scholarly journals Uncertainties in Snowpack Simulations—Assessing the Impact of Model Structure, Parameter Choice, and Forcing Data Error on Point‐Scale Energy Balance Snow Model Performance

2019 ◽  
Vol 55 (4) ◽  
pp. 2779-2800 ◽  
Author(s):  
Daniel Günther ◽  
Thomas Marke ◽  
Richard Essery ◽  
Ulrich Strasser
Keyword(s):  
Energy Balance ◽  
Model Performance ◽  
Model Structure ◽  
Structure Parameter ◽  
Point Scale ◽  
Parameter Choice ◽  
Data Error ◽  
Snow Model ◽  
The Impact

scholarly journals A two-layer canopy with thermal inertia for an improved modelling of the sub-canopy snowpack energy-balance

2015 ◽  
Vol 8 (1) ◽  
pp. 209-262 ◽  
Author(s):  
I. Gouttevin ◽  
M. Lehning ◽  
T. Jonas ◽  
D. Gustafsson ◽  
M. Mölder
Keyword(s):  
Energy Balance ◽  
Temperature Drop ◽  
Model Performance ◽  
Thermal Inertia ◽  
Thermal Response ◽  
Canopy Temperature ◽  
Night Time ◽  
The Difference ◽  
Snow Model ◽  
The Impact

Abstract. A new, two-layer canopy module with thermal inertia as part of the detailed snow model SNOWPACK (version 3.2.1) is presented and evaluated. This module is designed to reproduce the difference in thermal response between leafy and woody canopy elements, and their impact on the underlying snowpack energy balance. Given the number of processes resolved, the SNOWPACK model with its enhanced canopy module constitutes a very advanced, physics-based atmosphere-to-soil-through-canopy-and-snow modelling chain. Comparisons of modelled sub-canopy thermal radiation to stand-scale observations at an Alpine site (Alptal, Switzerland) demonstrate the improvements of the new canopy module. Both thermal heat mass and the two-layer canopy formulation contribute to reduce the daily amplitude of the modelled canopy temperature signal, in agreement with observations. Particularly striking is the attenuation of the night-time drop in canopy temperature, which was a key model bias. We specifically show that a single-layered canopy model is unable to produce this limited temperature drop correctly. The impact of the new parameterizations on the modelled dynamics of the sub-canopy snowpack is analysed and yields consistent results but the frequent occurrence of mixed-precipitation events at Alptal prevents a conclusive assessment of model performance against snow data. The new model is also successfully tested without specific tuning against measured tree temperatures and biomass heat storage fluxes at the boreal site of Norunda (Sweden). This provides an independent assessment of its physical consistency and stresses the robustness and transferability of the parameterizations used.

scholarly journals A two-layer canopy model with thermal inertia for an improved snowpack energy balance below needleleaf forest (model SNOWPACK, version 3.2.1, revision 741)

2015 ◽  
Vol 8 (8) ◽  
pp. 2379-2398 ◽  
Author(s):  
I. Gouttevin ◽  
M. Lehning ◽  
T. Jonas ◽  
D. Gustafsson ◽  
M. Mölder
Keyword(s):  
Energy Balance ◽  
Temperature Drop ◽  
Model Performance ◽  
Ground Surface ◽  
Thermal Inertia ◽  
Thermal Response ◽  
Canopy Temperature ◽  
Current Form ◽  
The Impact ◽  
Canopy Model

Abstract. A new, two-layer canopy module with thermal inertia as part of the detailed snow model SNOWPACK (version 3.2.1) is presented and evaluated. As a by-product of these new developments, an exhaustive description of the canopy module of the SNOWPACK model is provided, thereby filling a gap in the existing literature. In its current form, the two-layer canopy module is suited for evergreen needleleaf forest, with or without snow cover. It is designed to reproduce the difference in thermal response between leafy and woody canopy elements, and their impact on the underlying snowpack or ground surface energy balance. Given the number of processes resolved, the SNOWPACK model with its enhanced canopy module constitutes a sophisticated physics-based modeling chain of the continuum going from atmosphere to soil through the canopy and snow. Comparisons of modeled sub-canopy thermal radiation to stand-scale observations at an Alpine site (Alptal, Switzerland) demonstrate improvements induced by the new canopy module. Both thermal heat mass and the two-layer canopy formulation contribute to reduce the daily amplitude of the modeled canopy temperature signal, in agreement with observations. Particularly striking is the attenuation of the nighttime drop in canopy temperature, which was a key model bias. We specifically show that a single-layered canopy model is unable to produce this limited temperature drop correctly. The impact of the new parameterizations on the modeled dynamics of the sub-canopy snowpack is analyzed. The new canopy module yields consistent results but the frequent occurrence of mixed-precipitation events at Alptal prevents a conclusive assessment of model performance against snow data. The new model is also successfully tested without specific tuning against measured tree temperature and biomass heat-storage fluxes at the boreal site of Norunda (Sweden). This provides an independent assessment of its physical consistency and stresses the robustness and transferability of the chosen parameterizations. The SNOWPACK code including the new canopy module, is available under Gnu General Public License (GPL) license and upon creation of an account at https://models.slf.ch/.

scholarly journals Impact of Rain Gauges Distribution on the Runoff Simulation of a Small Mountain Catchment in Southern Ecuador

Water ◽  
2018 ◽  
Vol 10 (9) ◽  
pp. 1169 ◽  
Author(s):  
Adrián Sucozhañay ◽  
Rolando Célleri
Keyword(s):  
Hydrological Modeling ◽  
Rainfall Variability ◽  
Model Performance ◽  
Rainfall Data ◽  
Model Structure ◽  
Mountain Regions ◽  
Rainfall Estimation ◽  
Runoff Simulation ◽  
Rain Gauges ◽  
The Impact

In places with high spatiotemporal rainfall variability, such as mountain regions, input data could be a large source of uncertainty in hydrological modeling. Here we evaluate the impact of rainfall estimation on runoff modeling in a small páramo catchment located in the Zhurucay Ecohydrological Observatory (7.53 km2) in the Ecuadorian Andes, using a network of 12 rain gauges. First, the HBV-light semidistributed model was analyzed in order to select the best model structure to represent the observed runoff and its subflow components. Then, we developed six rainfall monitoring scenarios to evaluate the impact of spatial rainfall estimation in model performance and parameters. Finally, we explored how a model calibrated with far-from-perfect rainfall estimation would perform using new improved rainfall data. Results show that while all model structures were able to represent the overall runoff, the standard model structure outperformed the others for simulating subflow components. Model performance (NSeff) was improved by increasing the quality of spatial rainfall estimation from 0.31 to 0.80 and from 0.14 to 0.73 for calibration and validation period, respectively. Finally, improved rainfall data enhanced the runoff simulation from a model calibrated with scarce rainfall data (NSeff 0.14) from 0.49 to 0.60. These results confirm that in mountain regions model uncertainty is highly related to spatial rainfall and, therefore, to the number and location of rain gauges.

scholarly journals ESCIMO.spread (v2): parameterization of a spreadsheet-based energy balance snow model for inside-canopy conditions

2016 ◽  
Vol 9 (2) ◽  
pp. 633-646 ◽  
Author(s):  
T. Marke ◽  
E. Mair ◽  
K. Förster ◽  
F. Hanzer ◽  
J. Garvelmann ◽  
...  
Keyword(s):  
Energy Balance ◽  
Snow Cover ◽  
Forest Canopy ◽  
Model Performance ◽  
Snow Accumulation ◽  
Meteorological Conditions ◽  
Mountain Range ◽  
Point Energy ◽  
Snow Model ◽  
Mean Square Errors

Abstract. This article describes the extension of the ESCIMO.spread spreadsheet-based point energy balance snow model by (i) an advanced approach for precipitation phase detection, (ii) a method for cold content and liquid water storage consideration and (iii) a canopy sub-model that allows the quantification of canopy effects on the meteorological conditions inside the forest as well as the simulation of snow accumulation and ablation inside a forest stand. To provide the data for model application and evaluation, innovative low-cost snow monitoring systems (SnoMoS) have been utilized that allow the collection of important meteorological and snow information inside and outside the canopy. The model performance with respect to both, the modification of meteorological conditions as well as the subsequent calculation of the snow cover evolution, are evaluated using inside- and outside-canopy observations of meteorological variables and snow cover evolution as provided by a pair of SnoMoS for a site in the Black Forest mountain range (southwestern Germany). The validation results for the simulated snow water equivalent with Nash–Sutcliffe model efficiency values of 0.81 and 0.71 and root mean square errors of 8.26 and 18.07 mm indicate a good overall model performance inside and outside the forest canopy, respectively. The newly developed version of the model referred to as ESCIMO.spread (v2) is provided free of charge together with 1 year of sample data including the meteorological data and snow observations used in this study.

scholarly journals Comparison of hydrological model structures based on recession and low flow simulations

2011 ◽  
Vol 8 (4) ◽  
pp. 6833-6866 ◽  
Author(s):  
M. Staudinger ◽  
K. Stahl ◽  
J. Seibert ◽  
M. P. Clark ◽  
L. M. Tallaksen
Keyword(s):  
Hydrological Model ◽  
Lower Layer ◽  
Model Performance ◽  
Low Flow ◽  
Model Structure ◽  
Hydrological Models ◽  
Flow Simulations ◽  
Low Flows ◽  
The Impact ◽  
Model Structures

Abstract. Low flows are often poorly reproduced by commonly used hydrological models, which are traditionally designed to meet peak flow situations. Hence, there is a need to improve hydrological models for low flow prediction. This study assessed the impact of model structure on low flow simulations and recession behaviour using the Framework for Understanding Structural Errors (FUSE). FUSE identifies the set of subjective decisions made when building a hydrological model, and provides multiple options for each modeling decision. Altogether 79 models were created and applied to simulate stream flows in the snow dominated headwater catchment Narsjø in Norway (119 km2). All models were calibrated using an automatic optimisation method. The results showed that simulations of summer low flows were poorer than simulations of winter low flows, reflecting the importance of different hydrological processes. The model structure influencing winter low flow simulations is the lower layer architecture, whereas various model structures were identified to influence model performance during summer.

scholarly journals ESCIMO.spread (v2): parameterization of a spreadsheet-based energy balance snow model for inside-canopy conditions

2015 ◽  
Vol 8 (9) ◽  
pp. 8155-8191
Author(s):  
T. Marke ◽  
E. Mair ◽  
K. Förster ◽  
F. Hanzer ◽  
J. Garvelmann ◽  
...  
Keyword(s):  
Energy Balance ◽  
Snow Cover ◽  
Forest Canopy ◽  
Model Performance ◽  
Snow Accumulation ◽  
Meteorological Conditions ◽  
West Germany ◽  
Mountain Range ◽  
Point Energy ◽  
Snow Model

Abstract. This article describes the extension of the spreadsheet-based point energy balance snow model ESCIMO.spread by (i) an advanced approach for precipitation phase detection, (ii) a concept for cold and liquid water storage consideration and (iii) a canopy sub-model that allows to quantify the effect of a forest canopy on the meteorological conditions inside the forest as well as the simulation of snow accumulation and ablation inside a forest stand. To provide the data for model application and evaluation, innovative low-cost Snow Monitoring Systems (SnoMoS) have been utilized that allow the collection of important meteorological and snow information in and outside the canopy. The model performance with respect to both, the modification of meteorological conditions as well as the subsequent calculation of the snow cover evolution are evaluated using in- and outside-canopy observations of meteorological variables and snow cover evolution as provided by a pair of SnoMoS for a site in the Black Forest mountain range (south-west Germany). The validation results indicate a good overall model performance in and outside the forest canopy. The newly developed version of the model refered to as ESCIMO.spread (v2) is provided free of charge together with one year of sample data including the meteorological data and snow observations used in this study.

Investigating hydrological model versatility to simulate extreme flood events 

2021 ◽  
Author(s):  
Daniela Peredo Ramirez ◽  
Maria-Helena Ramos ◽  
Vazken Andréassian ◽  
Ludovic Oudin
Keyword(s):  
Hydrological Model ◽  
Model Performance ◽  
Original Model ◽  
Model Structure ◽  
Model Adaptation ◽  
Flood Events ◽  
Runoff Generation ◽  
Local Climate ◽  
Extreme Flood ◽  
The Impact

<p><span>High-impact flood events in the Mediterranean region are often the result of a combination of local climate and topographic characteristics of the region. Therefore, the way runoff generation processes are represented in hydrological models is a key factor to simulate and forecast floods. In this study, we adapt an existing model in order to increase its versatility to simulate flood events occurring under different conditions: during or after wet periods and after long and dry summer periods. The model adaptation introduces a dependency on rainfall intensity in the production function. The impact of this adaptation is analysed considering model performance over selected flood events and also over a continuous 10-year period of flows. The event-based assessment showed that the adapted model structure performs better than or equal to the original model structure in terms of differences in the timing of peak discharges, regardless of the season of the year when the flood occurs. The most important improvement was observed in the simulation of the magnitude of the flood peaks. A visualisation of model versatility is proposed, which allows detecting the time steps when the new model structure tends to behave more similarly or differently from the original model structure in terms of runoff production. Overall, the results show the potential of the model adaptation proposed to simulate floods originated by different hydrological processes and the value of increasing hydrological model versatility to simulate extreme events.</span></p>

scholarly journals Comparison of hydrological model structures based on recession and low flow simulations

2011 ◽  
Vol 15 (11) ◽  
pp. 3447-3459 ◽  
Author(s):  
M. Staudinger ◽  
K. Stahl ◽  
J. Seibert ◽  
M. P. Clark ◽  
L. M. Tallaksen
Keyword(s):  
Hydrological Model ◽  
Lower Layer ◽  
Model Performance ◽  
Low Flow ◽  
Model Structure ◽  
Hydrological Models ◽  
Flow Simulations ◽  
Low Flows ◽  
The Impact ◽  
Model Structures

Abstract. Low flows are often poorly reproduced by commonly used hydrological models, which are traditionally designed to meet peak flow situations. Hence, there is a need to improve hydrological models for low flow prediction. This study assessed the impact of model structure on low flow simulations and recession behaviour using the Framework for Understanding Structural Errors (FUSE). FUSE identifies the set of subjective decisions made when building a hydrological model and provides multiple options for each modeling decision. Altogether 79 models were created and applied to simulate stream flows in the snow dominated headwater catchment Narsjø in Norway (119 km2). All models were calibrated using an automatic optimisation method. The results showed that simulations of summer low flows were poorer than simulations of winter low flows, reflecting the importance of different hydrological processes. The model structure influencing winter low flow simulations is the lower layer architecture, whereas various model structures were identified to influence model performance during summer.

Results of the IACS Debris-covered Glaciers Working Group melt model intercomparison

2020 ◽  
Author(s):  
Francesca Pellicciotti ◽  
Adria Fontrodona-Bach ◽  
David Rounce ◽  
Lindsey Nicholson
Keyword(s):  
Energy Balance ◽  
Working Group ◽  
Model Performance ◽  
Poor Performance ◽  
Empirical Models ◽  
Model Complexity ◽  
Validation Data ◽  
Energy Balance Models ◽  
Model Components ◽  
The Impact

<p>Many mountain ranges across the globe support abundant debris-covered glaciers, and the proportion of glacierised area covered by debris is expected to increase under continuing negative mass balance. Within the activities of a newly established IACS Working Group (WG) on debris-covered glaciers, we have been carrying out an intercomparison of melt models for debris-covered ice, to identify the level of model complexity required to estimate sub-debris melt. This is a first necessary step to advance understanding of how debris impacts glacier response to climate at the local, regional, and global scale and accurately represent debris-covered glaciers in models of regional runoff and sea-level change projections.</p><p>We compare ice melt rates simulated by 15 models of different complexity, forced at the point scale using data from nine automatic weather stations in distinct climatic regimes across the globe. We include energy-balance models with a variety of structural choices and model components as well as a range of simplified approaches. Empirical models are run twice: with values from literature and after recalibration at the sites. We then calculate uncertainty bounds for all simulations by prescribing a range of plausible parameters and varying them in a Monte Carlo framework. We restrict the comparison to the melt season and exclude conditions as few current models have the capability to account for them.</p><p>Model results vary across sites considerably, with some sites where most models show a consistently good performance (e.g. in the Alps) which is also similar for energy-balance and empirical models, and sites where models diverge widely and the performance is overall poorer (e.g. in New Zealand and the Caucasus). It is also evident that with a few exceptions, most of the simpler, more empirical models have poor performance without recalibration. A few of the energy-balance models consistently give results different to the others, and we investigate structural differences, the impact of temporal resolution on the calculations (hourly versus daily) and the calculation of turbulent fluxes in particular.    </p><p>We provide a final assessment of model performance under different climate forcing, and evaluate models strengths and limitations against independent validation data from the same sites. We also provide suggestions for future model improvements and identify missing model components and crucial knowledge gaps and which require further attention by the debris-covered glacier community.</p>

Fiction and reality in the modelling world-balance between simplicity and complexity, calibration and identifiability, verification and falsification

1999 ◽  
Vol 39 (9) ◽  
pp. 1-8 ◽  
Author(s):  
P. Harremoës ◽  
H. Madsen
Keyword(s):  
Model Prediction ◽  
Model Performance ◽  
Data Series ◽  
Urban Drainage ◽  
Model Structure ◽  
And Control

Where is the balance between simplicity and complexity in model prediction of urban drainage structures? The calibration/verification approach to testing of model performance gives an exaggerated sense of certainty. Frequently, the model structure and the parameters are not identifiable by calibration/verification on the basis of the data series available, which generates elements of sheer guessing - unless the universality of the model is be based on induction, i.e. experience from the sum of all previous investigations. There is a need to deal more explicitly with uncertainty and to incorporate that in the design, operation and control of urban drainage structures.

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