Combined predictive and descriptive tests for extreme rainfall probability distribution selection

Author(s)

Ballarin, Andre S. ; Calixto, Kalyl G. ; Anache, Jamil A. A. ; Wendland, Edson

• Document type: Journal article
• Source: HYDROLOGICAL SCIENCES JOURNAL-JOURNAL DES SCIENCES HYDROLOGIQUES; v. 67, n. 7, p. 11-pg., 2022-05-07.

Abstract

The popular approach to select a suitable distribution to characterize extreme rainfall events relies on the assessment of its descriptive performance. This study examines an alternative approach to this task that evaluates, in addition to the descriptive performance of the models, their performance in estimating out-of-sample events (predictive performance). With a numerical experiment and a study case in Sao Paulo state, Brazil, we evaluated the adequacy of seven probability distributions widely used in hydrological analysis to characterize extreme events in the region and compared the selection process of both popular and altenative frameworks. The results indicate that (1) the popular approach is not capable of selecting distributions with good predictive performance and (2) combining different predictive and descriptive tests can improve the reliability of extreme event prediction. The proposed framework allowed the assessment of model suitability from a regional perspective, identifying the Generalized Extreme Value (GEV) distribution as the most adequate to characterize extreme rainfall events in the region. (AU)

• FAPESP's process: 15/03806-1 - Water availability and quality threats in a Guarani Aquifer System outcrop zone
• Grantee: Edson Cezar Wendland
• Support Opportunities: Program for Research on Bioenergy (BIOEN) - Thematic Grants
• FAPESP's process: 20/08140-0 - Extreme events in a climate change context: characterization based on climate model and nonstationarity
• Grantee: André Simões Ballarin
• Support Opportunities: Scholarships in Brazil - Doctorate