Abandoned channels are essential in the Quaternary floodplains, and their infill contains different paleoenvironment recorders. Grain-size distribution (GSD) is one proxy that helps characterize the alluviation and associated sedimentological processes of the abandoned channels. The classic statistical methods of the grain-size analysis provide insufficient information on the whole distribution; this necessitates a more comprehensive approach. Grain-size endmember modeling (EMM) is one approach beyond the traditional procedures that helps unmix the GSDs. This study describes the changes in the depositional process by unmixing the GSDs of a Holocene abandoned channel through parameterized EMM integrated with lithofacies, age–depth model, loss-on-ignition (LOI), and magnetic susceptibility (MS). This approach effectively enabled the quantification and characterization of up to four endmembers (EM1-4); the characteristics of grain-size endmembers imply changes in sedimentary environments since 8000 BP. EM1 is mainly clay and very fine silt, representing the fine component of the distribution corresponding to the background of quiet water sedimentation of the lacustrine phase. EM2 and EM3 are the intermediate components representing the distal overbank deposits of the flood. EM4 is dominated by coarse silt and very fine sand, representing deposition of overbank flow during the flood periods. This paper demonstrates that the parametrized grain-size EMM is reasonable in characterizing abandoned channel infill sedimentary depositional and sedimentation history.

Grain size distribution (GSD) is essential for characterizing the deposition process. However, it is necessary to consider its compositional constraint to comprehend the statistical distribution of size fractions within the sediments. Compositional data analysis (CoDA) and wavelet transform (WT) represent alternative methods beyond traditional approaches, e.g., probability density function (PDF). This paper introduces a quantitative approach for characterizing Quaternary depositional and environmental changes using abandoned channel infill sediments. The proposed approach integrates CoDA and WT to thoroughly comprehend the depositional patterns observed in abandoned channels and the underlying environmental variability. The depositional model constructed based on CoDA showed coarsening-upward sequences, suggesting a periodic connection between the main channel and the oxbow lake. Three scales of cycles consistent with the depositional model constructed using CoDA were identified based on WT: small, medium, and large-scale cycles of processes. The large-scale cycles indicate the main depositional events, while the medium and small scale reflects the variation within and during deposition. CoDA and WT demonstrate excellent potential in characterizing the GSD and interpreting oxbow lakes' deposition and sedimentation processes.

Recently, groundwater has been recognized as one of the primary sources of water supply in Sudan. However, groundwater quality continues to deteriorate due to natural and human-induced activities. This research employed groundwater quality index (GWQI), multivariate statistical methods and human health risk assessment to investigate the suitability of groundwater for domestic uses in northern Khartoum state, Sudan. The groundwater samples were analyzed for eleven physiochemical parameters, including pH, EC, TDS, TH, Cl-, SO4-2, NO3-, Ca+2, Mg+2, Na+, HCO3- and the primary investigation indicated the deviation of these parameters from World Health Organization (WHO) standards. The hydrochemical analysis revealed different groundwater facies with the dominance of Ca-Mg-HCO3 water type. Consequently, the groundwater samples were classified, based on GWQI, into three categories as 76.4 % of the samples fall in the excellent water class, 17.6 % are projected in the good water class, and 5.9 % of groundwater samples are considered unsuitable for human consumption. The multivariate statistical methods, including Pearson's correlation analysis, hierarchical cluster analysis (HCA), and principal component analyses (PCA), were applied to determine groundwater quality data's structure and the primary factors influencing groundwater quality. These techniques revealed that groundwater in the study area is mainly controlled by rock-water interaction and agricultural practice. Additionally, they were used to categorize groundwater samples based on their chemical content. As a result, three types of groundwater were identified low, medium, and highly mineralized. In the final stage, the non-carcinogenic human health risk was assessed based on the concentration of NO3- and the obtained hazard quotient for children indicated that 64.7 % of groundwater samples are beyond the permissible limit (1<) and the use of these samples may result in health consequences. As a result, remedial measures are suggested for the sustainable use of groundwater.

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