Abstract
The primary datasets used in this analysis include: from the treaty data extracted from Oregon State University and International Water Management, (summarized as mechanisms), summary statistics of the GDP and stability indices for each country used to estimate power differences, a historical drought index for each basin, and historical conflict data from Oregon State University’s Transboundary Freshwater Dispute Database. From the treaty data, specific components are summed to estimate a value for each of seven different mechanisms that together make up the strength, or resiliency, of a treaty. Projected water variability data extracted from global climate and runoff models is used in the case study analysis.
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Notes
- 1.
While many assertions of water-scarcity driven wars have been made, the first empirical study of the extent and magnitude of water’s impact on international and internal conflict was not conducted until 1998 by scholars involved with the BAR project at OSU. The study concluded that water scarcity does not increase the likelihood of interstate conflicts. However, the BAR study did not have annual flow/precipitation/drought data available, such as the PDSI data used in this study, to correlate with political activity.
- 2.
Some suggest that there is not enough empirical research or observations to identify critical causal factors, which are required to create regression equations geared to determine causality (USACE 2006). Others have found that the effectiveness of conflict resolutions mechanisms is strongly influenced by administrative and institutional frameworks, based on a few case-study basins (Saleth and Dinar 2004; Jagerskog 2003).This study recognizes and hopes to address these limitations with new treaty and drought data, as well as with in-depth case studies to explore the regression findings.
- 3.
It is recognized that this selection methodology introduces a certain amount of bias.
- 4.
The literature is not used in calculations in the unweighted method, but it is used to determine which attributes to include in the analysis.
- 5.
The A1B scenario assumes a homogenous world of “very rapid economic growth, global population that peaks in mid-century and declines thereafter, and the rapid introduction of new and more efficient technologies” (IPCC 2007). It also assumes a balanced use of energy sources. The most likely temperature rise in the A1B scenario is 2.8°C, with a potential range of 1.7–4.4°C.
- 6.
The scale and regions used for the modeling were defined by the World Bank. Some World Bank regions do not coincide exactly with basin delineations, resulting in some cases where CBUs of the same river basin belong to different regions and consequently CV values derived from different climate models. De Stefano et al. provide the Nile basin as an example where the ‘Ethiopian share of the Nile River basin is based on the ranking of models in the Sub-Saharan African region’ but the Egyptian share is “based on the ranking of model results for the Middle East and North Africa Bank region” (De Stefano et al. 2009).
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Zentner, M. (2011). Data and Methods: Treaties, Power, Scarcity and Conflict. In: Design and impact of water treaties. Springer Theses. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-23743-0_4
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