Investigating ecological indicators of freshwater ecosystems using signal analysis methods [Elektronische Ressource] / submitted by Jean Duclos Alegue Feugo

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• Publié par: brandenburgische_technische_universitat_cottbus
• Publié le: 01 janvier 2008
• Nombre de lectures: 34
• Langue: English
• Poids de l'ouvrage: 1 Mo

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Brandenburg University of Technology Cottbus
Faculty of Environmental Sciences and
Process Engineering



Investigating Ecological Indicators of Freshwater
Ecosystems Using Signal Analysis Methods


A Doctoral Dissertation, Approved by the Faculty of Environmental Sciences
and Process Engineering of the Brandenburg University of Technology
Cottbus and Submitted in Fulfilment of the Requirements for the Award of the
Degree of Ph.D


Submitted by
Jean Duclos Alegue Feugo, M.Sc.
From Bamenda, Cameroon



Supervision
Univ. - Prof. Dr. rer. nat. habil. Albrecht Gnauck, BTU Cottbus
Priv. - Doz. Dr. - Ing. habil. Thomas Rauschenbach, TU Ilmenau

thDate of disputation: 31 of March 2008 Brandenburg University of Technology, Cottbus
Faculty of Environmental Science and
Process Engineering




Investigating Ecological Indicators of Freshwater
Ecosystems Using Signal Analysis Methods


A dissertation submitted in partial fulfilment of the requirements for the
Degree of Ph.D. in Environmental and Resource Management under
the Department of Ecosystems and Environmental Informatics.



by
Jean Duclos Alegue Feugo, M.Sc.



Approved by supervisors
Univ. - Prof. Dr. rer. nat. habil. Albrecht Gnauck, BTU Cottbus

Priv. - Doz. Dr. - Ing. habil. Thomas Rauschenbach, TU Ilmenau

Declaration



I, Jean Duclos Alegue Feugo, declare that this dissertation is solely the result of
my effort and has never been submitted in another institution as a requirement
for any certificate. The dissertation was an independent investigation under the
supervision of Prof. Dr. habil. Albrecht Gnauck (main supervisor) and Priv. -
Doz. Dr. habil. Thomas Rauschenbach (second supervisor). All the sources
used for the writing of this dissertation have been adequately referenced.




Jean Duclos Alegue Feugo (M.Sc.)-------------------
Dept. of Ecosystem and Environmental Informatics, BTU











1 i 50
Dedication



I dedicate this work to my Mum and late Dad who always taught me that
excellence is granted to a man only as the reward of hard work.



















1ii 51
Acknowledgements



Without the comfort, wisdom, strength and joy from the Lord Jesus, this
dissertation would not have been possible. The encouragement and financial
support from my entire family enabled me to take this challenge to the end. My
professor, Albrecht Gnauck, spent quality time in training me and pushing me to
work harder and harder so as to develop the necessary skills required for a
PhD. I also express my gratitude to my second supervisor, PD Dr.
Rauschenbach who was very busy, but took quality time to advice me on how
to improve my work. My colleagues Shaffi Noor, Shouke wei, Ralf Heinrich,
Bernhard Luther and Hartmut Nemitz all contributed in creating a very nice
working environment.













iii
152
Abstract



Human life depends on water of good quality. Freshwater ecosystems are
being degraded as a result of anthropogenic activities. Managing freshwater
resources require a good understanding of the dynamics of the processes
affecting water quality and the interrelationship existing between them. Signal
analysis methods are used to extract information from water quality time series.
The information obtained from such analysis is required for developing dynamic
models as an aid in investigating the outcome of different management
scenarios. They are equally useful in determining the appropriate sampling
frequency required for monitoring ecological indicators. Modern methods
developed in other field such as mathematical statistics need to be investigated
in the fields of water quality management so as to enhance the knowledge of
the functioning and the structure of water bodies.
Classical methods consisting of time domain and frequency domain methods in
combination with a modern method, wavelet analysis, were used to extract
information from water quality indicators from the River Havel in the State of
Brandenburg in Germany. The indicators were dissolved oxygen, chlorophyll-a
and water temperature which are respectively chemical, biological and physical
indicators. The time domain methods revealed the behavior of the signal across
time as well as the relationship between them. The frequency domain methods
proved quite inadequate because the signals from water quality are non-
stationary with changing variance across time. The wavelet methods were quite
good in unraveling the behavior of these signals at different time-scales.
This analysis revealed that the high frequency changes have no significant
effect on the long term dynamics of water quality signals. Given that only the
low frequency components influence the long term behavior of these signals, it
was found that it makes more sense to sample most of the signals at a weekly
or two weekly intervals so as to avoid noisy or redundant information. In
15iv3
addition, the time-scale decomposition allows for noisy or redundant
information that blurs the long term dynamics thereby negatively affecting the
quality of models to be detected and kicked out. Moreover, it was also found
that the use of a time delay in a dynamic model should be based on the delay
from the time-scale that influence the long term dynamics the most in the
freshwater body by the help of the wavelet cross-correlation rather than the
classical cross-correlation. Finally, the same indicator from different water
bodies of the same watershed portrayed different time and frequency
dependent behavior implying that each freshwater body needs to be uniquely
investigated. Applying the same management techniques to different water
bodies without prior investigation will not be sound.
Freshwater ecosystems are more and more threatened by phenomena such as
global warming, pharmaceuticals in water bodies, invasive species requiring
more investigation on the applicability of tools developed in other fields of
science in the field of water resource management. Enhanced knowledge will
improve the existing knowledge on the structure and functioning of freshwater
bodies, the quality of models developed as management decision aid and the
quality of the data used for decision making.














v
154
Table of Contents



Declaration................................................................................................ i
Dedication ................................................................................................ ii
Acknowledgement.................................................................................. iii
Abstract................................................................................................... iv
Abbreviations ......................................................................................... ix
List of Symbols....................................................................................... x
List of Figures........................................................................................xiii
List of Tables .........................................................................................xvi
1 Introduction.......................................................................................1
2 Pollution and Indicators of Freshwater Ecosystems....................8
2.1 Pollution and pollutants of freshwater ecosystem......................... 9
2.1.1 Oxygen demanding wastes ........................................................... 10
2.1.2 Nutrients ........................................................................................ 11
2.1.3 Suspended solids .......................................................................... 12
2.1.4 Toxic organic and inorganic pollutants........................................... 13
2.1.5 Microbial contaminants.................................................................. 14
2.1.6 Thermal pollution ........................................................................... 14
2.1.7 Some health impacts ..................................................................... 15
2.2 Freshwater quality indicators ........................................................ 17
2.2.1 Types of water quality indicators ................................................... 18
2.2.2 Use of indicators............................................................................ 21
2.2.3 Essential freshwater quality indicators........................................... 23
2.2.3.1 Dissolved oxygen and biochemical oxygen demand .............. 23
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155
2.2.3.2 Nitrogen and phosphorus ....................................................... 26