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Assessment of temporal and spatial water quality in international Gomishan Lagoon, Iran, using multivariate analysis

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Abstract

Coastal lagoon ecosystems are vulnerable to eutrophication, which leads to the accumulation of nutrients from the surrounding watershed over the long term. However, there is a lack of information about methods that could accurate quantify this problem in rapidly developed countries. Therefore, various statistical methods such as cluster analysis (CA), principal component analysis (PCA), partial least square (PLS), principal component regression (PCR), and ordinary least squares regression (OLS) were used in this study to estimate total organic matter content in sediments (TOM) using other parameters such as temperature, dissolved oxygen (DO), pH, electrical conductivity (EC), nitrite (NO2), nitrate (NO3), biological oxygen demand (BOD), phosphate (PO4), total phosphorus (TP), salinity, and water depth along a 3-km transect in the Gomishan Lagoon (Iran). Results indicated that nutrient concentration and the dissolved oxygen gradient were the most significant parameters in the lagoon water quality heterogeneity. Additionally, anoxia at the bottom of the lagoon in sediments and re-suspension of the sediments were the main factors affecting internal nutrient loading. To validate the models, R2, RMSECV, and RPDCV were used. The PLS model was stronger than the other models. Also, classification analysis of the Gomishan Lagoon identified two hydrological zones: (i) a North Zone characterized by higher water exchange, higher dissolved oxygen and lower salinity and nutrients, and (ii) a Central and South Zone with high residence time, higher nutrient concentrations, lower dissolved oxygen, and higher salinity. A recommendation for the management of coastal lagoons, specifically the Gomishan Lagoon, to decrease or eliminate nutrient loadings is discussed and should be transferred to policy makers, the scientific community, and local inhabitants.

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Abbreviations

BOD:

Biochemical oxygen demand

CA:

Cluster analysis

DO:

Dissolved oxygen

EC:

Electrical conductivity

FA:

Factor analyses

NO2 − :

Nitrite

NO3 − :

Nitrate

OLS:

Ordinary least squares regression

PCA:

Principal component analyses

PCR:

Principal component regression

PLS:

Partial least squares

SRP:

Soluble reactive phosphorus

Temp:

Temperature

TOM:

Total organic matter

TP:

Total phosphorus

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Acknowledgements

The authors acknowledge “Gorgan University of Agricultural Sciences and Natural Resources” and “Inland Waters Aquatic Stocks Research Center-Gorgan” for providing the Framework of the studies and the access to data.

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Authors and Affiliations

  1. Faculty of Fisheries and Environmental Sciences, Gorgan University of Agricultural Sciences and Natural Resources, Golestan, Iran

    Nabee Basatnia & Seyed Abbas Hossein

  2. Instituto de Geomorfología y Suelos, Department of Geography, University of Málaga, 29071, Málaga, Spain

    Jesús Rodrigo-Comino

  3. Physical Geography, Trier University, 54286, Trier, Germany

    Jesús Rodrigo-Comino

  4. Department of Agronomy, Iowa State University, Ames, IA, USA

    Yones Khaledian

  5. Department of Natural Sciences, Dickinson State University, Dickinson, ND, USA

    Eric C. Brevik

  6. Department of Soil and Crop Sciences, Texas A&M University, College Station, TX, USA

    Jacqueline Aitkenhead-Peterson

  7. Centre for Environmental Studies, Department of Civil Engineering, Anna University, Chennai, 600 025, India

    Usha Natesan

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Basatnia, N., Hossein, S.A., Rodrigo-Comino, J. et al. Assessment of temporal and spatial water quality in international Gomishan Lagoon, Iran, using multivariate analysis. Environ Monit Assess 190, 314 (2018). https://doi.org/10.1007/s10661-018-6679-2

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