Journal of Korean Society on Water Environment (한국물환경학회지)

Korean Society on Water Environment (한국물환경학회)
권호 표지
DOI QR코드

DOI QR Code

Analysis of Impact of Climate Change on River Flows in an Agricultural Watershed Using a Semi-distributed Watershed Model STREAM

준분포형 유역모델 STREAM을 이용한 기후변화가 농업유역의 하천유량에 미치는 영향 분석

  • Jeong, Euisang (Hydrocore Ltd. Watershed Environmental Research Institute) ;
  • Cho, Hong-Lae (Hydrocore Ltd. Watershed Environmental Research Institute)
  • 정의상 ((주)하이드로코어 유역환경연구소) ;
  • 조홍래 ((주)하이드로코어 유역환경연구소)
  • Received : 2019.01.11
  • Accepted : 2019.03.19
  • Published : 2019.03.30
Download PDF
⟨ Previous Next ⟩

Abstract

Climate Change affects the hydrological cycle in agricultural watersheds through rising air temperature and changing rainfall patterns. Agricultural watersheds in Korea are characterized by extensive paddy fields and intensive water use, a resource that is under stress from the changing climate. This study analyzed the effects of climate change on river flows for Geum Cheon and Eun-San Choen watershed using STREAM, a semi-distributed watershed model. In order to evaluate the performance and improve the reliability of the model, calibration and validation of the model was done for one flow observation point and three reservoir water storage ratio points. Climate change scenarios were based on RCP data provided by the Korea Meteorological Administration (KMA) and bias corrections were done using the Quantile Mapping method to minimize the uncertainties in the results produced by the climate model to the local scale. Because of water mass-balance, evapotranspiration tended to increase steadily with an increase in air temperature, while the increase in RCP 8.5 scenario resulted in higher RCP 4.5 scenario. The increase in evapotranspiration led to a decrease in the river flow, particularly the decrease in the surface runoff. In the paddy agricultural watershed, irrigation water demand is expected to increase despite an increase in rainfall owing to the high evapotranspiration rates occasioned by climate change.

Keywords

SJBJB8_2019_v35n2_131_f0001.png 이미지

Fig. 1. Study area.

SJBJB8_2019_v35n2_131_f0002.png 이미지

Fig. 2. Representation of a watershed using square grid cells and link-node structures in STREAM (Cho et al., 2015).

SJBJB8_2019_v35n2_131_f0003.png 이미지

Fig. 3. Diagram for water flows in the rice paddy field.

SJBJB8_2019_v35n2_131_f0004.png 이미지

Fig. 4. Monitoring stations for flow-rate and reservoir water storage ratio.

SJBJB8_2019_v35n2_131_f0005.png 이미지

Fig. 5. Hydrographs and scatter plots of the observed and the simulated daily flow rates at the SeokDong Station.

SJBJB8_2019_v35n2_131_f0006.png 이미지

Fig. 6. Hydrographs and scatter plots of the observed and the simulated daily flow rates at the Oksan Reservoir Station

SJBJB8_2019_v35n2_131_f0007.png 이미지

Fig. 7. Hydrographs and scatter plots of the observed and the simulated daily flow rates at the Sangcheon Reservoir Station

SJBJB8_2019_v35n2_131_f0008.png 이미지

Fig. 8. Hydrographs and scatter plots of the observed and the simulated daily flow rates at the Bansan Reservoir Station

SJBJB8_2019_v35n2_131_f0009.png 이미지

Fig. 9. Boxplot of 30-year annual rainfall rate for the RCP 4.5 (a) and the RCP 8.5 (b) scenarios at the Buyue Station.

SJBJB8_2019_v35n2_131_f0010.png 이미지

Fig. 10. 30-year monthly rainfall rate for the RCP 4.5 (a) and the RCP 8.5 (b) scenarios and the monthly-observed rainfall rate during the period 1976-2005 at the Buyue Station.

SJBJB8_2019_v35n2_131_f0011.png 이미지

Fig 11. Boxplot of 30-year annual average air temperature for the RCP 4.5 (a) and the RCP 8.5 (b) scenarios at the Buyue Station.

SJBJB8_2019_v35n2_131_f0012.png 이미지

Fig. 12. 30-year monthly average air temperature for the RCP 4.5 (a) and the RCP 8.5 (b) scenarios and observed monthly average air temperature during 1976-2005 at the Buyue Station.

SJBJB8_2019_v35n2_131_f0013.png 이미지

Fig. 14. Surface runoff, interflow, and aquifer discharge from watershed for observation data and RCP 4.5 and 8.5 scenarios.

SJBJB8_2019_v35n2_131_f0014.png 이미지

Fig. 13. Evapotranspiration and discharge to rainfall for observation data and RCP 4.5 and 8.5 scenarios

Table 1. Land use within the study area

SJBJB8_2019_v35n2_131_t0001.png 이미지

Table 2. The recommended water depths for paddy fields

SJBJB8_2019_v35n2_131_t0002.png 이미지

Table 3. General performance ratings for recommended statistics for a daily time step (Moriasi et al., 2015)

SJBJB8_2019_v35n2_131_t0003.png 이미지

Table 4. Model statistical performance measures evaluated based on daily river flows at the monitoring stations for calibration and validation periods

SJBJB8_2019_v35n2_131_t0004.png 이미지

Table 5. Model statistical performance measures evaluated based on daily water storage ratio at the reservoir monitoring station

SJBJB8_2019_v35n2_131_t0005.png 이미지

Table 6. Selected model parameters and values for stream flow and water quality calibration

SJBJB8_2019_v35n2_131_t0006.png 이미지

Table 7. Water mass balance of Geum-Cheon and En-San-Cheon Watershed for RCP 4.5 and RCP 8.5 scenarios

SJBJB8_2019_v35n2_131_t0007.png 이미지

Table 8. Water mass balance of paddy fields in the Geum-Cheon and En-San-Cheon Watershed for RCP 4.5 and RCP 8.5 scenarios

SJBJB8_2019_v35n2_131_t0008.png 이미지

References

  1. Ahn, J. M., Im, T. H., Lee, I. J., and Cheon, S. U. (2014). Assessment of future river environment considering climate change and basin runoff characteristics, Journal of Korea Water Resources Association, 47(3), 269-283. [Korean Literature] https://doi.org/10.3741/JKWRA.2014.47.3.269
  2. Ahn, S. R., Park, M., J., Park, G. A., and Kim, S. J. (2009). Assessing future climate change impact on hydrologic components of Gyeongancheon watershed, Journal of Korea Water Resources Association, 42(1), 33-50. [Korean Literature] https://doi.org/10.3741/JKWRA.2009.42.1.33
  3. Bang, J. H., Lee, S. H., Choi, J. Y., and Lee, S. H. (2017). Evaluation of reservoir drought response capability considering precipitation of non-irrigation period using RCP scenario, Journal of the Korean Society of Agricultural Engineers, 59(1), 31-43. [Korean Literature] https://doi.org/10.5389/KSAE.2017.59.1.031
  4. Brown, I. M., Poggio, L., and Gimona, A. (2011). Climate change, drought risk and land capability for agriculture: implications for land use in Scotland, Regional Environmental Change, 11(3), 503-518. https://doi.org/10.1007/s10113-010-0163-z
  5. Chae, Y. R., Lee, C. H., and Hope, C. (2017). Analyzing damage costs of climate change in Korea applying IPCC scenario system, Korea Environmental Institute. [Korean Literature]
  6. Cho, H. L., Jeong, E., and Koo, B. K. (2015). Development of a hybrid watershed model STREAM: model structures and theories, Journal of Korean Society on Water Environment, 31(5), 491-506. [Korean Literature] https://doi.org/10.15681/KSWE.2015.31.5.491
  7. Chung, S. O. (2009). Climate change impacts paddy irrigation requirement in the Nakdong river basin, Journal of the Korean Society of Agricultural Engineers, 51(2), 35-41. [Korean Literature] https://doi.org/10.5389/KSAE.2009.51.2.035
  8. Han River Flood Control Office (HRFCO). (2018). Water Resources Management Information System (WAMIS), http://www.wamis.go.kr (accessed Dec. 2018)
  9. Intergovernmental Panel on Climate Change (IPCC). (2014). Climate Change 2014: Synthesis Report, Contribution of Working Groups I, II and III to the Fifth Assessment Report of the Intergovernmental Panel on Climate Change, IPCC, 1-151.
  10. Jeon, J. H., Yoon, C. G., Donigian, A. S., and Jung, K. W. (2007). Development of the HSPF-Paddy model to estimate watershed pollutant loads in paddy farming regions, Agricultural Water Management, 90, 75-86. https://doi.org/10.1016/j.agwat.2007.02.006
  11. Jung I. W., Lee, B. J., Jun. T. H., and Bae, D. H. (2008). Hydrological model response to climate change impact assessments on water resources, Journal of Korea Water Resources Association, 41(9), 907-917. [Korean Literature] https://doi.org/10.3741/JKWRA.2008.41.9.907
  12. Jung, H. C. and Suh, M, S. (2015). Correction of mean and extreme temperature simulation over South Korea using a trend-preserving bias correction method, Atmosphere Korean Meteorological Society, 25(2), 205-219. [Korean Literature]
  13. Jung, I. W., Bae, D. H., and Kim, G. (2011). Recent trends of mean and extreme precipitation in Korea, International Journal of Climatology, 31, 359-370. https://doi.org/10.1002/joc.2068
  14. Kim, Y. J. and Jung, E. S. (2011). Water resources: Their current state and assessment, Korea Environment Institute. [Korean Literature]
  15. Korea Meteorological Administration (KMA). (2018). 2017 abnormal climate report, 11-1360000000705-01, Korea Meteorological Administration, 1-218. [Korean Literature]
  16. Maeng, S. J., Jeong, J. H., Kim, H. S., Muhammad, A., and Hwang, M. H. (2015). Runoff analysis using precipitation by climate change scenario and observed precipitation, Crisis and Emergency Management, 11(2), 241-259. [Korean Literature]
  17. Maurer, E. P. and Pierce, D. (2014). Bias correction can modify climate model simulated precipitation changes without adverse effect on the ensemble mean, Hydrology and Earth System Sciences, 18, 915-925. https://doi.org/10.5194/hess-18-915-2014
  18. Moriasi, D. N., Gitau, M. W., and Daggupati, P. P. (2015) Hydrologic and water quality models: Performance measures and evaluation criteria, American Society of Agricultural and Biological Engineers, 58(6), 1763-1785.
  19. Moriasi, D. N., Gitau, M. W., and Daggupati, P. P. (2015) Hydrologic and water quality models: Performance measures and evaluation criteria, American Society of Agricultural and Biological Engineers, 58(6), 1763-1785.
  20. Myeong, S. (2014). Agriculture under UNFCCC, and its policy implications, Journal of Climate Change Research, 5(4), 313-321. [Korean Literature] https://doi.org/10.15531/ksccr.2014.5.4.313
  21. Nam, W. H., Hong, E. M., Kim, T., and Choi, J. Y. (2014). Projection of future water supply sustainability in agricultural reservoirs under RCP climate change scenarios, Journal of the Korean Society of Agricultural Engineers, 56(4), 59-68. [Korean Literature] https://doi.org/10.5389/KSAE.2014.56.4.059
  22. National Institute of Meteorological Sciences. (2012). Global climate change report for response to IPCC 5th assessment report 2012, National Institute of Meteorological Sciences. [Korean Literature]
  23. Nosrati, K. (2011). The effects of hydrological drought on water quality, IAHS-AISH Publication, 348, 51-56.
  24. Park, J. Y., Park, M. J., Ahn, S. R., and Kim, S. J. (2009). Watershed modeling for assessing climate change impact on stream water quality of Chungju dam watershed, Journal of Korea Water Resources Association, 42(10), 877-889. [Korean Literature] https://doi.org/10.3741/JKWRA.2009.42.10.877
  25. Park, J., Kang, M. S., and Song, I. (2012). Bias correction of RCP-based future extreme precipitation using a quantile mapping method; for 20-weather stations for South Korea, Journal of the Korean Society of Agricultural Engineers, 54(6), 133-142. [Korean Literature] https://doi.org/10.5389/KSAE.2012.54.6.133
  26. Rural Development Administration (RDA). (2018). Nongsaro, http://www.nongsaro.go.kr, (accessed Dec. 2018)
  27. Rural Research Institute. (2014). Development of improved farming methods for agricultural non-point source pollution reduction, Rural Research Institute. [Korean Literature]
  28. Ryu, J., Park, Y. S., Han, M., Ahn, K. H., Kum, D., Lim, K. J., and Park, B. K. (2014). Enhancement of land load estimation method in TMDLs for considering of climate change scenarios, Journal of Korean Society on Water Environment, 30(2), 212-219. [Korean Literature] https://doi.org/10.15681/KSWE.2014.30.2.212
  29. Ryu. J. H., Kang, M. S., Song, I., Park, J., Song, J. H., Jun, S. M., and Kim, K. (2015). Estimation of design flood for the Gyeryong reservoir watershed based on RCP scenarios, Journal of the Korean Society of Agricultural Engineers, 57(1), 59-68. [Korean Literature] https://doi.org/10.5389/KSAE.2015.57.1.059
  30. Sakaguchi, A., Eguchi, S., Kato, T., Kasuya, M., Ono, K., Miyata, A., and Tase, N. (2014). Development and evaluation of paddy module for improving hydrological simulation in SWAT, Agricultural Water Management, 137, 116-122. https://doi.org/10.1016/j.agwat.2014.01.009
  31. Song, J. H., Kang, M. S., Song, I. H., Hwang, S. H., Park J., and Ahn, J. H. (2013). Surface drainge simulation model for irrigation districts composed of paddy and protected cultivation, Journal of the Korean Society of Agricultural Engineers, 55(3), 63-73. [Korean Literature] https://doi.org/10.5389/KSAE.2013.55.3.063
  32. Yi, H. S., Kim, D. S., Hwang, M. H., and An, K. G. (2016). Assessment of runoff and water temperature variations under RCP climate change scenario in Yongdam dam watershed, South Korea, Journal of Korean Society on Water Environment, 32(2), 173-182. [Korean Literature] https://doi.org/10.15681/KSWE.2016.32.2.173
  33. Yun, D. K., Chung, S. O., and Kim, S. J. (2011). Climate change impacts on paddy water requirement, Journal of the Korean Society of Agricultural Engineers, 53(4), 39-47 [Korean Literature] https://doi.org/10.5389/KSAE.2011.53.4.037