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Browsing Theses and Dissertations by Author "Adams, Stephen K., author"

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    ItemOpen Access
    Ecologically-focused calibration of hydrological models for environmental flow applications
    (Colorado State University. Libraries, 2015) Adams, Stephen K., author; Bledsoe, Brian P., advisor; Poff, N. LeRoy, committee member; Stein, Eric D., committee member
    Hydrologic alteration resulting from watershed urbanization is a common cause of aquatic ecosystem degradation. Developing environmental flow criteria for managing the effects of urbanization and other human influences requires quantitative flow-ecology relationships that link biological responses to streamflow alteration. To the extent possible, gaged flow data are used; however, bioassessment sites are frequently ungaged and hydrological models must be used to characterize flow alteration. Physically-based rainfall-runoff models typically utilize a "best overall fit" calibration criterion, such as the Nash-Sutcliffe Efficiency (NSE), that does not focus on specific aspects of the flow regime relevant to biotic endpoints. This study aims to identify how accurately coastal southern California rainfall-runoff models can be calibrated using specific elements of the flow regime known a priori to be critical to benthic macroinvertebrates (ecologically-focused) versus a traditional best overall fit criterion. Additionally, this study seeks to assess the utility of ecologically-focused calibrated models by comparing flow metric accuracy and the strength of flow-ecology relationships among different calibration approaches versus gage data. For this study, continuous HEC-HMS 4.0 models were created for 19 coastal southern California watersheds and calibrated to USGS streamflow gages with nearby bioassessment sites using one best overall fit and three ecologically-focused criteria: NSE, Richards-Baker Flashiness Index (RBI), percent of time when the flow is < 28 L/s (< 1 cfs), and a Combined Calibration (RBI and < 1 cfs), respectively. Ecologically-focused criteria were selected based on preliminary statistical flow-ecology relationships at gaged bioassessment sites. Calibrated models were compared using flow metric accuracy relative to gage data and the strength of flow-ecology relationships. Models were highly accurately calibrated to ecologically-focused criteria, with calibration median percent errors less than 1.5% and only a single model with a percent error greater than 10%, and NSE criteria, with a median value of 0.634. Regardless of high calibration accuracy for ecologically-focused models, additional flow metrics not explicitly calibrated, especially those describing magnitude or rise and fall rates at aggregated daily time scales, were not consistently reproduced by models. Despite inaccuracies across a full suite of 71 flow metrics, low flow and flashiness metrics relevant to biotic endpoints were modeled accurately (< 20% error) and often provided stronger flow-ecology relationships than best overall fit criteria in terms of adjusted R2 in multiple regression analyses and variance explained in random forest modeling. This was especially true when two ecologically-focused criteria were combined, suggesting the importance of multiple calibration criteria. Flow metrics from the Combined Calibration provided the strongest flow-ecology models in correlation and regression analyses compared to the other three calibration approaches, and perform similarly in random forest models. This study demonstrates that if ecologically relevant flow metrics can be identified using published literature or preliminary statistical analyses of gaged bioassessment sites prior to developing a hydrologic foundation, they can be incorporated as calibration criteria and provide stronger modeled flow-ecology relationships than exclusive use of a best overall fit criterion.
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    ItemOpen Access
    Improving hydrologic modeling of ungaged basins to support environmental flow management in a heterogeneous region
    (Colorado State University. Libraries, 2021) Adams, Stephen K., author; Bledsoe, Brian P., advisor; Poff, N. LeRoy, committee member; Niemann, Jeffrey D., committee member; Stein, Eric D., committee member
    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.