Determinants of farm-level adaptation diversity to cyclone and flood: insights from a farm household-level survey in Eastern India

Abstract

A large number of farmers' livelihoods are susceptible to cyclones and floods, and farmers are taking up several adaptation mechanisms. Previous studies, therefore, have examined determinants of various adaptation options and provide policy suggestions to promote a specific one. However, options are undertaken at different points depending on the nature and intensity of extreme events. Hence, it is imperative to identify factors influencing farmers' decisions to adopt an additional option, particularly during ex-ante and ex-post periods. This could assist policy-makers to enhance various farm-level adaptation options. Using survey data from 285 farm households in cyclone- and flood-prone regions in eastern India, this study aims to assess the determinants of adaptation diversity. This study finds that the likelihood of undertaking adaptation diversity is high during the ex-post period, and cyclone-affected farmers are likely to adopt a higher number of adaptation measures. Further, size of household, farming experience, per capita income, agriculture as major source of income and crop loss compensation received are some of the important determinants. These findings emphasize the need for investments in scientific modeling for better prediction of extreme events and suggest restructuring the existing institutions to promote several farm-level adaptation measures.

The damages from climatic extremes in India: do disaster-specific and generic adaptation measures matter?

“…As discussed in the preceding section, the state economy is agrarian, and previous studies also report that agricultural output is more likely to be affected by cyclones and floods (Bhattacharya and Das 2007;Rao 2010). Further, Bahinipati (2014) also find that indicators related to agriculture emerged as the major determinants of vulnerability in Odisha. For instance, an average of 0.33 million ha agricultural land was damaged in the state due to flood during 1953-2011, which converts into a financial loss of INR 0.32 billion per year (GoO 2013).…”

“…The district with higher value for these exposure indicators is expected to be more vulnerable. It is observed that the coastal districts of Odisha are experience a relatively higher number of cyclones and floods (GoO 2011), and in particular, the intensity of cyclones is likely to be high for these districts (Bahinipati 2014)-therefore, the households living in the coastal districts are more exposed to these events. As discussed in the preceding section, the state economy is agrarian, and previous studies also report that agricultural output is more likely to be affected by cyclones and floods (Bhattacharya and Das 2007;Rao 2010).…”

“…Khordha, Mayurbhanj, Jajpur, Keonjhar, Dhenkanal, Cuttack, Nayagarh and Gajapati). Further, a study by Bahinipati (2014) report that eight districts of Odisha are having higher vulnerability level to cyclones and floods, e.g. 1990s, 2000s and 20011990s, 2000s and -20091990s, 2000s and , respectively (GoO 20041990s, 2000s and , 2011.…”

“…undertaken through Mahatma Gandhi National Rural Employment Guarantee Act (MGNREGA) 1 reduce the vulnerability of poor households to current climatic risks in rural India. Further, Bahinipati (2013) ascertains that development-based activities like participation in MGNREGA, and access to agricultural extension and formal credit enhance farmers' ability to undertake more number of farm-level adaptation measures against cyclones and floods in Odisha.…”

“…The study is with reference to the state of Odisha on the eastern coast of India (Fig. 1), where incidence of extreme events like cyclones and floods are frequent and its impacts in terms of damage to crops, houses and public utilities were increased over the years (Bhatta 1997;Chittibabu et al 2004;Government of Odisha, hereafter, GoO 2004IMD 2008;Mohanty et al 2008;Bahinipati 2014-the detailed explanation is given in the next section); in many instances both the events are complementary. In the aftermath of the super cyclone in 1999 that badly hit Odisha (GoO 1999;Brenkert and Malone 2005), the Odisha State Disaster Management Authority (OSDMA) has implemented the disaster risk management programme (DRM) in 16 disaster prone districts of the state (vulnerable to extreme events like cyclones, floods and earthquakes) during 2002-08 to reduce potential impacts of cyclones and floods, with the support of the Government of India (GoI) and the United Nations Development Programme (UNDP) 2 (Das and Smith 2012).…”