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Site-Specific Detections of Hydroclimatic Changes for Naran Watershed, Pakistan

  • Research Article - Civil Engineering
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Abstract

In this paper, studies have been made to detect the changes in key hydroclimatic variables including precipitation, surface-air temperatures and stream flow with their trends, constructed projection scenarios, and simulated projected climate parameters for Naran watershed. Extreme indices have been determined by least squares and weighted average regression analysis. Temperature extremes have indicated signs of warming trends and increase in variability. Precipitation extremes have depicted decrease in occurrences and magnitudes. The analysis has provided evidence of high confidence about these changes. Trends of from hydroclimatic parameters and stream flows were also determined using Mann–Kendall test for the period 1962–2011. Inter-annual trends have been detected to determine the sensitivity with a base period (1962–1991) by using equal and unequal overlapped moving periods. It has been found that there is a clear trend reversibility during 1996–1997 for temperatures and precipitation pattern. However, the analysis has revealed that no long-term trends are persistent in inter-annual surface-air temperatures and precipitation. Intra-annual trends and variations on the monthly scale from data sets of 1962–2011 have also been detected with their significant values. There seems evidence that variation of parameters in monthly scale is occurring that is affecting the ice melt schedule and evapotranspiration demand.

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References

  1. Bates, B.C.; Kundzewicz, Z.W.; Wu, S.; Palutik, J.P.: Climate Change and Water. Technical paper of the intergovernmental panel on climate change, IPCC Secretariat, Geneva, p. 210 (2008)

  2. Toreti A., Desiato F.: Changes in temperature extremes over Italy in the last 44 years. Int. J. Climatol. 28, 733–745 (2008). doi:10.1002/joc.1576

    Article  Google Scholar 

  3. Solomon, S.; Qin, D.; Manning, M.; Chen, Z.; Marquis, M.; et al.: The Physical Science Basis. Contribution of working group I to the fourth assessment report of the IPCC. Cambridge University Press, Cambridge, UK, p. 996 (2007)

  4. Jones J.A.: Hydrologic responses to climate change: considering geographic context and alternative hypotheses. Hydrol. Process. 25, 1996–2000 (2011). doi:10.1002/hyp.8004

    Article  Google Scholar 

  5. Sithole A., Murewi C.T.F.: Climate variability and change over southern Africa: impacts and challenges. Afr. J. Ecol. 47, 17–20 (2009). doi:10.1111/j.1365-2028.2008.01045.x

    Article  Google Scholar 

  6. Parida, B.P.; Moalafhi, D.B.; Dube, O.P.: Estimation of Likely Impact of Climate variability on Runoff Coefficients from Limpopo Basin Using Artificial Neural Networks (ANN). In: Proceedings of the international conference on monitoring, prediction and mitigation of water-related disasters, 12–15 Jan 2005. Kyoto University, Japan, (2005)

  7. McSweeney, C.; New, M.; Lizcano, G.: UNDP climate change country profile for Pakistan. http://country-profile.geog.ox.ac.uk (2010)

  8. Archer D.R., Forsythe N., Fowler H.J., Shah S.M.: Sustainability of water resources management in the Indus Basin under changing climatic and socio economic conditions. Hydrol. Earth Syst. Sci. 14, 1669–1680 (2010). doi:10.5194/hess-14-1669-2010

    Article  Google Scholar 

  9. Taylor, W.A.: Change-Point Analysis: A Powerful New Tool for Detecting Changes. http://www.variation.com/cpa/tech/changepoint.html (2000)

  10. Pettit A.N.: A non-parametric approach to the change-point problem. Appl. Stat. 28(2), 126–135 (1979). doi:10.2307/2346729

    Article  Google Scholar 

  11. Alexandersson H.: A homogeneity test applied to precipitation data. J. Climatol. 6, 661–675 (1986). doi:10.1002/joc.3370060607

    Article  Google Scholar 

  12. Buishand T.A.: Some methods for testing homogeneity of rainfall records. J. Hydrol. 58, 11–27 (1982). doi:10.1016/0022-1694(82)90066-X

    Article  Google Scholar 

  13. McCuen R.H., James L.D.: Nonparametric statistical methods in urban hydrologic Research. J. Am. Water Resour. Assoc. 8, 965–975 (1972). doi:10.1111/j.1752-1688.1972.tb05984.x

    Article  Google Scholar 

  14. Lazaro T.R.: Nonparametric statistical analysis of annual peak flow data from a recently urbanized watershed. J. Am. Water Resour. Assoc. 12, 101–107 (1976). doi:10.1111/j.1752-1688.1976.tb02641.x

    Article  Google Scholar 

  15. Lettenmaier D.P.: Detection of trends in water quality data from records with dependent observations. Water Resour. Res. 12(5), 1037–1046 (1976). doi:10.1029/WR012i005p01037

    Article  Google Scholar 

  16. Helsel D.R., Hirsch R.M.: “Applicability of the t-test for detecting trends in water quality variables,” by Robert H Montgomery and Jim C. Loftis. J. Am. Water Resour. Assoc. 24, 201–204 (1976). doi:10.1111/j.1752-1688.1988.tb00896.x

    Article  Google Scholar 

  17. Kiely G.: Climate change in Ireland from precipitation and streamflow observations. Adv. Water Res. 23, 141–151 (1999)

    Article  Google Scholar 

  18. Kiely G., Albertson J.D., Parlange M.B.: Recent trends in diurnal variation of precipitation at Valentia on the west coast of Ireland. J. Hydrol. 207(3-4), 270–279 (1998)

    Article  Google Scholar 

  19. Yue S., Wang C.Y.: The influence of serial correlation on the Mann–Whitney test for detecting a shift in median. Adv. Water Resour. 25(3), 325–333 (2002)

    Article  Google Scholar 

  20. Cohn T.A., Lins H.F.: Nature’s style: naturally trendy, Geophys. Res. Lett. 32, L23402 (2005). doi:10.1029/2005GL024476

    Article  Google Scholar 

  21. Dos Santos C.A.C., Neale C.M.U., Rao T.V.R., da Silva B.B.: Trends in indices for extremes in daily temperature and precipitation over Utah, USA. Int. J. Climatol. 31, 1813–1822 (2011). doi:10.1002/joc.2205

    Article  Google Scholar 

  22. Zhang X., Hegerl G., Zwiers F.W., Kenyon J.: Avoiding inhomogeneity in percentile-based indices of temperature extremes. J. Clim. 18, 1641–1651 (2005). doi:10.1175/JCLI3366.1

    Article  Google Scholar 

  23. Zhang, X.; Feng, Y.: RClimDex User Manual. Climate Research Division, Science and Technology Branch, Environment Canada. 23 (2004)

  24. Mastrandrea, M.D.; Field, C. B.; Stocker, T.F.; Edenhofer, O.; Ebi, K.L.; Frame, D.J.; Held, H.; Kriegler, E.; Mach, K.J.; Matschoss, P.R.; Plattner, G.K.; Yohe, G.W.; Zwiers, F.W.: Guidance Note for Lead Authors of the IPCC Fifth Assessment Report on Consistent Treatment of Uncertainties. Intergovernmental Panel on Climate Change (IPCC). http://www.ipcc.ch (2010)

  25. Mann H.B.: Nonparametric tests against trend. Econometrica 13(3), 245 (1945). doi:10.2307/1907187

    Article  MATH  MathSciNet  Google Scholar 

  26. Kendall M.G.: Rank correlation method 4th Ed. Charles Griffin, London (1975)

    Google Scholar 

  27. Sen P.K.: Estimates of the regression coefficient based on Kendall’s Tau. J. Am. Stat. Assoc. 63(324), 1379 (1968). doi:10.2307/2285891

    Article  MATH  Google Scholar 

  28. Haylock M.R., Cawley G.C., Harpham C., Wilby R.L., Goodess C.M.: Downscaling heavy precipitation over the United Kingdom: a comparison of dynamical and statistical methods and their future scenarios. Int. J. Climatol. 26, 1397–1415 (2006). doi:10.1002/joc.1318

    Article  Google Scholar 

  29. Dufek A.S., Ambrizzi T.: Precipitation variability in Sao Paulo State, Brazil. Theor. Appl. Climatol. 93, 167–178 (2008). doi:10.1007/s00704-007-0348-7

    Article  Google Scholar 

  30. Singh P., Kumar V., Thomas T., Arora M.: Basin-wide assessment of temperature trends in northwest and central India. Hydrol. Sci. J. 53, 421–433 (2008)

    Article  Google Scholar 

  31. Burn D.H., Sharif M., Zhang K.: Detection of trends in hydrological extremes for Canadian watersheds. Hydrol. Process. 24, 1781–1790 (2010). doi:10.1002/hyp.7625

    Article  Google Scholar 

  32. Salmi, T.; Määttä, A.; Anttila, P.; Ruoho-Airola, T.; Amnell T.: Detecting trends of annual values of atmospheric pollutants by the Mann–Kendall test and Sen’s slope estimates—the excel template application Makesens. Publication on Air Quality, Finnish Meteorological Institute, no. 31, Helsinki, Finland (2002)

  33. Wijngaard J.B., Klein Tank A.M.G., Können G.P.: Homogeneity of 20th century European daily temperature and precipitation series. Int. J. Climatol. 23, 679–692 (2003). doi:10.1002/joc.906

    Article  Google Scholar 

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Azim, F., Shakir, A.S., Rehman, H. et al. Site-Specific Detections of Hydroclimatic Changes for Naran Watershed, Pakistan. Arab J Sci Eng 40, 693–704 (2015). https://doi.org/10.1007/s13369-014-1555-z

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  • DOI: https://doi.org/10.1007/s13369-014-1555-z

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