DOI QR코드

DOI QR Code

Estimation of Irrigation Water Amounts for Farm Products based on Various Soil Physical Properties and Crops

다양한 토양의 물리적 특성과 작물에 따른 밭작물 관개용수량 산정

  • Lee, Taehwa (School of Agricultural Civil & Bio-Industrial Engineering, Kyungpook National University) ;
  • Shin, Yongchul (School of Agricultural Civil & Bio-Industrial Engineering, Kyungpook National University)
  • Received : 2016.09.09
  • Accepted : 2016.09.26
  • Published : 2016.11.30

Abstract

Crop damages due to agricultural drought has been increased in recent years. In Korea, water resources are limited indicating that proper management plans against agricultural drought are required for better water-use efficiency in agriculture. In this study, irrigation intervals and amounts for various crops and soil physical properties (sandy and silt loams) were estimated using the IWMM model. Five different crops (soybean, radish, potato, barley and maize) at the Bangdong-ri site in Chuncheon were selected to test the IWMM model. IWMM assessed agricultural drought conditions using the soil moisture deficit index (SMDI), and irrigation intervals and amounts were determined based on the degree of agricultural drought (SMDI). Additionally, we tested the effects of surface irrigation and sprinkler irrigation methods and various irrigation intervals of 2, 3, 5 and 7 days. In our findings, the irrigation intervals of 5 and 7 days showed the minimum rrigation amounts than others. When we considered that the intervals of 3 or 5 days are usually preferred to fields, the interval of 5 days was determined in our study. The estimated irrigation amounts for different crops were shown as maize > radish > barley > soybean > potato, respectively. The irrigation amounts for maize and barley were highly affected by soil properties, but other crops have less differences. Also, small differences in irrigation amounts were shown between the surface and sprinkler irrigation methods. These might be due to the lack of consideration of water loss (e.g., evapotranspiration, infiltration, etc.) in IWMM indicating model structural uncertainties. Thus, possible water loss (e.g., evapotranspiration, infiltration) need to be considered in application to fields. Overall, IWMM performed well in determining the irrigation intervals and amounts based on the degree of agricultural drought conditions (SMDI). Thus, the IWMM model can be useful for efficient agricultural water resources management in regions at where available water resources are limited.

Keywords

References

  1. Efron, B., 1982. The jackknife, the bootstrap and other resampling plans. Society for Industrial and Applied Mathematics, Philadelphia, PA.
  2. Feddes, R. A., P. J. Kowalik, and H. Zarandy, 1978. Simulation of field water use and crop yield, Wiley, New York.
  3. Goldberg, D. E., 1989. Genetic algorithms in search and optimization and machine learning, Addison-Wesley Publ., Reading, MA.
  4. Holland, J. H., 1975. On quantifying agricultural and water management practices from low spatial resolution RS data using genetic algorithms: a numerical study for mixed pixel environment. Adv. Water Resour. 28: 856-870.
  5. Ines, A. V. M., K. Honda, A. D. Gupta, P. Droogers, and R. S. Clemente, 2006. Combining remote sensing-simulation modeling and genetic algorithm optimization to explore water management options in irrigated agriculture. Agric. Water Manage. 83(3): 221-232. https://doi.org/10.1016/j.agwat.2005.12.006
  6. Kim, H. Y., Y. J. Suh, M. S. Sim, and K. Y. Lee, 1999. Determination of a new method for the upland water requirements. Proceedings of the Korean Society of Agricultural Engineers Conference: 41-46 (in Korean).
  7. Korea Ministry of Land, Transport and Maritime Affairs, 2011. Water Vision 2020, 18. Sejong, Korea.
  8. Korea Ministry of Agriculture, Food an Rural Affairs, 2015. Http://www.mafra.go.kr. Accessed 29 March. 2015.
  9. Kroes, J. G., J. C. van Dam, J. Huygen, and R. W. Vervoort, 1999. User's guide of SWAP version 2.0; Simulation of water, solute transport, and plant growth in the soil-atmosphere-plant environment. Rep. 81, DLO Winand Staring Centre, Wageningen, The Netherlands.
  10. Leij, F. J., W. J. Alves, M. Th. van Genuchten, and J. R. Williams, 1999, The UNSODA unsaturated soil hydraulic database. In: M.Th. Van Genuchten F. J. Leij and L. Wu. (eds.). Characterization and measurement of the hydraulic properties of unsaturated porous media, University of California, Riverside, CA. 1269-1281.
  11. Mualem, Y., 1976. A now model for predicting the hydraulic conductivity of unsaturated poous media. Water Resour. Res. 12(3): 513-522. https://doi.org/10.1029/WR012i003p00513
  12. Nam, W. H., E. M. Hong, M. W. Jang, and J. Y. Choi, 2014. Projection of consumptive use and irrigation water for major upland crops using soil moisture model under climate change, Journal of the Korean Society of Agricultural Engineers 56(5): 77-87 (in Korean).
  13. Narasimhan, B. and R. Srinivasan, 2005. Development and evaluation of soil moisture deficit index (SMDI) and evapotranspiration deficit index (ETDI) for agricultural drought monitoring. Agric. Forest Meteorol., 133(1-4): 69-88. https://doi.org/10.1016/j.agrformet.2005.07.012
  14. Shin, Y. and Y. Jung, 2014. Development of Irrigation Water Management Model for Reducing Drought Severity Using Remotely Sensed Soil Moisture Footprints. J. Irrig. Drain Eng. 10.1061.
  15. Shin, Y. and B. P. Mohanty, 2013. Development of a deterministic downscaling algorithm for remote sensing soil moisture footprint using soil and vegetation classifications. Water Resour. Res. 49(10): 6208-6228. https://doi.org/10.1002/wrcr.20495
  16. Suh, Y. J. and K. Y. Lee, 2002. Method of calculation in upland irrigation. Magazine of the Korean Society of Agricultural Engineers. 44(1): 25-34 (in Korean).
  17. van Dam, J. C., et al., 1997. Theory of SWAP version 2.0: Simulation of water flow and plant growth in the soil-wateratmosphere-plant environment. Technical Document 45, DLO Winand Staring Centre, Wageningen, Netherlands.
  18. van Dam, J. C., 2000. Field-scale water flow and solute transport. SWAP model concepts, parameter estimation and case studies. Ph.D. dissertation, Wageningen Univ., Wageningen, The Netherlands.
  19. van Genuchten, M. T., 1980. A closed-form equation foe predicting the hydraulic conductivity of unsaturated soils. Soil Sci. Soc. Am. J. 44(5): 892-898. https://doi.org/10.2136/sssaj1980.03615995004400050002x