Pamela Claure
Utah State University
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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:
As a part of my PhD research, I am developing a water management model within the Water Evaluation and Planning System (WEAP) platform for the Bear Watershed. However, there exists an established WEAP model for the specified area, covering the modeling period from 1966 to 2006 with a monthly time step.This notebook specifically concentrates on analyzing the Logan River. Given that the WEAP model's timeframe spans from 1966 to 2006, I will compare this modeled flow with data available from the Logan River Observatory (LRO) from 2018 to 2023. Referring to the schematic of the WEAP model, I selected the station Logan River at Guinavah Campground Bridge and obtained discharge data from the LRO website.
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Created: April 17, 2024, 6:30 p.m.
Authors: Claure, Pamela
ABSTRACT:
As a part of my PhD research, I am developing a water management model within the Water Evaluation and Planning System (WEAP) platform for the Bear Watershed. However, there exists an established WEAP model for the specified area, covering the modeling period from 1966 to 2006 with a monthly time step.This notebook specifically concentrates on analyzing the Logan River. Given that the WEAP model's timeframe spans from 1966 to 2006, I will compare this modeled flow with data available from the Logan River Observatory (LRO) from 2018 to 2023. Referring to the schematic of the WEAP model, I selected the station Logan River at Guinavah Campground Bridge and obtained discharge data from the LRO website.
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.