Ehsan Ebrahimi
Utah State University
| Subject Areas: | Water Management, Water resources systems |
Recent Activity
ABSTRACT:
This study presents a comprehensive comparison of gridded datasets for the Great Salt Lake (GSL) basin, focusing on precipitation and temperature as the main inputs for hydrological balances. The evaluated gridded datasets include PRISM, DAYMET, GRIDMET, NLDAS-2, and CONUS404, with in-situ data used for assessing alignment and accuracy. Key metrics such as Nash-Sutcliffe Efficiency (NSE), Kling-Gupta Efficiency (KGE), Root Mean Square Error (RMSE), Mean Absolute Error (MAE), and Correlation Coefficient (CC) were employed to evaluate gridded dataset performance. Spatial and temporal accuracy analyses were conducted across different GSL basin regions to understand variations in accuracy. DAYMET emerged as the leading dataset for precipitation across most metrics, demonstrating consistent performance. For temperature, GRIDMET and PRISM ranked higher, indicating better representation of temperature patterns in the GSL basin. Spatial analysis revealed variability in accuracy for both temperature and precipitation data, emphasizing the importance of selecting suitable datasets for different regions to enhance overall accuracy. The insights from this study can inform environmental forecasting and water resource management in the GSL basin, assisting researchers and decision-makers in choosing reliable gridded datasets for hydrological studies.
ABSTRACT:
This report details the development and hosting of a Jupyter Notebook on HydroShare, designed to provide a comprehensive, reproducible analysis of streamflow data from the USGS gaging station at Blacksmith Fork above Hyrum Reservoir Dam, Utah. The notebook utilizes Python libraries such as "pandas" for data manipulation and "matplotlib" for visualization, enabling users to reproduce the analyses of streamflow variability and assess the impact of the 2021 drought on local water resources.
Contact
| (Log in to send email) |
| All | 0 |
| Collection | 0 |
| Resource | 0 |
| App Connector | 0 |
ABSTRACT:
This report details the development and hosting of a Jupyter Notebook on HydroShare, designed to provide a comprehensive, reproducible analysis of streamflow data from the USGS gaging station at Blacksmith Fork above Hyrum Reservoir Dam, Utah. The notebook utilizes Python libraries such as "pandas" for data manipulation and "matplotlib" for visualization, enabling users to reproduce the analyses of streamflow variability and assess the impact of the 2021 drought on local water resources.
Created: April 20, 2024, 5:44 a.m.
Authors: Morovati, Reza · Ebrahimi, Ehsan · Kahrizi, Ehsan · Claure, Pamela
ABSTRACT:
This study presents a comprehensive comparison of gridded datasets for the Great Salt Lake (GSL) basin, focusing on precipitation and temperature as the main inputs for hydrological balances. The evaluated gridded datasets include PRISM, DAYMET, GRIDMET, NLDAS-2, and CONUS404, with in-situ data used for assessing alignment and accuracy. Key metrics such as Nash-Sutcliffe Efficiency (NSE), Kling-Gupta Efficiency (KGE), Root Mean Square Error (RMSE), Mean Absolute Error (MAE), and Correlation Coefficient (CC) were employed to evaluate gridded dataset performance. Spatial and temporal accuracy analyses were conducted across different GSL basin regions to understand variations in accuracy. DAYMET emerged as the leading dataset for precipitation across most metrics, demonstrating consistent performance. For temperature, GRIDMET and PRISM ranked higher, indicating better representation of temperature patterns in the GSL basin. Spatial analysis revealed variability in accuracy for both temperature and precipitation data, emphasizing the importance of selecting suitable datasets for different regions to enhance overall accuracy. The insights from this study can inform environmental forecasting and water resource management in the GSL basin, assisting researchers and decision-makers in choosing reliable gridded datasets for hydrological studies.