Abstract
In this study, eight record extension techniques were described, their properties were explored, and their performances were examined and compared. The eight record extension techniques are the Ordinary least-squares regression (OLS), Kendall-Theil robust line (KTRL), Maintenance of variance extension techniques (MOVE1, MOVE2, MOVE3, and MOVE4), and two recently developed techniques, the modified KTRL (KTRL2), and the robust line of organic correlation (RLOC). The two recently proposed techniques have the advantages of being robust in the presence of outliers, and they are able to maintain the variance in the extended records. Monte-Carlo experiments were conducted to evaluate the performance of the eight record extension techniques under different levels of data contamination (presence of outliers), different sizes of concurrent records, and different levels of association. The performance of the eight techniques was examined for bias, and standard error of: individual records, moment estimates, and the full range of percentiles. Results showed that for individual record estimates, with uncontaminated data (no outliers), OLS, MOVE3 and MOVE4 provide comparable results and outperform the other techniques under any level of association or size of concurrent records. However, under any level of data contamination, the KTRL outperforms other techniques, for the estimation of individual records, under any level of association or size of concurrent records. In the case of uncontaminated data, MOVE techniques, RLOC and KTRL2 were almost similar and outperform OLS and KTRL in preserving the characteristics of the entire distribution, while MOVE techniques were slightly more precise than RLOC and KTRL2 for small sizes of concurrent records. However, under any level of contaminated data, RLOC and KTRL2 outperform other techniques in preserving the characteristics of the entire distribution, under any level of association and/ or size of concurrent records.
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References
Albek E (2003) Estimation of point and diffuse contaminant loads to streams by non-parametric regression analysis of monitoring data. Water Air Soil Poll 147:229–243
Déry SJ, Mlynowski TJ, Hernandez-Henriquez MA, Straneo F (2011) Interannual variability and interdecadal trends in Hudson Bay streamflow. J Mar Syst 88:341–351
Draper, N.R. and H. Smith: Applied regression analysis, John Wiley, New York, p. 736, 1966.
Göncü S, Albek E (2010) Modeling climate change effects on streams and reservoirs with HSPF. Water Resour Manag 24:707–726
Granato, G.E.: Kendall-Theil Robust Line (KTRLine - version 1), A visual basic program for calculating and graphing robust nonparametric estimates of linear-regression coefficients between two continuous variables: Techniques and Methods of the U.S. Geological Survey, Book 4, chap. A7, 31 p., 2006
Hadzima-Nyarko M, Rabi A, Šperac M (2014) Implementation of artificial neural networks in modeling the water-air temperature relationship of the River Drava. Water Resour Manag 28(5):1379–1394
Helsel DR, Hirsch RM (2002) Statistical methods in water resources. Elsevier Science Publishers, Amsterdam, 522 p
Hirsch RM (1982) A comparison of four streamflow record extension techniques. Water Resour Res 18(4):1081–1088
Hirsch RM, Alexander R, Smith RA (1991) Selection of methods for the detection and estimation of trends in water quality. Water Resour Res 27(5):803–813
Jia Y, Culver TB (2006) Bootstrapped artificial neural networks for synthetic flow generation with a small data sample. J Hydrol 2006(331):580–590
Khalil B, Adamowski J (2012) Record-extension for short gauged water quality parameters using a newly proposed robust version of the line of organic correlation technique. Hydrol Earth Syst Sci 16:2253–2266
Khalil B, Ouarda TBMJ, St-Hilaire A, Chebana F (2010) A statistical approach for the rationalization of water quality indicators in surface water quality monitoring networks. J Hydrol 386:173–185
Khalil B, Ouarda TBMJ, St-Hilaire A (2011) Estimation of water quality characteristics at ungauged sites using artificial neural networks and canonical correlation analysis. J Hydrol 405:277–287
Khalil B, Ouarda TBMJ, St-Hilaire A (2012) Comparison of record-extension techniques for water quality variables. Water Resour Manag 26(14):4259–4280
Kousari MR, Dastorani MT, Niazi Y, Soheili E, Hayatzadeh M, Chezgi J (1857–1872) Trend Detection of Drought in Arid and Semi-Arid Regions of Iran Based on Implementation of Reconnaissance Drought Index (RDI) and Application of Non-Parametrical Statistical Method. Water Resour Manag 28(7):2014
Koutsoyiannis, D. and A. Langousis: Precipitation, Treatise on Water Science, edited by P. Wilderer and S. Uhlenbrook, 2, 27-28, Academic Press, Oxford, 2011
Matalas NC, Jacobs B (1964) A correlation procedure for augmenting hydrologic data. US Geol Survey Prof Paper 434-E:E1–E7
Moog DB, Whiting PJ (1999) Streamflow record extension using power transformations and application to sediment transport. Water Resour Res 35(1):243–254
Morrison, M.A. and J.V. Bonta (2008) Development of duration-curve based methods for quantifying variability and change in watershed hydrology and water quality, United States Environmental Protection Agency, EPA/600/R-08/065
Nevitt J, Tam HP (1998) A comparison of robust and nonparametric estimators under the simple linear regression model. Multi Linear Reg View 25:54–69
Olson O, Gassmann M, Wegerich K, Bauer M (2010) Identification of the effective water availability from streamflows in the Zerafshan river basin, Central Asia. J Hydrol 390:190–197
Raziei T, Saghafian B, Paulo AA, Pereira LS, Bordi I (2009) Spatial patterns and temporal variability of drought in western Iran. Water Resour Manag 23:439–455
Raziei T, Bordi I, Pereira LS (2011) An application of GPCC and NCEP/NCAR datasets for draught variability analysis in Iran. Water Resour Manag 25:1075–1086
Robinson RB, Wood MS, Smoot JL, Moore SE (2004) Parametric modelling of water quality and sampling strategy in a high-altitude Appalachian stream. J Hydrol 287:62–73
Ryu JH, Svoboda MD, Lenters JD, Tadesse T, Knutson CL (2010) Potential extents for ENSO-driven hydrologic drought forecasts in the United States. Clim Chang 101:575–597
Theil H.: A rank-invariant method of linear and polynomial regression analysis, 1, 2, and 3: Ned. Akad. Wentsch Proc., 53, 386-392, 521-525, and 1397-1412, 1950
Vogel RM, Stedinger JR (1985) Minimum variance streamflow record augmentation procedures. Water Resour Res 21(5):715–723
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This research was partially funded by an FQRNT Postdoctoral Fellowship held by Bahaa Khalil, and an NSERC Discovery Grant held by Jan Adamowski.
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Khali, B., Adamowski, J. Evaluation of the Performance of Eight Record-Extension Techniques Under Different Levels of Association, Presence of Outliers and Different Sizes of Concurrent Records: A Monte Carlo Study. Water Resour Manage 28, 5139–5155 (2014). https://doi.org/10.1007/s11269-014-0799-4
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DOI: https://doi.org/10.1007/s11269-014-0799-4