4.5 Article

Estimation of annual regional drought index considering the joint effects of climate and water budget for Krishna River basin, India

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出版社

SPRINGER
DOI: 10.1007/s10661-020-08379-y

关键词

Budyko equation; Turc model; Remote sensing; Thornthwaite model; SPEI; SPAEI

资金

  1. Science and Engineering Research Board (SERB), Department of Science and Technology, Government of India, through Start-up Grant for Young Scientists (YSS) Project [YSS/2015/002111]

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The Standardized Precipitation and Evapotranspiration Index (SPEI) became one of the popular drought indices due to the consideration of difference between precipitation (P) and potential evapotranspiration (PET), which represents the energy-based climatic water balance. Implementation of actual evapotranspiration (AET), which accounts for both water and energy-based climatic evaporative demand in drought characterization studies, is limited. This study proposes a meteorological drought index with the structure of theSPEIand actual evapotranspiration modeled with empirical formulations and remote sensing data integrated with surface energy models at annual scale. The proposed drought index imposes the effect of precipitation,PET, andAETusing operational meteorological data sets of precipitation and temperatures. The present study aimed to test how a drought index based onPETandPcan outperform with the inclusion ofAETat a river basin scale at 12-month scale. The proposed hypothesis was tested considering Krishna River basin, India, as a case study for which most of the basin is in arid climate. The performance of drought indices was compared using historical droughts in terms of severity, areal extent, frequency, and duration based on empiricalAETmodels along with satellite-based land surfaceETdata-based drought indices. The proposedAET-based drought indices have effectively captured the historical drought years over the Krishna River basin. The empiricalAETformulation-based drought index was identified as a more reliable measure in the estimation of drought characteristics by comparing with satellite-based land surfaceAET-based drought index. TheAET-based drought indices were able to drive the areas into moderate, which or otherwise categorized under severe drought regions withPET-based drought indices. Inclusion ofAETin the drought characterization along with precipitation andPETcan drive the highly intensified drought events determined bySPEIinto moderate and less frequent droughts with short durations over a large river basin with arid climate.

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