Socio-Hydrological Vulnerability: A New Science through Remote Sensing and GIS

Mukesh Singh Boori; Vit VoAenAlek

Socio-Hydrological Vulnerability: A New Science through Remote Sensing and GIS

Mukesh Singh Boori * § Honorary/UK; Postdoc/USA; PhD/Brazil; Predoc/Belgium; MSc, BSc/India

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Vit VoAenAlek

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Palacky University Olomouc

Socio-Hydrological Vulnerability: A New Science through Remote Sensing and GIS

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Abstract

Socio-hydrological vulnerability is a new area of research that integrates people and their activities into water science. This type of research is important in water scare areas such as arid and semi-arid areas on the globe. The main objective of this type of research is to develop a socio-hydrological vulnerability index in semi-arid region by combining remote sensing, bio-geophysical and social data. In general, vulnerability is expressed as a function of the exposure, sensitivity and adaptive capacity of a region to natural disasters and climate change effects. The heart of water security is the ability of water systems to meet changing human and environmental needs. Sociohydrological vulnerability research ensures that decisions made about our water resources incorporate a range of values and perspectives about the meaning, value and use of water. Presently scientists bring an interest in human values, markets, social organizations and political institutions to the traditional focus of water science on climate, social and hydrology. It is a reality that natural disasters (such as drought and floods) results in sets of sociohydrological impacts starting with crop-yield failure, unemployment, erosion of assets, income decrease, poor nutrition and decreasing risk absorptive capacity, thereby increasing the vulnerability of the community. In addition, it is demonstrated that the severity of these social impacts is experienced differently and depends one hand on sociohydrological characteristics and on other hand on people’s exposure and characteristics, which are respectively named bio-geophysical, hydrology and social vulnerability. Mapping socio-hydrological vulnerability patterns across space and time helps to identify socially and bio-geophysical vulnerable areas and assists with climate change adaptation strategies in areas to projected socio-hydrological vulnerability.

References

20 Cites in Article

Reference Format

M Boori,V Vozenilek,K Choudhary (2014). Exposer Intensity, Vulnerability Index And Landscape Change Assessment In Olomouc, Czech Republic.
E Unknown Title.
M Boori,V Vozenilek (2014). Remote sensing and GIS for Socio-hydrological vulnerability.
M Boori,V Vozenilek,J Burian (2014). Landcover disturbances due to tourism.
J Brus,M Boori,V Vozenilek (2013). Detection and visualizations of ecotones -important landscape pattern under uncertainty.
M Boori,R Ferraro (2013). Microwave polarization and gradient ratio (MPGR) for global land surface phenology.
V Voženílek,P Morkesová,A Vondráková (2014). Cognitive aspects of map symbology in the world school atlases.
M Boori,R Ferraro (2012). Northern Hemisphere snow variation with season and elevation using GIS and AMSR-E data.
M Boori,V Amaro,A Targino (2012). Coastal risk assessment and adaptation of the impact of sea-level rise, climate change and hazards: A RS and GIS based approach in Apodi-Mossoro estuary, Northeast Brazil.
M Boori (2011). Avaliação de impacto ambiental e gestão dos recursos natuarias no estuário Apodi Mossoró, nordeste do Brasil.
M Boori,V Amaro (2011). Natural and ecoenvironmental vulnerability assessment through multi-temporal satellite data sets in Apodi valley region, Northeast Brazil.
Mukesh Boori,Komal Choudhary (2011). Remote Sensing for Vegetation and Climate Change.
M Evers,A Jonoski,C Maksimovic,L Lange,S Ochoa,J Cortés,A Almoradie,A Dinkneh (2012). Enhancing stakeholders` role by collaborative modelling for urban flood risk reduction.
M Boori,V Amaro (2011). World Academy of Science, Engineering and Technology (WASET).
M Boori (2010). Coastal vulnerability, adaptation and risk assessment due to environmental change in Apodi-Mossoro estuary, Northeast Brazil.
M Boori,V Amaro,H Vital (2010). Coastal ecological sensitivity and risk assessment: A case study of sea level change in Apodi River (Atlantic Ocean), Northeast Brazil.
V Nevtipilova,J Pastwa,M Boori,V Vozenilek (2014). Testing artificial neural network (ANN) for spatial interpolation.
M Boori,V Amaro (2010). International Journal of Environmental Sciences.
M Boori,V Amaro (2010). Land use change detection for environmental management: using multi-temporal, satellite data in Apodi Valley of northeastern Brazil.
Vít Voženílek,Jan Michalík,Alena Vondráková,Alžběta Brychtová (2014). Mapping and Visualisation of Activities in Special Education.

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Funding

No external funding was declared for this work.

Conflict of Interest

The authors declare no conflict of interest.

Ethical Approval

No ethics committee approval was required for this article type.

Data Availability

Not applicable for this article.

How to Cite This Article

Mukesh Singh Boori, Vit VoAenAlek. 2014. "Socio-Hydrological Vulnerability: A New Science through Remote Sensing and GIS". Global Journal of Research in Engineering - E: Civil & Structural GJRE-E Volume 14 (GJRE Volume 14 Issue E4).

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GJRE Volume 14 Issue E4

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Journal Specifications

Crossref Journal DOI 10.17406/gjre

Print ISSN 0975-5861

e-ISSN 2249-4596

Keywords

GIS Remote Sensing socio-hydrological vulnerability

Classification

GJRE-E Classification FOR Code: 291099p

Submission ReceivedDecember 12, 2013
Peer Review Double Blind
Handling Editor
Accepted January 1, 2014
Published January 15, 2014

Version of record

v1.2

Issue date

September 25, 2014

Language

English

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Article Matrices

Total Score: 122

Country: Czech Republic

Subject: Global Journal of Research in Engineering

Authors: Mukesh Singh Boori, Vit VoAenAlek (PhD/Dr. count: 0)

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