Stochastic Environmental Research and Risk Assessment

, Volume 32, Issue 9, pp 2741–2759 | Cite as

Assessing the restoration time of surface water and groundwater systems under groundwater pumping

  • S. B. Seo
  • G. Mahinthakumar
  • A. Sankarasubramanian
  • M. Kumar
Original Paper


Since surface water and groundwater systems are fully coupled and integrated, increased groundwater withdrawal during drought may reduce groundwater discharges into the stream, thereby prolonging both systems’ recovery from drought. To analyze watershed response to basin-level groundwater pumping, we propose a modelling framework to understand the resiliency of surface water and groundwater systems using an integrated hydrologic model under transient pumping. The proposed framework incorporates uncertainties in initial conditions to develop robust estimates of restoration times of both surface water and groundwater and quantifies how pumping impacts state variables such as soil moisture. Groundwater pumping impacts over a watershed were also analyzed under different pumping volumes and different potential climate scenarios. Our analyses show that groundwater restoration time is more sensitive to variability in climate forcings as opposed to changes in pumping volumes. After the cessation of pumping, streamflow recovers quickly in comparison to groundwater, which has higher persistence. Pumping impacts on various hydrologic variables were also discussed. Potential for developing optimal conjunctive management plans using seasonal-to-interannual climate forecasts is also discussed.


Groundwater pumping Streamflow depletion Restoration time Watershed resiliency 



This research was supported in part by the National Science Foundation under Grant Number 1204368. Any opinions, findings, and conclusions or recommendations expressed in this material are those of the authors and do not necessarily reflect the views of the National Science Foundation.

Supplementary material

477_2018_1570_MOESM1_ESM.docx (397 kb)
Supplementary material 1 (DOCX 397 kb)


  1. Alley WM (2009) Groundwater. In: Likens GE (ed) Encyclopedia of inland waters (vol 1). Academic, LondonGoogle Scholar
  2. Barlow PM, Leake SA (2012) Streamflow depletion by wells—understanding and managing the effects of groundwater pumping on streamflow. U.S. Geological Survey Circular 1376, p 84Google Scholar
  3. Bhatt G, Kumar M, Duffy CJ (2014) A tightly coupled GIS and distributed hydrologic modeling framework. Environ Model Softw 62:70–84. CrossRefGoogle Scholar
  4. Chen X, Kumar M, McGlynn BL (2015) Variations in streamflow response to large hurricane-season storms in a southeastern U.S. watersshed. J Hydrometeorol 15:55–69. CrossRefGoogle Scholar
  5. Condon L, Maxwell R (2014) Feedbacks between managed irrigation and water availability: diagnosing temporal and spatial patterns using an integrated hydrologic model. Water Resour Res. CrossRefGoogle Scholar
  6. Daniel CC (1989) Statistical analysis relating well yield to construction practices and siting of wells in the Piedmont and Blue Ridge Provinces of North Carolina. USGPO; for sale by the books and open-file reports section, US Geological SurveyGoogle Scholar
  7. Devineni N, Sankarasubramanian A (2010a) Improved categorical winter precipitation forecasts through multimodel combinations of coupled GCMs. Geophys Res Lett 37:L24704. CrossRefGoogle Scholar
  8. Devineni N, Sankarasubramanian A (2010b) Improving the prediction of winter precipitation and temperature over the continental United States: role of the ENSO state in developing multimodel combinations. Mon Weather Rev 138(6):2447–2468CrossRefGoogle Scholar
  9. Draper C (2015) California’s excessive pumping during drought could permanently destroy aquifers. Glitch News. Retrieved on 15 May 2016.
  10. Filimonova EA, Shtengelov RS (2013) The dependence of stream depletion by seasonal pumping on various hydraulic characteristics and engineering factors. Hydrogeol J 21(8):1821–1832. CrossRefGoogle Scholar
  11. Fry J, Xian G, Jin S, Dewitz J, Homer C, Yang L, Barnes C, Herold N, Wickham J (2011) Completion of the 2006 national land cover database for the conterminous United States. Photogramm Eng Remote Sens 77(9):858–864Google Scholar
  12. Garner BD, Pool DR, Tillman FD, Forbes BT (2013) Human effects on the hydrologic system of the Verde Valley, Central Arizona, 1910–2005 and 2005–2110, using a regional groundwater flow model. U.S. Geological Survey Scientific Investigations Report 2013-5029Google Scholar
  13. Gleeson T, Wada Y, Bierkens MFP, van Beek LPH (2012) Water balance of global aquifers revealed by groundwater footprint. Nature 488(7410):197–200. CrossRefGoogle Scholar
  14. Harbaugh AW (2005) MODFLOW-2005, the U.S. Geological Survey modular ground-water model—the ground-water flow process: U.S. Geological Survey Techniques and Methods, pp 6-A16Google Scholar
  15. Heath RC (1984) Ground-water regions of the United States. US Government Printing Office, Washington, DC, p 78Google Scholar
  16. Kendy E, Bredehoeft JD (2006) Transient effects of groundwater pumping and surface-water-irrigation returns on streamflow. Water Resour Res 42:1–11. CrossRefGoogle Scholar
  17. Kenny JF, Barber NL, Hutson SS, Linsey KS, Lovelace JK, Maupin MA (2009) Estimated use of water in the United States in 2005: U.S. Geological Survey Circular 1344, p 52Google Scholar
  18. Kollet SJ, Maxwell RM (2008) Capturing the influence of groundwater dynamics on land surface processes using an integrated, distributed watershed model. Water Resour Res. CrossRefGoogle Scholar
  19. Konikow LF, Leake SA (2014) Depletion and capture: revisiting “The Source of Water Derived from Wells”. Groundwater 52(S1):100–111. CrossRefGoogle Scholar
  20. Kumar M, Duffy CJ (2015) Exploring the role of domain partitioning on efficiency of parallel distributed hydrologic model simulations. J Hydrogeol Hydrol Eng 4(1):1–12Google Scholar
  21. Kumar M, Bhatt G, Duffy CJ (2009a) An efficient domain decomposition framework for accurate representation of geodata in distributed hydrologic models. Int J Geogr Inf Sci 23(12):1569–1596CrossRefGoogle Scholar
  22. Kumar M, Duffy CJ, Salvage KM (2009b) A second-order accurate, finite volume-based, integrated hydrologic modeling (FIHM) framework for simulation of surface and subsurface flow. Vadose Zone J 8(4):873. CrossRefGoogle Scholar
  23. Leake SA, Pool DR (2010) Simulated effects of groundwater pumping and artificial recharge on surface-water resources and riparian vegetation in the Verde Valley sub-basin, Central ArizonaGoogle Scholar
  24. Li W, Sankarasubramanian A (2012) Reducing hydrologic model uncertainty in monthly streamflow predictions using multimodel combination. Water Resour Res 48:W12516. CrossRefGoogle Scholar
  25. Li H, Luo L, Wood EF, Schaake J (2009) The role of initial conditions and forcing uncertainties in seasonal hydrologic forecasting. J Geophys Res Atmos 114(4):1–10. CrossRefGoogle Scholar
  26. Li W, Sankarasubramanian A, Ranjithan RS, Sinha T (2016) Role of multimodel combination and data assimilation in improving streamflow prediction over multiple time scales. Stoch Environ Res Risk Assess 30:2255. CrossRefGoogle Scholar
  27. Lin H-T, Ke K-Y, Tan Y-C, Wu S-C, Hsu G, Chen P-C, Fang S-T (2013) Estimating pumping rates and identifying potential recharge zones for groundwater management in multi-aquifers system. Water Resour Manag 27(9):3293–3306. CrossRefGoogle Scholar
  28. Lindsey BBD, Falls WF, Ferrari MJ, Zimmerman TM, Harned DA, Sadorf EM, Chapman MJ (2006) Factors affecting occurrence and distribution of selected contaminants in ground water from selected areas in the Piedmont Aquifer System, Eastern United States, 1993–2003Google Scholar
  29. Lustgarten A (2015) Despite decades of accepted science, California and Arizona are still miscounting their water supplies. ProPublica. Retrieved on 15 May 2016.
  30. Maurer EP, Wood AW, Adam JC, Lettenmaier DP, Nijssen B (2002) A long-term hydrologically based dataset of land surface fluxes and states for the conterminous United States. J Clim 15(22):3237–3251CrossRefGoogle Scholar
  31. Moradkhani H, Hsu KL, Gupta H, Sorooshian S (2005) Uncertainty assessment of hydrologic model states and parameters: sequential data assimilation using the particle filter. Water Resour Res. CrossRefGoogle Scholar
  32. Mueller FA, Male JW (1993) A management model for specification of groundwater withdrawal permits. Eng Fac Publ Present. CrossRefGoogle Scholar
  33. Qu Y, Duffy CJ (2007) A semidiscrete finite volume formulation for multiprocess watershed simulation. Water Resour Res. CrossRefGoogle Scholar
  34. Rasmussen TC, Haborak KG, Young MH (2003) Estimating aquifer hydraulic properties using sinusoidal pumping at the Savannah River Site, South Carolina, USA. Hydrogeol J 11:466–482CrossRefGoogle Scholar
  35. Sankarasubramanian A, Vogel RM (2002) Annual hydroclimatology of the United States. Water Resour Res. ( CrossRefGoogle Scholar
  36. Sankarasubramanian A, Sabo JL, Larson KL, Seo SB, Sinha T, Bhowmik R, Vidal AR, Kunkel K, Mahinthakumar G, Berglund EZ, Kominoski J (2017) Synthesis of public water supply use in the U.S.: spatio-temporal patterns and socio-economic controls. Earth’s Future. CrossRefGoogle Scholar
  37. Scibek J, Allen DM, Cannon AJ, Whitfield PH (2007) Groundwater–surface water interaction under scenarios of climate change using a high-resolution transient groundwater model. J Hydrol 333(2–4):165–181. CrossRefGoogle Scholar
  38. Seo SB, Sinha T, Mahinthakumar K, Sankarasubramanian A, Kumar M (2016) Identification of dominant source of errors in developing streamflow and groundwater projection under near-term climate change. J Geophys Res Atmos. CrossRefGoogle Scholar
  39. Shi Y, Davis KJ, Duffy CJ, Yu H (2013) Development of a coupled land surface hydrologic model and evaluation at a critical zone observatory. J Hydrometeorol 15:1401–1419. CrossRefGoogle Scholar
  40. Singh H, Sinha T, Sankarasubramanian A (2014) Impacts of near-term climate change and population growth on within-year reservoir systems. J Water Resour Plan Manag. CrossRefGoogle Scholar
  41. Sinha T, Sankarasubramanian A (2013) Role of climate forecasts and initial conditions in developing streamflow and soil moisture forecasts in a rainfall–runoff regime. Hydrol Earth Syst Sci 17(2):721–733. CrossRefGoogle Scholar
  42. Sophocleous M (2002) Interactions between groundwater and surface water: the state of the science. Hydrogeol J 10(1):52–67. CrossRefGoogle Scholar
  43. Wang R, Kumar M, Marks D (2013) Anomalous trend in soil evaporation in a semi-arid, snow-dominated watershed. Adv Water Resour 57:32–40. CrossRefGoogle Scholar
  44. Weaver JC (2005) The drought of 1998–2002 in North Carolina-precipitation and hydrologic conditions, U.S. Geol. Surv. Scientific Investigations Report 2005–5053, p 88Google Scholar
  45. Winter TC, Harvey JW, Franke OL, Alley WM (1998) Ground water and surface water: a single resource, Circular 1139, U.S. Geological Survey, Denver, ColoGoogle Scholar
  46. Woolfenden R, Nishikawa T (2014) Simulation of groundwater and surface-water resources of the Santa Rosa Plain Watershed, Sonoma County, California. U.S. Geological Survey Scientific Investigations Report 2014-5052, p 292Google Scholar
  47. Yossef NC, Winsemius H, Weerts A, Van Beek R, Bierkens MFP (2013) Skill of a global seasonal streamflow forecasting system, relative roles of initial conditions and meteorological forcing. Water Resour Res 49(8):4687–4699. CrossRefGoogle Scholar
  48. Yu X, Lamačová A, Duffy CJ, Krám P, Hruška J, White T, Bhatt G (2013) Modeling the long term water yield effects of forest management in a Norway spruces forest. Hydrol Sci J. CrossRefGoogle Scholar
  49. Zhang M, Chen X, Kumar M, Marani M, Goralczyk M (2017) Hurricanes and tropical storms: a necessary evil to ensure water supply? Hydrol Process 31(24):4414–4428CrossRefGoogle Scholar
  50. Zume J, Tarhule A (2007) Simulating the impacts of groundwater pumping on stream–aquifer dynamics in semiarid northwestern Oklahoma, USA. Hydrogeol J 16(4):797–810. CrossRefGoogle Scholar

Copyright information

© Springer-Verlag GmbH Germany, part of Springer Nature 2018

Authors and Affiliations

  1. 1.Institute of Engineering ResearchSeoul National UniversitySeoulSouth Korea
  2. 2.Department of Civil Construction, and Environmental EngineeringNorth Carolina State UniversityRaleighUSA
  3. 3.Nicholas School of EnvironmentDuke UniversityDurhamUSA

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