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Natural Hazards and Earth System Sciences An interactive open-access journal of the European Geosciences Union
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Volume 14, issue 2 | Copyright

Special issue: Advances in meteorological hazards and extreme events

Nat. Hazards Earth Syst. Sci., 14, 413-426, 2014
https://doi.org/10.5194/nhess-14-413-2014
© Author(s) 2014. This work is distributed under
the Creative Commons Attribution 3.0 License.

Research article 26 Feb 2014

Research article | 26 Feb 2014

GIS and remote sensing techniques for the assessment of land use change impact on flood hydrology: the case study of Yialias basin in Cyprus

D. D. Alexakis1, M. G. Grillakis2, A. G. Koutroulis2, A. Agapiou1, K. Themistocleous1, I. K. Tsanis2,6, S. Michaelides3, S. Pashiardis3, C. Demetriou4, K. Aristeidou4, A. Retalis5, F. Tymvios3, and D. G. Hadjimitsis1 D. D. Alexakis et al.
  • 1Cyprus University of Technology, Department of Civil Engineering and Geomatics, Remote Sensing and Geo-Environment Lab, Limassol, Cyprus
  • 2Technical University of Crete, Department of Environmental Engineering, Chania, Crete, Greece
  • 3Cyprus Meteorological Department, Nicosia, Cyprus
  • 4Water Development Department, Nicosia, Cyprus
  • 5National Observatory of Athens, Athens, Greece
  • 6McMaster University, Department of Civil Engineering, Hamilton, Ontario, Canada

Abstract. Floods are one of the most common natural disasters worldwide, leading to economic losses and loss of human lives. This paper highlights the hydrological effects of multi-temporal land use changes in flood hazard within the Yialias catchment area, located in central Cyprus. A calibrated hydrological model was firstly developed to describe the hydrological processes and internal basin dynamics of the three major subbasins, in order to study the diachronic effects of land use changes. For the implementation of the hydrological model, land use, soil and hydrometeorological data were incorporated. The climatic and stream flow data were derived from rain and flow gauge stations located in the wider area of the watershed basin. In addition, the land use and soil data were extracted after the application of object-oriented nearest neighbor algorithms of ASTER satellite images. Subsequently, the cellular automata (CA)–Markov chain analysis was implemented to predict the 2020 land use/land cover (LULC) map and incorporate it to the hydrological impact assessment. The results denoted the increase of runoff in the catchment area due to the recorded extensive urban sprawl phenomenon of the last decade.

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