Special Issue "Urban Catchment: Rainfall–Runoff Issues and Responses"

A special issue of Water (ISSN 2073-4441). This special issue belongs to the section "Hydrology".

Deadline for manuscript submissions: closed (10 March 2021).

Special Issue Editor

Dr. Rupak Aryal
E-Mail Website
Guest Editor
School of Civil and Environmental Engineering, University of Technology Sydney, Ultimo, Australia
Interests: urban hydrology; urban runoff monitoring and modeling; emerging contaminants in urban runoff; pollutant transport; water-sensitive urban design for water management and reuse.

Special Issue Information

Dear Colleagues,

Rapid urbanisation across the globe in the last few decades has changed the rainfall–runoff response in many catchments. Along with population growth, numerous changes in the landscape and impervious ratio in urban areas have also occurred. The change in the landscape in many cities has had a tremendous impact on urban hydrology. This includes changes in rainfall–runoff balance and changes in physical, chemical and biological aspects of water quality. Besides this, urban flooding has become more frequent due to an increase in imperviousness and runoff peak flow. This Special Issue seeks to highlight studies on urban rainfall–runoff monitoring and modelling, the role of imperviousness in urban water quality, the adoption of water-sensitive urban designs to mitigate water quality problems, stormwater harvesting, analytical techniques to examine these linkages and water management, and water policy.

Dr. Rupak Aryal
Guest Editor

Manuscript Submission Information

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Keywords

  • urban rainfall runoff in a changing climate and landscape
  • urban rainfall runoff modelling
  • issues in urban drainage
  • urban pollutants and transport
  • water-sensitive urban design
  • stormwater recycling and reuse
  • urban runoff and ecological/human health risk
  • urban runoff and future water security
  • urban stormwater recycling and reuse policy and management.

Published Papers (6 papers)

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Research

Article
GPM Annual and Daily Precipitation Data for Real-Time Short-Term Nowcasting: A Pilot Study for a Way Forward in Data Assimilation
Water 2021, 13(10), 1422; https://doi.org/10.3390/w13101422 - 20 May 2021
Viewed by 801
Abstract
This study explores the quality of data produced by Global Precipitation Measurement (GPM) and the potential of GPM for real-time short-term nowcasting using MATLAB and the Short-Term Ensemble Prediction System (STEPS). Precipitation data obtained by rain gauges during the period 2015 to 2017 [...] Read more.
This study explores the quality of data produced by Global Precipitation Measurement (GPM) and the potential of GPM for real-time short-term nowcasting using MATLAB and the Short-Term Ensemble Prediction System (STEPS). Precipitation data obtained by rain gauges during the period 2015 to 2017 were used in this comparative analysis. The results show that the quality of GPM precipitation has different degrees efficacies at the national scale, which were revealed at the performance analysis stage of the study. After data quality checking, five representative precipitation events were selected for nowcasting evaluation. The GPM estimated precipitation compared to a 30 min forecast using STEPS precipitation nowcast results, showing that the GPM precipitation data performed well in nowcasting between 0 to 120 min. However, the accuracy and quality of nowcasting precipitation significantly reduced with increased lead time. A major finding from the study is that the quality of precipitation data can be improved through blending processes such as kriging with external drift and the double-kernel smoothing method, which enhances the quality of nowcast over longer lead times. Full article
(This article belongs to the Special Issue Urban Catchment: Rainfall–Runoff Issues and Responses)
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Article
Role of Environmental Variables in the Transport of Microbes in Stormwater
Water 2021, 13(9), 1146; https://doi.org/10.3390/w13091146 - 21 Apr 2021
Cited by 1 | Viewed by 473
Abstract
Microbial pathogens present in stormwater, which originate from human sewage and animal faecal matters, are one of the major impediments in stormwater reuse. The transport of microbes in stormwater is more than just a physical process. The mobility of microbes in stormwater is [...] Read more.
Microbial pathogens present in stormwater, which originate from human sewage and animal faecal matters, are one of the major impediments in stormwater reuse. The transport of microbes in stormwater is more than just a physical process. The mobility of microbes in stormwater is governed by many factors, such as dissolved organic matter, cations, pH, temperature and water flow. This paper examined the roles of three environmental variables, namely: dissolved organic matter, positive cations and stormwater flow on the transport of two faecal indicator bacteria (FIB), Enterococcus spp. and Escherichia coli. Stormwater runoff samples were collected during twelve wet weather events and one dry weather event from a medium density residential urban catchment in Brisbane. Enterococcus spp. numbers as high as 3 × 104 cfu/100 mL were detected in the stormwater runoff, while Escherichia coli numbers up to 3.6 × 103 cfu/100 mL were observed. The dissolved organic carbon (DOC) in the stormwater samples was in the range of 2.2–5.9 mg/L with an average concentration of 4.5 mg/L in which the hydrophilic carbon constituted the highest mass fraction of 60–80%. The results also showed that the transport of FIB in stormwater was reduced with an increasing concentration of the hydrophilic organic fraction, especially the humic fraction. On the contrary, the concentration of trivalent cations and stormwater flow rate showed a positive correlation with the FIB numbers. These findings indicated the potentiality to make a good use and measurement of simple environmental variables to reflect the degree of microbe transport in stormwater from residential/suburban catchments. Full article
(This article belongs to the Special Issue Urban Catchment: Rainfall–Runoff Issues and Responses)
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Article
Assessing the Feasibility of a Cloud-Based, Spatially Distributed Modeling Approach for Tracking Green Stormwater Infrastructure Runoff Reductions
Water 2021, 13(3), 255; https://doi.org/10.3390/w13030255 - 21 Jan 2021
Viewed by 564
Abstract
Use of green stormwater infrastructure (GSI) to mitigate urban runoff impacts has grown substantially in recent decades, but municipalities often lack an integrated approach to prioritize areas for implementation, demonstrate compelling evidence of catchment-scale improvements, and communicate stormwater program effectiveness. We present a [...] Read more.
Use of green stormwater infrastructure (GSI) to mitigate urban runoff impacts has grown substantially in recent decades, but municipalities often lack an integrated approach to prioritize areas for implementation, demonstrate compelling evidence of catchment-scale improvements, and communicate stormwater program effectiveness. We present a method for quantifying runoff reduction benefits associated with distributed GSI that is designed to align with the spatial scale of information required by urban stormwater implementation. The model was driven by a probabilistic representation of rainfall events to estimate annual runoff and reductions associated with distributed GSI for various design storm levels. Raster-based calculations provide estimates on a 30-m grid, preserving unique combinations of drainage factors that drive runoff production, hydrologic storage, and infiltration benefits of GSI. The model showed strong correspondence with aggregated continuous runoff data from a set of urbanized catchments in Salinas, California, USA, over a three-year monitoring period and output sensitivity to the storm drain network inputs. Because the model runs through a web browser and the parameterization is based on readily available spatial data, it is suitable for nonmodeling experts to rapidly update GSI features, compare alternative implementation scenarios, track progress toward urban runoff reduction goals, and demonstrate regulatory compliance. Full article
(This article belongs to the Special Issue Urban Catchment: Rainfall–Runoff Issues and Responses)
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Article
Development of a Model for Stormwater Runoff Prediction on Vertical Test Panels Coated with Plaster and Mortar
Water 2020, 12(9), 2593; https://doi.org/10.3390/w12092593 - 16 Sep 2020
Cited by 2 | Viewed by 757
Abstract
Leaching outdoor tests (LOT) are commonly used to assess the leaching of substances from construction materials. In this context, the amount of stormwater in contact with the surface material is of special interest for analyzing the runoff loads of substances from building façades. [...] Read more.
Leaching outdoor tests (LOT) are commonly used to assess the leaching of substances from construction materials. In this context, the amount of stormwater in contact with the surface material is of special interest for analyzing the runoff loads of substances from building façades. A numerical model was developed in MATLAB on the basis of previous analytical models to calculate the collected stormwater runoff volumes from the vertical test panels (VTP) during LOT. In the model, wind-driven rain (WDR) is considered to be the main mechanism for determining the amount of water impinging on the VTP, so it is a crucial factor in the modeling for the façade runoff. The new model makes it possible to simulate the runoff volumes from VTP that are covered with a wide variety of plaster and mortar. Using the new model, it was possible to relate the VTP runoff volumes obtained during an 18-month sampling period for LOTs performed at the Fraunhofer Institute for Building Physics in Valley, Germany. When comparing the simulation results with the field test accumulated runoffs, the model exhibited a difference of no more than 3.5% for each of the analyzed materials. The simulation results are satisfying, and the paper demonstrates the feasibility of the modelling approach for the runoff assessment of VTP covered with a variety of plaster and mortar. Full article
(This article belongs to the Special Issue Urban Catchment: Rainfall–Runoff Issues and Responses)
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Article
Rapid Urbanization Impact on the Hydrological Processes in Zhengzhou, China
Water 2020, 12(7), 1870; https://doi.org/10.3390/w12071870 - 30 Jun 2020
Cited by 3 | Viewed by 1067
Abstract
Changes in the hydrological process caused by urbanization lead to frequent flooding in cities. For fast-growing urban areas, the impact of urbanization on the hydrological process needs to be systematically analyzed. This study takes Zhengzhou as an example to analyze the impact of [...] Read more.
Changes in the hydrological process caused by urbanization lead to frequent flooding in cities. For fast-growing urban areas, the impact of urbanization on the hydrological process needs to be systematically analyzed. This study takes Zhengzhou as an example to analyze the impact of urbanization on the hydrological process based on 1971–2012 hourly rainfall-runoff data, combining Geographic Information Systems with traditional hydrological methods. Our study indicates that the rain island effect in different districts of city became stronger with the increase of its built-up. The uneven land use resulted in the difference of runoff process. The flood peak lag was 25–30% earlier with the change of land use. The change of flood peak increased by 10–30% with the change of built-up. The runoff coefficient increases by 20–35% with the increase of built-up, and its change increased with the change of land use. Affected by the rain island effect, precipitation tends to occur in areas where built-up is dominant, which overall magnifies the impact of urbanization on the hydrological process. This provides new ideas for urban flood control. Refine flood control standards according to regional land use changes to cope with the hydrological process after urbanization. Full article
(This article belongs to the Special Issue Urban Catchment: Rainfall–Runoff Issues and Responses)
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Article
WetSpa-Urban: An Adapted Version of WetSpa-Python, A Suitable Tool for Detailed Runoff Calculation in Urban Areas
Water 2019, 11(12), 2460; https://doi.org/10.3390/w11122460 - 23 Nov 2019
Cited by 4 | Viewed by 1349
Abstract
A tool called WetSpa-Urban was developed to respond to the need for precise runoff estimations in an increasingly urbanized world. WetSpa-Urban links the catchment model WetSpa-Python to the urban drainage model Storm Water Management Model (SWMM). WetSpa-Python is an open-source, fully distributed, process-based [...] Read more.
A tool called WetSpa-Urban was developed to respond to the need for precise runoff estimations in an increasingly urbanized world. WetSpa-Urban links the catchment model WetSpa-Python to the urban drainage model Storm Water Management Model (SWMM). WetSpa-Python is an open-source, fully distributed, process-based model that accurately represents surface hydrological processes but does not simulate hydraulic structures. SWMM is a well-known open-source hydrodynamic tool that calculates pipe flow processes in an accurate manner while runoff is calculated conceptually. Merging these tools along with certain modifications, such as improving the efficiency of surface runoff calculation and simulating flow at the sub-catchment level, makes WetSpa-Urban suitable for event-based and continuous rainfall–runoff modeling for urban areas. WetSpa-Urban was applied to the Watermaelbeek catchment in Brussels, Belgium, which recently experienced rapid urbanization. The model efficiency was evaluated using different statistical methods, such as Nash–Sutcliffe efficiency and model bias. In addition, a statistical investigation, independent of time, was performed by applying the box-cox transformation to the observed and simulated values of the flow peaks. By speeding up the simulation of the hydrological processes, the performance of the surface runoff calculation increased by almost 130%. The evaluation of the simulated 10 minute flow versus the observed flow at the outlet of the catchment for 2015 reached a Nash–Sutcliffe efficiency of 0.86 and a bias equal to 0.06. Full article
(This article belongs to the Special Issue Urban Catchment: Rainfall–Runoff Issues and Responses)
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