Water science and engineering最新文献

Harmful algal blooms (HABs) resulting from eutrophication pose a major threat to ecosystems and human health, necessitating effective control measures. Allelochemicals have shown their importance in slowing down algal proliferation due to their proven efficacy and low ecological impacts. In this study, allelopathy tea polyphenols (TPs) and β-cyclodextrin were combined to prepare slow-release algicidal microcapsules, and the diversity of microbial community in the algal inhibition process was analyzed. Results showed that TP slow-release microcapsules had strong algicidal activity. When against Microcystis aeruginosa within 20 d, their constant inhibitory rate was up to 99% compared to the control group. Microbial diversity decreased with an increase in algae density, and the species richness and diversity of algae increased under the stress of TP slow-release microcapsules. The redundancy analysis showed that the environmental factors with impacts on the abundance and diversity of bacterial communities in descending order were dissolved oxygen, pH, and temperature. This study provides a theoretical basis for the application of TP slow-release microcapsules to actual water.

The Tibetan Plateau (TP) has undergone significant warming and humidification in recent years, resulting in rapid permafrost degradation and spatiotemporal variations in hydrological processes, such as subsurface water transport, hydrothermal conversion, and runoff generation. Understanding the mechanisms of hydrological processes in permafrost areas under changing climate is crucial for accurately evaluating hydrological responses on the TP. This study comprehensively discusses the permafrost hydrological processes of the TP under changing climate. Topics include climate conditions and permafrost states, subsurface water transport under freeze–thaw conditions, development of thermokarst lakes and hydrothermal processes, and runoff response during permafrost degradation. This study offers a comprehensive understanding of permafrost changes and their hydrological responses, contributing significantly to water security and sustainable development on the TP.

Currently, more than ten ultrahigh arch dams have been constructed or are being constructed in China. Safety control is essential to long-term operation of these dams. This study employed the flexibility coefficient and plastic complementary energy norm to assess the structural safety of arch dams. A comprehensive analysis was conducted, focusing on differences among conventional methods in characterizing the structural behavior of the Xiaowan arch dam in China. Subsequently, the spatiotemporal characteristics of the measured performance of the Xiaowan dam were explored, including periodicity, convergence, and time-effect characteristics. These findings revealed the governing mechanism of main factors. Furthermore, a heterogeneous spatial panel vector model was developed, considering both common factors and specific factors affecting the safety and performance of arch dams. This model aims to comprehensively illustrate spatial heterogeneity between the entire structure and local regions, introducing a specific effect quantity to characterize local deformation differences. Ultimately, the proposed model was applied to the Xiaowan arch dam, accurately quantifying the spatiotemporal heterogeneity of dam performance. Additionally, the spatiotemporal distribution characteristics of environmental load effects on different parts of the dam were reasonably interpreted. Validation of the model prediction enhances its credibility, leading to the formulation of health diagnosis criteria for future long-term operation of the Xiaowan dam. The findings not only enhance the predictive ability and timely control of ultrahigh arch dams’ performance but also provide a crucial basis for assessing the effectiveness of engineering treatment measures.

Although big data is publicly available on water quality parameters, virtual simulation has not yet been adequately adapted in environmental chemistry research. Digital twin is different from conventional geospatial modeling approaches and is particularly useful when systematic laboratory/field experiment is not realistic (e.g., climate impact and water-related environmental catastrophe) or difficult to design and monitor in a real time (e.g., pollutant and nutrient cycles in estuaries, soils, and sediments). Data-driven water research could realize early warning and disaster readiness simulations for diverse environmental scenarios, including drinking water contamination.