Development of real-time reference evapotranspiration at the regional scale using satellite-based observations. Issue 24 (16th December 2016)

• Record Type: Journal Article
• Authors: Vyas, Swapnil S.; Nigam, Rahul; Bhattacharya, Bimal K.; Kumar, Prashant
• Is Part Of: International journal of remote sensing. Volume 37:Issue 24(2016)
• Page Start: 6108
• Page End: 6126
• Publication Date: 2016-12-16
• Subjects: Remote sensing -- Periodicals; Télédétection -- Périodiques; 621.3678
• DOI: 10.1080/01431161.2016.1253895
• Languages: English
• ISSNs: 0143-1161

Abstract

ABSTRACT: Real-time data of reference evapotranspiration (ET0 ) at different space-time scales are essential to regional agricultural drought assessment, water accounting at the watershed to basin scale, and provide irrigation advisory to farmers. Here, we present a data-fusion approach that integrates satellite-based insolation product (8 km) from an Indian geostationary satellite (Kalpana-1) sensor (VHRR; Very High Resolution Radiometer) and high-resolution (~ 5 km) short-range weather forecast into an FAO56 model based on the classical Penman–Monteith (P-M) formulation. Five year (2009–2013) mean monthly estimates from the daily ET0 product over the Indian landmass were found to vary between 10 and 350 mm. It increased from January to May (70–350 mm), followed by a decrease to reach the lowest in November (10–140 mm), thus typically showing unimodal distribution. The comparison of daily space-based and station-based estimates (at six ground stations) produced a root mean square deviation (RMSD) ranging from 21% to 38% for 977 paired data sets with the correlation coefficient ( r ) varying from 0.32 to 0.82. The error was reduced from 25% to 10% with an increase in ' r ' from 0.43 to 0.98 for daily to 10 day summation period. Spatial grid-to-grid comparison of monthly ET0 estimates with Global Data Assimilation System (GDAS) potential evapotranspiration (PET) showed RMSD within a range of 1.4–18.4% for most of the months, except for two. Further ET0 analysis over normal and drought years showed that it could be used for comprehensive drought assessment with other existing indicators.