Sustainable River and Lake Restoration: From Challenges to Solutions

Topic Information

Dear Colleagues,

Sustainable river and lake restoration is an extremely challenging yet profoundly significant research area. With the continuous exacerbation of climate change, industrialization, and urbanization, rivers and lakes worldwide are facing unprecedented pressures and threats. Systematically addressing a series of thorny issues such as water pollution and degradation of aquatic ecosystems by integrating modern science and technology, thereby achieving sustainable restoration of river and lake systems, is an urgent task that needs to be addressed. To this end, we welcome worldwide scholars in this field to contribute review articles and research papers to the Topic "Sustainable River and Lake Restoration: From Challenges to Solutions". The Topics will comprehensively summarize the major obstacles currently being faced in river and lake restoration, sharing the latest research advances and innovative technological approaches and providing forward-looking insights into future development directions. We believe this will help promote interdisciplinary integration and advance the in-depth development of research on sustainable river and lake restoration.

This Topics will invite experts and scholars from relevant fields, both domestically and internationally, to contribute review articles and research papers, covering but not limited to the following topics:

(1) Causes of degradation in river and lake ecosystems and their impacts on biodiversity and human activities;
(2) Application of Artificial Intelligence and Multi-source Data Fusion Methods in River and Lake Ecosystem Management;
(3) Methods for assessing the health of river and lake ecosystems and ecological risk analysis;
(4) Principles, technologies, and practical cases of river and lake ecological restoration;
(5) Scientific management and environmental governance strategies for river and lake ecosystems;
(6) New technologies and methods in river and lake ecosystem research and restoration engineering.

Prof. Dr. Yun Li
Prof. Dr. Hong Yang
Prof. Dr. Xiaogang Wang
Dr. Zhengxian Zhang
Dr. Boran Zhu
Topic Editors

Keywords

Participating Journals

Journal Name	Impact Factor	CiteScore	Launched Year	First Decision (median)	APC
Atmosphere atmosphere	2.5	4.6	2010	16.1 Days	CHF 2400	Submit
Journal of Marine Science and Engineering jmse	2.7	4.4	2013	16.4 Days	CHF 2600	Submit
Sustainability sustainability	3.3	6.8	2009	19.7 Days	CHF 2400	Submit
Water water	3.0	5.8	2009	17.5 Days	CHF 2600	Submit

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Published Papers (7 papers)

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24 pages, 14135 KiB  

Open AccessArticle

Developing a Novel Robust Model to Improve the Accuracy of River Ecosystem Health Assessment in the Qinghai–Tibet Plateau

by Yuan Xu, Yun Li, Xiaogang Wang, Jianmin Zhang and Zhengxian Zhang

Sustainability 2025, 17(5), 2041; https://doi.org/10.3390/su17052041 - 27 Feb 2025

Viewed by 548

Abstract

River ecosystem health assessment (REHA) is crucial for sustainable river management and water security. However, existing REHA methodologies still fail to consider the multiple effects of input uncertainty, environmental stochasticity, and the decision-maker’s bounded rationality. Moreover, REHA studies primarily focused on plain areas, [...] Read more.

River ecosystem health assessment (REHA) is crucial for sustainable river management and water security. However, existing REHA methodologies still fail to consider the multiple effects of input uncertainty, environmental stochasticity, and the decision-maker’s bounded rationality. Moreover, REHA studies primarily focused on plain areas, leaving the Qinghai–Tibet Plateau (QTP) understudied despite its ecosystems’ heightened fragility and complexity. To address these gaps, this study combined Pythagorean fuzzy sets with cloud modeling and proposed the Pythagorean fuzzy cloud (PFC) approach. Accordingly, a novel robust model (PFC-TODIM) was created by expanding the conventional TODIM method to the PFC algorithm. We provided an REHA indicator system tailored to the distinctive characteristics in the QTP, leveraging multisource data. River ecosystem health, driving mechanisms, and potential threats were investigated in the Lhasa River (LR) using the PFC-TODIM model. Results showed that the created model effectively took multiple uncertainties into consideration, thereby improving the REHA accuracy and robustness. In the LR, health conditions demonstrated substantial spatial disparities. Sampling sites of 28%, 48%, and 24% were subhealthy, healthy, and excellent, respectively. Findings showed that anthropogenic factors, such as dams, urban development, and fish release adversely affect river health and should be properly managed. Full article

(This article belongs to the Topic Sustainable River and Lake Restoration: From Challenges to Solutions)

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16 pages, 4538 KiB  

Open AccessArticle

Emphasizing the Role of Human Activities and Extreme Floods in Riverbed Evolution: Inspiration from Hainan Island

by Wei Zha, Xiaoqi Chen, Duofeng Wu, Siyang Yao and Zhaonan Li

J. Mar. Sci. Eng. 2025, 13(1), 37; https://doi.org/10.3390/jmse13010037 - 29 Dec 2024

Cited by 1 | Viewed by 884

Abstract

Riverbed morphology is in dynamic change due to the influences of both natural and human-induced factors. However, there is a knowledge gap in distinguishing the components caused by human activities as well as extreme flooding from the total riverbed evolution. The current study [...] Read more.

Riverbed morphology is in dynamic change due to the influences of both natural and human-induced factors. However, there is a knowledge gap in distinguishing the components caused by human activities as well as extreme flooding from the total riverbed evolution. The current study evaluated the water depth variation in the Nandu River (NR) and Wanquan River (WR) in Hainan Island in response to diverse driven factors. The results showed that the average water depth of both rivers significantly increased, but the spatial-temporal variation patterns were different. In the NR, the dominant spatial-temporal water depth variation was driven by extreme flooding, which contributed 59% to the total variance. Then, water–sediment conditions accounted for 30%, followed by direct human activities for 3.6%. However, the main spatial-temporal water depth variation patterns in the WR were 77%, driven by water–sediment conditions, 10% driven by extreme flooding, and 3.9% driven by direct human interventions, respectively. Considering the indirect effects of human activities on the water–sediment process, the total contributions of human activities on the water depth variation were 6.9% and 42.9% in the NR and WR, respectively. Due to the poor riverbed stability and worse resistance, island rivers are more fragile to extreme floods and human interventions. Our findings suggest that extreme floods usually lead to a significant increase in sediment carrying capacity, followed by severe erosion of the riverbed. In addition, combining with the decrease in sediment concentration and grainsize caused by human activities, the rebuilding effect on riverbeds would be magnified. These results highlight the important role of human activities and extreme floods in the evolution of island rivers, which can provide new insights and recommendations for river management and restoration engineering. Full article

(This article belongs to the Topic Sustainable River and Lake Restoration: From Challenges to Solutions)

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25 pages, 9659 KiB  

Open AccessArticle

Water Quality by Spectral Proper Orthogonal Decomposition and Deep Learning Algorithms

by Shaogeng Zhang, Junqiang Lin, Youkun Li, Boran Zhu, Di Zhang, Qidong Peng and Tiantian Jin

Sustainability 2025, 17(1), 114; https://doi.org/10.3390/su17010114 - 27 Dec 2024

Viewed by 848

Abstract

Water quality plays a pivotal role in human health and environmental sustainability. However, traditional water quality prediction models are limited by high model complexity and long computation time, whereas AI models often struggle with high-dimensional time series and lack physical interpretability. This paper [...] Read more.

Water quality plays a pivotal role in human health and environmental sustainability. However, traditional water quality prediction models are limited by high model complexity and long computation time, whereas AI models often struggle with high-dimensional time series and lack physical interpretability. This paper proposes a two-dimensional water quality surrogate model that couples physical numerical models and AI. The model employs physical simulation results as input, applies spectral proper orthogonal decomposition to reduce the dimensionality of the simulation results, utilizes a long short-term memory neural network for matrix forecasting, and reconstructs the two-dimensional concentration field. The simulation and predictive performance of the surrogate model were systematically evaluated through four design scenarios and three sampling dataset lengths, with a particular focus on the convection–diffusion zone and high-concentration zone. The results indicated that the model achieves high prediction accuracy for up to 7 h into the future, with sampling dataset lengths ranging from 20 to 80 h. Specifically, the model achieved an average R² of 0.92, a MAE of 0.38, and a MAPE of 1.77%, demonstrating its suitability for short-term water quality predictions. The methodology and findings of this study demonstrate the significant potential of integrating spectral proper orthogonal decomposition and deep learning for water quality prediction. By overcoming the limitations of traditional models, the proposed surrogate model provides high-accuracy predictions with enhanced physical interpretability, even in complex, dynamic environments. This work offers a practical tool for rapid responses to water pollution incidents and supports improved watershed water quality management by effectively capturing pollutant diffusion dynamics. Furthermore, the model’s scalability and adaptability make it a valuable resource for addressing intelligent management in environmental science. Full article

(This article belongs to the Topic Sustainable River and Lake Restoration: From Challenges to Solutions)

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15 pages, 5267 KiB  

Open AccessArticle

Investigating the Energy Dissipation Mechanism of Piano Key Weir: An Integrated Approach Using Physical and Numerical Modeling

by Zixiang Li, Fan Yang, Changhai Han, Ziwu Fan, Kaiwen Yu, Kang Han and Jingxiu Wu

Water 2024, 16(18), 2620; https://doi.org/10.3390/w16182620 - 15 Sep 2024

Cited by 1 | Viewed by 1004

Abstract

The enormous energy carried by discharged water poses a serious threat to the Piano Key Weir (PKW) and its downstream hydraulic structures. However, previous research on energy dissipation in PKWs has mainly focused downstream effects, and the research methods have been largely limited [...] Read more.

The enormous energy carried by discharged water poses a serious threat to the Piano Key Weir (PKW) and its downstream hydraulic structures. However, previous research on energy dissipation in PKWs has mainly focused downstream effects, and the research methods have been largely limited to physical model experiments. To deeply investigate the discharge capacity and hydraulic characteristics of PKW, this study established a PKW model with universally applicable geometric parameters. By combining physical model experiments and numerical simulations, the flow pattern of the PKW, the discharge at the overflow edges, and the variation in the energy dissipation were revealed for different water heads. The results showed that the discharge of the side wall constitutes the majority of the total discharge at low water heads, resulting in a relatively high overall discharge efficiency. As the water head increases, the proportion of discharge from the inlet and outlet keys increases, while the proportion from the side wall decreases. This change results in less discharge from the side wall and a consequent reduction in the overall discharge efficiency. The PKW exhibits superior energy dissipation efficiency under low water heads. However, this efficiency exhibits an inverse relationship with an increasing water head. The overall energy dissipation efficiency can reach 40% to 70%. Additionally, the collision of the water flows inside the outlet chamber and the mixing of the overflow jet play a primary role in energy dissipation. The findings of this study have significant implications for hydraulic engineering construction and PKW operational safety. Full article

(This article belongs to the Topic Sustainable River and Lake Restoration: From Challenges to Solutions)

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17 pages, 2162 KiB  

Open AccessArticle

Changes in the Buffer Properties of the Restored Lake Complex

by Jolanta Katarzyna Grochowska, Anna Maria Goździejewska and Renata Augustyniak-Tunowska

Sustainability 2024, 16(18), 7990; https://doi.org/10.3390/su16187990 - 12 Sep 2024

Viewed by 1021

Abstract

The objects of this study were lakes Mielenko (LM) (7.8 ha, 1.9 m), Klasztorne Małe (LKM) (13.7 ha, 20.0 m), and Klasztorne Duże (LKD) (57.5 ha, 8.5 m), located in north Poland (Kashubian Lake District). These lakes received raw sanitary and storm wastewater, [...] Read more.

The objects of this study were lakes Mielenko (LM) (7.8 ha, 1.9 m), Klasztorne Małe (LKM) (13.7 ha, 20.0 m), and Klasztorne Duże (LKD) (57.5 ha, 8.5 m), located in north Poland (Kashubian Lake District). These lakes received raw sanitary and storm wastewater, leading to extreme degradation of these water bodies. This study aimed to present changes in buffer indicators such as reaction, alkalinity, total hardness, and Ca and Mg content that occurred as an effect of their restoration using the sequential application of coagulants as an innovative approach to the phosphorus inactivation method. Sustainable phosphorus inactivation in the study lakes made it possible to achieve nutrient concentrations in the range of values typical for low-trophic lakes. A radical decrease in P concentration in the water resulted in a limitation of production processes. Moreover, after a, it was noticed that the water parameters determining its buffering properties did not show a clear vertical stratification with increasing values toward the bottom. For example, before restoration, the mean e value of alkalinity in LM fluctuated around 2.10 mval/L, and after restoration activities, the average value was 1.97 mval/L. In LKM, the mean alkalinity value in surface water layers was 2.53 mval/L, and in bottom water layers, it was 4.92 mval/L; after restoration treatments, the average alkalinity of surface water was 2.18 mval/L, and in bottom water, it was 2.99 mval/L. In the last LKD, under the influence of the applied restoration, the average alkalinity of surface waters changed from 2.21 to 2.07 mval/L, and in bottom water, it changed from 2.86 to 2.12 mval/L. The values of parameters determining the buffering properties of lake water after restoration activities allow their water to be classified as slightly or medium hard. The changes obtained can be considered beneficial because water that is too hard does not support the development of aquatic organisms, and the values obtained in the study lakes after sustainable restoration are optimal for the construction of plant walls, shells, and fish bones. Full article

(This article belongs to the Topic Sustainable River and Lake Restoration: From Challenges to Solutions)

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17 pages, 9693 KiB  

Open AccessArticle

Influence of Valvular Structures on the Flow Characteristics in an Island-Type Fishway

by Mengxue Dong, Guorui Zeng, Maosen Xu, Jiegang Mou and Yunqing Gu

Water 2024, 16(16), 2336; https://doi.org/10.3390/w16162336 - 20 Aug 2024

Viewed by 1082

Abstract

Fishways act as ecological corridors, enabling migratory fish species to surmount barriers such as weirs or dams, which are crucial for the restoration of river ecosystems. The island-type fishway is a novel design that utilizes a combination of island structures and valvular configurations [...] Read more.

Fishways act as ecological corridors, enabling migratory fish species to surmount barriers such as weirs or dams, which are crucial for the restoration of river ecosystems. The island-type fishway is a novel design that utilizes a combination of island structures and valvular configurations to dissipate the kinetic energy of water flow, decelerate the water velocity, and thus reduce the challenge faced by fish attempting to ascend the watercourse. The impact of valvular configurations on the hydrodynamic characteristics within an island-type fishway was explored. The results showed that the main high-velocity flow exhibits a nearly “S”-shaped characteristic, while a low-velocity region develops downstream of the valvular. The valvular configuration has a significant effect on the internal flow dynamics of the island-type fishway. Specifically, the smaller the valvular arc angle, the broader the high-velocity main flow becomes, and the smaller the area of the low-velocity region. When the valvular arc angle is set at 180°, the area dominated by low flow velocities maintains a coverage of over 60%. As the valvular arc angle decreases, turbulent kinetic energy rises, leading to an approximate 70% increase in the maximum turbulent kinetic energy across different water layers relative to the model with the initial angle setting. Within the range of valvular arc angles studied, an island-type fishway with a 180° valvular arc angle is most conducive to supporting the upstream migration of fish. This study can provide a reference for the further development of island-type fishways. Full article

(This article belongs to the Topic Sustainable River and Lake Restoration: From Challenges to Solutions)

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15 pages, 2698 KiB  

Open AccessArticle

Salinity Prediction Based on Improved LSTM Model in the Qiantang Estuary, China

by Rong Zheng, Zhilin Sun, Jiange Jiao, Qianqian Ma and Liqin Zhao

J. Mar. Sci. Eng. 2024, 12(8), 1339; https://doi.org/10.3390/jmse12081339 - 7 Aug 2024

Cited by 1 | Viewed by 1275

Abstract

Accurate prediction of estuarine salinity can effectively mitigate the adverse effects of saltwater intrusion and help ensure the safety of water resources in estuarine regions. Presently, diverse data-driven models, mainly neural network models, have been employed to predict tidal estuarine salinity and obtained [...] Read more.

Accurate prediction of estuarine salinity can effectively mitigate the adverse effects of saltwater intrusion and help ensure the safety of water resources in estuarine regions. Presently, diverse data-driven models, mainly neural network models, have been employed to predict tidal estuarine salinity and obtained considerable achievements. Due to the nonlinear and nonstationary features of estuarine salinity sequences, this paper proposed a multi-factor salinity prediction model using an enhanced Long Short-Term Memory (LSTM) network. To improve prediction accuracy, input variables of the model were determined through Grey Relational Analysis (GRA) combined with estuarine dynamic analysis, and hyperparameters for the LSTM model were optimized using a multi-strategy Improved Sparrow Search Algorithm (ISSA). The proposed ISSA-LSTM model was applied to predict salinity at the Cangqian and Qibao stations in the Qiantang Estuary of China, based on measured data from 2011–2012. The model performance is evaluated by mean absolute error (MAE), mean absolute percentage error (MAPE), root mean square error (RMSE), and Nash-Sutcliffe efficiency (NSE). The results show that compared to other models including Back Propagation neural network (BP), Gate Recurrent Unit (GRU), and LSTM model, the new model has smaller errors and higher prediction accuracy, with NSE improved by 8–32% and other metrics (MAP, MAPE, RMSE) improved by 15–67%. Meanwhile, compared with LSTM optimized with the original SSA (SSA-LSTM), MAE, MAPE, and RMSE values of the new model decreased by 13–16%, 15–16%, and 11–13%, and NSE value increased by 5–6%, indicating that the ISSA has a better hyperparameter optimization ability than the original SSA. Thus, the model provides a practical solution for the rapid and precise prediction of estuarine salinity. Full article

(This article belongs to the Topic Sustainable River and Lake Restoration: From Challenges to Solutions)

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