Uncertainty and multiple objective calibration in regional water balance modeling – Case study in 320 Austrian catchments

Institute of Hydraulic Engineering and Water Resources Management, Vienna University of Technology, Wien, Vienna, Austria
Hydrological Processes (Impact Factor: 2.68). 02/2007; 21(4):435 - 446. DOI: 10.1002/hyp.6253


We examine the value of additional information in multiple objective calibration in terms of model performance and parameter uncertainty. We calibrate and validate a semi-distributed conceptual catchment model for two 11-year periods in 320 Austrian catchments and test three approaches of parameter calibration: (a) traditional single objective calibration (SINGLE) on daily runoff; (b) multiple objective calibration (MULTI) using daily runoff and snow cover data; (c) multiple objective calibration (APRIORI) that incorporates an a priori expert guess about the parameter distribution as additional information to runoff and snow cover data. Results indicate that the MULTI approach performs slightly poorer than the SINGLE approach in terms of runoff simulations, but significantly better in terms of snow cover simulations. The APRIORI approach is essentially as good as the SINGLE approach in terms of runoff simulations but is slightly poorer than the MULTI approach in terms of snow cover simulations. An analysis of the parameter uncertainty indicates that the MULTI approach significantly decreases the uncertainty of the model parameters related to snow processes but does not decrease the uncertainty of other model parameters as compared to the SINGLE case. The APRIORI approach tends to decrease the uncertainty of all model parameters as compared to the SINGLE case. Copyright © 2006 John Wiley & Sons, Ltd.

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Available from: Juraj Parajka, Oct 09, 2015
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    • "Once these relationships are established for available gauged catchments, the values of the hydrologic model parameters in ungauged catchments can be estimated based on its physical/climatic characteristics. Strategies based on parameter regionalization have been criticized for ignoring the covariances among model parameter estimates (McIntyre et al., 2005; Bárdossy, 2007; Parajka et al., 2007; Oudin et al., 2008), and are restricted due to parameter identifiability issues (Beven and Freer, 2001) and model structural error (Wagener and Wheater, 2006). (ii) Constraining hydrologic model simulations by regionalized signatures – When regionalizing model parameters, one is invariably faced with problems such as the equifinality of 0022-1694/Ó 2014 Elsevier B.V. All rights reserved. "
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    ABSTRACT: Large uncertainties in streamflow projections derived from downscaled climate projections of precipitation and temperature can render such simulations of limited value for decision making in the context of water resources management. New approaches are being sought to provide decision makers with robust information in the face of such large uncertainties. We present an alternative approach that starts with the stakeholder's definition of vulnerable ranges for relevant hydrologic indicators. Then, the modeled system is analyzed to assess under what conditions these thresholds are exceeded. The space of possible climates and land use combinations for a watershed is explored to isolate sub-spaces that lead to vulnerability, while considering model parameter uncertainty in the analysis. We implement this concept using classification and regression trees (CART) that separate the input space of climate and land use change into those combinations that lead to vulnerability and those that do not. We test our method in a Pennsylvania watershed for nine ecological and water resources related streamflow indicators for which an increase in temperature between 3°C to 6 °C and change in precipitation between -17% and 19% is projected. Our approach provides several new insights, for example we show that even small decreases in precipitation (~5%) combined with temperature increases greater than 2.5ºC can push the mean annual runoff into a slightly vulnerable regime. Using this impact and stakeholder driven strategy, we explore the decision-relevant space more fully and provide information to the decision maker even if climate change projections are ambiguous.
    04/2014; 50(4). DOI:10.1002/2013WR014988
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    • "Thus, it was necessary to proceed with a modeling strategy (i) economic (i.e., provide the largest number of evaluations with the smallest number of model runs), (ii) effective (i.e., investigate the domain of existence of parameters as extensively as possible), and (iii) independent of modeler subjectivity. Considering (i) the large number of factors chosen to investigate (12), (ii) the quantitative and conceptual nature of factors, (iii) the computational power available limited to simple desktop machines, and hence (iv) the computational cost of every single run in both reaches (i.e., in reach A, but also in reach B), we discarded both the application of Monte Carlo techniques and other automatic calibration procedures well known in hydraulics [Fabio et al., 2010; Dung et al., 2011] and hydrological modeling [Engeland et al., 2006; Van Griensven et al., 2006; Parajka et al., 2007]. Therefore, we decided to adopt a more computationally sustainable two-step sensitivity analysis [Campolongo et al., 1999] followed by manual calibration and validation (Figure 3). "
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    Journal of Geophysical Research: Earth Surface 12/2013; 118(4). DOI:10.1002/jgrf.20154 · 3.44 Impact Factor
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    • "Elevations range from 310 to 3800 m. Mean annual precipitation ranges from 600 to more than 2000 mm yr −1 , resulting in mean annual runoff depths from 100 to 1600 mm yr −1 (Parajka et al., 2007; Nester et al., 2011). The Bavarian Danube and the Inn join at Passau. "
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    ABSTRACT: The June 2013 flood in the Upper Danube Basin was one of the largest floods in the past two centuries. An atmospheric blocking situation produced precipitation exceeding 300 mm over four days at the northern rim of the Alps. The high precipitation, along with high antecedent soil moisture, gave rise to extreme flood discharges in a number of tributaries including the Tiroler Ache, Saalach, Salzach and Inn. Runoff coefficients ranged from 0.2 in the Bavar-ian lowlands to 0.6 in the Alpine areas in Austria. Snow-fall at high altitudes (above about 1600 m a.s.l.) reduced the runoff volume produced. Precipitation was distributed over two blocks separated by a few hours, which resulted in a single peak, long-duration flood wave at the Inn and Danube. At the confluence of the Bavarian Danube and the Inn, the small time lag between the two flood waves exacerbated the downstream flood at the Danube. Because of the long dura-tion and less inundation, there was less flood peak attenu-ation along the Austrian Danube reach than for the August 2002 flood. Maximum flood discharges of the Danube at Vienna were about 11 000 m 3 s^−1 , as compared to 10 300, 9600 and 10 500 m 3 s^−1 in 2002, 1954 and 1899, respectively. This paper reviews the meteorological and hydrological charac-teristics of the event as compared to the 2002, 1954 and 1899 floods, and discusses the implications for hydrological research and flood risk management.
    Hydrology and Earth System Sciences 12/2013; 17(12):5197-5212. DOI:10.5194/hess-17-5197-2013 · 3.54 Impact Factor
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