Grade evaluation of black-odorous urban rivers in the Greater Bay Area of China using an improved back propagation (BP) neural network.

With the rapid development of urbanization, the urban water environment is receiving continuous attention. It is necessary to understand water quality in a timely manner and make a reasonable comprehensive evaluation. However, existing black-odorous water grade evaluation guidelines are not sufficient. Understanding the changing situation of black-odorous water in urban rivers is a growing concern, especially in real-world scenarios. In this study, a BP neural network combined with the fuzzy membership degree was applied to evaluate the black-odorous grade of urban rivers in Foshan City, which is within the Greater Bay Area of China. The optimal 4 × 11 × 1 topology structure of the BP model was constructed by taking the dissolved oxygen (DO), ammonia nitrogen (NH3-N), chemical oxygen demand (COD), and total phosphorus (TP) concentrations as input water quality indicators. There was almost no occurrence of black-odorous water in the two public rivers outside the region in 2021. Black-odorous water was most significant in 10 urban rivers, with grade IV and grade V occurring over 50% of the time in 2021. These rivers had three features, i.e., parallel with a public river, beheaded, and close proximity to Guangzhou City, the provincial capital of Guangdong. The results of the grade evaluation of the black-odorous water found basically matched those of the water quality assessment. The existence of some inconsistencies between the two systems justified the necessity to expand and extend the number of employed indicators and grades in the present guidelines. The results confirm the capability of the BP neural network combined with the fuzzy-based membership degree in the quantitative grade evaluation of black-odorous water in urban rivers. This study makes a step forward in understanding the grading of black-odorous urban rivers. The findings can provide a reference for local policy-makers regarding the priority of practical engineering projects in prevailing water environment treatment programs.

A procedure for comparing the ecological status and transformation measures in an anthropized coastal area.

The overall vitality and quality of the coastline can be improved through ecological transformation; ecological status assessment can scientifically guide this modification by putting forward a transformation plan for the coastline. This study took the Shenzhen Bay area between Hong Kong and Shenzhen as the study area to build an index system and combined it with quantitative and qualitative methods by designing the code of data processing, calculation, and analysis through the MATLAB platform, with the goal being to put forward the directions and suggestions for coastline transformation based on the analysis of results. The results and conclusions are as follows: (1) The key aspects of the ecological transformation of the Shenzhen Bay Coastline are water quality, coastal wetland restoration, landscape diversity, beach stability, and infrastructure improvement. (2) Actions to promote these aspects include overall shoreline control of water pollution, cultural landscape implantations, the improvement of existing infrastructure, and the restoration of selected beach sand regions, mangrove wetlands, and eroded shorelines. Suggestion includes the critical support which comes from the public needs for information acquisition and science education, in addition with the policy and management, all should be formulated into the transformation plan. The index system can be applied to other regions at home and abroad, and the results and conclusions based on the index system could also provide criteria for planning the ecological transformation process.

Spatiotemporal Trends, Sources and Ecological Risks of Heavy Metals in the Surface Sediments of Weitou Bay, China.

Heavy metals are extremely harmful materials to marine ecosystems and human health. To determine the anthropogenic contributions and ecological risks in Weitou Bay, China, the spatiotemporal variations in the concentrations of heavy metals in surface sediment were investigated during spring 2008 and 2017. The results indicated that high concentrations of pollutants were generally located near the river mouths and along the coast of industrial areas. Principal component analysis indicated that heavy metal contents were mainly affected by industrial waste drainage, urban development, natural weathering and erosion, and interactions between organic matter and sulfides. The potential ecological risk assessment demonstrated that, in 2008, 82% of the sampling sites were at low risk, while 18% were at moderate risk. The situation had deteriorated slightly by 2017, with 73%, 18%, and 9% of stations in Waytou Bay at low, moderate, and very high risk, respectively. Cd was the most harmful metal, followed by Hg. These two elements accounted for more than 80% of the potential ecological risk index (RI) value. The present work analyzed the source of heavy metals, identified the major pollution elements and high risk areas, and provides guidance for pollution control and ecological restoration in Weitou Bay.

Quantitative estimation of sea surface temperature increases resulting from the thermal discharge of coastal power plants in China.

The operation of coastal nuclear power plants and thermal power plants (CNATPPs) can cause regional sea surface temperature (SST) increases. To assess their effects on coastal ecosystems, the scope and extent of their impacts must be understood. We aimed to quantitatively assess the SST increases caused by thermal discharge under climate warming by comparing SSTs between control and test groups and among different offshore buffer zones based on daily MODIS SST data from 2002 to 2017. The results showed that (1) a good correlation occurred between the CNATPP installed capacity and SST increase in the 0-2 km offshore waters; (2) the SST increase caused by thermal discharge was the largest in summer and the smallest in winter; and (3) the effect of thermal discharge occurred within 2 km offshore when the installed capacity exceeded 2000 MW and extended to 5 km when it reaches more than 4000 MW.

Quantitative analysis of the factors influencing the dispersion of thermal pollution caused by coastal power plants.

In recent years, to meet the needs of economic development, an increasing number of coastal nuclear power plants and thermal power plants (CNATPPs) have used seawater as the source and sink of cooling water. Considering six CNATPPs along the coast of China, based on the model of conservation of mass and energy for an environmental fluid medium, this study quantitatively evaluates the thermal diffusion capacity (TDC) and contribution rate of factors influencing the thermal plume. The results showed that (1) the current velocity, shoreline topography and horizontal diffusion coefficient are linearly correlated with the TDC. The former two variables were the same and the largest and are highly sensitive parameters; (2) the average contribution rates of the current velocity and shoreline topography were the largest at 0.32, and that of the water depth ranged from 0 to 0.28; (3) the shoreline topography close to the outfall affects the TDC of the emitting source of CNATPPs, rather than the geographical location; and (4) this study can provide a comprehensive measurement tool for the planning, site selection and layout of CNATPPs to reduce the impact of their thermal pollution on aquatic organisms in the receiving water. Considering the TDC and thermal sensitivity of marine organisms, it might be assumed that the same heat and the same volume of thermal pollution may have smaller impacts on marine organisms in the East China Sea than in the South China Sea.

Landslide Susceptibility Prediction Modeling Based on Remote Sensing and a Novel Deep Learning Algorithm of a Cascade-Parallel Recurrent Neural Network.

Landslide susceptibility prediction (LSP) modeling is an important and challenging problem. Landslide features are generally uncorrelated or nonlinearly correlated, resulting in limited LSP performance when leveraging conventional machine learning models. In this study, a deep-learning-based model using the long short-term memory (LSTM) recurrent neural network and conditional random field (CRF) in cascade-parallel form was proposed for making LSPs based on remote sensing (RS) images and a geographic information system (GIS). The RS images are the main data sources of landslide-related environmental factors, and a GIS is used to analyze, store, and display spatial big data. The cascade-parallel LSTM-CRF consists of frequency ratio values of environmental factors in the input layers, cascade-parallel LSTM for feature extraction in the hidden layers, and cascade-parallel full connection for classification and CRF for landslide/non-landslide state modeling in the output layers. The cascade-parallel form of LSTM can extract features from different layers and merge them into concrete features. The CRF is used to calculate the energy relationship between two grid points, and the extracted features are further smoothed and optimized. As a case study, the cascade-parallel LSTM-CRF was applied to Shicheng County of Jiangxi Province in China. A total of 2709 landslide grid cells were recorded and 2709 non-landslide grid cells were randomly selected from the study area. The results show that, compared with existing main traditional machine learning algorithms, such as multilayer perception, logistic regression, and decision tree, the proposed cascade-parallel LSTM-CRF had a higher landslide prediction rate (positive predictive rate: 72.44%, negative predictive rate: 80%, total predictive rate: 75.67%). In conclusion, the proposed cascade-parallel LSTM-CRF is a novel data-driven deep learning model that overcomes the limitations of traditional machine learning algorithms and achieves promising results for making LSPs.

Dissipation Theory-Based Ecological Protection and Restoration Scheme Construction for Reclamation Projects and Adjacent Marine Ecosystems.

According to the 2017 results of the Special Inspector of Sea Reclamation, a substantial number of idle reclamation zones existed in 11 provinces (cities) along the coast of China. To improve the protection level of coastal wetlands and strictly control reclamation activities, it is necessary to carry out ecological restoration of reclamation projects and adjacent marine ecosystems. The characteristics of Guanghai Bay and its reclamation project are typical in China's coastal areas, making it an optimal representative site for this study. The dissipative structure and entropy theory was used to analyze ecological problems and environmental threats. The analytic hierarchy process was applied to determine the order of the negative entropy flow importance. The entropy increase and decrease mechanism was used to determine an ecological protection and restoration scheme for the reclamation, including the reclamation of wetland resource restoration, shoreline landscape restoration, environmental pollution control, and marine biological resource restoration. Finally, based on system logic, a typical ecological restoration system was constructed east of Guanghai Bay, with the mangrove wetland area as the model in the north and the artificial sandbeach recreation area as the focus in the south.

Regional Rainfall Warning System for Landslides with Creep Deformation in Three Gorges using a Statistical Black Box Model.

Establishing an efficient regional landslide rainfall warning system plays an important role in landslide prevention. To forecast the performance of landslides with creep deformation at a regional scale, a black box model based on statistical analysis was proposed and was applied to Yunyang County in the Three Gorges Reservoir area (TGRA), China. The data samples were selected according to the characteristics of the landslide displacement monitoring data. Then, the rainfall criteria applied to different time periods were determined by correlation analysis between rainfall events and landslides and by numerical simulation on landslide movement under certain rainfall conditions. The cumulative rainfall thresholds that were determined relied on the displacement ratio model, which considered landslide scale characteristics and the statistical relationship between daily rainfall data and monthly displacement data. These thresholds were then applied to a warning system to determine a five-level warning partition of landslides with creep deformation in Yunyang County. Finally, landslide cases and displacement monitoring data were used to validate the accuracy of the model. The validation procedure showed that the warning results of the model fit well with actual conditions and that this model could provide the basis for early warning of landslides with creep deformation.

Measuring Land Change in Coastal Zone around a Rapidly Urbanized Bay.

Urban development is a major cause for eco-degradation in many coastal regions. Understanding urbanization dynamics and underlying driving factors is crucial for urban planning and management. Land-use dynamic degree indices and intensity analysis were used to measure land changes occurred in 1990, 2002, 2009, and 2017 in the coastal zone around Quanzhou bay, which is a rapidly urbanized bay in Southeast China. The comprehensive land-use dynamic degree and interval level intensity analysis both revealed that land change was accelerating across the three time intervals in a three-kilometer-wide zone along the coastal line (zone A), while land change was fastest during the second time interval 2002⁻2009 in a separate terrestrial area within coastal zone (zone B). Driven by urbanization, built-up gains and cropland losses were active for all time intervals in both zones. Mudflat losses were active except in the first time interval in zone A due to the intensive sea reclamation. The gain of mangrove was active while the loss of mangrove is dormant for all three intervals in zone A. Transition level analysis further revealed the similarities and differences in processes within patterns of land changes for both zones. The transition from cropland to built-up was systematically targeted and stationary while the transition from woodland to built-up was systematically avoiding transition in both zones. Built-up tended to target aquaculture for the second and third time intervals in zone A but avoid Aquaculture for all intervals in zone B. Land change in zone A was more significant than that in zone B during the second and third time intervals at three-level intensity. The application of intensity analysis can enhance our understanding of the patterns and processes in land changes and suitable land development plans in the Quanzhou bay area. This type of investigation is useful to provide information for developing sound land use policy to achieve urban sustainability in similar coastal areas.

Effects of the thermal discharge from an offshore power plant on plankton and macrobenthic communities in subtropical China.

The ecological impact of thermal discharge has become an important issue in the field of marine and environmental protection. We focused on the effects of thermal discharge on seawater temperature and biological communities based on data from before (2006) and after (2013-2014) the construction of a power plant. The thermal discharge induced stratification, which resulted in changes in the vertical hydrodynamic conditions. Stratification combined with elevated temperatures significantly affected the phytoplankton abundance and community structure. Elevated seawater temperatures decreased the chlorophyll-a concentrations by 34% and 63%, at the surface and bottom, respectively. The elevated seawater temperature at the bottom might not be high enough to significantly affect the macrobenthos, but significantly affected the phytoplankton and zooplankton communities. Because these communities serve as food for the macrobenthic community, their changes resulted in growth of the macrobenthos. Furthermore, this effect induced macrobenthic community succession, resulting in decreased species diversity and increased dominance.

A web-based GPS system for displacement monitoring and failure mechanism analysis of reservoir landslide.

It is important to monitor the displacement time series and to explore the failure mechanism of reservoir landslide for early warning. Traditionally, it is a challenge to monitor the landslide displacements real-timely and automatically. Globe Position System (GPS) is considered as the best real-time monitoring technology, however, the accuracies of the landslide displacements monitored by GPS are not assessed effectively. A web-based GPS system is developed to monitor the landslide displacements real-timely and automatically in this study. And the discrete wavelet transform (DWT) is proposed to assess the accuracy of the GPS monitoring displacements. Wangmiao landslide in Three Gorges Reservoir area in China is used as case study. The results show that the web-based GPS system has advantages of high precision, real-time, remote control and automation for landslide monitoring; the Root Mean Square Errors of the monitoring landslide displacements are less than 5 mm. Meanwhile, the results also show that a rapidly falling reservoir water level can trigger the reactivation of Wangmiao landslide. Heavy rainfall is also an important factor, but not a crucial component.

[A conjunctival pulling-back technique for treatment of serious symblepharon].

OBJECTIVE: To evaluate a new technique for treatment of the symblepharon caused by physical and chemical burn. METHODS: Thirty-eight patients with 40 eyes were undergoing the treatment. It was carried out to reconstruct the conjunctival fornix by pulling the remained conjunctive backward from the corneal limbus in serious stages. RESULTS: Thirty-eight patients (40 eyes) were treated with this technique, with the successful results of 13 patients (13 eyes) in 2 times, 19 patients (21 eyes) in 3 and 6 patients (6 eyes) in 1. Only one case was failure. CONCLUSION: The above mentioned technique could be a safe and effective way for treatment of symblepharen.