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Civil-Comp Proceedings
ISSN 1759-3433
CCP: 102
PROCEEDINGS OF THE FOURTEENTH INTERNATIONAL CONFERENCE ON CIVIL, STRUCTURAL AND ENVIRONMENTAL ENGINEERING COMPUTING
Edited by:
Paper 191

Modeling the Soil Water Regime in the Framework of Climate Change Studies

M. Cisty, J. Skalova, M. Pasztorova, J. Bezak and T. Meszaros

Department of Land and Water Resources Management
Slovak University of Technology in Bratislava, Slovakia

Full Bibliographic Reference for this paper
M. Cisty, J. Skalova, M. Pasztorova, J. Bezak, T. Meszaros, "Modeling the Soil Water Regime in the Framework of Climate Change Studies", in , (Editors), "Proceedings of the Fourteenth International Conference on Civil, Structural and Environmental Engineering Computing", Civil-Comp Press, Stirlingshire, UK, Paper 191, 2013. doi:10.4203/ccp.102.191
Keywords: climate change, soil water modelling, data generation, impact study, support vector machines.

Summary
Global warming impacts the water cycle not only by changing regional precipitation and temperatures and their temporal variability, but also as a consequence of its affects on soil moisture dynamics, which is a crucial condition of crop production. Adaptation strategies, such as improved water management or the development of more efficient irrigation systems, will be important tools in limiting the adverse effects of expected climate changes. The characteristics of a water regime for such decision making can be obtained by the mathematical modeling of a soil water regime. This modeling depends on knowledge of the input data which are necessary for the numerical simulations. The aim of this paper is to contribute to solving this data acquisition task by using a data-driven methodology, namely support vector machines. The methodology is used for acquiring the most important inputs in such modelling, namely, groundwater levels. The results of the paper confirm that in soil water regime modeling, the effect of the limited availability of the data, which naturally exists in the context of climate change impact studies, has an acceptable effect on the final degree of precision and could be substituted by data modelling approach described in paper. This paper emphasizes the usefulness of the proposed symbiosis of data-driven and physically-based types of modeling.

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