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Title: Dataset: "Widespread Drought-driven Declines in Streamflows and Water quality in the Upper Colorado River Basin (1998-2022)"

Abstract

This data package contains the associated data and scripts for Nagamoto et al (2025). Widespread Drought-driven Declines in Streamflows and Water quality in the Upper Colorado River Basin (1998-2022). [Manuscript in preparation].This purpose of this study was to investigate the impact of the 21st century drought on water quantity and quality at catchments throughout the Upper Colorado River Basin (UCRB). We used stream flow, water temperature, specific conductance, air temperature, precipitation, and catchment attribute data for over 200 sites in the UCRB, collected from the National Water Information System using Basin3D (Varadharajan, 2023), GAGESII (Falcone, 2010), and the Google Earth Engine. We identified years of severe drought between 1998 and 2022 using the Standardized Precipitation Evaporation Index (SPEI), then calculated the relative change percentage of the stream flow, water temperature, and specific conductance from drought versus non-drought years. We used the attribute information from GAGESII to investigate what physical traits of catchments are associated streamflow vulnerability (greater relative change) or resilience to drought. We used land cover data from the National Land Cover Database (USGS, 2024) to assess any changes to physical attributes that may not be represented in the static attributes information in GAGESII. To increase data availability, wemore » modeled stream temperature using methods from Willard, 2023. While the study period is water years 1998 to 2022, the raw water quantity and quality data extends to 1950 and the meteorological data extends to 1980. The data and code can be downloaded via the UCRB_drought.zip. Within the zip, the files are organized as follows:- INPUTS: Contains all input data used in UCRB_Drought_Workflow.ipynb- OUTPUTS: Contains all intermediate data created from UCRB_Drought_Workflow.ipynb as well as final products including the calculated Standardized Evapotranspiration Index (SPEI)- climatic_variables: The code used to collect meteorologic data from Google Earth Engine- feature_importance: The code used for the catchment attributes analysis- preprocessing: Code used in UCRB_Drought_Workflow.ipynb- pyeto: Code used in UCRB_Drought_Workflow.ipynb- calculations: Code used in UCRB_Drought_Workflow.ipynb- README.md- UCRB_Drought_Workflow.ipynb: The main code for the analysis- requirements_ucrb-drought.yml: The requirements file to create a virtual environment and Jupyter Lab kernel to run the codeThe INPUTS folder is organized into the following major directories and sub-directories. The "RDC_WT_SC_RAW" folder contains raw data for streamflow, water temperature, and specific conductance in a ".h5" file. The "NLCD_RAW" folder contains ".csv" files with annual land cover percentages for counties within the UCRB. The "MET_RAW" folder contains a ".csv" file with monthly meteorological data (air temperature and precipitation) for the sites in the UCRB which was obtained from code in the climatic_variables folder. The "GAGESII" folder contains ".csv" files with physical catchment attribute variables for catchments across the country. The "WT_LSTM_data" folder contains ".csv" files with calculated WT (Willard, 2023) and the associated RMSEs. The "Upper_Colorado_River_Basin_Boundary" folder contains geographic data including a shapefile for plotting in the UCRB_Drought_Workflow.ipynb.The OUTPUTS folder is organized into the following major directories and sub-directories. The "RDC_WT_SC_data" folder contains a folder "Water_year" with the associated cleaned data, metadata, and data availability information in ".csv" files, a folder "Median_Relchange" with the relative change comparing drought to non-drought years in ".csv" files, and a folder "RDC_PeakFlow_Relchange" that has ".csv" files for the relative change in peak flow. The "NLCD_data" folder contains the difference in land cover from the beginning to end of the study period and the percentage of the county that is within UCRB bounds can be found in Nagamoto et al (2025)). The "MET_data" folder contains separated monthly air temperature and precipitation data and the calculated PET in ".csv" files. The "SPEI_data" folder contains ".csv" files with calculated SPEI values (one restricted to the study period and the other with information from the entire MET data period). The "Paper_Tables" folder contains two ".csv" files containing site information and data availability and information about the GAGESII trait aggregated categories. The base directory includes the file “flmd.csv” for a list and description of all files and the file “dd.csv” for data dictionaries.Scripts for preprocessing, analysis, and figure generation are located in the associated GitHub repository found at [https://github.com/iNAIADS/drought-impacts/tree/develop/UCRB-drought].UPDATE: Title and code file updated to match submitted manuscript 10-15-2025.To cite this code, please use the following BibTeX:@misc{nagamoto2025drought,author = {Emily Nagamoto and Fabio Ciulla and Mohammad Ombadi and Jared Willard and Rosemary Carroll and Charuleka Varadharajan},title = {Dataset: "Widespread Drought-driven Declines in Streamflows and Water quality in the Upper Colorado River Basin (1998-2022)"},year = {2025},doi = {10.15485/2551894},publisher = {ESS-DIVE Repository},url = {https://data.ess-dive.lbl.gov/datasets/doi:10.15485/2551894}}« less

Authors:
ORCiD logo ; ORCiD logo ; ORCiD logo ; ORCiD logo ; ORCiD logo ; ORCiD logo
  1. Lawrence Berkeley National Laboratory
  2. University of Michigan
  3. National Renewable Energy Laboratory
  4. Desert Research Institute
Publication Date:
DOE Contract Number:  
AC02-05CH11231
Research Org.:
iNAIADS
Sponsoring Org.:
U.S. DOE > Office of Science > Biological and Environmental Research (BER)
Subject:
54 ENVIRONMENTAL SCIENCES; EARTH SCIENCE > TERRESTRIAL HYDROSPHERE > SURFACE WATER; EARTH SCIENCE > TERRESTRIAL HYDROSPHERE > WATER QUALITY/WATER CHEMISTRY; ESS-DIVE File Level Metadata Reporting Format; Upper Colorado River Basin; drought; meteorologic drought; specific conductance; streamflow; water temperature
OSTI Identifier:
2551894
DOI:
https://doi.org/10.15485/2551894

Citation Formats

Nagamoto, Emily, Ciulla, Fabio, Ombadi, Mohammed, Willard, Jared, Carroll, Rosemary, and Varadharajan, Charuleka. Dataset: "Widespread Drought-driven Declines in Streamflows and Water quality in the Upper Colorado River Basin (1998-2022)". United States: N. p., 2025. Web. doi:10.15485/2551894.
Nagamoto, Emily, Ciulla, Fabio, Ombadi, Mohammed, Willard, Jared, Carroll, Rosemary, & Varadharajan, Charuleka. Dataset: "Widespread Drought-driven Declines in Streamflows and Water quality in the Upper Colorado River Basin (1998-2022)". United States. doi:https://doi.org/10.15485/2551894
Nagamoto, Emily, Ciulla, Fabio, Ombadi, Mohammed, Willard, Jared, Carroll, Rosemary, and Varadharajan, Charuleka. 2025. "Dataset: "Widespread Drought-driven Declines in Streamflows and Water quality in the Upper Colorado River Basin (1998-2022)"". United States. doi:https://doi.org/10.15485/2551894. https://www.osti.gov/servlets/purl/2551894. Pub date:Wed Jan 01 04:00:00 UTC 2025
@article{osti_2551894,
title = {Dataset: "Widespread Drought-driven Declines in Streamflows and Water quality in the Upper Colorado River Basin (1998-2022)"},
author = {Nagamoto, Emily and Ciulla, Fabio and Ombadi, Mohammed and Willard, Jared and Carroll, Rosemary and Varadharajan, Charuleka},
abstractNote = {This data package contains the associated data and scripts for Nagamoto et al (2025). Widespread Drought-driven Declines in Streamflows and Water quality in the Upper Colorado River Basin (1998-2022). [Manuscript in preparation].This purpose of this study was to investigate the impact of the 21st century drought on water quantity and quality at catchments throughout the Upper Colorado River Basin (UCRB). We used stream flow, water temperature, specific conductance, air temperature, precipitation, and catchment attribute data for over 200 sites in the UCRB, collected from the National Water Information System using Basin3D (Varadharajan, 2023), GAGESII (Falcone, 2010), and the Google Earth Engine. We identified years of severe drought between 1998 and 2022 using the Standardized Precipitation Evaporation Index (SPEI), then calculated the relative change percentage of the stream flow, water temperature, and specific conductance from drought versus non-drought years. We used the attribute information from GAGESII to investigate what physical traits of catchments are associated streamflow vulnerability (greater relative change) or resilience to drought. We used land cover data from the National Land Cover Database (USGS, 2024) to assess any changes to physical attributes that may not be represented in the static attributes information in GAGESII. To increase data availability, we modeled stream temperature using methods from Willard, 2023. While the study period is water years 1998 to 2022, the raw water quantity and quality data extends to 1950 and the meteorological data extends to 1980. The data and code can be downloaded via the UCRB_drought.zip. Within the zip, the files are organized as follows:- INPUTS: Contains all input data used in UCRB_Drought_Workflow.ipynb- OUTPUTS: Contains all intermediate data created from UCRB_Drought_Workflow.ipynb as well as final products including the calculated Standardized Evapotranspiration Index (SPEI)- climatic_variables: The code used to collect meteorologic data from Google Earth Engine- feature_importance: The code used for the catchment attributes analysis- preprocessing: Code used in UCRB_Drought_Workflow.ipynb- pyeto: Code used in UCRB_Drought_Workflow.ipynb- calculations: Code used in UCRB_Drought_Workflow.ipynb- README.md- UCRB_Drought_Workflow.ipynb: The main code for the analysis- requirements_ucrb-drought.yml: The requirements file to create a virtual environment and Jupyter Lab kernel to run the codeThe INPUTS folder is organized into the following major directories and sub-directories. The "RDC_WT_SC_RAW" folder contains raw data for streamflow, water temperature, and specific conductance in a ".h5" file. The "NLCD_RAW" folder contains ".csv" files with annual land cover percentages for counties within the UCRB. The "MET_RAW" folder contains a ".csv" file with monthly meteorological data (air temperature and precipitation) for the sites in the UCRB which was obtained from code in the climatic_variables folder. The "GAGESII" folder contains ".csv" files with physical catchment attribute variables for catchments across the country. The "WT_LSTM_data" folder contains ".csv" files with calculated WT (Willard, 2023) and the associated RMSEs. The "Upper_Colorado_River_Basin_Boundary" folder contains geographic data including a shapefile for plotting in the UCRB_Drought_Workflow.ipynb.The OUTPUTS folder is organized into the following major directories and sub-directories. The "RDC_WT_SC_data" folder contains a folder "Water_year" with the associated cleaned data, metadata, and data availability information in ".csv" files, a folder "Median_Relchange" with the relative change comparing drought to non-drought years in ".csv" files, and a folder "RDC_PeakFlow_Relchange" that has ".csv" files for the relative change in peak flow. The "NLCD_data" folder contains the difference in land cover from the beginning to end of the study period and the percentage of the county that is within UCRB bounds can be found in Nagamoto et al (2025)). The "MET_data" folder contains separated monthly air temperature and precipitation data and the calculated PET in ".csv" files. The "SPEI_data" folder contains ".csv" files with calculated SPEI values (one restricted to the study period and the other with information from the entire MET data period). The "Paper_Tables" folder contains two ".csv" files containing site information and data availability and information about the GAGESII trait aggregated categories. The base directory includes the file “flmd.csv” for a list and description of all files and the file “dd.csv” for data dictionaries.Scripts for preprocessing, analysis, and figure generation are located in the associated GitHub repository found at [https://github.com/iNAIADS/drought-impacts/tree/develop/UCRB-drought].UPDATE: Title and code file updated to match submitted manuscript 10-15-2025.To cite this code, please use the following BibTeX:@misc{nagamoto2025drought,author = {Emily Nagamoto and Fabio Ciulla and Mohammad Ombadi and Jared Willard and Rosemary Carroll and Charuleka Varadharajan},title = {Dataset: "Widespread Drought-driven Declines in Streamflows and Water quality in the Upper Colorado River Basin (1998-2022)"},year = {2025},doi = {10.15485/2551894},publisher = {ESS-DIVE Repository},url = {https://data.ess-dive.lbl.gov/datasets/doi:10.15485/2551894}}},
doi = {10.15485/2551894},
journal = {},
number = ,
volume = ,
place = {United States},
year = {Wed Jan 01 04:00:00 UTC 2025},
month = {Wed Jan 01 04:00:00 UTC 2025}
}