scholarly journals A new regionalization of rainfall patterns based on wavelet transform information and hierarchical cluster analysis in northeastern Algeria

Author(s):  
Bilel Zerouali ◽  
Mohamed Chettih ◽  
Zaki Abda ◽  
Mohamed Mesbah ◽  
Celso Augusto Guimarães Santos ◽  
...  
2021 ◽  
Author(s):  
Bilel Zerouali ◽  
Mohamed Chettih ◽  
Zaki Abda ◽  
Mohamed Mesbah ◽  
Celso Augusto Guimarães santos ◽  
...  

Abstract Due to its geographical location, Algeria is characterized by high spatiotemporal rainfall variability. In this study, data from 69 rain gauges located in representative humid, semiarid and arid Mediterranean basins in northeastern Algeria were analyzed from 1970–2007 on a monthly scale using continuous wavelet analysis and hierarchical cluster analysis with the aim of regionalizing the rainfall patterns. The analysis shows that northern Algeria (cluster #1), which has a humid climate, is dominated by periodic annual fluctuations in the 8–16-month band. This mode explains most of the total variance, with a contribution between 25 and 60%. In the cluster #2 and cluster #3 regions, the climate varies towards aridity (humid to arid from north to south), and the climate is dominated by long-term periodic phenomena characterizing multiannual fluctuations of 64–128 months to decadal periods greater than 128 months, which explains why the total cumulative contribution exceeds 50% of the total variance. In addition, the regional analysis of the isolated spectral bands of the 3–6-month (3 clusters), 8–16-month (3 clusters), and 1–3-year (4 clusters) scale-average variance revealed, globally and for the different regions, a long period of drought that was most pronounced during the 1970s, 1980s, and 1990s, whereas the wet years were marked by fluctuations that exceeded the 95% confidence level during the study period, with a very remarkable tendency towards wet conditions, particularly since the late 1990s. The obtained results can assist decision-makers in better sustainable development practices, especially in the fields of water resources, agriculture, and energy.


2011 ◽  
Vol 29 (6) ◽  
pp. 549-553
Author(s):  
Jian JIANG ◽  
Jun YANG ◽  
Fangfang HUANG ◽  
Shiqiang XU ◽  
Xiaoqing WANG ◽  
...  

Author(s):  
Milan Radojicic ◽  
Aleksandar Djokovic ◽  
Nikola Cvetkovic

Unpredictable and uncontrollable situations have happened throughout history. Inevitably, such situations have an impact on various spheres of life. The coronavirus disease 2019 has affected many of them, including sports. The ban on social gatherings has caused the cancellation of many sports competitions. This paper proposes a methodology based on hierarchical cluster analysis (HCA) that can be applied when a need occurs to end an interrupted tournament and the conditions for playing the remaining matches are far from ideal. The proposed methodology is based on how to conclude the season for Serie A, a top-division football league in Italy. The analysis showed that it is reasonable to play 14 instead of the 124 remaining matches of the 2019–2020 season to conclude the championship. The proposed methodology was tested on the past 10 seasons of the Serie A, and its effectiveness was confirmed. This novel approach can be used in any other sport where round-robin tournaments exist.


2010 ◽  
Vol 41 (2) ◽  
pp. 126-133 ◽  
Author(s):  
N. Kalamaras ◽  
H. Michalopoulou ◽  
H. R. Byun

In this study a method proposed by Byun & Wilhite, which estimates drought severity and duration using daily precipitation values, is applied to data from stations at different locations in Greece. Subsequently, a series of indices is calculated to facilitate the detection of drought events at these sites. The results provide insight into the trend of drought severity in the region. In addition, the seasonal distribution of days with moderate and severe drought is examined. Finally, the Hierarchical Cluster Analysis method is used to identify sites with similar drought features.


2019 ◽  
Vol 15 (S367) ◽  
pp. 397-399
Author(s):  
Arturo Colantonio ◽  
Irene Marzoli ◽  
Italo Testa ◽  
Emanuella Puddu

AbstractIn this study, we identify patterns among students beliefs and ideas in cosmology, in order to frame meaningful and more effective teaching activities in this amazing content area. We involve a convenience sample of 432 high school students. We analyze students’ responses to an open-ended questionnaire with a non-hierarchical cluster analysis using the k-means algorithm.


Author(s):  
Swarna Rajagopalan ◽  
Wesley Baker ◽  
Elizabeth Mahanna-Gabrielli ◽  
Andrew William Kofke ◽  
Ramani Balu

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