Association between Uncertainties in Meteorological Variables and Water-Resources Planning for the State of Texas
Publication: Journal of Hydrologic Engineering
Volume 16, Issue 12
Abstract
Because of the complexity and rapidly occurring changes in the dynamics of human demography and water demands, it is difficult to assess the future adequacy of limited freshwater resources. The planning of water resources largely depends on the meteorological variables (precipitation and evaporation) in terms of their distribution in space and time. Considering precipitation and evaporation as natural input and output without any human intervention for water-resources systems that can be perceived to represent the potential water-resources availability of an area, an uncertainty study was carried out for different water-resources regions in Texas. The entropy method was used for measuring the uncertainty in meteorological variables. It was observed that critical water-deficit regions based on meteorological variables are mostly located in the western part of Texas. The Mann-Kendall test was employed to understand the trend in precipitation, evaporation, and the meteorological excess index (MEI) in deficit and surplus water-resources zones. It was observed that increasing trends exist in both precipitation and evaporation at most of the grids, but the increasing trend of evaporation is more than precipitation in some of the water-resources zones, which is likely to make the deficit regions even more deficient and critical.
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Acknowledgments
This work was financially supported in part by the United States Geological Survey (USGS Project ID: USGS2009TX334G) and the Texas Water Resources Institute through the project “Hydrological Drought Characterization for Texas under Climate Change, with Implications for Water Resources Planning and Management” and by the National Research Foundation Grant funded by the Korean Government (MEST) (UNSPECIFIEDNRF-2009-220-D00104).
References
Barnett, T. P., et al. (2008). “Human-induced changes in the hydrology of the western United States.” Science, 319(5866), 1080–1083,
Barnett, T., Malone, T., Pennell, W., Stammer, D., Semtner, B., and Washington, W. (2004). “The accelerated climate prediction initiative.” Clim. Change, 62, 444.
Ebrahimi, N., Maasoumi, E., and Soofi, E. (1999). “Ordering univariate distributions by entropy and variance.” J. Econom., 90(2), 317–336.
Frederick, K. D. (1998). “Principles and concepts for water resources planning under climate uncertainty.” Water Resour. Update, 112, 41–46.
Grayman, W. M. (2005). “Incorporating uncertainty and variability in engineering analysis.” J. Water Resour. Plann. Management., 131(3), 158–160.
Hightower, M., and Pierce, S. A. (2008). “The energy challenge.” Nature, 452(7185), 285–286.
Hopkin, M. (2008). “Greenhouse effect has ‘significantly dried’ the western United States.” Nature, 〈http://www.nature.com/news/2008/080131/full/news.2008.545.html〉, (Nov. 20, 2008).
Intergovernmental Panel on Climate Change (IPCC). (2007). Climate change 2007: Impacts, adaptation and vulnerability: Contribution of Working Group II to the Fourth Assessment Report of the Intergovernmental Panel on Climate Change, M. L. Parry et al., eds., Cambridge University Press, Cambridge, U.K., 976.
Kawachi, T., Maruyama, T., and Singh, V. P. (2001). “Rainfall entropy for delineation of water resources zones in Japan.” J. Hydrol., 246(1–4), 36–44.
Kendall, M. G. (1975). Rank correlation methods, Charles Griffin, London, 202.
Knopman, D. S. (2006). “Success matters: Recasting the relationship among geophysical, biological, and behavioral scientists to support decision making on major environmental challenges.” Water Resour. Res., 42(3), W03S09.
Maasoumi, E., and Racine, J. (2002). “Entropy and predictability of stock market returns.” J. Econometrics, 107(1–2), 291–312.
Mann, H. B. (1945). “Nonparametric tests against trend.” Econometrica, 13(3), 245–259.
McCauley, J. (2003). “Thermodynamic analogies in economics and finance: Instability of markets.” Physica A, 329, 199–212.
Mishra, A. K., Özger, M., and Singh, V. P. (2009). “An entropy based investigation into the variability of precipitation.” J. Hydrol., 370(1–4), 139–154.
National Assessment Synthesis Team (NAST). (2000). Climate change impacts on the United States: The potential consequences of climate variability and change, Cambridge University Press, Cambridge, U.K.
Rodriguez-Iturbe, I., and Porporato, A. (2005). Ecohydrology of water-controlled ecosystems: Soil moisture and plant dynamics, Cambridge University Press, Cambridge, U.K.
Shannon, C. E. (1948). “A mathematical theory of communication.” Bell Syst. Tech. J., 27, 379–423.
Singh, V. P. (1997). “The use of entropy in hydrology and water resources.” Hydrol. Processes, 11(6), 587–626.
Texas State Historical Association (TSHA). (2008). “Handbook of Texas Online.” 〈http://www.tshaonline.org/handbook/online〉 (Mar. 25, 2009).
Texas Water Development Board (TWDB). (2007). “Water for Texas: 2007 state water plan.” Rep. No. GP-8-1, TWDB, Austin, TX.
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© 2011 American Society of Civil Engineers.
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Received: May 25, 2009
Accepted: Mar 1, 2010
Published online: Mar 3, 2010
Published in print: Dec 1, 2011
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