A stochastic model for drought risk analysis in The Netherlands

Abstract. Population growth and economic developments increase the demand for water resources. Furthermore, climate change is often projected to have negative impacts on the availability of these water resources. Measures to reduce the risk of water shortages can be costly and often require long-term planning strategies. In the decision making process, a thorough understanding of these drought-related risks for the various water users is of crucial importance. Historic time series of climatologic and hydrological variables, used as input for water allocation and drought impact models, are generally too short to provide such a detailed understanding. This makes the case for using lengthy synthetic time series. The challenge is to develop synthetic time series that are realistic and representative for the current and future climate conditions. We present a stochastic model for generating realistic times series of meteorological and hydrological variables that characterise drought events. The model is applied to a case study in the Netherlands, but is generic in set-up and can thus be applied elsewhere as well. It is demonstrated that the main features of the historic time series are well reproduced. The generated synthetic times series provide valuable insights into the frequency and severity of droughts and help improve the assessment of drought risks.