Abstract

Here we report a study of the temporal variation in daily rainfall recorded at meteorological stations in the state of Pernambuco, Brazil using the method of lacunarity to evaluate dry spell distribution. Results indicate coastal region rainfall has lower lacunarity and shows a more homogeneous behaviour with respect to dry spell duration. In the semiarid and dry regions rainfall series demonstrate higher lacunarity, indicating more complex behaviour and greater variation in dry spell duration. We show that clustering based on calculated lacunarity values can be used to identify geographical regions with characteristic temporal variability in rainfall pattern. For Pernambuco, three distinct spatial patterns were identified: one in the Zona de Mata , another in southern Agreste and Sertao Pernambucano , and third in Sertao Sao Francisco and the northern part of Agreste .

Highlights

  • IntroductionHydrological processes (rainfall, streamflow, evaporation, infiltration, etc.) are characterised by nonlinearity and high levels of complexity (Sivakumar & Singh, 2012)

  • Hydrological processes are characterised by nonlinearity and high levels of complexity (Sivakumar & Singh, 2012)

  • Highest averages occurred in the coastal region, while lowest averages occured for meteorological stations located in Sertão and Agreste Setentrional regions (Figure 3b)

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Summary

Introduction

Hydrological processes (rainfall, streamflow, evaporation, infiltration, etc.) are characterised by nonlinearity and high levels of complexity (Sivakumar & Singh, 2012). The complexity of hydrological processes has been extensively studied over the last decades, using classical statistical methods (Espinoza-Villar et al, 2009; Santos, Pulido-Calvo, & Portela, 2010), chaos theory (Jayawardena & Lai, 1994; Sivakumar, 2001), fractals (Li & Zhang, 2007), multifractals (Tessier, Lovejoy, Hubert, Schertzer, & Pecknold, 1996; Kantelhardt et al, 2006) and information theory (Li & Zhang, 2008; Mishra, Özger, & Singh, 2009; Zhang & Singh, 2012). Understanding the spatiotemporal variation in rainfall is crucial for the development of planning and management strategies for rational and sustainable water resource use in river basins

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