Evapotranspiration estimation: complementary versus classical methods
Location
Eccles Conference Center
Event Website
http://water.usu.edu/
Start Date
3-29-2011 1:40 PM
End Date
3-29-2011 2:00 PM
Description
It is important to reliably estimate evapotranspiration (ET) in semi-arid regions because rainfall is mostly lost as ET. Furthermore, rural river basins are characterized by scarcity of data and resources. This research aims at estimating ET in semi-arid rural river basins with limited data for the purpose of water resources planning and management. In the literature, several classical methods are used to estimate potential ET. Those methods are primarily based on temperature, radiation, combination, or pan evaporation. However, estimating actual ET requires detailed local data such as land cover/land use, crop pattern, growing cycle, etc. Still, these classical methods are mainly applicable to predict ET from crop covered areas during the growing seasons. In water resources planning, the important estimate needed is the total water loss from the land surface that mayor may not include transpiration from crop areas. For several decades, complementary methods, including Complementary Relationship Areal Evapotranspiration (CRAE), Advection-Aridity (AA), and Granger and Gray (GG) methods, have been used to estimate ET. These methods are attractive due to simplicity, practicability, and reliability in estimating actual, wet environment, and potential ET at regional scale using meteorological data only. Previous studies attempted to use the complementary methods with little success given the limited understanding of the methods and the confusion due to the definitions of various terms. Still the complementary methods offer a distinct advantage over the classical method given the simplicity of data and the ability to estimate total water loss as opposed to ET. In this study the applicability of the complementary methods in estimating ET and the needs to perform additional revisions to the methods to improve estimates if necessary are investigated. In addition, the estimates of the complementary methods are profoundly compared to those of the classical methods.
Evapotranspiration estimation: complementary versus classical methods
Eccles Conference Center
It is important to reliably estimate evapotranspiration (ET) in semi-arid regions because rainfall is mostly lost as ET. Furthermore, rural river basins are characterized by scarcity of data and resources. This research aims at estimating ET in semi-arid rural river basins with limited data for the purpose of water resources planning and management. In the literature, several classical methods are used to estimate potential ET. Those methods are primarily based on temperature, radiation, combination, or pan evaporation. However, estimating actual ET requires detailed local data such as land cover/land use, crop pattern, growing cycle, etc. Still, these classical methods are mainly applicable to predict ET from crop covered areas during the growing seasons. In water resources planning, the important estimate needed is the total water loss from the land surface that mayor may not include transpiration from crop areas. For several decades, complementary methods, including Complementary Relationship Areal Evapotranspiration (CRAE), Advection-Aridity (AA), and Granger and Gray (GG) methods, have been used to estimate ET. These methods are attractive due to simplicity, practicability, and reliability in estimating actual, wet environment, and potential ET at regional scale using meteorological data only. Previous studies attempted to use the complementary methods with little success given the limited understanding of the methods and the confusion due to the definitions of various terms. Still the complementary methods offer a distinct advantage over the classical method given the simplicity of data and the ability to estimate total water loss as opposed to ET. In this study the applicability of the complementary methods in estimating ET and the needs to perform additional revisions to the methods to improve estimates if necessary are investigated. In addition, the estimates of the complementary methods are profoundly compared to those of the classical methods.
https://digitalcommons.usu.edu/runoff/2011/AllAbstracts/29