\"The EPA Storm Water Management Model (SWMM) was used to perform single event simulations of Probable Maximum Precipitation (PMP) level rainfall events on the Loss Lake watershed in southcentral Missouri. Overland flow was simulated using kinematic wave routing and channel flow was simulated using dynamic wave routing.
Lag time was defined as the time between the centroid of the excess rainfall hyetograph and the centroid of the direct runoff hydrograph.
Rainfall depth, rainfall duration, and the distribution of rainfall intensity were found to be significant predictor variables for lag time. Defined as hydrologic parameters for this study, channel flow roughness, initial abstraction and infiltration were evaluated but found to have minimal effect on lag time. Overland flow roughness bad a measurable effect on basin lag time but not as significant as precipitation.
SWMM simulated lag times were compared to the lag times computed by the Kirpich, Kerby-Hathaway, Soil Conservation Service (SCS) Lag, and SCS Velocity methods. The results of the study indicate that the traditional approach of combining the overland and channel flow lag times from the Kerby-Hathaway and Kirpich equations underestimates basin lag time for rainfall events smaller than the 100 percent PMP event.
A regression analysis performed on the 6-hour and 12-hour SWMM simulated lag times indicated that overland flow length and slope, channel length and slope, precipitation and the shape of the drainage area all affect basin lag time. Two multivariate power series regression equations were derived to predict basin lag time for 6-hour and 12-hour duration events\"--Abstract, pages ii-iii.
","abstract_html":"<p>"The EPA Storm Water Management Model (SWMM) was used to perform single event simulations of Probable Maximum Precipitation (PMP) level rainfall events on the Loss Lake watershed in southcentral Missouri. Overland flow was simulated using kinematic wave routing and channel flow was simulated using dynamic wave routing.</p> <p>Lag time was defined as the time between the centroid of the excess rainfall hyetograph and the centroid of the direct runoff hydrograph.</p> <p>Rainfall depth, rainfall duration, and the distribution of rainfall intensity were found to be significant predictor variables for lag time. Defined as hydrologic parameters for this study, channel flow roughness, initial abstraction and infiltration were evaluated but found to have minimal effect on lag time. Overland flow roughness bad a measurable effect on basin lag time but not as significant as precipitation.</p> <p>SWMM simulated lag times were compared to the lag times computed by the Kirpich, Kerby-Hathaway, Soil Conservation Service (SCS) Lag, and SCS Velocity methods. The results of the study indicate that the traditional approach of combining the overland and channel flow lag times from the Kerby-Hathaway and Kirpich equations underestimates basin lag time for rainfall events smaller than the 100 percent PMP event.</p> <p>A regression analysis performed on the 6-hour and 12-hour SWMM simulated lag times indicated that overland flow length and slope, channel length and slope, precipitation and the shape of the drainage area all affect basin lag time. Two multivariate power series regression equations were derived to predict basin lag time for 6-hour and 12-hour duration events"--Abstract, pages ii-iii.</p>","abstract_has_math":false,"creators":["Swenty, Brian Jay"],"institution":"University of Missouri--Rolla","degree_name":"Ph. D. in Civil Engineering","degree_level":null,"degree_discipline":null,"degree_department":null,"school":null,"contributors":[],"advisors":[],"committee_chairs":[],"committee_members":[],"year":2016,"date_issued":"2016-02-10T08:00:00Z","date_published":"2016-02-10T08:00:00Z","updated_at":"2026-07-24T03:19:21Z","subjects":["Civil Engineering"],"languages":[],"rights":[],"rights_urls":[],"identifier_entries":[]},"links":{"outbound_url":"https://scholarsmine.mst.edu/doctoral_dissertations/719","outbound_label":"Repository record","outbound_source":"dc:identifier"},"metadata_groups":[{"id":"people","label":"People","entries":[{"key":"dc:creator","label":"Author","values":["Swenty, Brian Jay"]}]},{"id":"academic_context","label":"Academic Context","entries":[{"key":"dc:date.available","label":"Dc Date Available","values":["2016-02-10T08:00:00Z"]},{"key":"dc:type","label":"Dc Type","values":["Dissertation - Open Access"]},{"key":"thesis:degree_name","label":"Degree Name","values":["Ph. D. in Civil Engineering"]},{"key":"thesis:institution_name","label":"Thesis Institution Name","values":["University of Missouri--Rolla"]}]},{"id":"subjects_keywords","label":"Subjects and Keywords","entries":[{"key":"dc:subject","label":"Dc Subject","values":["Civil Engineering"]}]},{"id":"identifiers","label":"Identifiers","entries":[{"key":"dc:identifier","label":"Identifier","values":["https://scholarsmine.mst.edu/doctoral_dissertations/719"]}]},{"id":"additional","label":"Additional Metadata","entries":[{"key":"dc:description.abstract","label":"Abstract","values":["\"The EPA Storm Water Management Model (SWMM) was used to perform single event simulations of Probable Maximum Precipitation (PMP) level rainfall events on the Loss Lake watershed in southcentral Missouri. Overland flow was simulated using kinematic wave routing and channel flow was simulated using dynamic wave routing.
Lag time was defined as the time between the centroid of the excess rainfall hyetograph and the centroid of the direct runoff hydrograph.
Rainfall depth, rainfall duration, and the distribution of rainfall intensity were found to be significant predictor variables for lag time. Defined as hydrologic parameters for this study, channel flow roughness, initial abstraction and infiltration were evaluated but found to have minimal effect on lag time. Overland flow roughness bad a measurable effect on basin lag time but not as significant as precipitation.
SWMM simulated lag times were compared to the lag times computed by the Kirpich, Kerby-Hathaway, Soil Conservation Service (SCS) Lag, and SCS Velocity methods. The results of the study indicate that the traditional approach of combining the overland and channel flow lag times from the Kerby-Hathaway and Kirpich equations underestimates basin lag time for rainfall events smaller than the 100 percent PMP event.
A regression analysis performed on the 6-hour and 12-hour SWMM simulated lag times indicated that overland flow length and slope, channel length and slope, precipitation and the shape of the drainage area all affect basin lag time. Two multivariate power series regression equations were derived to predict basin lag time for 6-hour and 12-hour duration events\"--Abstract, pages ii-iii.
"]},{"key":"dc:title","label":"Title","values":["Time characteristics of small watersheds in response to the probable maximum precipitation"]}]}],"canonical_facts":{"dc:creator":["Swenty, Brian Jay"],"dc:date.available":["2016-02-10T08:00:00Z"],"dc:description.abstract":["\"The EPA Storm Water Management Model (SWMM) was used to perform single event simulations of Probable Maximum Precipitation (PMP) level rainfall events on the Loss Lake watershed in southcentral Missouri. Overland flow was simulated using kinematic wave routing and channel flow was simulated using dynamic wave routing.
Lag time was defined as the time between the centroid of the excess rainfall hyetograph and the centroid of the direct runoff hydrograph.
Rainfall depth, rainfall duration, and the distribution of rainfall intensity were found to be significant predictor variables for lag time. Defined as hydrologic parameters for this study, channel flow roughness, initial abstraction and infiltration were evaluated but found to have minimal effect on lag time. Overland flow roughness bad a measurable effect on basin lag time but not as significant as precipitation.
SWMM simulated lag times were compared to the lag times computed by the Kirpich, Kerby-Hathaway, Soil Conservation Service (SCS) Lag, and SCS Velocity methods. The results of the study indicate that the traditional approach of combining the overland and channel flow lag times from the Kerby-Hathaway and Kirpich equations underestimates basin lag time for rainfall events smaller than the 100 percent PMP event.
A regression analysis performed on the 6-hour and 12-hour SWMM simulated lag times indicated that overland flow length and slope, channel length and slope, precipitation and the shape of the drainage area all affect basin lag time. Two multivariate power series regression equations were derived to predict basin lag time for 6-hour and 12-hour duration events\"--Abstract, pages ii-iii.
"],"dc:identifier":["https://scholarsmine.mst.edu/doctoral_dissertations/719"],"dc:subject":["Civil Engineering"],"dc:title":["Time characteristics of small watersheds in response to the probable maximum precipitation"],"dc:type":["Dissertation - Open Access"],"thesis:degree_name":["Ph. D. in Civil Engineering"],"thesis:institution_name":["University of Missouri--Rolla"]},"updated_at":"2026-07-24T03:19:21Z"}