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An application of time-lag regression technique for assessment of groundwater fluctuations in a regulated river basin: a case study in Northeastern Thailand

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Abstract

Time series techniques have been applied to a wide variety of academic fields, particularly in the fields of economics, environment, and hydrology. This research work deals with application of the time-lag multiple linear regression technique to predicting the groundwater level and salinity fluctuation in a saline but irrigated area in Northeastern Thailand. Regulating gates are constructed to prevent flooding of the river downstream and to provide the surrounding upstream areas with sufficient irrigation water. The technique is essentially based on the lagged correlation between leading variables, i.e. rainfall and river stages, and their corresponding responses, i.e. groundwater depth and salinity. While the rainfall is simulated with a multiple sinusoidal model, the river stage model comprises two components: a single sinusoidal component and a multiple linear regression component implemented with independent variables, i.e. rainfall, regulating gate outflow, and irrigation supply. The shallow groundwater and groundwater salinity fluctuation in the irrigated area are shown by cross-correlation analysis to be dependent upon the surface water regulation and prior rainfall and thus can be simulated by a multiple linear regression with lagged time dependence. Once properly calibrated and verified, the model can perform better matching to the observed data vis-à-vis the conventional multiple linear regression model. The proposed model can also be deployed for forecasting and management of the future groundwater system, especially in situations in which costlier and more complex numerical modeling techniques are inapplicable.

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References

  • Abdalla OAE, Al-Rawahi AS (2013) Groundwater recharge dams in arid areas as tools for aquifer replenishment and mitigating seawater intrusion: example of AlKhod. Oman Environ Earth Sci 69(6):1951–1962

    Article  Google Scholar 

  • Adhikary SK, Rahman M, Gupta AD (2012) A stochastic modeling technique for predicting groundwater table fluctuations with time series analysis. Int J Appl Sci Eng Res 1(2):238–249

    Google Scholar 

  • Anderson MP, Woessner WW (1992) Applied groundwater modeling. Academic Press, San Diego

    Google Scholar 

  • Bennett R (1979) Spatial Time Series. Pion, London

    Google Scholar 

  • Berendrecht WL, Heemink AW, van Geer FC, Gehrels JC (2003) Decoupling of modeling and measuring interval in groundwater time series analysis based on response characteristics. J Hydrol 278:1–16

    Article  Google Scholar 

  • Box GEP, Jenkins GM (1976) Time series analysis: forecasting and control. Holden-Day, San Francisco

    Google Scholar 

  • Caselli F, Esquivel G, Lefort F (1996) Reopening the convergence debate: a new look at cross-country growth empirics. J Econ Growth 1(3):363–389

    Article  Google Scholar 

  • Clean Water Team (CWT) (2004) Electrical conductivity/salinity Fact Sheet, FS-3.1.3.0 (EC). In: The Clean Water Team Guidance Compendium for Watershed Monitoring and Assessment, Version 2.0. Division of Water Quality, California State Water Resources Control Board (SWRCB), Sacramento, CA

  • Commonwealth Scientific and Industrial Research Organization (CSIRO) (2009) Groundwater yields in south-west Western Australia report to the Australian Government from the CSIRO south-west Western Australia sustainable yields project. Technical report, Australia

    Google Scholar 

  • El-Din AG, Smith DW (2002) A combined transfer-function noise model to predict the dynamic behavior of a full-scale primary sedimentation tank. Water Res 36(15):3747–3764

    Article  Google Scholar 

  • Ferdowsian R, Pannell DJ, McCarron C, Ryder A, Crossing L (2001) Explaining groundwater hydrographs: separating typical rainfall events from time trends. Aust J Soil Res 39(4):861–875

    Article  Google Scholar 

  • Ferdowsian R, Ryser A, George R, Bee G, Smart R (2002) Groundwater level reductions under lucerne depend on the landform and groundwater flow systems (local and intermediate). Aust J Soil Res 40(3):381–396

    Article  Google Scholar 

  • Glamore W, Indraratna B (2001) The impact of floodgate modification on water quality in acid sulphate soil terrains. In: Barton ACT (ed) Coasts & Ports 2001: proceedings of the 15th Australasian Coastal and Ocean Engineering Conference, the 8th Australasian Port and Harbour Conference. Institution of Engineers, Australia, pp 265–270

    Google Scholar 

  • Hammer Q, Harper DAT (2006) Paleontological data analysis. Blackwell, Oxford

    Google Scholar 

  • Hammer Q, Harper DAT, Ryan PD (2001) PAST: paleontological statistics software package for education and data analysis. Paleontol Electron 4(1):1–9

    Google Scholar 

  • Harper DAT (1999) Numerical paleobiology. John Wiley, Chichester

    Google Scholar 

  • Hipel KW, McLeod AI (1994) Time series modeling of water resources and environmental systems. Elsevier, Amsterdam

    Google Scholar 

  • Houston JFT (1983) Groundwater system simulation by time series techniques. Groundwater 21(3):301–310

    Article  Google Scholar 

  • Johnston SG, Slavich PG, Hirst P (2005) Opening floodgates in coastal floodplain drains: effects on tidal forcing and lateral transport of solutes in adjacent groundwater. Agric Water Manag 74(1):23–46

    Article  Google Scholar 

  • Kalff J (2002) Limnology. Prentice Hall, Upper Saddle River

    Google Scholar 

  • Kim SJ, Hyun Y, Lee KK (2005) Time series modeling for evaluation of groundwater discharge rates into an urban subway system. Geosci J 9(1):15–22

    Article  Google Scholar 

  • Kroes JG, van Dam JC (2003) Reference Manual SWAP version 3.0.3. Alterra-report 773, Alterra, Research Institute, Wageningen, The Netherlands

  • Kumar CP (2012) Groundwater data requirement and analysis. Technical notes. National Institute of Hydrology, Roorkee

    Google Scholar 

  • Lee CH, Chen WP, Lee RH (2006) Estimation of groundwater recharge using water balance coupled with base-flow-record estimation and stable-base-flow analysis. Environ Geol 51:73–82

    Article  Google Scholar 

  • Machiwal D, Jha MK (2011) Hydrologic time series analysis: theory and practice. Springer (2012 edn)

  • Machiwal D, Jha MK (2014) Characterizing rainfall-groundwater dynamics in a hard-rock aquifer system using time series, geographic information system and geostatistical modelling. Hydrol Process 28:2824–2843

    Article  Google Scholar 

  • Maiti S, Tiwari RK (2014) A comparative study of artificial neural networks, Bayesian neural networks and adaptive neuro-fuzzy inference system in groundwater level prediction. Environ Earth Sci 71(7):3147–3160

    Article  Google Scholar 

  • McLeod AI (1994) Diagnostic checking periodic autocorrelation models with applications. J Time Ser Anal 15:221–233

    Article  Google Scholar 

  • McLeod AI, Hipel KW (1978) Simulation procedures for Box-Jenkins models. Water Resour Res 14(5):969–975

    Article  Google Scholar 

  • Mondal MS, Wasimi SA (2005) Periodic transfer function-noise model for forecasting. J Hydrol Eng 10(5):353–362

    Article  Google Scholar 

  • Mondal MS, Wasimi SA (2006) Generating and forecasting monthly flows of the Ganjes River with PAR Model. J Hydrol 232:41–56

    Article  Google Scholar 

  • Montanari A, Rosso R, Taqqu MS (2000) A seasonal fractional ARIMA model applied to the Nile river monthly flows at Aswan. Water Resour Res 36(5):1249–1259

    Article  Google Scholar 

  • Neill JC (1980) Prediction of rainfall trends. State Water Survey Division, Illinois Institute of Natural Resources

    Google Scholar 

  • Ogallo LAJ (1977) Periodicities and trends in the annual rainfall over Africa. Master’s Thesis, University of Nairobi

  • Panda DK, Mishra A, Jena SK, James BK, Kumar A (2007) The influence of drought and anthropogenic effects on groundwater levels in Orissa, India. J Hydrol 343:140–153

    Article  Google Scholar 

  • Peterson TJ, Western AW (2011) Time-series modeling of groundwater head and its decomposition to historic climate periods. The 34th IAHR World Congress, Brisbane, Australia

  • Renard P (2007) Stochastic hydrogeology: what professionals really need? Gr Water 45:531–541

    Article  Google Scholar 

  • Rodhe H, Virji H (1996) Trends and periodicities in East African rainfall data. Mon Weather Rev 104:307–315

    Article  Google Scholar 

  • Ropelewski CF, Halpert MS (1987) Global and regional scale precipitation patterns associated with El Nino/southern oscillation. Mon Weather Rev 115:1601–1626

    Google Scholar 

  • Salas JD, Delleur JW, Yevjevich V, Lane WL (1980) Applied modeling of hydrologic time series. Water Resources Publication, Colorado

    Google Scholar 

  • Seeboonruang U (2011) An investigation on the effect of groundwater and capillary rise on the salt ponds in Nakhon Panom province Thailand. AGU Fall Meeting 2011, San Francisco

  • Seeboonruang U (2014) Physico-chemical characterization of saline subsurface system near small endorheic ponds in Thailand. Environ Earth Sci 71(7):3273–3286

    Article  Google Scholar 

  • Soltani S, Modarres R, Eslamian SS (2007) The use of time series modeling for the determination of rainfall climates of Iran. Int J Climatol 27:819–829

    Article  Google Scholar 

  • Song SH, Zemansky G (2013) Groundwater level fluctuation in the Waimea Plains, New Zealand: changes in a coastal aquifer within the last 30 years. Environ Earth Sci 70(5):2167–2178

    Article  Google Scholar 

  • Soumya BS, Sekhar M, Riotte J, Banerjee A, Braun JJ (2013) Characterization of groundwater chemistry under the influence of lithologic and anthropogenic factors along a climatic gradient in Upper Cauvery basin South India. Environ Earth Sci 69(7):2311–2335

    Article  Google Scholar 

  • Stein EM (1993) Harmonic analysis. Princeton University Press, Princeton

    Google Scholar 

  • Tankersley CD, Graham WD (1994) Development of an optimal control system for maintaining minimum groundwater levels. Water Resour Res 30:3171–3181

    Article  Google Scholar 

  • Tankersley CD, Graham WD, Hatfield K (1993) Comparison of univariate and transfer function models of groundwater fluctuations. Water Resour Res 29(10):3517–3533

    Article  Google Scholar 

  • Thailand Mineral Resource Department (TMRD) (1998) The study of salt rock in the Lower Namkam Basin irrigation project-Nakhon Panom province. Final Report, Thailand

    Google Scholar 

  • Van Geer FC, Zuur AF (1997) An extension of Box–Jenkins transfer/noise models for spatial interpolation of groundwater head series. J Hydrol 192:65–80

    Article  Google Scholar 

  • Von Asmuch JR, Bierkens PF (2005) Modeling irregularly spaced residual series as a continuous stochastic process. Water Resour Res. doi:10.1029/2004WR003726

    Google Scholar 

  • Von Asmuth JR, Knotters M (2004) Characterizing groundwater dynamics based on a system identification approach. J Hydrol 296:118–134

    Article  Google Scholar 

  • Wetzel RG (2001) Limnology: lake and river ecosystems. Academic Press, San Diego

    Google Scholar 

  • Wildi W (2010) Environmental hazards of dams and reservoirs. http://www.unige.ch/sciences/near/pdf/Wildi%202010.pdf. Accessed 26 June 2013

  • Yi M, Lee K (2003) Transfer function-noise modeling or irregular observed groundwater heads using precipitation data. J Hydrol 288:272–287

    Article  Google Scholar 

Download references

Acknowledgments

This research has been fully funded by King Mongkut’s Institute of Technology Ladkrabang (KMITL). The result in the paper is part of the three-year project: “The Study of Soil and Water Resource Development for Saline Soil Area in Nam Kam Basin, Nakhon Panom Province”. Special thanks to all research assistants and colleagues in the Department of Civil Engineering, KMITL.

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  1. Faculty of Engineering, King Mongkut’s Institute of Technology Ladkrabang, Bangkok, 10520, Thailand

    Uma Seeboonruang

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  1. Uma Seeboonruang
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Correspondence to Uma Seeboonruang.

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Seeboonruang, U. An application of time-lag regression technique for assessment of groundwater fluctuations in a regulated river basin: a case study in Northeastern Thailand. Environ Earth Sci 73, 6511–6523 (2015). https://doi.org/10.1007/s12665-014-3872-7

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  • DOI: https://doi.org/10.1007/s12665-014-3872-7

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