Groundwater Irrigated Agriculture Evolution in Central Punjab, Pakistan

  • Muhammad UsmanEmail author
  • Rudolf Liedl
  • Fan Zhang
  • Muhammad Zaman
Part of the Sustainable Agriculture Reviews book series (SARV, volume 33)


Irrigation water for agriculture in Pakistan is an issue due to a significant difference between rainfall and crop water needs. Irrigation water is either coming from snowmelt and rainfall in the northern mountains, or being pumped from groundwater. Canal water is limited, and water distribution using the warabandi system, a fixed canal water rotation system among water users on a particular irrigation channel, is not adequate and flexible. The result is overdependence on groundwater, which has impaired crop growth, notably in regions of bad groundwater quality.

The history of groundwater use is not very old in Punjab, Pakistan. By the end of 1990s, canal irrigation was dominant, which was then surpassed by groundwater at the start of 1991s. Since then the groundwater development has expanded exponentially, and recently the groundwater share in irrigated agriculture of the country is about 50%. By the end of 2013, more than one million tubewells are operational in the country and most of them are located in the Punjab province. The consequence is a drop of groundwater level in majority canal commands including the lower Chenab canal irrigation system. Evapotranspiration is the major outflow from the water balance in the region. Cultivation of high delta crops during kharif seasons including rice, cotton and sugarcane are responsible, which is triggered by elevated temperatures. During rabi seasons, wheat is the single major crop all over the lower Chenab canal with its coverage on more than 50% area. The overall recharge results showed that rainfall is the major inflow during kharif seasons, while during rabi canal seepage dominates all other recharge sources. During kharif, the other major sources of recharge are field percolations, canal seepage, watercourse losses and distributary losses. Rainfall recharge, field percolation, watercourse losses and distributary losses are considered major recharge sources during rabi seasons.


Groundwater Recharge Remote sensing Modelling Kharif Rabi Climate change Punjab Pakistan 


  1. Agricultural Statistics of Pakistan (2008–09) Government of Pakistan. Ministry of Food and Agriculture (Economic Wing), Islamabad, PakistanGoogle Scholar
  2. Ahmed N, Chaudhry GR (1988) Irrigated Agriculture of Pakistan. Shahzad Nazir Publisher, LahoreGoogle Scholar
  3. Akhtar M, Ahmad N, Booij MJ (2008) The impact of climate change on the water resources of Hindukush–Karakorum–Himalaya region under different glacier coverage scenarios. J Hydrol 355(1–4):148–163. CrossRefGoogle Scholar
  4. Altman DG (1991) Practical statistics for medical research. Chapman and Hall, London. CrossRefGoogle Scholar
  5. Ashraf A, Ahmad Z (2008) Regional Groundwater Flow Modelling of upper Chaj Doab of Indus Basin, Pakistan using Finite Element Model (Feflow) and Geoinformatics. Geophys J Int 173(1):17–24CrossRefGoogle Scholar
  6. Aslam M, Prathapar SA (2006) Strategies to mitigate secondary salinization in the Indus Basin of Pakistan: a selective review. Research Report 97. Colombo, Sri Lanka: International Water Management Institute (IWMI).
  7. Awan UK, Ismaeel A (2015) A new technique to map groundwater recharge in irrigated areas using a SWAT model under changing climate. J Hydrol 519:1368–1382. CrossRefGoogle Scholar
  8. Ayars JE, Christen EW, Soppe RW, Meyer WS (2006) The resource potential of in-situ shallow ground water use in irrigated agriculture: a review. Irrig Sci 24:147–160CrossRefGoogle Scholar
  9. Baalousha H (2005) Using CRD method for quantification of groundwater recharge in the Gaza Strip, Palestine. Environ Geol 48(7):889–900CrossRefGoogle Scholar
  10. Badruddin M (1996) Country profile. Pakistan Internal Report. International Water Management Institute (IWMI): Lahore, PakistanGoogle Scholar
  11. Bastiaanssen WGM, Menenti M, Feddes RA, Holtslag AAM (1998) A remote sensing surface energy balance algorithm for land (SEBAL) 1. Formulation. J Hydrol 212(213):198–212CrossRefGoogle Scholar
  12. Bhutta MN, Alam MM (2005) Perspective and limits of groundwater use in Pakistan. Groundwater Research and Management: Integrating Science into Management Decisions, Roorkee, India, pp 105–113Google Scholar
  13. Bhutta MN, Smedema K (2007) One hundred years of waterlogging and salinity control in the Indus valley, Pakistan: a historical review. Irrig Drain 56:81–90CrossRefGoogle Scholar
  14. Bowen I (1926) The ratio of heat losses by conduction and by evaporation from any water surface. Phys Rev 27:779–787CrossRefGoogle Scholar
  15. Boonstra J, Bhutta MN (1996) Groundwater recharge in irrigated agriculture: the theory and practice of inverse modeling. J Hydrol 174(3–4):357–374CrossRefGoogle Scholar
  16. Brutsaert W (2005) Hydrology: an introduction. Cambridge University Press, New York, 605 pp, ISBN 0-521-82479-6Google Scholar
  17. Brutsaert W, Stricker H (1979) An advection-aridity approach to estimate actual regional evapotranspiration. Water Resour Res 15(2):443–450CrossRefGoogle Scholar
  18. Chaudhary MR, Bhutta NM, Iqbal M, Subhani KM (2002) Groundwater resources: use and impact on soil and crops. Paper presented at the Second South Asia Water Forum, 14–16 December, Islamabad, PakistanGoogle Scholar
  19. Christmann S, Martius C, Bedoshvili D et al (2009) Food security and climate change in Central Asia and the Caucasus. Sustainable agriculture in Central Asia and the Caucasus Series No. 7. CGIAR-PFU, Tashkent, UzbekistanGoogle Scholar
  20. Chu JT, Xia J, Xu CY, Singh VP (2010) Statistical downscaling of daily mean temperature, pan evaporation and precipitation for climate change scenarios in Haihe River, China. Theor Appl Climatol 99:149–161CrossRefGoogle Scholar
  21. COMSATS (Commission on Science and Technology for Sustainable Development in the South) (2003) Water resources in the south: present scenario and future prospects. COMSATS, IslamabadGoogle Scholar
  22. Congalton RG (1996) Accuracy assessment: a critical component of land cover mapping. In: Gap analysis: a landscape approach to biodiversity planning, a peer-reviewed proceedings of the ASPRS/GAP Symposium, 27 February – 2 March 1995, Charlotte, NC, pp 119–131Google Scholar
  23. Crosbie RS, McCallum JL, Harrington GA (2009) Diffuse groundwater recharge modelling across northern Australia. A report to the Australian government from the CSIRO northern Australia sustainable yields project. CSIRO Water for a Healthy Country Flagship, Australia, p 56Google Scholar
  24. Darcy H (1856) Les Fontaines Publiques de la Ville de Dijon. Dalmont, ParisGoogle Scholar
  25. Diaz-Nieto J, Wilby RL (2005) A comparison of statistical downscaling and climate change factor methods: impacts on low flows in the River Thames, United Kingdom. Clim Change 69(2):245–268. CrossRefGoogle Scholar
  26. Dibike YB, Coulibaly P (2005) Hydrologic impact of climate change in the Saguenay watershed: comparison of downscaling methods and hydrologic models. J Hydrol 307(1–4):145–163. CrossRefGoogle Scholar
  27. Döll P (2009) Vulnerability to the impact of climate change on renewable groundwater resources: a global-scale assessment. Environ Res Lett 4:035006. CrossRefGoogle Scholar
  28. Elshamy ME, Seierstad IA, Sorteberg A (2009) Impacts of climate change on Blue Nile flows using bias-corrected GCM scenarios. Hydrol Earth Syst Sci 13:551–565. CrossRefGoogle Scholar
  29. FAO (2010) AQUASTAT – FAO’s global information system on water and agriculture, FAO.
  30. Foody GM (2002) Status of land cover classification accuracy assessment. Remote Sens Environ 80:85–201CrossRefGoogle Scholar
  31. Giorgi F, Hewitson B, Christensen J, Hulme M, Von Storch H, Whetton P, Jones R, Mearns L, Fu C (2001) Regional climate information – evaluation and projections. In: Houghton JT, Ding Y, Griggs DJ, Noguer M, van der Linden PJ, Dai X, Maskell K, CA Johnson (eds) Climate change 2001: the scientific basis. contribution of Working Group I to the third assessment report of the intergovernmental panel on climate change. Cambridge University Press, Cambridge, New York, 881ppGoogle Scholar
  32. Giri C, Clinton J (2005) Land cover mapping of greater mesoamerica using MODIS data. Remote Sens 31(4):274–282Google Scholar
  33. GOP (2000) Agricultural statistics of Pakistan. Ministry of Food, Agriculture and Livestock, Economics Division, and Government of Pakistan, IslamabadGoogle Scholar
  34. Habib Z (2004) Scope for reallocation of river waters for agriculture in the Indus Basin. Ph.D thesis l’Ecole Nationale du Génie Rural, des Eaux et Forêts Centre de ParisGoogle Scholar
  35. Hashmi M, Shamseldin A, Melville B (2011) Comparison of SDSM and LARS-WG for simulation and downscaling of extreme precipitation events in a watershed. Stoch Env Res Risk A 25(4):475–484. CrossRefGoogle Scholar
  36. Hassan ZH, Bhutta MN (1996) A water balance model to estimate groundwater recharge in Rechna Doab. Irrig Drain Syst 10:297–317CrossRefGoogle Scholar
  37. Hay LE, Clark MP (2003) Use of statistically and dynamically downscaled atmospheric model output for hydrologic simulations in three mountainous basins in the western United States. J Hydrol 282(1–4):56–75. CrossRefGoogle Scholar
  38. Hetze F, Vaessen V, Himmelsbach T, Struckmeier W, Villholth K (2008) Groundwater and climate change: challenges and possibilities. BGR
  39. Hobbins MT, Ramirez JA (2001) The complementary relationship in estimation of regional evapotranspiration: an enhanced advection-aridity model. Water Resour Res 37(5):1389–1403CrossRefGoogle Scholar
  40. Huang J, Zhang J, Zhang Z, Xu C, Wang B, Yao J (2011) Estimation of future precipitation change in the Yangtze River basin by using statistical downscaling method. Stoch Env Res Risk A 25(6):781–792. CrossRefGoogle Scholar
  41. Huth R (2002) Statistical downscaling of daily temperature in Central Europe. J Clim 15(13):1731–1742.<1731:sdodti>2.0.CO;2 CrossRefGoogle Scholar
  42. IPCC (2007) Climate change 2007: the physical science basis. In: Solomon S, Qin D, Manning M, Chen Z, Marquis M, Averyt KB, Tignor M, Miller HL (eds) Contribution of working Group I to the fourth assessment report of the intergovernmental panel on climate change. Cambridge University Press, Cambridge/New York, 996 ppGoogle Scholar
  43. IPCC (2008) Climate change and water. IPCC technical paper VI. Available at:
  44. Irrigation Department (2008) Canal Atlas of Rohtak district. Irrigation Department, Office of the Executive Engineer, Rohtak (Haryana), IndiaGoogle Scholar
  45. IWASRI (International Waterlogging and Salinity Research Institute) (1998) Integrated water resources management program for Pakistan. Economic, social and environmental matters. Internal Report 98/5, Lahore, PakistanGoogle Scholar
  46. Jalota SK, Arora VK (2002) Model-based assessment of water balance components under different cropping systems in North – West India. Agric Water Manag 57:75–87CrossRefGoogle Scholar
  47. Jurriens R, Mollinga PP (1996) Scarcity by design: protective irrigation in India and Pakistan. ICID J 45(2):31–53Google Scholar
  48. Kazmi SI, Ertsen MW, Asi MR (2012) The impact of conjunctive use of canal and tube well water in Lagar irrigated area, Pakistan. Phys Chem Earth Parts A/B/C 47-48:86–98. CrossRefGoogle Scholar
  49. Lerner DN, Issar AS, Simmers I (1990) Groundwater recharge. A guide to understanding and estimating natural recharge. Int Contrib Hydrogeol Verlang Heinz Heise 8:345Google Scholar
  50. Liu S, Bai J, Jia Z, Jia L, Zhou H, Lu L (2010) Estimation of evapotranspiration in the land of China. Hydrol Earth Syst Sci 14(3):573–584CrossRefGoogle Scholar
  51. Llamas MR, Martinez-Santos P (2005) Intensive groundwater use: silent revolution and potential source of social conflicts. ASCE J Water Resour Plann Manag 131:337–341CrossRefGoogle Scholar
  52. Madramootoo CA (2012) Sustainable groundwater use in agriculture. Irrig Drain 61:26–33. CrossRefGoogle Scholar
  53. Mahmood R, Babel MS (2013) Evaluation of SDSM developed by annual and monthly sub-models for downscaling temperature and precipitation in the Jhelum basin, Pakistan and India. Theor Appl Climatol 113:27–44. CrossRefGoogle Scholar
  54. Malmberg GT (1975) Reclamation by tubewell drainage in Rechna doab and adjacent areas, Punjab region, Pakistan. Geological Survey water supply paper 1608-O. United States Government Printing Office, Washington, DC, 1975Google Scholar
  55. Maréchal JC, Dewandel B, Ahmed S, Galeazzi L, Zaidi FK (2006) Combined estimation of specific yield and natural recharge in a semi-arid groundwater basin with irrigated agriculture. J Hydrol 329(1-2):281–293CrossRefGoogle Scholar
  56. Mukherji A, Shah T (2005) Socio-ecology of groundwater irrigation in South Asia: an overview of issues and evidence. In: Selected papers of the symposium on intensive use of groundwater, held in Valencia (Spain), 10–14 December 2002, IAH Hydrogeology Selected Papers. Balkema PublishersGoogle Scholar
  57. Patwardhan A, Nieber J, Johns E (1990) Effective rainfall estimation methods. J Irrig Drain Eng 116(2):182–193CrossRefGoogle Scholar
  58. Postel SL (2003) Securing water for people, crops and ecosystems: new mindset and new priorities. Nat Res Forum 27:89–98CrossRefGoogle Scholar
  59. Punjab Development Statistics (2015) Bureau of statistics. Government of Punjab, Lahore.
  60. Punjab Private Sector Groundwater Development Consultants (1998) Canal seepage analysis for calculation of recharge to groundwater, Technical Report No. 14, PPSGDP, PMU, P&DD, Government of PakistanGoogle Scholar
  61. Qureshi AS, Shah T, Mujeeb A (2003) The groundwater economy of Pakistan. IWMI working paper No. 19Google Scholar
  62. Qureshi AS, McCornick PG, Sarwar A, Sharma BR (2010) Challenges and Prospects of Sustainable Groundwater Management in the Indus Basin, Pakistan. Water Resour Manag 24(8):1551–1569CrossRefGoogle Scholar
  63. Salzmann N, Frei C, Vidale PL, Hoelzle M (2007) The application of Regional Climate Model output for the simulation of high-mountain permafrost scenarios. Global Planet Chang 56(1–2):188–202. CrossRefGoogle Scholar
  64. Sarwar A (2000) A transient model approach to improve on-farm irrigation and drainage in semi-arid zones. PhD dissertation, Wageningen University, The NetherlandsGoogle Scholar
  65. Sarwar A, Eggers H (2006) Development of a conjunctive use model to evaluate alternative management options for surface and groundwater resources. Hydrogeol J 14(8):1676–1687. CrossRefGoogle Scholar
  66. Scanlon BR, Healy RW, Cook PG (2002) Choosing appropriate techniques for quantifying groundwater recharge. Hydrogeol J 10:18–39CrossRefGoogle Scholar
  67. Schicht RJ, Walton WC (1961) Hydrologic budgets for three small watersheds in Illinois. Illinois state water survey report invest. 40:40Google Scholar
  68. Shah T (2003) Governing the groundwater economy: comparative analysis of national institutions and policies in South Asia, China and Mexico. Water Perspect 1(1):2–27Google Scholar
  69. Shah T, Burke J, Villholth K (2007) Groundwater: a global assessment of scale and significance. In: Molden D (ed) Water for food, water for life. Earthscan/IWMI, London/Colombo, pp 395–423Google Scholar
  70. Siebert S, Burke J, Faures JM, Frenken K, Hoogeveen J, Döll P, Portmann FT (2010) Groundwater use for irrigation – a global inventory. Hydrol Earth Syst Sci 14:1863–1880. CrossRefGoogle Scholar
  71. Singh A (2011) Estimating long term regional groundwater recharge for the evaluation of potential solution alternatives to waterlogging and salinization. J Hydrol 406(3–4):245–255CrossRefGoogle Scholar
  72. Soomro AB (1975) A review of problem of waterlogging and salinity in Pakistan. Master Thesis No. 915, Asian Institute of Technology, Bangkok, ThailandGoogle Scholar
  73. Sunyer MA, Madsen H, Ang PH (2011) A comparison of different regional climate models and statistical downscaling methods for extreme rainfall estimation under climate change. Atmos Res. CrossRefGoogle Scholar
  74. Taylor AB, Martin NA, Everard E, Kelly TJ (2012) Modelling the Vale of St Albans: parameter estimation and dual storage. In: Shepley MG, Whiteman MI, Hulme PJ, Grout MW (eds) Groundwater resources modelling: a case study from the UK. Geological Society, London, Special Publications (364): 193–204Google Scholar
  75. Thi T, Nguyen H, De Bie CAJM, Amjad A, Smaling EMA, Chu TH (2012) Mapping the irrigated rice cropping patterns of the Mekong delta, Vietnam through hyper-temporal SPOT NDVI image analysis. Int J Remote Sens 33(2):415–434CrossRefGoogle Scholar
  76. Tyagi NK, Sharma DK, Luthra SK (2000a) Determination of evapotranspiration and crop coefficients of rice and sunflower. Agric Water Manag 45:41–54CrossRefGoogle Scholar
  77. Tyagi NK, Sharma DK, Luthra SK (2000b) Evapotranspiration and crop coefficients of wheat and sorghum. J Irrig Drain Eng 126:215–222CrossRefGoogle Scholar
  78. UNCED (2002) Conservation and management of resources for development. United Nations conference on environment and development. Johannesburg Summit, 26th Aug-04th Sep, Agenda 21, Ch: 14-18Google Scholar
  79. UNDESA (United Nations Department of Economic and Social Affairs, Population Division) (2009) World population prospects: the 2008 Revision, Highlights, Working Paper No. ESA/P/WP.210. New York, UNGoogle Scholar
  80. Usman M, Liedl R, Shahid MA (2014) Managing irrigation water by yield and water productivity assessment of a Rice-Wheat system using remote sensing. J Irrig Drain Eng. CrossRefGoogle Scholar
  81. Usman M, Liedl R, Awan UK (2015a) Spatio-temporal estimation of consumptive water use for assessment of irrigation system performance and management of water resources in irrigated Indus Basin, Pakistan. J Hydrol. CrossRefGoogle Scholar
  82. Usman M, Liedl R, Kavousi A (2015b) Estimation of distributed seasonal net recharge by modern satellite data in irrigated agricultural regions of Pakistan. Environ Earth Sci. CrossRefGoogle Scholar
  83. Usman M, Liedl R, Shahid MA, Abbas A (2015c) Land use/land cover classification and its change detection using multi-temporal MODIS NDVI data. J Geogr Sci 25:1479–1506. CrossRefGoogle Scholar
  84. Van der Velde EJ, Kijne JW (1992) Salinity and irrigation operations in Punjab. Pakistan: are there management options? Paper at Workshop on IIMI-India Collaborative Research in Irrigation Management (Lahore, IIMI)Google Scholar
  85. Wardlow BD, Egbert S, Kastens JH (2007) Analysis of time-series MODIS 250 m vegetation index data for crop classification in the U.S. Central Great Plains (2007). Drought Mitigation Center Faculty Publications. Paper 2.
  86. Wetterhall FA, Bárdossy D, Chen SH, Xu CY (2006) Daily precipitation-downscaling techniques in three Chinese regions. Water Resour Res 42:W11423. CrossRefGoogle Scholar
  87. Wilby RL, Dawson CW (2013) The statistical downscaling model: Insights from one decade of application. Int J Climatol 33:1707–1719. CrossRefGoogle Scholar
  88. Wilby RL, Harris I (2006) A framework for assessing uncertainties in climate change impacts: low-flow scenarios. Water Resour Res 42:W02419. CrossRefGoogle Scholar
  89. Wilby RL, Hay LE, Gutowski WJ, Arritt RW, Takle ES, Pan Z, Leavesley GH, Martyn PC (2000) Hydrological responses to dynamically and statistically downscaled climate model output. Geophys Res Lett 27(8):1199. CrossRefGoogle Scholar
  90. Wilson K, Goldstein A, Falge E, Aubinet M, Baldocchi D, Berbigier P (2002) Energy balance closure at FLUXNET sites. Agric For Meteorol 113:223–243CrossRefGoogle Scholar
  91. Xu CY (1999) Climate change and hydrologic models: a review of existing gaps and recent research developments. Water Resour Manag 13(5):369–382. CrossRefGoogle Scholar
  92. Yang W, Bárdossy A, Caspary HJ (2010) Downscaling daily precipitation time series using a combined circulation- and regression- based approach. Theor Appl Climatol 102(3–4):439–454. CrossRefGoogle Scholar
  93. Yin L, Guangcheng H, Jinting H, Dongguang W, Jiaqiu D, Wang X, Li H (2011) Groundwater recharge estimation in the Ordos Plateau, China: Comparison of methods. Hydrogeol J 19(8):1563–1575CrossRefGoogle Scholar
  94. Yuan F, Sawaya KE, Loeffelholz BC, Bauer ME (2005) Land cover classification and change analysis of the Twin Cities (Minnesota) metropolitan area by multi-temporal Landsat remote sensing. Remote Sens Environ 98:317–328CrossRefGoogle Scholar

Copyright information

© Springer Nature Switzerland AG 2018

Authors and Affiliations

  • Muhammad Usman
    • 1
    • 2
    Email author
  • Rudolf Liedl
    • 2
  • Fan Zhang
    • 3
  • Muhammad Zaman
    • 1
  1. 1.Department of Irrigation & DrainageUniversity of AgricultureFaisalabadPakistan
  2. 2.Institute for Groundwater ManagementTechnical University DresdenDresdenGermany
  3. 3.Institute for Tibetan Research PlateauChinese Academy of SciencesBeijingChina

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