Modeling Spatial Distribution of Some Contamination within the Lower Reaches of Diyala River Using IDW Interpolation

The aim of this research was to simulate the water quality along the lower course of the Diyala River using Geographic Information Systems (GIS) techniques. For this purpose, the samples were taken at 24 sites along the study area. The parameters: total dissolved solids (T.D.S), total suspended soli...

Full description

Saved in:
Bibliographic Details
Published in:Sustainability 2018-01, Vol.10 (2), p.22
Main Authors: Madhloom, Huda, Al-Ansari, Nadhir, Laue, Jan, Chabuk, Ali
Format: Article
Language:English
Subjects:
Chromium
Computer simulation
Contamination
Correlation coefficient
Correlation coefficients
Environmental indicators
Environmental monitoring
Geographic information systems
Indicators
Iron
Manganese
Model accuracy
Pollutants
Pollution control
Pollution indicators
Pollution monitoring
Quality standards
Rivers
Spatial distribution
Sustainability
Total dissolved solids
Total suspended solids
Water analysis
Water pollution
Water quality
Water quality standards
Water sampling
Citations: Items that this one cites
Online Access:Get full text
Tags: Add Tag
No Tags, Be the first to tag this record!
Description
Summary:The aim of this research was to simulate the water quality along the lower course of the Diyala River using Geographic Information Systems (GIS) techniques. For this purpose, the samples were taken at 24 sites along the study area. The parameters: total dissolved solids (T.D.S), total suspended solids (T.S.S), iron (Fe), copper (Cu), chromium (Cr), and manganese (Mn) were considered. Water samples were collected on a monthly basis for a duration of five years. The adopted analyzing approach was tested by calculating the mean absolute error (MAE) and the correlation coefficient (R) between observed water samples and predicted results. The result showed a percentage error less than 10% and significant correlation at R > 89% for all pollutant indicators. It was concluded that the accuracy of the applied model to simulate the river pollutants can decrease the number of monitoring station to 50%. Additionally, a distribution map for the concentrations’ results indicated that many of the major pollution indicators did not satisfy the river water quality standards.
ISSN:2071-1050
2071-1050
DOI:10.3390/su10010022