Assessment of Seasonal and Spatial Variations of Coastal Water Quality Using Multivariate Statistical Techniques

Abstract

This study investigates the seasonal and spatial trends in Kuwait’s coastal water’s physical, chemical, and biological parameters by applying multivariate statistical techniques, including cluster analysis (CA), principal component/factor analysis (PCA/FA), and the Pearson correlation (PC) method to the average daily reading of water quality parameters from fifteen stations over one year. The investigated parameters are pH, turbidity, chlorophyll-a, conductivity, dissolved oxygen (DO), phycoerythrin, salinity, and temperature. The results show that the coastal water of Kuwait is subjected to high environmental pressure due to natural and human interferences. During 2017, the DO levels were below the threshold limit, and at the same time, the water temperature and salinity were very high, causing a series of fish death events. CA resulted in three different regions based on the turbidity, including high, moderate, and low regions, and three seasons (winter, summer, and autumn). Spring is very short and overlaps with winter and summer. PCA/FA applied on the datasets assisted in extracting and identifying parameters responsible for the variations in the seasons and regions obtained from CA. Additionally, Pearson’s correlation resulted in a strong positive relation between chlorophyll and phycoerythrin in 7 out of the 15 stations. However, at high turbidity regions (stations 1 and 2), chlorophyll concentration was low. Additionally, the negative correlation between DO and temperature was observed at stations with rare human activities.

Predicting Coastal Dissolved Oxygen Values with the Use of Artificial Neural Networks: A Case Study for Cyprus

“…This study observed that the spatial distribution of DO had the highest surface levels recorded in March in most coastal stations, while temperature and salinity were lower than in the offshore stations. In another study of Alkhalidi et al [39], Statistical Analysis was applied in order to investigate the relationships between coastal water parameters; and it confirmed the negative relationship between high WT and low DO levels, which were associated with the fish kill events that occurred during April and May 2017 in the Kuwait bay.…”

Forecasting bathing water quality in the UK: A critical review

“…Indicator bacteria are sensitive to sunlight; therefore, the time of day when samples are collected may significantly influence the final enumeration results (Hijnen et al, 2006; Pullerits et al, 2020). The spatial distribution of microbial pollution depends also on their susceptibility to salinity, DO, turbidity, CSOs discharge patterns, location of sources of pollutants, advection, and the distribution of mixing on the site (Alkhalidi et al, 2021; Cherif et al, 2019; Poopipattana et al, 2021). In general, the highest values of bacteria and the poorest water quality according to in situ measurements are recorded next to the river mouth, while lower values and better water quality status are observed moving away from the confluence of the river mouth with the sea (Cherif et al, 2019).…”

Distribusi Horizontal Klorofil-A dan Material Padatan Tersuspensi di Muara Bodri, Jawa Tengah

“…Pada suhu perairan yang tinggi dapat menyebabkan kelarutan DO menjadi rendah dan hubungan terjadi sebaliknya. (Wu et al, 2010, Alkhalidi et al, 2021 Berdasarkan grafik sebaran stasiun (Gambar 5) dapat dilihat pengelompokan stasiun. Stasiun 1, 2 dan 3 yang terletak di badan sungai dicirikan oleh parameter tingginya klorofil-a dan MPT.…”