A simple temperature-based method to estimate heterogeneous frozen ground within a distributed watershed model

Follum, Michael L.; Niemann, Jeffrey D.; Parno, Julie; Downer, Charles W.

doi:10.5194/hess-22-2669-2018

Cited by 5 publications

(4 citation statements)

References 62 publications

(65 reference statements)

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“…The RTI method has been shown to produce better estimates of snow-covered area (SCA) than the TI method for the Senator Beck Basin (SBB) in Colorado (Follum et al, 2015) and had similar accuracy as the TI model in snow water equivalent (SWE) estimation at two observation points for the Sleepers River experimental watershed in Vermont (Follum, Niemann, Parno, & Downer, 2018). However, neither study considered whether the snowmelt hydrograph differed between the TI or RTI approaches.…”

mentioning

confidence: 99%

A comparison of snowmelt‐derived streamflow from temperature‐index and modified‐temperature‐index snow models

Follum

Niemann

Fassnacht

2019

Hydrological Processes

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Reliable estimation of the volume and timing of snowmelt runoff is vital for water supply and flood forecasting in snow‐dominated regions. Snowmelt is often simulated using temperature‐index (TI) models due to their applicability in data‐sparse environments. Previous research has shown that a modified‐TI model, which uses a radiation‐derived proxy temperature instead of air temperature as its surrogate for available energy, can produce more accurate snow‐covered area (SCA) maps than a traditional TI model. However, it is unclear whether the improved SCA maps are associated with improved snow water equivalent (SWE) estimation across the watershed or improved snowmelt‐derived streamflow simulation. This paper evaluates whether a modified‐TI model produces better streamflow estimates than a TI model when they are used within a fully distributed hydrologic model. It further evaluates the performance of the two models when they are calibrated using either point SWE measurements or SCA maps. The Senator Beck Basin in Colorado is used as the study site because its surface is largely bedrock, which reduces the role of infiltration and emphasizes the role of the SWE pattern on streamflow generation. Streamflow is simulated using both models for 6 years. The modified‐TI model produces more accurate streamflow estimates (including flow volume and peak flow rate) than the TI model, likely because the modified‐TI model better reproduces the SWE pattern across the watershed. Both models also produce better performance when calibrated with SCA maps instead of point SWE data, likely because the SCA maps better constrain the space‐time pattern of SWE.

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mentioning

confidence: 99%

A comparison of snowmelt‐derived streamflow from temperature‐index and modified‐temperature‐index snow models

Follum

Niemann

Fassnacht

2019

Hydrological Processes

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“…Perhaps these differences are indicative of local differences in spite of the intention that both datasets represent relatively large areas. Note that Follum et al (2018) modeled and measured frost depths at six sites in a small, approximately 3 km by 4 km subbasin of a watershed in Vermont and found significantly different results among the sites over an elevation range of 170 m. In comparison, the NDAWN stations are between 12 and 31 km from the nearest MERRA-2 grid point, and the absolute difference in elevation averages 27 m with a range from 3 to 115 m.…”

Section: Discussionmentioning

confidence: 91%

“…• Ground cover is not taken into account in MaxFrst. Follum et al (2018) find that the inclusion of insulation by ground cover makes a significant difference in modeled frost depths in their Continuous Frozen Ground Index model. That model does not, however, include soil moisture.…”

Section: Discussionmentioning

confidence: 95%

Evaluation of modeled and reanalysis estimates of frost depth through comparison to ground observations

Barna¹,

Vuyovich²,

Jones³

2019

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Frozen soils can withstand heavy vehicle loads where the soils would otherwise be too weak. This is important as vehicle mobility models require input of the ground conditions to assess seasonal traffickability. Modeling these frost depths uses the properties of the soil along with any snow cover and air temperature data. Though weather stations with air temperature data are becoming more widespread, station density varies worldwide. Gridded reanalysis products, on the other hand, provide weather data on a global scale.Our objectives are (a) to evaluate the usefulness of reanalysis data to provide estimates of frost depth and (b) to determine the accuracy of simulated frost depths using either measured or reanalysis air temperature data. We use two one-dimensional models: a coupled heat and moisture flow model that simulates frost and thaw depths throughout the winter and a decoupled heat and moisture model that calculates the maximum frost depth. We compare frost depths determined from measured soil temperatures at stations in North Dakota and Minnesota and reanalysis frost depths with modeled values using both station and reanalysis air temperature data. Modeled frost depths depend more strongly on the depth and density of the snow layer than on the soil properties.

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“…The third approach requires complex numerical solutions outside the scope of a study of this nature. Ground thawing-and freezing-depth models have proven adept at predicting frost depth (e.g., Follum et al 2018); however, linking these model results to infiltration or runoff effects is not straightforward.…”

Section: Fsim Formulationmentioning

confidence: 99%

Wintertime snow and precipitation conditions in the Willow Creek watershed above Ririe Dam, Idaho

Giovando¹,

Engel²,

Daly³

et al. 2021

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The Ririe Dam and Reservoir project is located on Willow Creek near Idaho Falls, Idaho, and is important for flood risk reduction and water supply. The current operating criteria is based on fully storing a large winter runoff event. These winter runoff events are generally from large storm events, termed atmospheric rivers, which produce substantial precipitation. In addition to the precipitation, enhanced runoff is produced due to frozen soil and snowmelt. However, the need for additional water supply by local stakeholders has prompted the U.S. Army Corps of Engineers to seek to better understand the current level of flood risk reduction provided by Ririe Dam and Reservoir. Flood risk analysis using hydrologic modeling software requires quantification of the probability for all of the hydrometeorologic inputs. Our study develops the precipitation, SWE, and frozen ground probabilities that are required for the hydrologic modeling necessary to quantify the current winter flood risk.

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A simple temperature-based method to estimate heterogeneous frozen ground within a distributed watershed model

Cited by 5 publications

References 62 publications

A comparison of snowmelt‐derived streamflow from temperature‐index and modified‐temperature‐index snow models

A comparison of snowmelt‐derived streamflow from temperature‐index and modified‐temperature‐index snow models

Evaluation of modeled and reanalysis estimates of frost depth through comparison to ground observations

Wintertime snow and precipitation conditions in the Willow Creek watershed above Ririe Dam, Idaho

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