A review on implementing infiltration-based green infrastructure in shallow groundwater environments: Challenges, approaches, and progress

Zhang, Kun; Chui, Ting Fong May

doi:10.1016/j.jhydrol.2019.124089

Cited by 50 publications

(24 citation statements)

References 86 publications

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“…The simulations covered three types of design measures that are potentially feasible to mitigate the impact of shallow groundwater on the PP's hydrologic performance (Zhang & Chui, 2017, 2019). For each scenario, only one design measure was changed, whilst the remaining ones remained unchanged.…”

Section: Methodsmentioning

confidence: 99%

“…Furthermore, shallow groundwater, that is, groundwater table shallower than 1–3 m below the ground surface, can be another major obstacle in implementing infiltration‐based GI. With a shorter distance from the groundwater table, GI's hydrologic performance can be affected (Locatelli et al, 2015; Jackisch & Weiler, 2017; Zhang, Chui, & Yang, 2018), and there is also a higher risk to contaminate the groundwater (Fischer, Charles, & Baehr, 2003; Datry, Malard, & Gilbert, 2004; Newman et al, 2004; Chui & Trinh, 2016; Zhang & Chui, 2017, 2018, 2019).…”

Section: Introductionmentioning

confidence: 99%

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Design measures to mitigate the impact of shallow groundwater on hydrologic performance of permeable pavements

Zhang

Chui

2020

Hydrological Processes

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Permeable pavements (PPs) are widely implemented in urban areas to mimic natural hydrologic processes through enhancing infiltration, and reducing, delaying, and retaining surface runoff. However, its performance can be affected by shallow groundwater since high soil moisture may inhibit its infiltration and exfiltration. This study built a numerical model, which was calibrated and validated based on laboratory experiment data, to evaluate the water balance and retention of PP in shallow groundwater conditions. It assessed the impacts of shallow groundwater and the hydrologic effectiveness of different PP design measures (i.e., building a PP with a smaller storage depth, implementing an underdrain at different elevations, and installing an impermeable liner) on relieving the impacts. Shallower groundwater led to larger amounts of surface runoff and underdrain flow, and a higher chance of saturating the PP reservoir. The three design measures had both benefits and drawbacks in mimicking natural hydrologic cycle and retaining the performance of PP under extreme conditions (e.g., areas of very shallow groundwater tables and/or extreme rainfalls). A PP with a smaller storage depth resulted in less underdrain flow but was prone to saturation. It is, thus, more recommended for PP with more-permeable subsoils, which can avoid frequent pavement saturation. Although a shallower PP corresponds to a smaller storage volume and shorter hydraulic retention time, it can increase the applicability of PP to shallow groundwater areas, which is beneficial to the regional hydrologic environment. Installing an underdrain generated underdrain flow, which is a burden to the downstream drainage system. However, it significantly reduced the surface runoff and the chance of saturating the PP reservoir, which, thus, is more recommended for PP with less-permeable subsoils. Comparatively, elevating the underdrain is recommended in areas of shallow groundwater because it can reduce the frequency and amount of groundwater-induced underdrain flow. In addition, a higher underdrain together with an impermeable liner can create a storage depth, increase the retention duration, enhance exfiltration and evaporation without increasing the saturation risk.

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Section: Methodsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Design measures to mitigate the impact of shallow groundwater on hydrologic performance of permeable pavements

Zhang

Chui

2020

Hydrological Processes

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“…This physically-based simulation allows assessing new NBS scenarios. Zhang and Chui (2019) concluded that the simulations of process-based models tend to be more effective and provide more robust results for NBS design and their in-situ monitoring than empirical and conceptual models. Based on their spatial characterisation, these can be categorised into one dimensional (1D), two dimensional (2D) or three dimensional (3D) models.…”

Section: Assessment Framework: Overview Of Modelling Approachesmentioning

confidence: 99%

“…A majority of these articles focused on the monitoring methods for NBS assessment ( Kumar et al, 2021 ), HMRs mapping and damage assessment ( Teng et al, 2017 ; Khan et al, 2020 ; Sahani et al, 2019 ), life cycle appraisals including the economic valuation of ecosystem services ( Newman et al, 2017 ; Eckhardt et al, 2019 ; Ovando and Brouwer, 2019 ; Nguyen et al, 2020 ), assessment frameworks for NBS ( Dumitru et al, 2020 ; Shah et al, 2020 ), upscaling and replication of NBS ( Saleh and Weinstein, 2016 ), and real-time forecasting of HMHs and/or HMRs. Zhang and Chui (2019) reviewed and presented models to evaluate the performance of green infrastructure in reducing runoff. They assessed the strategies for optimally allocating and designing NBS in shallow groundwater areas and highlighted that numerical modelling, and in-situ and laboratory monitoring methods can be applied simultaneously as engineering guidance and robust evaluation framework to understand the performance of green infrastructure.…”

Section: Introductionmentioning

confidence: 99%

Nature-based solutions efficiency evaluation against natural hazards: Modelling methods, advantages and limitations

Kumar

Debele

Sahani

et al. 2021

Science of The Total Environment

130

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Nature-based solutions (NBS) for hydro-meteorological risks (HMRs) reduction and management are becoming increasingly popular, but challenges such as the lack of well-recognised standard methodologies to evaluate their performance and upscale their implementation remain. We systematically evaluate the current state-of-the art on the models and tools that are utilised for the optimum allocation, design and efficiency evaluation of NBS for five HMRs (flooding, droughts, heatwaves, landslides, and storm surges and coastal erosion). We found that methods to assess the complex issue of NBS efficiency and cost-benefits analysis are still in the development stage and they have only been implemented through the methodologies developed for other purposes such as fluid dynamics models in micro and catchment scale contexts. Of the reviewed numerical models and tools MIKE-SHE, SWMM (for floods), ParFlow-TREES, ACRU, SIMGRO (for droughts), WRF, ENVI-met (for heatwaves), FUNWAVE-TVD, BROOK90 (for landslides), TELEMAC and ADCIRC (for storm surges) are more flexible to evaluate the performance and effectiveness of specific NBS such as wetlands, ponds, trees, parks, grass, green roof/walls, tree roots, vegetations, coral reefs, mangroves, sea grasses, oyster reefs, sea salt marshes, sandy beaches and dunes. We conclude that the models and tools that are capable of assessing the multiple benefits, particularly the performance and cost-effectiveness of NBS for HMR reduction and management are not readily available. Thus, our synthesis of modelling methods can facilitate their selection that can maximise opportunities and refute the current political hesitation of NBS deployment compared with grey solutions for HMR management but also for the provision of a wide range of social and economic co-benefits. However, there is still a need for bespoke modelling tools that can holistically assess the various components of NBS from an HMR reduction and management perspective. Such tools can facilitate impact assessment modelling under different NBS scenarios to build a solid evidence base for upscaling and replicating the implementation of NBS.

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“…Second, the complex hydro-environmental processes of SuDS and the surrounding environments are difficult to model using existing models. For instance, the macropore flow in the soil layer of SuDS is not accounted for in SWMM (Niazi et al, 2017), and models for assessing the performance of SuDS in shallow groundwater environment (Zhang and Chui, 2019) and cold climate (Johannessen et al, 2017) are limited.…”

mentioning

confidence: 99%

Modeling and interpreting hydrological responses of sustainable urban drainage systems with explainable machine learning methods

Yang¹,

Chui²

2020

Preprint

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Abstract. Sustainable drainage systems (SuDS) are decentralized stormwater management practices that mimic the natural drainage processes. Their modeling is often challenged by insufficient data and unknown factors affecting the hydrological processes. This study uses machine learning methods to model directly the correlation between hydrological responses and rainfalls at fine temporal scales in two catchments of different sizes. A feature engineering method is developed to extract useful information from rainfall time series and is used in combination with a nested cross-validation procedure to derive high-quality models and to estimate their generalization errors. The SHAP method is adopted to explain the basis of each prediction, which is then used for estimating catchment response time and hydrograph separation. The explanations of the predictions provide valuable insights into the models’ behavior and the involved hydrological processes. Thus, interpreting machine learning models is found as a useful way to study catchment hydrology.

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A review on implementing infiltration-based green infrastructure in shallow groundwater environments: Challenges, approaches, and progress

Cited by 50 publications

References 86 publications

Design measures to mitigate the impact of shallow groundwater on hydrologic performance of permeable pavements

Design measures to mitigate the impact of shallow groundwater on hydrologic performance of permeable pavements

Nature-based solutions efficiency evaluation against natural hazards: Modelling methods, advantages and limitations

Modeling and interpreting hydrological responses of sustainable urban drainage systems with explainable machine learning methods

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