Improving Complementary Methods to Predict Evapotranspiration for Data Deficit Conditions and Global Applications Under Climate Change

A reliable estimate of evapotranspiration (ET) in river basins is important for the purpose of water resources planning and management. ET represents a significant portion of rainfall in the water budget; therefore, the uncertainty in estimating ET can lead to the inaccurate prediction of water resources. While remote sensing techniques are available to estimate ET, such methods are expensive and necessary data may not be readily available. Classical methods of estimating ET require detailed land use/cover information that are not readily available in rural river basins. Complementary methods provide simple and reliable approaches to estimate ET using meteorological data only. However, these methods have not been investigated in detail to assess the overall applicability and the needs for revisions if any. In this work, an improved approach to use the complementary methods using readily available meteorological data is presented. The methodology is validated using 34 global FLUXNET sites with heterogeneous land use/cover, climatic, and physical conditions. The method was compared with classical methods using Ghana as a study area where original pioneering studies of ET have been performed. The work was extended to develop global maps of ET and water surplus (precipitation - ET) for the 20th century followed by climate change-induced 21st century estimates for 2040-2069 and 2070-2099 periods. The emission scenario used was the moderate A1B with the global climate models CGCM3.1 and HADGEM1. The results were assessed at different scales from global to regional such as for potential outcomes of climate change on ET and water surplus

Improving the Complementary Methods to Estimate Evapotranspiration Under Diverse Climatic and Physical Conditions

Reliable estimation of evapotranspiration (ET) is important for the purpose of water resources planning and management. Complementary methods, including complementary relationship areal evapotranspiration (CRAE), advection aridity (AA) and Granger and Gray (GG), have been used to estimate ET because these methods are simple and practical in estimating regional ET using meteorological data only. However, prior studies have found limitations in these methods especially in contrasting climates. This study aims to develop a calibration-free universal method using the complementary relationships to compute regional ET in contrasting climatic and physical conditions with meteorological data only. The proposed methodology consists of a systematic sensitivity analysis using the existing complementary methods. This work used 34 global FLUXNET sites where eddy covariance (EC) fluxes of ET are available for validation. A total of 33 alternative model variations from the original complementary methods were proposed. Further analysis using statistical methods and simplified climatic class definitions produced one distinctly improved GG-model-based alternative. The proposed model produced a single-step ET formulation with results equal to or better than the recent studies using data-intensive, classical methods. Average root mean square error (RMSE), mean absolute bias (BIAS) and R2 (coefficient of determination) across 34 global sites were 20.57 mm month−1, 10.55 mm month−1and 0.64, respectively. The proposed model showed a step forward toward predicting ET in large river basins with limited data and requiring no calibration

Is There a Global Model to Reliably Predicting Evapotranspiration?

A reliable estimate of Evapotranspiration (ET) in river basins is truly important for the purpose of water resources planning and management. Therefore, the uncertainty in estimating ET can lead to the inaccurate prediction of water balance and water resources needs. The 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 ET (or total water loss) at regional scale using meteorological data only. These methods are applied to 34 FLUXNET sites representing different physical and climatic conditions in the globe. In comparison to eddy covariance (EC) fluxes of ET, the results indicate that further improvements to those methods can be performed. A wide set of model variations are developed and statistically tested in order to better simulate the latent heat fluxes of ET. The GG method was found to be promising once wet environment ET is calculated by the Priestley-Taylor equation and the basic complementary relationship is applied to the method. The results of the modified GG model are equal or even better than those of the most recent ET studies. Eventually, the objective of this study was achieved by developing a global, simple but robust, model using minimal data requirements to reliably estimate regional ET in a variety of ecosystems, climates, and environmental conditions

Can complementary methods reliaby estimate evapotranspiration in semi-arid regions?

In semi-arid regions, the largest portion of rainfall is lost as evapotranspiration (ET). Therefore, the uncertainty in estimating ET can lead to the inaccurate prediction of water balance and water resources needs. Furthermore, rural river basins are characterized by scarcity of data and resources, adding additional challenges in estimating water resources needs in the basin. 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. However, estimating actual ET requires detailed local data such as temperature, 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. On the other hand, actual water loss from the land surface is not typically restricted to crop areas only; instead evaporation could happen from open water bodies as well as from open land surfaces with minimal vegetation cover. In water resources planning, the important estimate needed is the total water loss from the land surface that may or 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. The purpose of this study is to investigate the applicability of the complementary methods in estimating ET and the needs to perform additional revisions to the methods to improve estimates if necessary. A rural semi-arid region in northern Ghana is used as a case study. The monthly meteorological data from five synoptic stations are used in the analysis. The results show that the complementary methods overestimate ET. The probable reason for this discrepancy was due to the over estimation of net radiation. Once the method was modified, the estimates were promising compared to the results from prior studies conducted in the same region. It is found that the complementary wet environment ET is close to the Penman estimates while the complementary potential ET estimate is close to pan evaporation. The long term annual mean rainfall ranges from 984 to 1241 mm while the long term annual mean ET is 64% to 80% of rainfall

Can complementary methods reliably estimate evapotranspiration in semi-arid regions?

In semi-arid regions, the largest portion of rainfall is lost as evapotranspiration (ET). Therefore, the uncertainty in estimating ET can lead to the inaccurate prediction of water balance and water resources needs. Furthermore, rural river basins are characterized by scarcity of data and resources, adding additional challenges in estimating water resources needs in the basin. 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. However, estimating actual ET requires detailed local data such as temperature, 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. On the other hand, actual water loss from the land surface is not typically restricted to crop areas only; instead evaporation could happen from open water bodies as well as from open land surfaces with minimal vegetation cover. In water resources planning, the important estimate needed is the total water loss from the land surface that may or 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. The purpose of this study is to investigate the applicability of the complementary methods in estimating ET and the needs to perform additional revisions to the methods to improve estimates if necessary. A rural semi-arid region in northern Ghana is used as a case study. The monthly meteorological data from five synoptic stations are used in the analysis. The results show that the complementary methods overestimate ET. The probable reason for this discrepancy was due to the over estimation of net radiation. Once the method was modified, the estimates were promising compared to the results from prior studies conducted in the same region. It is found that the complementary wet environment ET is close to the Penman estimates while the complementary potential ET estimate is close to pan evaporation. The long term annual mean rainfall ranges from 984 to 1241 mm while the long term annual mean ET is 64% to 80% of rainfall

Is there a global model to reliably predicting evapotranspiration?

A reliable estimate of Evapotranspiration (ET) in river basins is truly important for the purpose of water resources planning and management. Therefore, the uncertainty in estimating ET can lead to the inaccurate prediction of water balance and water resources needs. The 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 ET (or total water loss) at regional scale using meteorological data only. These methods are applied to 34 FLUXNET sites representing different physical and climatic conditions in the globe. In comparison to eddy covariance (EC) fluxes of ET, the results indicate that further improvements to those methods can be performed. A wide set of model variations are developed and statistically tested in order to better simulate the latent heat fluxes of ET. The GG method was found to be promising once wet environment ET is calculated by the Priestley-Taylor equation and the basic complementary relationship is applied to the method. The results of the modified GG model are equal or even better than those of the most recent ET studies. Eventually, the objective of this study was achieved by developing a global, simple but robust, model using minimal data requirements to reliably estimate regional ET in a variety of ecosystems, climates, and environmental conditions

Predicting regional evapotranspiration and groundwater recharge: A country-wide study from Ghana

This study uses a modified Granger and Gray model to estimate evapotranspiration and then groundwater recharge in Ghana. The overall results show that the model is capable of reliably predicting regional evapotranspiration using a small number of monitoring stations with meteorological data only. This information allows the estimation of groundwater recharge via the water balance equation. The results indicate that the aquifer system is sufficiently recharged, especially in northern Ghana, where dry conditions prevail, to allow the development of groundwater resources to satisfy increasing water demands

Can complementary methods reliably estimate evapotranspiration in semi-arid regions?

In semi-arid regions, the largest portion of rainfall is lost as evapotranspiration (ET). Therefore, the uncertainty in estimating ET can lead to the inaccurate prediction of water balance and water resources needs. Furthermore, rural river basins are characterized by scarcity of data and resources, adding additional challenges in estimating water resources needs in the basin. 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. However, estimating actual ET requires detailed local data such as temperature, 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. On the other hand, actual water loss from the land surface is not typically restricted to crop areas only; instead evaporation could happen from open water bodies as well as from open land surfaces with minimal vegetation cover. In water resources planning, the important estimate needed is the total water loss from the land surface that may or 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. The purpose of this study is to investigate the applicability of the complementary methods in estimating ET and the needs to perform additional revisions to the methods to improve estimates if necessary. A rural semi-arid region in northern Ghana is used as a case study. The monthly meteorological data from five synoptic stations are used in the analysis. The results show that the complementary methods overestimate ET. The probable reason for this discrepancy was due to the over estimation of net radiation. Once the method was modified, the estimates were promising compared to the results from prior studies conducted in the same region. It is found that the complementary wet environment ET is close to the Penman estimates while the complementary potential ET estimate is close to pan evaporation. The long term annual mean rainfall ranges from 984 to 1241 mm while the long term annual mean ET is 64% to 80% of rainfall