Bayesian one, in which knowledge about model parameters is described through probability distributions. Unfortunately, Bayesian parameter calibration, a. k. a. inference, with stochastic models, is often a computationally intractable problem with traditional inference algorithms, such as the Metropolis algorithm, due to the expensive likelihood functions. Therefore, the prohibitive computational cost is often overcome by employing over-simplified error models, which leads to biased parameter estimates and unreliable predictions. However, thanks to recent advancements in algorithms and computing power, fully fledged Bayesian inference with stochastic models is no longer off-limits for hydrological applications. Our goal in this work is to demonstrate that a computationally efficient Hamiltonian Monte Carlo algorithm with a timescale separation makes Bayesian parameter inference with stochastic models feasible. Hydrology can potentially take great advantage of this powerful data-driven inference method as a sound calibration of model parameters is essential for making robust probabilistic predictions, which can certainly be useful in planning and policy-making. We demonstrate the Hamiltonian Monte Carlo approach by detailing a case study from urban hydrology. Discussing specific hydrological models or systems is outside the scope of our present work and will be the focus of further studies.

Functional urban ground-cover plants: identifying traits that promote rainwater retention and dissipation

Urban vegetation can influence urban hydrology and reduce the risk of flooding. Urban forestry studies have suggested that tree type and species choice affect the amount of rainwater intercepted and retained. Little information exists, however, for other landscape typologies, and the sorts of ground-cover plants that are best used to retain/detain rainwater during storm events. This is important as many urban spaces are too small to facilitate trees, but can accommodate roadside vegetation, buffer strips, rain gardens, green roofs and stormwater planters. Thus, this research aimed to determine how choice of ground-cover taxa affected rainwater interception and retention. Six model species with contrasting leaf morphologies were used to determine how well rainwater was intercepted, but also dissipated through evapotranspiration (ET). A pot-based system was used to determine how plant water balance changed during late summer in the UK, with the aim to understand how leaf traits affected hydrological processes. Plant choice was important, with fine-leaved taxa, Festuca glauca and Dianthus ‘Haytor White’ showing best rainwater interception and Festuca demonstrating highest rates of dissipation from the substrate. Overall, compared to non-planted pots, those with plants present were more effective at capturing water (by 2.3–3.0x), and evapo-transpiring water (by 2.5-4.0x). Results indicate that ground cover vegetation has potential to aid urban water management in those localities where space is limited for trees. Plant choice and community-structure should be considered, especially when there is a desire to dry out soil/substrate quickly and restore maximum soil moisture holding capacity.

Adapting drainage networks to the urban development: An assessment of different integrated approach alternatives for a sustainable flood risk mitigation in Northern Italy

Political bodies, planners and the scientific community agree on the need for making cities and communities resilient and sustainable in the near future. Urban infrastructures generate too often negative impacts on the surrounding environment. Hence, it is considered today an absolute priority implementing actions able to generate an optimal relationship between citizens and the environment. Even in the field of hydraulic constructions and urban hydrology, it is therefore essential to develop water management strategies able to contribute to the definition of this new paradigm of city. With regard to flood management, integrated strategies including the combined implementation of Stormwater Detention Tanks and Sustainable Drainage Strategies (SuDS) seem successful solutions but additional studies are required to define their potential. This research aims at assessing and comparing different integrated drainage alternatives involving the single or combined implementation of two categories of SuDS in Sesto Ulteriano (Northern Italy): Green Infrastructures (GI) and flood control areas. The Hydraulic Risk Mitigation Index (HRMI), is here proposed to account for different hydraulic parameters in the performance assessment of an integrated drainage strategy. Results highlighted the importance of HRMI as decision support measure and the effectiveness of SuDS strategies, especially those involving GI, at reducing urban flooding.

Corrigendum to “Dealing with shallow groundwater contexts for the modelling of urban hydrology – A simplified approach to represent interactions between surface hydrology, groundwater and underground structures in hydrological models” [Environ. Model. Software 144 (2021) 105144

Corrigendum to “Dealing with shallow groundwater contexts for the modelling of urban hydrology – A simplified approach to represent interactions between surface hydrology, groundwater and underground structures in hydrological models” [Environ. Model. Software 144 (2021) 105144

Effects of 66 years of water management and hydroclimatic change on the urban hydrology and water quality of the Panke catchment, Berlin, Germany

Long-term records of combined stream flow and water chemistry can be an invaluable source of information on changes in the quantity and quality of water resources. To understand the effect of hydroclimate and water management on the heavily urbanized Panke catchment in Berlin, Germany, an extensive search, collation and digitization of historic data from various sources was undertaken. This integrated a unique 66-year spatially distributed record of stream water quality, a 21-year record of groundwater quality and a 31-year stream flow record. These data were analysed in the context of hydroclimatic variability, as well as the history and technological evolution of water resource management in the catchment. To contextualize the effect of droughts, “average” and wet years the Standard Precipitation Index (SPI) was applied. As upstream sites have been less regulated by human impacts, the flow regime is most sensitive to changes in hydroclimatic conditions, while downstream sites are more influenced by wastewater effluents, urban storm drains and inter-basin transfers for flood alleviation. However, at all sites, a general increase in maximum event discharge was observed until a recent drought, starting in 2018. In general, water quality in the catchment has gradually improved as a result of management change and increasingly effective wastewater treatment, though in some places legacy and/or contemporary urban and rural groundwater contamination may be affecting the stream. Hydroclimatic changes, particularly drought years can affect water quality classes, and alter the chemostatic/dynamic behaviour of catchment export patterns. These insights from the Panke catchment underline the importance of strategic adaptation and improvement of water treatment and water resource management in order to enhance the quality of urban water courses. It also demonstrates the importance of long-term integrated data sets.

Defining intensity–duration–frequency curves at short durations: a methodological framework

ABSTRACT In the field of sub-hourly durations, and especially in urban hydrology, selecting the most appropriate form of the intensity–duration–frequency (IDF) curve becomes a relevant question. In this study, two different formulations of IDF curves – that are characterized by a curvature in the sub-hourly intervals and a power-law formulation for the super-hourly intervals – are proposed in order to maximize the overall information contribution in the sub-hourly and the super-hourly domains. The proposed formulations are compared with two well-known IDF formulations, respectively characterized by a power-law and a curvature (from the power-law) formulation, calibrated only using data referring to super-hourly durations. Findings indicated that the proposed IDF curves allow to account for the different lengths of the sub-hourly and canonical data series and eventually for the different behaviour/trend of sub-hourly and super-hourly data, thus providing the best reliability indicator, at least in the investigated return period.