This paper presents methods used for evaluation of risk and methods to predict peak demands based on a set of independent variables. With the ever-increasing need to maximize benefit/cost ratios, a more rational approach for selecting design parameters could result in cost savings through deferral of facilities. This would translate into lower customer rates. Deferring construction of facilities can be based on an understanding of what various design parameters mean in terms of the risk of failure of a system in not being able to meet a given water demand. Historical water demand data is analyzed to develop the probability of exceedance and the consequences of exceedance is evaluated to develop a level of risk. In addition to evaluation of risk, improving the ability to predict daily demands based on weather, seasonal rainfall, and temperature conditions could enhance daily operations. A series of statistical analyses are presented which have been explored including multiple linear regression analysis and ARIMA moving averages to develop a relationship between peak water demands and a set of independent variables. The analyses show that peak water demands can be reasonably predicted.