JCSET | Watershed Studies Institute Research Symposium

Title

“Got water? Forming an effective model for evapotranspiration in southern Kentucky utilizing remote sensors”

Presenter Information

Pamela RodriguezFollow

Academic Level at Time of Presentation

Senior

Major

Geology

List all Project Mentors & Advisor(s)

Dr. Bassil El Masri

Presentation Format

Poster Presentation

Abstract/Description

The hydrological cycle is an essential process on Earth, with its influence spanning from what places will have rain today to natural disasters that occur because of this cycle, like landslides and hurricanes. Due to it being integral to various processes, researchers have been studying the different components of the cycle. One component of this cycle is evapotranspiration (ET), the process in which water bodies evaporate and plants transpire water molecules, which has been monitored using satellite images and flux sites. Advances in remote sensing technology have made it possible to estimate ET in several different biomes using proven equations to form an effective model in observing ET at different temporal and spatial scales. In this research, the purpose is to improve the effectiveness of the Temperature and Green (TG) model through its application on two different biomes, located in Daniel Boone National Forest and Frankfort, KY. The data will be collected from NASA’s ECOsystem Spaceborne Thermal Radiometer Experiment on Space Station’s Water Use Efficiency (ECOSTRESS WUE) and MODIS remote sensing satellites to gather enhanced vegetation index (EVI) and land surface temperature (LST) of both sites. The relationship between Gross Primary Product and other environmental factors will be investigated to determine which variable demonstrates the strongest correlation to predicted and actual GPP, improving the current model’s accuracy in the observed sites. Our preliminary results showed ECOSTRESS WUE can depict the general trend in flux tower WUE for both the forest and pasture sites. Statistical analysis revealed the mean absolute errors and mean bias for ECOSTRESS WUE are dominated by MODIS GPP. Improving satellite ET estimates for shrublands will help better understand the effects of climate change on this biome's hydrological cycle on spatial and temporal scale.

Spring Scholars Week 2022 Event

Watershed Studies Institute Symposium

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“Got water? Forming an effective model for evapotranspiration in southern Kentucky utilizing remote sensors”

The hydrological cycle is an essential process on Earth, with its influence spanning from what places will have rain today to natural disasters that occur because of this cycle, like landslides and hurricanes. Due to it being integral to various processes, researchers have been studying the different components of the cycle. One component of this cycle is evapotranspiration (ET), the process in which water bodies evaporate and plants transpire water molecules, which has been monitored using satellite images and flux sites. Advances in remote sensing technology have made it possible to estimate ET in several different biomes using proven equations to form an effective model in observing ET at different temporal and spatial scales. In this research, the purpose is to improve the effectiveness of the Temperature and Green (TG) model through its application on two different biomes, located in Daniel Boone National Forest and Frankfort, KY. The data will be collected from NASA’s ECOsystem Spaceborne Thermal Radiometer Experiment on Space Station’s Water Use Efficiency (ECOSTRESS WUE) and MODIS remote sensing satellites to gather enhanced vegetation index (EVI) and land surface temperature (LST) of both sites. The relationship between Gross Primary Product and other environmental factors will be investigated to determine which variable demonstrates the strongest correlation to predicted and actual GPP, improving the current model’s accuracy in the observed sites. Our preliminary results showed ECOSTRESS WUE can depict the general trend in flux tower WUE for both the forest and pasture sites. Statistical analysis revealed the mean absolute errors and mean bias for ECOSTRESS WUE are dominated by MODIS GPP. Improving satellite ET estimates for shrublands will help better understand the effects of climate change on this biome's hydrological cycle on spatial and temporal scale.