Techniques for monthly rainfall regionalization in southwestern Colombia.

An Acad Bras Cienc

Universidad del Valle, Grupo de Investigación Percepción y Sistemas Inteligentes (PSI), Escuela de Ingeniería Eléctrica y Electrónica, Calle 13, No. 100-00, Campus Meléndez, Cali, Colombia.

Published: July 2022

AI Article Synopsis

  • Understanding rainfall patterns is crucial for water management, risk management, and agriculture in regions like Southwestern Colombia.
  • The study validated four techniques to identify homogeneous rainfall regions, using monthly rainfall data from Nariño, a complex area.
  • Findings indicated that non-linear methods, especially principal component analysis and self-organizing maps, were most effective, revealing distinct rainfall regimes in the Andean (bimodal) and Pacific (unimodal) regions.

Article Abstract

The knowledge of rainfall regimes is a relevant requirement for many activities such as water resources planning, risk management, agriculture activities management, and other hydrologic applications. The present study has consisted of validating four techniques (one linear, one non-linear, and two hybrids) that allow identifying homogenous regions. We take the monthly rainfall in the Southwestern Colombia (Nariño), an area of 33,268 km2 characterized by complex topography and local factors that can influence the rainfall behavior, to test all techniques. The results showed overall the best performance for the approach related to non-linear principal component analysis and self-organizing map. However, in all mainly prevail two regions: the Andean Region and Pacific Region with a bimodal and unimodal regime, respectively. The bimodal one dominates over the Andes mountains range and the unimodal one the coastal zone. The application of non-linear approaches provided a better understanding of the seasonality of rainfall, and the results may be useful for water resource management.

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Source
http://dx.doi.org/10.1590/0001-3765202220201000DOI Listing

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