Estimating snowmelt infiltration into frozen soils

Zhao, Lulu; Gray, David B.

doi:10.1002/(sici)1099-1085(199909)13:12/13<1827::aid-hyp896>3.0.co;2-d

Cited by 109 publications

(85 citation statements)

References 25 publications

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“…This confirms that the model's snowmelt infiltration into frozen soils (Zhao and Gray, 1999), rainfall infiltration (Ayers, 1959), canopy interception , and evaporation algorithms (Priestley and Taylor, 1972;Granger and Gray, 1989) were able to simulate the water dynamics and storage in the top soil layer for the lodgepole pine forest. Differences in mean values of soil moisture are most likely due to observation depths being shallower than modelling depths.…”

Section: Discussionsupporting

confidence: 64%

“…Infiltration module: Gray's parametric snowmelt infiltration algorithm (Zhao and Gray, 1999) estimates snowmelt infiltration into frozen soils; Ayers' infiltration (Ayers, 1959) estimates rainfall infiltration into unfrozen soils based on soil texture and ground cover. Both infiltration algorithms link moisture content to the soil column in the hillslope module.…”

Section: Cold Regions Hydrological Modelling Platformmentioning

confidence: 99%

“…To parameterise Gray's parametric infiltration into frozen soils (Zhao and Gray, 1999), initial soil saturation was determined from autumn soil moisture measurements, and initial soil temperature was taken from the measured value prior to snowmelt at various hydrometeorological stations in the basin. For the surface saturation, a value of 1 was given due to preferential flow through snowpacks of early meltwater reaching the surface before the start of the main melt period (Marsh and Pomeroy, 1996).…”

Section: Soil Infiltration Parametersmentioning

confidence: 99%

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Multi-variable evaluation of hydrological model predictions for a headwater basin in the Canadian Rocky Mountains

Fang

Pomeroy

Ellis

et al. 2013

Hydrol. Earth Syst. Sci.

113

151

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Abstract.One of the purposes of the Cold Regions Hydrological Modelling platform (CRHM) is to diagnose inadequacies in the understanding of the hydrological cycle and its simulation. A physically based hydrological model including a full suite of snow and cold regions hydrology processes as well as warm season, hillslope and groundwater hydrology was developed in CRHM for application in the Marmot Creek Research Basin (∼ 9.4 km 2 ), located in the Front Ranges of the Canadian Rocky Mountains. Parameters were selected from digital elevation model, forest, soil, and geological maps, and from the results of many cold regions hydrology studies in the region and elsewhere. Non-calibrated simulations were conducted for six hydrological years during the period 2005-2011 and were compared with detailed field observations of several hydrological cycle components. The results showed good model performance for snow accumulation and snowmelt compared to the field observations for four seasons during the period 2007-2011, with a small bias and normalised root mean square difference (NRMSD) ranging from 40 to 42 % for the subalpine conifer forests and from 31 to 67 % for the alpine tundra and treeline larch forest environments. Overestimation or underestimation of the peak SWE ranged from 1.6 to 29 %. Simulations matched well with the observed unfrozen moisture fluctuation in the top soil layer at a lodgepole pine site during the period 2006-2011, with a NRMSD ranging from 17 to 39 %, but with consistent overestimation of 7 to 34 %. Evaluations of seasonal streamflow during the period 2006-2011 revealed that the model generally predicted well compared to observations at the basin scale, with a NRMSD of 60 % and small model bias (1 %), while at the sub-basin scale NRMSDs were larger, ranging from 72 to 76 %, though overestimation or underestimation for the cumulative seasonal discharge was within 29 %. Timing of discharge was better predicted at the Marmot Creek basin outlet, having a Nash-Sutcliffe efficiency (NSE) of 0.58 compared to the outlets of the sub-basins where NSE ranged from 0.2 to 0.28. The Pearson product-moment correlation coefficient of 0.15 and 0.17 for comparisons between the simulated groundwater storage and observed groundwater level fluctuation at two wells indicate weak but positive correlations. The model results are encouraging for uncalibrated prediction and indicate research priorities to improve simulations of snow accumulation at treeline, groundwater dynamics, and small-scale runoff generation processes in this environment. The study shows that improved hydrological cycle model prediction can be derived from improved hydrological understanding and therefore is a model that can be applied for prediction in ungauged basins.

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Section: Discussionsupporting

confidence: 64%

Section: Cold Regions Hydrological Modelling Platformmentioning

confidence: 99%

Section: Soil Infiltration Parametersmentioning

confidence: 99%

See 1 more Smart Citation

Multi-variable evaluation of hydrological model predictions for a headwater basin in the Canadian Rocky Mountains

Fang

Pomeroy

Ellis

et al. 2013

Hydrol. Earth Syst. Sci.

113

151

View full text Add to dashboard Cite

show abstract

“…For example it puts in question the use of soil texture as an index for classifying or scaling land areas of frozen mineral soils in respect to their water entry, transmission and storage potential. Also, the finding suggests that a single, parametric relationship, such as that proposed by Zhao and Gray (1999), may provide reasonable estimates of snowmelt infiltration into a wide range of frozen soils of various textures.…”

mentioning

confidence: 83%

Influence of soil texture on snowmelt infiltration into frozen soils

Zhao¹,

Gray²,

Toth³

2002

Can. J. Soil. Sci.

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Zhao, L., Gray, D. M. and Toth, B. 2002. Influence of soil texture on snowmelt infiltration into frozen soils. Can. J. Soil Sci. 82: 75-83. This paper describes the influence of soil texture on snowmelt infiltration into frozen soils. Field data collected on frozen, unsaturated agricultural soils of the Canadian Prairies during snow ablation demonstrate: (a) poor association between the amount of infiltration of meltwater released by the seasonal snowcover and soil texture, and (b) small differences in cumulative amounts among soils of widely different textures. A physics-based numerical simulation of heat and mass transfers with phase changes in frozen soils is used to study the mechanics of the infiltration process in representative clay, silty clay loam, silt loam and sandy loam soils. The results of the simulations show that the differences among cumulative snowmelt infiltration into clay, silty clay loam and silt loam soils after 24 h of continuous infiltration are small. Infiltration into a lighter-textured sandy loam after 24 h was on average 23% higher than in the other three soils with most of the increase occurring in the first 5 h of the simulation. In the northern hemisphere, a large part of the annual precipitation occurs as snow, and melting of the seasonal snowcover in the spring is one of the most important hydrological events of the water year. Reliable methods for partitioning the meltwater released during snow ablation to runoff and infiltration are requisite for efficient management of the water resources of these regions.The infiltrability of frozen ground is affected by the thermal and hydrophysical properties of the soil, the soil temperature and moisture regimes, and the quantity and rate of release of meltwater from the snowcover. Many field studies of snowmelt infiltration into frozen soils are reported in the literature (e.g., Willis et al. 1961;Kane 1980;Kane and Stein 1983;Granger et al. 1984;Gray et al. 1985;Burn 1990;Woo and Marsh 1990). These studies show that the cumulative infiltration of meltwater released by a seasonal snowcover (seasonal infiltration) varies directly with the snow water equivalent and inversely with the total water

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“…The river network is extracted using the digital elevation model (DEM) of the study area, and the slopes and rivers are determined by the threshold of the catchment grid with a field investigation having been carried out to validate the data [26]. The corresponding time interval of the confluence is then calculated.…”

Section: Calculation Of Confluencementioning

confidence: 99%

Spring Flood Forecasting Based on the WRF-TSRM Mode

et al. 2018

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Abstract:The snowmelt process is becoming more complex in the context of global warming, and the current existing studies are not effective in using the short-term prediction model to drive the distributed hydrological model to predict snowmelt floods. In this study, we selected the Juntanghu Watershed in Hutubi County of China on the north slope of the Tianshan Mountains as the study area with which to verify the snowmelt flood prediction accuracy of the coupling model. The weather research and forecasting (WRF) model was used to drive a double-layer distributed snowmelt runoff model called the Tianshan Snowmelt Runoff Model (TSRM), which is based on multi-year field snowmelt observations. Moreover, the data from NASA's moderate resolution imaging spectroradiometer (MODIS) was employed to validate the snow water equivalent during the snow-melting period. Results show that, based on the analysis of the flow lines in 2009 and 2010, the WRF-driven TSRM has an overall 80% of qualification ratios (QRs), with determination coefficients of 0.85 and 0.82 for the two years, respectively, which demonstrates the high accuracy of the model. However, due to the influence of the ablation of frozen soils, the forecasted flood peak is overestimated. This problem can be solved by an improvement to the modeled frozen soil layers. The conclusion reached in this study suggests that the WRF-driven TSRM can be used to forecast short-term snowmelt floods on the north slope of the Tianshan Mountains, which can effectively improve the local capacity for the forecasting and early warning of snowmelt floods.

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Estimating snowmelt infiltration into frozen soils

Cited by 109 publications

References 25 publications

Multi-variable evaluation of hydrological model predictions for a headwater basin in the Canadian Rocky Mountains

Multi-variable evaluation of hydrological model predictions for a headwater basin in the Canadian Rocky Mountains

Influence of soil texture on snowmelt infiltration into frozen soils

Spring Flood Forecasting Based on the WRF-TSRM Mode

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