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Water
Special Issues
Numerical Modelling and Data Analytics for Resilient Urban Water Infrastructure
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Numerical Modelling and Data Analytics for Resilient Urban Water Infrastructure

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

Deadline for manuscript submissions: closed (31 August 2022) | Viewed by 1877

Special Issue Editors

Dr. Xilin Xia

E-Mail Website
Guest Editor
School of Architecture, Building and Civil Engineering, Loughborough University, Loughborough, Leicestershire LE11 3TU, UK
Interests: numerical modelling of hydrological hazards; flood risk management
Dr. Fanlin Meng

E-Mail Website
Guest Editor
College of Engineering, Mathematics and Physical Sciences, Harrison Building, Streatham Campus, University of Exeter, North Park Road, Exeter EX4 4QF, UK
Interests: modelling and risk and resilience management of urban water systems; optimisation; water policy
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Urban water infrastructure consists of water and wastewater distribution/collection and treatment and flood control systems. Climate change is putting increasing stress on urban water infrastructure by increasing the frequency of natural hazards such as flooding or drought. At the same time, rapid urban population growth increases the exposure and vulnerability to these hazards. It is important to build resilience to natural hazards to adapt to climate change and achieve sustainability. Numerical modelling and data analytics play an increasingly important role in understanding and predicting the impacts of natural hazards, assessing risks, optimizing planning and operation, and ultimately increasing resilience. This special issue provides a platform to showcase recent advances in methodological development or applications of numerical or data-driven methods for increasing resilience of urban water infrastructure to natural hazards. Submission of research articles, case studies and review articles related but not limited to the following topics are encouraged:

  • Modelling of natural hazards and their impacts on urban water infrastructure
  • Digital twins of urban water infrastructure
  • Data analytics for assessing and/or enhancing resilience of urban water systems
  • Resilience assessment of urban water infrastructure
  • Optimal planning or operation for building resilient urban water infrastructure

Dr. Xilin Xia
Dr. Fanlin Meng
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Water is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2600 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • natural hazards
  • climate change
  • urban water infrastructure
  • resilience
  • numerical modelling
  • data analytics
  • machine learning

Published Papers (1 paper)

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Research

30 pages, 26635 KiB  
Article
Investigating the Impact of Spatial Distribution of Sustainable Drainage System (SuDS) Components on Their Flood Mitigation Performance in Communities with High Groundwater Levels
by Yao Ma, Xilin Xia, Qiuhua Liang and Hongyou Wan
Water 2022, 14(9), 1367; https://0-doi-org.brum.beds.ac.uk/10.3390/w14091367 - 22 Apr 2022
Cited by 2 | Viewed by 1919
Abstract
This paper investigated the impact of the spatial distribution of SuDS components on their flood reduction performance and the underlying mechanisms in a community with high groundwater levels. The effects of SuDS components’ connectivity, decentralized level, and installation position along the flow direction [...] Read more.
This paper investigated the impact of the spatial distribution of SuDS components on their flood reduction performance and the underlying mechanisms in a community with high groundwater levels. The effects of SuDS components’ connectivity, decentralized level, and installation position along the flow direction on the reduction of total discharge volume (TDV), average discharge flow rate (ADFR), maximum discharge flow rate (MDFR), inundated area (IA), average inundated depth (AID), and maximum inundated depth (MID) were studied by coupling of the storm water management model (SWMM) and high-performance integrated hydrodynamic modelling system (HiPIMS). The results demonstrate that the connectivity has a positive linear correlation with the reduction of TDV (R2 > 0.991), ADFR (R2 > 0.992), and MDFR (R2 > 0.958), while the decentralized level of rain gardens and green roofs present positive one-phase exponential correlation with the reduction of TDV (R2 > 0.935), ADFR (R2 > 0.934) and MDFR (R2 > 0.967). A better-integrated mitigation of TDV and ADFR could be achieved by installing SuDS upstream along the flow direction. The connectivity from green roofs to rain gardens has a positive effect on the reduction of AID and MID but leads to the increase of IA. The findings of this study may contribute to the development of general spatial distribution guidelines and strategies to optimize the overall performance of SuDS components, especially at a community scale. Full article
(This article belongs to the Special Issue Numerical Modelling and Data Analytics for Resilient Urban Water Infrastructure)
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