Spatial Distribution and Trend Analysis of Groundwater Contaminants Using the ArcGIS Geostatistical Analysis (Kriging) Algorithm; The case of Gurage Zone, Ethiopia DOI Creative Commons

Abel Amsalu Ayalew,

Moges Tariku Tegenu

Research Square (Research Square), Journal Year: 2024, Volume and Issue: unknown

Published: Oct. 24, 2024

Abstract The study explores the spatial distribution and trends of groundwater pollutants focusing on calcium four other key water quality parameters in Gurage Zone, Ethiopia, 2024. It uses ArcGIS geostatistical analysis tool with Kriging algorithm to map analyze variability contaminants. primary aim is identify areas high levels understand patterns. identifies contamination hotspots associated natural processes human activities. Twenty-seven samples were collected from various sites, like calcium, total dissolved solids, hardness, conductivity, alkalinity measured. findings show that contaminants varies significantly across different areas, some exceeding safe drinking limits. reveals southern region has highest concentration, shallow local boreholes. deeper wells have higher conductivity. trend shows increased pollutant along X Y axes. model effectively predicted unsampled offering a reliable technique aimed at monitoring. provides important insights for authorities implement interventions protection Zone.

Language: Английский

Risk assessment of potentially toxic elements and mapping of groundwater pollution indices using soft computer models in an agricultural area, Northeast Algeria DOI
Azzeddine Reghais, Abdelmalek Drouiche, Faouzi Zahi

et al.

Journal of Hazardous Materials, Journal Year: 2025, Volume and Issue: unknown, P. 137991 - 137991

Published: March 1, 2025

Language: Английский

Citations

1
An advanced approach for drinking water quality indexing and health risk assessment supported by machine learning modelling in Siwa Oasis, Egypt DOI Creative Commons
Mohamed Hamdy Eid, Viktória Mikita, Mustafa Eissa

et al.

Journal of Hydrology Regional Studies, Journal Year: 2024, Volume and Issue: 56, P. 101967 - 101967

Published: Sept. 16, 2024

Language: Английский

Citations

3
Spatial Dynamics and Ecotoxicological Health Hazards of Toxic Metals in Surface Water Impacted by Agricultural Runoff: Insights from Gis-Based Risk Assessment in the Sebou Basin, Morocco DOI
Hatim Sanad, Rachid Moussadek,

Latifa Mouhir

et al.

Published: Jan. 1, 2025

Language: Английский

Citations

0
Integrating Unsupervised Machine Learning, Statistical Analysis, and Monte Carlo Simulation to Assess Toxic Metal Contamination and Salinization in Non-Rechargeable Aquifers DOI Creative Commons
Mohamed Hamdy Eid, Omar Saeed, András Székács

et al.

Results in Engineering, Journal Year: 2025, Volume and Issue: unknown, P. 104989 - 104989

Published: April 1, 2025

Language: Английский

Citations

0
New approach to predict wastewater quality for irrigation utilizing integrated indexical approaches and hyperspectral reflectance measurements supported with multivariate analysis DOI Creative Commons
Mohamed Gad,

Reda Abd El Hamed,

Ezzat A. El Fadaly

et al.

Scientific Reports, Journal Year: 2025, Volume and Issue: 15(1)

Published: May 12, 2025

Abstract Irrigation water quality is critical to maintaining agricultural output. Reusing wastewater a global activity that serves as an alternative resource in agriculture. This study integrates indices and hyperspectral reflectance measurements assess predict the drain for irrigation Egypt. For that, 50 samples were collected surrounding Rosette Branch Four major findings emerge from this Nile Delta study: First, integrated index approach revealed significant spatial variability, with 4% of drains (IWQI < 60) requiring pretreatment 94% showing low metal contamination (PI 1), except Zn hotspots near industrial areas. Second, newly developed spectral such RSI 566, 1140 564, strongly related Total Chlorophyll R 2 = 0.73, 456,422 was (IWQI) 0.67. As well 500, 400 had good relationship Biochemical Oxygen Demand (BOD) 0.75. Third, optimized PLSR models demonstrated higher accuracy estimating WQIs. instance, model produced reliable estimates T Chl., achieving 0.87 0.77 calibration validation dataset. Similarly, provided accurate predictions BOD, 0.96 0.81 validation. Finally, hydrochemical analysis established evaporation dominance (Gibbs ratio > 0.8) 72% samples, explaining Ca-Mg-SO4 facies prevalence. While currently validated conditions, methodology’s 89% cross-region preliminary tests suggests broad applicability schemes. Future implementation should focus on: (1) farmer-adoptable sensors identified optimal bands (566–570 nm, nm), (2) targeted filtration Zn/Mn reduction high-PI drains, (3) seasonal account flow variations. work establishes new paradigm combining precision spectroscopy traditional assessment water-scarce systems.

Language: Английский

Citations

0
Geochemical characterization and health risk assessment of groundwater in Wadi Ranyah, Saudi Arabia, using statistical and GIS-based models DOI Creative Commons
Ahmed Asmoay,

Eltaher M. Shams,

Wael F. Galal

et al.

Environmental Geochemistry and Health, Journal Year: 2025, Volume and Issue: 47(6)

Published: May 16, 2025

Language: Английский

Citations

0
Chemometric investigation of river system contamination: Source identification and risk assessment using positive matrix factorization and Monte Carlo simulation DOI
Fikret Ustaoğlu, Bayram Yüksel, Mehmet Metin Yazman

et al.

Journal of Contaminant Hydrology, Journal Year: 2025, Volume and Issue: 273, P. 104627 - 104627

Published: May 24, 2025

Language: Английский

Citations

0
Spatial Distribution and Trend Analysis of Groundwater Contaminants Using the ArcGIS Geostatistical Analysis (Kriging) Algorithm; The case of Gurage Zone, Ethiopia DOI Creative Commons

Abel Amsalu Ayalew,

Moges Tariku Tegenu

Research Square (Research Square), Journal Year: 2024, Volume and Issue: unknown

Published: Oct. 24, 2024

Abstract The study explores the spatial distribution and trends of groundwater pollutants focusing on calcium four other key water quality parameters in Gurage Zone, Ethiopia, 2024. It uses ArcGIS geostatistical analysis tool with Kriging algorithm to map analyze variability contaminants. primary aim is identify areas high levels understand patterns. identifies contamination hotspots associated natural processes human activities. Twenty-seven samples were collected from various sites, like calcium, total dissolved solids, hardness, conductivity, alkalinity measured. findings show that contaminants varies significantly across different areas, some exceeding safe drinking limits. reveals southern region has highest concentration, shallow local boreholes. deeper wells have higher conductivity. trend shows increased pollutant along X Y axes. model effectively predicted unsampled offering a reliable technique aimed at monitoring. provides important insights for authorities implement interventions protection Zone.

Language: Английский

Citations

1