Award Date

12-1-2017

Degree Type

Thesis

Degree Name

Master of Science in Engineering (MSE)

Department

Civil and Environmental Engineering and Construction

First Committee Member

Haroon Stephen

Second Committee Member

Sajjad Ahmad

Third Committee Member

Jacimaria Batista

Fourth Committee Member

Ashok Singh

Number of Pages

153

Abstract

Urban flooding is the most frequently occurring disaster in rapidly urbanizing cities. Rapid urbanization in general, is characterized by an increase in the total impervious surface area, which means less soil cover for the stormwater to infiltrate and a greater volume of runoff from the area in case of a storm event. This increased volume of surface runoff, if not drained, results in urban flooding. Urban flooding can cause serious economic and environmental damages by disrupting transportation and spreading pollution. It is therefore, essential to understand the cause, behavior and effects of urban flooding so as to minimize the risks and costs associated with urban floods.

Hydrologic models are useful tools for understanding hydrologic processes and for designing urban stormwater drainage infrastructure to reduce the risks of floodings. This research aims to study urban hydrology by estimating surface runoff from an urban area using an event based distributed parameter hydrologic model. In this research, an event-based distributed parameter hydrologic model is developed, which uses Green-Ampt infiltration model to estimate the surface runoff from a given catchment. The developed model is tested on two small catchments. The ‘rainfall-runoff modeling’ part of the developed model is calibrated for the rainfall events of May 22, 2017 and, May 24, 2017 over the Moores Run study area, and, validated for the rainfall event of April 17, 2017. The ‘flood-modeling’ part of the developed model is validated for the rainfall event of Sep 11, 2012 over the Parking-lots area at UNLV. The results of the rainfall-runoff simulation and flood depth and extent estimation for different land-cover change scenarios over the Parking-lots catchment is also provided.

The testing on Moores Run study area resulted in calibration at 30-m resolution DEM and a hydraulic conductivity value of 0.19 cm/hr. for soil group D. The error in the model’s estimation of the catchment area is 7.75%. The model over-predicted the runoff volume from the catchment for the first rainfall event while under-predicted the runoff volume from the catchment for the second rainfall event. The average error in estimation of the runoff volume is 1.8%. The model also over-predicts the ‘time-to-peak’ and under-predicts ‘peak runoff’ in both cases. The average of RMSE between the predicted hydrograph and actual hydrograph for the two rainfall events is 0.0071 m3/s in calibration, and, 0.011 m3/s in validation. The testing on UNLV Parking-lots area resulted in calibration at 10-m resolution DEM. For the rainfall event of Sep 11, 2012, the model predicts over predicts the peak flood depth and under-predicts the maximum extent of flooding. The error in flood depth estimation is found be 12.9%. From watershed hydrologic response to landcover change analysis, it is observed that Manning’s roughness coefficient doesn’t affect the total volume of runoff, however, the time to peak is significantly delayed for landcover with higher values of Manning’s roughness co-efficient.

This research provides an insight into surface hydrologic modeling. It also provides an overview of calibration against DEM resolution and hydraulic conductivity values. Finally, it provides an understanding of watershed hydrologic response to different landcovers with various Manning’s roughness values.

Keywords

Green-Ampt infiltration model; Hydraulic conductivity; Manning's equation; numerical model; urban flooding; water flux

Disciplines

Civil Engineering

Language

English


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