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Integrating Model Predictive Control With Stormwater System Design: A Cost‐Effective Method of Urban Flood Risk Mitigation During Heavy Rainfall

Water resources research, 2024-04, Vol.60 (4), p.n/a [Peer Reviewed Journal]

2024. The Authors. ;2024. This article is published under http://creativecommons.org/licenses/by-nc-nd/4.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License. ;ISSN: 0043-1397 ;EISSN: 1944-7973 ;DOI: 10.1029/2023WR036495

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  • Title:
    Integrating Model Predictive Control With Stormwater System Design: A Cost‐Effective Method of Urban Flood Risk Mitigation During Heavy Rainfall
  • Author: Sun, Lanxin ; Xia, Jun ; She, Dunxian
  • Subjects: Case studies ; Catchment area ; Catchment areas ; Control methods ; Control systems ; Controlled storage ; Cost benefit analysis ; Cost control ; Cost reduction ; Design ; Effectiveness ; Environmental risk ; Extreme weather ; Flood control ; Flood management ; Flood predictions ; Flood risk ; Flooding ; Floods ; Heavy rainfall ; Infrastructure ; Mitigation ; model framework ; model predictive control (MPC) ; peak flow ; Precipitation ; Predictive control ; Rainfall ; Retrofitting ; Risk reduction ; Storage tanks ; Storms ; Stormwater ; Stormwater management ; stormwater system design ; Systems design ; Urban areas ; Urban catchments ; urban flooding
  • Is Part Of: Water resources research, 2024-04, Vol.60 (4), p.n/a
  • Description: The integration of green‐gray infrastructures with advanced control approaches is revolutionizing the stormwater system retrofitting, emerging as an innovative strategy to mitigate urban flood risks. However, a major challenge lies in balancing the substantial investments of these infrastructure projects with their environmental benefits, such as reduced flooding volume and lower peak flow. Model predictive control (MPC), a dynamic and intelligent control approach, optimizes these environmental benefits but is underutilized in the system design phase for cost‐effectiveness analysis. This study introduces a multi‐scenario model framework that incorporates MPC and other control approaches into stormwater system designs, including the implementation of controlled storage tanks and green infrastructures. This framework provides comprehensive modeling tools for practitioners to evaluate the flood control benefits and costs across various infrastructure designs and control scenarios, ultimately identifying solutions that are both environmentally and economically viable. A case study conducted in a small urban catchment area in Shenzhen City, China, demonstrates the effectiveness of this framework. The results indicate that MPC outperforms other control scenarios, particularly under heavy or extreme rainfall conditions. Notably, MPC not only provides superior environmental benefits but also yields considerable cost savings, ranging from 1,787 to 9,371 USD per hectare compared to static control, equating to a 5% reduction in cost relative to rule‐based control. Such findings suggest that integrating MPC is a cost‐effective alternative to extensive infrastructure expansion for flood management, which significantly enhances the benefit contribution of controlled infrastructures without substantial additional expenses. Plain Language Summary Implementing advanced control methods for green‐gray infrastructures is a new method to reduce urban flooding. However, constructing and updating these infrastructures can be very expensive, which is a significant challenge for many urban areas. Our research explores how to use a smart control approach, specifically the model predictive control (MPC), to enhance environmental benefits and save money in the system design phase. We present a multi‐scenario model framework that combines MPC and other methods into the design of stormwater systems, which include controlled storage tanks and green infrastructures. This framework can be used to evaluate the flood control benefits and costs across various infrastructure designs and control scenarios, and to identify the solutions that are both environmentally and economically viable. We conducted a case study in Shenzhen City, China, to test our framework. The results show that MPC is effective particularly during heavy or extreme rainfalls, offering higher environmental benefits and cost savings compared to the scenarios without MPC. Integrating MPC is more cost‐effective than expanding infrastructures for flood management as it notably increases the benefit contribution of controlled infrastructures at a modest cost. Key Points A framework is proposed to assess the environmental and economic impacts of integrating model predictive control (MPC) with stormwater infrastructure designs Assessments are conducted in a small urban catchment involving heavy rainfall events The MPC yields higher environmental benefits and saves economic costs compared to other control approaches
  • Publisher: Washington: John Wiley & Sons, Inc
  • Language: English
  • Identifier: ISSN: 0043-1397
    EISSN: 1944-7973
    DOI: 10.1029/2023WR036495
  • Source: Wiley Blackwell AGU Digital Library
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