Skip to main content

Quantitative Assessment of Impact of Climate Change on Crop Yield over Sikkim and Central Region of India

  • Chapter
  • First Online:
Hydro-Meteorological Extremes and Disasters

Abstract

The present work focuses on (1) assessing the yield of rice, wheat crop under RCPs scenario 4.5 and 8.5 using AquaCrop yield simulating model and (2) determining the best sowing date of crops for maximum yield output across Sikkim and Central region of India. The bias corrected GCM outputs were utilised to simulate the yields of wheat and rice. The AquaCrop model was first calibrated (1998–2007), validated (2008–2015) and then future yield of wheat and rice was simulated for years 2021–2099. The Aquacrop simulated results over Sikkim shows an increase in yield of 0.5–20% for rice crop and 2–44% for wheat crop during the future years 2021–2099. For the Central region of India, the result depicts the highest impact of future climate with reduction in crop yields particularly during for future period (2081–2099) under RCP 8.5 climate scenario. Under the changed climate over Central India, shifting of planting date of rice (5 days later for period 2021–2060, 10 days later for period 2061–2099) and for wheat (15 days later for period 2021–2099) is proposed as a practical adaptation measure for sustaining the future yields.

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

Access this chapter

Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 129.00
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 169.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info
Hardcover Book
USD 169.99
Price excludes VAT (USA)
  • Durable hardcover edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

References

  • Abedinpour M, Sarangi A, Rajput TBS, Singh M, Pathak H, Ahmad T (2012) Performance evaluation of AquaCrop model for maize crop in a semi-arid environment. Agric Water Manag 110:55–66

    Article  Google Scholar 

  • ASSOCHAM Report (2016) Drought situation to cost Rs 6.5 lakh crore to economy

    Google Scholar 

  • Balvanshi A, Tiwari HL (2018) Analysis of GCMs for prediction of precipitation for hoshangabad region of Madhya Pradesh. J Agrometeorol 20(4):302–304

    Article  Google Scholar 

  • Balvanshi A, Tiwari HL (2019) Mitigating future climate change on wheat and soybean yields in central region of Madhya Pradesh by shifting sowing dates. J Agrometeorol 20(4):468–473

    Google Scholar 

  • Das J, Umamahesh NV (2017) Uncertainty and nonstationarity in streamflow extremes under climate change scenarios over a River Basin. J Hydrol Eng Am Soc Civil Eng 22(10):04017042. https://doi.org/10.1061/(ASCE)HE.1943-5584.0001571

    Article  Google Scholar 

  • Das J, Poonia V, Jha S, Goyal MK (2020) Understanding the climate change impact on crop yield over eastern Himalayan region: ascertaining GCM and scenario uncertainty. Theor Appl Climatol 142(1–2):467–482. https://doi.org/10.1007/s00704-020-03332-y

    Article  ADS  Google Scholar 

  • Deb P, Kiem AS, Babel MS, Chu ST, Chakma B (2015a) Evaluation of climate change impacts and adaptation strategies for maize cultivation in the Himalayan foothills of India. J Water Climate Change 6(3):596–614, IWA Publishing. https://doi.org/10.2166/wcc.2015.070

    Article  Google Scholar 

  • Deb P, Shrestha S, Babel MS (2015b) Forecasting climate change impacts and evaluation of adaptation options for maize cropping in the hilly terrain of Himalayas: Sikkim, India. Theor Appl Climatol 121(3–4):649–667, Springer-Verlag Wien

    Article  ADS  Google Scholar 

  • Foster T, Brozović N, Butler AP, Neale CMU, Raes D, Steduto P, Fereres E, Hsiao TC (2017) AquaCrop-OS: an open source version of FAO’s crop water productivity model. Agri Water Manag 181:18–22, Elsevier BV

    Article  Google Scholar 

  • IPCC (2013) AR5 climate change 2013: the physical science basis – IPCC. Contribution of working group I to the fifth assessment report of the intergovernmental panel on climate change. Cambridge University Press

    Google Scholar 

  • Johnson F, Sharma A (2009) Measurement of GCM skill in predicting variables relevant for hydroclimatological assessments. J Climate Am Meteorol Soc 22(16):4373–4382

    ADS  Google Scholar 

  • Jones JW, Hoogenboom G, Porter CH, Boote KJ, Batchelor WD, Hunt LA, Wilkens PW, Singh U, Gijsman AJ, Ritchie JT (2003) The DSSAT cropping system model. Eur J Agron:235–265, Elsevier

    Google Scholar 

  • Kumar RK, Sahai AK, Kumar KK, Patwardhan SK, Mishra PK, Revadekar JV, Kamala K, Pant GB (2006) High-resolution climate change scenarios for India for the 21st century. Curr Sci 90(3):334–345

    Google Scholar 

  • Kumar N, Poonia V, Gupta BB, Goyal MK (2021) A novel framework for risk assessment and resilience of critical infrastructure towards climate change. Technol Forecast Soc Change 165(January):120532, Elsevier Inc

    Article  Google Scholar 

  • Mohammad S, Tiwari HL, Balvanshi. (2018) Evaluation of yield of soybean crop using Aquacrop model for Ujjain district. Int J Recent Sci Res 9(5):26968–26972

    Google Scholar 

  • Mohanty M, Sinha NK, Hati KM, Reddy KS, Chaudhary RS (2015) Elevated temperature and carbon dioxide concentration effects on wheat productivity in Madhya Pradesh: a simulation study. J Agrometeorol 17(2):185–189

    Article  Google Scholar 

  • Patel C, Nema AK, Singh RS, Yadav MK, Singh KK, Singh SK, Rai PK, Singh SM (2018) Assessment of climate change impact on wheat crop using MarkSim GCM in Varanasi, Uttar Pradesh. J Agrometeorol 20(3):216–218

    Article  Google Scholar 

  • Poonia V, Das J, Goyal MK (2021a) Impact of climate change on crop water and irrigation requirements over eastern Himalayan region. In: Stochastic Environmental Research and Risk Assessment, Springer, Berlin/Heidelberg, 35(6):1175–1188. https://doi.org/10.1007/s00477-020-01942-6

  • Poonia V, Goyal MK, Gupta BB, Gupta AK, Jha S, Das J (2021b) Drought occurrence in Different River basins of India and blockchain technology based framework for disaster management. J Clean Prod 312:127737

    Article  Google Scholar 

  • Poonia V, Jha S, Goyal MK (2021c) Copula based analysis of meteorological, hydrological and agricultural drought characteristics across Indian river basins. Int J Climatol (August 2020):1–16

    Google Scholar 

  • Raes D, Steduto P, Hsiao TC, Fereres E (2009) Aquacrop-the FAO crop model to simulate yield response to water: II. Main algorithms and software description. Agron J 101(3):438–447, Wiley

    Article  Google Scholar 

  • Sandhu SS, Mahal SS, Kaur P (2015) Calibration, validation and application of AquaCrop model in irrigation scheduling for rice under Northwest India. J Appl Nat Sci 7(2):691–699, ANSF Publications

    Article  CAS  Google Scholar 

  • Sethi RR, Mandal KG, Sarangi A, Behera A (2016) Simulating paddy crop response to irrigation using FAO AquaCrop mode: a case study. J Food Agri Environ 14:99–103

    CAS  Google Scholar 

  • Simonovic SP (2017) Bringing future climatic change into water resources management practice today. Water Res Manag 31(10):2933–2950, Springer Netherlands. https://doi.org/10.1007/s11269-017-1704-8

    Article  Google Scholar 

  • Steduto P, Hsiao TC, Raes D, Fereres E (2009) Aquacrop-the FAO crop model to simulate yield response to water: I. concepts and underlying principles. Agron J 101(3):426–437, Wiley. https://doi.org/10.2134/agronj2008.0139s

    Article  Google Scholar 

  • Subash N, Singh SS, Priya N (2013) Observed variability and trends in extreme temperature indices and rice-wheat productivity over two districts of Bihar, India – a case study. Theor Appl Climatol 111(1–2):235–250, Springer-Verlag Wien. https://doi.org/10.1007/s00704-012-0665-3

    Article  ADS  Google Scholar 

  • Walikar LD, Bhan M, Giri AK, Dubey AK, Agrawal KK (2018) Impact of projected climate on yield of soybean using CROPGRO-Soybean model in Madhya Pradesh. J Agrometeorol 20(3):211–215

    Article  Google Scholar 

  • Wang E, Robertson MJ, Hammer GL, Carberry PS, Holzworth D, Meinke H, Chapman SC, Hargreaves JNG, Huth NI, McLean G (2002) Development of a generic crop model template in the cropping system model APSIM. Eur J Agron 18:121–140, Elsevier

    Article  Google Scholar 

  • Zadeh LA (1999) Fuzzy sets as a basis for a theory for possibility. Fuzzy Sets Syst 100:9–34. https://doi.org/10.1016/S0165-0114(99)80004-9

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Akhilesh Gupta .

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2022 The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

About this chapter

Check for updates. Verify currency and authenticity via CrossMark

Cite this chapter

Balvanshi, A., Poonia, V., Tiwari, H.L., Goyal, M.K., Gupta, A.K., Gupta, A. (2022). Quantitative Assessment of Impact of Climate Change on Crop Yield over Sikkim and Central Region of India. In: Goyal, M.K., Gupta, A.K., Gupta, A. (eds) Hydro-Meteorological Extremes and Disasters. Disaster Resilience and Green Growth. Springer, Singapore. https://doi.org/10.1007/978-981-19-0725-8_12

Download citation

Publish with us

Policies and ethics