Document Type : Research Article

Authors

1 Birjand University

2 Urmia University

3 Urmia Unuversity

Abstract

Introduction: Drought from the hydrological viewpoint is a continuation of the meteorological drought that cause of the lack of surface water such as rivers, lakes, reservoirs and groundwater resources. This analysis, which is generally on the surface streams, reservoirs, lakes and groundwater, takes place as hydrological drought considered and studied. So the data on the quantity of flow of the rivers in this study is of fundamental importance. This data are included, level, flow, river flow is no term (5). Overall the hydrological drought studies are focused on annual discharges, maximum annual discharge or minimum discharge period. The most importance of this analysis is periodically during the course of the analysis remains a certain threshold and subthresholdrunoff volume fraction has created. In situations where water for irrigation or water of a river without any reservoir, is not adequate, the minimum flow analysis, the most important factor to be considered (4). The aim of this study is evaluatingthe statistical distributions of drought volume rivers data from the Urmia Lake’s rivers and its return period.
Materials and Methods: Urmia Lake is a biggest and saltiest continued lake in Iran. The Lake Urmia basin is one of the most important basins in Iran region which is located in the North West of Iran. With an extent of 52700 square kilometers and an area equivalent to 3.21% of the total area of the country, This basin is located between the circuit of 35 degrees 40 minutes to 38 degrees 29 minutes north latitude and the meridian of 44 degrees 13 minutes to 47 degrees 53 minutes east longitude. In this study used the daily discharge data (m3s-1) of Urmia Lake Rivers.
Extraction of river drought volume The drought durations were extracted from the daily discharge of 13 studied stations. The first mean year was calculated for each 365 days using the Eq 1 (14).
(1) (For i=1,2,3,…,365)

That Ki is aith mean year, Yijis ith day discharge in jth year and n is number of period years. After the extraction the 1 to ndays drought duration, the years with no data were complete with Regression or interpolation methods. After the extraction, data initial evaluation (Trend, Independence and Stationarity) and completed the drought volume data, these data were fitted by the common distribution functions and select the best function based on Kolmogorov-Sminnov test. To read more information about the data initial evaluations see the NazeriTahroudi et al (15).
Log Pearson type 3 distribution Log Pearson type 3 distribution and its parameters is (7 & 12):
(2)

After selectingthe best distribution function based on Kolmogorov - Smirnov test, estimated the selected function parameter to evaluate the return period. For this purpose, there are many methods such as moments, Sundry Average method (SAM), Logarithm of applied moments observations and maximum likelihood that in this study were compared.
Results and Discussion: In this study, using daily flow data fromstations studied; the drought volume of days 1 to 60 was extracted, corrected, and completed. Before fitting the extraction drought volume river data with distribution function, the mentioned data were investigated with Wald-Wolfowitz (Independence and Stationary), Kendall (Trend) and Wilcoxon (Homogeneity) tests and the results of these tests were accepted in two significant levels of 1 and 5 percentages. Before estimatingthe Log Pearson type III parameters, first the drought volume river data were modeled by the Easy Fit software and common distribution functions and Log Pearson type III was selected by the Kolmogorov – Smirnov test as the best function. Results of two Anderson Darling and Chi Squared tests foraccurate evaluation were added. After initial evaluation of data and statistic tests, the time series of drought Volume River data of the studyarea were fitted by log Pearson type III. To estimatethe Log Pearson type III parameters used the sundry average method and to investigatethe accuracy of this method, 3 methods (moment, maximum likelihood and Logarithm of applied moment observations) were used and 4 mentioned methods for all of rivers were calculated. The most river drought relating to Gadar-Chai river with 1742 million cubic meters low volume and the lowest of it relating to Mardoq-Chai river with 68 million cubic meters low volume in 10000 year return period. After Gadar-Chai river the most low volume of discharge relating the Zarineh-rood river. Two Zarineh-rood and Gadar-Chai rivers among other rivers have a higher average discharge. Log Normal III, Gamma, Wikeby and GEV distributions have a good fitting on river flows data and no difference in investigation models that corresponded with Mosaedi et al (13) and NazeriTahroudi et al (15). The results of Grifits (7) also introduced the Wikeby distribution has a better than Beta distribution. Lee (12) also with evaluation the rainfall frequency in the study the rainfall concentration properties in Chia-Nan (Taiwan) introduced the Log Pearson type III as the best distribution function between the common distribution function. Results of Chi-Squared test in methods of parameter estimation showed that all methods are acceptable.
Conclusion: Drought occurrence can be estimated bythe analysis of historical data for different regions and using the results of predicting problems can be reduced. In this research daily river flow of Lake Urmia basin applied to calculate drought volume of rivers. Log Pearson III distribution selected among current hydrological distribution functions for fitting drought volume of rivers. Using selected distribution function and Sundry Average Moment method for estimating parameters return period of drought from 2 to 10000 years extracted. Results showed that volume of drought for Shahar-chai , Barandoz-chai, Nazlu-Chai, Mahabad-Chai, Rozeh-Chai, Gadar-chai, Simineh-rood, Zola-chai, Aji-chai, Sofi-chai, Leilan-chai and Mardoq-chay rivers in the return period of 10000 years will be 92, 125, 228, 150, 110, 1742, 90, 77, 690, 280, 65, 68 Mm3 respectively.

Keywords

1- Bobee B., and Ashkar F. 1988. Sundry Averages Method (SAM) for Estimating Parameters of the Log-Pearson Type 3 Distribution. INRS-Eau Publication, Quebec Canada, 30 pages.
2- Bowker AH., Gerald J., and Lieberman H. 1972. Engineering Statistics, Prentice-Hall, Second Edition.
3- Claudio A., Cannarozzo M., and Rosario Mazzola M. 2006. Multi-year drought frequency analysis at multiple sites by operational hydrology– A comparison of methods. Physics and Chemistry of the Earth, Parts A/B/C. 31(18): 1146-1163.
4- Dai AK., and Trenberth K. 1998. Palmer Drought servity. Global variation in drought and wet spells 1900-1950. Geophysical Research letter 253367.
5- Farajzadeh M. 2005. Drought (From concept to solution). Page 112. Armed Forces Geographical Organization. (In Persian with English abstract).
6- Fatehi-Peykani H. 2009. A statistical approach for distribution of wind speed. Seventh National Conference on Energy. Tehran. (In Persian with English abstract).
7- Griffiths GA. 1989. A theoretically based Wakeby distribution for annual flood series. Hydrological Sciences, journal, des sciences Hidrologiques, 34. pages 231-248.
8- Houghton JC. 1978. Birth of a parent: the Wakeby distribution for modeling flood flow. Water Resources Research, 14(6): 1105-1109.
9- Khalili K., Nazeri Tahrudi M., Abbaszadeh Afshar M., and Nazeri Tahrudi Z. 2014. Comparison different peak flow frequency distribution functions. Journal of Middle East Applied Science and Technology. Issue 7. Vol 4.
10- Kroll CN., and Voge RM. 2002. Probability distribution Of low stream flow series in the United states. Journal of hydrologic Engineering, 7(2), 137-146.
11- Kumar R., and Chatterjee C. 2005. Regional flood frequency analysis using L-moments for North Bahmaputra region of India. Journal of hydrologic Engineering, 10(1), 1-7.
12- Lee CY. 2004, Department of Soil and Water Conservation National Pingtung University of Science and Technology,Neipu,Pingtung Hsien 912, Taiwan (ROC).
13- Mosaedi A., Zanganeh M., Saman-Manesh H., and Karimirad A. 2009. Choose the bests distributions functions of 1 to 30 days discharges, the case study: Gonbad Kavous hydrometer station. Watershed's Fifth National Conference on Science and Engineering. (Sustainable management of natural disasters). Gorgan University. (In Persian with English abstract)
14- Nazeri Tahroudi M., and Khalili K. 2013. Investigation the SAM and Moments methods to estimation the Log-Pearson type III parameters (Case study: Urmia lake basin rivers). National Conference of Recession impact on water resources and soil water level in the Urmia Lake. Tabriz. (In Persian with English abstract)
15- Nazeri Tahroudi M., Gholamzadeh Bazarbash R., Nazeri Tahroudi Z., and Khalili K. 2013. Evaluation of the distribution models to estimation the peak discharge return period using the HYFRAN models (Case study: Babolrood River). National conference on applied research in science and engineering, Takestan. (In Persian with English abstract)
16- Nguyen VT. 2006. On regional estimation of floods for ungaged sites, Asia oceania geosciences society, McGill University, Singapore.
17- Serinaldi F., Bonaccorso B., Cancelliere A., and Grimaldi S. 2009. Probabilistic characterization of drought properties through copulas. Physics and Chemistry of the Earth, Parts A/B/C, 34(10): 596-605.
18- Shahmohammadi Z., Hagigatjo P., and Afrasiab P. 2001. Determined the number of long-term drought and wet years based on annual rainfall in Irene, Proceedings of the first conference examining ways to tackle water crisis, Zabol University. (In Persian with English abstract)
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