Mitigating Soil Erosion Caused by Artificial Disturbances in Hilly Lake Environs: Scenario Approach to LID Planning

Yang, Tianxiang; Wang, Shoubing; Zhang, Ming

doi:10.1061/jswbay.0000839

J. Sustainable Water Built Environ.

2018

DOI: 10.1061/jswbay.0000839

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Mitigating Soil Erosion Caused by Artificial Disturbances in Hilly Lake Environs: Scenario Approach to LID Planning

Tianxiang Yang

Shoubing Wang

Ming Zhang

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Cited by 3 publications

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“…In Yang et al (2018), the use of LID practices to mitigate soil erosion during artificial disturbance in hilly lake environs is discussed. Taking the Nanyi Lake region as an example, this paper modeled the scenario effectiveness of LID under the existing framework and evaluated multiple-aspect effectiveness of planning on mitigating soil erosion in hilly lake environs.…”

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confidence: 99%

Green Infrastructure and Sponge City Research

Jia

Davis

2018

J. Sustainable Water Built Environ.

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The special collection on Green Infrastructure and Sponge City Research is available in the ASCE Library (https://ascelibrary.org /page/jswbay/green_infrastructure_sponge_city).Green infrastructure (GI) and sponge city construction (integrating green and gray) principles have become the new paradigm for a sustainable urban stormwater management strategy (Jia et al. 2017). It has become a widespread focus in urban water management research and practices globally.Specifically in China, over the past decade built-up areas have increased by 17,252 km 2 . This roughly equates to an addition of 165 million people dwelling in urban areas in a decade. This rapid urbanization, sometimes lacking adequate planning and design, has led to a worsening city syndrome situation, such as urban flooding, water pollution, heat-island effects, and ecologic deterioration (Jia et al. 2013).In order to promote a sustainable urbanization strategy, in 2013 the Chinese government announced a new urban drainage infrastructure building paradigm, branding it the sponge city initiative. Deviating from the traditional rapid-draining approach, the new paradigm calls for the use of natural systems such as soil and vegetation as part of the urban runoff control strategy. The six-word principle, which includes infiltrate, detain, store, cleanse, use, and drain, forms the basis of the guidelines for urban stormwater management.In this context, in order to provide an international forum for stormwater management professionals to present the latest developments, technologies, and case studies related to GI and sponge city technology, the 2016 International Low Impact Development (LID) Conference was organized and held in Beijing. More than 1,200 delegates from over 20 countries attended the meeting with more than 400 papers presented orally or as posters.For this special collection, we have invited selected participants at the conference to highlight some of the important aspects of LID-GI and sponge city implementation. These papers cover the following areas: case studies on sustainable urban design and management using LID-GI principles and practices, methods of quantifying benefits of sustainable drainage system (SuDS) implementation, rainwater utilization, practices that mitigate urban flooding and soil erosion, and LID applications in managing highway runoff.In more detail, this special collection contains seven papers. Within the context of frequent extreme weather events that led to dramatic urban waterlogging and flash flood hazards in mountainous cities, Ma et al. (2018) use the city of Fuzhou, China, as a case study and discuss comprehensive defense measures to prevent and/or mitigate the impacts of these hazards. They first review the progress of preventive measures of these two types of hazards in China, such as those employed in the nationwide construction of sponge cities and national flash flood prevention projects. They analyze the characteristics of waterlogging and flash flood hazards in China using 25 years of records from the Chine...

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confidence: 99%

Green Infrastructure and Sponge City Research

Jia

Davis

2018

J. Sustainable Water Built Environ.

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Field investigation of the feasibility of MICP for Mitigating Natural Rainfall-Induced erosion in gravelly clay slope

Zhang,

Lu,

Tang

et al. 2024

Bull Eng Geol Environ

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Rainfall-induced erosion on slopes is a prevalent natural process leading to soil loss. One promising application of microbially induced carbonate precipitation (MICP) is to mitigate rainfall-induced erosion. Conducting field tests is an essential step to verify and improve its performance. In the current work, field tests were conducted to assess the feasibility of using MICP to mitigate rainfall-induced erosion on a gravelly clay slope in Longyan, Fujian, China. A temporary laboratory was set up to cultivate bacteria, and a non-sterilizing method was employed to prepare large volumes of bacterial suspensions in a single batch. Slopes were treated by spraying solutions onto their surfaces. The amount of discharged soils and 3D surface scanning results were used for evaluating the erosion intensity of the slopes. The results demonstrated that the method could effectively mitigate the surface erosion caused by natural rainfall and prevent erosion-induced collapse. Notably, approximately one year after the treatment, the grass had started to grow on the heavily cemented slope, indicating that the MICP method is both effective and eco-friendly for soil stabilization method. However, further improvements are needed to enhance the uniformity and long-term durability of the MICP treatment.

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Machine learning based soil erosion susceptibility prediction using social spider algorithm optimized multivariate adaptive regression spline

Tran

Cao

et al. 2020

Measurement

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Mitigating Soil Erosion Caused by Artificial Disturbances in Hilly Lake Environs: Scenario Approach to LID Planning

Cited by 3 publications

References 58 publications

Green Infrastructure and Sponge City Research

Green Infrastructure and Sponge City Research

Field investigation of the feasibility of MICP for Mitigating Natural Rainfall-Induced erosion in gravelly clay slope

Machine learning based soil erosion susceptibility prediction using social spider algorithm optimized multivariate adaptive regression spline

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