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«Caitlin Anne Lyman Riddick Submitted to: Biological and Environmental Sciences University of Stirling May 2016 For the degree of Doctor of Philosophy ...»

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Remote sensing and bio-geo-optical

properties of turbid, productive inland

waters: a case study of Lake Balaton

Caitlin Anne Lyman Riddick

Submitted to:

Biological and Environmental Sciences

University of Stirling

May 2016

For the degree of Doctor of Philosophy

Supervisors:

Prof. Andrew N. Tyler

Dr. Peter D. Hunter

Statement of Originality

I hereby confirm that this is an original piece of work conducted independently by the undersigned, and all work contained herein has not been submitted for any other degree.

All research material has been duly acknowledged and cited.

Signature of Candidate:

Caitlin Anne Lyman Riddick Date: 24 May 2016 Abstract Algal blooms plague freshwaters across the globe, as increased nutrient loads lead to eutrophication of inland waters and the presence of potentially harmful cyanobacteria. In this context, remote sensing is a valuable approach to monitor water quality over broad temporal and spatial scales. However, there remain several challenges to the accurate retrieval of water quality parameters, and the research in this thesis investigates these in an optically complex lake (Lake Balaton, Hungary).

This study found that bulk and specific inherent optical properties [(S)IOPs] showed significant spatial variability over the trophic gradient in Lake Balaton. The relationships between (S)IOPs and biogeochemical parameters differed from those reported in ocean and coastal waters due to the high proportion of particulate inorganic matter (PIM). Furthermore, wind-driven resuspension of mineral sediments attributed a high proportion of total attenuation to particulate scattering and increased the mean ̅ refractive index (np) of the particle assemblage. Phytoplankton pigment concentrations [chlorophyll-a (Chl-a) and phycocyanin (PC)] were also accurately retrieved from a times series of satellite data over Lake Balaton using semi-analytical algorithms.

Conincident (S)IOP data allowed for investigation of the errors within these algorithms, indicating overestimation of phytoplankton absorption [aph(665)] and underestimation of the Chl-a specific absorption coefficient [a*ph(665)]. Finally, Chl-a concentrations were accurately retrieved in a multiscale remote sensing study using the Normalized Difference Chlorophyll Index (NDCI), indicating hyperspectral data is not necessary to retrieve accurate pigment concentrations but does capture the subtle heterogeneity of phytoplankton spatial distribution.

The results of this thesis provide a positive outlook for the future of inland water remote sensing, particularly in light of contemporary satellite instruments with continued or improved radiometric, spectral, spatial and temporal coverage.

Furthermore, the value of coincident (S)IOP data is highlighted and contributes towards the improvement of remote sensing pigment retrieval in optically complex waters.

Acknowledgements Without the combination of intellectual, technical, financial and familial support, this PhD would most certainly not have been possible. First and foremost, I would like to thank my supervisors at the University of Stirling, Prof. Andrew Tyler and Dr. Peter Hunter, for their endless guidance, patience and support throughout this PhD. Their efforts to accommodate me and my family throughout the last several years have ultimately made this PhD possible, and I am incredibly grateful for their commitment to my study.

I would also like to acknowledge the Centre for Ecology and Hydrology (CEH) for a desk to work at in Edinburgh and PhD training and support, particularly the phytoplankton knowledge provided by my CEH supervisor Dr. Laurence Carvalho.

Thanks to Dr. Linda May, Dr. Bernie Dudley and Dr. Brian Spears for additional guidance and advice on lab and field work logistics.

Funding for this PhD was provided for by the University of Stirling Research Apprenticeship scheme and departmental funding from Biological and Environmental Sciences. The Lake Balaton field campaign was made possible by an equipment grant from the National Environmental Research Council (NERC) Field Spectroscopy Facility (FSF) and a grant from the NERC Airborne Research and Survey Facility (ARSF) (EU10-03). Specifically, the in situ optics equipment (AC-S, DH4 and ECOBB3 (WET Labs Inc.), and the CTD (Sea-Bird Electronics) used for this work were provided by NERC Field Spectroscopy Facility (EU10-03). Funding for contributions from the Balaton Limnological Institute (BLI) were provided in part by the TÁMOPA-11/1/KONV-2012-0038 project for evaluation and processing of field data.

Travel to Lake Balaton and shipping funds were partially provided by the Carnegie Trust. Additional funding is acknowledged from the University of Stirling Article Processing Charge fund and Dr. Betsey Fuller for an award covering the substantial page fees to publish Chapter 3 in the Journal of Geophysical Research – Oceans.

I am grateful for field assistance on Lake Balaton provided by Eszter Zsigmond and Géza Dobos and lab assistance from Terézia Horváth and Erika Kozma (BLI).

Valuable advice was appreciated from Attila Kovács, Hajnalka Horváth (BLI) and Tom Preston (Scottish Universities Environmental Research Centre). Additionally, wind speed data were measured by automatic stations established by predecessor in the title of Lake Balaton Development Coordination Agency and operated by the CentralTransdanubian Water Directorate. In particular, I would like to acknowledge the late Mátyás Présing, who was a warm and welcoming host in Tihany, imparted much knowledge on Lake Balaton and was a valued colleague and friend.





From the University of Stirling, cell size data from Clare Neil is gratefully acknowledged, and valuable advice from Evangelos Spyrakos was provided on technical remote sensing queries. Other university staff were invaluable to this PhD, including Jon McArthur for GIS and ENVI technical support, Scott Jackson for IT solutions for my ancient MacBook, Bill Jamieson for production of the Balaton map for publication of Chapter 3, and Lynn, Rose and the Biological and Environmental Sciences office staff for their administrative support. Thank you especially to Rebecca Barclay for the printing and submission of this thesis.

Many thanks to Jose Antonio Dominguez-Gomez (Czech University of Life Sciences Prague) for providing SCAPE-M_B2 corrected MERIS data for Chapter 5 and useful manuscript comments for the related manuscript submission to Remote Sensing of Environment.

The Plymouth Marine Laboratory (PML) is gratefully acknowledged for lab space and use of the dual beam spectrophotometer. Particular thanks go to Victor Martinez-Vicente for his guidance in all things related to IOPs, his infinite patience in the field and the lab, and the comments provided towards Chapters 3, 4 and 5. Also, thanks to Andrey Kurekin at PML for providing ATCOR-4 corrected AISA Eagle data for Chapter 6 and associated advice on working with this dataset.

I am grateful also for the additional field assistance provided by Stuart Bradley, Fiona Thompson, Shona McMillan and Stuart Riddick on Lochs Leven and Lomond, although this work is unfortunately not included in this thesis.

I cannot forget to thank my parents, Robert and Susan Lyman, who have provided incredible positivity and support throughout my PhD. They also gratefully offered Nona and Grandad’s daycare, which allowed me invaluable time to work. My sister Sara also contributed master babysitting skills that were much appreciated. My parents in-law, John and Linda Riddick, are also gratefully acknowledged for their support and childcare in Scotland. Thank you as well to my grandparents, whose beach houses provided excellent writing havens.

Last but certainly not least, I would like to thank my wonderful husband Stuart, and our little ones Maxwell and Isabelle. It has been a long road, and I am so grateful to have such a patient and loving family to have shared this journey with.

Table of Contents

Statement of Originality

Abstract

Acknowledgements

Table of Contents

List of Figures

List of Tables

List of Acronyms and Abbreviations

1 Introduction

1.1 Research context

1.1.1 Thesis aims and structure

1.1.2 Study site

2 Remote sensing of inland water quality

2.1 Phytoplankton and eutrophication

2.2 Importance of monitoring water quality

2.3 Remote sensing of inland waters

2.3.1 History of remote sensing application to lakes

2.3.2 Types of platform and sensors

2.4 Principles of light in water

2.4.1 Optically Active Constituents

2.4.2 Inherent and Apparent Optical Properties

2.5 Remote sensing algorithm types for extraction of in-water constituents......... 41 2.5.1 Empirical, semi-empirical and semi-analytical algorithms

2.5.2 Other algorithm approaches

2.5.3 Inversion of bio-optical models (analytical algorithms)

2.6 Remote sensing of phytoplankton pigments

2.6.1 Phytoplankton pigments and optical discrimination

2.6.2 Remote sensing of chlorophyll-a

2.6.3 Remote sensing of phycocyanin

2.7 Considerations for the remote sensing of inland waters

2.7.1 Satellite mission capability

2.7.2 Geography of inland waters

2.7.3 Algorithms

2.7.4 In situ data

2.7.5 Atmospheric correction

2.7.6 Operational

2.8 Previous remote sensing studies of Lake Balaton

2.9 Summary and research priorities

2.9.1 Thesis in context

3 Spatial variability of absorption coefficients over a biogeochemical gradient in a large and optically complex shallow lake

3.1 Introduction

3.2 Methods

3.2.1 Study site

3.2.2 Water sampling

3.2.3 In situ optical measurements

3.2.4 Chlorophyll-a

3.2.5 Phycocyanin

3.2.6 Biomass and phytoplankton counts

3.2.7 Total suspended matter

3.2.8 Coloured dissolved organic matter absorption

3.2.9 Laboratory measurement of particulate absorption

3.3 Results

3.3.1 Comparison of in situ and laboratory measured absorption

3.3.2 Variability in optically active constituents

3.3.3 Variability in the inherent optical properties

3.4 Discussion

3.4.1 Contributions to the absorption budget

3.4.2 Variability in the IOPs

Relationships between aph(λ), Chl-a and phytoplankton biomass.......... 103 3.4.3 3.4.4 Chl-a specific absorption

3.4.5 Phytoplankton and CDOM absorption in the UV

3.4.6 SIOPs and distance from the Zala River

aNAP(λ) and suspended matter

3.4.7 3.4.8 Effect of wind-driven resuspension

3.5 Conclusions

4 Scattering and backscattering of suspended matter in an optically complex, shallow lake

4.1 Introduction

4.2 Methods

4.2.1 Study area

4.2.2 Water sampling

4.2.3 In situ optical measurements

4.2.4 Chlorophyll-a

4.2.5 Phycocyanin

4.2.6 Biomass and phytoplankton counts

4.2.7 Total suspended matter and inorganic/organic fractions

4.2.8 Absorption by coloured dissolved organic matter

4.2.9 Particulate attenuation and scattering coefficients

4.2.10 Particulate backscattering coefficients

4.2.11 Bulk refractive index and particle size discrimination slope.................. 122

4.3 Results

4.3.1 Nature of suspended particles across the basins

4.3.2 Relative contributions of absorption and scattering to total attenuation 126 4.3.3 Variability in scattering, backscattering and attenuation coefficients.... 127 4.3.4 Relationships between scattering coefficients and biogeochemical parameters

4.3.5 Backscattering ratio, bulk refractive index and particle size distribution

4.4 Discussion

4.4.1 Contributions to particulate attenuation

4.4.2 Variability in the scattering and backscattering properties, and relationships with optically active particles

4.4.3 Backscattering ratio, bulk refractive index and particle size distribution

4.5 Conclusions

5 Evaluation of algorithms for retrieval of cyanobacterial pigments in highly turbid, optically complex waters using MERIS data

5.1 Introduction

5.1.1 Satellite remote sensing of cyanobacteria blooms

5.1.2 MERIS phycocyanin algorithms

5.2 Methods

5.2.1 Study site

5.2.2 Routine monitoring programmes

5.2.3 MERIS validation campaign

5.2.4 MERIS data processing

5.3 Results

5.3.1 Pigment and cell counts

5.3.2 Validation of atmospheric correction

5.3.3 Algorithm performance

5.3.4 Chlorophyll-a retrieval

5.3.5 Phycocyanin retrieval

5.3.6 IOP retrievals

5.3.7 Time series analysis

5.4 Discussion

5.4.1 Algorithm performance for pigment retrievals at 1 day matchups......... 188 5.4.2 Ability to retrieve biomass using Simis05 and Gons05

5.4.3 Temporal windows for satellite validation

5.4.4 Impact of dataset used and sampling methods

5.4.5 Sources of error in the retrieval of (S)IOPs

5.4.6 Applicability of algorithms

5.5 Conclusions

6 Multiscale remote sensing observations of water quality in a large, turbid shallow lake 197

6.1 Introduction

6.2 Methods

Study area – Lake Balaton

6.2.1 6.2.2 Water sampling

6.2.3 Chlorophyll-a pigment analysis

6.2.4 Phytoplankton biomass, total suspended matter and coloured dissolved organic matter

6.2.5 HyperSAS radiometry

6.2.6 Remote sensing datasets

6.2.7 Validation of atmospheric correction routines

6.2.8 The Normalized Difference Chlorophyll Index (NDCI)

6.2.9 Method for resampling resolution of Landsat 5 TM and AISA Eagle datasets 210

6.3 Results

6.3.1 Summary of biogeochemical parameters and biomass

6.3.2 Validation of atmospheric corrections

6.3.3 Algorithm performance

6.3.4 Degradation of AISA Eagle and Landsat 5 TM datasets

6.4 Discussion

6.4.1 Atmospheric corrections

6.4.2 Chlorophyll-a retrieval with NDCI

6.4.3 Resampling of Landsat 5 TM and AISA Eagle datasets

6.5 Conclusions

7 Discussion, conclusions and future research

7.1 Contributions of this research



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