An analytical review of physical blue and green water scarcity in terms of agricultural use, and its amenability to economic interpretation, is presented, employing more than 600 references. The main definitions and classifications involved and information about reserves and resources are critically analyzed, blue and green water scarcity are examined along with their interchange, while their causal connection with climate in general is analyzed along with the particular instances of Europe, Africa, Asia and the WANA region. The role of teleconnections and evaporation/moisture import-export is examined as forms of action at a distance. The human intervention scarcity driver is examined extensively in terms of land use land cover change (LULCC), as well as population increase. The discussion deals with following critical problems: green and blue water availability, inadequate accessibility, blue water loss, unevenly distributed precipitation, climate uncertainty and country level over global level precedence. The conclusion singles out, among others, problems emerging from the inter-relationship of physical variables and the difficulty to translate them into economic instrumental variables, as well as the lack of imbedding uncertainty in the underlying physical theory due to the fact that country level measurements are not methodically assumed to be the basic building block of regional and global water scarcity.
An analysis of the following aspects of water economics was undertaken: Water as an Economic and Social Good, Modes of Government Intervention, Water Scarcity in Economic Theory and Agricultural Water Management Changes, with the support of over 300 sources. Emphasis was placed on the connection with primary aspects of economics, in contrast to the usual applicative expositions found in water economics literature. This is a novel approach comparing international bodies’ definitions with economic theory at primary level which leads, upon occasion, to serious contradictions which were exhibited in broad lines. Furthermore, it compares the global implications of these definitions to the existing reality at country level, and a lack of bilateral consistency is exhibited. The uniform picture presented at global level is shown to become a non-uniform one at country level, where sharp variations in resources and availability form a competitive market between nations, and water-rich countries already possessing a competitive advantage are shown to attain a water-based comparative advantage as well. It is shown that although at country level water has a quasi-public good character with minimal private good market existence, this is achieved with the existence of a private goods market at international level via international trade in virtual water. A novel approach to management problems stemming from authority levels starting at global level and ending at farm level is analyzed and redressed by employing reality gap theory.
<p>Complex Time Methods and Chameleon Scalar Fields in the Dynamics of Spatial Extremes</p><p>Dionysia Panagoulia1 and Kalomoira Zisopoulou 2</p><p>1 School of Civil Engineering, Department of Water Resources and Environmental Engineering, National Technical University of Athens, Zografou, Greece. E-mail dpanag@hydro.ntua.gr</p><p>&#160;2 Travaux Publics, Becket House, London, United Kingdom</p><p>It is shown that complex time in classical physics may transform the action functional Lagrangian and Lagrangian density processes to, among others, energy descriptive functionals. By imposing restrictions in the problem coordinate space as per need, such as Sobolev or Hardy spaces, or to the complex time plane such as the two variable Hilbert Space dependent Bergman. Decomposition new results are obtained which facilitate a better understanding of the mechanism governing spatial extremes in terms of flows. <br>The introduction of Khoury-Weltman type chameleon scalar fields will, by the recognition of existing oscillatory patterns, pave a connective chain of momenta between smaller and larger objects which will uncover the causal relationships between them which will allow for variable reduction in multivariate methods.</p>
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