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Yi Li, Robert Horton, Tusheng Ren, and Chunyan Chen

1. Introduction Crop water requirements (CWR) are important parameters in the design of irrigation systems, irrigation scheduling, water resources management, and water cycle research (e.g., Donatelli et al. 2006 ; Maule et al. 2006 ; Xu et al. 2006a , b ). Direct measures of CWR are difficult because of equipment and funding limitations. CWR can be obtained from estimates of evapotranspiration (ET). The quantity ET is often estimated from measurements of free water evaporation or from

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Pat J-F. Yeh and J. S. Famiglietti

1. Introduction In shallow water table areas, summer drying of root-zone soil moisture often results in an upward capillary flux from the underlying aquifer to sustain the strong evapotranspiration demand; this is referred to as groundwater evapotranspiration (hereafter groundwater evaporation). In wetland and playa areas, or in semiarid riparian environments, groundwater evaporation represents the major source of water for plants, particularly during drought periods ( Schmidhalter et al. 1994

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Christian Seiler and Arnold F. Moene

1. Introduction Actual evapotranspiration ET act can be estimated in different ways. Among them are (i) in situ measurements using lysimeters or flux towers, (ii) the crop coefficient approach by Allen et al. ( Allen et al. 1998 ), and (iii) remote sensing algorithms. Kalma et al. ( Kalma et al. 2008 ) divide the latter into two main classes: empirical/statistical approaches and energy balance approaches. The first correlates ET act either to air–surface temperature differences (e

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Natalia Hasler and Roni Avissar

1. Introduction While the Amazonian forest has been widely recognized as a major component of the regional and global hydroclimate system, spatial and temporal variability of its hydrologic functions are not fully understood ( Avissar et al. 2002 ). Amazonia hosts the largest block of tropical rain forest, considered as the prime contributor to land surface evapotranspiration (ET) ( Choudhury et al. 1998 ). Besides the significant influence on the global hydrological cycle, these sizable water

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Dev Niyogi, Sajad Jamshidi, David Smith, and Olivia Kellner

Network (GHCN), and the citizen science Community Collaborative Rain, Hail and Snow Network (CoCoRaHS) program, have been implemented for precipitation monitoring. However, evapotranspiration (ET) data, an important component of the state’s water balance, are not as readily available as precipitation data. To accurately evaluate the regional water resources and seasonal hydrological cycle, information about ET data is necessary. This lack of ET data is not unique to Indiana and is indeed more broadly

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Ayman Suleiman, Jawad Al-Bakri, Mohammad Duqqah, and Rich Crago

1. Introduction Estimates of evapotranspiration (ET) are needed for many applications in diverse disciplines, such as agriculture and hydrology. Many studies of long-term averages have shown that more than half of the net solar energy, and subsequently two thirds of precipitation, goes to ET ( Brutsaert 1982 ). ET is linked to the land surface energy budget as follows (e.g., Brutsaert 1982 ): where R n (W m −2 ) is the net incoming radiation, G is the heat flux into the ground (W m −2

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Sajad Jamshidi, Shahrokh Zand-parsa, Mojtaba Pakparvar, and Dev Niyogi

reliable estimate of the regional evapotranspiration (ET) that can be used in terms of designing decision tools at local and regional scales. ET estimates are important to improve decision-making tools, detect crop stress, refine irrigation scheduling, and manage of water resources at the watershed scale ( Gibson et al. 2013 ; Kongo and Jewitt 2006 ; Kamali and Zand-Parsa 2017 ). For ET estimation, a number of approaches are available. These include direct measurements like lysimeters and eddy

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M. A. Rawlins, S. Frolking, R. B. Lammers, and C. J. Vörösmarty

problem in the Arctic where gauge undercatch is often substantial. Precipitation underestimates of 20% to 25% have been determined across North America ( Karl et al. 1993 ), while biases of 80% to 120% (in winter) have been estimated for the terrestrial Arctic north of 45°N ( Yang et al. 2005 ). In regions where precipitation exceeded potential evapotranspiration (PET), uncertainty in precipitation translated to an uncertainty in simulated runoff of roughly similar magnitude ( Fekete et al. 2004 ). To

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Andrew Tait and Ross Woods

1. Introduction Knowledge of potential evapotranspiration (PET) is crucial for water balance studies. A water balance is simply the balance between precipitation coming into a system (such as a soil profile) and water leaving the system through evapotranspiration (ET), drainage, or runoff. Computations of the water balance are included in estimates of irrigation demand, pasture production, groundwater recharge, and streamflows, for example. Thus, there is a significant scientific and economic

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Ryan R. Spies, Kristie J. Franz, Terri S. Hogue, and Angela L. Bowman

, such as the application of gridded model inputs ( Koren et al. 2004 ; NWS 2011 ). The HL-RDHM is grid based and employs a conceptual rainfall–runoff model to perform the water balance functions for each grid, including meeting potential evapotranspiration (PET) demands ( NWS 2011 ). The PET data implemented in the HL-RDHM are based on climatological potential evaporation (PE) values estimated from the seasonal and annual free water surface maps and mean monthly station data from National Oceanic

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