Improving hydrologic modeling of ungaged basins to support environmental flow management in a heterogeneous region
Date
2021
Authors
Adams, Stephen K., author
Bledsoe, Brian P., advisor
Poff, N. LeRoy, committee member
Niemann, Jeffrey D., committee member
Stein, Eric D., committee member
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Abstract
Environmental streamflow management can sustain aquatic ecosystems and the services they provide by reestablishing elements of the natural flow regime that are necessary for ecological health. One of the more difficult challenges with developing environmental flow criteria is estimating streamflow at locations without gage data; however, this challenge is not unique to environmental flows. Streamflow prediction in ungaged basins is a very common problem in hydrology and engineering with no clear solution, but it is particularly difficult to model environmental streamflow metrics across heterogeneous regions with highly diverse land uses, geologic settings, and hydroclimatological processes. In this dissertation, I create a new regionalization framework, "Streamflow Regionalization with Hydrologic Model-based Classification" (SR-HMC), for modeling challenging flow metrics in ungaged basins across a heterogeneous region. I also test the efficacy of the new framework for developing environmental streamflow criteria. In Chapter 2, I explore different approaches for classifying streams with similar flow regimes and develop a novel classification technique for prioritizing regional accuracy of hydrologic models. As the precursor to SR-HMC, this "Hydrologic Model-based Classification" (HMC) groups hydrologically similar streams by determining the degree of reciprocity of calibrated parameters between a regional catalog of rainfall-runoff models as quantified through jackknife resampling. Results show that HMC complements traditional classifications based on streamflow metrics and watershed characteristics, and offer advantages over these traditional classifications when used to regionalize ungaged basins. Next, Chapter 3 describes implementation of ensemble modeling to optimize HMC into a regionalization framework for producing time series of streamflow at ungaged sites. For gaged locations, hydrologic model parameters that cannot be calculated directly can be calibrated using observed flows; however, these same model parameters are much more uncertain and difficult to estimate at ungaged locations. SR-HMC uses geographically-weighted model output averaging with regionally-calibrated parameter sets to reduce parameter uncertainty in models of ungaged basins. This new framework is tested at five sites across a large and diverse region. Results were improved using SR-HMC over standard nearest-neighbor regionalization approaches. Finally, I turn to management applications of these novel methods in ungaged basins by analyzing the statistical relationships between streamflow alteration and ecological integrity. In Chapter 4, I compare the explanatory power of simple flow-ecology relationships produced by different methods for regionalizing ungaged basins and different metrics of flow alteration. Results highlight robust modeling practices amenable to management. Development of environmental streamflow recommendations based on prediction in ungaged basins is an ongoing challenge; however, this research demonstrates how novel approaches to classification and model extrapolation can improve streamflow estimation at ungaged locations in heterogeneous regions, and thereby bolster the scientific basis of environmental flow management.
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Subject
flow-ecology relationships
regionalization
water resources management
hydrologic modeling
environmental streamflow management
ungaged basins