Experimental investigation for impacts of rain storms and terrain slopes on low impact development effect in an idealized urban catchment

Hou, Jingming; Han, Hao; Qi, Wang; Guo, Kaihua; Li, Zhanbin; Hinkelmann, Reinhard

doi:10.1016/j.jhydrol.2019.124176

Cited by 28 publications

(11 citation statements)

References 49 publications

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“…Moreover, to deal with the increase in the flooding risk caused by climate change, the LID project is recommended as climate mitigation measures in this research, which was capable of alleviating the adverse impact of increased stormwater based on the collection and retention facilities of the rainwater. The obtained results are consistent with the related studies, such as Guo et al (2019b), Morvarid et al (2019), andHou et al (2019). Specifically, it is concluded that the LID projects are beneficial to reduce the flooding risk and cope with the stormwater management issue arising from heavy rainfall under climate change.…”

Section: Discussionsupporting

confidence: 89%

A Low-Impact Development–Based Multi-Objective Optimization Model for Regional Water Resource Management under Impacts of Climate Change

Bao

Han-sheng

et al. 2020

Front. Earth Sci.

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Section: Discussionsupporting

confidence: 89%

A Low-Impact Development–Based Multi-Objective Optimization Model for Regional Water Resource Management under Impacts of Climate Change

Bao

Han-sheng

et al. 2020

Front. Earth Sci.

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“…Structure scale mainly focuses on comparing the input and outflow runoff quantity and quality to assess individual LID performance for optimized parameter design (Hunt et al, 2008;Chen et al, 2018;Bortolini and Zanin, 2019;Zaqout and Andradóttir, 2021;Zhang et al, 2021). Catchment scale normally aims at runoff control in micro urban catchments (<0.5 km 2 ) (Hou et al, 2019;Randall et al, 2019;Yao et al, 2020). Barely focus on individual LID structure performance is inadequate to understand stormwater runoff regulation and pollution control within urban catchments.…”

Section: Introductionmentioning

confidence: 99%

The Role of Spatial Patterns of Low Impact Development in Urban Runoff Pollution Control Within Parcel Based Catchments

Zhao²

2022

Front. Environ. Sci.

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Landscape patterns significantly affect urban runoff pollution, and a reasonable arrangement of pervious patches in urban catchments is critical to control urban non-point-source pollution. Low impact development (LID) can be recognized as a pervious surface type, and many previous studies have analyzed the LID performance at a system scale. However, the influence of the LID spatial distribution on runoff pollutant transport at a catchment scale remains unclear. This study analyzed the influence of pervious/impervious patterns on runoff pollution within two urban catchments constructed with LID. It was found that the runoff pollution was influenced by the area ratio, circumference, shape, and pervious patch connectivity of pervious surfaces (i.e., LID). Catchments with high perviousness ratios are more efficient in reducing the runoff volume and suspended solids, and LID should focus on removing runoff pollutants at catchments with high imperviousness ratios. Six typical landscape metrics that represented the fragmentation, complexity and vergence of pervious surfaces were selected to investigate the influence of pervious/impervious patterns on runoff pollution. The results show that larger fragmentation, smaller complexity and smaller vergence of pervious patches result in larger runoff volumes and more pollutants. Therefore, it is recommended that large pervious areas should be retained and close to one another to enhance the retention capacity of LID, and the outline of pervious patches should be long and irregular to reduce pollution confluence. The results of this study are helpful in arranging LID structures for efficient runoff regulation and pollution control at an urban catchment scale.

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“…Many reported studies have focused on certain aspects of hydrologic performance of LID based on field or experimental investigations (Montalto et al, 2007;Emerson et al, 2010;Thompson et al, 2016;Hou et al, 2019). Some hydrological or hydraulic modeling studies have focused on the potential variations in long-term performances of LID but these studies assumed that LID functions perfectly after installation (Liu et al, 2015;Wang et al, 2021).…”

Section: Introductionmentioning

confidence: 99%

A Bayesian Decision Model for Optimum Investment and Design of Low-Impact Development in Urban Stormwater Infrastructure and Management

Wang¹,

Zhang²,

Zheng³

et al. 2021

Front. Environ. Sci.

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Uncertainties concerning low-impact development (LID) practices over its service life are challenges in the adoption of LID. One strategy to deal with uncertainty is to provide an adaptive framework which could be used to support decision-makers in the latter decision on investments and designs dynamically. The authors propose a Bayesian-based decision-making framework and procedure for investing in LID practices as part of an urban stormwater management strategy. In this framework, the investment could be made at various stages of the service life of the LID, and performed with deliberate decision to invest more or suspend the investment, pending the needs and observed performance, resources available, anticipated climate changes, technological advancement, and users’ needs and expectations. Variance learning (VL) and mean-variance learning (MVL) models were included in this decision tool to support handling of uncertainty and adjusting investment plans to maximize the returns while minimizing the undesirable outcomes. The authors found that a risk-neutral investor tends to harbor greater expectations while bearing a higher level of risks than risk-averse investor in the VL model. Constructed wetlands which have a higher prior mean performance are more favorable during the initial stage of LID practices. Risk-averse decision-makers, however, could choose porous pavement with stable performance in the VL model and leverage on potential technological advancement in the MVL model.

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Experimental investigation for impacts of rain storms and terrain slopes on low impact development effect in an idealized urban catchment

Cited by 28 publications

References 49 publications

A Low-Impact Development–Based Multi-Objective Optimization Model for Regional Water Resource Management under Impacts of Climate Change

A Low-Impact Development–Based Multi-Objective Optimization Model for Regional Water Resource Management under Impacts of Climate Change

The Role of Spatial Patterns of Low Impact Development in Urban Runoff Pollution Control Within Parcel Based Catchments

A Bayesian Decision Model for Optimum Investment and Design of Low-Impact Development in Urban Stormwater Infrastructure and Management

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