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This paper concentrates on studying the application of fuzzy soft sets and the construction of an algorithm to identify a better approach flood alarm prediction model that applies to eight selected provinces sites in Northern Thailand. Finally, an example is provided to show which of the methods can be successfully used to predict potential flood in the future. [ABSTRACT FROM AUTHOR]

This paper reports fruitful utilization of satellite-based MODIS optical data on sea-surface Chl-a concentration determination and mapping over Upper Gulf of Thailand (UGoT) region during 2010-2012 period. To fulfil this task, the optimal algorithm for extraction of the constituent through the applied MODIS reflectance data was identified first based on their effectiveness in determination of reference Chl-a data. The preferred Chl-a concentration maps were then generated through the identified algorithm along with their associated trophic state maps established regarding the modified OECD criteria. In the first step, the OC3M algorithm was selected (out of five initial candidates) as it provided the most satisfied output (with R² of 0.60) and used to make Chl-a density maps for the area. These obtained maps indicated that the concerned critical areas which are potentially vulnerable to red-tide occurrence (i.e., those in eutrophic/hyper-eutrophic states with high amount of Chl-a mixture) were frequently assembled over shallow water close to shore and main surrounding river mouths in the north, especially that of the Tha Chin River. However, patterns and strength of their distribution over the area were remarkably dynamic all year round with relatively low activity evidenced in dry season and more pronounced situation seen in monsoon season. In this regard, notable drop in total amount of the critical areas during wet season of 2011 was attributed to the influence of megaflooding over central Thailand at that time. [ABSTRACT FROM AUTHOR]