Abstract
Algerian climate is characterized by the transition between the subtropical climate in the north and the hot Saharan climate in the south. Understanding the spatiotemporal variability of rainfall patterns in such areas has significant implications for water resources management. To account for the spatial variation in the rainfall pattern of north Algeria, Tsallis entropy analysis, pattern recognition, and Precipitation Concentration Index (PCI) have been analyzed over a period of 33 years (1980–2013). The rainfall trend is identified by analyzing the results of the structural break test and Mann-Kendall (MK) trend tests. The Tsallis entropy produced spatial patterns for a better understanding of rainfall characteristics and the results show that entropy values were higher for higher rainfall values. The magnitude of rainfall change indicates that a large amount of rainfall occurs over the northern country boundary compared with the central part of Algeria. The rainfall record shows a structural break in the year 1992 during the selected time period. The MK trend analysis revealed a significant decreasing trend over the central and no trend in north and south of the study area. The PCI indicates a moderate rainfall concentration across the northern border region compared with a significant irregular rainfall distribution over the central region. The Wavelet Coherence Analysis (WCA) between El Nino Modoki (EMI) and Southern Oscillation Index (SOI) events on monthly rainfall data were also investigated to find a possible influence of global climatic indicators on the rainfall events. The results show a significant correlation of EMI and SOI with the rainfall pattern of north Algeria.
![](http://media.springernature.com/m312/springer-static/image/art%3A10.1007%2Fs00704-021-03542-y/MediaObjects/704_2021_3542_Fig1_HTML.png)
![](http://media.springernature.com/m312/springer-static/image/art%3A10.1007%2Fs00704-021-03542-y/MediaObjects/704_2021_3542_Fig2_HTML.png)
![](http://media.springernature.com/m312/springer-static/image/art%3A10.1007%2Fs00704-021-03542-y/MediaObjects/704_2021_3542_Fig3_HTML.png)
![](http://media.springernature.com/m312/springer-static/image/art%3A10.1007%2Fs00704-021-03542-y/MediaObjects/704_2021_3542_Fig4_HTML.png)
![](http://media.springernature.com/m312/springer-static/image/art%3A10.1007%2Fs00704-021-03542-y/MediaObjects/704_2021_3542_Fig5_HTML.png)
![](http://media.springernature.com/m312/springer-static/image/art%3A10.1007%2Fs00704-021-03542-y/MediaObjects/704_2021_3542_Fig6_HTML.png)
![](http://media.springernature.com/m312/springer-static/image/art%3A10.1007%2Fs00704-021-03542-y/MediaObjects/704_2021_3542_Fig7_HTML.png)
![](http://media.springernature.com/m312/springer-static/image/art%3A10.1007%2Fs00704-021-03542-y/MediaObjects/704_2021_3542_Fig8_HTML.png)
![](http://media.springernature.com/m312/springer-static/image/art%3A10.1007%2Fs00704-021-03542-y/MediaObjects/704_2021_3542_Fig9_HTML.png)
Similar content being viewed by others
References
Alexandersson H, Moberg A (1997) Homogenization of Swedish temperature data. Part I: Homogeneity test for linear trends. Int J Climatol 17:25–34
Ashok K, Yamagata T (2009) Climate change: the El Nino with a difference. Nature 61(7263):481
Bartolomeu S, Carvalho MJ, Rocha A (2016) Recent trends of extreme precipitation indices in the Iberian Peninsula using observations and WRF model results. Phys Chem Earth 94:10–21
Behera S, Yamagata T (2010) Imprint of the El NinoModoki on decadal sea level changes. Geophys Res Lett 37:L23702
Brunsell NA (2010) A multiscale information theory approach to assess spatial–temporal variability of daily precipitation. J Hydrol 385:165–172. https://doi.org/10.1016/j.jhydrol.2010.02.016
Chang C, Glover GH (2010) Time frequency dynamics of resting state brain connectivity measured with MRI. Neuro Image 50(1):81–98
Cheng L, Niu J, Liao D (2017) Entropy-based investigation on the precipitation variability over the Hexi Corridor in China. Entropy 19:660. https://doi.org/10.3390/e19120660
Dar H, Roshni T (2019) Spatio-temporal variation of drought characteristics, water resource availability and the relation of drought with large scale climate indices: a case study of Jhelum basin, India. Quaternary International Journal 525:140–150. https://doi.org/10.1016/j.quaint.2019.07.018
Deng S, Chen T, Yang N, Qu L, Li M, Chen D (2018) Spatial and temporal distribution of rainfall and drought characteristics across the Pearl River basin. Sci Total Environ 619–620(5):28–41
Feng J, Li J (2011) Influence of El Nino Modoki on spring rainfall over south China. J Geophys Res-Atmos 116:D13102
Feng X, Porporato A, Rodriguez-Iturbe I (2013) Changes in rainfall seasonality in the tropics. Nat Clim Chang 3(9):811–815
Feng J, Li J, Zhu J, Liao H (2016) Influences of El Nino Modoki event 1994/1995 on aerosol concentrations over southern China. J Geophys Res-Atmos 121(4):1637–1651
Forootan E, Khaki M, Schumacher M, Wulfmeyer V, Mehrnegar N, Van Dijk AIJM (2019) Understanding the global hydrological droughts of 2003 – 2016 and their relationships with teleconnections. Sci Total Environ 650(9):2587–2604
Fuwape IA, Ogunjo ST, Oluyamo SS, Rabiu AB (2016) Spatial variation of deterministic chaos in mean daily temperature and rainfall over Nigeria. Theor Appl Climatol 130:119–132. https://doi.org/10.1007/s00704-016-1867-x
Grinsted A, Moore JC, Jevrejeva S (2004) Application of the cross wavelet transform and wavelet coherence to geophysical time series. Nonlinear Process Geophys 45(2):561–566
Joshi N, Gupta D, Suryavanshi S, Adamowski J, Madramootoo CA (2016) Analysis of trends and dominant periodicities in drought variables in India: a wavelet transform based approach. Atmos Res 182(4):200–220
Kendall MG (1975) Rank correlation methods. Griffin, London
Lebel T, Ali A (2009) Recent trends in the Central and Western Sahel rainfall regime (1990-2007). J Hydrol 375(1–2):52–64
Lee JH, Ramirez JA, Kim TW, Julien PY (2018) Variability, teleconnection, and predictability of Korean precipitation in relation to large scale climate indices. J Hydrol 568:12–25. https://doi.org/10.1016/j.jhydrol.2018.08.034
Li X, Jiang F, Li L, Wang G (2011) Spatial and temporal variability of precipitation concentration index, concentration degree and concentration period in **njiang, China. Int J Climatol 31(11):1679–1693
Mann HB (1945) Nonparametric tests against trend. Econometrica 13:245–259
Martin-Vide J (2004) Spatial distribution of a daily precipitation concentration index in peninsular Spain. Int J Climatol 24(8):959–971
Mishra AK, Ozger M, Singh VP (2009) An entropy based investigation into the variability of precipitation. J Hydrol 370:139–154. https://doi.org/10.1016/j.jhydrol.2009.03.006
Mrad D, Djebbar Y, Hammar Y (2018) Analysis of trend rainfall: case of north-eastern Algeria. Journal Of Water and Land Development 36(I–III):105–115
Oliver JE (1980) Monthly precipitation distribution - a comparative index. Prof Geogr 32(3):300–309
Ramu DA, Rao SA, Pillai PA, Pradhan M, George G, Rao DN, Mahapatra S, Pai DS, Rajeevan M (2017) Prediction of seasonal summer monsoon rainfall over homogenous regions of India using dynamical prediction system. J Hydrol 546:103–112
Remya R, Unnikrishnan KP (2010) Chaotic Behaviour of interplanetary magnetic field under various geomagnetic conditions. J Atmos Solar Terr Phys 72:662–675. https://doi.org/10.1016/j.jastp.2010.03.007
Roshni T, Jha MK, Deo RC, Vandana A (2019) Development and evaluation of hybrid artificial neural network architectures for modeling spatio-temporal groundwater fluctuations in a complex aquifer system. Water Resour Manag:1–17
Sahu N, Behera SK, Ratnam JV, Da Silva RV, Parhi P, DuanW TK, Singh RB, Yamagata T (2014) El Nino Modoki connection to extremely-low streamflow of the Paranaiba River in Brazil. Clim Dyn 42(5–6):1509–1516
Salimun E, Tangang F, Juneng L, Behera SK, Yu W (2014) Differential impacts of conventional El Nino versus El NinoModoki on Malaysian rainfall anomaly during winter monsoon. Int J Climatol 34(8):2763–2774
Shannon CE (1948) A mathematical theory of communication. Bell Syst Tech J 27:379–423. https://doi.org/10.1002/bltj.1948.27.issue-3
Silva VPR, Enilson PC, Marília G. do N, & João Hugo B. da C. (2003) Use of entropy theory in analysis of rainfall and air temperature. Agriambi 7(2):269–274
Tamaddun KA, Kalra A, Ahmad S (2019) Spatiotemporal variation in the continental US streamflow in association with large-scale climate signals across multiple spectral bands. Water Resour Manag 33:1947–1968
Yesilirmak E, Atatanir L (2016) Spatiotemporal variability of precipitation concentration in western Turkey. Nat Hazards 81(1):687–704
Zhang Q, Wang Y, Singh VP, Gu X, Kong D, **ao M (2016) Impacts of ENSO and ENSO Modoki+A regimes on seasonal precipitation variations and possible underlying causes in the Huai River basin, China. J Hydrol 533:308–319
Acknowledgments
The authors would also like to thank the editors and the unknown reviewers for improving the quality of the paper.
Author information
Authors and Affiliations
Contributions
Mohammad Ali Ghorbani: Formal assessment, conceptualization, model development, supervision, and validation
Ercan Kahya: Framework of methodology, resources, supervision, and validation
Thendiyath Roshni: Software, initial draft writing, review and editing
Mahsa H.Kashani: Formal assessment, conceptualization, methodology
Anurag Malik: Formal assessment, conceptualization, methodology
Salim Heddam: Data collection and data analysis
Corresponding author
Ethics declarations
Conflict of interest
The authors declare no conflict of interest.
Additional information
Publisher’s note
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
Rights and permissions
About this article
Cite this article
Ghorbani, M.A., Kahya, E., Roshni, T. et al. Entropy analysis and pattern recognition in rainfall data, north Algeria. Theor Appl Climatol 144, 317–326 (2021). https://doi.org/10.1007/s00704-021-03542-y
Received:
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1007/s00704-021-03542-y