The Lancang–Mekong River basin, as an important transboundary river in Southeast Asia, is challenged by rapid socio-economic development, especially the construction of hydropower dams. Furthermore, substantial factors, such as terrain, rainfall, soil properties and agricultural activity, affect and are highly susceptible to soil erosion and sediment yield. This study aimed to estimate average annual soil erosion in terms of spatial distribution and sediment deposition by using the revised universal soil loss equation (RUSLE) and GIS techniques. This study also applied remote sensing and available data sources for soil erosion analysis. Annual soil erosion in most parts of the study area range from 700 to 10,000 t/km2/y with a mean value of 5350 t/km2/y. Approximately 45% of the total area undergoes moderate erosion. Moreover, the assessments of sediment deposition and erosion using the modified RUSLE and the GIS techniques indicate high sediment erosion along the flow direction of the mainstream, from the upper Mekong River to the Mekong Delta. The northern part of the upper Mekong River and the central and southern parts of the lower Mekong River are the most vulnerable to the increase in soil erosion rates, indicating sediment deposition.
Thailand currently ranks third among the most water-intensive countries in the world. The percentage shares of water demand in the country's agriculture, manufacturing, and service sectors, which are major economic sectors, are 75%, 3%, and 5%, respectively. With the continuous growth of the economy, the demand for water is steadily rising, while the expansion of water supply remains constrained by several factors and the water supply is also affected by climate change. This study uses the input-output model to examine the relationship between water usage and the economic system in Thailand in 2010. The constructed input-output model is the integration of the Leontief inverse matrix, the matrix of water usage, and the details of the gross domestic product (GDP). The model indicates the linkage between GDP expansion and water demand in both direct and indirect usage. The computation result obtained from the model indicates that the agricultural sector is the major water user, with its ratio of direct water use being the highest. The manufacturing sector records the highest ratio of indirect water use, which is influenced by its supply chain comprising the agriculture and service sectors. This model and its results may serve as the main foundation for the design of economic and environmental policies oriented toward optimizing water demand and supply. The model can also be extended and enriched with detailed mechanisms of economic behavior to allow further complex analyzes such as water pricing policies.
This study aims to develop more inclusive and sustainable waste management practices to be implemented in Bang Chalong Housing, a model community with unsatisfactory waste separation and recycling rate. The extended theory of planned behavior was employed to investigate the effect of attitude, subjective norm, perceived behavioral control, knowledge, and situational factors on household waste separation intention and behavior, using structural equation modeling as a tool. Based on the questionnaire responses of 321 residents, the house owner’s status exhibited a considerable impact on waste-sorting behavior. Knowledge (β = 0.653; p < 0.001) and subjective norm (β = 0.160; p < 0.05) were two significant predictors of the respondents’ intention, which showed a strong influence on household waste separation behavior (β = 0.804; p < 0.001). Various waste management scenarios were also evaluated through material flow analysis and life cycle assessment. Installing a waste-sorting plant in addition to the current approach (recycling and landfilling) could annually reduce 26.4 tons of solid waste from being landfilled and mitigate GHG emissions by up to 47.4 tons CO2 equivalent. Finally, the implications of these results on designing interventions and amending waste management schemes were discussed.
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