An Investigation on Sudden Change in Water Quality of Brahmaputra River Using Remote Sensing and GIS

The study of shoreline changes is essential for updating the changes in shoreline maps and management of natural resources as the shoreline is one of the most important features on the earth’s surface. Shorelines are the key element in coastal GIS that provide information on coastal landform dynamics. The purpose of this paper is to investigate shoreline changes in the study area and how it affects surface water quality using Landsat imagery from 1987 to 2016. The image processing techniques adopted involves supervised classification, object-based image analysis, shoreline extraction and image enhancement. The data obtained was analyzed and maps were generated and then integrated in a GIS environment. The results indicate that LULC changes in wetland areas increases rapidly during the years (1987-2016) from 34.83 to 38.96%, vegetation cover reduces drastically through the year which range from 30% to 20%. Polluted surface water was observed to have decreased from 30% to 20% during 1984-2010 and reduced by about 3% in 2016. In addition, the result revealed the highest level of erosion from 1987 to 2016 which is -49.60% against the highest level of accretion of 13.39% EPR and NSM -1400 erosion against 350 accretions. It was also observed that variations in shoreline changes affect the quality of surface water possibly due to shoreline movement hinterland. This study has demonstrated that through satellite remote sensing and GIS techniques, the Nigerian coastline can adequately be monitored for various changes that have taken place over the years.Key Words: Shoreline, Remote Sensing, Erosion, Accretion, GIS

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Analysis on the evolution trend of water resources and water environment in Xiangjiang River basin

MATEC Web of Conferences ◽

10.1051/matecconf/201824602030 ◽

2018 ◽

Vol 246 ◽

pp. 02030

Author(s):

Xingyi Xu ◽

Chuqiu Xiao ◽

Chunyan Hu ◽

Guiyuan Li ◽

Xiang Gao ◽

...

Keyword(s):

Water Quality ◽

Water Resources ◽

River Basin ◽

Water Environment ◽

Sudden Change ◽

Xiangjiang River ◽

Flood Season ◽

Xiangjiang River Basin ◽

Evolution Trend

According to the daily flow data collected by three representative hydrological stations in the Xiangjiang River basin which are the Guiyang station in the upstream section, the Hengshan station in the midstream section, and the Xiangtan station in the downstream section, and the water environment data collected from the Hunan Water Resources Bulletin, Mann-Kendal method was used to analyze the changes of the annual average flow of the Xiangjiang River basin in the past 20 years as well as the variation of water environment quality in the whole year, flood season and non-flood season. Based on these analysis, the evolution trend of water resources and water environment in the Xiangjiang River basin is further forecasted. The results show that the annual runoff of the upper reaches of the Xiangjiang River basin tends to be stable, and the runoff of the middle and lower reaches is decreasing. The water quality of the Xiangjiang River basin got deteriorated from 1996 to 2010. A sudden change occurred around 2012, and the water quality of the basin gradually improved.

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Remote sensing of the water quality of shallow lakes: A mixture modelling approach to quantifying phytoplankton in water characterized by high‐suspended sediment

International Journal of Remote Sensing ◽

10.1080/01431160500419311 ◽

2006 ◽

Vol 27 (8) ◽

pp. 1521-1537 ◽

Cited By ~ 108

Author(s):

A. N. Tyler ◽

E. Svab ◽

T. Preston ◽

M. Présing ◽

W. A. Kovács

Keyword(s):

Remote Sensing ◽

Water Quality ◽

Suspended Sediment ◽

Shallow Lakes ◽

Mixture Modelling ◽

Modelling Approach

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Remote sensing and GIS application for river runoff and water quality modeling in a hilly forested watershed of Japan

Journal of Hydroinformatics ◽

10.2166/hydro.2010.055 ◽

2010 ◽

Vol 13 (2) ◽

pp. 198-216 ◽

Cited By ~ 3

Author(s):

Binaya R. Shivakoti ◽

Shigeo Fujii ◽

Shuhei Tanaka ◽

Hirotaka Ihara ◽

Masashi Moriya

Keyword(s):

Remote Sensing ◽

Water Quality ◽

Land Cover ◽

Spatial Information ◽

Remote Sensing And Gis ◽

Water Quality Modeling ◽

Model Verification ◽

Modeling Framework ◽

Area Index ◽

Distributed Modeling

The main objective of this study is to present a simplified distributed modeling framework based on the storage balance concept of a Tank Model and by utilizing inputs from remote sensing data and GIS analysis. The modeling process is simplified by (1) minimizing the number of parameters with unknown values and 2) retaining important characteristics (such as land cover, topography, geology) of the study area in order to account for spatial variability. Remote sensing is used as a main source of distributed data and the GIS environment is used to integrate spatial information into the model. Remote sensing is utilized mainly to derive land cover, leaf area index (Lai) and transpiration coefficient (Tc). Topographic variables such as slope, drainage direction and soil topographic index (Tindex) are derived from a digital elevation model (DEM) using GIS. The model is used to estimate evapotranspiration (Et) loss, river flow rate and selected water quality parameters (CODMn and TP). Model verification adopted a comparison of estimated results with observed data collected at different temporal scales (storm events, daily, alternate days and every 10 days). A simplified distributed modeling framework coupled with remote sensing and GIS is expected to be an alternative to complex distributed modeling processes, which required values of parameters usually unavailable at a grid scale.

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