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Water Resources Management

, Volume 24, Issue 14, pp 3757–3772 | Cite as

Remote Sensing and GIS Innovation with Hydrologic Modelling for Hydroelectric Power Plant (HPP) in Poorly Gauged Basins

  • H. Gonca Coskun
  • Ugur Alganci
  • Ebru Eris
  • Necati Agıralioglu
  • H. Kerem Cigizoglu
  • Levent Yilmaz
  • Z. Fuat Toprak
Article

Abstract

Within the last two decades, modelling of rainfall–runoff has become an important topic in water resources assessment due to increasing water demand and energy, particularly in the determination of hydropower potential. In addition to remote sensing (RS) and geographical information systems (GIS), with the development on satellite technologies, it becomes possible to asses rapid and economic solutions to determine a practical rainfall–runoff relation, particularly poorly gauged or ungauged basins. In this paper, Solakli Watershed which is located in Eastern Black Sea Region of Turkey is selected as the study area. To determine the hydroelectric water potential in a poorly gauged basin, basin boundary and area, minimum maximum and mean elevation, slope information of the basin have been derived from the digital elevation model (DEM) using remote sensing (RS) and geographical information systems (GIS) techniques. IRS P5 stereo satellite data with 2.5-m spatial resolution has been used for deriving the DEM. This DEM is used to produce the flow direction and flow accumulation maps of the basin. Afterward, synthetic drainage network is obtained with the analysis of these maps. Using topographical data such as area, mean basin elevation and limited point observations of rainfall data; a regression model was derived for the whole watershed. This regression model was validated on a sub-basin with satisfactory results using mean areal rainfall which was calculated isohyetal map produced by kriging method. Suggested hydropower station points are also determined.

Keywords

Hydrologic modelling Remote sensing Geographical information systems Digital elevation model Stereo satellite data Regression analysis 

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Copyright information

© Springer Science+Business Media B.V. 2010

Authors and Affiliations

  • H. Gonca Coskun
    • 1
  • Ugur Alganci
    • 1
  • Ebru Eris
    • 2
  • Necati Agıralioglu
    • 2
  • H. Kerem Cigizoglu
    • 2
  • Levent Yilmaz
    • 2
  • Z. Fuat Toprak
    • 3
  1. 1.Department of Geodesy and Photogrammetry, Faculty of Civil EngineeringIstanbul Technical University (ITU)MaslakTurkey
  2. 2.Department of Hydraulics, Faculty of Civil EngineeringIstanbul Technical University (ITU)MaslakTurkey
  3. 3.Faculty of Civil EngineeringDicle University (DU)DiyarbakirTurkey

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