Electronic Theses and Dissertations

Date

2024

Document Type

Dissertation

Degree Name

Doctor of Philosophy

Department

Civil Engineering

Committee Chair

Claudio Meier

Committee Member

Antonino Cancelliere

Committee Member

Thomas H. W. Goebel

Committee Member

Paul Palazolo

Abstract

Regional models for peak-flow prediction and other established methods in hydrology, including regional calibration of physically based model parameters and multi-basin training of deep-learning hydrologic models, all rely on lumped basin characterizations. On the other hand, it is known that lumped models are heavily affected by the inherent trade-off between the detail in basin representation and the complexity in hydrologic processes that can be captured. Current lumped methods consider straightforward averages of distributed basin characteristics, which may be overly simplistic in many cases. Indeed, existing lumped descriptors may easily fall short in accounting for system heterogeneity, with the risk that basins with distinct spatial arrangements of distributed characteristics of interest, and consequentially different responses to precipitation events, are treated as similar only because they display similar average values of those characteristics. This issue is particularly evident when trying to capture the effects of land development and other land-use/land-cover (LULC) changes. As this kind of information is typically specified as a fraction of the total basin area, LULC descriptors, including the popular percentage of total impervious area (TIA) for characterizing urban watersheds, are blind to the effects of the location of land patches with different LULC types. For instance, measuring urbanization impacts through a basin’s TIA implicitly assumes that changes in flood characteristics are proportional to the extents of land-development, without considering that such impacts may vary depending on the actual location of the developed areas within the basin. To overcome such limitations, we propose a novel framework for deriving a new type of lumped basin descriptors, incorporating hydrologic connectivity, and we then deploy such methodology for deriving connectivity-based urbanization metrics. The proposed hydrologic-connectivity-based index of urbanization HCIU quantifies the impacts of developed sectors in terms of their distributed effect on watershed connectivity, resulting in a lumped metric that displays sensitivity to the spatial arrangement of fully developed as well as less developed or undeveloped patches, each with different effects on hydrologic connectivity and thus response. HCIU enhances the predictive power of regional equations for peak flow in three large case-study homogeneous regions, when used in place of the traditional TIA.

Comments

Data is provided by the student.

Library Comment

Dissertation or thesis originally submitted to ProQuest.

Notes

Embargoed until 07-17-2025

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Available for download on Thursday, July 17, 2025

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