Stubble management effects on canola performance across different climatic regions of western Canada

2015 ◽  
Vol 95 (1) ◽  
pp. 149-159 ◽  
Author(s):  
Michael J. Cardillo ◽  
Paul Bullock ◽  
Rob Gulden ◽  
Aaron Glenn ◽  
Herb Cutforth
Keyword(s):  
Snow Water Equivalent ◽  
Growing Season ◽  
Moisture Stress ◽  
Climatic Conditions ◽  
Western Canada ◽  
Spring Precipitation ◽  
Canadian Prairies ◽  
Climatic Regions ◽  
Snow Water ◽  
Management Effects

Cardillo, M. J., Bullock, P., Gulden, R., Glenn, A. and Cutforth, H. 2015. Stubble management effects on canola performance across different climatic regions of western Canada. Can. J. Plant Sci. 95: 149–159. Previous research in the most arid region of the Canadian prairies has shown that wheat stubble cut tall the previous year can improve performance of the following canola crop. This study aimed to determine if tall stubble could benefit canola across the climatic conditions typically experienced in western Canada. Tall stubble impacts on canola were monitored over 11 site-years located throughout the prairies. At each site, tall stubble (50 cm) was compared with short stubble (20 cm). At some sites the stubble lodged allowing an unintended comparison between stubble that remained intact and stubble that was flattened. The comparison of snow water equivalent showed tall stubble caught more snow than short stubble but the benefit of additional spring soil moisture was masked by heavy spring precipitation in both 2011 and 2012. Canola biomass and yield were significantly lower in damaged versus intact stubble, either short or tall. In both years, wet spring conditions were followed by hotter and drier weather in the mid to late growing season. Soil under the damaged stubble (short or tall) likely warmed and dried more slowly in the spring, limiting early-season growth, biomass and yield. At sites where both tall and short stubble remained intact, there was a significant yield advantage with tall stubble. The intact tall stubble may have slowed evaporation and soil drying compared with intact short stubble, which reduced moisture stress later in the growing season, imparting a yield advantage.

scholarly journals Forest Phenology Shifts in Response to Climate Change over China–Mongolia–Russia International Economic Corridor

Forests ◽  
2020 ◽  
Vol 11 (7) ◽  
pp. 757
Author(s):  
Lingxue Yu ◽  
Zhuoran Yan ◽  
Shuwen Zhang
Keyword(s):  
Climate Change ◽  
International Economic ◽  
Forest Ecosystem ◽  
Vegetation Index ◽  
Snow Water Equivalent ◽  
Global Climate ◽  
Growing Season ◽  
Observation Data ◽  
Single Temperature ◽  
Snow Water

Vegetation phenology is a sensitive indicator of climate change. With the intensification of global warming, the changes in growing seasons of various vegetation types have been widely documented across the world. However, as one of the most vulnerable regions in response to the global climate change, the phenological responses and associated mechanisms in mid–high latitude forests are still not fully understood. In this study, long-term changes in forest phenology and the associated relationship with the temperature and snow water equivalent in the China–Mongolia–Russia International Economic Corridor were examined by analyzing the satellite-measured normalized difference vegetation index and the meteorological observation data during 1982 to 2015. The average start date of the growing season (SOS) of the forest ecosystem in our study area advanced at a rate of 2.5 days/decade, while the end date of the growing season (EOS) was delayed at a rate of 2.3 days/decade, contributing to a growing season that was approximately 15 days longer in the 2010s compared to that in 1980s. A higher April temperature is beneficial to the advance in the SOS, and a higher summer temperature has the potential to extend the EOS in the forest ecosystem. However, our results also suggest that a single temperature cannot fully explain the advance of the SOS, as well as the delay in the EOS. The preseason Snow Water Equivalent (SWE) is also an essential factor in influencing the growing season. A higher SWE in February and March and lower SWE in April tend to advance the SOS, while higher SWE in pre-year December and lower SWE in current year October are beneficial to the extension of the EOS.

scholarly journals How does soil water availability control phytotoxic O<sub>3</sub> dose to montane pines? Modelling and experimental study from two contrasting climatic regions in Europe

2017 ◽  
Author(s):  
Svetlana Bičárová ◽  
Zuzana Sitková ◽  
Hana Pavlendová ◽  
Peter Fleischer Jr. ◽  
Peter Fleischer Sr. ◽  
...  
Keyword(s):  
Meteorological Data ◽  
Stomatal Closure ◽  
Growing Season ◽  
Climatic Conditions ◽  
Moisture Regime ◽  
Mediterranean Forests ◽  
Climatic Regions ◽  
Soil Moisture Regime ◽  
Swiss Stone Pine ◽  
The Mediterranean

Abstract. Montane forests are exposed to high ambient ozone (O3) concentrations that may adversely affect physiological processes in internal cells when O3 molecules enter the plants through the stomata. This study addresses the model results of Phytotoxic Ozone Dose metric (POD) based on estimation of stomatal O3 flux to dwarf mountain pine (Pinus mugo) and Swiss stone pine (Pinus cembra). We focused on two different bioclimatic regions: (1) the temperate mountain forests in the High Tatra Mts (SK–HT) of the Western Carpathians, and (2) the Mediterranean forests of the Alpes–Mercantour (FR–Alp) in the Alpes–Maritimes. Field measurement of O3 concentration and meteorological data incorporated into deposition model DO3SE showed lower O3 flux in FR–Alp than in SK–HT plots for the 2016 growing season. Model outputs showed that soil humidity play a key role in stomatal O3 uptake by montane pines at the alpine timberline. We found that temperate climatic conditions in SK–HT with sufficient precipitation did not limit stomatal conductivity and O3 uptake of P. mugo and P. cembra. On the other hand, the Mediterranean mountain climate characterised by warm and dry summer reduced stomatal conductance of pines in FR–Alp. POD without threshold limitation i.e. POD0 as a recently developed biologically sounded O3 metric varied near around and below critical level (CLef) depending upon different conditions of sunshine exposure in SK–HT plots. Field observation at these plots showed relatively weak visible O3 injury on P. cembra (2 % and 7 %) when compared with P. mugo (8 % and 18 %) for one year (C+1) and two year (C+2) old needles, respectively. Despite of low POD0 values, clearly below CLef, the highest level of visible O3 damage on average from 10 % (C+1) to 25 % (C+2) was observed on P. cembra needles in Mediterranean (FR–Alp) area. Further research is needed to clarify the effect of real soil moisture regime on stomatal closure in dry areas (FR–Alp) and resistance of pine species against visible O3 injury in wet subalpine zones (SK–HT). More attention should be paid to O3 fluxes covering a year-round growing season as well as intra-daily dynamics, especially the night hours, since these time spans appear to play significant role in O3 uptake by mountain conifers.

scholarly journals Snow water equivalents exclusively from snow depths and their temporal changes: the Δsnow model

2021 ◽  
Vol 25 (3) ◽  
pp. 1165-1187
Author(s):  
Michael Winkler ◽  
Harald Schellander ◽  
Stefanie Gruber
Keyword(s):  
Snow Depth ◽  
Snow Water Equivalent ◽  
Optimal Parameter ◽  
R Package ◽  
Model Parameters ◽  
Major Advance ◽  
Newtonian Viscosity ◽  
Climatic Regions ◽  
Depth Data ◽  
Snow Water

Abstract. Reliable historical manual measurements of snow depths are available for many years, sometimes decades, across the globe, and increasingly snow depth data are also available from automatic stations and remote sensing platforms. In contrast, records of snow water equivalent (SWE) are sparse, which is significant as SWE is commonly the most important snowpack feature for hydrology, climatology, agriculture, natural hazards, and other fields. Existing methods of modeling SWE either rely on detailed meteorological forcing being available or are not intended to simulate individual SWE values, such as seasonal “peak SWE”. Here we present a new semiempirical multilayer model, Δsnow, for simulating SWE and bulk snow density solely from a regular time series of snow depths. The model, which is freely available as an R package, treats snow compaction following the rules of Newtonian viscosity, considers errors in measured snow depth, and treats overburden loads due to new snow as additional unsteady compaction; if snow is melted, the water mass is stepwise distributed from top to bottom in the snowpack. Seven model parameters are subject to calibration. Snow observations of 67 winters from 14 stations, well-distributed over different altitudes and climatic regions of the Alps, are used to find an optimal parameter setting. Data from another 71 independent winters from 15 stations are used for validation. Results are very promising: median bias and root mean square error for SWE are only −3.0 and 30.8 kg m−2, and +0.3 and 36.3 kg m−2 for peak SWE, respectively. This is a major advance compared to snow models relying on empirical regressions, and even sophisticated thermodynamic snow models do not necessarily perform better. As such, the new model offers a means to derive robust SWE estimates from historical snow depth data and, with some modification, to generate distributed SWE from remotely sensed estimates of spatial snow depth distribution.

scholarly journals GNSS signal-based snow water equivalent determination for different snowpack conditions along a steep elevation gradient

2021 ◽  
Author(s):  
Achille Capelli ◽  
Franziska Koch ◽  
Patrick Henkel ◽  
Markus Lamm ◽  
Florian Appel ◽  
...  
Keyword(s):  
Snow Water Equivalent ◽  
Low Cost ◽  
Elevation Gradient ◽  
Liquid Water Content ◽  
Climatic Conditions ◽  
Swiss Alps ◽  
Snow Density ◽  
Validation Data ◽  
Snow Water ◽  
Snow Conditions

Abstract. Snow water equivalent (SWE) can be measured using low-cost Global Navigation Satellite System (GNSS) sensors with one antenna placed below the snowpack and another one serving as a reference above the snow. The underlying GNSS signal-based algorithm for SWE determination for dry- and wet-snow conditions processes the carrier phases and signal strengths and derives additionally liquid water content (LWC) and snow depth (HS). So far, the algorithm was tested intensively for high-alpine conditions with distinct seasonal accumulation and ablation phases. In general, snow occurrence, snow amount, snow density and LWC can vary considerably with climatic conditions and elevation. Regarding alpine regions, lower elevations mean generally earlier and faster melting, more rain-on-snow events and shallower snowpack. Therefore, we assessed the applicability of the GNSS-based SWE measurement at four stations along a steep elevation gradient (820, 1185, 1510 and 2540 m a.s.l.) in the eastern Swiss Alps during two winter seasons (2018–2020). Reference data of SWE, LWC and HS were collected manually and with additional automated sensors at all locations. The GNSS-derived SWE estimates agreed very well with manual reference measurements along the elevation gradient and the accuracy (RMSE = 34 mm, RMSRE = 11 %) was similar under wet- and dry-snow conditions, although significant differences in snow density and meteorological conditions existed between the locations. The GNSS-derived SWE was more accurate than measured with other automated SWE sensors. However, with the current version of the GNSS algorithm, the determination of daily changes of SWE was found to be less suitable compared to manual measurements or pluviometer recordings and needs further refinement. The values of the GNSS-derived LWC were robust and within the precision of the manual and radar measurements. The additionally derived HS correlated well with the validation data. We conclude that SWE can reliably be determined using low-cost GNSS-sensors under a broad range of climatic conditions and LWC and HS are valuable add-ons.

scholarly journals Spatial heterogeneity in snow water equivalent induced by forest canopy in a mixed beech–fir stand in the Pyrenees

2008 ◽  
Vol 49 ◽  
pp. 83-90 ◽  
Author(s):  
J. Ignacio López-Moreno ◽  
J. Latron
Keyword(s):  
Spatial Heterogeneity ◽  
Forest Canopy ◽  
Snow Water Equivalent ◽  
Climatic Conditions ◽  
Important Influence ◽  
Snow Season ◽  
Snow Water ◽  
The Relationship ◽  
Dominant Influence ◽  
Stand Characteristics

AbstractThis paper analyzes the effect of forest canopy on snow water equivalent during two consecutive snow seasons in a mixed beech–fir stand in the Pyrenees. The results confirm that the forest canopy is a dominant influence on snowpack distribution during the accumulation and melting periods. In general, a noticeable decrease in snow water equivalent and an increase in variability among observations are detected with increasing density of the forest canopy. The influence of the forest canopy on melting rates is complex and highly dependent on the dominant climatic conditions. Similar conclusions are reached for both of the snow seasons for which measurements are available, but several differences are also recorded. This study highlights the important influence of climatic conditions observed during the snow season on the relationship between stand characteristics and snowpack dynamics.

Monitoring snowpack evolution with meteorological reanalysis data in the Atlas Mountains

2021 ◽  
Author(s):  
Wassim Mohamed Baba ◽  
Abdelghani Boudhar ◽  
Simon Gascoin ◽  
Lahoucine Hanich ◽  
Ahmed Marchane ◽  
...  
Keyword(s):  
Snow Cover ◽  
Snow Water Equivalent ◽  
Growing Season ◽  
Reanalysis Data ◽  
Water Runoff ◽  
Snow Cover Area ◽  
Seasonal Snow ◽  
Atlas Mountains ◽  
Snow Water ◽  
Seasonal Snow Cover

&lt;p&gt;The seasonal snow cover in the Altas mountains of Morocco is an important resource, mostly because it provides melt-water runoff for irrigation during the crop growing season. However, the knowledge on physical properties of the snowpack (e.g., snow water equivalent (SWE) and snowmelt) is still very limited due to the scarcity or the lack of ground measurements in the elevated area. In this study we suggest that the recent progresses of meteorological reanalysis data (e.g., MERRA-2 and ERA-5) open new perspectives to overcome this issue. We fed a distributed snowpack evolution model (SnowModel) with downscaled ERA-5 and MERRA-2 reanalyses and evaluate their performance to simulate snow cover. The modeling covers the period 1981 to 2019 (37 water years). SnowModel simulations were assessed using observations of river discharge, snow height and snow cover area derived from MODIS.&lt;/p&gt;&lt;p&gt;For most of hydrological years, the results show a good performance for both MERRA-2 and ERA-5 with a slight superiority of ERA-5, to reproduce the snowpack state.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Key words&lt;/strong&gt;: snow, snow water equivalent, reanalysis , MERRA-2, ERA-5&lt;/p&gt;

scholarly journals Discrimination of a wet snow cover using passive microwave satellite data

1993 ◽  
Vol 17 ◽  
pp. 307-311 ◽  
Author(s):  
A.E. Walker ◽  
B.E. Goodison
Keyword(s):  
Snow Cover ◽  
Snow Water Equivalent ◽  
Winter Season ◽  
Microwave Remote Sensing ◽  
Passive Microwave ◽  
Western Canada ◽  
Polarization Data ◽  
Wet Snow ◽  
Snow Water ◽  
Remote Sensing Methods

Snow-cover monitoring using passive microwave remote sensing methods has been shown to be seriously limited under melt conditions when the snowpack becomes wet. A wet snow indicator has been developed using DMSP SSM/I 37 GHz dual-polarization data for the open prairie region of western Canada. The indicator is used to identify areas of wet snow and discriminate them from areas of snow-free land. Validation and testing efforts have illustrated that the addition of the indicator to the current SSM/I snow water equivalent algorithm provides a more accurate representation of spatial snow coverage throughout the winter season for the open prairie region. The improved spatial and temporal information resulting from the use of the indicator enhances both climatological and hydrological analyses of snow-cover conditions using passive microwave data. Although the wet snow indicator has only been validated for the open prairie region of western Canada, it may also be applicable to other regions of similar terrain and vegetative characteristics. However, in areas of dense vegetation, such as the boreal forest, the performance of the indicator is poor due to the generally low 37 GHz polarization differences of the vegetation cover.

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