Mapping Corporate Water Risk – Investigation of Baseline Water Stress for Japanese Companies

Abstract

As water risk becomes more severe and noticeable in recent years, corporate water risk also receives more attention in corporate management. Realizing that water risk should be examined on a regional scale, this study started from a location perspective and examined corporate water risk of ten Japanese companies by mapping their facilities on the Aqueduct global baseline water stress map and calculating fraction of facilities that are in areas with high water risk (“number fraction”). It was found that about 40% of water-sensitive facilities both inside and outside Japan are in high-waterrisk areas. Variation in number fraction values is generally weak and become stronger when number of facilities is low. As number of facilities of a certain corporation, line of business or region increases, the number fraction value approaches world average. This indicates that larger entities are able to adopt more universal water management strategies. By using different layers of water risk data provided by Aqueduct, it was observed that results vary with the chosen indicator. When seasonal variability or overall water risk is used, number fraction values drop significantly to less than 20%, especially in Japan. High number fraction values can be attributed to facilities in certain regions, but the results derived from one indicator cannot be used to predict results derived from another indicator because they all focus on different aspects of water risk. This suggests that choice of indicators should be based on specific situations. Finally, validation of number fraction as a measurement of impacts from water risk using share price fluctuation was done. The validation was not successful and the ten corporations don’t show significant differences in their share price behavior with different number fractions. It was suggested that sector-specific indexes and more financial metrics be used for future analysis, which can be focusing on a bigger portfolio.Master of ScienceSchool for Environment and SustainabilityUniversity of Michiganhttps://deepblue.lib.umich.edu/bitstream/2027.42/154878/1/Chen Muhan Thesis.pd