Drivers of hydrological model diversity and model selection factors - The example of Switzerland.

Hydrological models are fundamental tools that play a key role in many areas of hydrological science and climate change impact studies. However, it is well known that the number of models has increased beyond what is necessary. One of the key drivers for model diversity in hydrology is the wide range of model applications, motivated by specific needs and contexts that require suitable models. Yet, a significant part of this diversity is not driven by the context, as different models are applied under analogue circumstances.

To better understand the main drivers of model diversity, a review of hydrological modelling habits was conducted on studies carried out in Switzerland. Despite being a small country, Switzerland has a variety of hydro-climatological regimes, water resource management challenges, and hydrological research institutes, and can thus be representative of other regions. A first observation was that the motivations for selecting a model are rarely stated in scientific articles, and the adequacy of the model for the context or landscape is often not addressed. Thus, a survey was conducted to evaluate some subjective aspects that are otherwise difficult to retrieve from the scientific literature.

Not surprisingly, researchers are very keen on using a model developed at their own institute, which provides the benefit of expertise and efficiency, but at increased risk of context inadequacy and automatism in decisions. Other aspects were considered relevant in the model selection process, such as – indeed – adequacy, access to the code, reuse of existing model setups, collaborations, technical constraints or data availability.

Several hydrological models exist in Switzerland, while the vast majority of the studies were conducted using a single model. To some extent, model diversity is desirable to assess model variability, but multi-model applications to harness this diversity are largely missing. The survey could highlight that most researchers consider multi-model approaches important, but most do not apply them for various practical reasons, such as lack of resources (time and/or money) or lack of expertise in another model. We believe that some barriers can be lowered to facilitate multi-model approaches, requiring efforts from the modelling community and the funding agencies.