Abstract
Abstract. The calibration of stochastic point process rainfall models, such as of the Bartlett-Lewis type, suffers from the presence of multiple local minima which local search algorithms usually fail to avoid. To meet this shortcoming, four relatively new global optimization methods are presented and tested for their ability to calibrate the Modified Bartlett-Lewis Model. The list of tested methods consists of: the Downhill Simplex Method, Simplex-Simulated Annealing, Particle Swarm Optimization and Shuffled Complex Evolution. The parameters of these algorithms are first optimized to ensure optimal performance, after which they are used for calibration of the Modified Bartlett-Lewis model. Furthermore, this paper addresses the choice of weights in the objective function. Three alternative weighing methods are compared to determine whether or not simulation results (obtained after calibration with the best optimization method) are influenced by the choice of weights.
Highlights
Rainfall is an important input for many models in various branches of applied sciences
This paper proposes to use relatively new optimization methods as they are expected to be more robust than more traditional local search methods
In the Modified BL (MBL) model, the average cell duration is allowed to vary between storms
Summary
Rainfall is an important input for many models in various branches of applied sciences. Certain applications (such as design studies) require very long time series which are not available from observations (Wheater et al, 2006) To circumvent this problem, one can make use of rainfall models (Boughton and Droop, 2003). To fit the model to a series of observations, the generalized method of moments is used In this method, the model is fitted to observed sample properties of rainfall intensity at different aggregation levels. Three different approaches to the weighing of the objective function are compared in order to shed some light on their advantages and disadvantages in terms of model performance and practicality For these purposes, data recorded at the Uccle-site of the Royal Meteorological Institute (RMI) in Brussels (Belgium), are used. The data set consists of 105 yr of recorded rainfall at an aggregation level of 10 min (De Jongh et al, 2006)
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