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Accueil du site → Doctorat → Inde → 2017 → Estimation of reference evapotranspiration and crop water requirment using artificial neural network for semiarid region of Maharashtra

Vasantrao Naik Marathwada Krishi Vidyapeeth, Parbhani (2017)

Estimation of reference evapotranspiration and crop water requirment using artificial neural network for semiarid region of Maharashtra

Awari, Harishchandra Wamanrao

Titre : Estimation of reference evapotranspiration and crop water requirment using artificial neural network for semiarid region of Maharashtra

Auteur : Awari, Harishchandra Wamanrao

Université de soutenance : Vasantrao Naik Marathwada Krishi Vidyapeeth, Parbhani

Grade : Doctor of Philosophy (PhD) in Agricultural Engineering 2017

Résumé
Evapotranspiration is a major and important component of hydrological process consisting of evaporation from land surface and transpiration of water from plants. Accurate estmation of reference crop evapotranspiration (ETo) in the water balance or irrigation scheduling allows to improve water resources utilization pattern in general and crop water management practices in particular for the region. Several methods including the most intricate energy balance methods requiring detail climatic data to simpler methods requiring less data were developed and modified worldover to estimate reference crop evapotranspiration (ETo) under various climatic conditions. Amongst them Penman-Monteith FAO-56 (PM 56) method has been accepted as the standardized method for precise estimation of ETo. For several resons the input data on climatic variables required for PM 56 method may not be easily available at every location because of either unavailability of nearby metereological station or difficulties in collecting accurate data on all necessary climatic variables at available station, especially in developing countries. Under such circumastance one may be forced to use data from the station which is far away, with completely different hydrometereological settings which manytimes restricts application of Penman-Monteith FAO-56 method. This directs towards development of simple alternative techniques like artificial neural network for accurate estimation of ETo for situations where values of some of the potential variables are not available. Marathwada, the semiarid region always remains under the threats of frequesnt droughts and subsequent crop failure for want of water. Identifying the most suitable method or advance technique for accurate estimation of ETo, its forecasting for water resources planning and computing the crop water requirement of major cropping system of the region is therefore a major challenge

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