Comparison of evaporation estimates from the REEM and EEFlux models in a shallow water body. Case: Bustillos Lake, Chihuahua, Mexico
Waterbody evaporation (E) within endorheic basins in semiarid areas is a critical factor in determining the water balance. Accurate E measurements can provide valuable information for the sustainable management of water resources in the face of climate change scenarios. However, evaporation can be e...
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| Other Authors: | , , , , |
| Format: | Artículo |
| Language: | en_US |
| Published: |
2022
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| Subjects: | |
| Online Access: | https://doi.org/10.24850/j-tyca-13-6-5 https://docs.google.com/viewer?url=http://revistatyca.org.mx/index.php/tyca/libraryFiles/downloadPublic/108 http://revistatyca.org.mx/index.php/tyca/libraryFiles/downloadPublic/108 |
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| Summary: | Waterbody evaporation (E) within endorheic basins in semiarid areas is a critical factor in determining the water balance. Accurate E measurements can provide valuable information for the sustainable management of water resources in the face of climate change scenarios. However, evaporation can be estimated through methods as efficient as Penman using variables from agroclimatic stations, such as wind velocity, net radiation, relative humidity, and air temperature, which have a
spatiotemporal variability. Within the evaporation models based on remote sensing (RS) is the surface energy balance model (SEB), which has been applied to different methodologies and extends the measurements of evapotranspiration (ET) at a regional level. SEB-based methodologies use physical principles with minimal weather data requirements to estimate ET. Hence, this article compares two methodologies that estimate evaporation using RS: The Regional Evapotranspiration Estimate Model (REEM) and the Earth Engine Evapotranspiration Flux (EEFlux). Comparing ET measurements obtained from REEM and EEFlux for seven Landsat OLI scenes in the agriculture cycle of April to September applied against the simplified Penman equation showed that the REEM performed better (d=94%) than the EEFlux (d=68%) for the indicated period. Although the comparison of
REEM and EEFlux show accurate E measurements (REEM), gridded weather data (EEFlux) needs to improve, increasing the scale using local information. |
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