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• Observed crop water use efficiency(WUE) in Canadian prairies with eddy covariance. • WUE varies between crop type, soil, and weather and should not be considered static. • Eddy covariance reported lower and less variable WUE than water balance approaches. • Environmental factors that increase evaporative demand decrease WUE. Crop–water interactions define productivity in water-limited dryland agricultural production systems in cold regions. Despite the agronomic and economic importance of this relationship there are challenges in quantifying crop water use efficiency (WUE). To understand dynamics driving crop water use and agricultural productivity in these environments, observations of evapotranspiration, carbon assimilation, meteorology, and crop growth were collected over 17 site-years at 5 agricultural sites in the sub-humid continental Canadian Prairies. Eddy-covariance (EC) derived water and carbon fluxes provided a means to comprehensively assess the WUE of current agricultural practices by both physiological (WUE P : g C kg−1 H 2 O) and agronomic (WUE Y): kg yield mm H 2 O−1 hectare−1) approaches. Mean field scale WUE Y for grain yields were 10.4 (Barley), 10.2 (Wheat), 6.0 (Canola), 19.3 (Peas), 12.2 (Lentils) and for silage/forage crops were 23.0 (Barley), 11.9 (Forage), and 20.7 (Corn) (kg yield mm H 2 O−1 hectare−1). An assessment of environmental factors and their covariance with WUE , utilising a conditional inference tree approach, demonstrated that WUE decreased when crops were under greater evapotranspiration demands. EC-based areal WUE approaches, measuring fluxes over footprints of hundreds of square metres, were compared with more commonly reported point-scale water balance residual approaches (WUE WB) and demonstrated consistently smaller magnitudes. WUE WB was greater than EC-estimated WUE Y by an average of 52% and 65% for grain and forage/silage crops respectively. WUE WB also had greater variability than EC estimates, with standard deviations 188% and 128% greater than Barley and Wheat crops, respectively. This comparison highlights the scale dependency of WUE estimation methods, demonstrates considerable uncertainty in point scale water balance approaches due to spatial variability in crop–water interactions, and shows how this variability can be accounted for by EC observations. This improves the understanding of WUE and quantifies its variability in cold continental water-limited climates and provides a means to diagnose improved agricultural water management. [ABSTRACT FROM AUTHOR]

On the Canadian Prairies, agricultural practices result in millions of hectares of standing crop stubble that gradually emerges during snowmelt. The importance of stubble in trapping wind-blown snow and retaining winter snowfall has been well demonstrated. However, stubble is not explicitly accounted for in hydrological or energy balance snowmelt models. This paper relates measurable stubble parameters (height, width, areal density, and albedo) to the snowpack energy balance and snowmelt with the new, physically based Stubble–Snow–Atmosphere Model (SSAM). Novel process representations of SSAM quantify the attenuation of shortwave radiation by exposed stubble, the sky and vegetation view factors needed to solve longwave radiation terms, and a resistance scheme for stubble–snow–atmosphere fluxes to solve for surface temperatures and turbulent fluxes. SSAM results were compared to observations of radiometric snow-surface temperature, stubble temperature, snow-surface solar irradiance, areal-average turbulent fluxes, and snow water equivalent from two intensive field campaigns during snowmelt in 2015 and 2016 over wheat and canola stubble in Saskatchewan, Canada. Uncalibrated SSAM simulations compared well with these observations, providing confidence in the model structure and parameterization. A sensitivity analysis conducted using SSAM revealed compensatory relationships in energy balance terms that result in a small increase in net snowpack energy as stubble exposure increases. [ABSTRACT FROM AUTHOR]

Improving the calculation of land‐atmosphere fluxes of heat and water vapor in mountain terrain requires better resolution of thermally driven diurnal winds (i.e., valley, slope winds) due to differential heating by terrain and radiative fluxes. In this study, the Weather Research and Forecasting model is used to simulate flow in large‐eddy simulation (LES) mode over the complex terrain of the Fortress Mountain and Marmot Creek research basins, Kananaskis Valley, Canadian Rockies, Alberta in mid‐summer. The model was used to examine the temporal and spatial evolution of local winds and near‐surface boundary layer processes with variability in topography and elevation. Numerically resolving complex terrain wind flow effects require smaller grid cell size. However, the use of terrain‐following coordinates in most numerical weather prediction models results in large numerical errors when flow over steep terrain is simulated. These errors propagate through the domain and can result in numerical instability. To avoid this issue when simulating flow over steep terrain a local smoothing approach was used, where smoothing is applied only where slope exceeds some predetermined threshold. LES results from local smoothing were compared with a mesoscale model and LES with global smoothing. Simulations are evaluated using sounding data and meteorological stations. The differences in flow patterns and reversals in two mountain basins suggest that valley geometry and volume is relevant to the break up of inversion layers, removal of cold‐air pools, and strength of thermally driven winds. Key Points: Large‐eddy simulations in complex terrain utilizing smoothing techniques resolve thermally driven mountain flowsMesoscale flow interactions with mountainous terrain can influence valley windsTopographical differences in mountain basins affects local flows and cold‐air pooling [ABSTRACT FROM AUTHOR]

Vegetation has a tremendous influence on snow processes and snowpack dynamics, yet remote sensing techniques to resolve the spatial variability of sub-canopy snow depth are not always available and are difficult from space-based platforms. Unmanned aerial vehicles (UAVs) have had recent widespread application to capture high-resolution information on snow processes and are herein applied to the sub-canopy snow depth challenge. Previous demonstrations of snow depth mapping with UAV structure from motion (SfM) and airborne lidar have focussed on non-vegetated surfaces or reported large errors in the presence of vegetation. In contrast, UAV-lidar systems have high-density point clouds and measure returns from a wide range of scan angles, increasing the likelihood of successfully sensing the sub-canopy snow depth. The effectiveness of UAV lidar and UAV SfM in mapping snow depth in both open and forested terrain was tested in a 2019 field campaign at the Canadian Rockies Hydrological Observatory, Alberta, and at Canadian prairie sites near Saskatoon, Saskatchewan, Canada. Only UAV lidar could successfully measure the sub-canopy snow surface with reliable sub-canopy point coverage and consistent error metrics (root mean square error (RMSE) <0.17 m and bias -0.03 to -0.13 m). Relative to UAV lidar, UAV SfM did not consistently sense the sub-canopy snow surface, the interpolation needed to account for point cloud gaps introduced interpolation artefacts, and error metrics demonstrated relatively large variability (RMSE<0.33 m and bias 0.08 to -0.14 m). With the demonstration of sub-canopy snow depth mapping capabilities, a number of early applications are presented to showcase the ability of UAV lidar to effectively quantify the many multiscale snow processes defining snowpack dynamics in mountain and prairie environments. [ABSTRACT FROM AUTHOR]

Forest clearings are common features of evergreen forests and produce snowpack accumulation and melt differing from that in adjacent forests and open terrain. This study has investigated the challenges in specifying the turbulent fluxes of sensible and latent heat to snowpacks in forest clearings. The snowpack in two forest clearings in the Canadian Rockies was simulated using a one-dimensional (1D) snowpack model. A trade-off was found between optimizing against measured snow surface temperature or snowmelt when choosing how to specify the turbulent fluxes. Schemes using the Monin–Obukhov similarity theory tended to produce negatively biased surface temperature, while schemes that enhanced turbulent fluxes, to reduce the surface temperature bias, resulted in too much melt. Uncertainty estimates from Monte Carlo experiments showed that no realistic parameter set could successfully remove biases in both surface temperature and melt. A simple scheme that excludes atmospheric stability correction was required to successfully simulate surface temperature under low wind speed conditions. Nonturbulent advective fluxes and/or nonlocal sources of turbulence are thought to account for the maintenance of heat exchange in low-wind conditions. The simulation of snowmelt was improved by allowing enhanced latent heat fluxes during low-wind conditions. Caution is warranted when snowpack models are optimized on surface temperature, as model tuning may compensate for deficiencies in conceptual and numerical models of radiative, conductive, and turbulent heat exchange at the snow surface and within the snowpack. Such model tuning could have large impacts on the melt rate and timing of the snow-free transition in simulations of forest clearings within hydrological and meteorological models. [ABSTRACT FROM AUTHOR]

Greenhouse tomato cropping with under-mulch drip irrigation is common in arid and semi-arid Northwest China. To investigate the influence of drip-line layout and irrigation amount on yield, fruit quality, irrigation water use efficiency, and comprehensive benefit of tomato production, the experiment was conducted during two cropping seasons of spring to summer in 2015 and winter in 2015 to spring in 2016. In these two cropping seasons, two drip-line layout types were conducted, including a one drip-line for each plant-row and a one drip-line for two plant-rows, with four levels of irrigation amount, i.e., 0.6, 0.8, 1.0, and 1.2 times of accumulated evaporation of a 20 cm standard pan. The results showed that one drip-line for two plant-rows outperformed one drip-line for each plant-row in achieving higher yield and irrigation water use efficiency with the same irrigation amount. In these two drip-line layouts, tomato yield increased at first and then decreased with the increase of irrigation amount; while irrigation water use efficiency decreased all the way with the increase of irrigation amount. A principal component analysis demonstrated that the combination of one drip-line for each plant-row and 1.0 times of pan evaporation obtained the highest comprehensive fruit nutritional quality among all combinations of drip-line layout and irrigation amount in spring-summer season; while the combination of one drip-line for two plant-rows and 0.8 times of pan evaporation had the highest comprehensive fruit quality in winter-spring season. To purse high comprehensive benefits, combinations of one drip-line for two plant-rows and 0.8 times of pan evaporation, and one drip-line for each plant-row and 0.6 times of pan evaporation should be recommended for spring-summer and winter spring cropping seasons, respectively. The findings of this study can provide irrigation guidance for greenhouse tomato growing in Northwest China. • One drip-line for two plant-rows was a better layout practice achieving higher yield and irrigation water use efficiency. • Irrigation with 1.0 and 0.8 times pan evaporation can obtain high fruit quality in spring-summer and winter-spring seasons. • High comprehensive benefit can be achieved through irrigation treatments and can be used to guide tomato production. [ABSTRACT FROM AUTHOR]

Recent evidence suggests that the relationships between climate and boreal tree growth are generally non‐stationary; however, it remains uncertain whether the relationships between climate and carbon (C) fluxes of boreal forests are stationary or have changed over recent decades. In this study, we used continuous eddy‐covariance and microclimate data over 21 years (1996–2016) from a 100‐year‐old trembling aspen stand in central Saskatchewan, Canada to assess the relationships between climate and ecosystem C and water fluxes. Over the study period, the most striking climatic event was a severe, 3‐year drought (2001–2003). Gross ecosystem production (GEP) showed larger interannual variability than ecosystem respiration (Re) over 1996–2016, but Re was the dominant component contributing to the interannual variation in net ecosystem production (NEP) during post‐drought years. The interannual variations in evapotranspiration (ET) and C fluxes were primarily driven by temperature and secondarily by water availability. Two‐factor linear models combining precipitation and temperature performed well in explaining the interannual variation in C and water fluxes (R2 >.5). The temperature sensitivities of all three C fluxes (NEP, GEP and Re) declined over the study period (p <.05), and, as a result, the phenological controls on annual NEP weakened. The decreasing temperature sensitivity of the C fluxes may reflect changes in forest structure, related to the over‐maturity of the aspen stand at 100 years of age, and exacerbated by high tree mortality following the severe 2001–2003 drought. These results may provide an early warning signal of driver shift or even an abrupt status shift of aspen forest dynamics. They may also imply a universal weakening in the relationship between temperature and GEP as forests become over‐mature, associated with the structural and compositional changes that accompany forest ageing. [ABSTRACT FROM AUTHOR]

Long‐term trends in ecosystem resource use efficiencies (RUEs) and their controlling factors are key pieces of information for understanding how an ecosystem responds to climate change. We used continuous eddy covariance and microclimate data over the period 1999–2017 from a 120‐year‐old black spruce stand in central Saskatchewan, Canada, to assess interannual variability, long‐term trends, and key controlling factors of gross ecosystem production (GEP) and the RUEs of carbon (CUE = net primary production [NPP]/GEP), light (LUE = GEP/absorbed photosynthetic radiation [APAR]), and water (WUE = GEP/evapotranspiration [E]). At this site, annual GEP has shown an increasing trend over the 19 years (p < 0.01), which may be attributed to rising atmospheric CO2 concentration. Interannual variability in GEP, aside from its increasing trend, was most strongly related to spring temperatures. Associated with the significant increase in annual GEP were relatively small changes in NPP, APAR, and E, so that annual CUE showed a decreasing trend and annual LUE and WUE showed increasing trends over the 19 years. The long‐term trends in the RUEs were related to the increasing CO2 concentration. Further analysis of detrended RUEs showed that their interannual variation was impacted most strongly by air temperature. Two‐factor linear models combining CO2 concentration and air temperature performed well (R2~0.60) in simulating annual RUEs. LUE and WUE were positively correlated both annually and seasonally, while LUE and CUE were mostly negatively correlated. Our results showed divergent long‐term trends among CUE, LUE, and WUE and highlighted the need to account for the combined effects of climatic controls and the 'CO2 fertilization effect' on long‐term variations in RUEs. Since most RUE‐based models rely primarily on one resource limitation, the observed patterns of relative change among the three RUEs may have important implications for RUE‐based modeling of C fluxes. [ABSTRACT FROM AUTHOR]

Insect outbreaks can significantly influence carbon (C) and water balances of forests. Forest tent caterpillars (FTC) ( Malacosoma disstria Hübner) are one of the most prominent insects found in aspen forests in Canada and have the potential to considerably influence regional C and water fluxes. In the summer of 2016, an FTC infestation occurred in a ca. 100 -year-old trembling aspen ( Populus tremuloides ) stand in the southern boreal forest where the longterm research site known as Old Aspen (OA) is located. The infestation led to nearly complete defoliation of the canopy during the leafing out period when photosynthesis, and thus C uptake, is progressing towards maximum levels. We used 21 years of eddy-covariance (EC) and climate measurements covering pre-infestation and infestation periods to estimate the impact of the FTC infestation on net ecosystem production (NEP), gross ecosystem production (GEP) and evapotranspiration (E). Defoliation in 2016 reduced annual NEP to −130 g C m −2  y −1 and GEP to 798 g C m −2  y −1 , respectively, which were much less than their 20-year means (NEP = 118 ± 53 g C m −2  y −1 , GEP = 1057 ± 74 g C m −2  y −1 ), and resulted in the most negative annual NEP value of the 21 years of measurements at the OA site. NEP for 2016 was even lower than values observed during three drought years (2001–2003). However, FTC infestation caused little effect on annual E. FTC infestation reduced the near-surface remotely-measured greenness index, green chromatic coordinate (GCC), to ∼0.32 on June 10 in comparison to ∼0.40 in other years. The defoliation, observable from space as reductions in normalized difference vegetation index (NDVI) values, also showed a negligible effect on E but a large effect on the C fluxes. [ABSTRACT FROM AUTHOR]

Over Saint-Sorlin Glacier in the French Alps (45° N, 6.1° E; ~3 km²) in summer, we study the atmospheric surface-layer dynamics, turbulent fluxes, their uncertainties and their impact on surface energy balance (SEB) melt estimates. Results are classified with regard to largescale forcing. We use high-frequency eddy-covariance data and mean air-temperature and wind-speed vertical profiles, collected in 2006 and 2009 in the glacier's atmospheric surface layer. We evaluate the turbulent fluxes with the eddycovariance (sonic) and the profile method, and random errors and parametric uncertainties are evaluated by including different stability corrections and assuming different values for surface roughness lengths. For weak synoptic forcing, local thermal effects dominate the wind circulation. On the glacier, weak katabatic flows with a wind-speed maximum at low height (2-3 m) are detected 71% of the time and are generally associated with small turbulent kinetic energy (TKE) and small net turbulent fluxes. Radiative fluxes dominate the SEB. When the large-scale forcing is strong, the wind in the valley aligns with the glacier flow, intense downslope flows are observed, no wind-speed maximum is visible below 5 m, and TKE and net turbulent fluxes are often intense. The net turbulent fluxes contribute significantly to the SEB. The surface-layer turbulence production is probably not at equilibrium with dissipation because of interactions of largescale orographic disturbances with the flow when the forcing is strong or low-frequency oscillations of the katabatic flow when the forcing is weak. In weak forcing when TKE is low, all turbulent fluxes calculation methods provide similar fluxes. In strong forcing when TKE is large, the choice of roughness lengths impacts strongly the net turbulent fluxes from the profile method fluxes and their uncertainties. However, the uncertainty on the total SEB remains too high with regard to the net observed melt to be able to recommend one turbulent flux calculation method over another. [ABSTRACT FROM AUTHOR]