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Theoretical and Applied Climatology

, Volume 129, Issue 3–4, pp 1295–1307 | Cite as

Regional maximum rainfall analysis using L-moments at the Titicaca Lake drainage, Peru

  • Carlos Antonio Fernández-PalominoEmail author
  • Waldo Sven Lavado-Casimiro
Original Paper
  • 240 Downloads

Abstract

The present study investigates the application of the index flood L-moments-based regional frequency analysis procedure (RFA-LM) to the annual maximum 24-h rainfall (AM) of 33 rainfall gauge stations (RGs) to estimate rainfall quantiles at the Titicaca Lake drainage (TL). The study region was chosen because it is characterised by common floods that affect agricultural production and infrastructure. First, detailed quality analyses and verification of the RFA-LM assumptions were conducted. For this purpose, different tests for outlier verification, homogeneity, stationarity, and serial independence were employed. Then, the application of RFA-LM procedure allowed us to consider the TL as a single, hydrologically homogeneous region, in terms of its maximum rainfall frequency. That is, this region can be modelled by a generalised normal (GNO) distribution, chosen according to the Z test for goodness-of-fit, L-moments (LM) ratio diagram, and an additional evaluation of the precision of the regional growth curve. Due to the low density of RG in the TL, it was important to produce maps of the AM design quantiles estimated using RFA-LM. Therefore, the ordinary Kriging interpolation (OK) technique was used. These maps will be a useful tool for determining the different AM quantiles at any point of interest for hydrologists in the region.

Keywords

Return Period Annual Maximum Ordinary Kriging Generalise Extreme Value Generalise Extreme Value Distribution 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

Notes

Acknowledgments

This study was possible because of the availability (to the scientific community) of various free software packages of statistical software R, particularly, the lmomRFA package for RFA-LM and the gstat package for spatial geo-statistical modelling. Moreover, we thanks the SNF project DECADE by supporting this publication.

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Copyright information

© Springer-Verlag Wien 2016

Authors and Affiliations

  • Carlos Antonio Fernández-Palomino
    • 1
    Email author
  • Waldo Sven Lavado-Casimiro
    • 1
  1. 1.Servicio Nacional de Meteorología e Hidrología del Perú (SENAMHI)LimaPeru

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