Urban areas face significant water management challenges due to population growth and climate change. Understanding how climatic variables impact water storage levels is essential for effective water management. In this paper, the key components in the mass balance conservation of storage levels are streamflow and the volume of water drawn from reservoirs (water consumption). The multiple linear regression (MLR) analysis is employed to gain insight into the effects of climatic variables on storage levels in four harvesting dams in Greater Melbourne, Australia. Annual climatic variables such as precipitation (Pr), maximum and minimum temperatures (Tmax and Tmin), and evaporation (Evap) recorded at a Bureau of Meteorology gauging station from 1985 to 2020 have been analyzed and correlated with streamflow and water consumption, recorded by Melbourne Water during the same period. Initially, the datasets were examined using Pearson correlation to avoid multicollinearity. The MLR analysis indicated that Tmax and Pr are statistically significant factors affecting streamflow, with P-values of 0.009 and 3 × 10–3, respectively, and an R2 of 0.87. Additionally, the MLR analysis for per capita water consumption shows a significant P-value of 0.0079 for Tmax and an R2 of 0.72. These findings provide crucial insights for urban planners and policymakers to develop more effective water management strategies, enhancing resilience against climate variability and ensuring a sustainable water supply.