Water demand management is crucial for ensuring the efficient use of water resources, and consumption data collected by smart water meters is a valuable tool for managing water use at residential accounts. Outdoor water demands represent a large percentage of residential water consumption, and analysis of medium resolution, or hourly water demand data can provide valuable insights for informing water resources management strategies. Despite the promise of AMI data, methods for estimating outdoor water use rely on remotely sensed data and analysis of monthly water bills. This research develops new methods to estimate outdoor water consumption using medium-resolution consumption data. The Minimum Day Method (MDM) estimates outdoor water use by identifying the day with the least consumption over a specified period, assuming that this represents indoor water use. The Minimum Hour Method (MHM) focuses on the hour with the lowest consumption to represent indoor water use. Both methods are applied at the network (N) level where the demand is aggregated and at the account (A) level where each account outdoor use is estimated separately.These methods are applied for hourly demand data collected at 18,000 residential accounts over a two-year period. Our findings indicate that, on average, outdoor water use ranges from 31% to 41% using the MDM-N, MDM-A, and MHM-N methods. This variation emphasizes the sensitivity of outdoor usage estimates to the choice of analytical approach. This study highlights the potential of smart water meter data analysis to develop more effective water demand policies and inform water resource management strategies by providing an improved estimate of outdoor water usage.
