Using Spatial Data for Geo-Environmental Studies [Elektronische Ressource] / Khaled Haider. Betreuer: Wolfram Mauser

Khaled Haider

Informations

• Publié par: ludwig-maximilians-universitat_munchen
• Publié le: 01 janvier 2011
• Nombre de lectures: 87
• Langue: English
• Poids de l'ouvrage: 9 Mo

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USING SPATIAL DATA FOR GEO-ENVIRONMENTAL
STUDIES




A thesis submitted to the Faculty of Geosciences at Ludwig-
Maximilians-University, Munich in partial fulfilment of the
requirements for the Ph.D. degree.



By
Khaled Haider
From Damascus, Syria

September 2011
















1. Referee: Prof. Dr. Wolfram Mauser
2. Co-Referee: Prof. Dr. Ralf Ludwig


Date of Disputation: 23 September 2011



“The important thing is not to
stop questioning“
-Albert Einstein















Acknowledgements
All praise is due to Almighty ALLAH (God) for granting me the health, strength, and
time to complete this work. I would also like to express my deepest gratitude and
appreciation to all those people who have directly or indirectly contributed to the
successful completion of this study. First of all, I would like to thank my PhD
supervisor Prof. Dr. Wolfram Mauser, not only for giving me the opportunity to do my
PhD thesis at the Ludwig-Maximilian-University in Munich (one of the most
prestigious universities in Europe), but also for having so much trust and confidence
in me. He provided me with his model PROMET, which was essential for the
successful fulfilment of this thesis. I did make much profit from his extensive
knowledge and experience in the field of environmental modelling in general and in
hydrological modelling in particular. For his continuous guidance, encouragement,
support, fruitful suggestions, constructive criticism, and patience throughout the
course of this study, I would like to thank him profoundly. I would also like to express
my gratitude to the Syrian Ministry of Higher Education for funding this work. Many
thanks go to the staff members of the following ministries and organization in Syria:
Ministry of Defence (the General Directorate of Meteorology); Ministry of Irrigation
(Directorate of Water Resources Management); Ministry of Agriculture and Agrarian
Reform (MAAR); General Organization of Remote Sensing (GORS); Arab Center for
the Studies of Arid Zones and Dry Lands (ACSAD) for providing some of the data
used in this study. I am particularly grateful to Prof. Dr. Ralf Ludwig for accepting to
spend his precious time in reviewing my thesis and giving me valuable comments
and suggestions. Special thanks go to my dear office-mates Dr. Markus Muerth and
Dr. Daniel Waldmann, not only for introducing me to the model PROMET and helping
me solve many technical computing problems that have arisen during the course of
this work, but also for being good friends. I would also like to extend my thanks to all
of my former and current colleagues (alphabetically arranged) Andrea Reiter, Dr.
Carola Weiss, Dr. Christoph Heinzellerr, Florian Schlenz, Florian Zabel, Franziska
Kock, Inga May, Johanna Dall’ Amico, Lu Dong, Lu Gao, Matthias Locherer, Dr.
Matthias Bernhard, Dr. Monika Prasch, Monika Tepfenhart, Ruth Weidinger, Dr. Sara
Stober, Sascha Berger, Susan Niebergall, Tamara Avellan, Dr. Thomas Marke and
Toni Frank for their unending support and encouragement. In addition, particular
appreciations and thanks go to Dr. Florian Siebel, Dr. Heike Bach, Dr. Ingo Keding,
Dr. Jochen Henkel, Prof. Dr. Karsten Schulz, Prof. Dr. Natascha Oppelt, Prof. Dr.
Ralf Ludwig, Dr. Roswitha Stolz, Dr. Tobias Hank and Prof. Dr. Ulrich Strasser, who
have always helped me with scientific advice.
Last, but not least, I’d like to thank my family, father, mother, lovely sisters and
brothers for supporting me for such a long time and being so patient with me. My
final, and most heartfelt, acknowledgment must go to my wife “Ola” for her
unconditional love, constant encouragement and unwavering faith in me.


I
Abstract
The physically-based spatially-distributed model PROMET (Processes of Radiation,
Mass and Energy Transfer) is applied to the Greater Damascus Basin, which is
considered as one of the most important basins in Syria, to serve as a case study of
using spatial data for Geo-environmental studies. Like most areas of the Middle East,
the study area is characterized by large temporal and spatial variations in
precipitation and by limited water resources. Due to the increasing water demand
caused by the economic development and the rapid growth of population, the study
area is expected to suffer from further water shortages in the future. This highlights
the necessity of developing an integrated Decision Support System (DSS) to
evaluate strategies for efficient and sustainable water resources management in the
basin, taking into consideration global environmental changes and socio-economic
conditions. The work presented here represents the first steps toward achieving this
goal through applying a distributed hydrological model (an important component of
any integrated DSS for water resources management) to the Greater Damascus
Basin utilizing different types of spatial data used as time-dependent (e.g.,
meteorology) and time-independent (e.g., topography and soil) input parameters. The
model PROMET, which was developed within the GLOWA-Danube project as part of
the decision support system DANUBIA, is run on an hourly time step (for the period
from 1991 to 2005) and a 180*180m spatial resolution to simulate the water and
energy fluxes in this basin. The model is embedded within a raster-based GIS-
structure which facilitates the integration of the diverse types of spatial data. The
spatial information related to topography (such as elevation, slope, and exposition)
as well as those related to runoff routing (such as upstream-area, channel width, and
downstream proxel) are automatically extracted from Digital Elevation Model (Shuttle
Radar Topography Mission, SRTM-90m DEM). The spatial patterns of the different
land use/land cover classes are derived from remote sensing data (classification of a
cloud-free LANDSAT 7 ETM+ image using the supervised classification algorithm).
The spatial fields of meteorological input data are provided on an hourly basis
through spatiotemporal interpolation of the measurements of the available weather
stations. Spatial information about the soil texture is provided through generalization
and aggregation of the soil type classes of the Soil Map of Syria (prepared by
USAID) and transferring the soil types to texture classes. Several pedotransfer
functions are then used to estimate the soil hydraulic properties for each soil texture
class (and each soil layer) found in the study area. While plant physiological
parameters (which are assumed to be static, such as minimum stomatal resistance)
are estimated for each vegetation class using information taken from literature
sources, the temporal evolution of Albedo and Leaf Area Index (LAI) are derived from
five cloud-free LANDSAT-7 images acquired at different seasons of the year.
The goodness of the results obtained by the model PROMET are verified and/or
validated by comparing them either with their corresponding data observed in the
II
filed or with remote sensing-derived information (e.g., snow cover). Two
subcatchments are selected for the purpose of calculating the spatially-distributed
annual water balances. The results indicate that the modelled mean annual runoff
volume fits well with the measured discharge for both chosen subcatchment. In
addition, the simulated discharge is compared to the observed one (at seven gauge
stations) on a monthly basis, covering the whole simulation period (15 years). The
results of the regression analysis for each of these gauge stations (with slope of
regression line ranges from 0.79 to 1.04; coefficient of determination 0.69-0.90; and
Nash-Sutcliffe Coefficient 0.73-0.95) indicate that there is a good correlation between
simulated and observed monthly mean discharge volumes.
































III
TABLE OF CONTENTS
Acknowledgements …………………………………………………………………....... I
Table of Contents ………………………………………………………………………. IV
List of Figures …………………………………………………………………………. .VII
List of Tables ………………………………………………………………………. …..XII
List of Acronyms ……………………………………………………………………... XIII
List of Symbols …………………………..………………………………………….... XV

1. Introduction …………………………………………………………………………. 1
1.1. Definitions ………………………………………………………………………..... 1
1.1.1. Spatial Data ………………………………………………………………... 1
1.1.2. Geo-environmental Studies ………………………..... 2
1.2. The Role of Spatially-distributed hydrological modelling in Water Resources
Management …………………………………………………………………….... 3
1.3. Motivation, objectives and the structure of the thesis ……………………...…. 4

2. The Study Area …………………………………………………………………….… 6
2.1. General remarks ……………………………………………………………….…6
2.2. Physical Environment ………………………….…7
2.2.1. Morphology / Topography …………………………………………….…..7
2.2.2. Geology ………………………………………………………………….…7