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Ecosystem Metabolism Data for Brownlee Reservoir, Snake River, Idaho/Oregon, 2017-2023

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DataCite Commons2025-05-27 更新2026-05-07 收录
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https://www.sciencebase.gov/catalog/item/67e6d65bd34ee3695ea1d836
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This data release presents multi-year ecosystem metabolism model outputs for Brownlee Reservoir at varying depths across three locations (River Miles 318, 300, and 286) along the Snake River. Data include field-collected model input data and model outputs of daily gross primary production (GPP), ecosystem respiration (R), and net ecosystem production (NEP). Field data were collected from 2017 to 2023 (excluding winter months) and include high-frequency measurements of dissolved oxygen (DO) and temperature at varying depths, photosynthetically active radiation (PAR), and wind speed. Biweekly water column profiles of DO, temperature, and PAR, used to support the estimation of thermocline depth and the calculation of light extinction curves, are also presented. Gaps in raw field data were filled using linear regression and spline interpolation. Ecosystem metabolism was modeled using the LakeMetabolizer package in R. The modeling process included calculations of DO saturation concentration (from water temperature), gas exchange velocity (from wind speed and water temperature) and mixing depth (via harmonic regression of thermocline depth). An adapted maximum likelihood estimation (MLE) model was employed for estimating daily GPP, R, and NEP at different depths and locations within the reservoir. LakeMetabolizer inputs and outputs are provided as CSV files, along with R scripts to enable users to understand and reproduce the data processing, variable derivation, and ecosystem metabolism modeling steps. These scripts are structured to accommodate future integration of additional datasets by stakeholders, including Idaho Power Company and the United States Geological Survey. The data and scripts aim to support continued research, enhance reproducibility, and inform the study of broader water quality patterns, such as nutrient loading, contamination, and algal blooms, on both seasonal and long-term scales.
提供机构:
U.S. Geological Survey
创建时间:
2025-05-27
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