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Time series analysis of groundwater levels and projection of future trend

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Journal of the Geological Society of India

Abstract

A study was under taken for identifying the trends in pre and post-monsoon groundwater levels using Mann- Kendall test and Sen’s slope estimator, and for time series modelling of groundwater levels for forecasting the pre and post-monsoon water levels in Karnal district of Haryana. Results showed that the groundwater levels had significantly declined during 1974 to 2010. Average rates of water level decline were 0.228 and 0.267 m/yr during pre and postmonsoon seasons, respectively. There was rapid decline in water level between 2001 and 2010. The ARIMA (0, 1, 2) was identified as the appropriate model for time series modelling and forecasting. Results showed that the pre and postmonsoon groundwater level in 2050 would decline by 12.97 m and 12.00 m over the observed water level in 2010, and reach to a level of 29.95 m and 28.14 m below ground surface. The average rate of decline of pre and post-monsoon groundwater level in the district during this period would be 0.32 and 0.30 m/yr, respectively.

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References

  • Adamowski, K. and Hamory, T. (1983) A stochastic systems model of groundwater level fluctuations. Jour. Hydrol., v.62, pp.129–147.

    Article  Google Scholar 

  • Allen, D.M. (2010) Historical trends and future projections of groundwater levels and recharge in costal British Columbia, Canada. Azores, Portugal SWIM 21-21st Salt Water Intrusion meeting June 21–26, pp. 267–270.

    Google Scholar 

  • Ambast, S.K., Tyagi, N.K. and Raul, S.K. (2006) Management of declining groundwater in the Trans Indo-Gangetic Plain (India): some options. Agric.Water Manag., v.82, pp. 279–296.

    Article  Google Scholar 

  • Arora, M., Goel, N.K. and Singh, P. (2005) Evaluation of temperature trends over India. Hydrol. Sci. Jour., v.50(1), pp.81–93.

    Google Scholar 

  • Aziz, O.I.A. and Burn, D.H. (2006) Trends and variability in the hydrological regime of the Mackenzie River basin. Jour. Hydrol., v.319(1–4), pp. 282–94.

    Article  Google Scholar 

  • Bandyopadhyay, A., Bhadra, A., Raghuwanshi, N.S. and Singh, R. (2009) Temporal trends in estimates of reference evapotranspiration over India. Jour. Hydrol. Engg., v.4(5), pp.508–15.

    Article  Google Scholar 

  • Box, G.E.P. and Jenkins, G.M. (1976) Time series analysis,forecasting and control. Holden Day: San Francisco, California, USA, pp.625.

    Google Scholar 

  • Cgwb (2012) Groundwater year book-India. Central Ground Water Board Ministry of Water Resources Government of India Faridabad, pp.1–63.

    Google Scholar 

  • Chen, Hu., Guoa, S., Chong-Yu Xu, and Singh, V.P. (2007) Historical temporal trends of hydro-climatic variables and runoff response to climate variability and their relevance in water resource management in the Hanjiang basin. Jour. Hydrol., v.344, pp.171–184.

    Article  Google Scholar 

  • Cwc (2010) Water and related statistics. Information system organization Water planning & project wing Central Water Commission, India, pp.1–264.

    Google Scholar 

  • Goyal, S.K., Chaudhari, B.S., Singh, O., Sethi, G.K. and Thakur, P.K. (2010) Variability analysis of groundwater levels–A GIS based case Study. Jour. Indian Soc. Remote Sens., v.38, pp.355–364.

    Article  Google Scholar 

  • Hamdi, M.R., Ahmed N. Bdour, A.N., Zeyad, S. and Tarawneh, Z.S. (2008) Developing reference crop evapotranspiration time series simulation model using class a pan: a case study for the Jordan Valley /Jordan. Jordan Jour. Earth and Environ. Sci., v.1(1), pp.33–44.

    Google Scholar 

  • Hesel, D.R. and Hirsch, R.M. (1992) Statistical Methods in Water Resources, Elsevier, Amsterdam.

    Google Scholar 

  • Hirsch, R.M. and Slack, J.R. (1984) A nonparametric trend test for seasonal data with serial dependence. Water Resour. Res., v.20(6), pp.727–732.

    Article  Google Scholar 

  • Houston, J.F.T. (1983) Groundwater system simulation by time series techniques. Ground Water, v.3(3), pp.301–310.

    Article  Google Scholar 

  • Jahanbakhsh, S. and Babapour Basseri, E.A. (2003) Studying and forecasting of the mean monthly temperature of Tabriz, using ARIMA model. Jour. Geographic Res., v.15(3), pp.34–46.

    Google Scholar 

  • Kampata, J.M., Parida, B.P. and Moalafhi, D. B. (2008) Trend analysis of rainfall in the head streams of the Zambezi River Basin in Zambia. Physics and Chemistry of the Earth, v.33, pp.621–625.

    Article  Google Scholar 

  • Karamouz, M. and Zahraie, B. (2004). Seasonal stream flow forecasting using snow budget and ElNino Southern Oscillation climate signals: Application to the Salt River Basin in Arizona. Jour. Hydrol. Engg., v.9(6), pp.523–533.

    Google Scholar 

  • Kawamura, A., Bui, D.D., Tong, T.N, Amaguchi, H., and Nakagawa, N. (2011) Trend Detection in Groundwater Levels of Holocene Unconfined Aquifer in Hanoi, Vietnam, by Non-Parametric Approaches. 9th Symp. Groundwater Hydrology, Quality, and Management, pp.914–923.

    Google Scholar 

  • Kendall, M.G. (1955) Rank Correlation Methods, Charles Griffin: London.

    Google Scholar 

  • Kendall, M.G. (1975) Rank Correlation Methods, 4th edition. Charles Griffin, London, U.K.

    Google Scholar 

  • Law, A.G. (1974) Stochastic analysis of groundwater time series in the western United States, Hydrology paper no. 68. Colorado State University, Fort Collins, Colorado, USA, 26.

    Google Scholar 

  • Luo, Y., Liu, S., Fu, S. F., Liu, J., Wang, G. and Zhou, G. (2008) Trends of precipitation in Beijiang River Basin, GuangdongProvince, China. Hydrol. Processes, v.22, pp.2377–2386.

    Article  Google Scholar 

  • Mann, H. B. (1945) Nonparametric tests against trend. Econometrica, v.13, pp.245–259.

    Article  Google Scholar 

  • Mondal, A., Kundu, S. and Mukhopadhyay, A. (2012) Rainfall trend analysis by Mann-Kendall Test: A case study of North-Eastern part of Cuttack district, Orissa. Internat. Jour. Geol., Earth Environ. Sci., v.2(1), pp.70–78.

    Google Scholar 

  • Panda, D.K. and Kumar, A. (2011) Evaluation of an over-used costal aquifer (Orissa, India) using statistical approaches. Hydrol. Sci. Jour., v.56(3), pp. 486–497.

    Article  Google Scholar 

  • Panda, D.K., Mishra, A. and Kumar, A. (2012) Quantification of trends in groundwater levels of Gujarat in western India. Hydrol. Sci. Jour., v.57(7), pp.1325–1336.

    Article  Google Scholar 

  • Partal, T. and Kahya, E. (2006) Trend analysis in Turkish precipitation data. Hydrol. Processes, v.20, pp. 2011–2026.

    Article  Google Scholar 

  • Patle, G.T., Singh, D.K., Sarangi, A., Rai, A., Khanna, M. and Sahoo, R.N. (2013) Temporal variability of climatic parameters and potential evapotranspiration. Indian Jour. Agric. Sci., v.83(4), pp.518–524.

    Google Scholar 

  • Ramazanipour, M. and Roshani, M. (2011) Seasonal trend analysis of precipitation and discharge parameters in Guilan, north of the Iran. International Conference on Humanities, Geography and Economics (ICHGE’2011) Pattaya, pp.290–293.

    Google Scholar 

  • Salmi, T., Maata, A., Antilla, P., Ruoho Airola, T. and Amnell, T. (2002) Detecting trends of annual values of atmospheric pollutants by the Mann-Kendall test and Sen’s slope estimatesthe Excel template application Makesens. Finnish Meteorological Institute, Helsinki, Finland, 35p.

    Google Scholar 

  • Samsudin, R., Saad, P. and Shabri, A. (2011) River flow time series using least squares support vector machines. Hydrol. Earth System Sci., v.15, pp.1835–1852.

    Article  Google Scholar 

  • Sen, P.K. (1968) Estimates of the regression coefficient based on Kendall’s tau. Journal of American Statistical Association, v.39, pp.1379–1389.

    Article  Google Scholar 

  • Shamsnia, S. A., Shahidi, N., Liaghat, A. Sarraf, A. and Vahdat, S.F. (2011) Modeling of weather parameters using stochastic methods (ARIMA Model) Case Study: Abadeh Region, Iran. Int. Conf. on Environment and Industrial Innovation IPCBEE, v.12, pp. 282–285.

    Google Scholar 

  • Shamsudduha, M., Chandler, R.E., Taylor, R.G. and Ahmed, K.M. (2009) Recent trends in groundwater levels in a highly seasonal hydrological system: the Ganges-Brahmaputra-Meghna Delta. Hydrol. Earth System Sci., v.13, pp. 2373–2385.

    Article  Google Scholar 

  • Sharma, K.D. (2009) Groundwater management for food security. Current sci., v.96(11), pp. 444–447.

    Google Scholar 

  • Tabari, H., Marofi, S., Aeini, A., Talaee, P.H. and Mohammadi, K. (2011) Trend analysis of reference evapotranspiration in the western half of Iran. Agric. and Forest Meteorol., v.151(2), pp.128–136.

    Article  Google Scholar 

  • Tabari, H., Nikbakht, J. and ShiftehsomeE, B. (2012) Investigation of groundwater level fluctuations in the north of Iran. Environ. Earth Sci., v.66(1), pp.231–243

    Article  Google Scholar 

  • Thakur, G.S. and Thomas, T. (2011) Analysis of Groundwater levels for Detection of Trend in Sagar District, Madhya Pradesh. Jour. Geol. Soc. India, v.77, pp.303–308.

    Article  Google Scholar 

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Patle, G.T., Singh, D.K., Sarangi, A. et al. Time series analysis of groundwater levels and projection of future trend. J Geol Soc India 85, 232–242 (2015). https://doi.org/10.1007/s12594-015-0209-4

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  • DOI: https://doi.org/10.1007/s12594-015-0209-4

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