Vol. 10, Special Issue 10 (2021)

Author(s):
Sunil Kumar and Shweta Gautam

Abstract:
Bundelkhand needs extra care to combat the impact of drought in the region which frequency has been increased due to climate change. This study presents a methodology for spatial and temporal assessment of drought in each 13 districts come under Bundelkhand region. Standardized Precipitation Index (SPI) methods were used to identify meteorological drought in terms of SPI and it was calculated by in different time steps 1 and 3-months time scales for the duration of 1990-2019. In most of districts it was found severe to extreme drought condition in the years 1991, 1993, 2000 and 2015 in Bundelkhand region. It was found that based on 1 and 3-months scale extreme dry condition was there during 1991, 1993, 2000, 2006, 2012, 2015 and 2018 in Banda district. In Chhatarpur district, 1-month scale SPI indicates that during 1992, 2000, 2001, 2002 and 2009, extreme drought condition was prevailing. In these years dry spell periods were also long. in the 3-month scale of SPI indicates 1991, 1992, 2000, 2002, 2005 and 2009 were affected by extreme drought condition in Datia. Likewise, in Chitrakoot, Damoh, Hamirpur, Jalaun, Mahoba, Jhansi, Lalitpur and Panna these years were drought affected either extreme drought or severe drought in the scales of 1 month and 3 months. In 1-month scale of SPI, 1991 and 2002 were extreme drought years whereas 1992, 2000, 2001,2005, 2007, 2009, 2011, 2017, 2018 were severe drought affected years in Sagar district. In the years 1991, 1992, 2000, 2002, 2004, there was extreme dry condition and severe dry condition was prevailing in the years 2006, 2010 and 2018 indicated by 3-months scale of SPI. In Tikamgarh district, there was extreme drought condition in the years 1992, 2001, 2002 and 2017 whereas in the years 1991, 2000, 2004, 2005, 2009 and 2013 there was severe dry condition as shown by 1-month scale of SPI. Drought analysis can provide a tool to diagnose the impacts on food production associated with drought and for early warning of crop yield by predicting the yield at an early stage of the crop growth.