Long‐Term Simulation of Snow Cover and Its Potential Impacts on Seasonal Frost Dynamics in Croplands Across Southern Canada

Li, Ziwei; Qi, Zhiming; Smith, Ward; Pattey, E.; Qian, Budong

doi:10.1029/2021wr031674

Cited by 7 publications

(14 citation statements)

References 89 publications

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“…In addition, a greater degree of intercept of the snow cover by canopies is possible in denser stands [139,140]. This was indirectly confirmed by the shift to earlier dates of the climatic response in April-May, possibly associated with an earlier end of snowmelt and the thaw of soil [141,142].…”

Section: Climatic Response Of Pine Radial Growth Parameters and Its D...mentioning

confidence: 94%

The More the Merrier or the Fewer the Better Fare? Effects of Stand Density on Tree Growth and Climatic Response in a Scots Pine Plantation

Kholdaenko

Babushkina

Belokopytova

et al. 2023

Forests

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In forests, the growth and productivity of individual trees and stands as a whole are regulated by stand density among other factors, because access to vital resources is limited by competition between trees. On 18 experimental plots of Scots pine (Pinus sylvestris L.) planted with a density of 500–128,000 trees/ha in the south taiga (Middle Siberia), interactions between stand density, tree- and stand-scale productivity, and tree-ring parameters were investigated. Tree-scale productivity variables, tree-ring width, and latewood width had stable negative allometric relationships with stand density (R2 > 0.75), except for tree height (insignificant for inventory surveys at ages of 20 and 25 years; R2 > 0.4 at the age of 35 years), while positive allometry was registered for stand productivity variables (R2 > 0.7) and the all-time average latewood ratio (R2 = 0.5 with planting density). Tree-ring parameters aside from the age trends correlate (p < 0.05) between the plots and demonstrate common responses to moderate moisture deficit. Although, its seasonality apparently depends on the resource base and intensity changes with stand density. February–June precipitation is more important for pine growth in dense stands, July–August conditions affect the latewood ratio stronger in sparse stands, and medium-density stands are more resistant to winter frosts.

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Section: Climatic Response Of Pine Radial Growth Parameters and Its D...mentioning

confidence: 94%

The More the Merrier or the Fewer the Better Fare? Effects of Stand Density on Tree Growth and Climatic Response in a Scots Pine Plantation

Kholdaenko

Babushkina

Belokopytova

et al. 2023

Forests

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“…Table S10 summarized the soil P dynamics model parameters used in this study. We used the coefficient of determination ( R 2 ) and the index of agreement ( d ) (Li et al., 2022; Wang et al., 2021) to assess the modeling accuracy, expressed as

R^{2} goodbreak= {(\frac{n * \sum_{i = 1}^{i = n} ()(, {Sim}_{i} * {Obs}_{i}) - \sum_{i = 1}^{i = n} {Sim}_{i} * \sum_{i = 1}^{i = n} {Obs}_{i}}{\sqrt{n * \sum_{i = 1}^{i = n} {Sim}_{i}^{2} - {(\sum_{i = 1}^{i = n} {Sim}_{i})}^{2}} * \sqrt{n * \sum_{i = 1}^{i = n} {Obs}_{i}^{2} - {(\sum_{i = 1}^{i = n} {Obs}_{normali})}^{2}}})}^{2},

d goodbreak= 1 goodbreak- \frac{\sum_{i = 1}^{i = n} {({Sim}_{i} - {Obs}_{i})}^{2}}{\sum_{i = 1}^{i = n} {(|{Sim}_{i} - \overset{true¯}{Obs}| + |{Obs}_{i} - \overset{true¯}{Obs}|)}^{2}},

where

n

is the number of paired observed and simulated values,

{Obs}_{i}

is the i th observed value,

\overset{Obs}{true}

is the mean obs...…”

Section: Methodsmentioning

confidence: 99%

“…Table S10 summarized the soil P dynamics model parameters used in this study. We used the coefficient of determination (R 2 ) and the index of agreement (d) (Li et al, 2022;Wang et al, 2021)…”

Section: Model Validationmentioning

confidence: 99%

Managing mineral phosphorus application with soil residual phosphorus reuse in Canada

Wang,

Qi,

Bennett

2023

Global Change Biology

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With limited phosphorus (P) supplies, increasing P demand, and issues with P runoff and pollution, developing an ability to reuse the large amounts of residual P stored in agricultural soils is increasingly important. In this study, we investigated the potential for residual soil P to maintain crop yields while reducing P applications and losses in Canada. Using a P cycling model coupled with a soil P dynamics model, we analyzed soil P dynamics over 110 years across Canada's provinces. We found that using soil residual P may reduce mineral P demand as large as 132 Gg P year−1 (29%) in Canada, with the highest potential for reducing P applications in the Atlantic provinces, Quebec, Ontario, and British Columbia. Using residual soil P would result in a 21% increase in Canada's cropland P use efficiency. We expected that the Atlantic provinces and Quebec would have the greatest runoff P loss reduction with use of residual soil P, with the average P loss rate decreasing from 4.24 and 1.69 kg ha−1 to 3.45 and 1.38 kg ha−1, respectively. Ontario, Manitoba, and British Columbia would experience relatively lower reductions in P loss through use of residual soil P, with the average runoff P loss rate decreasing from 0.44, 0.36, and 4.33 kg ha−1 to 0.19, 0.26, and 4.14 kg ha−1, respectively. Our study highlights the importance of considering residual soil P as a valuable resource and its potential for reducing P pollution.

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“…At the St. Emmanuel site after, flow was measured and water samples were collected, water was drained out through a sink on the floor to an external pump station and disposed of in an open ditch nearby through underground pipes. In the current study, the winter season was defined as from the first day of November to the last day of April to cover the time span with the existence of snow for the two sites (Li et al, 2022) instead of from the winter solstice to the spring equinox. The spring snowmelt season was defined as the first day when significant snowmelt occurred during February or March (when snow depth peaked and commenced decreasing) towards the last day when the snowpack was melted entirely, plus ten days as a grace period for the snowmelt water to be fully discharged through drains.…”

Section: The Experimental Sitesmentioning

confidence: 99%

“…The effective drain radius for the St. Emmanuel site and Harrow sites was 4.4 cm and 0.5 cm based on previously reported values and recommendations (Singh et al, 1994;Ghane, 2022). Li et al (2022) described detailed auto-calibration procedures for the RZ-SHAW model. Calibration of initial snow density, maximum average snowpack density, dry soil albedo, wet soil albedo, surface resistance, and lateral hydraulic conductivity was conducted against observed snow depth, soil temperature, and subsurface drainage discharge through a customized auto-calibration script.…”

Section: Model Simulationmentioning

confidence: 99%

Predicted Contribution of Snowmelt to Subsurface Drainage Discharge in Two Subsurface-Drained Fields in Southern Quebec and Ontario

Li,

Qi,

Madramootoo

et al. 2024

Journal of the ASABE

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Highlights RZ-SHAW model delivered a satisfactory simulation for winter subsurface drainage discharge. Snowmelt dominated the drainage discharge during the winter and spring snowmelt seasons in southern Quebec. Snowmelt contributed to 29% and 18% of winter and annual drainage discharge, respectively, in southern Ontario. Abstract. Late winter/early spring has been recognized as a critical period for subsurface drainage discharge and associated nutrient losses due to snowmelt and rainfall in croplands under cold, humid climates in North America and Europe. Although the detachment and transport processes of soil particles under snowmelt and rainfall are known to be different, studies quantifying the contribution of snowmelt to winter drainage discharge are limited. This study aims to investigate the contribution of snowmelt to subsurface drainage discharge at two winterized experimental sites in southern Quebec and Ontario, Canada, using observed data and the Root Zone Water Quality Model-Simultaneous Heat and Water model (RZ-SHAW model). The RZ-SHAW model was calibrated and validated against the measured snow depth and year-round subsurface drainage discharge data from 2021 to 2023 at St. Emmanuel, Quebec, and from 2000 to 2003 at Harrow, Ontario. RZ-SHAW demonstrated satisfactory Nash-Sutcliffe model efficiency values (NSE = 0.50) for simulating snow depth, soil temperature, and winter subsurface drainage discharge. The calibrated RZ-SHAW model was used to simulate the contribution of snowmelt to subsurface drainage for the two sites from 1990 to 2022. The snowmelt was predicted to contribute 55% and 44% of the winter and annual subsurface drainage discharge for the cropland in Southern Quebec. In contrast, for the southern Ontario site, the contribution of snowmelt to winter and annual subsurface drainage discharge was 29% and 18%, respectively. Considering that snowmelt in Southern Quebec contributed a significant fraction of winter and annual subsurface drainage discharge, more attention should be devoted to adapting and developing new winter management for nutrient loss in future research in the region. Keywords: Cold region, Cropland drainage, Drainage partition, RZ-SHAW, RZWQM2, Snowmelt, Soil freeze and thaw, Winter subsurface drainage.

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Long‐Term Simulation of Snow Cover and Its Potential Impacts on Seasonal Frost Dynamics in Croplands Across Southern Canada

Cited by 7 publications

References 89 publications

The More the Merrier or the Fewer the Better Fare? Effects of Stand Density on Tree Growth and Climatic Response in a Scots Pine Plantation

The More the Merrier or the Fewer the Better Fare? Effects of Stand Density on Tree Growth and Climatic Response in a Scots Pine Plantation

Managing mineral phosphorus application with soil residual phosphorus reuse in Canada

Predicted Contribution of Snowmelt to Subsurface Drainage Discharge in Two Subsurface-Drained Fields in Southern Quebec and Ontario

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