DOI QR코드

DOI QR Code

Agricultural Drought Assessment and Diagnosis Based on Spatiotemporal Water Supply in Irrigated Area

필지단위 관개용수 공급에 따른 농업가뭄진단 평가

  • Shin, Ji-Hyeon (School of Social Safety and Systems Engineering, Hankyong National University) ;
  • Nam, Won-Ho (School of Social Safety and Systems Engineering, Institute of Agricultural Environmental Science, National Agricultural Water Research Center, Hankyong National University) ;
  • Kim, Ha-Young (School of Social Safety and Systems Engineering, Hankyong National University) ;
  • Mun, Young-Sik (Department of Bioresources and Rural Systems Engineering, National Agricultural Water Research Center, Hankyong National University) ;
  • Bang, Na-Kyoung (Department of Convergence of Information and Communication Engineering, Hankyong National University) ;
  • Lee, Jueng-Chol (Overseas Project Department, Korea Rural Community Corporation) ;
  • Lee, Kwang-Ya (Integrated Water Management Supporting Department, Water Resources Planning Office, Korea Rural Community Corporation)
  • Received : 2021.03.30
  • Accepted : 2021.05.11
  • Published : 2021.07.31

Abstract

Agricultural drought is a natural phenomenon that is not easy to observe and predict and is difficult to quantify. In South Korea, the amount of agricultural water used is large and the types of use are varied, so even if an agricultural drought occurs due to insufficient precipitation, the drought actually felt in the irrigated area is it can be temporally and spatially different. In order to interpret the general drought in the past, drought disasters were evaluated using single indicators such as drought damage area, precipitation shortage status, and drought index, and a comprehensive drought management system is needed through drought diagnosis survey. Therefore, we intend to conduct research on agricultural drought assessment and diagnosis using re-evaluation of agricultural facilities and irrigation water supply network due to changes in various conditions such as climate change, irrigation canal network, and evaluation of water supply capacity of agricultural facilities. In this study, agricultural drought diagnosis was conducted on two agricultural reservoirs located in Sangju, Gyeongsangbuk-do, with structural or non-structural evaluations to increase spatiotemporal water supply and efficiency in terms of water shortages. The results of the agricultural drought diagnosis evaluation can be used to identify irrigated areas and canal network vulnerable to drought and to prioritize drought response.

Keywords

Acknowledgement

본 연구는 행정안전부 극한재난대응기반기술개발사업의 연구비 지원 (2019-MOIS31-010)에 의해 수행되었습니다.

References

  1. Ahn, S. R., G. A. Park, Y. H. Shin, and S. J. Kim, 2009. Assessment of the potential water supply rate of agricultural irrigation facilities using MODSIM. Journal of Korea Water Resources Association 42(10): 825-843.doi:10.3741/JKWRA.2009.42.10.825.
  2. Bang, N. K., W. H. Nam, E. M. Hong, M. J. Hayes, and M. D. Svoboda, 2018. Assessment of the meteorological characteristics and statistical drought frequency for the extreme 2017 spring drought event across South Korea. Journal of the Korean Society of Agricultural Engineers 60(4): 37-48. doi:10.5389/KSAE.2018.60.4.037.
  3. Choi, M. J., G. U. Park, D. W. Koh, and B. H. Jung, 2020. Study on the selection of excellent air force budget managers using AHP and probability distribution. Journal of the Korean Society of Supply Chain Management 20(2): 15-26. doi:10.25052/KSCM.2020.10.20.2.15.
  4. Coelho, C. A., I. A. Cavalcanti, S. M. Costa, S. R. Freitas, E. R. Ito, G. Luz, A. F. Santos, C. A. Nobre, J. A. Marengo, and A. B. Pezza, 2012. Climate diagnostics of three major drought events in the Amazon and illustrations of their seasonal precipitation predictions. Meteorological Applications 19(2): 237-255. doi:10.1002/met.1324.
  5. Eztollah, K., 2006. Appropriateness of farmers' adoption of irrigation methods: The application of the AHP model. Agricultural Systems 87(1): 101-119. doi:10.1016/j.agsy.2005.01.001.
  6. Hafeez, K., Y. Zhang, and N. Malak, 2002. Determining key capabilities of a firm using analytic hierarchy process. International Journal of Production Economics 76(1): 39-51. doi:10.1016/S0925-5273(01)00141-4.
  7. Hayes, M. J., O. V. Wilhelmi, and C. L. Knutson, 2004. Reducing drought risk: Bridging theory and practice. Natural Hazards Review 5(2): 106-113. doi:10.1061/(ASCE) 1527-6988(2004)5:2(106).
  8. Hong, E. M., J. Y. Choi, W. H. Nam, and J. T. Kim, 2016. Decision support system for the real-time operation and management of an agricultural water supply. Irrigation and Drainage 65(2): 197-209. doi:10.1002/ird.1935.
  9. Jang, J. S., 2019. Hydrometeorological characteristics and the spatial distribution of agricultural droughts. Journal of the Korean Society of Agricultural Engineers 61(2): 105-115. doi:10.5389/KSAE.2019.61.2.105.
  10. Jang, J. Y., and S. H. Kim, 2008. Globalization and the nation's health; Climate change and health. Korean Public Health Research 34(1): 38-53. doi:10.22900/kphr.2008.34.1.004.
  11. Jeon, M. G., W. H. Nam, H. J. Lee, E. M. Hong, S. A. Hwang, and S. O. Hur, 2021. Drought risk assessment for upland crops using satellite-derived evapotranspiration and soil available water capacity. Journal of the Korean Society of Hazard Mitigation 21(1): 25-33. doi:10.9798/KOSHAM.2021.21.1.25.
  12. Jung, J. H., D. H. Park, and J. H. Ahn, 2020. Drought evaluation using unstructured data: A case study for Boryeong area. Journal of Korea Water Resources Association 53(12): 1203-1210. doi:10.3741/JKWRA.2020.53.12.1203.
  13. Kim, J. S., J. Y. Lee, J. B. Lee, C. M. Song, and J. S. Park, 2016. Evaluation of agricultural water supply potential in agricultural reservoirs. Journal of the Korean Society of Agricultural Engineers 58(2): 65-71. doi:10.5389/KSAE.2016.58.2.065.
  14. Kim, S. H., and M. A. Jung, 2020. A study on the diffusion of Korean precision livestock farming using AHP method. Korea Society of Innovation 15(4): 211-239. doi:10.46251/INNOS.2020.11.15.4.211.
  15. Lee, C. W., H. J. Shin, M. S. Kwon, G. M. Lee, S. H. Nam, and M. S. Kang, 2019. An approach to drought vulnerability assessment using TOPSIS method. Journal of the Korean Association of Geographic Information Studies 22(4): 102-115. doi:10.11108/kagis.2019.22.4.102.
  16. Lee, G. H., 2019. A study on the maintenance system of water resources facilities, 61-62. Seoul: National Assembly Research Service.
  17. Lee, H. J., and M. P. Shim, 2002. Decision making for priority of water llocation during drought by analytic hierarchy process. Journal of Korea Water Resources Association 35(6): 703-714. doi:10.3741/JKWRA.2002.35.6.703.
  18. Lee, H. J., W. H. Nam, D. H. Yoon, M. W. Jang, E. M. Hong, T. G. Kim, and D. E. Kim, 2020. Estimation of water storage in small agricultural reservoir using Sentinel-2 satellite imagery. Journal of the Korean Society of Agricultural Engineers 62(6): 1-9. doi:10.5389/KSAE.2020.62.6.001.
  19. Lee, S. J., J. D. Song, T. I. Jang, D. M. Sul, and J. K. Son, 2018. A study on the derivation of the user-oriented agricultural drought assessment criteria using the AHP technique. Journal of the Korean Society of Rural Planning 24(4): 47-55. doi:10.7851/Ksrp.2018.24.4.047.
  20. Mun, Y. S., W. H. Nam, M. G. Jeon, H. J. Kim, K. K, J. C. Lee, T. H. Ha, and K. Y. L, 2020. Evaluation of regional drought vulnerability assessment based on agricultural water and reservoirs. Journal of the Korean Society of Agricultural Engineers 62(2): 97-109. doi:10.5389/KSAE.2020.62.2.097.
  21. Nam, W. H., M. J. Hayes, D. A. Wilhite, and M. D. Svoboda, 2015. Projection of temporal trends on drought characteristics using the standardized precipitation evapotranspiration index (SPEI) in South Korea. Journal of the Korean Society of Agricultural Engineer 57(1): 37-45. doi:10.5389/KSAE.2015.57.1.037.
  22. Park, J. Y., J. Y. Yoo, M. Choi, and T. W. Kim, 2011. Evaluation of drought risk in Gyeongsang-do using EDI. Journal of the Korean Society of Civil Engineers 31(3B): 243-252. doi:10.12652/Ksce.2011.31.3B.243.
  23. Park, J. Y., J. Y. Yoo, M. Lee, and T. W. Kim, 2012. Assessment of drought risk in Korea: Focused on data-based drought risk map. Journal of the Korean Society of Civil Engineers 32(4B): 203-211. doi:10.12652/Ksce.2012.32.4B.203.
  24. Ridgley, M. A., 1993. multicriteria approach to allocation water during drought. Resource Management and Optimization 9(2): 135-149.
  25. Saaty, T. L., 2008. Relative measurement and its generalization in decision making why pairwise comparisons are central in mathematics for the measurement of intangible factors the analytic hierarchy/network process. RACSAM-Revista de la Real Academia de Ciencias Exactas, Fisicas y Naturales. Serie A. Matematicas 102(2): 251-318. doi:10.1007/BF03191825.
  26. Saaty, T. L., 1980. The Analytic Hierarchy Process, New York: McGraw-Hill.
  27. Shin, J. H., W. H. Nam, N. K. Bang, H. J. Kim, H. U. An, J. W. Do, and K. Y. Lee, 2020a. Assessment of water distribution and irrigation efficiency in agricultural reservoirs using SWMM model. Journal of the Korean Society of Agricultural Engineers 62(3): 1-13. doi:10.5389/KSAE.2020.62.3.001.
  28. Shin, J. H., W. H. Nam, N. K. Bang, H. J. Kim, H. U. An, and K. Y. Lee, 2020b. Assessment of irrigation efficiency and water supply vulnerability using SWMM. Journal of the Korean Society of Agricultural Engineers 62(6): 73-83. doi:10.5389/KSAE.2020.62.6.073.
  29. Tadesse, T., J. F. Brown, and M. J. Hayes, 2005. A new approach for predicting drought-related vegetation stress: Integrating satellite, climate, and biophysical data over the US central plains. ISPRS Journal of Photogrammetry & Remote Sensing 59(4): 244-253. doi:10.1016/j.isprsjprs.2005.02.003.
  30. van Oel, P. R., E. S. Martins, A. C. Costa, N. Wanders, and H. A. van Lanen, 2018. Diagnosing drought using the downstreamness concept: The effect of reservoir networks on drought evolution. Hydrological Sciences Journal 63(7): 979-990. doi:10.1080/02626667.2018.1470632.
  31. Wilhite, D. A., and M. D. Svoboda, 1982. Drought early warning systems in the context of drought preparedness and mitigation. National Drought Mitigation Center, Lincoln, NE, USA.
  32. Wilhite, D. A., M. J. Hayes, C. Knutson, and K. H. Smith, 2000. Planning for drought: Moving from crisis to risk management. Journal of the American Water Resources Association 36(4): 697-710. doi:10.1111/j.1752-1688.2000.tb04299.x.
  33. Yoon, D. H., W. H. Nam, H. J. Lee, E. M. Hong, and T. Kim, 2020. Drought hazard assessment using MODIS-based Evaporative Stress Index (ESI) and ROC analysis. Journal of the Korean Society of Agricultural Engineers 62(3): 51-61. doi:10.5389/KSAE.2020.62.3.051.