Modelling livelihoods and household resilience to droughts using Bayesian networks

Abstract

Over the last four decades, the Indian government has been investing heavily in watershed development (WSD) programmes that are intended to improve the livelihoods of rural agrarian communities and maintain or improve natural resource condition. Given the massive investment in WSD in India, and the recent shift from micro-scale programmes (ha) to meso-scale (~5000 ha) clusters, robust methodological frameworks are needed to measure and analyse impacts of interventions across landscapes as well as between and within communities. In this paper, the sustainable livelihoods framework is implemented using Bayesian networks (BNs) to develop models of drought resilience and household livelihoods. Analysis of the natural capital component model provides little evidence that watershed development has influenced household resilience to drought and indicators of natural capital, beyond an increased area of irrigation due to greater access to groundwater. BNs have proved a valuable tool for implementing the sustainable livelihoods framework in a retrospective evaluation of implemented WSD programmes. Many of the challenges of evaluating watershed interventions using BNs are the same as for other analytical approaches. These are reliance on retrospective studies, identification and measurement of relevant indicators and isolating intervention impacts from contemporaneous events. The establishment of core biophysical and socio-economic indicators measured through longitudinal household surveys and monitoring programmes will be critical to the success of BNs as an evaluation tool for meso-scale WSD

Livelihood Strategies of Rural Households in Ning’er Earthquake-Stricken Areas, Yunnan Province, China

“…The SLA considers both tangible (including resources and stores) and intangible assets (such as claims and access), which are crucial to build a livelihood [36]. The SLA has proven useful for assessing the capability of households to deal with external shocks, such as natural disasters, climate change and disease [9][10][11][12]35]. It has also been used as a prominent tool in many developmental programs to reduce poverty and livelihood vulnerability in rural households [37,38].…”

“…In addition, as part of efforts to enhance physical capitals, housing construction planning and technical guidance are of critical importance to improve the anti-seismic performance of rural buildings and decrease their livelihood risk in earthquake-prone areas. It is important for farmers to improve and diversify their livelihood strategies according to regional geographical environment and the comparative advantages of their own livelihood assets.Sustainability 2019, 11, 5905 2 of 18 livelihood assets, natural disasters and livelihood strategies [8][9][10], the work on quantitatively studying their internal connections is still very scarce [11,12].China is a country affected by some of the most serious natural disasters in the world. The frequent occurrence of natural disasters has a serious impact on local social economy, which is also a main factor leading to the poverty in rural areas.…”

“…Sustainability 2019, 11, 5905 2 of 18 livelihood assets, natural disasters and livelihood strategies [8][9][10], the work on quantitatively studying their internal connections is still very scarce [11,12].…”

An integrated approach to improving rural livelihoods: examples from India and Bangladesh

“…The information collected in these surveys was used to develop a Bayesian network model for each study area (Merritt et al, 2011(Merritt et al, , 2016.…”

Quantitative Assessment and Diagnosis for Regional Agricultural Drought Resilience Based on Set Pair Analysis and Connection Entropy

“…Larger patches of woodland habitat reduced population sensitivity to the drought event and also facilitated faster recovery [16]. The application of Bayesian networks (BNs) to drought resilience and household livelihood provides evidence that watershed development and management has influenced household resilience to drought [17]; (3) Water supply: Long severe droughts in the nineteenth century provided an opportunity to test water supply system behavior in a range of actual drought events. The test indicates that significant demand restrictions and engineering measures had to be introduced [18].…”