Storm water drainage systems represent a major investment that need to be managed in a cost-effective manner and need to be kept in an acceptable level of service to avoid costly failures and floods. These drainage systems tend to be complex because they consist of different types of infrastructure assets (culverts, open channels, drop structures, etc.) that are built over time with different standards and design loads. As the main objective of managing drainage systems is to prevent or reduce flooding during extreme storm events, these systems need to be kept in acceptable level of service through appropriate asset management processes. What is missing is drainage infrastructure data that are sufficiently detailed to be useful for decision making and at the same time not so demanding of time and resources as to be unaffordable to collect and update for most local agencies. This research contributed to addressing the data issues for GIS-based storm water drainage management systems through defining inventory data requirements, developing practical and simplified condition assessment methods that consider both hydraulic capacity and physical condition of assets, and integrating inventory and condition data in relational database and GIS. The developed data requirements and condition assessment methods were applied to the City of El Paso storm water drainage system to demonstrate their applicability.
