Planning Framework for Mesolevel Optimization of Urban Runoff Control Schemes

Arnbjerg‐Nielsen

et al. 2021

Water

Self Cite

Urban floods are detrimental to societies, and flood mapping techniques provide essential support for decision-making on the better management of flood risks. This study presents a GIS-based flood characterization methodology for the rapid and efficient identification of urban flood-prone areas, which is especially relevant for large-scale flood hazards and emergency assessments for data-scarce studies. The results suggested that optimal flood mapping was achieved by adopting the median values of the thresholds for local depression extraction, the topographic wetness index (TWI) and aggregation analyses. This study showed the constraints of the depression extraction and TWI methods and proposed a methodology to improve the performance. A new performance indicator was further introduced to improve the evaluation ability of hazard mapping. It was shown that the developed methodology has a much lower demand on the data and computation efforts in comparison to the traditional two-dimensional models and, meanwhile, provides relatively accurate and robust assessments of flood hazards.

Section: Methodology and Case Study 21 Methodologymentioning

confidence: 99%

A GIS-Based Hydrological Modeling Approach for Rapid Urban Flood Hazard Assessment

Arnbjerg‐Nielsen

et al. 2021

Water

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“…Urban water is a challenging problem for water quantity and quality management in many cities. Urbanization and climate change can lead to direct increases of surface runoff volume and pollution (Huong & Pathirana, 2013; Jiang et al, 2018; Mei et al, 2018; Zhou et al, 2017). Traditional management of urban runoff is based on drainage systems that aimed to transport excess surface runoff from a site as quickly as possible (Kong et al, 2017; Mei et al, 2018).…”

Section: Introductionmentioning

confidence: 99%

“…The planning of LIDs needs to take into account conditions at multiple spatial scales in various planning stages (Demuzere et al, 2014; Messner et al, 2006; Zhou et al, 2017). When an overall control objective (e.g., runoff control, pollution reduction, and low cost) is given for a region, the first and vital process is the conceptual planning that prioritizes, and assigns the LID measures to the subcatchments.…”

Section: Introductionmentioning

confidence: 99%

“…Many LIDs are multifunctional and the allocation strategy can vary depending on the criteria, perspectives, and preferences proposed. The planning of LIDs needs to take into account conditions at multiple spatial scales in various planning stages (Demuzere et al, 2014; Messner et al, 2006; Zhou et al, 2017). There are different planning phrases and each requires different decision‐aid tools to support the design and implementation (Zhou et al, 2017).…”

Section: Introductionmentioning

confidence: 99%

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Conceptual planning approach of low impact developments for combined water quality‐quantity control at an urban scale: A case study in Southern China

J Flood Risk Management

Luo

Zhao

et al. 2021

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Managing urban water in many cities becomes more challenging under impacts of climate change and urbanization. Low impact development (LID) measures have been increasingly recognized and applied thanks to their capability of tackling multi‐dimensional water problems associated with both quantity and quality issues. Yet, in China limited attention has been paid to guide the planning strategy of LIDs in the preliminary stage, which often suffers from inadequate and imprecise data and information. In this study, an approach integrating a GIS‐based spatial evaluation model, a fuzzy comprehensive evaluation module and a multi‐objective optimization algorithm, is proposed to prioritize the spatial distribution of LIDs (i.e., type, placement, and extent) at the subcatchment scale in a case study in Southern China. By evaluating the trade‐offs among runoff reduction, pollution control, and economic investment, the synergies, and combination strategies of four types of LIDs are explored. Knowledge gained from this study is necessary and beneficial for water planners and practitioners to improve LID planning efficiency under constrained conditions.

“…In a majority of the UDS literature reviewed, besides the common parameters (e.g., population size, generations), the settings of operators (e.g., crossover, mutation) are either not discussed (Barreto et al 2010;Dong et al 2012;Muschalla 2008) or simply based on subjective judgment or recommended values in literature (Delelegn et al 2011;Udias et al 2012). Even with limited studies exploring the sensitivity of optimization results (Chui et al 2016;Yazdi et al 2017b;Zare et al 2012;Zhou et al 2017), the major attention has been dedicated to examining the settings of decision variables and objective functions rather than understanding the working principles of different MOEAs.…”

Section: Introductionmentioning

confidence: 99%

Comparison of Multiobjective Optimization Methods Applied to Urban Drainage Adaptation Problems

Wang

J. Water Resour. Plann. Manage.

Lei

et al. 2018

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This article compares three multi-objective evolutionary algorithms (MOEAs) with application to the urban drainage system (UDS) adaptation of a capital city in North China.Particularly, the well-known NSGA-II, the built-in solver in the MATLAB Global Optimization Toolbox (MLOT), and a newly-developed hybrid MOEA called GALAXY are considered. A variety of parameter combinations of each MOEA are systemically applied to examine their impacts on optimization efficiency. Results suggest that traditional MOEAs suffer from severe parameterization issues. For NSGA-II, the distribution indices of crossover and mutation operators were found to have dominant impacts, while the probabilities of the two operators played a secondary role. For MLOT, the two-point and scattered crossover accompanying the adaptive feasible mutation gained the best Pareto fronts, provided that the crossover fraction is set to lower values. In contrast, GALAXY was the most robust and easy-to-use tool among the three MOEAs, owing to its mechanism for substantially alleviating the parameterization issues.This study contributes to the literature by showing how to improve solution robustness through better selection of operators and associated parameter settings for real-world UDS applications.