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Nirma University (2017)

Regional Agricultural drought characterization using remote sensing based observations from geostationary satellites

Vyas Swapnil

Titre : Regional Agricultural drought characterization using remote sensing based observations from geostationary satellites

Auteur : Vyas Swapnil

Université de soutenance : Nirma University

Grade : Doctor of Philosophy (PhD) 2017

Résumé
Agricultural drought has been a prime concern in an agrarian country like India. The dependencies on the vagaries of the south west monsoon and the erratic climatic conditions have made the country more vulnerable to increased frequency of drought in the recent years. The untimely onset and uneven distribution of south-west monsoon rainfall lead to agricultural drought causing reduction in food-grain production with high vulnerability over semi-arid tract (SAT) of India. In addition to current system of implementation, there is a need of advanced monitoring and assessment of agricultural drought at regional scale regarding its onset, progression and impact on crops to minimize the damage. The present study aimed to develop a pathway of three-stage (early, mid, late) regional agricultural drought characterization including early warning using biophysical, meteorological and hydrological parameters derived from a suite of Indian geostationary satellites. The study used time-series data for a period of five years (2009-2013) to develop three indicators applicable for early, mid newlineand late-season drought characterization. Finally, a seasonal agricultural drought newlineassessment (SADA) approach has been developed from the combination of all the newlinethree drought indicators based on weighted ranges of four drought severity classes newlinedefined for all the three classes of indicators. An early warning indicator (EWI) newlinehas been developed from satellite-based reference evapotranspiration (ET0) and rainfall newlinefor early-season drought characterization corresponding to early vegetative stage newlinecrops during June to July. A water scalar (Wscalar) has been developed from shortwave newlineinfrared (SWIR) and near infrared (NIR) band combinations, to characterize newlinemid-season agricultural drought corresponding to peak vegetative stage corresponding newlineto August September. A Combined Deficit Index (CDI) has been developed newlinefrom deficit of tri-monthly sum antecedent rainfall and deficit in monthly vegetation newlinevigor in terms normalized difference vegetation Inde

Mots clés : agriculture drought geostationary monsoon rainfall science

Présentation et version intégrale (Shodhganga)

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