Representation of the spatial association between salinity and water chemical properties in Al-Hassa Oasis

Authors

  • Ibrahim Alhawas Department of Environment & Agricultural Natural Resources, College of Agricultural and Food Sciences, King Faisal University, KSA
  • Abdalhaleem A. Hassaballa Department of Environment & Agricultural Natural Resources, College of Agricultural and Food Sciences, King Faisal University, KSA

Keywords:

statistical correlation, GIS, water salinity, Al-Hassa, prediction rate

Abstract

With poor irrigation water quality, cultivation difficulties are certainly expected to rise. This will cause a severe reduction in crops yield unless a strong strategy is followed to control and sustain high yielding capacity under particular circumstances. Water salinity presented in the form of water electrical conductivity (EC), has been presented in this study as one of the parameters that significantly participated in decreasing the quality of irrigation water in Al-Hassa oasis at Kingdom of Saudi Arabia. The sharing factors in quantifying water EC and its distribution spacewise has been examined by applying the frequency ratio (FR) technique (spatial autocorrelation) between salinity status and water measured elements, specifically, chlorine (Cl-), sodium (Na+), calcium (Ca2+), potassium (K+) and magnesium (Mg2+). A threshold salinity value of (EC ≥ 2.0 dS/m) was identified as a break-line for classifying the well-water sources that non-valid for irrigating vegetables grown in the area. A statistical correlation among the examined parameters and EC was conducted using the statistical package for social sciences (SPSS), and compared to the applied FR technique. A dosage of Cl- in irrigation water was observed to be the most significant candidate that raised EC, proved by an R2 of 63%. However, the FR technique has shown the validity in analyzing the spatial distribution of water measured variables; in addition to nominating the variable that had the higher association portion, which was assessed to be Na+, followed by Cl- with prediction rates of 4.22 and 3.22, respectively. Keywords: statistical correlation, GIS, water salinity, Al-Hassa, prediction rate DOI: 10.25165/j.ijabe.20201302.5298 Citation: Alhawas I, Hassaballa A A. Representation of the spatial association between salinity and water chemical properties in Al-Hassa Oasis. Int J Agric & Biol Eng, 2020; 13(2): 168–174.

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Published

2020-04-10

How to Cite

(1)
Alhawas, I.; Hassaballa, A. A. Representation of the Spatial Association Between Salinity and Water Chemical Properties in Al-Hassa Oasis. Int J Agric & Biol Eng 2020, 13, 168-174.

Issue

Vol. 13 No. 2 (2020): IJABE

Section

Natural Resources and Environmental Systems

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