Vietnam is located in the tropical monsoon region and it often faces many types of extreme weather events, especially storms and droughts. In addition to the effect of climate change, extreme weather events have been becoming more complicated and difficult to predict, causing heavy losses to many areas and economic sectors of the country. These problems impose a great threat to the country to achieve its socio-economic targets and sustainable development goals. This study uses a Riparian approach integrated with two-stage Hsiao method using a panel dataset from 2000–2018 to examine the impact of extreme weather events and climate change on the output of agriculture and fishery enterprises in the Central and Central Highlands regions of Vietnam. Findings from the study indicate that extreme weather events and climate change have a negative impact on agriculture and fishery enterprises in the regions. Specifically, the model results show that the value-added loss to agriculture and fishery enterprises as the impact of extreme weather events and climate change may escalate from billion VND 3597.72 to 18,891.2 under different climate change scenarios. The results also indicate the impact of various factors regarding extreme weather events and climate change on the efficiency of enterprises in the study area. Findings from this study provide insights on the impacts of extreme weather events and climate change on value-added of enterprises in the study regions and help to propose appropriate solutions to adapt and mitigate their impacts in the future.

Understanding changes in precipitation extremes is critical for designing mitigation measures for the potential implications of a warming climate. This study assessed changes in the magnitude and frequency of precipitation extremes over Vietnam using high-quality gridded daily precipitation observations from 1980 to 2010. The annual maxima precipitation was analyzed to detect historical changes in the magnitude of precipitation extremes, while the number of heavy precipitation events, defined using the peak-over-threshold approach, was used to assess changes in the frequency of precipitation extremes. We found a strong signal of changes in the frequency of heavy precipitation, with 28.3% of Vietnam’s landmass exhibiting significant increasing trends. The magnitude of annual maxima precipitation shows a mixed pattern of changes, with less than 10% of Vietnam’s landmass exhibiting significant (both increasing and decreasing) trends. To identify possible mechanisms driving changes in precipitation, we assessed the relationship between inter-annual variations in precipitation extremes and climate variability represented by the teleconnection patterns of the Northern Hemisphere. Using five climate indices, we found that teleconnections across the Indian and Pacific Oceans have implied large control over the characteristics of precipitation extremes across Vietnam, with up to 30% of Vietnam’s landmass exhibiting a significant relationship.

Remote sensing of precipitation has been paid attention to recently for improving water resources estimation and hydrological applications. This study aims to assess one of the latest satellite rainfall product – Integrated Multi-satelliE Retrievals for GPM (IMERG) for Northern Vietnam. This study used the Tropical Rainfall Measurement Mission (TRMM), which is the predecessor of IMERG as a benchmark. The work consists of two parts: (i) comparison of IMERG and TRMM with rain gauge at a daily time scale; (ii) simulation of daily streamflow with IMERG-based and TRMM-based hydrological models. Four different precipitation metrics have been used to evaluate the IMERG and TRMM datasets, and the Soil and Water Assessment Tool (SWAT) hydrological model has been used in simulating daily streamflow at two river basins. The results indicated that IMERG did not significantly improve than TRMM when compared them with rain gauge. However, IMERG-based SWAT models were comparable with rain-gauge-based SWAT models in simulating daily streamflow. The TRMM-based SWAT models only produced reasonable results at one basin. Overall, the IMERG rainfall dataset can be an alternative rainfall dataset for Northern Vietnam with respect to estimated rainfall as well as input for hydrological simulation. This study provides useful information for environmental assessment, water resources management, and decision-making with support of remote sensing datasets.

This study focuses on developing and validating a measurement scale to assess the factors influencing sustainable tourism development, with Long An province as a case study. Based on theoretical foundations and data collected through qualitative discussions with ten experts and a quantitative survey of 500 tourists, the study identifies six key factors: tourism resources, tourism infrastructure, tourism types, regulatory policies, community participation, and tourism demand. Exploratory Factor Analysis (EFA) reveals a total variance explained of 84.967%, confirming high convergent and discriminant validity of the factors. The measurement scales achieve a Cronbach’s Alpha coefficient exceeding 0.9, ensuring reliability and internal consistency. This study contributes to the theoretical understanding of sustainable tourism development by providing a comprehensive framework for future research. Additionally, the developed measurement scales serve as a valuable reference for researchers and practitioners seeking to enhance tourism competitiveness in diverse contexts beyond the study’s focal area. The research findings offer essential scientific tools to support strategic planners and tourism enterprises in formulating effective development strategies, thereby strengthening the theoretical foundation of sustainable tourism while providing practical insights to improve the competitiveness and sustainability of tourist destinations.