## 3 Results and Discussion
### Importance of Input Variables and Processing Methods on WUE Estimates
#### 3.3.1 Impact of Crop Physiology at Different Timescales on Water Use Efficiency Estimate  
While input variable selection is responsible for differences between WUE estimation methods, it is crop physiological components that drive the inconsistencies between these calculations. Sometimes we need to look at shorter timescales, but the WUE observed at different time steps and the discrepancies between the methods are going to differ due to physiology and farming practices, which influence crop physiology. Moreover, the timescales at which WUE is quantified can result in inconsistencies between methods, and, these inconsistencies can differ from what is observed at the seasonal or growing season timescale. For example, growing season EWUES was greater in alfalfa whereas median half-hourly EWUES was greater in maize (Table 2). Since alfalfa is a perennial plant in its third year, it began growing immediately following snowmelt, which promoted a longer growing season (22 days longer than maize). This resulted in greater seasonal  
Figure 3: Half-hourly ETS versus ETF (**a,b**), GPPS versus GPPF (**c,d**), NEES versus NEEF (**e,f**), and EWUES versus EWUEF for alfalfa (green; (**a,c,e,g**)) and maize (yellow; (**b,d,f,h**)) over the 2018 growing season. Line of best fit and 1:1 line were included where R\({}^{2}\) = 0.75 (**a**), n = 2104), R\({}^{2}\) = 0.74 (**(b)**, n = 1304), R\({}^{2}\) = 0.28 (**(c)**, n = 2056), R\({}^{2}\) = 0.50 (**(d)**, n = 1314), R\({}^{2}\) = 0.75 (**(e)**, n = 2065), and R\({}^{2}\) = 0.69 (**(f)**, n = 1315). Only half-hour intervals where a value for both flux components or EWUE values existed prior to gap-filling were used. aETS = Evapotranspiration from EddyPro processing; bETF = Evapotranspiration from Fluxpart processing; cGPPS = Gross primary productivity from EddyPro/REddyPro processing; dGPPF = Gross primary productivity from Fluxpart processing; eNEES = Net ecosystem exchange from EddyPro processing; fNEF = Net ecosystem exchange from Fluxpart processing; gEWUES = Ecosystem water use efficiency from EddyPro/REddyPro processing (mg C g\({}^{-1}\) H\({}_{2}\)O); hEWUEF = Ecosystem water use efficiency from Fluxpart processing (mg C g\({}^{-1}\) H\({}_{2}\)O). EWUE estimates since growing crops under cooler conditions can improve WUE due to lower evaporative demand [81; 82]. Maize, on the other hand, took a while to establish after planting. However, the maize crops did experience higher median EWUES, which is likely attributed to C4 plants containing greater WUE at higher temperatures [65; 83]. At lower temperatures, the energy costs of trapping the carbon internally are greater than the photorespiratory costs and therefore the C4 pathway is less efficient [84]. Over the course of the growing season, this C4 pathway advantage did not overcome that of alfalfa due to its earlier start in cooler conditions, but it did result in greater median half-hourly EWUES. Where measurements are taken in the growing season is also relevant due to physiological mechanisms in the crops considered. This is a result of physiological changes at different growing stages in crops, which is especially apparent for single harvest crops such as maize. Alfalfa, however, did not experience drastic growth stage changes since it is a perennial crop and multiple harvests interrupted the lifecycle. As such, this study divided alfalfa into different cuts which contained relatively steady growth rates (Figure 4a; 1.5-1.6 cm day\({}^{-1}\) average per cut) while maize was divided by growth stages which exhibited drastically different growth rates (Figure 4a). These growth rates were 1.9 cm day\({}^{-1}\), 5.7 cm day\({}^{-1}\), and 4.0 cm day\({}^{-1}\) for GS1-3, respectively. Growth stage 4 did not experience height growth since it was directing growth into reproductive organs and experiences senescence (see LAI; Figure 4b). This complicates direct comparison of HWUE methods for sub-periods in the growing season, whereas EWUE is based on meteorological measurements and can therefore be more easily compared.