Advertisement

Influence mechanism of climate change on paddy farming practices and irrigation water demand

  • Gun-Ho Cho
  • Mirza Junaid Ahmad
  • Seulgi Lee
  • Kyung-Sook ChoiEmail author
  • Won-Ho Nam
  • Hyung-Joong Kwon
Article

Abstract

Technological and socioeconomic interventions accompanied by climate warming strongly dictate farming practices, lending a direct impact over future irrigation water demand and supply. In this article, two pivotal factors of farming practices and climate change were included to assess their role in the future paddy water management of Korea. Field surveys were conducted across irrigated areas of twelve agricultural reservoirs to distinguish traditional and current paddy farming practices. Projected climate for two future time slices the 2060s (2020 to 2059) and the 2100s (2060 to 2100) under two representative concentration pathway scenarios (4.5 and 8.5) were used for climate change impact assessment. Crop evapotranspiration (ETc), effective rainfall, gross duty of water (GDW) and annual inflow were simulated from 1987 to 2100 under both farming practices. Future climate projections suggested a continuous warming trend accompanied by distinctively negative/positive shifts in central/southern region annual rainfall by the end of the twenty-first century. Annual inflow in the central (southern) region reservoirs exhibited downward (upward) trends during the 2060s and only upward trends during the 2100s, respectively, whereas rice ETc showed upward tendencies regardless of the farming practices. Rice season effective rainfall varied for different reservoirs mostly showing increasing tendencies. The GDW increased implying that projected positive rainfall shifts might not withhold the driving impacts of temperature rise over regional irrigation water demands. Following the traditional farming practices in future would intensify the anticipated rise in irrigation demand and may lead to water shortages given the present storage capacities of agricultural reservoirs.

Keywords

Irrigation water demand Climate change Farming practices Paddy rice 

Notes

Acknowledgements

This research was supported by the Korea Rural Research Institution (KRRI). The views expressed in this paper are those of the authors and do not necessarily reflect the views of KRRI or any of its sub-agencies.

References

  1. Allen RG, Pereira LS, Raes D, Smith M (1998) Crop evapotranspiration-guidelines for computing crop water requirements. FAO irrigation and drainage paper 56, United Nations Food and Agriculture Organization, RomeGoogle Scholar
  2. Arnell NW, van Vuuren DP, Isaac M (2011) The implications of climate policy for the impacts of climate change on global water resources. Glob Environ Change 21:592–603.  https://doi.org/10.1016/j.gloenvcha.2011.01.015 CrossRefGoogle Scholar
  3. Ashofteh Parisa S, Haddad Omid B, Miguel AM (2013) Climate change impact on reservoir performance indexes in agricultural water supply. J Irrig Drain Eng 139:85–97.  https://doi.org/10.1061/(ASCE)IR.1943-4774.0000496 CrossRefGoogle Scholar
  4. Baek CW, Coles NA (2013) An artificial catchment rainfall-runoff collecting system: design efficiency and reliability potential considering climate change in Western Australia. Agric Water Manag 121:124–134.  https://doi.org/10.1016/j.agwat.2013.01.013 CrossRefGoogle Scholar
  5. Chukalla AD, Haile AM, Schultz B (2013) Optimum irrigation and pond operation to move away from exclusively rainfed agriculture: the Boru Dodota Spate Irrigation Scheme, Ethiopia. Irrig Sci 31:1091–1102.  https://doi.org/10.1007/s00271-012-0390-9 CrossRefGoogle Scholar
  6. Culley S et al (2016) A bottom-up approach to identifying the maximum operational adaptive capacity of water resource systems to a changing climate. Water Resour Res 52:6751–6768.  https://doi.org/10.1002/2015WR018253 CrossRefGoogle Scholar
  7. de Hamer W, Love D, Owen R, Booij MJ, Hoekstra AY (2008) Potential water supply of a small reservoir and alluvial aquifer system in southern Zimbabwe. Phys Chem Earth Parts A/B/C 33:633–639.  https://doi.org/10.1016/j.pce.2008.06.056 CrossRefGoogle Scholar
  8. Green M, Weatherhead EK (2014) The application of probabilistic climate change projections: a comparison of methods of handling uncertainty applied to UK irrigation reservoir design. J Water Clim Change 5:652–666CrossRefGoogle Scholar
  9. Hong E-M, Choi J-Y, Nam W-H, Kim J-T (2016) Decision support system for the real-time operation and management of an agricultural water supply. Irrig Drain 65:197–209.  https://doi.org/10.1002/ird.1935 CrossRefGoogle Scholar
  10. Kim T-C, Lee J-M, Kim D-S (2003) Decision support system for reservoir operation considering rotational supply over irrigation blocks. Paddy Water Environ, 1:139–147.  https://doi.org/10.1007/s10333-003-0022-3 CrossRefGoogle Scholar
  11. Kim J, Choi J, Choi C, Park S (2013) Impacts of changes in climate and land use/land cover under IPCC RCP scenarios on streamflow in the Hoeya River Basin, Korea. Sci Total Environ 452–453:181–195.  https://doi.org/10.1016/j.scitotenv.2013.02.005 CrossRefGoogle Scholar
  12. Lee T, Jeong C (2014) Nonparametric statistical temporal downscaling of daily precipitation to hourly precipitation and implications for climate change scenarios. J Hydrol 510:182–196.  https://doi.org/10.1016/j.jhydrol.2013.12.027 CrossRefGoogle Scholar
  13. Lee YH, Singh VP (1999) Tank model using Kalman filter. J Hydrol Eng 4:344–349.  https://doi.org/10.1061/(ASCE)1084-0699(1999)4:4(344) CrossRefGoogle Scholar
  14. Lee S-H, Yoo S-H, Choi J-Y, Hwang S (2017) GCM-related uncertainity in forcasting irrigation and design water requirement for paddy rice fields. Int J Climatol 38:1298–1313CrossRefGoogle Scholar
  15. Masia S, Sušnik J, Marras S, Mereu S, Spano D, Trabucco A (2018) Assessment of irrigated agriculture vulnerability under climate change in Southern Italy. Water 10:209CrossRefGoogle Scholar
  16. Milly PCD, Betancourt J, Falkenmark M, Hirsch RM, Kundzewicz ZW, Lettenmaier DP, Stouffer RJ (2008) Stationarity is dead: whither water management? Science 319:573–574CrossRefGoogle Scholar
  17. Moradi-Jalal M, Bozorg Haddad O, Karney BW, Mariño MA (2007) Reservoir operation in assigning optimal multi-crop irrigation areas. Agric Water Manag 90:149–159.  https://doi.org/10.1016/j.agwat.2007.02.013 CrossRefGoogle Scholar
  18. Nam W-H, Choi J-Y (2014) Development of an irrigation vulnerability assessment model in agricultural reservoirs utilizing probability theory and reliability analysis. Agric Water Manag 142:115–126.  https://doi.org/10.1016/j.agwat.2014.05.009 CrossRefGoogle Scholar
  19. Nam W-H, Choi J-Y, Yoo S-H, Jang M-W (2012) A decision support system for agricultural drought management using risk assessment. Paddy Water Environ, 10:197–207.  https://doi.org/10.1007/s10333-012-0329-z CrossRefGoogle Scholar
  20. Nam W-H, Choi J-Y, Hong E-M (2015) Irrigation vulnerability assessment on agricultural water supply risk for adaptive management of climate change in South Korea. Agric Water Manag 152:173–187.  https://doi.org/10.1016/j.agwat.2015.01.012 CrossRefGoogle Scholar
  21. Nam W-H, Kim T, Hong E-M, Choi J-Y (2017) Regional climate change impacts on irrigation vulnerable season shifts in agricultural water availability for South Korea. Water 9:735.  https://doi.org/10.3390/w9100735 CrossRefGoogle Scholar
  22. Seung-Hwan Y, Jin-Yong C, Sang-Hyun L, Yun-Gyeong O, Dong Koun Y (2013) Climate change impacts on water storage requirements of an agricultural reservoir considering changes in land use and rice growing season in Korea. Agric Water Manag 117:43–54.  https://doi.org/10.1016/j.agwat.2012.10.023 CrossRefGoogle Scholar
  23. Song J-H, Kang Moon S, Song I, Jun Sang M (2016) Water balance in irrigation reservoirs considering flood control and irrigation efficiency variation. J Irrig Drain Eng 142:04016003.  https://doi.org/10.1061/(ASCE)IR.1943-4774.0000989 CrossRefGoogle Scholar
  24. Suresh KR, Mujumdar PP (2004) A fuzzy risk approach for performance evaluation of an irrigation reservoir system. Agric Water Manag 69:159–177.  https://doi.org/10.1016/j.agwat.2004.05.001 CrossRefGoogle Scholar
  25. Thanh Nguyen T, Hoang V-N, Seo B (2012) Cost and environmental efficiency of rice farms in South Korea. Agric Econ 43:369–378.  https://doi.org/10.1111/j.1574-0862.2012.00589.x CrossRefGoogle Scholar
  26. Vano JA et al (2010) Climate change impacts on water management and irrigated agriculture in the Yakima River Basin, Washington, USA. Clim Change 102:287–317.  https://doi.org/10.1007/s10584-010-9856-z CrossRefGoogle Scholar
  27. Yoo S-H, Choi J-Y, Jang M-W (2008) Estimation of design water requirement using FAO Penman–Monteith and optimal probability distribution function in South Korea. Agric Water Manag 95:845–853CrossRefGoogle Scholar
  28. Zhang H, Huang GH, Wang D, Zhang X (2011) Uncertainty assessment of climate change impacts on the hydrology of small prairie wetlands. J Hydrol 396:94–103.  https://doi.org/10.1016/j.jhydrol.20 CrossRefGoogle Scholar

Copyright information

© The International Society of Paddy and Water Environment Engineering 2019

Authors and Affiliations

  • Gun-Ho Cho
    • 1
  • Mirza Junaid Ahmad
    • 1
  • Seulgi Lee
    • 1
  • Kyung-Sook Choi
    • 1
    Email author
  • Won-Ho Nam
    • 2
  • Hyung-Joong Kwon
    • 3
  1. 1.Department of Agricultural Civil Engineering, Institute of Agricultural Science and TechnologyKyungpook National UniversityDaeguRepublic of Korea
  2. 2.Department of Bio-resources and Rural Systems EngineeringHankyong National UniversityAnseongRepublic of Korea
  3. 3.Department of Research CenterLido Engineering Co., LTDGoyangRepublic of Korea

Personalised recommendations