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Using multivariate factor analysis to assess surface/logged water quality and source of contamination at a large irrigation project at Al-Fadhli, Eastern Province, Saudi Arabia

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Abstract

A multivariate statistical technique, factor analysis, has been used to assess the impact of irrigation on near-surface water at a farm at Fadhli, Eastern Province, Saudi Arabia. A total of 34 surface water samples were analyzed for 23 different water quality parameters including pH, TDS, conductivity and alkalinity, sulphate, chloride, bicarbonate, nitrate, phosphate, bromide, fluoride, calcium, magnesium, sodium, potassium, arsenic, boron, copper, cobalt, iron, lithium, manganese, molybdenum, nickel, selenium, mercury, and zinc. The water quality data were subjected to both Q-mode and R-mode factor analysis. R-mode analysis resulted in three major factors for both summer and winter sampling events. Factor 1 (representing 48.91% of the summer and 53.66% of the winter variance) comprised elements likely to be due to the application of fertilizers and the dissolution of soil material. Factor 2 (14.04% of the summer and 11.94% of the winter variance) included elements common in irrigation water (related to the dissolution of aquifer materials). Factor 3 (7.36% of the summer and 10.18% of the winter variance) included molybdenum, manganese and nickel, which are common in micro-nutrients. Q-mode analysis showed that the most affected areas are located at the northwest corner of the farm.

Résumé

Une technique d’analyse statistique multidimensionnelle, l’analyse factorielle, a été utilisée pour évaluer l’impact de l’irrigation sur la nappe phréatique auprès d’une exploitation agricole à Fadhli (Arabie Saoudite, province de l’Est). Un ensemble de 34 échantillons d’eau a été analysé, 23 paramètres relatifs à la qualité de l’eau étant pris en compte. Ceux-ci concernaient le pH, le TDS, la conductivité et l’alcalinité, les teneurs en sulphates, chlorures, bicarbonates, nitrates, phosphates, bromures, fluorures, calcium, magnésium, sodium, potassium, arsenic, bore, cuivre, cobalt, fer, lithium, manganèse, molybdène, nickel, sélénium, mercure et zinc. Les données relatives à la qualité de l’eau ont fait l’objet d’une analyse factorielle en mode Q et en mode R. L’analyse en mode R a fait apparaître trois facteurs principaux à la fois pour les échantillons d’été et d’hiver. Le facteur 1 (représentant 48,9% de la variance des échantillons d’été et 53,7% de la variance des échantillons d’hiver) rassemble des éléments susceptibles de résulter de l’épandage de produits fertilisants et de la dissolution d’éléments inclus dans le sol. Le facteur 2 (représentant 14,0% de la variance des échantillons d’été et 11,9% de la variance des échantillons d’hiver) rassemble des éléments communs dans les eaux d’irrigation (en rapport avec les éléments présents dans l’aquifère). Le facteur 3 (représentant 7,4% de la variance des échantillons d’été et 10,2% de la variance des échantillons d’hiver) rassemble des éléments tels que le molybdène, le manganèse et le nickel qui sont communs dans les micronutriments. L’analyse en mode Q a montré que les zones les plus affectées sont situées en partie nord-ouest de l’exploitation agricole.

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Acknowledgments

The authors gratefully acknowledge the support of King Fahd University of Petroleum and Minerals (KFUPM), Dhahran, Saudi Arabia for providing overall logistic and analytical support to carry out this project. Special thanks to the Research Institute KFUPM for their support in analyzing the water samples. Thanks are also due to the Water Resources Division, Abunayyan Group, Al-Khobar, Saudi Arabia for allowing time and resources to complete the manuscript.

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Correspondence to Syed Munaf Ahmed.

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Ahmed, S.M., Hussain, M. & Abderrahman, W. Using multivariate factor analysis to assess surface/logged water quality and source of contamination at a large irrigation project at Al-Fadhli, Eastern Province, Saudi Arabia. Bull Eng Geol Environ 64, 315–323 (2005). https://doi.org/10.1007/s10064-005-0277-6

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  • DOI: https://doi.org/10.1007/s10064-005-0277-6

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