Spatial Modeling Principles in Earth Sciences
A comprehensive presentation of spatial modeling techniques used in the earth sciences, this book also outlines original techniques developed by the author. Data collection in the earth sciences is difficult and expensive. It requires special care to gath
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Zekai S¸en
Spatial Modeling Principles in Earth Sciences
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Prof. Zekai S¸en ˙Istanbul Technical University Civil Engineering Faculty Campus Maslak 34469 Istanbul Turkey [email protected]
ISBN 978-1-4020-9671-6 e-ISBN 978-1-4020-9672-3 DOI 10.1007/978-1-4020-9672-3 Springer Dordrecht Heidelberg London New York Library of Congress Control Number: 2009920941 c Springer Science+Business Media B.V. 2009 No part of this work may be reproduced, stored in a retrieval system, or transmitted in any form or by any means, electronic, mechanical, photocopying, microfilming, recording or otherwise, without written permission from the Publisher, with the exception of any material supplied specifically for the purpose of being entered and executed on a computer system, for exclusive use by the purchaser of the work. Printed on acid-free paper Springer is part of Springer Science+Business Media (www.springer.com)
This work is dedicated to my students all over the world with the hope that they will produce more advanced scientific works in different aspects of earth sciences
Preface
Earth sciences phenomena have evolved in time and space jointly, but in practical applications their records are available as temporal records, spatial measurements, or both. If the records are available only spatially, then they are one realization from the regionalized variable (ReV), which has geometrical locations as longitudes (or easting) or latitudes (or northing), with a record of the earth sciences phenomena at the same location, Hence, in practical applications a set of triplicate values (longitude, latitude, record) provides the realization out of many realizations from the ReV concerned. The worth of data in earth sciences and geology is very high since most of the interpretations and decisions are based on their qualitative and quantitative information content. This information is hidden in representative field samples, which are analyzed for the extraction of numerical or descriptive characteristics. These characteristics are referred to as data. Data collection in earth sciences is difficult, expensive, and requires special care for accurately representing the geological phenomenon. After all various parameters necessary for the description and modeling of the geological event, such as bearing capacity, effective strength, porosity, hydraulic conductivity, chemical contents, are hidden within each sample, they individually represent a specific point in space and time. Change of locations leads to another realization, which is different than the others, but they are statistically indistinguishable from each other. This property provides a common basis for the development of convenient prediction models for the ReVs. In general, the collection of methodologies for modeling such a set of triplicates falls within the geostatistical domain, which has been in practical use for the past four decades. Kriging is the methodology that is used invariably in earth sciences for the regional (spatial) prediction of spatial variability. Prio
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