Testing and Development of Evapotranspiration Models for India: A Simplified Approach for Estimation of Evapotranspiration - Couverture souple

Abraham, M.; Mohan, S.

 
9786202015431: Testing and Development of Evapotranspiration Models for India: A Simplified Approach for Estimation of Evapotranspiration
Couverture souple
ISBN 10 : 6202015438 ISBN 13 : 9786202015431
Editeur : LAP LAMBERT Academic Publishing, 2017

Synopsis

The book contains comparative evaluation of existing evapotranspiration (ET) models and development of site specific evapotranspiration models for various agro-climatic regions of India. Evapotranspiration was estimated using existing models for twelve stations falling under different agro-climatic regions. Sensitivity analysis was carried out to identify more sensitive parameters to understand the relative importance of variables on ET and the impact of estimation errors due to individual variables. Uncertainty analysis was carried out for finding the input variable uncertainty to judge the goodness of fit. Modifications to existing ET equations were made based on regression analysis and genetic algorithm. New regression equations were developed with stepwise regression and using the most significant variables identified by Principal Component Analysis (PCA). Simplified models were developed for ET estimation by Artificial Neural Network (ANN) with all the climatic variables and with the variables identified by PCA. The regression equation using PCA variable was identified as the best method to estimate of ET.

Les informations fournies dans la section « Synopsis » peuvent faire référence à une autre édition de ce titre.

Présentation de l'éditeur

The book contains comparative evaluation of existing evapotranspiration (ET) models and development of site specific evapotranspiration models for various agro-climatic regions of India. Evapotranspiration was estimated using existing models for twelve stations falling under different agro-climatic regions. Sensitivity analysis was carried out to identify more sensitive parameters to understand the relative importance of variables on ET and the impact of estimation errors due to individual variables. Uncertainty analysis was carried out for finding the input variable uncertainty to judge the goodness of fit. Modifications to existing ET equations were made based on regression analysis and genetic algorithm. New regression equations were developed with stepwise regression and using the most significant variables identified by Principal Component Analysis (PCA). Simplified models were developed for ET estimation by Artificial Neural Network (ANN) with all the climatic variables and with the variables identified by PCA. The regression equation using PCA variable was identified as the best method to estimate of ET.

Biographie de l'auteur

Dr. M. Abraham is Scientist-E in Centre for Remote Sensing and Geoinformatics, Sathyabama University, Chennai, Dr. S. Mohan is professor in Department of Civil Engineering, Indian Institute of Technology, Madras, and Dr. K. S. Rawat is Scientist-E in Centre for Remote Sensing and Geoinformatics, Sathyabama University, Chennai.

Les informations fournies dans la section « A propos du livre » peuvent faire référence à une autre édition de ce titre.

Éditeur
LAP LAMBERT Academic Publishing
Date d'édition
2017
Langue
anglais
ISBN 10 
6202015438
ISBN 13 
9786202015431
Reliure
Broché
Nombre de pages
148
Éditeur
Rawat K. S.
Coordonnées du fabricant
non disponible
Personne responsable
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