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Brooks, N. and Adger, W.N. (2005) Assessing and Enhancing Adaptive Capacity. In Chopra, K., Leemans, R., Kumar, P. and Simons, H., Eds., Adaptation Policy Frameworks for Climate Change: Developing Strategies, Policies and Measures, CUP, Cambridge, 165-181.

has been cited by the following article:

• TITLE: Assessment of Livelihood Vulnerability to Rainfall Variability among Crop Farming Households in Kitui South Sub-County, Kenya

  AUTHORS: Morris M. Mwatu, Charles W. Recha, Kennedy N. Ondimu

  KEYWORDS: Livelihood Vulnerability, Exposure, Sensitivity, Adaptive Capacity

  JOURNAL NAME: Open Access Library Journal, Vol.7 No.6, June 5, 2020

  ABSTRACT: Rainfall variability has negatively impacted rain-fed crop farming in arid and semi-arid lands increasing households’ vulnerability. This study sought to establish the extent to which rain-fed crop farming households in Kitui South sub-County in semi-arid Southeastern Kenya are vulnerable to rainfall variability. The study used index-based approach where Livelihood Vulnerability Index (LVI) for each of the randomly sampled 311 households was calculated using the IPCC framework. Rainfall data for six rainfall seasons for the period 2016-2018 was used to calculate index for exposure while questionnaires were administered to the household heads to establish sensitivity and adaptive capacity indices. Responses from the selected sub-components were assigned index values ranging between zero and one. LVI levels were scored between -1 and +1. The study established that indices for exposure, sensitivity and adaptive capacity were 0.71, 0.09 and 0.19 respectively and that 97.4% of the households in the study area were vulnerable to rainfall variability. The study concludes that households in the study area have different livelihood vulnerability levels to rainfall variability due to differences in their sensitivity and adaptive capacity. The study recommends use of households’ LVI levels in determining appropriate intervention measures to effects of vulnerability to rainfall variability among different farming households in order to avoid generalization.