Soil Moisture Droughts under the Retrospective and Projected Climate in India

Vimal Mishra Civil Engineering, Indian Institute of Technology Gandhinagar, and Information Technology Research Academy Water Project: Measurement to Management (M2M), Gujarat, India

Search for other papers by Vimal Mishra in
Current site
Google Scholar
PubMed
Close
,
Reepal Shah Civil Engineering, Indian Institute of Technology Gandhinagar, and Information Technology Research Academy Water Project: Measurement to Management (M2M), Gujarat, India

Search for other papers by Reepal Shah in
Current site
Google Scholar
PubMed
Close
, and
Bridget Thrasher Climate Analytics Group, Palo Alto, California

Search for other papers by Bridget Thrasher in
Current site
Google Scholar
PubMed
Close
Restricted access

Abstract

Changes in precipitation, air temperature, and model-simulated soil moisture were examined for the observed (1950–2008) and projected (2010–99) climate for the sowing period of Kharif and Rabi [KHARIF_SOW (May–July) and RABI_SOW (October–December)] and the entire Kharif and Rabi [KHARIF (May–October) and RABI (October–April)] crop-growing periods in India. During the KHARIF_SOW and KHARIF periods, precipitation declined significantly in the Gangetic Plain, which in turn resulted in declines in soil moisture. Statistically significant warming trends were noticed as all-India-averaged air temperature increased by 0.40°, 0.90°, and 0.70°C in the KHARIF, RABI_SOW, and RABI periods, respectively, during 1950–2008. Frequency and areal extent of soil moisture–based droughts increased substantially during the latter half (1980–2008) of the observed period. Under the projected climate (2010–99), precipitation, air temperature, and soil moisture are projected to increase in all four crop-growing seasons. In the projected climate, all-India ensemble mean precipitation, air temperature, and soil moisture are projected to increase up to 39% (RABI_SOW period), 2.3°C, and 5.3%, respectively, in the crop-growing periods. While projected changes in air temperature are robust across India, robust increases in precipitation and soil moisture are projected to occur in the end-term (2070–99) climate. Frequency and areal extents of soil moisture–based severe, extreme, and exceptional droughts are projected to increase in the near- (2010–39) and midterm (2040–69) climate in the majority of crop-growing seasons in India. However, frequency and areal extent of droughts during the crop-growing period are projected to decline in the end-term climate in the entire crop-growing period because of projected increases in the monsoon season precipitation.

Supplemental information related to this paper is available at the Journals Online website: http://dx.doi.org/10.1175/JHM-D-13-0177.s1.

Corresponding author address: Vimal Mishra, Civil Engineering, IIT Gandhinagar, Shed-3, Room 216, VGEC Campus, Chandkheda, Ahmedabad, Gujarat 382424, India. E-mail: vmishra@iitgn.ac.in

Abstract

Changes in precipitation, air temperature, and model-simulated soil moisture were examined for the observed (1950–2008) and projected (2010–99) climate for the sowing period of Kharif and Rabi [KHARIF_SOW (May–July) and RABI_SOW (October–December)] and the entire Kharif and Rabi [KHARIF (May–October) and RABI (October–April)] crop-growing periods in India. During the KHARIF_SOW and KHARIF periods, precipitation declined significantly in the Gangetic Plain, which in turn resulted in declines in soil moisture. Statistically significant warming trends were noticed as all-India-averaged air temperature increased by 0.40°, 0.90°, and 0.70°C in the KHARIF, RABI_SOW, and RABI periods, respectively, during 1950–2008. Frequency and areal extent of soil moisture–based droughts increased substantially during the latter half (1980–2008) of the observed period. Under the projected climate (2010–99), precipitation, air temperature, and soil moisture are projected to increase in all four crop-growing seasons. In the projected climate, all-India ensemble mean precipitation, air temperature, and soil moisture are projected to increase up to 39% (RABI_SOW period), 2.3°C, and 5.3%, respectively, in the crop-growing periods. While projected changes in air temperature are robust across India, robust increases in precipitation and soil moisture are projected to occur in the end-term (2070–99) climate. Frequency and areal extents of soil moisture–based severe, extreme, and exceptional droughts are projected to increase in the near- (2010–39) and midterm (2040–69) climate in the majority of crop-growing seasons in India. However, frequency and areal extent of droughts during the crop-growing period are projected to decline in the end-term climate in the entire crop-growing period because of projected increases in the monsoon season precipitation.

Supplemental information related to this paper is available at the Journals Online website: http://dx.doi.org/10.1175/JHM-D-13-0177.s1.

Corresponding author address: Vimal Mishra, Civil Engineering, IIT Gandhinagar, Shed-3, Room 216, VGEC Campus, Chandkheda, Ahmedabad, Gujarat 382424, India. E-mail: vmishra@iitgn.ac.in

Supplementary Materials

    • Supplemental Materials (DOCX 579.65 KB)
Save
  • Andreadis, K. M., and Lettenmaier D. P. , 2006: Trends in 20th century drought over the continental United States. Geophys. Res. Lett., 33, L10403, doi:10.1029/2006GL025711.

    • Search Google Scholar
    • Export Citation
  • Andreadis, K. M., Clark E. A. , Wood A. W. , Hamlet A. F. , and Lettenmaier D. P. , 2005: Twentieth-century drought in the conterminous United States. J. Hydrometeor., 6, 9851001, doi:10.1175/JHM450.1.

    • Search Google Scholar
    • Export Citation
  • Battisti, D. S., and Naylor R. L. , 2009: Historical warnings of future food insecurity with unprecedented seasonal heat. Science, 323, 240244, doi:10.1126/science.1164363.

    • Search Google Scholar
    • Export Citation
  • Bollasina, M. A., Ming Y. , and Ramaswamy V. , 2011: Anthropogenic aerosols and the weakening of the South Asian summer monsoon. Science, 334, 502505, doi:10.1126/science.1204994.

    • Search Google Scholar
    • Export Citation
  • Bürger, G., Murdock T. Q. , Werner A. T. , Sobie S. R. , and Cannon A. J. , 2012: Downscaling extremes—An intercomparison of multiple statistical methods for present climate. J. Climate, 25, 43664388, doi:10.1175/JCLI-D-11-00408.1.

    • Search Google Scholar
    • Export Citation
  • Burke, E. J., and Brown S. J. , 2008: Evaluating uncertainties in the projection of future drought. J. Hydrometeor., 9, 292299, doi:10.1175/2007JHM929.1.

    • Search Google Scholar
    • Export Citation
  • Burke, E. J., Brown S. J. , and Christidis N. , 2006: Modeling the recent evolution of global drought and projections for the twenty-first century with the Hadley Centre climate model. J. Hydrometeor., 7, 11131125, doi:10.1175/JHM544.1.

    • Search Google Scholar
    • Export Citation
  • Cayan, D. R., Maurer E. P. , Dettinger M. D. , Tyree M. , and Hayhoe K. , 2008: Climate change scenarios for the California region. Climatic Change, 87, 2142, doi:10.1007/s10584-007-9377-6.

    • Search Google Scholar
    • Export Citation
  • Cherkauer, K. A., and Lettenmaier D. P. , 1999: Hydrologic effects of frozen soils in the upper Mississippi River basin. J. Geophys. Res., 104, 19 59919 610, doi:10.1029/1999JD900337.

    • Search Google Scholar
    • Export Citation
  • Cherkauer, K. A., Bowling L. C. , and Lettenmaier D. P. , 2003: Variable infiltration capacity cold land process model updates. Global Planet. Change, 38, 151159, doi:10.1016/S0921-8181(03)00025-0.

    • Search Google Scholar
    • Export Citation
  • Dai, A., 2011a: Characteristics and trends in various forms of the Palmer drought severity index during 1900–2008. J. Geophys. Res.,116, D12115, doi:10.1029/2010JD015541.

  • Dai, A., 2011b: Drought under global warming: A review. Wiley Interdiscip. Rev.: Climate Change, 2, 4565, doi:10.1002/wcc.81.

  • Dai, A., 2012: Increasing drought under global warming in observations and models. Nat. Climate Change, 3, 5258, doi:10.1038/nclimate1633.

    • Search Google Scholar
    • Export Citation
  • Demaria, E. M. C., Maurer E. P. , Sheffield J. , Bustos E. , Poblete D. , Vicuña S. , and Meza F. , 2013: Using a gridded global dataset to characterize regional hydroclimate in central Chile. J. Hydrometeor., 14, 251265, doi:10.1175/JHM-D-12-047.1.

    • Search Google Scholar
    • Export Citation
  • Dorigo, W. A., and Coauthors, 2011: The International Soil Moisture Network: A data hosting facility for global in situ soil moisture measurements. Hydrol. Earth Syst. Sci., 15, 1675–1698, doi:10.5194/hess-15-1675-2011.

    • Search Google Scholar
    • Export Citation
  • Dorigo, W. A., Jeu R. , Chung D. , Parinussa R. , Liu Y. , Wagner W. , and Fernández-Prieto D. , 2012: Evaluating global trends (1988–2010) in harmonized multi-satellite surface soil moisture. Geophys. Res. Lett., 39, L18405, doi:10.1029/2012GL052988.

    • Search Google Scholar
    • Export Citation
  • Han, E., Merwade V. , and Heathman G. C. , 2012: Implementation of surface soil moisture data assimilation with watershed scale distributed hydrological model. J. Hydrol., 416–417, 98117, doi:10.1016/j.jhydrol.2011.11.039.

    • Search Google Scholar
    • Export Citation
  • Hansen, J., Sato M. , Ruedy R. , Lo K. , Lea D. W. , and Medina-Elizade M. , 2006: Global temperature change. Proc. Natl. Acad. Sci. USA, 103, 14 28814 293, doi:10.1073/pnas.0606291103.

    • Search Google Scholar
    • Export Citation
  • Hansen, M. C., DeFries R. S. , Townshend J. R. , and Sohlberg R. , 2000: Global land cover classification at 1 km spatial resolution using a classification tree approach. Int. J. Remote Sens., 21, 13311364, doi:10.1080/014311600210209.

    • Search Google Scholar
    • Export Citation
  • Hayhoe, K., and Coauthors, 2004. Emissions pathways, climate change, and impacts on California. Proc. Natl. Acad. Sci. USA,101,12 42212 427, doi:10.1073/pnas.0404500101.

  • Hollmann, R., and Coauthors, 2013: The ESA climate change initiative satellite data records for essential climate variables. Bull. Amer. Meteor. Soc., 94, 15411552, doi:10.1175/BAMS-D-11-00254.1.

    • Search Google Scholar
    • Export Citation
  • Huntington, T. G., 2006: Evidence for intensification of the global water cycle: Review and synthesis. J. Hydrol., 319, 8395, doi:10.1016/j.jhydrol.2005.07.003.

    • Search Google Scholar
    • Export Citation
  • Jury, M. R., and Funk C. , 2012: Climatic trends over Ethiopia: Regional signals and drivers. Int. J. Climatol., 33, 1924–1935, doi: 10.1002/joc.3560.

    • Search Google Scholar
    • Export Citation
  • Kalnay, E., and Coauthors, 1996: The NCEP/NCAR 40-Year Reanalysis Project. Bull. Amer. Meteor. Soc., 77, 437471, doi:10.1175/1520-0477(1996)077<0437:TNYRP>2.0.CO;2.

    • Search Google Scholar
    • Export Citation
  • Knutti, R., and Sedláček J. , 2013: Robustness and uncertainties in the new CMIP5 climate model projections. Nat. Climate Change, 3, 369373, doi:10.1038/nclimate1716.

    • Search Google Scholar
    • Export Citation
  • Koster, R. D., and Coauthors, 2004: Regions of strong coupling between soil moisture and precipitation. Science, 305, 11381140, doi:10.1126/science.1100217.

    • Search Google Scholar
    • Export Citation
  • Krishna Kumar, K., Kumar R. K. , Ashrit R. G. , Deshpande N. R. , and Hansen J. W. , 2004: Climate impacts on Indian agriculture. Int. J. Climatol., 24, 13751393, doi:10.1002/joc.1081.

    • Search Google Scholar
    • Export Citation
  • Levine, R. C., Turner A. G. , Marathayil D. , and Martin G. M. , 2013: The role of northern Arabian Sea surface temperature biases in CMIP5 model simulations and future projections of Indian summer monsoon rainfall. Climate Dyn., 41, 155172, doi:10.1007/s00382-012-1656-x.

    • Search Google Scholar
    • Export Citation
  • Liang, X., Lettenmaier D. P. , Wood E. F. , and Burges S. J. , 1994: A simple hydrologically based model of land surface water and energy fluxes for general circulation models. J. Geophys. Res.,99, 14 415–14 428, doi:10.1029/94JD00483.

  • Liang, X., Wood E. F. , and Lettenmaier D. P. , 1996: Surface soil moisture parameterization of the VIC-2L model: Evaluation and modification. Global Planet. Change, 13, 195206, doi:10.1016/0921-8181(95)00046-1.

    • Search Google Scholar
    • Export Citation
  • Lobell, D. B., and Field C. B. , 2007: Global scale climate–crop yield relationships and the impacts of recent warming. Environ. Res. Lett., 2, 014002, doi:10.1088/1748-9326/2/1/014002.

    • Search Google Scholar
    • Export Citation
  • Lobell, D. B., and Burke M. B. , 2008: Why are agricultural impacts of climate change so uncertain? The importance of temperature relative to precipitation. Environ. Res. Lett., 3, 034007, doi:10.1088/1748-9326/3/3/034007.

    • Search Google Scholar
    • Export Citation
  • Lobell, D. B., Ortiz-Monasterio J. I. , Sibley A. M. , and Sohu V. S. , 2013: Satellite detection of earlier wheat sowing in India and implications for yield trends. Agric. Syst., 115, 137143, doi:10.1016/j.agsy.2012.09.003.

    • Search Google Scholar
    • Export Citation
  • Mann, H. B., 1945: Nonparametric tests against trend. Econometrica, 13, 245259, doi:10.2307/1907187.

  • Maurer, E. P., and Hidalgo H. G. , 2008: Utility of daily vs. monthly large-scale climate data: An intercomparison of two statistical downscaling methods. Hydrol. Earth Syst. Sci., 12, 551563, doi:10.5194/hess-12-551-2008.

    • Search Google Scholar
    • Export Citation
  • Maurer, E. P., Wood A. W. , Adam J. C. , Lettenmaier D. P. , and Nijssen B. , 2002: A long-term hydrologically based dataset of land surface fluxes and states for the conterminous United States. J. Climate, 15, 32373251, doi:10.1175/1520-0442(2002)015<3237:ALTHBD>2.0.CO;2.

    • Search Google Scholar
    • Export Citation
  • Maurer, E. P., Hidalgo H. G. , Das T. , Dettinger M. D. , and Cayan D. R. , 2010: The utility of daily large-scale climate data in the assessment of climate change impacts on daily streamflow in California. Hydrol. Earth Syst. Sci., 14, 11251138, doi:10.5194/hess-14-1125-2010.

    • Search Google Scholar
    • Export Citation
  • Menon, A., Levermann A. , Schewe J. , Lehmann J. , and Frieler K. , 2013: Consistent increase in Indian monsoon rainfall and its variability across CMIP-5 models. Earth Syst. Dyn.,4, 287–300, doi:10.5194/esd-4-287-2013.

  • Mishra, V., and Cherkauer K. A. , 2010: Retrospective droughts in the crop growing season: Implications to corn and soybean yield in the Midwestern United States. Agric. For. Meteor., 150, 10301045, doi:10.1016/j.agrformet.2010.04.002.

    • Search Google Scholar
    • Export Citation
  • Mishra, V., and Lettenmaier D. P. , 2011: Climatic trends in major U.S. urban areas, 1950–2009. Geophys. Res. Lett., 38, L16401, doi:10.1029/2011GL048255.

    • Search Google Scholar
    • Export Citation
  • Mishra, V., Cherkauer K. A. , and Shukla S. , 2010: Assessment of drought due to historic climate variability and projected future climate change in the Midwestern United States. J. Hydrometeor., 11, 4668, doi:10.1175/2009JHM1156.1.

    • Search Google Scholar
    • Export Citation
  • Mishra, V., Somalik B. V. , Lettenmaier D. P. , and Wallace J. M. , 2012: A prominent pattern of year-to-year variability in Indian summer monsoon rainfall. Proc. Natl. Acad. Sci. USA, 109, 7213–7217, doi:10.1073/pnas.1119150109.

    • Search Google Scholar
    • Export Citation
  • Naidu, C. V., Durgalakshmi K. , Muni Krishna K. , Ramalingeswara Rao S. , Satyanarayana G. C. , Lakshminarayana P. , and Malleswara Rao L. , 2009: Is summer monsoon rainfall decreasing over India in the global warming era? J. Geophys. Res.,114, D24108, doi:10.1029/2008JD011288.

  • Nijssen, B., O’Donnell G. M. , Hamlet A. F. , and Lettenmaier D. P. , 2001: Hydrologic sensitivity of global rivers to climate change. Climatic Change, 50, 143175, doi:10.1023/A:1010616428763.

    • Search Google Scholar
    • Export Citation
  • Pai, D. S., Sridhar L. , Badwaik M. R. , and Rajeevan M. 2014: Analysis of the daily rainfall events over India using a new long period (1901–2010) high resolution (0.25° × 0.25°) gridded rainfall data set. Climate Dyn., doi:10.1007/s00382-014-2307-1, in press.

    • Search Google Scholar
    • Export Citation
  • Raje, D., and Krishnan R. , 2012: Bayesian parameter uncertainty modeling in a macroscale hydrologic model and its impact on Indian river basin hydrology under climate change. Water Resour. Res., 48, W08522, doi:10.1029/2011WR011123.

    • Search Google Scholar
    • Export Citation
  • Raje, D., Priya P. , and Krishnan R. , 2014: Macroscale hydrological modelling approach for study of large scale hydrologic impacts under climate change in Indian river basins. Hydrol. Processes, 28, 18741889, doi:10.1002/hyp.9731.

    • Search Google Scholar
    • Export Citation
  • Robock, A., Vinnikov K. Y. , Srinivasan G. , Entin J. K. , Hollinger S. E. , Speranskaya N. A. , Liu S. , and Namkhai A. , 2000: The global soil moisture data bank. Bull. Amer. Meteor. Soc., 81, 12811300, doi:10.1175/1520-0477(2000)081<1281:TGSMDB>2.3.CO;2.

    • Search Google Scholar
    • Export Citation
  • Rodell, M., and Coauthors, 2004: The Global Land Data Assimilation System. Bull. Amer. Meteor. Soc., 85, 381394, doi:10.1175/BAMS-85-3-381.

    • Search Google Scholar
    • Export Citation
  • Rodell, M., Velicogna I. , and Famiglietti J. S. , 2009: Satellite-based estimates of groundwater depletion in India. Nature, 460, 9991002, doi:10.1038/nature08238.

    • Search Google Scholar
    • Export Citation
  • Sen, P. K., 1968: Estimates of the regression coefficient based on Kendall’s tau. J. Amer. Stat. Assoc., 63, 13791389, doi:10.1080/01621459.1968.10480934.

    • Search Google Scholar
    • Export Citation
  • Seneviratne, S. I., Lüthi D. , Litschi M. , and Schär C. , 2006: Land–atmosphere coupling and climate change in Europe. Nature, 443, 205209, doi:10.1038/nature05095.

    • Search Google Scholar
    • Export Citation
  • Seneviratne, S. I., and Coauthors, 2012: Changes in climate extremes and their impacts on the natural physical environment. Managing the Risks of Extreme Events and Disasters to Advance Climate Change Adaptation, C. B. Field et al., Eds., Cambridge University Press, 109–230.

  • Sheffield, J., and Wood E. F. , 2007: Characteristics of global and regional drought, 1950–2000: Analysis of soil moisture data from off-line simulation of the terrestrial hydrologic cycle. J. Geophys. Res.,112, D17115, doi:10.1029/2006JD008288.

  • Sheffield, J., and Wood E. F. , 2008a: Global trends and variability in soil moisture and drought characteristics, 1950–2000, from observation-driven simulations of the terrestrial hydrological cycle. J. Climate, 21, 432458, doi:10.1175/2007JCLI1822.1.

    • Search Google Scholar
    • Export Citation
  • Sheffield, J., and Wood E. F. , 2008b: Projected changes in drought occurrence under future global warming from multi-model, multi-scenario, IPCC AR4 simulations. Climate Dyn., 31, 79105, doi:10.1007/s00382-007-0340-z.

    • Search Google Scholar
    • Export Citation
  • Sheffield, J., Goteti G. , Wen F. , and Wood E. F. , 2004: A simulated soil moisture based drought analysis for the United States. J. Geophys. Res.,109, D24108, doi:10.1029/2004JD005182.

  • Sheffield, J., Goteti G. , and Wood E. F. , 2006: Development of a 50-year high-resolution global dataset of meteorological forcings for land surface modeling. J. Climate, 19, 30883111, doi:10.1175/JCLI3790.1.

    • Search Google Scholar
    • Export Citation
  • Sheffield, J., Wood E. F. , and Roderick M. L. , 2012: Little change in global drought over the past 60 years. Nature, 491, 435438, doi:10.1038/nature11575.

    • Search Google Scholar
    • Export Citation
  • Sivakumar, M. V. K., Das H. P. , and Brunini O. , 2005: Impacts of present and future climate variability and change on agriculture and forestry in the arid and semi-arid tropics. Climatic Change, 70, 3172, doi:10.1007/s10584-005-5937-9.

    • Search Google Scholar
    • Export Citation
  • Svoboda, M., and Coauthors, 2002: The Drought Monitor. Bull. Amer. Meteor. Soc.,83, 1181–1190.

  • Taylor, K. E., Stouffer R. J. , and Meehl G. A. , 2009: A summary of the CMIP5 experiment design. WCRP CMIP5 Doc., 33 pp. [Available online at http://cmip-pcmdi.llnl.gov/cmip5/docs/Taylor_CMIP5_design.pdf.]

  • Taylor, K. E., Stouffer R. J. , and Meehl G. A. , 2012: An overview of CMIP5 and the experiment design. Bull. Amer. Meteor. Soc., 93, 485–498, doi:10.1175/BAMS-D-11-00094.1.

    • Search Google Scholar
    • Export Citation
  • Tebaldi, C., Arblaster J. M. , and Knutti R. , 2011: Mapping model agreement on future climate projections. Geophys. Res. Lett., 38, L23701, doi:10.1029/2011GL049863.

    • Search Google Scholar
    • Export Citation
  • Thrasher, B., Maurer E. P. , McKellar C. , and Duffy P. B. , 2012: Technical note: Bias correcting climate model simulated daily temperature extremes with quantile mapping. Hydrol. Earth Syst. Sci., 16, 33093314, doi:10.5194/hess-16-3309-2012.

    • Search Google Scholar
    • Export Citation
  • Trenberth, K. E., Dai A. , van der Schrier G. , Jones P. D. , Barichivich J. , Briffa K. R. , and Sheffield J. , 2014: Global warming and changes in drought. Nat. Climate Change, 4, 1722, doi:10.1038/NCLIMATE2067.

    • Search Google Scholar
    • Export Citation
  • Turner, A. G., and Annamalai H. , 2012: Climate change and the South Asian summer monsoon. Nat. Climate Change, 2, 587595, doi:10.1038/nclimate1495.

    • Search Google Scholar
    • Export Citation
  • Wang, A., Lettenmaier D. P. , and Sheffield J. , 2011: Soil moisture drought in China, 1950–2006. J. Climate, 24, 32573271, doi:10.1175/2011JCLI3733.1.

    • Search Google Scholar
    • Export Citation
  • Wilhite, D. A., Hayes M. J. , Knutson C. , and Smith K. H. , 2000: Planning for drought: Moving from crisis to risk management. J. Amer. Water Resour. Assoc., 36, 697710, doi:10.1111/j.1752-1688.2000.tb04299.x.

    • Search Google Scholar
    • Export Citation
  • Wood, A. W., Maurer E. P. , Kumar A. , and Lettenmaier D. , 2002: Long-range experimental hydrologic forecasting for the eastern United States. J. Geophys. Res.,107, 4429, doi:10.1029/2001JD000659.

  • Wood, A. W., Leung L. R. , Sridhar V. , and Lettenmaier D. P. , 2004: Hydrologic implications of dynamical and statistical approaches to downscaling climate model outputs. Climatic Change, 62, 189216, doi:10.1023/B:CLIM.0000013685.99609.9e.

    • Search Google Scholar
    • Export Citation
  • Yue, S., and Wang C. Y. , 2002: Applicability of prewhitening to eliminate the influence of serial correlation on the Mann–Kendall test. Water Resour. Res., 38, 1068, doi:10.1029/2001WR000861.

    • Search Google Scholar
    • Export Citation
All Time Past Year Past 30 Days
Abstract Views 0 0 0
Full Text Views 1725 485 24
PDF Downloads 1205 161 9