In developing countries, where economic expansion depends on extractive activities such as agriculture and mining, water quantity and quality considerations need to be examined in tandem with GDP growth and poverty reduction efforts. Poorest households in the Tupiza watershed in Bolivia are located in rural areas where water access for irrigation and safe drinking water is becoming increasingly scarce. Small-scale unregulated mining offers an alternative for revenue making in rural households, although wastewater from industry threatens water quality and new technologies to reduce water pollution are not implemented in this region yet. This study analyses water access and poverty linkages using the Multidimensional Poverty Analysis (MDPA) framework from the Swedish International Development Cooperation Agency (SIDA) to guide a survey and to develop indicators using the Shapley-Owen decomposition method and multivariate regressions. A set of household-level policies were included to predict the influence of these policies on poverty reduction estimates. Results have shown that remote communities in rural areas have the lowest value of multidimensional poverty and for some of these communities mining activities represent an alternative that could be considered if their water access conditions worsen over time. While mining can bring better monetary benefits, it can cause the degradation of ecological flows from the produced wastewater. Under the current technologies and processes, it can pose negative impacts on water quality and threatens the public health of these communities.
Food, water, and energy (FWE) policies often entail contentious tradeoffs. For example, increasing food production may involve irrigation from riparian sources that may adversely impact fisheries habitats, the siting of solar energy on agricultural lands can impact food production, and increasing food production capacity may require pesticides in certain locations, resulting in environmental pollution. Because public preferences are an important component of support for and opposition to FWE policy design and implementation, it is important to understand the correlates of support and opposition to FWE policy tradeoffs. Using survey data from random household surveys conducted in western U.S. states during 2018, this study examined how environmental efficacy, values, and knowledge affected FWE public tradeoff preferences. The findings suggest that these characteristics do affect public FWE tradeoff preferences, with knowledge being a strong driver of support for food production over biofuels, water friendly crops over meat production and conservation over water intensive agriculture. Additionally, environmental efficacy and pro-ecological attitudes drive support for access to safe drinking water and sanitation over food security for a growing population.
Achieving sustainable water resources management objectives can work in tandem with poverty reduction efforts. This study evidenced the strong social hydrological linkages that exist in Cambodia, which allowed for presenting a broader understanding of water resources challenges to better formulate and connect policies at the local and national levels. Models are often not developed with household- or community-level input, but rather with national- or coarse-level datasets. The method used in this study consisted of linking qualitative and quantitative social analysis with a previously developed technical water planning model. The results from the social inequalities analysis were examined for three water use types: domestic, rice production, and fishing in three parts of the watershed, namely, upstream, midstream, and downstream. Knowledge generated from the social analysis was used to refine previous water planning modeling. The model results indicate that without household data to consider social inequalities, the technical analysis for the Stung Chinit watershed was largely underrepresenting the shortages in irrigation supply seen by groups in the most downstream sections of the irrigation system. Without adding social considerations into the model, new policies or water infrastructure development suggested by the model could reinforce existing inequalities.
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