Change point analysis of discharge time series in some hydrometric stations in Golestan Province
Subject Areas : environmental managementEbrahim Asgari 1 , Raoof Mostafazadeh 2 , Khadije Haji 3
1 - M.Sc. student of Watershed Engineering, Faculty of Agriculture and Natural Resources, University of Mohaghegh Ardabili
2 - Assistant Professor, Department of Natural Resources, Faculty of Agriculture and Natural Resources, University of Mohaghegh Ardabili. (Corresponding author)
3 - M.Sc. student of Watershed Engineering, Faculty of Agriculture and Natural Resources, University of Mohaghegh Ardabili
Keywords: Change point analysis, Bootstrap, Water discharge, Gorganroud, Time series,
Abstract :
Background and Objective: Change point analysis technique is an important method to detect potential change in time series. Therefore, the main objective of this research is to determine and analysis of change points in the annual discharge of Golestan Province over 20 hydrometric stations in a 34-years period. Methodology: Time and magnitude of change points have been defined and the results have been analysed along with variations of temperature and precipitation through the study area. According to the results, a significant positive correlation is exist between discharge and precipitation (p<0.001). While, the correlation between discharge and temperature had a negative non-significant correlation. Findings: The results showed that the dominance of change points are decreasing over the study area along with some increasing and no change cases. The number of significant decreasing points were significantly higher than increasing changes and the major changes had occurred in the 1994, 1995, and 1998 years in 4, 5, and 3 stations, respectively (the decreasing points happened over 1994-1998-time span). The highest observed changes was related to Lazoureh station in 1980 and 2011 years which the values of changes in discharge were 3.01 and 0.9 cubic meter per seconds, respectively. Discussion and Conclusion: It can be concluded that, the number and amount of changes in water discharge can be determined by the change point analysis technique. Understanding the trends decrease or increase in watershed rainfall and discharge have an important role in water resources management and water-related issues.
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- Chapman, D., 1996. Water quality assessments - a guide to use of biota, sediments and water in environmental monitoring. Second Edition, Great Britain at the University Press, Cambridge, 609p.
- Xiong, L., and Guo, Sh., 2004. Trend test and change-point detection for the annual discharge series of the Yangtze River at the Yichang hydrological station. Hydrological Sciences Journal, Vol. 49, No. 1, pp. 99-112.
- Dingman, S.L., 2002. Physical hydrology. Second Edition, Prentice Hall, Upper Saddle River, 646p.
- Taylor, W.A., 2000. Change point analysis: a powerful new tool for detecting changes.
- Pettitt, A.N., 1979. A non-parametric approach to change point problem. Applied Statistics, Vol. 28, No. 2, pp. 126-135.
- Killick, R., Fearnhead, P., and Eckley, I.A., 2012. Optimal detection of change points with a linear computational cost. Journal of the American Statistical Association, Vol. 107, No. 500, pp. 1590-1598.
- Kim, Ch., Suh, M.S., and Hong, K.O., 2009. Bayesian changepoint analysis of the annual maximum of daily and subdaily precipitation over South Korea. Journal of Climate, Vol. 22, No. 24, pp. 6741-6757.
- Killick, R., and Eckley, I.A., 2014. Change point: An R package for change point analysis. Journal of Statistical Software, Vol.58, No. 3, pp. 1-19.
- Scott, A.J., and Knott, M., 1974. A cluster analysis method for grouping means in the analysisof variance. Biometrics, Vol. 30, No. 3, pp. 507-512.
- Sen, A., and Srivastava, M.S., 1975. On tests for detecting change in mean. The Annals ofStatistics, Vol. 3, No. 1, pp. 98-108.
- Auger, I.E., and Lawrence, C.E., 1989. Algorithms for the optimal identification of segment Neighborhoods. Bulletin of Mathematical Biology, Vol.51, No. 1, pp. 39-54.
- Bai, J., and Perron, P., 1998. Estimating and testing linear models with multiple structuralchanges. Econometrica, Vol. 66, No. 1, pp. 47-78.
- Reeves, J., Chen, J., Wang, X.L., Lund, R., and Lu, Q., 2007. A review and comparison of changepoint detection techniques for climate data. Journal of Applied Meteorology and Climatology, Vol. 46, No. 6, pp. 900-915.
- Erdman, C., and Emerson, J.W., 2008. A fast bayesian change point analysis for the segmentation of microarray data. Bioinformatics, Vol. 24, No. 19, pp. 2143-2148.
- Zeileis, A., Shah, A., and Patnaik, I., 2010. Testing, monitoring, and dating structural changes inexchange rate regimes. Computational Statistics & Data Analysis, Vol. 54, No. 6, pp. 1696-1706.
- Killick, R., Eckley, I.A., Jonathan, P., and Ewans, K., 2010. Detection of changes in the characteristics of oceanographic timeseries using statistical change point analysis. OceanEngineering, Vol. 37, No. 13, pp. 1120-1126.
- Cavanagh, W.G., Hirst, S., and Litton, C.D., 1988. Soil phosphate, site boundaries, and change pointanalysis. Journal of FieldArchaeology, Vol. 15, pp. 67-83.
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- Zanchettin, D., Traverso, P., and Tomasino, M., 2008. Po River discharges: a preliminary analysis of a 200-year timeseries. Climatic Change, No. 89, pp. 411-433.
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- Mix, K., Lopes, V.L., and Rast, W., 2012. Environmental drivers of streamflow change in the Upper Rio Grande. Water Resources Management, Vol. 26, pp. 253-272.
- Efron, B., 1979. Bootstrap methods: another look at the jackknife«. Annals of Statistics, No. 7, pp. 1-26.
- Wu, C.F.J., 1986. Jackknife, Bootstrap and other resampling methods in regression analysis. The Annals of Statistics, Vol. 14, No. 4, pp. 1261-1295.
- Erdman, C., and Emerson, J.W., 2007. bcp: An R package for performing a Bayesian analysis of change point problems. Journal of Statistical Software, Vol. 23, No. 3, pp. 1-13.