Spatial monitoring of drought in the Khatun Abad basin using SPI and remote sensing technique

Document Type : Original Article

Authors

1 Assistant Professor, Department of Geography and urban planning Shahid Bahonar University of Kerman

2 Geography department, Literature faculty, Shahid Bahonar university, Kerman, Iran

10.22052/jdee.2019.174651.1052

Abstract

Drought is a natural and recurrent phenomenon. It is considered ‘a natural disaster’ whenever it occurs intensively in highly populated regions, resulting in significant damage (material and human) and loss (socioeconomic). In this regard, this research aims to evaluate the drought of the Khatun Abad basin using the combination of NDVI (Normalized Difference Vegetation Index) and LST (Land surface temperature) MODIS sensors and an SPI indicator. For this purpose, the VHI index was calculated from the combination of VCI and TCI indices based on the 18-year time series (2000-2017) in June. Finally, drought zoning maps based on the VHI index were produced in five classes: very intense, intense, median, and mild and without drought. The evaluation of the time series derived from the VCI and TCI indices shows that there is a significant relationship between NDVI and LST variations. The results show that an extreme drought class is observed in 2017, covering an area of 46 km² from the plain involved with the extreme drought. This is despite the fact that the highest levels of severe drought class occurred in 2008 with an area of approximately 900 km². The total severe and extreme drought classes are observed in 2007, 2008 and 2017. In 2017, a total area of approxiamtely 844 km² from the Khatun Abad basin was involved with the drought, reaching 902 km² in 2008 and 809 km² in 2007. According to the results, the lowest level of drought in Khatun Abad in 2009 was 34 km² classified as a severe and extreme drought. Additionally, the results of the data analysis using the index SPI show that, the most severe drought in the region occurred in 2008. As a result, 33% of the area was severely subjected to drought, and 65% was placed in the middle class drought. In general, the research results indicate that drought changes in the Khatun Abad plain are not logical, and in different years, different drought intensities have been observed.

Keywords

References

  1. Bakhtiyari, B, 2003. An Analytical Attitude on Climate Change in the City of Kerman, Third Regional Conference and First National Conference on Climate Change, Meteorological Organization, Isfahan, 181-187.
  2. Berhan, G., Hill, S., Tadesse, T., & Atnafu, S., 2011, Using Satellite Images for Drought Monitoring: A Knowledge Discovery Approach. Journal of Strategic Innovation and Sustainability, 7 (1), 135-153.
  3. Brian D. Wardlow, Martha C. Anderson, James P. Verdin. 2012. Remote Sensing of Drought. Taylor & Francis Group.
  4. Damavandi, A. Rahimi, M. Yazdani, M. Noroozi, A. 2016. Agricultural Drought Location Tracking by NDVI and LST in MODIS sensor. Geographical Information Journal. Vol. 99. PP. 115-126.
  5. El-Naqa, A., Hammouri, A. 2007. Drought Assessment Using GIS and Remote Sensing in Amman-Zarqa Basin, Jordan, Jordan Journal of Civil Engineering, Volume 1, No. 2.
  6. Bruce, J. P., 1994, Natural disaster reduction and global change. Bull. Amer. Meteor. Soc., 75, 1831–1835.
  7. Ebrahimi, M., Matkan, A. A., Darvishzadeh, R., 2010, remote sensing for drought assessment in arid regions (Case study of central part of Iran, Shirkooh-Yazd), ISPRS TC VII Symposium – 100 Years ISPRS, Vienna, Austria, July 5–7, IAPRS, Vol. XXXVIII, Part 7B.
  8. Hammouri, N, El-Naqa, A. (2007). Drought Assessment Using GIS and Remote Sensing in Amman-Zarqa Basin, Jordna. Jordan Journal of Civil Engineering. No. 2. Pp: 142-152.
  9. Hanafi, A. Khosh Akhlagh, F. Soltani, M. 2011. Analyzing Tehran Province Droughts by using SPI index and predicting that by Markov Chain. Geography and Environmental stability (3) 2. Pp 87-100.
  10. Kebede, A. Manjit, S. Kang, and Endashaw Bekele. 2019. Advances in mechanisms of drought tolerance in crops, with emphasis on barley. Advances in Agronomy.
  11. Kogan, F. N., 1997, Global Drought Watch from Space. Bulletin of the American Meteorological Society, Vol. 78, No. 4, 621–636.
  12. Kogan, F. 1995, “Droughts of the Late 1980s in the United States as Derived from NOAA Polar Orbiting Satellite Data,” Bulletin of the American Meteorological Society, Vol. 76, No. 5, pp. 655-668.
  13. Li, J., J. Lewis, et al. 2004. "Evaluation of land performance in Senegal using multitemporal NDVI and rainfall series." Journal of Arid Environments Vol.59: pp.463–480.
  14. Linsley, Ray K, Jr., Max A. Kohler, Joseph L.H. Paulhus. 1975. Hydrology for engineers. McGraw Hill Book Co. pp: 53-55.
  15. Luisa Febrina Amalo et al 2017 IOP Conf. Ser.: Earth Environ. Sci. 54 012009
  16. Mala, S and Mahesh Kumar Jat, Parul Pradhan. 2014. An Approach to analyze Drought occurrences using Geospatial Techniques, 15th Esri India User Conference 2014.
  17. Mostafa Zade, R. Zabihi, M. 2016. SPI and SPEI Analysis and Comparison in Meteorological drought assessment using R software (Case study: Kordestan province, Iran). Earth and Space Physics. (3) 42. Pp 633-643.
  18. Nicolai-Shaw, N., Zscheischler, J., Hirschi, M., Gudmundsson, L., Seneviratne, S., 2017. A drought event composite analysis using satellite remote-sensing based soil moisture, Remote Sensing of Environment. 216–225.
  19. Obasi, G. O. P., 1994, WMO’s Role in the international decade for natural disaster reduction. Bulletin of the American Meteorological Society. 75, 1655–1661.
  20. Owrangi, M, Adamowski, J, Rahnemaei, M, Mohammadzade, A, Afshin Sharifan, R. 2011. Drought Monitoring Methodology Based on AVHRR Images and SPOT Vegetation Maps. Journal of Water Resource and Protection. Pp: 325-334.
  21. Panu, U.S., Sharma T. C. 2002. Challenges in drought research: some perspectives and future directions, Hydrological Sciences Journal, 47: S1, S19-S30.
  22. Pourkhosravani, M, Mehrabi, A, Moosavi, H. 2016. Analyzing Sirjan Spatial Drought by Remote Sensing. Journal of Desert Ecosystems Engineering. Vol 20. Pp: 13-22.
  23. 2009. M.S. State Level analysis of Drought Policies and Impacts in Rajasthan, India. Working Paper 93, Drought Series, Paper-6.
  24. Safari Shad, M., IldoromiB, A., Akhzari, D., 2017, Drought Monitoring Using Vegetation Indices and MODIS Data (Case Study: Isfahan Province, Iran), Journal of Rangeland Science, Vol. 7, No. 2, PP: 148-158.
  25. Sruthi, S and Aslamm M.A. 2015. Agricultural Drought Analysis Using the NDVI and Land Surface Temperature Data; a Case Study of Raichur District. International Conference on Water Resources, Coastal and Ocean Engineering (ICWRCOE 2015).
  26. Thenkabail, Prasad & S. D. N. Gamage, M & Smakhtin, Vladimir. (2004). The Use of Remote Sensing Data for Drought Assessment and Monitoring in Southwest Asia.
  27. Wan, Z., Wang, P. and Li, X.,2004, 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, 2(1): 61-72.
  28. Wilhite, D. A. 2000, Drought as a natural hazard: Concepts and definitions, in Droughts: A Global Assessment, edited by D. A. Wilhite, pp. 3–18, Routledge, London.
  29. Zorn, Matija. (2018). Natural Disasters and Less Developed Countries. 10.1007/978-3-319-59002-8_4
Desert Ecosystem Engineering Journal
Volume 2, Issue 1
April 2019
Pages 31-44

Files

Share

How to cite

Statistics