Thesis
Development of a physically based streamflow temperature prediction model for a river network
University of Iowa
Master of Science (MS), University of Iowa
Spring 2024
DOI: 10.25820/etd.007494
Abstract
Water temperature is a crucial water quality variable, as it controls the concentration of dissolved oxygen and nutrients. Also, stream temperature influences the productivity and distribution of aquatic ecosystems, since most species can tolerate a specific range of temperatures. During the last few years, Iowa’s agricultural activities have increased nutrients and nitrates concentration in water bodies, which has had devastating environmental impacts both locally and downstream. In 2015, Iowa installed the Iowa Water Quality (IWQ) network with more than 50 sensors in order to access real-time water quality data of water temperature, nitrate, pH, and dissolved oxygen concentrations. However, the IWQ network only provides observations at specific locations, limiting the information required to develop a water quality model. Therefore, the main goal of our work is to develop a distributed model to predict hourly water temperature for all streams. Our model describes the energy balance at the air-water interface, and estimates the heat flux by taking into account the solar radiation, net longwave radiation, evaporative heat flux, and convective heat transfer. We formulated the model for a general river network as a set of Ordinary Differential Equations (ODE). We compute water temperature using the asynchronous numerical solver from the Hillslope Link Model (HLM) developed for river networks. We evaluated the model using the High-Resolution Rapid Refresh (HRRR) meteorological data and discharge simulated by the Iowa Flood Center forecasting model. We tested and validated the temperature model using the 2021 records from the USGS gauges in Cedar River at Waverly. The preliminary results of the model for the Cedar River subbasin show potential for further evaluation in other basins in the state. We expect to provide accurate forecasts of stream water temperatures to support decision-making for stakeholders such as researchers, fisheries, and members of the community. This model is the first step in developing a higher-level water quality model to predict concentrations of nutrients in the water, which will be helpful for Iowa's environmental management.
Details
- Title: Subtitle
- Development of a physically based streamflow temperature prediction model for a river network
- Creators
- Valeria Garcia Munera
- Contributors
- Witold F. Krajewski (Advisor)Nicolas Velasquez Giron (Advisor)Larry J. Weber (Committee Member)
- Resource Type
- Thesis
- Degree Awarded
- Master of Science (MS), University of Iowa
- Degree in
- Civil and Environmental Engineering
- Date degree season
- Spring 2024
- Publisher
- University of Iowa
- DOI
- 10.25820/etd.007494
- Number of pages
- xii, 73 pages
- Copyright
- Copyright 2024 Valeria Garcia Munera
- Language
- English
- Date submitted
- 04/22/2024
- Description illustrations
- Illustrations, tables, graphs, charts
- Description bibliographic
- Includes bibliographical references (pages 68-73).
- Public Abstract (ETD)
During the last few years, agricultural activities have increased Iowa's nutrients and nitrates concentration in water bodies. In 2015, Iowa installed the Iowa Water Quality (IWQ) network with more than 50 sensors to access real-time water quality data of water temperature, nitrate, pH, and dissolved oxygen concentrations in streams. However, the IWQ network only provides observations at specific locations, limiting the information required to develop a water quality model. Nutrient concentration and dissolved oxygen are controlled by water temperature. To predict water temperature for Iowa’s Cedar River basin, we formulated a model that took the conservation of thermal energy balance for a vertical well-mixed stream at the air-water interface. We evaluated the model using High-Resolution Rapid Refresh (HRRR) meteorological data and discharge simulated by the Iowa Flood Center forecasting model. We tested and validated the temperature model using the 2021 records from the USGS gauge in Cedar River at Waverly. The preliminary results of the model for the Cedar River subbasin indicate potential for further evaluation in other basins in the state.
- Academic Unit
- Civil and Environmental Engineering
- Record Identifier
- 9984647256602771
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