Anthropogenic Impacts on Water Quality of River Nile and Marine Environment, Rosetta Branch Using Geospatial Analyses

Document Type : Original Article

Authors

1 Environmental Studies Department, National Authority for Remote Sensing and Space Sciences (NARSS), Cairo, Egypt

2 Marine Pollution Department, National Institute of Oceanography & Fisheries, Alexandria, Egypt.

Abstract

Present research focused on studying water quality of three ecosystems in Rosetta branch;
fresh River Nile, estuary and Sea water based on Landsat data and samples analyses. Two
multispectral Landsat images dated 26th of February 2017 and 1st of March 2018 provided the
necessary spectral data to this research. Nineteen surface water samples were collected on 18th
March 2017 and investigated for pH, EC, silicate, phosphate, nitrite, nitrate, organic matter (OM)
content and Nitrogen/Phosphorus ratio. The calibrated Landsat data, synchronized with the field
trip, was processed to produce Land use cover map (LULC), Vegetation (NDVI), built-up (NDBI)
and salinity indices (NDSI) to highlight the human activities in the adjacent areas. Statistical
analyses were carried out to correlate the existed land uses in 2017 with water quality
characteristics and to monitor spectral reflectance change in 2018 responding to water quality
change. NDVI showed positive correlations with nitrate (0.416), nitrite (0.517), silicate (0.272)
and N/P ratio (0.345) which confirmed the impact of agricultural activities on water nutrients.
Although urban areas occupied 4.87 %, they contributed to water OM levels (R= 0.488). Means
of nitrite, nitrate, phosphate and N/P followed the order; Estuary > River > Sea however for OM
and EC, they followed the order; Sea > Estuary > River. N/P ratio ranged from 12.91 to 31.52
which indicated that phosphorus is the limiting factor for bio-growth of algae in the three studied
environments. In this study, innovative model for calculating water phosphate was developed in
2017 which indicated a similar fluctuation in phosphate levels in 2018 within different locations.
It can be concluded that remote sensing facilitates the spatial identification of the potential
sources of water pollution and helps in the qualitative assessment of nutrients and organic
pollutant levels in water resources.

Keywords

Files

Share

How to cite

Statistics