Natural Hazards

, Volume 54, Issue 3, pp 643–656 | Cite as

Application of meteorological and vegetation indices for evaluation of drought impact: a case study for Rajasthan, India

  • Sanjay K. Jain
  • Ravish Keshri
  • Ajanta Goswami
  • Archana Sarkar
Original Paper
First Online:
Received:
Accepted:

Abstract

Drought is a serious climatic condition that affects nearly all climatic zones worldwide, with semi-arid regions being especially susceptible to drought conditions because of their low annual precipitation and sensitivity to climate changes. Drought indices such as the standardized precipitation index (SPI) using meteorological data and vegetation indices from satellite data were developed for quantifying drought conditions. Remote sensing of semi-arid vegetation can provide vegetation indices which can be used to link drought conditions when correlated with various meteorological data based drought indices. The present study was carried out for drought monitoring for three districts namely Bhilwara, Kota and Udaipur of Rajasthan state in India using SPI, normalized difference vegetation index (NDVI), water supply vegetation index (WSVI) and vegetation condition index (VCI) derived from the Advanced Very High resolution Radiometer (AVHRR). The SPI was computed at different time scales of 1, 2, 3, 6, 9 and 12 months using monthly rainfall data. The NDVI and WSVI were correlated to the SPI and it was observed that for the three stations, the correlation coefficient was high for different time scales. Bhilwara district having the best correlation for the 9-month time scale shows late response while Kota district having the best correlation for 1-month shows fast response. On the basis of the SPI analysis, it was found that the area was worst affected by drought in the year 2002. This was validated on the basis of NDVI, WSVI and VCI. The study clearly shows that integrated analysis of ground measured data and satellite data has a great potential in drought monitoring.

Keywords

Drought Standardized precipitation index (SPI) Normalized difference vegetation index (NDVI) Water supply vegetation index (WSVI) Vegetation condition index (VCI) National oceanic atmospheric administration (NOAA) 
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References

  1. Alley WM (1985) The Palmer Drought Severity Index as a measure of hydrological drought. Water Resour Bull 21:105–114Google Scholar
  2. Anyamba A, Tucker CJ (2005) Analysis of Sahelian vegetation dynamics using NOAA-AVHRR NDVI data from 1981–2003. J Arid Environ 63(3):596–614CrossRefGoogle Scholar
  3. Bhalme HN, Mooley DA (1980) Large scale droughts/floods and monsoon circulation. Mon Wea Rev 108:1197–1211CrossRefGoogle Scholar
  4. Chaudhari KN, Dadhwal VK (2004) Assessment of impact of drought- 2002 on the production of major kharif and rabi crops using standardized precipitation index. J Agrometeorology 6:10–15Google Scholar
  5. Farrar TJ, Nicholson SE, Lare AR (1994) “The influence of soil type on the relationships between NDVI, rainfall and soil moisture in semiarid Botswana II:NDVI response to soil moisture. Remote Sens Environ 50:121–133CrossRefGoogle Scholar
  6. Franklin J, Hiernaux PHY (1991) Estimating foliage and woody biomass in Sahelian and Sudanian woodlands using a remote sensing model. Int J Remote Sens 12:1387–1404CrossRefGoogle Scholar
  7. Gutman GG (1990) Towards monitoring drought from space. J Climate 3:282–295CrossRefGoogle Scholar
  8. Hayes MJ, Svoboda MD (1999) Monitoring the 1996 drought using SPI. Bull Am Meteorol Soc 80:429–438CrossRefGoogle Scholar
  9. Herrieksen BL, Durkin JW (1986) Growing period and drought early warning in African using satellite data. Int J Remote Sens 11:1608–1853Google Scholar
  10. Jain SK, Keshri R, Goswami A, Sarkar A, Chaudhry A (2009) Identification of drought-vulnerable areas using NOAA AVHRR data. Int J Remote Sen 1366-5901 30(10):2653–2668Google Scholar
  11. Ji L, Peters AJ (2003) Assessing vegetation response to drought in the northern Great Plains using vegetation and drought indices. Remote Sens Environ 87:85–98CrossRefGoogle Scholar
  12. Justice CO, Townshend JRD, Chaudhary BJ (1989) Comparision of AVHRR and SMMR data for monitoring vegetation phenology on the continental scale. Int J Remote Sens 14:603–608Google Scholar
  13. Karl T, Quinlan F, Ezell DS (1987) Drought termination and amelioration: its climatological probability. J Clim Appl Met 26:1198–1209CrossRefGoogle Scholar
  14. Kogan FN (1995) Application of vegetation index and brightness temperature for drought detection. Adv Space Res 15(11):91–100CrossRefGoogle Scholar
  15. Kogan FN (1997) Global drought watch from space. Bull Am Meteorol Soc 78:621–636CrossRefGoogle Scholar
  16. Kogan FN, Sullivan J (1993) Development of global drought-watch system using NOAA/AVHRR data. Adv Space Res 13:219–222CrossRefGoogle Scholar
  17. Komuscu AU (1999) Using the SPI to analyze spatial and temporal pattern of drought in Turkey. Drought Netw News 11:7–13Google Scholar
  18. Lana X, Serra C, Burgueno A (1998) Spatial and temporal characterization of annual extreme droughts of Catalonia (North Spain). Int J Clim 18:93–110CrossRefGoogle Scholar
  19. Lana X, Serra C, Burgueno A (2002) Patterns of monthly rainfall shortage and excess in terms of the standardized precipitation index for Catalonia (NE Spain). Int J Climate 21(13):1669–1691CrossRefGoogle Scholar
  20. Lei J, Peters AJ (2003) Assessing vegetation response to drought in the northern great plains using vegetation and drought indices. Remote Sens Environ 87:85–98CrossRefGoogle Scholar
  21. Li B, Tao S (2002) Relations between AVHRR NDVI and ecoclimatic parameters in China. Int J Remote Sens 23(5):989–999CrossRefGoogle Scholar
  22. McKee TB, Doesken NJ, Kleist J (1993) The relationship of drought frequency and duration to time scales, Preprints, 8th conference on applied climatology, January 17–22, Anaheim, California, pp 179–148Google Scholar
  23. Mishra AK, Desai VR (2005) Spatial and temporal drought analysis in the Kansabati river basin, India. Int River Basin Manag 3(1):31–41CrossRefGoogle Scholar
  24. Mohler RR, Well GL, Hallum CR, Trenchard MH (1986) Monitoring vegetation of drought environments. Bioscience 36:478–483Google Scholar
  25. NCDC (2003) Online document library: satellite documentation. Available online at: http://www2.ncdc.noaa.gov/docs/klm/html/c7/sec7.htm
  26. NOAA (2006) NOAA KLM User’s guide. Available online at: http://www2.ncdc.noaa.gov/docs/klm/html/c7/sec7-1.htm
  27. Palmer WC (1965) Meteorological drought. US department of commerce, Weather bureau research paper No. 45, US Weather, Washington, DC, USAGoogle Scholar
  28. Rainwaterharvesting.org (2006) Drought. Available online at http://www.downtoearth.org.in/editors/ShowLetter.asp?FolderName=20030215&LetterID=3
  29. Rathore MS (2004) State level analysis of drought policies and impacts in Rajasthan, India. Working paper 93, Drought Series. Paper 6, International Water Management InstituteGoogle Scholar
  30. Rouse JW, Haas RH, Scell JA, Deering DW, Harlan JC (1974) Monitoring the vernal advancements and retroradation (Green wave effect) of nature vegetation. NASA/GSFC final report, NASA, Greenbelt, MD.371Google Scholar
  31. Seiler R, Hayes M, Bressan L (2002) Using the standardized precipitation index for flood risk monitoring. Int J Climate 22:1365–1376CrossRefGoogle Scholar
  32. Sen Z (1998) Probabilistic formulation of spatio-temporal pattern. Theor Appl Climatol 61:197–206CrossRefGoogle Scholar
  33. Song X, Saito G, Kodama M, Sawada H (2004) Early detection system of drought in ast Asia using NDVI from NOAA AVHRR data. Int J Remote Sen 25(16–18):3105–3111CrossRefGoogle Scholar
  34. Srivastava SK, Jayaraman V, Nageswar Rao PP, Manikiam B, Chandraeskhar MG (1994) Agro climatic zonal characterization using NOAA AVHRR and meteorological data, IAF-94-B.5.107. Proceeding of the 45th Congress of International Astronotical Federation 9–14 October, Jerusalem, IsarelGoogle Scholar
  35. Stahl K, Demuth S (1999) Linking stream flow drought to occurrence of atmospheric circulation pattern. Hydrol Sci J 44(5):665–680CrossRefGoogle Scholar
  36. Thiruvengadachari S, Gopalkrishna HR (1994) Satellite added regional vegetation dynamics over India—a case study in Karnataka state, global change studies. Scientific report no. ISRO-GBP-SR-42-94, Bangalore: Indian Space Research Organization, pp 167–192Google Scholar
  37. Tucker CJ (1979) Red and photographic infrared linear combinations for monitoring vegetation. Remote Sens Environ 8:127–150CrossRefGoogle Scholar
  38. Tucker CJ, Chaudhary BJ (1987) Satellite remote sensing of drought conditions. Remote Sens Environ 23:243–251CrossRefGoogle Scholar
  39. Wang J, Rich PM, Price KP (2003) Temporal responses of NDVI to precipitation and temperature in the central Great Plains, USA. Int J Remote Sens 24:2345–2364CrossRefGoogle Scholar
  40. Wilhite DA (2000) Drought as a natural hazard: concepts and definitions. Drought: a global assessment, vol 1. W. D.A. Routlegde, pp 1–3Google Scholar
  41. Xiao Q, Chen W, Liang G, Du P (1995) A study on drought monitoring using meteorological satellite data. Technical Reports of National Satellite Meteorological Centre, 9509:9Google Scholar

Copyright information

© Springer Science+Business Media B.V. 2010

Authors and Affiliations

  • Sanjay K. Jain
    • 1
  • Ravish Keshri
    • 2
  • Ajanta Goswami
    • 3
  • Archana Sarkar
    • 1
  1. 1.National Institute of HydrologyRoorkeeIndia
  2. 2.College of Technology and EngineeringUdaipurIndia
  3. 3.Indian Institute of TechnologyRoorkeeIndia

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