Assessing the potential impact of glacial lake outburst floods on individual objects using a high-performance hydrodynamic model and open-source data.

Glacial lake outburst floods (GLOFs) are one of the major natural hazards in certain populated mountainous areas, e.g., the Himalayan region, which may lead to catastrophic consequences including substantial loss of lives. Evaluating the potential socio-economic impact of GLOFs is essential for risk mitigation and enhancing community resilience. Yet in most of the cases, this is confronted with the challenges of limited availability of data and inaccessibility to most of the glacial lakes in the high-altitude areas. This study aims to exploit open data from different sources and high-performance hydrodynamic modelling to develop a new framework for GLOF exposure and impact assessment. In the new framework, different GLOF scenarios are created using a simple dam breach model. A high-performance hydrodynamic model is then adopted to simulate the resulting flood hydrodynamics. Necessary socio-economic information is collected and processed from multiple sources including OpenStreetMap, Google Earth, and global data products to support exposure analysis. Established depth-damage curves are used to assess the GLOF damage extents to different exposed objects and an existing fatality estimating procedure is adopted to assess the potential loss of lives. The evaluation framework is applied to the Tsho Rolpa glacial lake in Nepal. From the results, the worst GLOF scenario as considered can potentially inundate 1647 buildings, impact 5038 people and hit 123 key facilities including schools, hospitals, airports, hydropower plants, etc. It may substantially damage 900 buildings, 10.63 km2 of agricultural land and 50.9 km roads and may potentially lead to 45 deaths even if warning is available.

Distribution of antibiotic resistance genes and their association with bacteria and viruses in decentralized sewage treatment facilities.

The distribution of antibiotic resistance genes (ARGs) has been intensively studied in large-scale wastewater treatment plants and livestock sources. However, small-scale decentralized sewage treatment facilities must also be explored due to their possible direct exposure to residents. In this study, six wastewater treatment facilities in developed rural areas in eastern China were investigated to understand their risks of spreading ARGs. Using metagenomics and network analysis tools, ARGs and bacterial and viral communities were identified in the influent (INF) and effluent (EFF) samples. The dominant ARGs belonged to the bacitracin class, which are different from most of municipal wastewater treatment plants (WWTPs). The dominant hosts of ARGs are Acidovorax in bacterial communities and Prymnesiovirus in viral communities. Furthermore, a positive relationship was found between ARGs and phages. The ARGs significantly correlated with phages were all hosted by specific genera of bacteria, indicating that phages had contributed to the ARG's proliferation in sewage treatment facilities. Paying significant concern on the possible enhanced risks caused by bacteria, viruses and their related ARGs in decentralized sewage treatment facilities is necessary. ELECTRONIC SUPPLEMENTARY MATERIAL: Supplementary material is available in the online version of this article at 10.1007/s11783-021-1469-4 and is accessible for authorized users.