scholarly journals Elevation based correction of snow coverage retrieved from satellite images to improve model calibration

2009 ◽  
Vol 13 (5) ◽  
pp. 639-649 ◽  
Author(s):  
C. Corbari ◽  
G. Ravazzani ◽  
J. Martinelli ◽  
M. Mancini
Keyword(s):  
Satellite Images ◽  
River Flow ◽  
Simple Procedure ◽  
Model Parameters ◽  
Distributed Hydrological Model ◽  
Temperature Index ◽  
Improve Model ◽  
Index Approach ◽  
Snow Model ◽  
Parameter Values

Abstract. The most widely used method for snow dynamic simulation relies on temperature index approach, that makes snow melt and accumulation processes depend on air temperature related parameters. A recently used approach to calibrate these parameters is to compare model results with snow coverage retrieved from satellite images. In area with complex topography and heterogeneous land cover, snow coverage may be affected by the presence of shaded area or dense forest that make pixels to be falsely classified as uncovered. These circumstances may have, in turn, an influence on calibration of model parameters. In this paper we propose a simple procedure to correct snow coverage retrieved from satellite images. We show that using raw snow coverage to calibrate snow model may lead to parameter values out of the range accepted by literature, so that the timing of snow dynamics measured at two ground stations is not correctly simulated. Moreover, when the snow model is implemented into a continuous distributed hydrological model, we show that calibration against corrected snow coverage reduces the error in the simulation of river flow in an Alpine catchment.

scholarly journals Assessing the benefit of snow data assimilation for runoff modeling in Alpine catchments

2016 ◽  
Vol 20 (9) ◽  
pp. 3895-3905 ◽  
Author(s):  
Nena Griessinger ◽  
Jan Seibert ◽  
Jan Magnusson ◽  
Tobias Jonas
Keyword(s):  
Time Series ◽  
Data Assimilation ◽  
Hydrological Model ◽  
Temperature Index ◽  
Degree Day ◽  
Index Approach ◽  
Snow Model ◽  
Alpine Catchments ◽  
Time Invariant ◽  
Snowmelt Time

Abstract. In Alpine catchments, snowmelt is often a major contribution to runoff. Therefore, modeling snow processes is important when concerned with flood or drought forecasting, reservoir operation and inland waterway management. In this study, we address the question of how sensitive hydrological models are to the representation of snow cover dynamics and whether the performance of a hydrological model can be enhanced by integrating data from a dedicated external snow monitoring system. As a framework for our tests we have used the hydrological model HBV (Hydrologiska Byråns Vattenbalansavdelning) in the version HBV-light, which has been applied in many hydrological studies and is also in use for operational purposes. While HBV originally follows a temperature-index approach with time-invariant calibrated degree-day factors to represent snowmelt, in this study the HBV model was modified to use snowmelt time series from an external and spatially distributed snow model as model input. The external snow model integrates three-dimensional sequential assimilation of snow monitoring data with a snowmelt model, which is also based on the temperature-index approach but uses a time-variant degree-day factor. The following three variations of this external snow model were applied: (a) the full model with assimilation of observational snow data from a dense monitoring network, (b) the same snow model but with data assimilation switched off and (c) a downgraded version of the same snow model representing snowmelt with a time-invariant degree-day factor. Model runs were conducted for 20 catchments at different elevations within Switzerland for 15 years. Our results show that at low and mid-elevations the performance of the runoff simulations did not vary considerably with the snow model version chosen. At higher elevations, however, best performance in terms of simulated runoff was obtained when using the snowmelt time series from the snow model, which utilized data assimilation. This was especially true for snow-rich years. These findings suggest that with increasing elevation and the correspondingly increased contribution of snowmelt to runoff, the accurate estimation of snow water equivalent (SWE) and snowmelt rates has gained importance.

scholarly journals Modelling temperature variations in polar snow using DAISY

1997 ◽  
Vol 43 (143) ◽  
pp. 180-191 ◽  
Author(s):  
Ε. M. Morris ◽  
H. -P. Bader ◽  
P. Weilenmann
Keyword(s):  
Field Experiments ◽  
A Priori ◽  
Model Parameters ◽  
Data Set ◽  
International Geophysical Year ◽  
Snow Model ◽  
Using Data ◽  
Polar Snow ◽  
Parameter Values ◽  
The Antarctic

AbstractA physics-based snow model has been calibrated using data collected at Halley Bay, Antarctica, during the International Geophysical Year. Variations in snow temperature and density are well-simulated using values for the model parameters within the range reported from other polar field experiments. The effect of uncertainty in the parameter values on the accuracy of the predictions is no greater than the effect of instrumental error in the input data. Thus, this model can be used with parameters determined a priori rather than by optimization. The model has been validated using an independent data set from Halley Bay and then used to estimate 10 m temperatures on the Antarctic Peninsula plateau over the last half-century.

scholarly journals Assessing the transferability and robustness of an enhanced temperature-index glacier-melt model

2009 ◽  
Vol 55 (190) ◽  
pp. 258-274 ◽  
Author(s):  
Marco Carenzo ◽  
Francesca Pellicciotti ◽  
Stefan Rimkus ◽  
Paolo Burlando
Keyword(s):  
Energy Balance ◽  
Meteorological Conditions ◽  
Shortwave Radiation ◽  
Balance Model ◽  
Model Parameters ◽  
Radiation Factor ◽  
Temperature Index ◽  
Clear Sky ◽  
Few Data ◽  
Parameter Values

AbstractWe investigate the transferability of an enhanced temperature-index melt model that was developed and tested on Haut Glacier d’Arolla, Switzerland, in the 2001 season. The model’s empirical parameters (temperature factor, TF, and shortwave radiation factor, SRF) are recalibrated for: (1) other locations on Haut Glacier d’Arolla; (2) subperiods of distinct meteorological conditions; (3) different years on Haut Glacier d’Arolla; and (4) other glaciers in different years. The model parameters are optimized against simulations of an energy-balance model validated against ablation observations. Results are compared with those obtained with the original parameters. The model works very well when applied to other sites, seasons and glaciers, with the exception of overcast conditions. Differences are due to underestimation of high melt rates. The parameter values are associated with the prevailing energy-balance conditions, showing that high SRF are obtained on clear-sky days, whereas higher TF are typical of locations where glacier winds prevail and turbulent fluxes are high. We also provide a range of parameters clearly associated with the site’s location and its meteorological characteristics that could help to assign parameter values to sites where few data are available.

scholarly journals Development of a semi-distributed hydrological model on a tidal-affected river: application to the Adour catchment, France.

2020 ◽  
Author(s):  
Valentin Mansanarez ◽  
Guillaume Thirel ◽  
Olivier Delaigue ◽  
Benoit Liquet
Keyword(s):  
Hydrological Model ◽  
Potential Evapotranspiration ◽  
River Mouth ◽  
Model Parameters ◽  
Distributed Hydrological Model ◽  
Natural Systems ◽  
Tidal Influence ◽  
Novel Approach ◽  
Spatio Temporal ◽  
Parameter Values

<p>Streamflow estimation from rain events is a delicate exercise. Watersheds are complex natural systems and their response to rainfall events is influenced by many factors. Hydrological rainfall-runoff modelling is traditionally used to understand those factors by predicting discharges from precipitation data. These models are simplified conceptualisations and thus still struggle when facing some particular processes linked to the catchment. Among those processes, the tide influence on river discharges is rarely accounted for in hydrological modelling when estimating streamflow series at river mouth areas. Instead, estimated streamflow series are sometimes corrected by coefficients to account for the tide effect.</p><p>In this presentation, we explored a semi-distributed hydrological model by adapting it to account for tidal-influence in the river mouth area. This model uses observed spatio-temporal rainfall and potential evapotranspiration databases to predict streamflow at gauged and ungauged locations within the catchment. The hydrological model is calibrated using streamflow observations and priors on parameter values to calibrate each model parameters of each sub-catchments. A drift procedure in the calibration process is used to ensure continuity in parameter values between upstream and downstream successive sub-catchments.</p><p>This novel approach was applied to a tidal-affected catchment: the Adour’s catchment in southern France. Estimated results were compared to simulations without accounting for the tidal influence. Results from the new hydrological model were improved at tidal-affected locations of the catchment. They also show similar estimations in tidal-unaffected part of the catchment.</p>

scholarly journals Assessing the benefit of snow data assimilation for runoff modelling in alpine catchments

2016 ◽  
Author(s):  
Nena Griessinger ◽  
Jan Seibert ◽  
Jan Magnusson ◽  
Tobias Jonas
Keyword(s):  
Time Series ◽  
Data Assimilation ◽  
Hydrological Model ◽  
Temperature Index ◽  
Degree Day ◽  
Index Approach ◽  
Snow Model ◽  
Alpine Catchments ◽  
Time Invariant ◽  
Snowmelt Time

Abstract. Snow models have been developed with a wide range of complexity depending on the purpose of application. In alpine catchments, snowmelt often is a major contribution to runoff; therefore, modeling snow processes is important when concerned with flood or drought forecasting, reservoir operation and inland waterway management. In this study, we address the question, whether the performance of a hydrological model can be enhanced by integrating data from a dedicated external snow monitoring system. As a framework for our tests we used the hydrological model HBV (in the version HBV light), which has been applied in many hydrological studies and is also in use for operational purposes. While HBV originally follows a temperature index approach with time-invariant calibrated degree-day factors to represent snowmelt, in this study the HBV model was modified to use snowmelt time series from an external and spatially distributed snow model as model input. The external snow model integrates three-dimensional sequential assimilation of snow monitoring data with a snowmelt model, which is also based on the temperature-index approach but uses a time-variant degree-day factor. The following three variations of this external snow model were applied: a) the full model with assimilation of observational snow data from a dense monitoring network, b) the same snow model but with data assimilation switched off, c) a downgraded version of the same snow model representing snowmelt with a time-invariant degree-day factor. Model runs were conducted for 20 catchments at different elevations within Switzerland for 15 years. Our results show that at low and mid elevations the performance of the runoff simulations did not vary considerably with the snow model version chosen. At higher elevations, however, best performance in terms of simulated runoff was obtained when using the snowmelt time series from the snow model, which utilized data assimilation. This was especially true for snow-rich years. These findings suggest that with increasing elevation and correspondingly increased contribution of snowmelt to runoff, the accurate estimation of snowmelt rates gains importance.

scholarly journals Assessing snow water equivalent of an Alpine catchment using snow dynamic model calibrated with satellite images

2008 ◽  
Vol 5 (6) ◽  
pp. 3129-3156
Author(s):  
C. Corbari ◽  
G. Ravazzani ◽  
J. Martinelli ◽  
M. Mancini
Keyword(s):  
Satellite Images ◽  
Snow Water Equivalent ◽  
Model Performance ◽  
Distributed Hydrological Model ◽  
Temperature Thresholds ◽  
Basin Scale ◽  
Snow Water ◽  
Snow Model ◽  
Height Data ◽  
Good Agreement

Abstract. This paper presents a simplified numerical model of snow dynamic implemented into a continuous distributed hydrological model for hydrograph simulations at basin scale. This snow model is based on air temperature thresholds that rule the snow melt and accumulation processes. A procedure to calibrate these temperature thresholds from NOAA satellite snow cover maps is discussed. We show that, for an accurate model calibration from satellite images, it is necessary to consider the presence of areas with complex topography such as mountain slopes. Snow model performance is tested both at local and basin scale on Alpine catchment. At local scale a good agreement between modelled snow dynamic and observed snow height data at snow gauge stations in the river Anza basin (Italy) is shown; at basin scale agreement between observed and simulated hydrographs at the discharge station of river Toce (Italy) is reported.

scholarly journals Intercomparison of different uncertainty sources in hydrological climate change projections for an alpine catchment (Clutha River, New Zealand)

2017 ◽  
Author(s):  
Andreas M. Jobst ◽  
Daniel G. Kingston ◽  
Nicolas J. Cullen ◽  
Josef Schmid
Keyword(s):  
Climate Change ◽  
Bias Correction ◽  
General Circulation ◽  
River Flow ◽  
Emission Scenario ◽  
Circulation Model ◽  
Distributed Hydrological Model ◽  
Uncertainty Sources ◽  
Snow Storage ◽  
Snow Model

Abstract. As climate change is projected to alter both temperature and precipitation, snow controlled mid-latitude catchments are expected to experience substantial shifts in their seasonal regime, which will have direct implications for water management. In order to provide authoritative projections of climate change impacts, the uncertainty inherent to all components of the modelling chain needs to be accounted for. This study assesses the uncertainty in potential impacts of climate change on the hydro-climate of New Zealand’s largest catchment (the Clutha River) using a fully distributed hydrological model (WaSiM) and unique ensemble encompassing different uncertainty sources: General Circulation Model (GCM), emission scenario, bias correction and snow model. The inclusion of snow models is particularly important, given that (1) they are a rarely considered aspect of uncertainty in hydrological modelling studies, and (2) snow has a considerable influence on seasonal patterns of river flow in alpine catchments such as the Clutha. Projected changes in river flow for the 2050s and 2090s encompass substantial increases in streamflow from May to October, and a decline between December and March. The dominant drivers are changes in the seasonal distribution of precipitation (for the 2090s +25 to +76 % in winter) and substantial decreases in the seasonal snow storage due to temperature increase. A quantitative comparison of uncertainty identified GCM structure as the dominant contributor in the seasonal streamflow signal (44–57 %) followed by emission scenario (16–49 %), bias correction (4–22 %) and snow model (3–10 %). While these findings suggest that the role of the snow model is comparatively small, its contribution to the overall uncertainty was still found to be noticeable for winter and summer.

scholarly journals Intercomparison of different uncertainty sources in hydrological climate change projections for an alpine catchment (upper Clutha River, New Zealand)

2018 ◽  
Vol 22 (6) ◽  
pp. 3125-3142 ◽  
Author(s):  
Andreas M. Jobst ◽  
Daniel G. Kingston ◽  
Nicolas J. Cullen ◽  
Josef Schmid
Keyword(s):  
Climate Change ◽  
Bias Correction ◽  
General Circulation ◽  
River Flow ◽  
Emission Scenario ◽  
Circulation Model ◽  
Distributed Hydrological Model ◽  
Uncertainty Sources ◽  
Snow Storage ◽  
Snow Model

Abstract. As climate change is projected to alter both temperature and precipitation, snow-controlled mid-latitude catchments are expected to experience substantial shifts in their seasonal regime, which will have direct implications for water management. In order to provide authoritative projections of climate change impacts, the uncertainty inherent to all components of the modelling chain needs to be accounted for. This study assesses the uncertainty in potential impacts of climate change on the hydro-climate of a headwater sub-catchment of New Zealand's largest catchment (the Clutha River) using a fully distributed hydrological model (WaSiM) and unique ensemble encompassing different uncertainty sources: general circulation model (GCM), emission scenario, bias correction and snow model. The inclusion of snow models is particularly important, given that (1) they are a rarely considered aspect of uncertainty in hydrological modelling studies, and (2) snow has a considerable influence on seasonal patterns of river flow in alpine catchments such as the Clutha. Projected changes in river flow for the 2050s and 2090s encompass substantial increases in streamflow from May to October, and a decline between December and March. The dominant drivers are changes in the seasonal distribution of precipitation (for the 2090s +29 to +84 % in winter) and substantial decreases in the seasonal snow storage due to temperature increase. A quantitative comparison of uncertainty identified GCM structure as the dominant contributor in the seasonal streamflow signal (44–57 %) followed by emission scenario (16–49 %), bias correction (4–22 %) and snow model (3–10 %). While these findings suggest that the role of the snow model is comparatively small, its contribution to the overall uncertainty was still found to be noticeable for winter and summer.

scholarly journals Modelling temperature variations in polar snow using DAISY

1997 ◽  
Vol 43 (143) ◽  
pp. 180-191 ◽  
Author(s):  
Ε. M. Morris ◽  
H. -P. Bader ◽  
P. Weilenmann
Keyword(s):  
Field Experiments ◽  
A Priori ◽  
Model Parameters ◽  
Data Set ◽  
International Geophysical Year ◽  
Snow Model ◽  
Using Data ◽  
Polar Snow ◽  
Parameter Values ◽  
The Antarctic

AbstractA physics-based snow model has been calibrated using data collected at Halley Bay, Antarctica, during the International Geophysical Year. Variations in snow temperature and density are well-simulated using values for the model parameters within the range reported from other polar field experiments. The effect of uncertainty in the parameter values on the accuracy of the predictions is no greater than the effect of instrumental error in the input data. Thus, this model can be used with parameters determined a priori rather than by optimization. The model has been validated using an independent data set from Halley Bay and then used to estimate 10 m temperatures on the Antarctic Peninsula plateau over the last half-century.

scholarly journals A Model-Based Tool for Assessing the Impact of Land Use Change Scenarios on Flood Risk in Small-Scale River Systems—Part 1: Pre-Processing of Scenario Based Flood Characteristics for the Current State of Land Use

Hydrology ◽  
2021 ◽  
Vol 8 (3) ◽  
pp. 102
Author(s):  
Frauke Kachholz ◽  
Jens Tränckner
Keyword(s):  
Land Use ◽  
River Flow ◽  
Land Use Changes ◽  
Small Rivers ◽  
Small Scale ◽  
Model Parameters ◽  
Ungauged Catchments ◽  
Model Based ◽  
Current State ◽  
The Impact

Land use changes influence the water balance and often increase surface runoff. The resulting impacts on river flow, water level, and flood should be identified beforehand in the phase of spatial planning. In two consecutive papers, we develop a model-based decision support system for quantifying the hydrological and stream hydraulic impacts of land use changes. Part 1 presents the semi-automatic set-up of physically based hydrological and hydraulic models on the basis of geodata analysis for the current state. Appropriate hydrological model parameters for ungauged catchments are derived by a transfer from a calibrated model. In the regarded lowland river basins, parameters of surface and groundwater inflow turned out to be particularly important. While the calibration delivers very good to good model results for flow (Evol =2.4%, R = 0.84, NSE = 0.84), the model performance is good to satisfactory (Evol = −9.6%, R = 0.88, NSE = 0.59) in a different river system parametrized with the transfer procedure. After transferring the concept to a larger area with various small rivers, the current state is analyzed by running simulations based on statistical rainfall scenarios. Results include watercourse section-specific capacities and excess volumes in case of flooding. The developed approach can relatively quickly generate physically reliable and spatially high-resolution results. Part 2 builds on the data generated in part 1 and presents the subsequent approach to assess hydrologic/hydrodynamic impacts of potential land use changes.

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