Results 141 to 150 of about 3,180 (206)

High-resolution spatially interpolated FAO Penman-Monteith crop reference evapotranspiration maps of Sicily Island (Italy) and Jucar River system (Spain) using AgERA5 and ERA5-Land reanalysis datasets.

J Hydrol Reg Stud
Garcia-Prats A, Carricondo-Antón JM, Ippolito M, De Caro D, Jiménez-Bello MA, Manzano-Juárez J, Pulido-Velazquez M.   +6 more
europepmc   +1 more source

Large Variations in the Transpiration of Sorghum Canopies Under High Evaporative Demand Are Positively Related to Water Use Efficiency. [PDF]

Plant Cell Environ
Pilloni R, Aparna K, El Ghazzal Z, Kar S, Hajjarpoor A, Xue W, Affortit P, Ribière W, Badji R, Sine B, Kholova J, Tardieu F, Vadez V.   +12 more
europepmc   +1 more source

Regionalization of the calculation of reference evapotranspiration (ETo) at monthly and annual scales for the department of Cundinamarca, based on evaporation data from the Class A tank related to ETo values obtained by the FAO Penman-Monteith method

Se han desarrollado bastantes métodos para el cálculo de la evapotranspiración, entre ellos el propuesto por la FAO Penman-Monteith. Para Colombia, el IDEAM (2018) concluyó que el método de la FAO Penman-Monteith es el más apropiado para calcular la ...
Castillo Molano, Ivan Dario
core  

Comparative assessment of empirical and hybrid machine learning models for estimating daily reference evapotranspiration in sub-humid and semi-arid climates. [PDF]

Sci Rep
Acharki S, Raza A, Vishwakarma DK, Amharref M, Bernoussi AS, Singh SK, Al-Ansari N, Dewidar AZ, Al-Othman AA, Mattar MA.   +9 more
europepmc   +1 more source

Global spatially detailed water footprint of crop production over five decades. [PDF]

Sci Rep
Demeke BW, Mekonnen MM, Brauman KA, Magliocca N, Moradkhani H.   +4 more
europepmc   +1 more source

A 0.1° monthly potential evapotranspiration dataset based on the optimal models over global vegetation zones. [PDF]

Sci Data
Bi Z, Sun S, Ma Q, Liu Y, Li X, Li J, Liu Y, Zhou Y, Zhou B, Chen H.   +9 more
europepmc   +1 more source

Warming accelerates global drought severity. [PDF]

Nature
Gebrechorkos SH, Sheffield J, Vicente-Serrano SM, Funk C, Miralles DG, Peng J, Dyer E, Talib J, Beck HE, Singer MB, Dadson SJ.   +10 more
europepmc   +1 more source

Physically-constrained evapotranspiration models with machine learning parameterization outperform pure machine learning: Critical role of domain knowledge. [PDF]

PLoS One
Kim Y, Garcia M, Andrew Black T, Johnson MS.   +3 more
europepmc   +1 more source

Comparison of the performances of six empirical mass transfer-based reference evapotranspiration estimation models in semi-arid conditions. [PDF]

PeerJ
Usta S.
europepmc   +1 more source

CMIP6-based global estimates of future aridity index and potential evapotranspiration for 2021-2060. [PDF]

Open Res Eur
Zomer RJ, Xu J, Spano D, Trabucco A.
europepmc   +1 more source