Integrated Surface and Subsurface Hydrological Modeling with Snowmelt and Pore Water Freeze–Thaw

Schilling, Oliver S.; Park, Youngjin; Therrien, René; Nagare, Ranjeet M.

doi:10.1111/gwat.12841

Cited by 41 publications

(39 citation statements)

References 71 publications

(128 reference statements)

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“…But with the capabilities of the current generation of flow models, one is no longer restricted to the simulation of such simple GW systems anymore or forced to oversimplify more complex GW systems—the current trend is toward the simulation of complex systems based on integrated surface water (SW)‐GW flow models (IFMs; Barthel & Banzhaf, ; Paniconi & Putti, ). Compared to numerical models that exclusively simulate GW flow, IFMs enable the simulation of GW and SW flow in a physically‐based and fully‐coupled way and allow the inclusion of many hydrologically relevant processes such as unsaturated flow through complex heterogeneous structures (e.g., Irvine et al, ; Schilling, Irvine, et al, ; Tang et al, , ), heat and mass transport (e.g., Carniato et al, ; Karan et al, ; Kurtz et al, ; Schilling et al, ), snow accumulation, melt and pore water freeze‐thaw (e.g., Cochand et al, ; Evans & Ge, ; Painter et al, ; Schilling et al, ; Shojae Ghias et al, ), and SW‐GW‐vegetation interactions (e.g., Banks et al, ; Maxwell & Condon, ; Schomburg et al, ). Compared to numerical flow models that exclusively simulate GW flow, IFMs require more parameters and boundary conditions to be defined and calibrated (the minimally required parameters and boundary conditions of different types of GW and SW simulations are listed in Table ).…”

Section: Introductionmentioning

confidence: 99%

Beyond Classical Observations in Hydrogeology: The Advantages of Including Exchange Flux, Temperature, Tracer Concentration, Residence Time, and Soil Moisture Observations in Groundwater Model Calibration

Schilling

Cook

Brunner

2019

Reviews of Geophysics

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Traditionally, groundwater and surface water flow models have been calibrated against two observation types: hydraulic heads and surface water discharge. It has repeatedly been demonstrated, however, that these classical observations do not contain sufficient information to calibrate flow models. To reduce the predictive uncertainty of flow models, the consideration of other observation types constitutes a promising way forward. Despite the ever-increasing availability of other observation types, however, they are still unconventional when it comes to flow model calibration. By reviewing studies that included nonclassical observations in flow model calibration, benefits and challenges associated with their integration in flow model calibration were identified, and their information content was analyzed. While explicit simulation of mass transport processes in flow models poses challenges, even simplified approaches to integrate tracer concentrations yield significantly better calibration results than using only classical observations. For a majority of calibrated flow models, observations of tracer concentrations and of exchange fluxes were beneficial. Temperature observations improved the simulation of heat transport but often worsened all other model outcomes. Only when temperature observations were made within 2 m of the surface water-groundwater interface did they have the potential to also improve flow and mass transport simulations. Surprisingly, many models were calibrated manually rather than with the widely available, mathematically robust and automated tools. There is a clear need for more systematic implementation of unconventional observations and automated flow model calibration as well as for more systematic quantification of the information content of unconventional observations. Plain Language Summary Traditionally, groundwater and surface water flow models, which are critical for water resources assessment, have been calibrated against only two classical observation types: groundwater levels and surface water discharge. In the past, it has repeatedly been demonstrated that these classical observations do not contain sufficient information to calibrate the parameters required for the simulation of groundwater and surface water flow systems. Owing to the rapid development of measurement techniques throughout the last three decades, however, many other observations of hydrological systems have become widely available. Despite this, observation types other than the classical ones are still unconventional when it comes to flow model calibration. The overall goal of this review is to identify optimal observation types and procedures for flow model calibration and hydrological predictions. We found that observations of tracer concentrations and exchange fluxes are beneficial for most flow models. Temperatures improve the simulation of heat transport but often worsen other flow model outcomes, unless temperatures are measured within 2 m of the surface water-groundwater interface. We identified a need for...

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Section: Introductionmentioning

confidence: 99%

Beyond Classical Observations in Hydrogeology: The Advantages of Including Exchange Flux, Temperature, Tracer Concentration, Residence Time, and Soil Moisture Observations in Groundwater Model Calibration

Schilling

Cook

Brunner

2019

Reviews of Geophysics

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“…The melting rate q melt depends on air temperature ( T air ) and is given by:

ρ_{italicsnow} q_{italicmelt} = α (T_{italicair} - T_{italicthreshold}) when T_{italicair} > T_{italicthreshold}

ρ_{italicsnow} q_{italicmelt} = 0 when T_{italicair} \leq T_{italicthreshold}

which corresponds to the degree‐day approach. Schilling et al () provide more details on the simulation of winter processes with HGS along with illustrative examples.…”

Section: Integrated Surface‐subsurface Flow Modelmentioning

confidence: 99%

Integrated Hydrological Modeling of Climate Change Impacts in a Snow‐Influenced Catchment

Therrien

Lemieux

2018

Groundwater

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The potential impact of climate change on water resources has been intensively studied for different regions and climates across the world. In regions where winter processes such as snowfall and melting play a significant role, anticipated changes in temperature might significantly affect hydrological systems. To address this impact, modifications have been made to the fully integrated surface‐subsurface flow model HydroGeoSphere (HGS) to allow the simulation of snow accumulation and melting. The modified HGS model was used to assess the potential impact of climate change on surface and subsurface flow in the Saint‐Charles River catchment, Quebec (Canada) for the period 2070 to 2100. The model was first developed and calibrated to reproduce observed streamflow and hydraulic heads for current climate conditions. The calibrated model was then used with three different climate scenarios to simulate surface flow and groundwater dynamics for the 2070 to 2100 period. Winter stream discharges are predicted to increase by about 80, 120, and 150% for the three scenarios due to warmer winters, leading to more liquid precipitation and more snowmelt. Conversely, the summer stream discharges are predicted to fall by about 10, 15, and 20% due to an increase in evapotranspiration. However, the annual mean stream discharge should remain stable (±0.1 m3/s). The predicted increase in hydraulic heads in winter may reach 15 m and the maximum decrease in summer may reach 3 m. Simulations show that winter processes play a key role in the seasonal modifications anticipated for surface and subsurface flow dynamics.

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“…There have been substantial efforts to develop snowmelt models [3,7], from simple empirical approaches [8][9][10][11] to more complex ones that include the influence of forest canopies [3,[12][13][14][15][16][17].…”

Section: Introductionmentioning

confidence: 99%

Does Data Availability Constrain Temperature-Index Snow Models? A Case Study in a Humid Boreal Forest

Parajuli

Nadeau

Anctil

et al. 2020

Water

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Temperature-index (TI) models are commonly used to simulate the volume and occurrence of meltwater in snow-fed catchments. TI models have varying levels of complexity but are all based on air temperature observations. The quality and availability of data that drive these models affect their predictive ability, particularly given that they are frequently applied in remote environments. This study investigates the performance of non-calibrated TI models in simulating the subcanopy snow water equivalent (SWE) of a small watershed located in Eastern Canada, for which some distinctive observations were collected. Among three relatively simple TI algorithms, the model that performed the best was selected based on the average percent bias (Pbias of 24%) and root mean square error (RMSE of 100 mm w.e.), and was designated as the base TI model. Then, a series of supplemental tests were conducted in order to quantify the performance gain that resulted from including the following inputs/processes to the base TI model: subcanopy incoming radiation, canopy interception, snow surface temperature, sublimation, and cold content. As a final test, all the above modifications were performed simultaneously. Our results reveal that, with the exception of snow sublimation (Pbias of 5.4%) and snow surface temperature, the variables mentioned above were unable to improve TI models within our sites. It is therefore worth exploring other feasible alternatives to existing TI models in complex forested environments.

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Integrated Surface and Subsurface Hydrological Modeling with Snowmelt and Pore Water Freeze–Thaw

Cited by 41 publications

References 71 publications

Beyond Classical Observations in Hydrogeology: The Advantages of Including Exchange Flux, Temperature, Tracer Concentration, Residence Time, and Soil Moisture Observations in Groundwater Model Calibration

Beyond Classical Observations in Hydrogeology: The Advantages of Including Exchange Flux, Temperature, Tracer Concentration, Residence Time, and Soil Moisture Observations in Groundwater Model Calibration

Integrated Hydrological Modeling of Climate Change Impacts in a Snow‐Influenced Catchment

Does Data Availability Constrain Temperature-Index Snow Models? A Case Study in a Humid Boreal Forest

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