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ARS Home » Plains Area » Fort Collins, Colorado » Center for Agricultural Resources Research » Water Management and Systems Research » Research » Publications at this Location » Publication #370261
Research Project: Response of Ecosystem Services in Agricultural Watersheds to Changes in Water Availability, Land Use, Management, and Climate

Location: Water Management and Systems Research

Title: Chlorophyll-a concentration assessment using remotely sensed data over multiple years along the coasts of the United Arab Emirates

Author
item FATHELRAHMAN, EIHAB - United Arab Emirates
item HUSSEIN, KHALID - United Arab Emirates
item PARAMBAN, SAFWAN - United Arab Emirates
item Green, Timothy
item Vandenberg, Bruce

Submitted to: Emirates Journal of Food and Agriculture
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 5/20/2020
Publication Date: 6/30/2020
Citation: Fathelrahman, E.M., Hussein, K.A., Paramban, S., Green, T.R., Vandenberg, B.C. 2020. Chlorophyll-a concentration assessment using remotely sensed data over multiple years along the coasts of the United Arab Emirates. Emirates Journal of Food and Agriculture. 32(5):345-357.

Interpretive Summary: The United Arab Emirates (UAE) recently witnessed algae/phytoplankton blooms attributed to the high concentrations of Chlorophyll-a associated with the spread and accumulation of a wide range of organisms with toxic effects that impact ecological and fishing economic activities and water desalination along coastal areas. This research explores the UAE coasts as a case study for the framework presented here. In this research, we argue that advances in satellite remote sensing and imaging of spatial and temporal data offer sufficient information to find the best-fit regression method and relationship between Chlorophyll-a concentration and a set of climatic and biological explanatory variables over time. Three functional forms of regression models were tested and analysed to reveal that the Log-Linear Model provides the most statistically robust model compared to the Linear and the Generalised Least Square models. In addition, it is useful to identify the factors that influence Chlorophyll-a concentration. Research results can be beneficial to aid decision-makers in building a best-fit statistical system and models of algal blooms in the study area. Furthermore, the model can support awareness and preparedness efforts in the study area. Lessons learned from this study should apply to similar environments around the world.

Technical Abstract: The United Arab Emirates (UAE) recently witnessed algae/phytoplankton blooms attributed to the high concentrations of Chlorophyll-a associated with the spread and accumulation of a wide range of organisms with toxic effects that impact ecological and fishing economic activities and water desalination along coastal areas. This research explores the UAE coasts as a case study for the framework presented here. In this research, we argue that advances in satellite remote sensing and imaging of spatial and temporal data offer sufficient information to find the best-fit regression method and relationship between Chlorophyll-a concentration and a set of climatic and biological explanatory variables over time. Three functional forms of regression models were tested and analysed to reveal that the Log-Linear Model provides the most statistically robust model compared to the Linear and the Generalised Least Square models. In addition, it is useful to identify the factors that influence Chlorophyll-a concentration. Research results can be beneficial to aid decision-makers in building a best-fit statistical system and models of algal blooms in the study area. Furthermore, the model can support awareness and preparedness efforts in the study area. Lessons learned from this study should apply to similar environments around the world.