Hydrological models are mediating models

Abstract

Despite the increasing role of models in hydrological research and decision-making processes, only few accounts of the nature and function of models exist in hydrology. Earlier considerations have traditionally been conducted while making a clear distinction between physically-based and conceptual models. A new philosophical account, primarily based on the fields of physics and economics, transcends classes of models and scientific disciplines by considering models as "mediators" between theory and observations. The core of this approach lies in identifying models as (1) being only partially dependent on theory and observations, (2) integrating non-deductive elements in their construction, and (3) carrying the role of instruments of scientific enquiry about both theory and the world. The applicability of this approach to hydrology is evaluated in the present article. Three widely used hydrological models, each showing a different degree of apparent physicality, are confronted to the main characteristics of the "mediating models" concept. We argue that irrespective of their kind, hydrological models depend on both theory and observations, rather than merely on one of these two domains. Their construction is additionally involving a large number of miscellaneous, external ingredients, such as past experiences, model objectives, knowledge and preferences of the modeller, as well as hardware and software resources. We show that hydrological models convey the role of instruments in scientific practice by mediating between theory and the world. It results from these considerations that the traditional distinction between physically-based and conceptual models is necessarily too simplistic and refers at best to the stage at which theory and observations are steering model construction. The large variety of ingredients involved in model construction would deserve closer attention, for being rarely explicitly presented in peer-reviewed literature. We believe that devoting more importance to identifying and communicating on the many factors involved in model development might increase transparency of model building

Enhancing hydrological model calibration through hybrid strategies in data‐scarce regions

“…This allows users to analyse phenomena at basin, regional, and global scales that are in synchronous with the hydrological systems. (Babel & Karssenberg, 2013; Singh et al, 2020; Tessema, 2011). Hydrological modelling is a useful tool for various purposes such as water resources planning and management but it is always a challenging task to carry out hydrological modelling in a data‐scarce region due to the deficit in quantity and quality of data.…”