Show simple item record

dc.contributor.authorTahneen Jahan Neelam
dc.contributor.authorScott Steinschneider
dc.contributor.authorDonald E. Woodward
dc.contributor.authorRichard Hawkins
dc.contributor.authorM. Todd Walter
dc.date.accessioned2025-04-20T10:27:38Z
dc.date.available2025-04-20T10:27:38Z
dc.date.copyright9/25/2024 12:00:00 AM
dc.date.issued2024
dc.identifier.otherJHYEFF.HEENG-6180.pdf
dc.identifier.urihttp://yetl.yabesh.ir/yetl1/handle/yetl/4304763
dc.description.abstractThe curve number (CN) equation is a semiempirical, event-based model commonly used to estimate rainfall runoff. This model was originally developed in the 1950s to estimate storm runoff from 24-h rainfall events from small catchments. The model consists of two parameters: (1) the curve number (CN), which represents soil type, land use, and land cover; and (2) the initial abstraction (Ia), i.e., the amount of rain that needs to accumulate before storm runoff begins. Despite its narrow-intended use, the CN model is widely used for many applications from engineering design to hydrologic modeling and uses parameter tables and guidelines developed in the mid-20th century. Changes in land management and hydrological science pose questions about the continued relevancy of the model in general and the tabulated parameters specifically. We used Catchment Attributes and Meteorology for Large-Sample Studies (CAMELS), a recently collated data set of watershed characteristics and performed regression analyses on the watershed attributes to determine whether the CN and Ia parameters can better fit a wider range of attributes than can the currently used tables. Our analyses focused on 5–35 year peak runoff events. We considered 333 small to medium watersheds distributed across the contiguous US and more than 40 watershed characteristics. We found that the CN model generally worked best if Ia was much smaller than traditionally assumed. Indeed, Ia=0 generally worked well. We also found that CN-values generally correlated well with climate (elevation, average precipitation) and soil permeability (sand fraction, saturated hydraulic conductivity). Our results suggest that the CN model can work relatively well for engineering purposes in ungauged watersheds and that the expanding stream of remotely sensed geographic data may allow for better CN-values than those from the current tables. We suggest that this study be expanded to include a wider range of watershed and storm characteristics.
dc.publisherAmerican Society of Civil Engineers
dc.titleImproved Regionalization of the CN Method for Extreme Events at Ungauged Sites across the US
dc.typeJournal Article
dc.journal.volume29
dc.journal.issue6
dc.journal.titleJournal of Hydrologic Engineering
dc.identifier.doi10.1061/JHYEFF.HEENG-6180
dc.journal.fristpage04024043-1
dc.journal.lastpage04024043-14
dc.page14
dc.treeJournal of Hydrologic Engineering:;2024:;Volume ( 029 ):;issue: 006
dc.contenttypeFulltext


Files in this item

Thumbnail

This item appears in the following Collection(s)

Show simple item record