Using spatio-temporal Markov model for flood mapping: the case study of Yialias River in Cyprus

Dimitrios D. Alexakis; Aristeidis Koutroulis; Manolis Gryllakis; Athos Agapiou; Kyriacos Themistocleous; Ioannis Tsanis; Diofantos G. Hadjimitsis

doi:10.1117/12.2029276

16 October 2013 Using spatio-temporal Markov model for flood mapping: the case study of Yialias River in Cyprus

Dimitrios D. Alexakis, Aristeidis Koutroulis, Manolis Gryllakis, Athos Agapiou, Kyriacos Themistocleous, Ioannis Tsanis, Diofantos G. Hadjimitsis

Author Affiliations +

Proceedings Volume 8887, Remote Sensing for Agriculture, Ecosystems, and Hydrology XV; 88870U (2013) https://doi.org/10.1117/12.2029276
Event: SPIE Remote Sensing, 2013, Dresden, Germany

Abstract

Flooding is one of the most common disasters worldwide. This paper strives to highlight the hydrological effects of multi-temporal land use changes in flood hazard. The study area is Potamia basin established in the broader Yialias catchment basin located in Nicosia –Cyprus. The certain area has suffered from several flood disasters in the recent past. Initially, the land cover regime of the study area (last 20 years) was thoroughly studied using multi-temporal satellite (ASTER) and implementing g sophisticated classification methodologies such as Object oriented analysis. Land use/ Land cover (LULC) maps for the periods of 1990, 2000 and 2010 were developed. All these maps were incorporated in the CA-Markov chain analysis model and the LULC map of 2020 was constructed. The Markov chain analysis describes the probability of land cover change from one period to another by developing a transition probability matrix between two different time periods. Following, the hydrological analysis was performed using the Hydrological Modeling System (HEC-HMS). HEC-HMS is designed to simulate the precipitation-runoff processes of dendritic watershed systems. The HEC-HMS model was set up in distributed mode, enabling the utilization of the spatial information on the land use via the Curve number coefficient. Thus, the 2020LULC map was incorporated in the hydrological model in order to predict the hydrological behavior of the catchment area for the next decade. The results were compared with the present hydrological regime and denoted the future increase of runoff due o the predicted extensive urban sprawl phenomenon.

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Dimitrios D. Alexakis, Aristeidis Koutroulis, Manolis Gryllakis, Athos Agapiou, Kyriacos Themistocleous, Ioannis Tsanis, and Diofantos G. Hadjimitsis "Using spatio-temporal Markov model for flood mapping: the case study of Yialias River in Cyprus", Proc. SPIE 8887, Remote Sensing for Agriculture, Ecosystems, and Hydrology XV, 88870U (16 October 2013); https://doi.org/10.1117/12.2029276

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KEYWORDS

Floods

Systems modeling

Calibration

Remote sensing

Satellites

Agriculture

Data modeling

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