[go: up one dir, main page]
Skip to main content

Advertisement

SpringerLink
Log in

Global effect of irrigation and its impact on the onset of the Indian summer monsoon

  • Published:
Climate Dynamics Aims and scope Submit manuscript

Abstract

In a context of increased demand for food and of climate change, the water consumptions associated with the agricultural practice of irrigation focuses attention. In order to analyze the global influence of irrigation on the water cycle, the land surface model ORCHIDEE is coupled to the GCM LMDZ to simulate the impact of irrigation on climate. A 30-year simulation which takes into account irrigation is compared with a simulation which does not. Differences are usually not significant on average over all land surfaces but hydrological variables are significantly affected by irrigation over some of the main irrigated river basins. Significant impacts over the Mississippi river basin are shown to be contrasted between eastern and western regions. An increase in summer precipitation is simulated over the arid western region in association with enhanced evapotranspiration whereas a decrease in precipitation occurs over the wet eastern part of the basin. Over the Indian peninsula where irrigation is high during winter and spring, a delay of 6 days is found for the mean monsoon onset date when irrigation is activated, leading to a significant decrease in precipitation during May to July. Moreover, the higher decrease occurs in June when the water requirements by crops are maximum, exacerbating water scarcity in this region. A significant cooling of the land surfaces occurs during the period of high irrigation leading to a decrease of the land-sea heat contrast in June, which delays the monsoon onset.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Subscribe and save

Springer+ Basic
$34.99 /Month
  • Get 10 units per month
  • Download Article/Chapter or eBook
  • 1 Unit = 1 Article or 1 Chapter
  • Cancel anytime
Subscribe now

Buy Now

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6
Fig. 7
Fig. 8
Fig. 9
Fig. 10
Fig. 11
Fig. 12
Fig. 13
Fig. 14
Fig. 15
Fig. 16
Fig. 17

Similar content being viewed by others

Notes

  1. For clarity, the value (1−P) is plotted rather than P for SITES when it progresses in the opposite way than T1. The differences in means are considered significant only when the two tests, SITES and T1, give P ≥ 0.95 or P ≤ 0.05 for a 95% confidence level.

  2. In our simulation, all the months of the year have 30 days.

References

  • Adegoke J, Pielke R Sr, Eastman J, Mahmood R, Hubbard K (2003) Impact of irrigation on midsummer surface fluxes and temperature under dry synoptic conditions: a regional atmospheric model study of the US High Plains. Mon Weather Rev 131(3):556–564

    Article  Google Scholar 

  • Ananthakrishnan R, Soman M (1988) The onset of the southwest monsoon over Kerala: 1901–1980. Int J Climatol 8(3):283–296

    Article  Google Scholar 

  • Barnston A, Schickedanz P (1984) The effect of irrigation on warm season precipitation in the southern Great Plains. J Appl Meteorol 23:865–888

    Article  Google Scholar 

  • Belward A, Estes J, Kline K (1999) The IGBP-DIS global 1-km land-cover data set DISCover: a project overview. Photogramm Eng Remote Sens 65(9):1013–1020

    Google Scholar 

  • Benke A, Cushing C (2005) Rivers of North America: the natural history. Academic/Elsevier Press, Amsterdam, Boston

  • Biemans H, Haddeland I, Kabat P, Ludwig F, Hutjes R, Heinke J, von Bloh W, Gerten D (2011) Impact of reservoirs on river discharge and irrigation water supply during the 20th century. Water Resour Res 47(3):W03,509

    Article  Google Scholar 

  • Bonfils C, Lobell D (2007) Empirical evidence for a recent slowdown in irrigation-induced cooling. Proc Natl Acad Sci 104(34):13,582

    Article  Google Scholar 

  • Boucher O, Myhre G, Myhre A (2004) Direct human influence of irrigation on atmospheric water vapour and climate. Clim Dyn 22(6):597–603

    Article  Google Scholar 

  • De Rosnay P, Polcher J (1998) Modelling root water uptake in a complex land surface scheme coupled to a GCM. Hydrol Earth Syst Sci 2(2-3):239–255

    Article  Google Scholar 

  • De Rosnay P, Polcher J, Laval K, Sabre M (2003) Integrated parameterization of irrigation in the land surface model ORCHIDEE. Validation over Indian Peninsula. Geophys Res Lett 30(19). doi:10.1029/2003GL018024

  • DeAngelis A, Dominguez F, Fan Y, Robock A, Kustu M, Robinson D (2010) Evidence of enhanced precipitation due to irrigation over the great plains of the United States. J Geophys Res Atmos 115:1–14

    Article  Google Scholar 

  • Diffenbaugh N (2009) Influence of modern land cover on the climate of the United States. Clim Dyn 33(7):945–958

    Article  Google Scholar 

  • Döll P, Siebert S (1999) A digital global map of irrigated areas. Kassel world water series 1 p 23 pp. plus appendix

  • Döll P, Siebert S (2000) A digital global map of irrigated areas. ICIDJ 49(2):55–66

    Google Scholar 

  • Döll P, Siebert S (2002) Global modeling of irrigation water requirements. Water Resour Res 38(4):8

    Article  Google Scholar 

  • Douglas E, Niyogi D, Frolking S, Yeluripati J, Pielke R Sr, Niyogi N, Vörösmarty C, Mohanty U (2006) Changes in moisture and energy fluxes due to agricultural land use and irrigation in the Indian Monsoon Belt. Geophys Res Lett 33:14

    Google Scholar 

  • Douglas E, Beltrán-Przekurat A, Niyogi D, Pielke R Sr, Vörösmarty C (2009) The impact of agricultural intensification and irrigation on land-atmosphere interactions and Indian monsoon precipitation—a mesoscale modeling perspective. Global Planet Change 67(1–2):117–128

    Article  Google Scholar 

  • Ducoudré N, Laval K, Perrier A (1993) SECHIBA, a new set of parameterizations of the hydrologic exchanges at the land atmosphere interface within the LMD atmospheric global circulation model. J Clim 6(2):248–273

    Article  Google Scholar 

  • FAO (2010) http://www.fao.org/nr/water/aquastat/dbase/, last access: 29 November, 2010. AQUASTAT

  • Fasullo J, Webster P (2003) A hydrological definition of Indian monsoon onset and withdrawal. J Clim 16(19):3200–3211

    Article  Google Scholar 

  • Fekete B, Vorosmarty C, Grabs W (1999) Global, composite runoff fields based on observed river discharge and simulated water balances. Tech. rep., Global Runoff Data Centre, Koblenz, Germany

  • Goswami B, Wu G, Yasunari T (2006) The annual cycle, intraseasonal oscillations, and roadblock to seasonal predictability of the Asian summer monsoon. J Clim 19(20):5078–5099

    Article  Google Scholar 

  • Haddeland I, Lettenmaier D, Skaugen T (2006) Effects of irrigation on the water and energy balances of the Colorado and Mekong river basins. J Hydrol 324(1–4):210–223

    Article  Google Scholar 

  • Hagemann S, Dumenil L (1998) A parametrization of the lateral waterflow for the global scale. Clim Dyn 14(1):17–31

    Article  Google Scholar 

  • Halley E (1686) 1686: An historical account of the trade winds and monsoons observable in the seas between and near the tropics with an attempt to assign a physical cause of the said winds. Phil Trans Roy Soc Lond 16:153–168

    Article  Google Scholar 

  • Hanasaki N, Kanae S, Oki T, Masuda K, Motoya K, Shirakawa N, Shen Y, Tanaka K (2008) An integrated model for the assessment of global water resources—Part 1: model description and input meteorological forcing. Hydrol Earth Syst Sci 12:1007–1025

    Article  Google Scholar 

  • Hanasaki N, Inuzuka T, Kanae S, Oki T (2010) An estimation of global virtual water flow and sources of water withdrawal for major crops and livestock products using a global hydrological model. J Hydrol 384(3–4):232–244

    Article  Google Scholar 

  • Hourdin F, Musat I, Bony S, Braconnot P, Codron F, Dufresne J, Fairhead L, Filiberti M, Friedlingstein P, Grandpeix J et al (2006) The LMDZ4 general circulation model: climate performance and sensitivity to parametrized physics with emphasis on tropical convection. Clim Dyn 27(7):787–813

    Article  Google Scholar 

  • Huffman G, Adler R, Rudolf B, Schneider U, Keehn P (1995) Global precipitation estimates based on a technique for combining satellite-based estimates, rain-gauge analysis, and NWP model precipitation information. J Clim 8(5, Part 2):1284–1295

    Article  Google Scholar 

  • Jarvis P (1976) The interpretation of the variations in leaf water potential and stomatal conductance found in canopies in the field. Philos Trans Roy Soc Lond Ser B Biol Sci 273(927):593–610

    Article  Google Scholar 

  • Kueppers L, Snyder M, Sloan L (2007) Irrigation cooling effect: regional climate forcing by land-use change. Geophys Res Lett 34(3):L03,703

    Article  Google Scholar 

  • Lee E, Chase T, Rajagopalan B, Barry R, Biggs T, Lawrence P (2009) Effects of irrigation and vegetation activity on early Indian summer monsoon variability. Int J Climatol 29(4):573–581

    Article  Google Scholar 

  • Lee E, Sacks W, Chase T, Foley J (2011) Simulated impacts of irrigation on the atmospheric circulation over Asia. J Geophys Res 116(D8):D08,114

    Article  Google Scholar 

  • Li C, Yanai M (1996) The onset and interannual variability of the Asian summer monsoon in relation to land-sea thermal contrast. J Clim 9(2):358–375

    Article  Google Scholar 

  • Lobell D, Bonfils C (2008) The effect of irrigation on regional temperatures: a spatial and temporal analysis of trends in California, 1934–2002. J Clim 21(10):2063–2071

    Article  Google Scholar 

  • Lobell D, Bala G, Duffy P (2006) Biogeophysical impacts of cropland management changes on climate. Geophys Res Lett 33(6):L06708

    Google Scholar 

  • Lobell D, Bonfils C, Faurès J (2008) The role of irrigation expansion in past and future temperature trends. Earth Interact 12(3):1–11

    Article  Google Scholar 

  • Lobell D, Bala G, Mirin A, Phillips T, Maxwell R, Rotman D (2009) Regional differences in the influence of irrigation on climate. J Clim 22(8):2248–2255

    Article  Google Scholar 

  • Lohammar T, Larsson S, Linder S, Falk S (1980) FAST: simulation models of gaseous exchange in scots pine. Ecol Bull 32:505–523

    Google Scholar 

  • Lohar D, Pal B (1995) The effect of irrigation on premonsoon season precipitation over South West Bengal, India. J Clim 8(10):2567–2570

    Article  Google Scholar 

  • Miller J, Russell G, Caliri G (1994) Continental-scale river flow in climate models. J Clim 7(6):914–928

    Article  Google Scholar 

  • Mirza M (1997) Hydrological changes in the Ganges system in Bangladesh in the post-Farakka period. Hydrol Sci J 42(5):613–631

    Article  Google Scholar 

  • Moore N, Rojstaczer S (2001) Irrigation-induced rainfall and the great plains. J Appl Meteorol 40(8):1297–1309

    Article  Google Scholar 

  • Ngo-Duc T, Polcher J, Laval K (2005) A 53-year forcing data set for land surface models. J Geophys Res Atmos 110(D6). doi:10.1029/2004JD005434

  • Ngo-Duc T, Laval K, Ramillien G, Polcher J, Cazenave A (2007) Validation of the land water storage simulated by organising carbon and hydrology in dynamic ecosystems (ORCHIDEE) with gravity recovery and climate experiment (GRACE) data. Water Resour Res 43(4). doi:10.1029/2006WR004941

  • Oki T, Nishimura T, Dirmeyer P (1999) Assessment of annual runoff from land surface models using total runoff integrating pathways (TRIP). J Meteorol Soc Jpn 77(1B):235–255

    Google Scholar 

  • Olson J, Watts J, Allison L (1983) Carbon in live vegetation of major world ecosystems (ORNL-5862). Environ Sci Division Publication, Oak Ridge

    Google Scholar 

  • Perrier A (1975) Etude physique de l’évaporation dans les conditions naturelles. Ann Sgronomiques 26(1–18):105–123–229–243

    Google Scholar 

  • Pielke R (2001) Influence of the spatial distribution of vegetation and soils on the prediction of cumulus convective rainfall. Rev Geophys 39(2):151–177

    Article  Google Scholar 

  • Polcher J (2003) Les processus de surface à l’échelle globale et leurs interactions avec l’atmosphère. Habilitation à diriger des recherches

  • Preisendorfer R, Barnett T (1983) Numerical model-reality intercomparison tests using small-sample statistics. J Atmos Sci 40(8):1884–1896

    Article  Google Scholar 

  • Puma M, Cook B (2010) Effects of irrigation on global climate during the 20th century. J Geophys Res 115(D16):D16,120

    Article  Google Scholar 

  • Roberts L (1998) World resources 1998–1999. Oxford University Press, Oxford

    Google Scholar 

  • Sacks W, Cook B, Buenning N, Levis S, Helkowski J (2008) Effects of global irrigation on the near-surface climate. Clim Dyn 33:159–175

    Google Scholar 

  • Saeed F, Hagemann S, Jacob D (2009) Impact of irrigation on the South Asian summer monsoon. Geophys Res Lett 36(20):L20,711

    Article  Google Scholar 

  • Seckler D (1998) World water demand and supply, 1990 to 2025: Scenarios and issues. International Water Management Institute

  • Segal M, Pan Z, Turner R, Takle E (1998) On the potential impact of irrigated areas in North America on summer rainfall caused by large-scale systems. J Appl Meteorol 37(3):325–331

    Article  Google Scholar 

  • Shiklomanov I (1997) Assessment of water resources and water availability in the world. Tech. rep., Stockholm Environment Institute, Geneva, Switzerland

  • Shiklomanov I (2000) Appraisal and assessment of world water resources. Water Int 25(1):11–32

    Article  Google Scholar 

  • Siebert S, Döll P (2001) A digital global map of irrigated areas—an update for Latin America and Europe. Kassel world water series 4, Center for Environmental Systems Research, University of Kassel, Germany pp 14 pp. + appendix

  • Siebert S, Doll P, Hoogeveen J, Faures J, Frenken K, Feick S (2005) Development and validation of the global map of irrigation areas. Hydrol Earth Syst Sci 9(5):535–547

    Article  Google Scholar 

  • Sitch S, Smith B, Prentice I, Arneth A, Bondeau A, Cramer W, Kaplan J, Levis S, Lucht W, Sykes M et al (2003) Evaluation of ecosystem dynamics, plant geography and terrestrial carbon cycling in the LPJ dynamic global vegetation model. Glob Change Biol 9(2):161–185

    Article  Google Scholar 

  • Solomon S, Qin D, Manning M, Chen Z, Marquis M, Averyt K, Tignor M, Miller H (2007) IPCC, 2007: climate change 2007: the physical science basis. Contribution of working group I to the fourth assessment report of the intergovernmental panel on climate change. Cambridge University Press, New York

  • Takata K, Saito K, Yasunari T (2009) Changes in the Asian monsoon climate during 1700–1850 induced by preindustrial cultivation. Proc Natl Acad Sci 106(24):9586

    Article  Google Scholar 

  • Viovy N (1996) Interannuality and CO2 sensitivity of the SECHIBA-BGC coupled SVAT-BGC model. Phys Chem Earth 21(5–6):489–497

    Article  Google Scholar 

  • Vörösmarty C, Fekete B, Meybeck M, Lammers R (2000) Global system of rivers: Its role in organizing continental land mass and defining land-to-ocean linkages. Global Biogeochem Cycles 14(2):599–621

    Article  Google Scholar 

  • Wang B, Ding Q, Joseph P (2009) Objective definition of the Indian summer monsoon onset. J Clim 22:3303–3316

    Article  Google Scholar 

  • Webster P (1987) The elementary monsoon. Monsoons Wiley, New York, pp 3–32

    Google Scholar 

  • Wigley T, Santer B (1990) Statistical comparison of spatial fields in model validation, perturbation, and predictability experiments. J Geophys Res Atmos 95(D1):851–865

    Google Scholar 

  • Wisser D, Fekete B, Vörösmarty C, Schumann A (2010) Reconstructing 20th century global hydrography: a contribution to the global terrestrial network- hydrology (GTN-H). Hydrol Earth Syst Sci 14(1):1–24

    Article  Google Scholar 

  • Yamashima R, Takata K, Matsumoto J (2011) Numerical study of the impacts of land use/cover changes between 1700 and 1850 on the seasonal hydroclimate in monsoon Asia (Special issue on MAHASRI: monsoon Asian hydro-atmosphere scientific research and prediction initiative). J Meteorol Soc Jpn 89:291–298

    Article  Google Scholar 

Download references

Acknowledgments

Simulations were performed using computational facilities of the Institut du Développement et des Ressources en Informatique Scientifique (IDRIS, CNRS, France). The authors would like to thank the European Union project WATCH (WATer and global CHange, contract No. 036946) for the financial support. Great thanks to Camille Risi (LMD, CNRS, France) for her useful comments on the English writing.

Author information

Authors and Affiliations

  1. Laboratoire de Météorologie Dynamique, Université de Paris 6, Tour 45-55, 3ème ét., Case Postale 99, 4, Place Jussieu, 75252, Paris Cedex 05, France

    Matthieu Guimberteau

  2. Laboratoire de Météorologie Dynamique, Paris, France

    Katia Laval

  3. AgroParisTech, UFR Physique de l’Environnement, Paris, France

    Alain Perrier

  4. Laboratoire de Météorologie Dynamique, CNRS, Paris, France

    Jan Polcher

Authors
  1. Matthieu Guimberteau
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Katia Laval
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Alain Perrier
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Jan Polcher
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Matthieu Guimberteau.

Appendix

Appendix

1.1 Leaves transpiration and potential transpiration in ORCHIDEE

Crops water loss mainly occurs through their leaves transpiration, T v   (kg/m2/s) (Eq. 3), driven by the potential evaporation, E pot  (kg/m2/s), between the evaporating surface and the overlying air, and limited by resistances.

$$ T_{v}=f_{v}.\left(\frac{1}{1+\frac{r_{sto_{v}}^{}+r_{s_{v}}}{r_{a}}}\right).U_{s_{v}}.E_{pot} $$
(3)

where f v is the fraction of PFT in the grid box, \(r_{sto_{v}}\) (s/m) the stomatal resistance (Eq. 4), \(r_{s_{v}}\) (s/m) the structural resistance, r a (s/m) the aerodynamic resistance, \(U_{s_{v}}\) the water extraction potential of roots and E pot (kg/m2/s) the potential evaporation.

Three resistances are included in equation of T v :

  • The aerodynamic resistance, r a (s/m), inversely proportional to the product of the drag coefficient and the wind speed, opposes the transfer of water vapour from the evaporating surface into the air above the canopy.

  • The structural (or architectural) resistance, \(r_{s_{v}}\) (s/m), accounts for aerodynamic resistance between the leaves and the top of the canopy (Perrier 1975).

  • The canopy resistance (including both bulk stomatal and leaf aerodynamic resistances), \(r_{sto_{v}}\) (s/m) (Eq. 4), is derived by Lohammar et al. (1980) from Jarvis (1976). It depends on the net solar radiation (R SW net  (W/m2)) and the water vapor deficit of the air (δ c  (kg/m3)) which are limiting factors for transpiration, and it is inversely proportional to the LAI.

$$ r_{sto_{v}}=\frac{a}{k_{0_{v}}}.\left[\frac{1}{LAI_{v}}.\frac{R_{net}^{SW}+R_{0}}{R_{net}^{SW}}.\left(1+\lambda.\frac{\delta_{c}}{a}\right)\right] $$
(4)

where a (equal to 23.0 s/m) is a mean minimal theoretical stomatal resistance of the leaf, \(k_{0_{v}}\) (varying from 12.10−2 to 30.10−2) a number which characterizes the PFT regarding a and \(\frac{a}{k_{0_{v}}}\) (s/m) a mean minimal theoretical stomatal resistance for a given vegetation. λ (equal to 1,5.10−3 m 2.s.kg−1) is an enhancement factor of stomatal closure under the effect of water deficit δ c  (kg/m3). R SW net  (W/m2) is the net shortwave radiation and R 0 the constant solar radiation (equal to 125 W/m2).

Maximal water loss by crops, computed to estimate irrigation requirement, is derived from the effective transpiration parametrization under stress-free conditions, called potential transpiration, T pot v  (kg/m2/s). In these conditions, soil water is not limiting (\(U_{s_{v}}=1\) in Eq. 3), the stomatal opening is no longer dependant on net solar radiation and water deficit of the air is zero (respectively \(\frac{R_{net}^{SW}+R_{0}}{R_{net}^{SW}}=1\) and δ c  = 0 in Eq. 4). The stomatal resistance of the foliage is thus minimal (respectively \(r_{sto_{v}=}r_{sto_{v}}^{min}\)).

Rights and permissions

Reprints and permissions

About this article

Cite this article

Guimberteau, M., Laval, K., Perrier, A. et al. Global effect of irrigation and its impact on the onset of the Indian summer monsoon. Clim Dyn 39, 1329–1348 (2012). https://doi.org/10.1007/s00382-011-1252-5

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s00382-011-1252-5

Keywords

Search

Navigation