Atmosphere (대기)

Korean Meteorological Society (한국기상학회)
권호 표지
DOI QR코드

DOI QR Code

Evaluation of High-Resolution Hydrologic Components Based on TOPLATS Land Surface Model

TOPLATS 지표해석모형 기반의 고해상도 수문성분 평가

  • Lee, Byong-Ju (Applied Meteorological Research Lab., National Institute of Meteorological Research) ;
  • Choi, Young-Jean (Applied Meteorological Research Lab., National Institute of Meteorological Research)
  • 이병주 (국립기상연구소 응용기상연구과) ;
  • 최영진 (국립기상연구소 응용기상연구과)
  • Received : 2012.06.18
  • Accepted : 2012.09.02
  • Published : 2012.09.30
Download PDF
⟨ Previous Next ⟩

Abstract

High spatio-temporal resolution hydrologic components can give important information to monitor natural disaster. The objective of this study is to create high spatial-temporal resolution gridded hydrologic components using TOPLATS distributed land surface model and evaluate their accuracy. For this, Andong dam basin is selected as study area and TOPLATS model is constructed to create hourly simulated values in every $1{\times}1km^2$ cell size. The observed inflow at Andong dam and soil moisture at Andong AWS site are collected to directly evaluate the simulated one. RMSEs of monthly simulated flow for calibration (2003~2006) and verification (2007~2009) periods show 36.87 mm and 32.41 mm, respectively. The hourly simulated soil moisture in the cell located Andong observation site for 2009 is well fitted with observed one at -50 cm. From this results, the cell based hydrologic components using TOPLATS distributed land surface model show to reasonably represent the real hydrologic condition in the field. Therefore the model driven hydrologic information can be used to analyze local water balance and monitor natural disaster caused by the severe weather.

Keywords

References

  1. 강전호, 서명석, 2011: 지면경계조건이 UM을 이용한 동아시아 여름철 단기예보에 미치는 영향, 대기, 21(4), 415-427.
  2. 김형진, 정일웅, 조민수, 2005: 대기 대순환 모형과 지면 모형의 접합에 관하여, 한국기상학회지, 41(6), 1137-1149.
  3. 하경자, 김정우, 김기영, 문자연, 1998: 다층 지면과정 모형 접합에 대한 AGCM의 민감도 실험, 한국기상학회지, 34(4), 630-642.
  4. Betts, A., F. Chen, K. Mitchell, and Z. Janjic, 1997: Assessment of the land surface and boundary layer models in two operational versions of the NCEP Eta model using FIFE data, Mon. Weather Rev., 125, 2896-2916. https://doi.org/10.1175/1520-0493(1997)125<2896:AOTLSA>2.0.CO;2
  5. Beven, K., 1986: Runoff production and flood frequency in catchments of order n: an alternative approach. In V. K. Gupta, I. Rodriquez-Iturbe, and E. F. Wood (Eds.), Scale Problems in Hydrology, Reidel, Dordrecht, 107-131.
  6. Beven, K., and M. J. Kirby, 1979: A physically based, variable contributing area model of basin hydrology. Hydrological Sciences Bulletin, 24(1), 43-69. https://doi.org/10.1080/02626667909491834
  7. Burnash, R. J. C., R. L. Ferral, R. A. McGuire, 1973: A generalized streamflow simulation system: Conceptual models for digital computers, Technical Report, Joint Fed.-State River Forecast Cent., U.S. NWS and Calif. Dep. of Water Resour., Sacramento, Calif.
  8. Chen, F., Z. Janjic, and K. Mitchell, 1997: Impact of atmospheric surface layer parameterizations in the new land-surface scheme of the NCEP mesoscale Eta model, Boundary Layer Meteorology, 85, 391-421. https://doi.org/10.1023/A:1000531001463
  9. Crow, W. T., D. Ryu, and J. S. Famiglietti, 2005: Upscaling of field-scale soil moisture measurements using distributed land surface modeling, Advances in Water Resour., 28, 1-14. https://doi.org/10.1016/j.advwatres.2004.10.004
  10. Doms, G., and U. Schättler, 1999: The non-hydrostatic limited-area model LM(Lokal-Modell) of the DWD. Deutscher Wetterdienst, Technical Report, 180.
  11. Ek, M. B., K. E. Mitchell, Y. Lin, E. Rogers, P. Grunmann, V. Koren, G. Gayno, and J. D. Tarpley, 2003: Implementation of Noah land surface model advances in the National Centers for Environmental Prediction operational mesoscale Eta model, J. Geophys. Res., 108(D22), 8851. https://doi.org/10.1029/2002JD003296
  12. Famiglietti, J. S., and E. F. Wood, 1994: Application of multiscale water and energy balance models on a tallgrass prairie. Water Resour. Res., 30(11), 3061-3078. https://doi.org/10.1029/94WR01498
  13. Koster, R., and M. Suarez, 1994: The components of a SVAT scheme and their effects on a GCM's hydrological cycle, Advances in Water Resour., 17, 61-78. https://doi.org/10.1016/0309-1708(94)90024-8
  14. Koster, R., M., Suarez, and M. Heiser, 2000: Variance and predictability of precipitation at seasonal-to-interannual timescales, J. Hydrometeorology, 1, 26-46. https://doi.org/10.1175/1525-7541(2000)001<0026:VAPOPA>2.0.CO;2
  15. Liang, X., D. P. Lettenmaier, E. F. Wood, and S. J. Burges, 1994: A simple hydrologically based model of land surface water and energy fluxes for GCMs, J. Geophys Res., 99, 415-428
  16. Lim, Y. -J., K. -Y., Byun, T. -Y., Lee, H. Kwon, J. Hong, and J. Kim, 2012: A land data assimilation system using the MODIS-drived land data and its application to numerical weather prediction in East Asia, Asia-Pacific J. Atmos. Sci., 48(1), 83-95. https://doi.org/10.1007/s13143-012-0008-4
  17. Milly, P. C. D., 1986: An event based simulation model of moisture and energy fluxes at a bare soil surface, Water Resour. Res., 22, 1680-1692. https://doi.org/10.1029/WR022i012p01680
  18. Monteith, J. L., 1965: Evaporation and environment, in: Sympos. The state and movement of water in living organism, edited by: Fogy, G. T., Cambridge (Univ Press), 205-234.
  19. Peters-Lidard, C. D., F. Pan, and E. F. Wood, 2001: A reexamination of modeled and measured soil moisture spatial variability and its implications for land surface modeling, Advances in Water Resour., 24, 1069-1083. https://doi.org/10.1016/S0309-1708(01)00035-5
  20. Rawls, W. J. D. Gimenez, and R. Grossman, 1998: Use of soil texture, bulk density, and the slope of the water retention curve to predict saturated hydraulic conductivity. Trans. ASAE, 41(4), 983-988. https://doi.org/10.13031/2013.17270
  21. Rawls, W. J., D. L. Brakensiek, and K. E. Saxton, 1982: Estimation of soil water properties. Trans. ASAE, 25(5), 1316-1320. https://doi.org/10.13031/2013.33720
  22. Seuffert, G., P. Gross, and C. Simmer, 2002: The influence of hydrologic modeling on the predicted local weather: two-way coupling of a mesoscale weather prediction model and a land surface hydrologic model, J. Hydrometeorology, 3, 505-523. https://doi.org/10.1175/1525-7541(2002)003<0505:TIOHMO>2.0.CO;2
  23. Sivapalan, M., Beven, K., and Wood, E. F., 1987: On hydrologic similarity. 2. A scaled model of storm turnoff production, Water Resour. Res., 23, 2266-2278. https://doi.org/10.1029/WR023i012p02266
  24. Wood, E. F., D. P. lettenmaier, X. Liang, B. Nijssen, and S. W. Wetzel, 1997: Hydrological modeling of continental-scale basins, Annu. Rev. Earth Planet. Sci., 25, 279-300. https://doi.org/10.1146/annurev.earth.25.1.279

Cited by

  1. A Study on Statistical Methods for the Development of Flash Flood Index vol.15, pp.6, 2015, https://doi.org/10.9798/KOSHAM.2015.15.6.189
  2. Gridded Flash Flood Risk Index Coupling Statistical Approaches and TOPLATS Land Surface Model for Mountainous Areas vol.11, pp.3, 2019, https://doi.org/10.3390/w11030504