Article

Uncertainty and multiple objective calibration in regional water balance modelling: case study in 320 Austrian catchments

Institute for Hydraulic and Water Resources Engineering, Vienna University of Technology, Karlsplatz 13/222, A-1040 Vienna, Austria
Hydrological Processes (Impact Factor: 2.5). 02/2007; 21(4):435 - 446. DOI: 10.1002/hyp.6253

ABSTRACT 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.

0 Bookmarks
 · 
53 Views
  • Source
    [Show abstract] [Hide abstract]
    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.
    Water Resources Research. 04/2014;
  • Source
    [Show abstract] [Hide abstract]
    ABSTRACT: A "Holy Grail" of hydrology is to understand catchment processes well enough that models can provide detailed simulations across a variety of hydrologic settings at multiple spatio-temporal scales, and under changing environmental conditions. Clearly, this cannot be achieved only through intensive place-based investigation at a small number of heavily instrumented catchments, or by regionalization methods that do not fully exploit our understanding of hydrology. Here, we discuss the need to actively promote and pursue the use of a "large catchment sample" approach to modeling the rainfall-runoff process, thereby balancing depth with breadth. We examine the history of such investigations, discuss the benefits (improved process understanding resulting in robustness of prediction at ungaged locations and under change), examine some practical challenges to implementation and, finally, provide perspectives on issues that need to be taken into account as we move forward. Ultimately, our objective is to provoke further discussion and participation, and to promote a potentially important theme for the upcoming IAHS Scientific Decade entitled "Panta Rhei".
    Hydrology and Earth System Sciences Discussions 07/2013; 10(7):9147-9189. · 3.59 Impact Factor
  • Source
    [Show abstract] [Hide abstract]
    ABSTRACT: Conceptual environmental systems models, such as rainfall runoff models, generally rely on calibration for parameter identification. Increasing complexity of this type of model for better representation of hydrological process heterogeneity typically makes parameter identification more difficult. Although various, potentially valuable, strategies for better parameter identification were developed in the past, strategies to impose general conceptual understanding regarding how a catchment works into the process of parameterizing a conceptual model has still not been fully explored. In this study we assess the effect of imposing semi-quantitative, relational expert knowledge into the model development and parameter selection, efficiently exploiting the complexity of a semi-distributed model formulation. Making use of a topography driven rainfall-runoff modeling (FLEX-TOPO) approach, a catchment was delineated into three functional units, i.e. wetland, hillslope and plateau. Ranging from simplicity to complexity, three model set-ups, FLEXA, FLEXB and FLEXC have been developed based on these functional units. While FLEXA is a lumped representation of the study catchment, the semi-distributed formulations FLEXB and FLEXC introduce increasingly more complexity by distinguishing 2 and 3 functional units, respectively. In spite of increased complexity, FLEXB and FLEXC allow modelers to compare parameters as well as states and fluxes of their different functional units to each other. Based on these comparisons, expert knowledge based, semi-quantitative relational constraints have been imposed on three models structures. More complexity of models allows more imposed constraints. It was shown that a constrained but uncalibrated semi-distributed model, FLEXC, can predict runoff with similar performance than a calibrated lumped model, FLEXA. In addition, when constrained and calibrated, the semi-distributed model FLEXC exhibits not only higher performance but also reduced uncertainty for prediction, compared to the calibrated, lumped FLEXA model.
    Hydrology and Earth System Sciences Discussions 12/2013; 10(12):14801-14855. · 3.59 Impact Factor

Full-text (2 Sources)

Download
85 Downloads
Available from
Jun 5, 2014