4.7 Article

A retrospective on hydrological catchment modelling based on half a century with the HBV model

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HYDROLOGY AND EARTH SYSTEM SCIENCES
卷 26, 期 5, 页码 1371-1388

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COPERNICUS GESELLSCHAFT MBH
DOI: 10.5194/hess-26-1371-2022

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Hydrological catchment models are important tools for water resource management planning. Although computer capabilities have greatly increased, some relatively simple models are still widely used. The HBV model, first applied in Sweden 50 years ago, is a typical example of a conceptual catchment model. The history of model development, from consideration of different model structures to studies using numerous catchments and cloud computing facilities, is described, and the wide range of model applications is discussed.
Hydrological catchment models are important tools that are commonly used as the basis for water resource management planning. In the 1960s and 1970s, the development of several relatively simple models to simulate catchment runoff started, and a number of so-called conceptual (or bucket-type) models were suggested. In these models, the complex and heterogeneous hydrological processes in a catchment are represented by a limited number of storage elements and the fluxes between them. While computer limitations were a major motivation for such relatively simple models in the early days, some of these models are still used frequently despite the vast increase in computational opportunities. The HBV (Hydrologiska Byrans Vattenbal-ansavdelning) model, which was first applied about 50 years ago in Sweden, is a typical example of a conceptual catchment model and has gained large popularity since its inception. During several model intercomparisons, the HBV model performed well despite (or because of) its relatively simple model structure. Here, the history of model development, from thoughtful considerations of different model structures to modelling studies using hundreds of catchments and cloud computing facilities, is described. Furthermore, the wide range of model applications is discussed. The aim is to provide an understanding of the background of model development and a basis for addressing the balance between model complexity and data availability that will also face hydrologists in the coming decades.

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