9786202015431 - Testing and Development of Evapotranspiration Models for India: A Simplified Approach for Estimation of Evapotranspiration de Abraham, M.; Mohan, S. (6 resultados)

Paperback. Condición: Brand New. 148 pages. 8.66x5.91x0.34 inches. In Stock.

Taschenbuch. Condición: Neu. Testing and Development of Evapotranspiration Models for India | A Simplified Approach for Estimation of Evapotranspiration | M. Abraham (u. a.) | Taschenbuch | 148 S. | Englisch | 2017 | LAP LAMBERT Academic Publishing | EAN 9786202015431 | Verantwortliche Person für die EU: preigu GmbH & Co. KG, Lengericher Landstr. 19, 49078 Osnabrück, mail[at]preigu[dot]de | Anbieter: preigu.

Taschenbuch. Condición: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -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. 148 pp. Englisch.

Condición: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Autor/Autorin: Abraham M.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.

Taschenbuch. Condición: Neu. This item is printed on demand - Print on Demand Titel. Neuware -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.VDM Verlag, Dudweiler Landstraße 99, 66123 Saarbrücken 148 pp. Englisch.

Taschenbuch. Condición: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - 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.