This study uses data from the Tar-River Basin in North Carolina to explore how space-time rainfall variability influences the hydrologic response from observational and modeling perspectives. For understanding the basin scale effect, the Tar-River Basin is divided into four cascade sub-basins ranging from 1106 km2 up to 5654 km2. The study evaluates the catchments’ response to rainfall for a large number of storm events by computing the event runoff coefficient based on streamflow observations and through simulations from a semi-distributed hydrological model. Comparison of observed to simulated hydrographs from the hydrological model shows that distributed rainfall forcing gives improved performance evaluation metrics relative to basin-average rainfall forcing data. We employ the concepts of “Spatial Moments of Catchment Rainfall (defined as Δ1 and Δ2)” and “Catchment Scale Storm Velocity (defined as Vs)” reported in Zoccatelli et al. (2011) to quantify the effect of spatial rainfall organization and basin geomorphology on modeling the flood response. Our analysis using the above conceptual framework shows that the rainfall spatiotemporal variation plays a significant role on the timing and dispersion of the simulated hydrographs. Specifically, Δ1 increases linearly with the difference in timing between lumped and distributed rainfall forcing. Δ2 and the product between Vs and the variance of hydrograph arrival time exhibit an increasing trend with the difference in dispersion of simulated hydrographs between lumped and distributed rainfall forcing.
","abstract_html":"<p>This study uses data from the Tar-River Basin in North Carolina to explore how space-time rainfall variability influences the hydrologic response from observational and modeling perspectives. For understanding the basin scale effect, the Tar-River Basin is divided into four cascade sub-basins ranging from 1106 km<sup>2</sup> up to 5654 km<sup>2</sup>. The study evaluates the catchments’ response to rainfall for a large number of storm events by computing the event runoff coefficient based on streamflow observations and through simulations from a semi-distributed hydrological model. Comparison of observed to simulated hydrographs from the hydrological model shows that distributed rainfall forcing gives improved performance evaluation metrics relative to basin-average rainfall forcing data. We employ the concepts of “Spatial Moments of Catchment Rainfall (defined as <em>Δ<sub>1</sub></em> and <em>Δ<sub>2</sub></em>)” and “Catchment Scale Storm Velocity (defined as <em>V<sub>s</sub></em>)” reported in Zoccatelli et al. (2011) to quantify the effect of spatial rainfall organization and basin geomorphology on modeling the flood response. Our analysis using the above conceptual framework shows that the rainfall spatiotemporal variation plays a significant role on the timing and dispersion of the simulated hydrographs. Specifically, <em>Δ<sub>1</sub></em> increases linearly with the difference in timing between lumped and distributed rainfall forcing. <em>Δ<sub>2</sub></em> and the product between <em>V<sub>s</sub></em> and the variance of hydrograph arrival time exhibit an increasing trend with the difference in dispersion of simulated hydrographs between lumped and distributed rainfall forcing.</p>","abstract_has_math":false,"creators":["Mei, Yiwen"],"institution":null,"degree_name":"Master of Science","degree_level":null,"degree_discipline":"Environmental Engineering","degree_department":null,"school":null,"contributors":["Guiling Wang; Amvrossios Bagtzoglou","Emmanouil N. Anagnostou"],"advisors":[],"committee_chairs":[],"committee_members":[],"year":2012,"date_issued":"2012-06-08T07:00:00Z","date_published":"2012-06-08T07:00:00Z","updated_at":"2026-07-24T06:31:50Z","subjects":["Spatiotemporal Variability of Rainfall","Storm Velocity","Runoff Coefficient","Hydrologic Model"],"languages":[],"rights":[],"rights_urls":[],"identifier_entries":[]},"links":{"outbound_url":"https://digitalcommons.lib.uconn.edu/gs_theses/295","outbound_label":"Repository record","outbound_source":"dc:identifier"},"metadata_groups":[{"id":"people","label":"People","entries":[{"key":"dc:contributor","label":"Contributor","values":["Guiling Wang; Amvrossios Bagtzoglou","Emmanouil N. 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For understanding the basin scale effect, the Tar-River Basin is divided into four cascade sub-basins ranging from 1106 km2 up to 5654 km2. The study evaluates the catchments’ response to rainfall for a large number of storm events by computing the event runoff coefficient based on streamflow observations and through simulations from a semi-distributed hydrological model. Comparison of observed to simulated hydrographs from the hydrological model shows that distributed rainfall forcing gives improved performance evaluation metrics relative to basin-average rainfall forcing data. We employ the concepts of “Spatial Moments of Catchment Rainfall (defined as Δ1 and Δ2)” and “Catchment Scale Storm Velocity (defined as Vs)” reported in Zoccatelli et al. (2011) to quantify the effect of spatial rainfall organization and basin geomorphology on modeling the flood response. Our analysis using the above conceptual framework shows that the rainfall spatiotemporal variation plays a significant role on the timing and dispersion of the simulated hydrographs. Specifically, Δ1 increases linearly with the difference in timing between lumped and distributed rainfall forcing. Δ2 and the product between Vs and the variance of hydrograph arrival time exhibit an increasing trend with the difference in dispersion of simulated hydrographs between lumped and distributed rainfall forcing.
"]},{"key":"dc:title","label":"Title","values":["Rainfall Organization and Geomorphologic Controls on the Flood Response of Mild-slope Basins in the South Atlantic Region of US"]}]}],"canonical_facts":{"dc:contributor":["Guiling Wang; Amvrossios Bagtzoglou","Emmanouil N. Anagnostou"],"dc:creator":["Mei, Yiwen"],"dc:date.available":["2012-12-03T08:00:00Z"],"dc:description.abstract":["This study uses data from the Tar-River Basin in North Carolina to explore how space-time rainfall variability influences the hydrologic response from observational and modeling perspectives. For understanding the basin scale effect, the Tar-River Basin is divided into four cascade sub-basins ranging from 1106 km2 up to 5654 km2. The study evaluates the catchments’ response to rainfall for a large number of storm events by computing the event runoff coefficient based on streamflow observations and through simulations from a semi-distributed hydrological model. Comparison of observed to simulated hydrographs from the hydrological model shows that distributed rainfall forcing gives improved performance evaluation metrics relative to basin-average rainfall forcing data. We employ the concepts of “Spatial Moments of Catchment Rainfall (defined as Δ1 and Δ2)” and “Catchment Scale Storm Velocity (defined as Vs)” reported in Zoccatelli et al. (2011) to quantify the effect of spatial rainfall organization and basin geomorphology on modeling the flood response. Our analysis using the above conceptual framework shows that the rainfall spatiotemporal variation plays a significant role on the timing and dispersion of the simulated hydrographs. Specifically, Δ1 increases linearly with the difference in timing between lumped and distributed rainfall forcing. Δ2 and the product between Vs and the variance of hydrograph arrival time exhibit an increasing trend with the difference in dispersion of simulated hydrographs between lumped and distributed rainfall forcing.
"],"dc:identifier":["https://digitalcommons.lib.uconn.edu/gs_theses/295"],"dc:subject":["Spatiotemporal Variability of Rainfall","Storm Velocity","Runoff Coefficient","Hydrologic Model"],"dc:title":["Rainfall Organization and Geomorphologic Controls on the Flood Response of Mild-slope Basins in the South Atlantic Region of US"],"thesis:degree_discipline":["Environmental Engineering"],"thesis:degree_name":["Master of Science"]},"updated_at":"2026-07-24T06:31:50Z"}