The calibration objective in the large scale applications is not to provide an optimal model for a specific region, but rather to identify a model that averages performance across a group of basins.
Arctic -HYPE was calibrated and evaluated, with respect to monthly discharge, in a multi-basin approach. Model structure and parameters were initially adopted from the Swedish and Pan-European applications of HYPE and updated in a step-wise calibration procedure starting with parameters governing accumulation and melt of snow, glaciers and evapotranspiration using in-situ data on snow, glaciers and actual evapotranspiration. Data sets originated from Former Soviet Union snow course data (nsidc.org), World Glacier Monitoring Service (wgms.ch) and FluxNet (fluxnet.ornl.gov), respectively. The hydrological response of all land use classes and soil type classes in the model, including parameters for evapotranspiration, infiltration and runoff was calibrated using upstream discharge data from sub-basins without so-called outlet lakes (lakes on the main stream). Lake discharge parameters were calibrated separately for 4 classes of internal lakes (lakes not on the main stream) and 3 classes of outlet lakes, using river discharge data in upstream areas without outlet lakes and river discharge data downstream of outlet lakes, respectively. The model performance was evaluated for the Arctic HYCOS flow-to-ocean and upstream discharge stations.
Different performance criteria are used here to define the performance of the model towards the observed discharge. The criteria presented here investigate the relative adequacy of the model with regard to timing, variability and volume error. In here, we present model performance at different stations in terms of the Nash-Sutcliffe Efficiency (NSE; Nash and Sutcliffe, 1970), the correlation coefficient, the relative error in mean, the relative error in standard deviation, and Kling-Gupta Efficiency (KGE; Gupta et al., 2009). The optimum value for each criterion (describing a perfect model) is not the same; NSE, KGE and correlation coefficient have optimum value at 1, while the remaining relative error based criteria have optimum value at 0.
The colour of the circle corresponds to a range of model performance, which segments are presented at the histogram plot; depicting the number of stations that have performance within each segment.
The overall model performance in terms of mean annual discharge is presented in the “Simulated versus observed river discharge” plot. A perfect agreement between simulated and observed mean annual discharge would correspond to dots lying on the red 1:1 line. The user can click on a specific dot in the graph, and the selected station will appear in the map. The user can further select one of the “evaluation criteria” and the histogram is automatically updated for the selected criterion. Additional information for individual stations can be presented by Selection of individual stations (simply by left-clicking a circle) would provide additional information about the station (name and upstream area) and basic flow characteristics, i.e. simulated and observed mean discharge.
Nash, J. E., & Sutcliffe, J. V. (1970). River flow forecasting through conceptual models. Journal of Hydrology, 10, 282–290.
Gupta, H. V., Kling, H., Yilmaz, K. K., & Martinez, G. F. (2009). Decomposition of the mean squared error and NSE performance criteria: Implications for improving hydrological modelling. Journal of Hydrology, 377(1-2), 80–91. doi:10.1016/j.jhydrol.2009.08.003