Development and evaluation of a watershed-scale hybrid hydrologic model

<p>A watershed-scale hybrid hydrologic model (Distributed-Clark), which is a lumped conceptual and distributed feature model, was developed to predict spatially distributed short- and long-term rainfall runoff generation and routing using relatively simple methodologies and state-of-the-art spatial data in a GIS environment. In Distributed-Clark, spatially distributed excess rainfall estimated with the SCS curve number method and a GIS-based set of separated unit hydrographs (spatially distributed unit hydrograph) are utilized to calculate a direct runoff flow hydrograph, and time-varied SCS CN values and conditional unit hydrograph approach for different runoff depth-based flow convolution are also used to compute long-term rainfall-runoff flow hydrographs. Spatial data processing and model execution can be performed by Python script tools that were developed in a GIS platform.</p> <p>Model case studies of short- and long-term hydrologic application for four river watersheds to evaluate performance using spatially distributed (Thiessen polygon and NEXRAD radar-based) precipitation data demonstrate relatively good fit against observed streamflow as well as improved fit in comparison with the outputs of spatially averaged rainfall data simulations as follows: (1) application with 24 single storm events using Thiessen polygon distributed rainfall provided overall statistical results in <em>ENS</em> of 0.84 and <em>R2</em> of 0.86 (improved <em>ENS</em> by 1.8% and <em>R2</em> by 2.1% relative to averaged data inputs) for direct runoff, (2) simulation of direct runoff flow for the same storm events using NEXRAD data provided <em>ENS</em> of 0.85 and <em>R2</em> of 0.89 (increase of <em>ENS</em> by 3.0% and <em>R 2</em> by 6.0%), and (3) 6-year long-term daily NEXRAD data provided total simulated streamflow statistics of <em>ENS</em> 0.71 and <em>R2</em> 0.72 (increased <em>ENS</em> of 42.0% and <em>R2</em> of 33.3%). These results also indicate that NEXRAD radar-based data are more appropriate for rainfall-runoff flow predictions than rain gauge observations by capturing spatially distributed rainfall amounts and having fewer missing or erroneous records.</p> <p>The Distributed-Clark model presented in this research is, therefore, potentially significant to improved implementation of hydrologic simulation, particularly for spatially distributed rainfall-runoff routing using gridded types of quantitative precipitation estimation (QPE) data in a GIS environment, as a relatively simple (few parameter) hydrologic model.</p>

Name thesis:degree_name

Doctor of Philosophy (PhD)

Level thesis:degree_level

Dissertation

Discipline thesis:degree_discipline

Agricultural and Biological Engineering

Year

2016

Author dc:creator

• Cho, Younghyun

Contributors dc:contributor

• Bernard A. Engel
• Dennis C. Flanagan
• Margaret Gitau
• Rao S. Govindaraju
• Venkatesh M. Merwade

• Applied sciences
• Earth sciences
• Geographic information system
• Hybrid hydrologic model
• Next-Generation Weather Radar
• Soil Conservation Service curve number
• Spatially distributed rainfall-runoff flow simulation
• Unit hydrograph
• Bioresource and Agricultural Engineering
• Civil Engineering
• Hydrology

Repository record dc:identifier

https://docs.lib.purdue.edu/open_access_dissertations/635

OAI identifier oai:identifier

oai:docs.lib.purdue.edu:open_access_dissertations-1742