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

Zerouali, Bilel; Chettih, Mohamed; Abda, Zaki; Mesbah, Mohamed; Santos, Celso Augusto Guimarães; Neto, Reginaldo Moura Brasil

doi:10.1007/s00704-021-03883-8

Cited by 19 publications

(6 citation statements)

References 101 publications

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“…The significance of applied climatology increased after World War II, with numerous studies being published addressing the direct impacts of climate [ 2 , 3 ]. Knowledge of rainfall data and characteristics is indispensable for water planning and management [ [4] , [5] , [6] , [7] ]. Several studies have assessed the spatiotemporal rainfall change and variability worldwide [ [8] , [9] , [10] , [11] , [12] , [13] , [14] ].…”

Section: Introductionmentioning

confidence: 99%

Artificial intelligent systems optimized by metaheuristic algorithms and teleconnection indices for rainfall modeling: The case of a humid region in the mediterranean basin

Zerouali¹,

Santos²,

Farias³

et al. 2023

Heliyon

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Section: Introductionmentioning

confidence: 99%

Artificial intelligent systems optimized by metaheuristic algorithms and teleconnection indices for rainfall modeling: The case of a humid region in the mediterranean basin

Zerouali¹,

Santos²,

Farias³

et al. 2023

Heliyon

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“…Various hydrology and water resource-related disciplines have recently shown an increased interest in using wavelet analysis. Particularly in terms of periodicity, numerous research studies have demonstrated that wavelet analysis is a useful tool for characterizing and analyzing climatic and hydrological data [22][23][24][25][26][27][28][29][30][31], and, also, the frequency domain variable structures of various climatic or hydrological variables can be examined and synthesized using wavelet analysis, which is also an effective method for exploring relationships between them [32][33][34][35][36][37][38][39][40][41]. Recent research has shown that wavelet analysis is an effective technique for identifying irregularly distributed multiscale characteristics in hydrometeorological data, and, also, the ability to establish quantitative correlations between various observation series using wavelet-based expressions has been demonstrated [42][43][44][45][46][47][48][49][50][51].…”

Section: Introductionmentioning

confidence: 99%

Wavelet Analysis and the Information Cost Function Index for Selection of Calibration Events for Flood Simulation

Jam-Jalloh,

Liu,

Wang

et al. 2023

Water

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Globally, floods are a prevalent type of natural disaster. Simulating floods is a critical component in the successful implementation of flood management and mitigation strategies within a river basin or catchment area. Selecting appropriate calibration data to establish a reliable hydrological model is of great importance for flood simulation. Usually, hydrologists select the number of flood events used for calibration depending on the catchment size. Currently, there is no numerical index to help hydrologists quantitatively select flood events for calibrating the hydrological models. The question is, what is the necessary and sufficient amount (e.g., 10 events) of calibration flood events that must be selected? This study analyses the spectral characteristics of flood data in Sequences before model calibration. The absolute best set of calibration data is selected using an entropy-like function called the information cost function (ICF), which is calculated from the discrete wavelet transform (DWT) decomposition results. Given that the validation flood events have already been identified, we presume that the greater the similarity between the calibration dataset and the validation dataset, the higher the performance of the hydrological model should be after calibration. The calibration datasets for the Tunxi catchment in southeast China were derived from 21 hourly flood events, and the calibration datasets were generated by arranging 14 flood events in sequences from 3 to 14 (i.e., a Sequence of 3 with 12 sets (set 1 = flood events 1, 2, 3; set 2 = flood events 2, 3, 4, …, and so on)), resulting in a total of 12 sequences and 78 sets. With a predetermined validation set of 7 flood events and the hydrological model chosen as the Hydrologic Engineering Center (HEC–HMS) model, the absolute best calibration flood set was selected. The best set from the Sequence of 10 (set 4 = S10′) was found to be the absolute best calibration set of flood events. The potential of the percentile energy entropy was also analyzed for the best calibration sets, but the ICF was the most consistent index to reveal the ranking based on similarity with model performance. The proposed ICF index in this study is helpful for hydrologists to use data efficiently with more hydrological data obtained in the new era of big data. This study also demonstrates the possibility of improving the effectiveness of utilizing calibration data, particularly in catchments with limited data.

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“…Annual global precipitation increased gradually from 1900 to the late 1950s, decreased until 1970, increased in the 1970s, and decreased after 1980. According to previous evaluations, the rainfall patterns study and investigation have become a more active research issue for better regional water resources and hazards management in recent years (Zerouali et al 2022).…”

Section: Introductionmentioning

confidence: 99%

“…DWT and CWT wavelet transform techniques have been used successfully in many applications, including transient image and signal analysis and processing and communication systems (Chandrasekhar and Eswara Rao 2012;Galiana-Merino et al 2013;Hill and Uvarova 2018). Wavelet transform is an excellent way to analyze nonstationary signals in nature (Zerouali et al 2022;Sang et al 2013). CWT and DWT are two procedures of wavelet transform (Brassarote et al 2018;Rhif et al 2019;Adhikari et al 2020).…”

Section: Introductionmentioning

confidence: 99%

Improving the visualization of rainfall trends using various innovative trend methodologies with time–frequency-based methods

et al. 2022

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In this paper, the Innovative Trend Methodology (ITM) and their inspired approaches, i.e., Double (D-ITM) and Triple (T-ITM), were combined with Hilbert Huang transform (HHT) time frequency-based method. The new hybrid methods (i.e., ITM-HHT, D-ITM-HHT, and T-ITM-HHT) were proposed and compared to the DWT-based methods in order to recommend the best method. Three total annual rainfall time series from 1920 to 2011 were selected from three hydrological basins in Northern Algeria. The new combined models (ITM-HHT, D-ITM-HHT, and T-ITM-HHT) revealed that the 1950–1975 period has significant wet episodes followed by a long-term drought observed in the western region of Northern Algeria, while Northeastern Algeria presented a wet period since 2001. The proposed approaches successfully detected, in a visible manner, hidden trends presented in the signals, which proves that the removal of some modes of variability from the original rainfall signals can increase the accuracy of the used approaches.

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

Abstract: Availability of data and material:The datasets generated during and/or analysed during the current study are available from the corresponding author on reasonable request.

Cited by 19 publications

References 101 publications

Artificial intelligent systems optimized by metaheuristic algorithms and teleconnection indices for rainfall modeling: The case of a humid region in the mediterranean basin

Artificial intelligent systems optimized by metaheuristic algorithms and teleconnection indices for rainfall modeling: The case of a humid region in the mediterranean basin

Wavelet Analysis and the Information Cost Function Index for Selection of Calibration Events for Flood Simulation

Improving the visualization of rainfall trends using various innovative trend methodologies with time–frequency-based methods

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