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Impact of flooded rice paddy on remotely sensed evapotranspiration in the Krishna River basin, India
Author(s) -
Teluguntla Pardhasaradhi,
Ryu Dongryeol,
George Biju,
Walker Jeffrey P.
Publication year - 2020
Publication title -
hydrological processes
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.222
H-Index - 161
eISSN - 1099-1085
pISSN - 0885-6087
DOI - 10.1002/hyp.13748
Subject(s) - evapotranspiration , environmental science , hydrology (agriculture) , hydrometeorology , transpiration , structural basin , paddy field , drainage basin , water balance , arid , vegetation (pathology) , potential evaporation , precipitation , geology , meteorology , geography , ecology , medicine , paleontology , photosynthesis , botany , geotechnical engineering , cartography , archaeology , pathology , biology
Evapotranspiration (ET) is one of the major water exchange processes between the earth's surface and the atmosphere. ET is a combined process of evaporation from open water bodies, bare soil and plant surfaces, and transpiration from vegetation. Remote sensing‐based ET models have been developed to estimate spatially distributed ET over large regions, however, many of them reportedly underestimate ET over semi‐arid regions (Jamshidi et al., Journal of Hydrometeorology, 2019, 20, 947–964). In this work, we show that underestimation of ET can occur due to the open water evaporation from flooded rice paddies ignored in the existing ET models. To address the gap in ET estimation, we have developed a novel approach that accounts for the missing ET component over flooded rice paddies. Our method improved ET estimates by a modified Penman‐Monteith algorithm that considered the fraction of open water evaporation from flooded rice paddies. Daily ET was calculated using ground based meteorological data and the MODIS satellite data over the Krishna River Basin. Seasonal and annual ET values over the Krishna Basin were compared with two different ET algorithms. ET estimates from these two models were also compared for different crop combinations. Results were validated with flux tower‐based measurements from other studies. We have identified a 17 mm/year difference in average annual ET over the Krishna River Basin with this new ET algorithm. This is very critical in basin scale water balance analysis and water productivity studies.