Earth and environmental models are relied upon to investigate system responses that cannot otherwise be examined. In simulating physical processes, models have adjustable parameters which may, or may not, have a physical meaning. Determining the values to assign to these model parameters is an enduring challenge for earth and environmental modellers. Selecting different error metrics by which the models results are compared to observations will lead to different sets of calibrated model parameters, and thus different model results. Furthermore, models may exhibit ‘equifinal’ behaviour, where multiple combinations of model parameters lead to equally acceptable model performance against observations. These decisions in model calibration introduce uncertainty that must be considered when model results are used to inform environmental decision-making. This presentation focusses on the uncertainties that derive from the calibration of a four parameter lumped catchment hydrological model (GR4J). The GR models contain an inbuilt automatic calibration algorithm that can satisfactorily calibrate against four error metrics in only a few seconds. However, a single, deterministic model result does not provide information on parameter uncertainty. Furthermore, a modeller interested in extreme events, such as droughts, may wish to calibrate against more low flows specific error metrics. In a comprehensive assessment, the GR4J model has been run with 500,000 Latin Hypercube Sampled parameter sets across 303 catchments in the United Kingdom. These parameter sets have been assessed against six error metrics, including two drought specific metrics. This presentation compares the two approaches, and demonstrates that the inbuilt automatic calibration can outperform the Latin Hypercube experiment approach in single metric assessed performance. However, it is also shown that there are many merits of the more comprehensive assessment, which allows for probabilistic model results, multi-objective optimisation, and better tailoring to calibrate the model for specific applications such as drought event characterisation. Modellers and decision-makers may be constrained in their choice of calibration method, so it is important that they recognise the strengths and limitations of their chosen approach.

Intermittent rivers are prevalent in many countries across Europe and in Mediterranean countries outside Europe, but little is known about the temporal evolution of intermittency characteristics and their relationships with climate variability. In this study, a trend analysis is performed on the annual and seasonal number of zero-flow days, the maximum duration of dry spells and the mean date of the zero-flow events, on a database of 452 rivers in European and in Mediterranean countries outside Europe, with varying degrees of intermittence. In addition, the relationships between flow intermittence and climate are investigated using the Standardized Precipitation Evapotranspiration Index (SPEI) and six climate indices describing large scale atmospheric circulation. Results indicated a strong spatial variability of the seasonal patterns of intermittence and the annual and seasonal number of zero-flow days, which highlights the controls exerted by local catchment properties. Most of the detected trends indicate an increasing number of zero-flow days which also tend to occur earlier in the year, in particular in Southern Europe. The SPEI is found to be strongly related to the annual and seasonal zero-flow day occurrence in more than half of the stations for different accumulation times between 12 and 24 months. Conversely, there is a weak dependence of river intermittence with large-scale circulation indices. Overall, these results suggest increased water stress in intermittent rivers that may affect their biota and biochemistry and also reduce available water resources.