Water security and quality are among the six focal areas of the Eighth Phase of the International Hydrological Program. Several cities are struggling to meet water demand due to factors such as urbanization, pollution, and disasters. Consequently, water scarcity impacts various sectors, including human health and socio-economic development. Against this backdrop, we conducted research to examine the current state of water resources and the factors contributing to water scarcity in the Kathmandu Valley (KV), currently experiencing acute water shortages. The study employed three primary data collection methods, observation, interviews, and secondary data analysis, followed by qualitative analysis to achieve its research objectives. We analyzed the findings using the framework of the three pillars of Urban Water Security (UWS): water resource security, water environment security, and water disaster security. The dimensions of water quantity and quality interconnect with these pillars, which define the manifestations of water insecurity. The analysis showed that the KV significantly weakens all three of the UWS pillars. Through this research, the author developed a novel framework (PUMI): pollution, urbanization, management, and investment are root causes of water insecurity in the KV. These four factors identified and analyzed specific challenges such as inadequate building permit regulations, donor-driven investments, and poor management practices.

The application of big data in early warning systems (EWS) for multi-hazard risk management is becoming increasingly popular due to its enormous potential. Nevertheless, despite noteworthy achievements, there are still several enduring obstacles. This study aims to evaluate the advantages and difficulties through a comprehensive SWOT (strengths, weaknesses, opportunities, threats) analysis and the use of existing literature. An extensive literature analysis was conducted, incorporating perspectives of researchers from diverse background investigating both technical and social elements. The study results showed several notable strengths, such as unmatched accuracy and comprehensiveness, the incorporation of several data sources to improve prediction and forecasting, and the exploitation of up-to-the-minute data. On the other hand, problems, such as insufficient monitoring of hazards and a scarcity of interconnected sensors, especially common in less developed countries, were recognized. Lack of adequate coverage leaves a substantial percentage of the population vulnerable to disaster risks as a result of inadequate early warning systems. Ultimately, although big data offers significant possibilities, its complete capacity remains unexplored in the least developing nations due to existing obstacles, such as shortage of skilled worker, data accuracy and privacy which can be solved by enhancing technology education, capacity building, and practice. The objective of this study is to help such nations identify and overcome underlying challenges by implementing suitable measures.

Citizen science is increasingly significant in scientific research and disaster management, especially as disaster risks intensify globally. While numerous studies confirm the value of citizen science programs in mitigating disaster risks, further research is needed to understand how these programs contribute to disaster risk reduction and to identify indicators of their success. This study investigates key success factors and challenges of citizen science programs through a case study of Safecast, a radiation monitoring initiative in Japan. Six critical factors were identified: active participation, knowledge production, data accuracy, expansion of spatial and temporal data, and citizen-related outcomes. Safecast’s broad engagement of participants, open-source data collection, and significant contributions to scientific research and policy decisions have been key to its effectiveness. In addition, the rigorous data accuracy measures and data expansion over time and space have further supported disaster risk reduction efforts. However, challenges remain in maintaining participant engagement, addressing the digital divide, and ensuring data consistency. Safecast exemplifies how citizen science can bridge grassroots data collection with formal disaster management, highlighting its potential to strengthen disaster resilience and empower communities.