•  
  •  
 

Abstract

Karst is a hydrogeological environment of importance not only for its water resources potential but also for its scenic and economic potential, thereby increasing the intensity of human impact. The uniqueness of karst in this regard stems from its high sensitivity and vulnerability to imposed pressures and its distinctive response to these pressures. Therefore, a clear definition and formulation of the concept of ‘intrinsic vulnerability’ is essential for the design of vulnerability and/or management criteria of the karstic system as a resource. In this regard, the recharge rate, the amount of water passing through the unsaturated zone into the aquifer, is among the principal attributes of the intrinsic vulnerability. Where data and measurements are available for even large areas, recharge can be evaluated quantitatively on the basis of field measurements and the water balance equation. However, particularly for countries suffering from lack of essential data for a quantitative evaluation of the net recharge rate, the recharge can be estimated using some derived parameters such as the so called ‘Surface Cover Infiltration Index’ proposed in this paper. The DRASTIC method which is modified by using SCI, soil thickness and precipitation, allows the unique hydrological behavior of karst to be considered by redistributing of the intrinsic vulnerability values on the basis of hydrologic connections between neighboring cells. Following a detailed description of the SCI index and the modification of DRASTIC method for karst aquifers, a case study carried out to demonstrate this method is presented in this paper whose objective is to discuss and thus elaborate the suggested methodology. The Olimpos National Park area was selected because the great variation in lithology, landuse and topography. It was found that the relative vulnerability may vary particularly in the neighborhood of the highly vulnerable cells covered by carbonate rocks. The methodology was applied using ARC-GIS software. All spatial features used in computations were classified by the appropriate functions built into the software.

DOI

http://dx.doi.org/10.5038/1827-806X.33.1.4

Download

Included in

Geology Commons

Share

COinS