Analysis of Daily Rainfall and Spatiotemporal Trends of Extreme Rainfall at Paraná Slope of the Itararé Watershed, Brazil

Abstract

The knowledge of intensity and frequency of rainfall allows establishing predictive measures to minimize impacts caused by high volume of rainfall totals in a region. Therefore, the objective is to evaluate daily rainfall for Paraná slope of the Itararé watershed (PSIW) and to verify the spatiotemporal trend of intense and extreme daily rainfall. Rainfall data from 14 stations collected from 1976 to 2012 were used with less than 4% of data faults. Multivariate analysis based on cluster analysis technique (CA) was used applying the Euclidean distance for the identification of homogeneous groups, and the quantiles technique to classify daily rainfall. The Mann-Kendall (MK) test was used to identify trends for annual rainfall totals, annual number of rainy days (ANRD) and for the occurrence of intense (R95p) and extreme (R99p) rainfall. The CA technique identified three rainfall groups (HG I, II and III). Given the latitudinal position of the area, rainfall at the southern sector is characterized by its greater similarities with the subtropical climate, whereas in the North sector there is a consistent reduction of rainfall totals in autumn and, especially, during winter months, which are characteristic of the tropical climate. The MK test identified the downward trend of ANRD, with greater significance for the south-centered sectors of the basin. The observed trends for the intense (R95p) and extreme (R99p) daily rainfall show the predominance of reduction for the Southwest and central sector, followed by a significant increase in the Southeast and North sectors of the PSIW.

Spatiotemporal analysis of drought and rainfall in Pakistan via Standardized Precipitation Index: homogeneous regions, trend, wavelet, and influence of El Niño-southern oscillation

“…Homogeneous groups were used for all of the coefficients of variation (CVs, %) below 100%. Thus, except for two seasons (ID 24 = 108.52 per cent and ID 25 = 102.49 per cent), all-time series data in group G1 were homogeneous (Wilks 2011;Gois et al 2020). In contrast to the other groups, the G1 group had a larger prevalence of negative lower bounds in the exploratory statistics of yearly rainfall data at 21 sites.…”

“…It is noteworthy that the MK test is the most appropriate method for locating and approximately detecting the starting point of a given trend, being the most suitable method for analyzing climate change in time series (Gois et al 2020;Terassi et al 2020). The non-significant increase in the magnitude of rainfall in Pakistan, according to Sen's method, was recorded mainly in homogeneous groups G2, G3 and G4, the exception being group G1 (Table 5).…”

“…. The nonparametric statistical tests of MK and Pettitt are the most critical instruments in time series analysis (Gois et al 2020). The years 1998 (El Niño powerful) were found using the Pettitt test, indicating a 17-fold occurrence -( who identified 1987, 1991, 2000, 2001, 2002, and 2005 from the crossover of information between the SPI and the Single Z-Index.…”

“…The Standardized Precipitation Index (SPI), which uses solely rain as an input, is the most often used index in the scientific literature for drought identification (McKee et al 1993), which is a consensus among several experts (Mishra and Singh 2010;Zagar et al 2011;Oliveira Júnior et al 2012;Khan and Gadiwala 2013;Kim et al 2014;Lyra et al 2017;Terassi et al 2020;Oliveira-Júnior et al 2021). The World Meteorological Organization (WMO) -( WMO 2021) has recognized the SPI as a reliable tool for monitoring meteorological droughts.…”

Long-term changes in precipitation in the eastern portion of the Guanabara Bay hydrographic region, Rio de Janeiro, Brazil

“…Rainfall is a fundamental element of climate which for supporting planning and territorial management [1,2]. Changes in precipitation extremes and characteristics at both regional and global scales due to climate change and variability need to be investigated [3,4].…”