Assessment and Prediction of Saline Sea Water Transport in Groundwater Using 3-D Numerical Modelling

Abstract

This paper presents the application of a three-dimensional numerical model to the Al-Raudhatain and Umm A-Aish fresh water aquifers located in north Kuwait. The two aquifers have been polluted by saline sea water imported to extinguish the oil well fires during the Gulf war. A time-variant salinity transport model was calibrated simultaneously with the transient groundwater flow system to assess the impact of saline sea water. Variably saturated flow and transport were modelled. The results of the salinity transport model suggest that although the fresh water–saline water interface, as defined by the 1500 mg/L contour, has moved towards the centre of the lens, in some areas up-gradient of the fresh water recharge, the extent of the fresh water lens has actually increased slightly in the down-gradient areas. After 23 years (simulation period 1990–2013), the areal extent of the total dissolved solids plume is estimated at 27 and 29% of the Al-Raudhatain and Umm A-Aish fresh water bodies, respectively. Under the scenarios assumed, there are large masses of salts stored in the soil profile that will leach over time to the water table. The total dissolved solids concentrations are predicted by the model to decrease to 4500 mg/L from 7800 mg/L, after 73 years (simulation period 1990–2063) from the moment the saline sea water was added. The predicted total dissolved solids concentration simulation provides a worst-case scenario of the likely extent of contaminant movement in groundwater in the two fresh water fields. Solute transport modelling has become increasingly important tool for interpreting groundwater quality data and processes relevant to natural and contaminant aquifer systems to a wide range of real-world groundwater quality problems. Further data, from drilling sampling and other testing and experimentations should help clarify the assumptions made and assist in updating the solute transport modelling effort which helps to provide insights into the past and present behavior, and allows to predict water quality management scenarios.