|Document Type:||Master's Thesis|
|Name:||Jennifer Leigh Kilgore|
|Title:||DEVELOPMENT AND EVALUATION OF A GIS-BASED SPATIALLY DISTRIBUTED UNIT HYDROGRAPH MODEL|
|Degree:||Master of Science|
|Department:||Biological Systems Engineering|
|Committee Chair:||Dr. Conrad Heatwole|
|Committee Members:||Dr. Conrad Heatwole|
|Dr. David F. Kibler|
|Dr. Saied Mostaghimi|
|Keywords:||GIS, unit hydrograph, hydrologic modeling, spatial modeling|
|Date of defense:||December 10, 1997|
|Availability:||Release the entire work immediately worldwide.|
Synthetic unit hydrographs, which assume uniform rainfall excess distribution and static watershed conditions, are frequently used to estimate hydrograph characteristics when observed data are unavailable. The objective of this research was to develop a spatially distributed unit hydrograph (SDUH) model that directly reflects spatial variation in the watershed in generating runoff hydrographs.
The SDUH model is a time-area unit hydrograph technique that uses a geographic information system (GIS) to develop a cumulative travel time map of the watershed based on cell by cell estimates of overland and channel flow velocities. The model considers slope, land use, watershed position, channel characteristics, and rainfall excess intensity in determining flow velocities. The cumulative travel time map is divided into isochrones which are used to generate a time-area curve and the resulting unit hydrograph.
Predictions of the SDUH model along with the Snyder, SCS, and Clark synthetic unit hydrographs were compared with forty observed storm events from an 1153-ha Virginia Piedmont watershed. The SDUH model predictions were comparable or slightly better than those from the other models, with the lowest relative error in the peak flow rate prediction for 12 of the 40 storms, and a model efficiency of at least 0.90 for 21 of the storms. Despite the good predictions of the hydrograph peak flow rate and shape, the time to peak was underpredicted for 34 of the 40 storms.
Runoff from the 40 storms was also generated for two subwatersheds (C: 462 ha; D: 328 ha) in Owl Run to assess the effect of scale on the SDUH model. Peak flow rate predictions were more accurate for the entire watershed than for either subwatershed. The time to peak prediction and model efficiency statistics were comparable for the entire watershed and subwatershed D. Subwatershed C had poorer predictions, which were attributed to a large pond in the main channel, rather than to scale effects.
The SDUH model provides a framework for predicting runoff hydrographs for ungauged watersheds that can reflect the spatially distributed nature of the rainfall-runoff process. Predictions were comparable to the other synthetic unit hydrograph techniques. Because the time to peak and model efficiency statistics were similar for the 1153-ha watershed and a 328-ha subwatershed, scale does not have a major impact on the accuracy of the SDUH model.
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