Quantitative Analysis of Correlation between US Army Installation Characteristics and Water Price
This study applied statistical approaches (e.g., Spearman’s rank correlation coefficient, regression tree analyses) to characterize Army site-specific factors (e.g., water demand, installation size, climate zone, Army mission type, utility privatization, water source, population, installation status on mission capacity) correlated with Army installation water unit price (USD Kgal-1). The results from Spearman’s rank correlation coefficient for individual factors showed that annual water consumption, size of installation, and population were the major influencing factors (positive correlation) to annual water billed. For Army installation water unit prices, however, negative correlation with annual water consumption and less significant correlation with climate zone were observed. This could lead to a failure in promoting water conservation in water-stressed areas with limited water supplies. From the results of regression tree analyses with combination of characterized variables, installation mission type, type of primary water source, and assured access to water were statistically significant factors to Army installation water unit prices. The regression trees provided coarser but actionable insights while clustering water unit prices by the influencing factors. The results of this study support site-specific reconsideration of water pricing and further development of installation water security and resiliency through deeper understanding of factors correlated with installation water unit price. Also, this research adds to existing studies on water infrastructure system characteristics, specialized use cases and water price across scales and locations at the United States.
Journal of Water Resources Planning and Management
Hur, A. Y., Garfinkle, N. W., Ploschke, C. M., Guest, J. S., & Chini, C. M. (2024). Quantitative Analysis of Correlation between US Army Installation Characteristics and Water Price. Journal of Water Resources Planning and Management, 150(1), 05023018. https://doi.org/10.1061/JWRMD5.WRENG-6189