A Novel Water Quality Index for Iraqi Surface Water

Abstract

The study aims to build a water quality index that fits the Iraqi aquatic systems and reflects the environmental reality of Iraqi water. The developed Iraqi Water Quality Index (IQWQI) includes physical and chemical components. To build the IQWQI, Delphi method was used to communicate with local and global experts in water quality indices for their opinion regarding the best and most important parameter we can use in building the index and the established weight of each parameter. From the data obtained in this study, 70% were used for building the model and 30% for evaluating the model. Multiple scenarios were applied to the model inputs to study the effects of increasing parameters. The model was built 4 by 4 until it reached 17 parameters for 10 sampling times. Obviously, with the increasing number of parameters, the value of the index will change. To minimize the effect of eclipse that arises in WQI and to solve the problem of overlapping quality and pollution, this study has created another index linked with IQWQI, which included both the quality and the degree of pollution. The second index is called the Environmental Risk Index (ERI), where only the variables that exceed the permissible environmental limits were included. Sensitivity Analysis was done to predicate IQWQI and to determine the most influential parameters in the IQWQI score; two types of models were chosen for the run of the sensitivity test, which are the Artificial Neural Network Regression (ANNR) and Backward Linear Regression (BLR). The results of IWOI and ERI for freshwater use during the dry season were very poor water quality with a high degree of risk. While in the wet season, both indices' values ranged from poor water quality to very poor water quality with a high degree of risk.

Keywords

• ANNR, BLR, IQWQI, Iraq, Tigris River, Surface Water, Water Quality