The occurrence of natural disasters as a consequence of accidental hazardous chemical spills remains a concern. The inadequate, or delayed, initial response may fail to mitigate their impact; hence, imminent monitoring of responses in the initial stage is critical. Classical contact-type measurement methods, however, sometimes miss solvent chemicals and invoke risks for operators during field operation. Remote sensing methods are an alternative method as non-contact, spatially distributable, efficient and continuously operatable features. Herein, we tackle challenges posed by the increasingly available UAV-based hyperspect ral images in riverine environments to identify the presence of hazardous chemical solvents in rivers, which are less investigated in the absence of direct measurement strategies. We propose a referable standard procedure for a unique spectral library based on pre-scanning hyperspectral sensors with respect to representative hazardous chemicals registered on the national hazardous chemical list. We utilized the hyperspectral images to identify 18 types of hazardous chemicals injected into the river in an outdoor environment, where a dedicated hyperspectral ground imaging system mounted with a hyperspectral camera was designed and applied. Finally, we tested the efficiency of the library to recognize unknown chemicals, which showed >70% success rate.

Chemical accidents in rivers may be triggered by natural or anthropogenic causes and refer to the flow of large quantities of hazardous chemicals into rivers. In South Korea, domestic water is sourced from large rivers, such as the Nakdong River. However, owing to rapid industrialization, industrial facilities have become heavily concentrated in the middle and upper reaches of the Nakdong River. Therefore, severe problems could arise if harmful chemicals are leaked from industrial facilities into the river, and this contaminated river water is supplied to cities. Quantitative evaluation based on instrumental analysis during chemical accidents and prediction research based on modeling is actively being conducted however, research on the initial response is insufficient. Therefore, in this study, the variations in pH and EC were analyzed according to their chemical concentrations for seven chemicals. These seven chemicals are designated accident-preparedness substances that frequently cause chemical spills in South Korea. Additionally, we evaluated the possibility of identifying unknown substances by comparing the variations in pH and EC and statistics while diluting unknown substances. Thus, the potential of pH and EC as alternative indicators for detecting and identifying chemicals was evaluated in this study. NaF, NH4HF2, NaCN, and NH4OH were classified by comparing their spatial distributions in a pH-EC relation curve. However, H2SO4, HCl, and SOCl2 showed similar spatial distributions in the pH-EC curves and were difficult to identify. The results of this study provide information for chemical detection and identification using alternative sensors that permit easy and rapid field measurements in the event of a chemical spill and could be used as preliminary data for rapidly responding to accidents.