DOI QR코드

DOI QR Code

Simulation of Agricultural Water Supply Considering Yearly Variation of Irrigation Efficiency

연단위 관개효율 변화를 고려한 관개지구 용수 공급량 모의

  • Song, Jung Hun (Department of Rural Systems Engineering, Seoul National University) ;
  • Song, Inhong (Research Institute of Agriculture and Life Sciences, Seoul National University) ;
  • Kim, Jin Taek (Rural Research Institute, Korea Rural Community Corporation) ;
  • Kang, Moon Seong (Department of Rural Systems Engineering, Research Institute of Agriculture and Life Sciences, Institute of Green Bio Science and Technology, Seoul National University)
  • 송정헌 (서울대학교 지역시스템공학전공) ;
  • 송인홍 (서울대학교 농업생명과학연구원) ;
  • 김진택 (한국농어촌공사 농어촌연구원) ;
  • 강문성 (서울대학교 지역시스템공학전공, 농업생명과학연구원, 그린바이오과학기술연구원)
  • Received : 2015.03.14
  • Accepted : 2015.04.07
  • Published : 2015.06.30

Abstract

The objective of this study was to evaluate simulation of agricultural water supply considering yearly variation of irrigation efficiency. The water supply data of the Idong reservoir from 2001 through 2009 was collected and used for this study. Total 6 parameters including irrigation efficiency (Es), drainage outlet height, and infiltration, were used for sensitivity analysis, calibration, and validation. Among the parameters, the Es appeared to be the most sensitivity parameter. The Es was calibrated on a yearly basis considering sensitivity and time-varying characteristic, while other parameters were set to fixed values. The statistics of percent bias (PBLAS), Nash-Sutcliffe efficiency (NSE), and root means square error to the standard deviation of measured data (RSR) for a monthly step were 2.7%, 0.93, and 0.26 for the calibration, and 3.9%, 0.89, and 0.32 for the validation, correspondently. The results showed a good agreement with the observations. This implies that the modeling only with appropriate parameter values, apart from modeling approaches, can simulate the real supply operation reasonably well. However, the simulations with uncalibrated parameters from previous studies produced poor results. Thus, it is important to use calibrated values, and especially, we suggest the Es's yearly calibration for simulating agricultural water supply.

본 연구에서는 관개효율의 연별 변화와 필요수량을 고려하여 추정된 관개지구 용수 공급량이 현장에서 실제 공급되는 수량을 잘 모의하는지를 평가하였다. 대상지구로 이동저수지 지구를 선정하여, 2001~2009년 기간에 대한 실측 공급량 자료를 구축하였다. 관개효율, 물꼬높이, 침투량 등 총6개의 매개변수에 대해 민감도 분석, 보정 및 검정을 수행하였다. 민감도 분석결과, 관개효율이 가장 민감한 매개변수로 나타났다. 관개효율은 가장 민감하게 나타난 점과 연마다 값이 달라지는 특징을 반영하여 연별로 보정하였다. 통계적 지표 산정 결과 월단위에 대한 PBIAS, NSE, 그리고 RSR은 보정기간 동안 각각 2.7%, 0.93, 0.26로, 검정기간 동안 각각 3.9%, 0.89, 0.32로 매우 우수하게 나타났다. 따라서 비록 농업용수 공급량은 인위적 요소이나, 적절한 매개변수 값을 사용하여 모의한다면 모의치가 실측치와 유사하게 모의될 수 있을 것이다. 하지만 대상지구의 실측 자료가 확보되지 않아 보정되지 않은 매개변수를 사용하는 경우 결과가 매우 안 좋을 수 있을 가능성이 나타났다. 따라서 농업용수 공급량의 모의 시 적절한 매개변수의 선정은 매우 중요할 것으로 사료되며, 특히 관개효율은 연별로 보정하는 것을 제안한다.

Keywords

References

  1. Allen, R.G., Pereira, L.S., Raes, D., and Smith, M. (1998). Crop evapotranspiration-Guidelines for computing crop water requirements. FAO Irrigation and drainage paper 56, Food and Agriculture Organization of the United Nations, Rome.
  2. Anan, M., Yuge, K., Nakano, Y., Funakoshi, T., and Haraguchi, T. (2004). "The relationship between water intake rates, paddy ponding depth, and farmers' water management techniques." Paddy and Water Environment, Vol. 2, No. 1, pp. 11-18. https://doi.org/10.1007/s10333-004-0035-6
  3. Anbumozhi, V., Yamaji, E., and Tabuchi, T. (1998). "Rice crop growth and yield as influenced by changes in ponding water depth, water regime and fertigation level." Agricultural Water Management, Vol. 37, No. 3, pp. 241-253. https://doi.org/10.1016/S0378-3774(98)00041-9
  4. Bos, M.G., and Nugteren, J. (1990). On irrigation efficiencies. Report 19, International Institute for Land Reclamation and Improvement, Wageningen, The Netherlands, pp. 91.
  5. Cho, J., and Mostaghimi, S. (2009). "Dynamic agricultural non-point source assessment tool (DANSAT): Model application." Biosystems Engineering, Vol. 102, No. 4, pp. 500-515. https://doi.org/10.1016/j.biosystemseng.2009.01.012
  6. Chung, H.W., Kim, S.J., Kim, J.S., Noh, J.K., Park, K.U., Son, J.K., Yoon, K.S., Lee, K.H., Lee, N.H., Chung, S.O., Choi, J.D., and Choi, J.Y. (2006). Irrigation and Drainage Engineering. Dongmyeong Publisher.
  7. Gupta, H.V., Sorooshian, S., and Yapo, P.O. (1999). "Status of automatic calibration for hydrologic models: Comparison with multilevel expert calibration." Journal of Hydrologic Engineering, Vol. 4, No. 2, pp. 135-143. https://doi.org/10.1061/(ASCE)1084-0699(1999)4:2(135)
  8. Howell, T.A. (2003). "Irrigation efficiency." Encyclopedia of water science, Marcel Dekker, New York, pp. 467-472.
  9. Huh, Y.M., Park, C.E., and Park, S.W. (1993). "A streamflow network model for daily water supply and demands on small watershed (II): model development." Journal of the Korean Society of Agricultural Engineers, Vol. 35, No. 2, pp. 23-32.
  10. Im, S.J., Park, S.W., and Kim, H.J. (2000a). "Methodology for estimating agricultural water supply in the Han River basin." Journal of Korea Water Resources Association, Vol. 33, No. 6, pp. 765-774.
  11. Im, S.J., Park, S.W., Chin, Y.M., and Yoon, K.S. (2000b). "Development of CREAMS-PADDY model." Proceedings 2000 ASAE Annual International Meeting, Milwaukee, Wisconsin, USA, pp. 1-13.
  12. Im, S.J., Park, S.W., Kim, S.M., and Kim, H.J. (2000c). "Surveying the daily pumpage for irrgating paddy rice in the Han River basin." Journal of the Korean Society of Agricultural Engineers, Vol. 42, No. 1, pp. 57-65.
  13. James, L.D., and Burgess, S.J. (1982). "Selection, calibration and testing of hydrologic models." Hydrologic Modeling of Small Watersheds, Edited by Haan, C.T., Johnson, H.P., and Brakensiek, D.L., ASAE, St. Joseph, Mich, pp. 437-472.
  14. Jesiek, J.B., and Wolfe, M.L. (2005). "Sensitivity analysis of the Virginia phosphorus index management tool." Transactions of the ASAE, Vol. 48, No. 5, pp. 1773-1781. https://doi.org/10.13031/2013.20011
  15. Ju, W.J., Kim, J.T., Park, K.W., and Lee, Y.J. (2006). "Developing of system for estimating water demand considering variation of farming conditions in paddy field." KCID Journal, Vol. 13, No. 1, pp. 82-90.
  16. Kang, M.G., Oh, S.T., and Kim, J.T. (2014). "Estimation of amounts of water release from reservoirs considering customary irrigation water management practices in paddy-field districts." Journal of the Korean Society of Agricultural Engineers, Vol. 56, No. 5, pp. 1-9. https://doi.org/10.5389/KSAE.2014.56.5.001
  17. Kang, M.S., Park, S.W., Lee, J.J., and Yoo, K.H. (2006). "Applying SWAT for TMDL programs to a small watershed containing rice paddy fields." Agricultural Water Management, Vol. 79, No. 1, pp. 72-92. https://doi.org/10.1016/j.agwat.2005.02.015
  18. Khepar, S.D., Yadav, A.K., Sondhi, S.K., and Siag, M. (2000). "Water balance model for paddy fields under intermittent irrigation practices." Irrigation Science, Vol. 19, No. 4, pp. 199-208. https://doi.org/10.1007/PL00006713
  19. Kim, H.K., Jang, T., Im, S.J., and Park, S.W. (2009). "Estimation of irrigation return flow from paddy fields considering the soil moisture." Agricultural Water Management, Vol. 96, No. 5, pp. 875-882. https://doi.org/10.1016/j.agwat.2008.11.009
  20. Kim, H.K., Kang, M.S., Park, S.W., Choi, J.Y., and Yang, H.J. (2009). "Auto-calibration for the SWAT model hydrological parameters using multi-objective optimization method." Journal of the Korean Society of Agricultural Engineers, Vol. 51, No. 1, pp. 1-9. https://doi.org/10.5389/KSAE.2009.51.1.001
  21. Kim, J.S., Oh, S.Y., Oh, K.Y., and Cho, J.W. (2005). "Delivery management water requirement for irrigation ditches associated with large-sized paddy plots in Korea." Paddy and Water Environment, Vol. 3, No. 1, pp. 57-62. https://doi.org/10.1007/s10333-005-0072-9
  22. Kim, S., and Kim, H.S. (2007). "Neural networks-Genetic Algorithm model for modeling of nonlinear evaporation and evapotranspiration time series 1. theroy and application of the model." Journal of Korea Water Resources Association, Vol. 40, No. 1, pp. 73-88. https://doi.org/10.3741/JKWRA.2007.40.1.073
  23. Korea Agricultural and Rural Infrastructure Corporation (KRC) (2005). A study on water supply methods considering variation of farming conditions in paddy field.
  24. Lee, Y.J., Kim, S.J., Kim, P.S., Joo, U.J., and Yang, Y.S. (2006). "Study on the effective calculation method of irrigation water in a paddy fields area." Journal of the Korean Society of Agricultural Engineers, Vol. 48, No. 3, pp. 11-20. https://doi.org/10.5389/KSAE.2006.48.3.011
  25. Legates, D.R., and McCabe, G.J. (1999). "Evaluating the use of "goodness-of-fit" measures in hydrologic and hydroclimatic model validation." Water Resources Research, Vol. 35, No. 1, pp. 233-241. https://doi.org/10.1029/1998WR900018
  26. Ministry of Agriculture and Forestry (MAF) (1997). A study on the water requirement variation with the farming conditions in the paddy field.
  27. Ministry of Agriculture and Forestry (MAF) (1998). Agricultural Infrastructure Design Standards: Irrigation.
  28. Ministry of Land, Transport and Maritime Affairs (MOLTM) (2011). Long-term Korea national water resources plan. pp. 18.
  29. Mistry of Agriculture, Food an Rural Affairs (MAFRA) (2014). Statistical yearbook of land and water development for agriculture. pp. 23-27.
  30. Moriasi, D.N., Arnold, J.G., Van Liew, M.W., Bingner, R.L., Harmel, R.D., and Veith, T.L. (2007). "Model evaluation guidelines for systematic quantification of accuracy in watershed simulations." Transactions of the ASABE, Vol. 50, No. 3, pp. 885-900. https://doi.org/10.13031/2013.23153
  31. Nam, W.H., Choi, J.Y., Choi, S.G., Jang, M.W., Lee, N.H., and Ko, K.D. (2011). "A survey on irrigation timing and water saving strategies of agricultural reservoirs." KCID Journal, Vol. 18, No. 1, pp. 81-93.
  32. Nam, W.H., Choi, J.Y., Hong, E.M., and Kim, J.T. (2013). "Assessment of irrigation efficiencies using smart water management." Journal of the Korean Society of Agricultural Engineers, Vol. 55, No. 4, pp. 45-53. https://doi.org/10.5389/KSAE.2013.55.4.045
  33. Nam, W.H., Kim, T., Choi, J.Y., and Lee, J. (2012). "Vulnerability assessment of water supply in agricultural reservoir utilizing probability distribution and reliability analysis methods." Journal of the Korean Society of Agricultural Engineers, Vol. 54, No. 2, pp. 37-46. https://doi.org/10.5389/KSAE.2012.54.2.037
  34. Nash, J., and Sutcliffe, J.V. (1970). "River flow forecasting through conceptual models part I-A discussion of principles." Journal of hydrology, Vol. 10, No. 3, pp. 282-290. https://doi.org/10.1016/0022-1694(70)90255-6
  35. Park, B.J., Cha, H.S., and Kim, J.H. (1997). "A study on parameters estimation of storage function model using the Genetic Algorithms." Journal of Korea Water Resources Association, Vol. 30, No. 4, pp. 347-355.
  36. Park, C.E., KIm, J.T., and Oh, S.T. (2012). "Analysis of stage-discharge relationships in the irrigation canal with auto-measuring system." Journal of the Korean Society of Agricultural Engineers, Vol. 54, No. 1, pp.109-114. https://doi.org/10.5389/KSAE.2012.54.1.109
  37. Rural Research Institute (RRI) (2012). Research on a test watershed for integrated agricultural water resources. pp. 136-137.
  38. Song, J.H. (2013). A daily surface drainage simulation model for irrigation districts consisting of paddy and protected cultivation. M.S. thesis, Seoul National University.
  39. Song, J.H., Kang, M.S., Song, I., and Jang, J.R. (2012). "Comparing farming methods in pollutant runoff loads from paddy fields using the CREAMS-PADDY model." Korean Journal of Environmental Agriculture, Vol. 31, No. 4, pp. 318-327. https://doi.org/10.5338/KJEA.2012.31.4.318
  40. Song, J.H., Kang, M.S., Song, I., Hwang, S.H., Park, J., and Ahn, J.H. (2013). "Surface drainage simulation model for irrigation districts composed of paddy and protected cultivation." Journal of the Korean Society of Agricultural Engineers, Vol. 55, No. 3, pp. 63-73. https://doi.org/10.5389/KSAE.2013.55.3.063
  41. Song, J.H., Jeong, H.S., Park, J.H., Song, I.H., Kang, M.S., and Park, S.W. (2014). "Analysis of water quality and soil environment in paddy fields partially irrigated with untreated wastewater." Journal of the Korean Society of Agricultural Engineers, Vol. 56, No. 6, pp. 19-29. https://doi.org/10.5389/KSAE.2014.56.6.019
  42. Song, J.H., Song, I., Kim, J.T., and Kang, M.S. (2015). "Characteristics of irrigation return flow in a reservoir irrigated district." Journal of the Korean Society of Agricultural Engineers, Vol. 57, No. 1, pp. 69-78. https://doi.org/10.5389/KSAE.2015.57.1.069
  43. Storm, D.E., Dillaha, T.A., Mostaghimi, S., and Shanholtz, V.O. (1988). "Modeling phosphorus transport in surface runoff." American Society of Agricultural Engineers, Vol. 31, No. 1, pp. 117-127. https://doi.org/10.13031/2013.30676
  44. Wu, Y., and Chen, J. (2012). "An operation-based scheme for a multiyear and multipurpose reservoir to enhance macroscale hydrologic models." Journal of Hydrometeorology, Vol. 13, No. 1, pp. 270-283. https://doi.org/10.1175/JHM-D-10-05028.1
  45. Yoo, S.H., Choi, J.Y., and Jang, M.W. (2006). "Estimation of paddy rice crop coefficients for FAO Penman-Monteith and Modified Penman method." Journal of the Korean Society of Agricultural Engineers, Vol. 48, No. 1, pp. 13-23. https://doi.org/10.5389/KSAE.2006.48.1.013
  46. Yoo, S.H., Choi, J.Y., and Jang, M.W. (2008). "Estimation of design water requirement using FAO Penman-Monteith and optimal probability distribution function in South Korea." Agricultural Water Management, Vol. 95, No. 7, pp. 845-853. https://doi.org/10.1016/j.agwat.2008.02.010
  47. Yoo, S.H., Choi, J.Y., Lee, S.H., Oh, Y.G., and Yun, D.G. (2013). "Climate change impacts on water storage requirements of an agricultural reservoir considering changes in land use and rice growing season in Korea." Agricultural Water Management, Vol. 117, pp. 43-54. https://doi.org/10.1016/j.agwat.2012.10.023

Cited by

  1. Hydrologic Modeling for Agricultural Reservoir Watersheds Using the COMFARM vol.58, pp.3, 2016, https://doi.org/10.5389/KSAE.2016.58.3.071
  2. Regression Equations for Estimating the TANK Model Parameters vol.57, pp.4, 2015, https://doi.org/10.5389/KSAE.2015.57.4.121
  3. Web-Based Data Processing and Model Linkage Techniques for Agricultural Water-Resource Analysis vol.57, pp.5, 2015, https://doi.org/10.5389/KSAE.2015.57.5.101
  4. Water Balance in Irrigation Reservoirs Considering Flood Control and Irrigation Efficiency Variation vol.142, pp.4, 2016, https://doi.org/10.1061/(ASCE)IR.1943-4774.0000989