Using NOAA Atlas 15 to Identify Shifts in the Geographic Dependency of the NRCS Initial Abstraction Ratio

Glenn Moglen; Julianne Miller; Justin Gifford; Tianyang Chen

This presentation describes a study that leverages pilot data from NOAA Atlas 15 to assess how future climate scenarios may influence runoff estimation using the NRCS Curve Number method. Focusing on the State of Montana, precipitation frequency estimates were analyzed under Global Thermal Index (GTI) scenarios representing temperature increases from 1.5°C to 5.0°C, with emphasis on 24-hour storm durations. These data provide a critical foundation for evaluating shifts in hydrologic behavior under projected climate conditions. Building on recent work that introduced “hydrologic conservatism zones” to guide the selection of the initial abstraction ratio based on rainfall frequency and geography, this study investigates how those zones may evolve in response to climate change. Results show that rising global temperatures and more frequent extreme precipitation events are likely to increase runoff estimates. Under these future conditions, an initial abstraction ratio of 0.2, rather than the most common alternative of 0.05, produces more conservative runoff estimates across return periods and GTI scenarios. This suggests a statewide and potentially regional shift toward adopting the higher ratio for more climate-resilient hydrologic designs. In addition to identifying this trend, a tabulation will be presented of projected precipitation depths relative to current values across return periods and GTI scenarios. These findings offer valuable insights for engineers, planners, and policymakers preparing for future water resource challenges and infrastructure design under changing climate conditions.

The Curve Number Method: An Oral History

Glenn Moglen; Julianne Miller; Donald Woodward; Suresh Sharma; Ernest Tollner; Steve McCutcheon; Richard Hawkins

The Natural Resources Conservation Service (NRCS) Curve Number (CN) method remains one of the most widely applied tools in hydrologic engineering practice for estimating stormwater runoff. The CN method was institutionalized by the NRCS (formerly the Soil Conservation Service) through the National Engineering Handbook, which has undergone multiple revisions as practice and evidence evolved. To better understand the use of the CN method for runoff estimation in watershed management, the Oral History subcommittee of the ASCE Curve Number Hydrology Task Committee interviewed key experts in hydrologic engineering. These interviews of practitioners and academic investigators focused on the development approach and timeline, advancements, and challenges of the CN method, as well as on practitioners’ firsthand experiences. The participants' discussions created a narrative of the CN method's development, from its early beginnings to its current state, highlighting the contributions of Victor Mockus and other pioneers of the method. The oral history revealed a timeline marked by significant milestones, including the method's initial development and its subsequent refinement through advances in hydrologic modeling and computer applications, as well as current adaptations for use with contemporary farming practices and urban best management practices. The participants also reflected on the challenges and limitations of the CN method. By sharing their individual experiences and perspectives, the oral history participants provided a unique glimpse into the evolution of the CN method, including the human dimension stories behind the method, as well as offering valuable insight to more accurate and effective rainfall-runoff estimation techniques.

Adjusting Curve Number for Short-Duration Storms

Sunil Bista; John Ramirez-Avila; Michael Meadows; Suresh Sharma; Rocky Tachabhadel

The Natural Resources Conservation Service (NRCS) Curve Number (CN) method remains a fundamental component of applied hydrology for estimating direct runoff. However, its empirical derivation from 24-hour rainfall data introduces significant incongruity when applied to sub-daily, high-intensity storm events. This practice is prevalent in urban hydrology and flash flood modeling, where the hydrologic response is dictated by short-duration rainfall. This study investigates the critical discrepancy arising from this temporal misapplication, demonstrating that the direct use of unadjusted 24-hour CN values leads to a systematic and substantial underestimation of runoff volumes. This study presents a comparative analysis between runoff calculated using the standard CN equation and runoff derived from a proposed duration-adjustment methodology. The adjusted approach normalizes the 24-hour infiltration volume by its duration to establish an average infiltration rate, which is then scaled to the specific, shorter duration of the storm event. This correction accounts for the reduced time available for infiltration processes to occur during high-intensity and short-burst rainfall. The analysis quantifies the magnitude of runoff underestimation by the standard method. Results establish that the duration-adjusted runoff volume is significantly greater than the unadjusted prediction. Furthermore, by back-calculating from the corrected runoff volume, an equivalent short-duration CN is derived, which is comparatively higher than its 24-hour counterpart. These findings underscore the imperative to incorporate storm duration adjustments into CN based hydrologic modeling. Failure to do so carries tangible implications, including the potential under design of critical stormwater infrastructure and diminished accuracy in watershed management and flood-risk assessments.