American Journal of Biological and Environmental Statistics

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Geographical Information Based Evaluation System for Drought

Received: 09 December 2016    Accepted: 23 February 2017    Published: 14 December 2017
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Abstract

Drought is one of the major natural hazards affecting the environment and economy of countries worldwide. As a natural hazard, drought is best characterized by multiple climatological and hydrological parameters. An understanding of the relationships between these two sets of parameters is necessary to develop measures for mitigating the impacts of droughts. Droughts are recognized as an environmental disaster and have attracted the attention of environmentalists, ecologists, hydrologists, meteorologists, geologists, and agricultural scientists.. Low rainfall has mainly caused droughts and subsequent reduction in agricultural production. Droughts have been a recurring feature of the Indian climate, therefore, study of historical droughts may help in the delineation of major areas facing drought risk and thereby, management plans can be formulated by the government authorities to cope with the disastrous effects of this hazard. In recent years, Geographic Information System (GIS) and Remote Sensing (RS) have played a key role in studying different types of hazards, either natural or man-made. This paper emphasizes upon the application of RS and GIS in the field of drought risk evaluation. The study area taken is a part of the Jamnagar district of Gujarat between latitude 22°19′46′′N to 22°46′01′′N and longitude 70°20′56′′E to 70°47′34′′E. The study was conducted with satellite images of year 1977, 1990 and 1999. Data has been acquired mainly from two sources, firstly Normalized Difference Vegetation Index (NDVI) obtained from satellite sources and secondly rainfall obtained from ground rainfall stations record. In the present paper, an effort has been made to derive drought risk areas facing agricultural as well as meteorological drought by use of Normalized Difference Vegetation Index (NDVI) from Landsat images. NDVI values reflect the different geographical conditions quite well. The NDVI and rainfall was found to be highly correlated. It is therefore concluded that temporal variations of NDVI are closely linked with precipitation.

DOI 10.11648/j.ajbes.20170304.12
Published in American Journal of Biological and Environmental Statistics (Volume 3, Issue 4, December 2017)
Page(s) 49-53
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This is an Open Access article, distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution and reproduction in any medium or format, provided the original work is properly cited.

Copyright

Copyright © The Author(s), 2024. Published by Science Publishing Group

Keywords

Drought, GIS, RS, NDVI

References
[1] Hagman G., “Prevention Better than cure: Report on Human and Natural Disasters in the Third World”, Swedish Red Cross, Stockholm (1984).
[2] Wilhite, D. A., “Drought: A Global Assessment, Hazards and Disasters”, A series of Definitive Major Works, vol. 2. Routledge Publishers, London. (2000).
[3] Kogan, F. N., “Global drought watch from space.” Bull. Am. Meteorol. Soc. 78, 621–636, (1997).
[4] Palmer, W. C., “Meteorological drought.” Research Paper 45, U. S. Department of Commerce, Weather Bureau, Washington, DC. (1965).
[5] Palmer, W. C., “Keeping track of crop moisture conditions, nationwide: the new crop moisture index.” Weather wise, 21 (4), 156–161, (1968).
[6] McKee, T. B., Doesken, N. J., Kleist, J., “The relationship of drought frequency and duration to time scales.” Proceedings of the 8th Conference on Applied Climatology, American Meteorological Society, Anaheim, CA, Boston, MA, 17–22 January, pp. 179–184. (1993).
[7] Shafer, B. A., Dezman, L. E., “Development of surface water supply index (SWSI) to assess the severity of drought conditions in snow pack runoff areas.” Proceedings of the 50thWestern Snow Conference, Colorado State University Press, Reno, NV/Fort Collins, CO, pp. 164–175, (1982).
[8] Tucker, C. J., H. E. Dregne, and W. W. Newcomb, “Expansion and contraction of the Sahara Desert from 1980 to 1990.” Science, 253:299-301, (1991).
[9] Thenkabail, P. S., M. S. D. N. Gamage, “The Use of Remote Sensing data for drought assessment and monitoring in south west Asia.” Colombo, Srilanka, International Water Management Institute: pp.1-23. (2004).
[10] Z. Wang, P. Wang, "Using MODIS Land Surface Temperature and Normalized Difference Vegetation Index products for Monitoring Drought in the Southern Great Plains, USA." International Journal of Remote Sensing Vol.25 (No.1): pp. 61-72. (2004).
[11] Farrar, T. J., S. E. Nicholson, et al. "The influence of soil type on the relationships between NDVI, rainfall and soil moisture in semiarid Botswana:II. NDVI response to soil."ote Sensing of Environment Vol.50: pp. 121-133. (1994).
Author Information
  • Department of Civil Engg., G B Pant Engg Collge, Pauri, Uttarakhand, India

  • Department of Water Resource Management, IIT Roorkee, Uttarakhand, India

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    Dilip Kumar, Sushil Kr. Himanshu. (2017). Geographical Information Based Evaluation System for Drought. American Journal of Biological and Environmental Statistics, 3(4), 49-53. https://doi.org/10.11648/j.ajbes.20170304.12

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    Dilip Kumar; Sushil Kr. Himanshu. Geographical Information Based Evaluation System for Drought. Am. J. Biol. Environ. Stat. 2017, 3(4), 49-53. doi: 10.11648/j.ajbes.20170304.12

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    Dilip Kumar, Sushil Kr. Himanshu. Geographical Information Based Evaluation System for Drought. Am J Biol Environ Stat. 2017;3(4):49-53. doi: 10.11648/j.ajbes.20170304.12

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  • @article{10.11648/j.ajbes.20170304.12,
      author = {Dilip Kumar and Sushil Kr. Himanshu},
      title = {Geographical Information Based Evaluation System for Drought},
      journal = {American Journal of Biological and Environmental Statistics},
      volume = {3},
      number = {4},
      pages = {49-53},
      doi = {10.11648/j.ajbes.20170304.12},
      url = {https://doi.org/10.11648/j.ajbes.20170304.12},
      eprint = {https://download.sciencepg.com/pdf/10.11648.j.ajbes.20170304.12},
      abstract = {Drought is one of the major natural hazards affecting the environment and economy of countries worldwide. As a natural hazard, drought is best characterized by multiple climatological and hydrological parameters. An understanding of the relationships between these two sets of parameters is necessary to develop measures for mitigating the impacts of droughts. Droughts are recognized as an environmental disaster and have attracted the attention of environmentalists, ecologists, hydrologists, meteorologists, geologists, and agricultural scientists.. Low rainfall has mainly caused droughts and subsequent reduction in agricultural production. Droughts have been a recurring feature of the Indian climate, therefore, study of historical droughts may help in the delineation of major areas facing drought risk and thereby, management plans can be formulated by the government authorities to cope with the disastrous effects of this hazard. In recent years, Geographic Information System (GIS) and Remote Sensing (RS) have played a key role in studying different types of hazards, either natural or man-made. This paper emphasizes upon the application of RS and GIS in the field of drought risk evaluation. The study area taken is a part of the Jamnagar district of Gujarat between latitude 22°19′46′′N to 22°46′01′′N and longitude 70°20′56′′E to 70°47′34′′E. The study was conducted with satellite images of year 1977, 1990 and 1999. Data has been acquired mainly from two sources, firstly Normalized Difference Vegetation Index (NDVI) obtained from satellite sources and secondly rainfall obtained from ground rainfall stations record. In the present paper, an effort has been made to derive drought risk areas facing agricultural as well as meteorological drought by use of Normalized Difference Vegetation Index (NDVI) from Landsat images. NDVI values reflect the different geographical conditions quite well. The NDVI and rainfall was found to be highly correlated. It is therefore concluded that temporal variations of NDVI are closely linked with precipitation.},
     year = {2017}
    }
    

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  • TY  - JOUR
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    Y1  - 2017/12/14
    PY  - 2017
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    T2  - American Journal of Biological and Environmental Statistics
    JF  - American Journal of Biological and Environmental Statistics
    JO  - American Journal of Biological and Environmental Statistics
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    PB  - Science Publishing Group
    SN  - 2471-979X
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    AB  - Drought is one of the major natural hazards affecting the environment and economy of countries worldwide. As a natural hazard, drought is best characterized by multiple climatological and hydrological parameters. An understanding of the relationships between these two sets of parameters is necessary to develop measures for mitigating the impacts of droughts. Droughts are recognized as an environmental disaster and have attracted the attention of environmentalists, ecologists, hydrologists, meteorologists, geologists, and agricultural scientists.. Low rainfall has mainly caused droughts and subsequent reduction in agricultural production. Droughts have been a recurring feature of the Indian climate, therefore, study of historical droughts may help in the delineation of major areas facing drought risk and thereby, management plans can be formulated by the government authorities to cope with the disastrous effects of this hazard. In recent years, Geographic Information System (GIS) and Remote Sensing (RS) have played a key role in studying different types of hazards, either natural or man-made. This paper emphasizes upon the application of RS and GIS in the field of drought risk evaluation. The study area taken is a part of the Jamnagar district of Gujarat between latitude 22°19′46′′N to 22°46′01′′N and longitude 70°20′56′′E to 70°47′34′′E. The study was conducted with satellite images of year 1977, 1990 and 1999. Data has been acquired mainly from two sources, firstly Normalized Difference Vegetation Index (NDVI) obtained from satellite sources and secondly rainfall obtained from ground rainfall stations record. In the present paper, an effort has been made to derive drought risk areas facing agricultural as well as meteorological drought by use of Normalized Difference Vegetation Index (NDVI) from Landsat images. NDVI values reflect the different geographical conditions quite well. The NDVI and rainfall was found to be highly correlated. It is therefore concluded that temporal variations of NDVI are closely linked with precipitation.
    VL  - 3
    IS  - 4
    ER  - 

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