Applications of Remote Sensing and GIS in Hydrological and Hydrogeological Studies

2022 ◽  
pp. 237-251
Author(s):  
Athar Hussain ◽  
Richa Madan ◽  
Vishal Kamboj
Keyword(s):  
Remote Sensing ◽  
Watershed Management ◽  
Spatial Information ◽  
Holistic Approach ◽  
Remote Sensing And Gis ◽  
Quality Of Water ◽  
Integrated Watershed Management ◽  
Vegetation Water ◽  
Hydrogeological Studies

Integrated watershed management is a holistic approach aimed at linking upstream and downstream areas. It encompasses preventing the watershed from being polluted and maintaining the quality of water and prevention of soil erosion. Remote sensing and GIS techniques play a crucial role in assessing watershed conditions through modeling. These techniques are also very helpful in acquiring the spatial information of the land use, land cover, vegetation, water resources, etc. With the available data, characteristics of aquifers can easily be deciphered. Remote sensing aids in identifying and assessing the topographical features and alienates the unnecessary ones. Integration of GIS with remote sensing along with hydrological, hydrogeological, geomorphologic studies will make the practice of integrated watershed management more effective. The primary aim of this chapter is to encompass the remote sensing and GIS technologies currently in use for watershed monitoring and management.

scholarly journals Integrated Remote Sensing and GIS Applications for Sustainable Watershed Management: A Case Study from Cyprus

10.5772/39307 ◽  
2013 ◽  
Author(s):  
Diofantos G. ◽  
Dimitrios D. ◽  
Athos Agapiou ◽  
Kyriacos Themistocleous ◽  
Silas Michaelides ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Watershed Management ◽  
Remote Sensing And Gis ◽  
Gis Applications

scholarly journals Priority Analysis of Remote Sensing and Geospatial Information Techniques to Water-Related Disaster Damage Reduction for Inter-Korean Cooperation

2020 ◽  
Vol 2020 ◽  
pp. 1-10
Author(s):  
Sunmin Lee ◽  
Sung-Hwan Park ◽  
Moung-Jin Lee ◽  
Taejung Song
Keyword(s):  
Remote Sensing ◽  
South Korea ◽  
North Korea ◽  
Spatial Information ◽  
Remote Sensing And Gis ◽  
Geospatial Information ◽  
Radar Images ◽  
Database Construction ◽  
The Social

The social and economic harm to North Korea caused by water-related disasters is increasing with the increase in the disasters worldwide. Despite the improvement of inter-Korean relations in recent years, the issue of water-related disasters, which can directly affect the lives of people, has not been discussed. With consideration of inter-Korean relations, a government-wide technical plan should be established to reduce the damage caused by water-related disasters. Therefore, the purpose of this study was to identify remote sensing and GIS techniques that could be useful in reducing the damage caused by water-related disasters while considering inter-Korean relations and the disasters that occur in North Korea. To this end, based on the definitions of disasters in South and North Korea, water-related disasters that occurred during a 17-year period from 2001 to 2017 in North Korea were first summarized and reclassified into six types: typhoons, downpours, floods, landslides, heavy snowfalls, and droughts. In addition, remote sensing- and GIS-based techniques in South Korea that could be applied to water-related disasters in North Korea were investigated and reclassified according to applicability to the six disaster types. The results showed that remote sensing and other monitoring techniques using spatial information, GIS-based database construction, and integrated water-related disaster management have high priorities. Especially, the use of radar images, such as C band images, has proven essential. Moreover, case studies were analyzed within remote sensing- and GIS-based techniques that could be applicable to the water-related disasters that occur frequently in North Korea. Water disaster satellites with high-resolution C band synthetic aperture radar are scheduled to be launched by South Korea. These results provide basic data to support techniques and establish countermeasures to reduce the damage from water-related disasters in North Korea in the medium to long term.

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

2020 ◽  
Vol 43 (7) ◽  
pp. 619-623
Author(s):  
Thota Sivasankar ◽  
Suranjana B. Borah ◽  
Ranjit Das ◽  
P. L. N. Raju
Keyword(s):  
Remote Sensing ◽  
Water Quality ◽  
Sudden Change ◽  
Remote Sensing And Gis ◽  
Brahmaputra River

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

2010 ◽  
Vol 13 (2) ◽  
pp. 198-216 ◽  
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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