Underpinned by the ultrahigh-core rockfill dam at the Nuozhadu Hydropower Station, comprehensive studies and engineering practices have been conducted to address several critical challenges: coordination of seepage deformation in dam materials, prevention and control of high-water-pressure seepage failure, static and dynamic deformation control, and construction quality monitoring. Advanced technologies have been developed for modifying impermeable soil materials and utilizing soft rocks. Constitutive models and high-performance fine computational methods for dam materials have been improved, along with innovative seismic safety measures. Additionally, a “Digital Dam” and an information system for monitoring the construction quality were implemented. These efforts ensured the successful construction of the Nuozhadu Dam, making it the tallest dam in China and the third tallest dam in the world upon completion. This achievement increased the height of core dams in China by 100 m and established a design and safety evaluation framework for ultrahigh-core rockfill dams exceeding 300 m in height. Furthermore, the current safety monitoring results indicate that the Nuozhadu Dam is safe and controllable.

The planning and treatment of wastewater discharged into rivers and seas is vital for tourism, domestic water supply, and other key sectors. This study used the MIKE 21 model to evaluate water quality trends and the assimilative capacity of the Vu Gia River estuary and the major reservoirs in Da Nang, considering future pollution loads and climate change scenarios (RCP8.5). Key parameters assessed include DO, BOD₅, COD, and Coliform. Results show a general decline in water quality (WQI) from 2019 to 2030 and again by 2070, with DO and BOD₅ contributing most to pollution. While COD and Coliform remained within acceptable limits (WQI > 75), the Phu Loc River had the lowest WQI (66.0–62.2). Other affected areas include the Han River (downstream and upstream) and the Cu De River. Reservoirs like Dong Nghe and Hoa Trung maintained better water quality (WQI > 80), though a downward trend was still observed.

Among natural disasters, flash floods are the most destructive events, causing significant damage to the economy and posing a serious threat to human life and property. Comprehensive risk assessment of these sudden floods is a key strategy to mitigate their impact. Accurate analysis of flash flood hazards can greatly enhance prevention efforts and inform critical decision-making processes, ultimately improving our ability to protect communities from these fast-onset disasters. This study analyzed the driving forces of flash flood disaster-causing factors in Heilongjiang Province. Meanwhile, nine different categories of variables affecting the occurrence of flash floods were selected, and the degree of influence of each driving factor on flash floods was quantitatively analyzed, and the driving force analysis of the driving factors of flash floods in Heilongjiang Province was carried out by using the geographic probe model. This paper employs an uncertainty approach, utilizing a statistical-based interval weight determination technique for evaluation indices and a two-dimensional information-based interval number sorting method. These methodologies are combined to construct a comprehensive flash flood risk assessment model. On this basis, the model was implemented in six regions within China's Heilongjiang province to evaluate and prioritize flash flood risks. The resulting risk ranking for these areas was as follows: Bayan > Shuangcheng > Boli > Suibin > Hailun > Yian. The findings demonstrate that the interval number-based evaluation method effectively handles uncertainty, providing a more reliable risk grading system. This approach, by leveraging modern scientific advances and risk quantification techniques, is crucial for improving disaster management and mitigating flash flood impacts.

The present study describes a river channel management method for restoring riverine environments degraded by sand mining in rivers. Specifically, three conditions that must be met for a restored river channel in the lower reach of the Kelani River in Sri Lanka were proposed: (1) flood discharge capacity of the channel for a given flood, (2) prevention of saltwater intrusion, and (3) creation of a diverse physical environment. The allowable mining volume satisfies the three conditions, while continuing to mine sand was discussed based on the sediment budget calculations in the target river reach. In this case, the amount of sediment stored in the target reach and its variation are determined by the amount of sediment supplied to the target reach, the amount of sediment discharged from the target reach to the sea, and the amount of sediment excavated. This means that the dynamic equilibrium channel of the target reach is determined by the amount of sediment supplied and the amount of sediment excavated. The amount of sand mined when the dynamic equilibrium channel meets the three conditions of the restored channel is a candidate for the allowable amount of sand mined. One of these, the most desirable one, is set as the allowable mining volume. As described above, we proposed a method to develop a restoring reach taking the sediment budget and associated hydraulic and hydro morphological conditions in the target reach into consideration.

This study aims to develop and expand a new perspective on ecological value realization (EVR) and provide policy recommendations for marine ecological value realization (MEVR) based on Carbon Trading. Currently, the immaturity of EVR calculation methods and difficulties in determining the price of ecological products pose significant challenges to ecological value trading. By employing mathematical models and logical reasoning, this study proposes a novel framework for EVR, illustrated through several diagrams. According to this framework, ecological value is not static but fluctuates with factors such as human well-being (HV) or gross domestic product (GDP). Therefore, ecological value should be determined by an exchange market rather than solely relying on hypothetical calculation methods. Consequently, carbon trading cases are crucial in understanding ecological value. Based on the analysis of blue carbon (BC) trading cases, including the lack of international BC exchanges, challenges in carbon sink projects, and the Free Rider Effect, this paper identifies current issues in MEVR and BC trading in China. To address these challenges, we propose integrating carbon trading databases with evaluations of ecological protection and restoration projects, along with BC trading data, to calculate ecological value. Additionally, we recommend increasing the supply of BC products in both national carbon trading markets and voluntary markets, promoting the internationalization of BC accounting, addressing the Free Rider Effect through government actions and market mechanisms, attracting more foreign investment in BC enhancement projects, and formulating a BC enhancement plan during marine resource development.

Values of individuals and organizations involved in decision-making processes form the basis for prioritizing outcomes in water governance. The novelty of this study lies in applying values to a specific decision-making context. It aims to assess the prioritized water governance outcomes and the underlying value systems shaping the actions of the primary water utility responsible for water governance in Delhi, the Delhi Jal Board (DJB). The paper will critically examine the policies and acts of the DJB that drive water governance in Delhi at present, utilizing a values-based framework in conjunction with secondary literature and expert interviews, to draw a picture of the values reflected. The study does not substantiate the notion of economic values dominating the water-related decisions; rather, recent policy guidelines indicate prioritization of equitable and fair distribution of water. Findings of this paper show that making the values explicit is largely disregarded in formulating water acts and policies, and values are never elucidated in the public domain, doing which can encourage water policies and practices that are socially, economically, and ecologically viable in the long run. It is expected that this paper will generate a discussion on water values being an integral part of water governance discourses.

Located in Nanhai Town, Songzi City, Hubei Province, Xiaonanhai Lake is the largest natural lake in Songzi. It was once severely polluted due to the discharge of urban and rural domestic sewage, disorderly development of agricultural planting, unregulated aquaculture, and poultry farming. However, relevant estimations of the pollutant content in its sediment have not been carried out. This study analyzed the spatial patterns of heavy metal pollution and eutrophication at 36 water sampling sites in the Xiaonanhai Lake area, focusing on eight heavy metals: Cd, Cr, Cu, Ni, As, Pb, Hg, and Zn. The nutrient status of the lake area was evaluated using the nitrogen-phosphorus comprehensive pollution index, and heavy metal pollution status of the lake area was evaluated using geo-accumulation and the potential ecological risk index. Spatial autocorrelation analysis revealed the spatial correlation and aggregation of eutrophication levels in Xiaonanhai Lake. The results showed that the overall trophic state of the Xiaonanhai Lake area was moderate eutrophication, with a gradually decreasing eutrophication level from north to south. The Chengnan Wastewater Treatment Plant in the northern part of the lake area and surface source pollution from aquaculture were the main nitrogen and phosphorus sources. The overall ecological risk index of heavy metal pollution was medium and gradually weakened from north to south, consistent with the thickness of the bottom mud. The heavy metal pollution load was mainly precipitated from the bottom mud in the lake area. The eutrophication and heavy metal pollution levels in the lake area showed significant positive spatial autocorrelation, the influence range of the regional eutrophication level was small, and the spatial heterogeneity of the eutrophication and heavy metal pollution levels in Xiaonanhai Lake was relatively high. The northern part of the lake was a hotspot (high/high aggregation) of eutrophication (p < 0.01) while the southern part was a cold spot (low/low concentration; p < 0.05). The middle and northern part of the lake area was the hot spot (high/high concentration) of heavy metal pollution level (p < 0.1) while the southern part was the cold spot (low/low concentration; p < 0.1). Therefore, when carrying out water environment management in Xiaonanhai Lake, the northern area and the middle area should be prioritized for eutrophication prevention and control and dredging.

The Kulsi River basin, situated in the South Kamrup district of Assam, India, is noted for its rich fish diversity and significant deposits of Pre-Cambrian quality sand in its headstreams. These deposits gradually make their way downstream, acting as a catalyst for local livelihoods. However, the intricate ecosystem fostered by the Kulsi River is under significant ecological threat due to urbanization, population growth, and associated environmental stressors such as rampant sand mining, deforestation, and soil erosion. These changes pose a risk to the basin's ecological sustainability, increasing its vulnerability. This study employs the Analytical Hierarchical Process (AHP), a GIS-based multi-criteria decision analysis method, to assess and monitor the basin's ecological vulnerability. It seeks sustainable methods to rejuvenate ecological sustainability in the basin. Criteria such as slope, C factor, stream density, proximity to roads, soil erosion, literacy rate, soil erodibility factor, and rainfall were analyzed. The findings reveal varied vulnerability across the Kulsi River basin, with 6.24% of the area classified as extremely vulnerable, 25.56% as highly vulnerable, 24.56% as moderately vulnerable, 32.67% as low vulnerable, and 10.94% as non-vulnerable. Highly vulnerable zones are notably in newly developed suburban areas adjacent to national highways. However, non-vulnerable zones are primarily in the upper river course and its surrounding regions in the southern direction. The findings highlight the urgent need for targeted mitigation strategies to address the adverse effects of human activities and natural processes on the basin's ecological integrity. This study maps the vulnerability of the Kulsi River basin. It provides valuable insights into sustainable management and hazard mitigation. The study highlights the link between human activity, ecological sustainability, and geomorphological hazards.

Detecting the complexity of natural systems, such as hydrological systems, can help improve our understanding of complex interactions and feedback between variables in these systems. The correlation dimension method, as one of the most useful methods, has been applied in many studies to investigate the chaos and detect the intrinsic dimensions of underlying dynamic systems. However, this method often relies on manual inspection due to uncertainties from identifying the scaling region, making the correlation dimension value calculation troublesome and subjective. Therefore, it is necessary to propose a fast and intelligent algorithm to solve the above problem. This study implies the distinct windows tracking technique and fuzzy C-means clustering algorithm to accurately identify the scaling range and estimate the correlation dimension values. The proposed method is verified using the classic Lorenz chaotic system and 10 streamflow series in the Daling River basin of Liaoning Province, China. The results reveal that the proposed method is an intelligent and robust method for rapidly and accurately calculating the correlation dimension values, and the average operation efficiency of the proposed algorithm is 30 times faster than that of the original Grassberger-Procaccia algorithm.

Freshwater essential for civilization faces risk from untreated effluents discharged by industries, agriculture, urban areas, and other sources. Increasing demand and abstraction of freshwater deteriorate the pollution scenario more. Hence, water quality analysis (WQA) is an important task for researchers and policymakers to maintain sustainability and public health. This study aims to gather and discuss the methods used for WQA by the researchers, focusing on their advantages and limitations. Simultaneously, this study compares different WQA methods, discussing their trends and future directions. Publications from the past decade on WQA are reviewed, and insights are explored to aggregate them in particular categories. Three major approaches, namely—water quality indexing, water quality modeling (WQM) and artificial intelligence-based WQM, are recognized. Different methodologies adopted to execute these three approaches are presented in this study, which leads to formulate a comparative discussion. Using statistical operations and soft computing techniques have been done by researchers to combat the subjectivity error in indexing. To achieve better results, WQMs are being modified to incorporate the physical processes influencing water quality more robustly. The utilization of artificial intelligence was primarily restricted to conventional networks, but in the last 5 years, implications of deep learning have increased rapidly and exhibited good results with the hybridization of feature extracting and time series modeling. Overall, this study is a valuable resource for researchers dedicated to WQA.