A Spatiotemporal Classification of the Peruvian Precipitations Between 1990 and 2015
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Pure and Applied Geophysics
A Spatiotemporal Classification of the Peruvian Precipitations Between 1990 and 2015 BABAK VAHEDDOOST1 Abstract—Precipitation and its variations have great importance in water resource management and sustainable development. In this study, the Peruvian precipitations between January 1990 to October 2015, were used. The precipitations were classified under spatial, temporal, and spatiotemporal classes. For this aim, properties of the precipitation time series including the monthly mean, monthly standard deviation, and principal components at monthly and annual scale were evaluated. Results were projected on a map using the Kriging method. Later, the double mass curves of the monthly precipitation time series were used to classify the temporal changes in the precipitations. Thereafter, the Spearman rank-order correlation was used to evaluate the spatiotemporal changes in monthly and annual precipitation time series by projected t-values on the Peruvian map. Finally, precipitations time series were plotted against Ko¨ppen–Geiger climate class of each station and several large scale oscillations namely North Atlantic Oscillation (NAO), El Nin˜o/Southern Oscillation (ENSO), Atlantic Multidecadal Oscillation (AMO), and Pacific Decadal Oscillation (PDO) simultaneously. It was concluded that there are at least three major climatic regions in the country. Spatial classes, depicts that the Andes Ranges is a major role player in the climate of the country while the ENSO and PDO are the main drivers of the precipitation extremes. Results also indicated to an ascending changes in the amount of precipitation from west to east, while a descending changes were observed at Amazon forest near San Ramon. Keywords: Classification, oscillation.
climate,
Peru,
large
scale
1. Introduction Studying the long-term hydro-meteorological parameters is of the great importance in sustainable development and water resource planning. In this regard, precipitation is the cornerstone in defining the renewable water and sustainability analysis (Gocic and Trajkovic 2013). Hence, many socio-economical, hydrological, and decision support choices can be
1
Department of Civil Engineering, Bursa Technical University, Bursa, Turkey. E-mail: [email protected]
linked to the temporal and spatial changes in the precipitation patterns. For instance, Vaheddoost and Aksoy (2017) evaluated the structural characteristics of annual precipitation in the Lake Urmia region to investigate the role of precipitation on Lake Urmia. Several statistical properties such as mean, standard deviation, kurtosis, skewness, etc., of the annual precipitation time series, were used and projected on the map. It was concluded that the precipitation patterns vary across time and space whilst the local terrain has a great effect on the emerged patterns. Similarly, conducted studies on the properties of the precipitation time series (e.g. Nourani et al. 2018; Akkoyunlu et al. 2019; Bohlinger et al. 2019; Nourani and Farboudfam 2019; Teegavarapu
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