A framework for strategic river restoration in China

Speed, Robert; Li, Yuanyuan; Tickner, David; Huang, Huojian; Naiman, Robert J.; Cao, Jianting; Lei, Gang; Yu, Lili; Sayers, Paul; Zhao, Zhongnan; Yu, Wei

doi:10.1080/02508060.2016.1247311

Cited by 26 publications

(32 citation statements)

References 42 publications

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“…In China, the concept of environmental flows has gained currency in the river basin management discourse in the last decade (Chen et al, 2016), but examples of implementation remain rare (Sun et al, 2008;Li et al, 2009;Chen and Zhao, 2011). Nevertheless, recent shifts in policy priorities that emphasize the need for more environmentally sustainable approaches to socio-economic development have led to an increased focus on river restoration, including environmental flow implementation (Speed et al, 2016).…”

Section: Introductionmentioning

confidence: 99%

Managing the Three Gorges Dam to Implement Environmental Flows in the Yangtze River

Cheng¹,

Opperman

Tickner

et al. 2018

Front. Environ. Sci.

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Section: Introductionmentioning

confidence: 99%

Managing the Three Gorges Dam to Implement Environmental Flows in the Yangtze River

Cheng¹,

Opperman

Tickner

et al. 2018

Front. Environ. Sci.

Self Cite

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“…Thus, there is an urgency to restore the ecological quality of these systems and conserve aquatic biodiversity. However, many restoration programs fail in their objectives and achieve limited ecological rehabilitation due to poor planning or failure to address the factors driving change at an appropriate scale (Beechie et al, 2010; Hermoso et al, 2012; Speed et al, 2016). In addition, in most places around the world, financial constraints limit the implementation of rehabilitation measures, and thus, the determination of the most cost‐effective solutions is essential (Langhans, Gessner, Hermoso, & Wolter, 2016).…”

Section: Introductionmentioning

confidence: 99%

Rehabilitation scenarios for reservoirs: Predicting their effect on invertebrate communities through machine learning

Azevêdo

Bezerra‐Neto

Molozzi

et al. 2020

River Research & Apps

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Reservoirs are ecosystems that provide important services and reserves of aquatic biodiversity, especially in arid and semiarid regions. However, they are also highly vulnerable to pollution, water abstraction and land use change. Here, we aimed to develop a “dirty‐water” predictive model that could be used to create recovery scenarios and analyze the effect of measures on the biological quality of reservoirs. Accordingly, we constructed a machine learning predictive model that was trained with environmental and macroinvertebrate community data from 129 sites, sampled in six reservoirs in Northeast Brazil. Two different rehabilitation scenarios were simulated (D1 = lower improvement, 25% change; and D2 = higher improvement, 75% change), and three initial levels of disturbance were considered based on PCA analyses: least disturbed, moderately disturbed and severely disturbed. The effects were analyzed in terms of changes in expected taxa (E), observed/expected taxon ratio (OE), biotic and trophic status indices and the spatial distribution of sensitive taxa. The simulations resulted in significant improvements (p < .001) for all disturbance levels and indicators analyzed. Furthermore, rehabilitation measures in artificial systems, such as reservoirs, could result in a higher biodiversity, biological quality and water quality, also in the least disturbed sites. Thus, this approach has the potential to provide information on management and conservation measures, since the simultaneous predictions of many taxa can be used, including: mapping the distribution of species; monitor the population dynamics of species at risk of extinction; and determining the best rehabilitation measures to improve disturbed ecosystems, allowing the determination of the most cost‐effective restoration measures.

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“…Stable flow regimes are valuable to human society because of their key roles in climate regulation, river dredging, transporting nutrients, hydro-electric power generation and maintaining the diversity of aquatic organisms [1][2]. However, in the last few decades, the river flow regime has undergone a profound change due to climate change and human interference [3][4][5][6][7][8][9][10][11][12][13].…”

Section: Introductionmentioning

confidence: 99%

“…And in the 1980s, Australia, England, South Africa and many other regions started relevant research. Three kinds of important approaches for estimating EFR appeared as follows: (1) hydrological-based, (2) hydraulic-based and (3) biological-based. Among the above approaches, the hydraulic-based approach and biological-based approach are quite complex, and many hydraulic parameters and biological-related information must be measured.…”

Section: Introductionmentioning

confidence: 99%

Ecological Flow Regime and its Satisfactory Degree Assessment Based on an Integrated Method

Wei¹,

Dong²,

Hao³

et al. 2019

Pol. J. Environ. Stud.

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Ecological flow regime (EFR) evaluation is essential in river ecosystem protection. To evaluate and maintain EFR under a changing environment reasonably, an integrated method based on both the monthly 7Q10 method and biological analysis method was put forward for its simple modelling and small data requirement, and then reasonable EFR was obtained after a reasonable check by the Tennant method. Meanwhile, the concept and quantitative formula of the ecological flow regime satisfactory degree (EFRSD) were recommended and successfully applied in the Luanhe River. The results showed that the flow regime of the Luanhe was significantly interrupted by human activities after 1979, and EFRSD has been distinctly damaged since 1998; after 1979, from good to bad, the EFRSD of the Luanhe was the upstream, midstream and downstream. Then the driving forces leading to the Luanhe's EFRSD deterioration that included reduction in the natural rainfall, construction and operating of water conservation projects, and overexploitation of groundwater were discussed and analyzed. Finally, countermeasures for the ecological rehabilitation of the river were pertinently put forward.

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A framework for strategic river restoration in China

Cited by 26 publications

References 42 publications

Managing the Three Gorges Dam to Implement Environmental Flows in the Yangtze River

Managing the Three Gorges Dam to Implement Environmental Flows in the Yangtze River

Rehabilitation scenarios for reservoirs: Predicting their effect on invertebrate communities through machine learning

Ecological Flow Regime and its Satisfactory Degree Assessment Based on an Integrated Method

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