Livelihood Dynamics Across a Variable Flooding Regime
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Variability in environmental phenomena such as fire, flooding, and weather-related events can have significant impacts for social and environmental systems and their coupled interactions. Livelihoods systems reliant on the natural environment can be disrupted or eliminated, while associated governance regimes require negotiation to ensure equitable and sustainable management responses. These patterns can be particularly pronounced within areas prone to flooding, as these sites can experience variability in the location, timing, amount, and duration of flooding events. While research within the social and natural sciences has evaluated these dynamics within flooding regimes, the coupled interactions can be underemphasized even though they are integral in producing livelihood systems and possibilities for environmental management. This paper details research conducted from 2011 to 2016 in five villages located in different locations within the Okavango Delta of Botswana. We report the findings from qualitative interviewing and livelihood mapping activities that are integrated with remote sensing analysis to provide concrete empirical detail on the variability of flooding and resulting variations in perception and livelihood responses. The paper demonstrates that flooding dynamics vary at discrete locations and produce diverse perceptions that are tied to livelihood adjustments in place-specific ways. These patterns are also embedded in regional and global processes that have significant implications for household vulnerability within socio-ecological systems strongly impacted by local and distant climatic and hydrological drivers of change.
KeywordsFlooding Flooding regime Variability Livelihood Socio-ecological system Botswana Okavango Delta
This research was supported by the United States National Science Foundation (BCS/GSS-0964596) andBCS/GSS Research Experiences for Undergraduates (REU) Supplement Award. The work was also supported by grant, P2CHD042849 awarded to the Population Research Center at The University of Texasat Austin by the Eunice Kennedy Shriver National Institute of Child Health and Human Development. The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health. Fuata John, Japhet John, and Kentse Madise were invaluable as our research assistants. Allison White and Evan Griffin helped conduct the qualitative interviews in the Etsha region in 2011, and Amelia C. Eisenhart contributed to the remote sensing analysis that informed Figure 1. We are especially appreciative of our many informants for their time and generous insights.
Compliance with Ethical Standards
Conflict of Interest
The authors declare that they have no conflict of interest.
- Conca, K. (2015). Which Risks Get Managed? Addressing Climate Effects in the Context of Evolving Water-Governance Institutions. Water Alternatives 8(3): 301–316.Google Scholar
- Cox, M., Villamayor-Tomas, S., Epstein, G., Evans, L., Ban, N. C., Fleischman, F., Nenadovic, M., and Garcia-Lopez, G. (2016). Synthesizing Theories of Natural Resource Management and Governance. Global Environmental Change 39: 45–56. https://doi.org/10.1016/j.gloenvcha.2016.04.011.CrossRefGoogle Scholar
- Girard, C., Pulido-Velazquez, M., Rinaudo, J. D., Pagé, C., and Caballero, Y. (2015). Integrating Top-Down and Bottom-Up Approaches to Design Global Change Adaptation at the River Basin Scale. Global Environmental Change 34: 132–146. https://doi.org/10.1016/j.gloenvcha.2015.07.002.CrossRefGoogle Scholar
- Huitema, D., Mostert, E., Egas, W., Moellenkamp, S., Pahl-Wostl, C., and Yalcin, R. (2009). Adaptive Water Governance: Assessing the Institutional Prescriptions of Adaptive (co-) Management from a Governance Perspective and Defining a Research Agenda. Ecology and Society 14(1): 26.CrossRefGoogle Scholar
- IPCC (2007). Climate Change 2007: The Physical Science Basis. Contribution of Working Group I to the Fourth Assessment Report of the Intergovernmental Panel on Climate Change. In Solomon, S., D. Qin, M. Manning, Z. Chen, M. Marquis, K.B. Averyt, M. Tignor and H.L. Miller (eds.), Cambridge University Press, Cambridge.Google Scholar
- IPCC (2014). Summary for policymakers. In Stocker, T. F., Qin, D., Plattner, G.-K., Tignor, M., Allen, S. K., Boschung, J., Nauels, A., Xia, Y., Bex, V., and Midgley, P. M. (eds.), Climate Change 2013: The Physical Science Basis. Contribution of Working Group I to the Fifth Assessment Report of the Intergovernmental Panel on Climate Change, Cambridge University Press, Cambridge.Google Scholar
- Leauthaud, C., Duvail, S., Hamerlynck, O., Paul, J. L., Cochet, H., Nyunja, J., Albergel, J., and Grünberger, O. (2013). Floods and Livelihoods: The Impact of Changing Water Resources on Wetland Agro-ecological Production Systems in the Tana River Delta, Kenya. Global Environmental Change 23: 252–263. https://doi.org/10.1016/j.gloenvcha.2012.09.003.CrossRefGoogle Scholar
- Lemos, M. C., and Agrawal, A. (2006). Environmental Governance. Annual Review of Environmental Resources 31: 297–325. https://doi.org/10.1146/annurev.energy.31.042605.135621.CrossRefGoogle Scholar
- Magole, L., and Thapelo, K. (2005). The Impact of Extreme Flooding of the Okavango River on the Livelihood of the molapo Farming Community of Tubu village, Ngamiland Sub-district, Botswana. Botswana Notes and Records 37: 125–137.Google Scholar
- Marcus, R. R. (2007). Where Community-Based Water Resource Management has Gone Too Far: Poverty and Disempowerment in Southern Madagascar. Conservation and Society 5(2): 202–231.Google Scholar
- McCarthy, T. S., Cooper, G. R. J., Tyson, P. D., and Ellery, W. N. (2000). Seasonal Flooding in the Okavango Delta, Botswana – Recent History and Future Prospects. South African Journal of Science 96: 25–33.Google Scholar
- Meyer, T., and Bendsen, H. (2003). The dynamics of land use systems in Ngamiland: Changing livelihood options and strategies. In Bernard, T., Mosepele, K., and Ramberg, L. (eds.), Environmental Monitoring of Tropical and Subtropical Wetlands, HOORC Report Series No. 1, Maun, pp. 278–307.Google Scholar
- Midekisa, A., Holl, F., Savory, D. J., Andrade-Pacheco, R., Gething, P. W., Bennett, A., and Sturrock, H. J. W. (2017). Mapping Land Cover Change Over Continental Africa Using Landsat and Google Earth Engine Cloud Computing. PLOS ONE 12(9): e0184926. https://doi.org/10.1371/journal.pone.0184926.CrossRefGoogle Scholar
- Millington, A., and Jepson, W. (eds.) (2008). Land-Change Science in the Tropics: Changing Agricultural Landscapes, Springer, NY.Google Scholar
- Murray-Hudson, M., Wolski, P., Cassidy, L., Brown, M. T., Thito, K., Kashe, K., and Mosimanyana, E. (2015). Remote Sensing-Derived Hydroperiod as a Predictor of Floodplain Vegetation Composition. Wetlands Ecology and Management 23(4): 603–616. https://doi.org/10.1007/s11273-014-9340-z.CrossRefGoogle Scholar
- Nelson, D. R., Adger, W. N., and Brown, K. (2007). Adaptation to Environmental Change: Contributions of a Resiliency Framework. Annual Review of Environmental Resources 32: 395–419. https://doi.org/10.1146/annurev.energy.32.051807.090348.CrossRefGoogle Scholar
- Niang, I., Ruppel, O. C., Abdrabo, M. A., Essel, A., Lennard, C., Padgham, J., and Urquhart, P. (2014). Africa. In Barros, V. R., Field, C. B., Dokken, D. J., Mastrandrea, M. D., Mach, K. J., Bilir, T. E., Chatterjee, M., Ebi, K. L., Estrada, Y. O., Genova, R. C., Girma, B., Kissel, E. S., Levy, A. N., MacCracken, S., Mastrandrea, P. R., and White, L. L. (eds.), Climate Change 2014: Impacts, Adaptation, and Vulnerability. Part B: Regional Aspects. Contribution of Working Group II to the Fifth Assessment Report of the Intergovernmental Panel on Climate Change, Cambridge University Press, Cambridge.Google Scholar
- Ramankutty, N., and Coomes, O. T. (2016). Land-Use Regime Shifts: An Analytical Framework and Agenda for Future Land-Use Research. Ecology and Society 21(1). https://doi.org/10.5751/ES-08370-210201.
- Wolski, P., Murray-Hudson, M., Thito, K., and Cassidy, L. (2017). Keeping it Simple: Monitoring Flood Extent in Large Data-Poor Wetlands Using MODIS SWIR Data. International Journal of Applied Earth Observation and Geoinformation 57: 224–234. https://doi.org/10.1016/j.jag.2017.01.005.CrossRefGoogle Scholar