Water Quality Modelling Using Multivariate Statistical Analysis and Remote Sensing in South Florida Mohammad Hajigholizadeh [email protected]

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Water Quality Modelling Using Multivariate Statistical Analysis and Remote Sensing in South Florida Mohammad Hajigholizadeh Mhaji002@Fiu.Edu Florida International University FIU Digital Commons FIU Electronic Theses and Dissertations University Graduate School 11-7-2016 Water Quality Modelling Using Multivariate Statistical Analysis and Remote Sensing in South Florida Mohammad Hajigholizadeh [email protected] DOI: 10.25148/etd.FIDC001230 Follow this and additional works at: https://digitalcommons.fiu.edu/etd Part of the Civil Engineering Commons, and the Environmental Engineering Commons Recommended Citation Hajigholizadeh, Mohammad, "Water Quality Modelling Using Multivariate Statistical Analysis and Remote Sensing in South Florida" (2016). FIU Electronic Theses and Dissertations. 2992. https://digitalcommons.fiu.edu/etd/2992 This work is brought to you for free and open access by the University Graduate School at FIU Digital Commons. It has been accepted for inclusion in FIU Electronic Theses and Dissertations by an authorized administrator of FIU Digital Commons. For more information, please contact [email protected]. FLORIDA INTERNATIONAL UNIVERSITY Miami, Florida WATER QUALITY MODELLING USING MULTIVARIATE STATISTICAL ANALYSIS AND REMOTE SENSING IN SOUTH FLORIDA A dissertation submitted in partial fulfillment of the requirements for the degree of DOCTOR OF PHILOSOPHY in CIVIL ENGINEERING by Mohammad Hajigholizadeh 2016 To: Interim Dean Ranu Jung College of Engineering and Computing This dissertation, written by Mohammad Hajigholizadeh, and entitled Water Quality Modelling Using Multivariate Statistical Analysis and Remote Sensing in South Florida, having been approved in respect to style and intellectual content, is referred to you for judgment. We have read this dissertation and recommend that it be approved. _______________________________________ Michael C. Sukop _______________________________________ Walter Z. Tang _______________________________________ Seung J. Lee _______________________________________ Hector R. Fuentes, Co-Major Professor _______________________________________ Assefa M. Melesse, Co-Major Professor Date of Defense: November 7, 2016 The dissertation of Mohammad Hajigholizadeh is approved. _______________________________________ Interim Dean Ranu Jung College of Engineering and Computing _______________________________________ Andres G. Gil Vice President for Research and Economic Development and Dean of the University Graduate School Florida International University, 2016 ii © Copyright 2016 by Mohammad Hajigholizadeh All rights reserved. iii DEDICATION To my mother, Afagh, who encouraged my curiosity and have always supported my aspirations no matter how fanciful they have been, also to my father, Heidar, who is no longer physically present in my life, I still feel his impact every day. And to Samira, whose love and wisdom has kept me grounded. iv ACKNOWLEDGMENTS The work presented in this dissertation was not accomplished solely by the author. Many individuals assisted me throughout this process with mentorship and logistical support. I would fist like to thank Dr. Assefa M. Melesse and Dr. Hector R. Fuentes, my co-major advisors. Your level of energy and excitement seem boundless and are often a needed reminder of what I love about science. Special thanks to Dr. Assefa M. Melesse. You have been an excellent role model for me, both professionally and personally. You believed in my ideas and allowed me to run with them. Working under your mentorship has given me the resources and confidence to pursue my career aspirations. I am grateful for all of the members of my dissertation committee: Dr. Walter Z. Tang, Dr. Michael C. Sukop, and Dr. Seung Jae Lee. I appreciate your generous contributions of expertise and time during my research. Special thanks to Dr. Lakshmi Reddi for his support during the early stages of this research, when it was still a dissertation proposal. During my research I was generously supported by the Department of Civil and Environmental Engineering, and University Graduate School of Florida International University through both the Presidential Fellowship and Graduate Assistantship. v ABSTRACT OF THE DISSERTATION WATER QUALITY MODELLING USING MULTIVARIATE STATISTICAL ANALYSIS AND REMOTE SENSING IN SOUTH FLORIDA by Mohammad Hajigholizadeh Florida International University, 2016 Miami, Florida Professor Assefa M. Melesse, Co-Major Professor Professor Hector R. Fuentes, Co-Major Professor The overall objective of this dissertation research is to understand the spatiotemporal dynamics of water quality parameters in different water bodies of South Florida. Two major approaches (multivariate statistical techniques and remote sensing) were used in this study. Multivariate statistical techniques include cluster analysis (CA), principal component analysis (PCA), factor analysis (FA), discriminant analysis (DA), absolute principal component score-multiple linear regression (APCS-MLR) and PMF receptor modeling techniques were used to assess the water quality and identify and quantify the potential pollution sources affecting the water quality of three major rivers of South Florida. For this purpose, a 15-year (2000–2014) data set of 12 water quality variables, and about 35,000 observations were used. Agglomerative hierarchical CA grouped 16 monitoring sites into three groups (low pollution, moderate pollution, and high pollution) based on their similarity of water quality characteristics. DA, as an important data reduction method, was used to assess the water pollution status and vi analysis of its spatiotemporal variation. PCA/FA identified potential pollution sources in wet and dry seasons, respectively, and the effective mechanisms, rules, and causes were explained. The APCS-MLR and PMF models apportioned their contributions to each water quality variable. Also, the bio-physical parameters associated with the water quality of the two important water bodies of Lake Okeechobee and Florida Bay were investigated based on remotely sensed data. The principal objective of this part of the study is to monitor and assess the spatial and temporal changes of water quality using the application of integrated remote sensing, GIS data, and statistical techniques. The optical bands in the region from blue to near infrared and all the possible band ratios were used to explore the relation between the reflectance of a waterbody and observed data. The developed MLR models appeared to be promising for monitoring and predicting the spatiotemporal dynamics of optically active and inactive water quality characteristics in Lake Okeechobee and Florida Bay. It is believed that the results of this study could be very useful to local authorities for the control and management of pollution and better protection of water quality in the most important water bodies of South Florida. vii TABLE OF CONTENTS CHAPTER PAGE DISCLAIMER..............................................................................................................1 PREFACE.....................................................................................................................2 I. INTRODUCTION ........................................................................................................3 1. Introduction and research rationale...............................................................................4 2. Current water quality challenges in South Florida .......................................................5 3. Objectives of study .......................................................................................................9 References.....................................................................................................................14 II. A COMPREHENSIVE REVIEW ON WATER QUALITY PARAMETERS ESTIMATION USING REMOTE SENSING TECHNIQUES ...................................19 Abstract.........................................................................................................................20 1. Introduction...................................................................................................................21 2. An overview of water quality assessment and remote sensing ....................................23 3. Spaceborne and airborne sensors for water quality studies .........................................25 4. Water quality investigations through remote sensing techniques ................................26 4.1. Chlorophyll-a .........................................................................................................31 4.2. Colored dissolved organic matters (CDOM) .........................................................37 4.3. Secchi disk depth ...................................................................................................41 4.4. Turbidity and total suspended sediments...............................................................44 4.5. Total phosphorus....................................................................................................47 4.6. Water temperature..................................................................................................51 4.7. Sea surface salinity (SSS) ......................................................................................54 4.8. Dissolved oxygen (DO), biochemical oxygen demand (BOD) and chemical oxygen demand (COD)...........................................................................................56 5. Limitations of remote sensing for the assessment of water quality parameters ...........59 6. Discussion.....................................................................................................................61
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