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Optimizing the Assessment of Runoff with HEC-HMS Model Using Spatial Evapotranspiration by SEBS model

Document Type : Research Paper

Authors

1 hormozgan university

2 University of Hormozgan

3 Researcher, Fars Agricultural & Natural Resources Research & Education Center

4 Soil Conservation and Watershed Management Research Department, Fars Agricultural and Natural Resources Research and Education Center, Agricultural Research, Education and Extension Organization (AREEO), Shiraz, Iran

Abstract

Limitations of physical and experimental methods for estimating the evapotranspiration have been rationalized the employment of remote sensing technology to solve the energy balance equation in recent years. In this study, in order to investigate the evapotranspiration factor in the application of the HEC-HMS model and to optimize the flood estimation, using Landsat 8 Satellite Images (nine images) and the meteorological data related to the Kelestan Station and the SEBS Evapotranspiration Model for the period 2015-2017, ET values were calculated in the region of Kelestan Located in the Northwest of Shiraz, and the results were compared to the FAO Penman-Monteith equation to verify the accuracy of this model in the region of Kolding with water body. Evaporation in HEC-HMS including the direct evaporation of water, evaporation from soil surface, and transpiration of plants was estimated as an average elevation. In this study, we attempted to replace the actual evapotranspiration in the HEC-HMS model, The amount of runoff from the precipitation is calculated more accurately. The results showed that after scrutinizing the ET input, the simulated flood correlation with the measured flood was increased with R2 from 92 to 99%, and RMSE from 0.14 to 0.01, respectively. The results also indicated that the use of Landsat 8 Satellite Images and SEBS model is a suitable tool for estimating actual evapotranspiration in mountainous and field areas in hydrological studies. This research is for the performance of SEBS in determining the spatial and temporal distribution of evapotranspiration in a mountainous and hydrological area. Because the calculation of ET in hydrological models can improve the results and increase the accuracy of these models.

Keywords

References
  1. Aghdasi, 2010. Crop water requirement assessment and annual planning of water allocation. University of Twente, Faculty of Geo-Information and Earth Observation (ITC), 72 pages.
  2. Bansouleh, V.F., K. Khalil Valizadeh and M. Pirnazar. 2015. Land surface temperature retrieval from Landsat 8 TIRS: comparison between split window algorithm and SEBAL method. Third International Conference on Remote Sensing and Geoinformation of the Environment, 953503-953503-953512.
  3. Bastiaanssen, W., M. Menenti, R. Feddes and A. Holtslag. 1998. A remote sensing Surface Energy Balance Algorithm For Land (SEBAL). Journal of Hydrology, 212: 198-212.
  4. Bastiaanssen, W., E. Noordman, H. Pelgrum, G. Davids, B. Thoreson and R. Allen. 2005. SEBAL model with remotely sensed data to improve water-resources management under actual field conditions. Journal of Irrigation and Drainage Engineering, 131(1): 85-93.
  5. Bastiaanssen, W.G., M.U.D. Ahmad and Y. Chemin. 2002. Satellite surveillance of evaporative depletion across the Indus Basin. Water Resources Research, 38(12): 25-39.
  6. Brooks, K., H. Gregersen, E. Berglund and M. Tayaa. 1982. Economic evaluation of watershed projects‐an overview methodology and application. Journal of the American Water Resources Association, 18(2): 245-250.
  7. Chang, J.X., T. Bai, Q. Huang and D.W. Yang. 2013. Optimization of water resources utilization by PSO-GA. Water Resources Management, 27(10): 3525-3540.
  8. Chen, X., Z. Su, Y. Ma, K. Yang, J. Wen and Y. Zhang. 2013. An improvement of roughness height parameterization of the Surface Energy Balance System (SEBS) over the Tibetan Plateau. Journal of Applied Meteorology and Climatology, 52(3): 607-622.
  9. Dastorani, M.T., R. Khodaparast, A. Talebi, M. Vafakhah and J. Dashti. 2011. Determination of the ability of HEC-HMS model components in rainfall-runoff simulation. Research Journal of Environmental Sciences, 5(10): 790-800.
  10. Doan, J. 2000. Geospatial hydrologic modeling extension HEC-GeoHMS user’s manual, version 1.0. US Army Corps of Engineers Hydrologic Engineering Center, Davis, California, USA.
  11. Enko, T. 2009. Estimation of evapotranspiration from satellite remote sensing and meteorological data over the Fogera Floodplain, Ethiopia. MSc Thesis, ITC, Enschede, The Netherlands, 156 pages.
  12. Gibson, L., C. Jarmain, Z. Su, and F. Eckardt. 2013. Estimating evapotranspiration using remote sensing and the surface energy balance system, a South African perspective. Energies, 39(4): 477-484.
  13. Gokmen, M., Z. Vekerdy, A. Verhoef, W. Verhoef, O. Batelaan and C. Van der Tol. 2012. Integration of soil moisture in SEBS for improving evapotranspiration estimation under water stress conditions. Remote Sensing of Environment, 121: 261-274.
  14. Gowda, P.H., T.A. Howell, G. Paul, P.D. Colaizzi, T.H. Marek, B. Su and K.S. Copeland. 2013. Deriving hourly evapotranspiration rates with SEBS: a lysimetric evaluation. Vadose Zone Journal, 12: 25-37.
  15. Han, H. and L. Yang. 2004. Evaluation of regional scale evapotranspiration using SEBS model in western Chinese Loess Plateau. International Geoscience and Remote Sensing Symposium, 2: 1339-1342.
  16. Joo, J., T. Kjeldsen, H.J. Kim and H. Lee. 2014. A comparison of two event-based flood models (ReFH-rainfall runoff model and HEC-HMS) at two Korean catchments, Bukil and Jeungpyeong. KSCE Journal of Civil Engineering, 18(1): 330-343.
  17. Kustas, W.P., M.S. Moran, K.S. Humes, D.I. Stannard, P. Pinter, L.E. Hipps, E. Swiatek and D.C. Goodrich. 1994. Surface energy balance estimates at local and regional scales using optical remote sensing from an aircraft platform and atmospheric data collected over semiarid rangelands. Water Resources Research, 30(5): 1241-1259.
  18. Kamanbedast, A. and Y. Esfandiar. 2011. Investigation and study of morphological changing of rivers using HEC-GeoRAS and Mike 11 Software. World Applied Sciences Journal, 13(5): 1253-1258.
  19. Kustas, W.P. and J.M. Norman. 1999. Evaluation of soil and vegetation heat flux predictions using a simple two-source model with radiometric temperatures for partial canopy cover. Agricultural and Forest Meteorology, 94(1): 13-29.
  20. Kamali, B., S.J. Mousavi and K. Abbaspour. 2013. Automatic calibration of HEC‐HMS using single‐objective and multi‐objective PSO algorithms. Hydrological Processes, 27(26): 4028-4042.
  21. Knebl, M., Z.L. Yang, K. Hutchison and D. Maidment. 2005. Regional scale flood modeling using NEXRAD rainfall, GIS and HEC-HMS/RAS, a case study for the San Antonio River Basin summer 2002 storm event. Journal of Environmental Management, 75(4): 325-336.
  22. Lu, J., Z.L. Li, R. Tang, B.H. Tang, H. Wu, F. Yang, J. Labed and G. Zhou. 2013. Evaluating the SEBS‐estimated evaporative fraction from MODIS data for a complex underlying surface. Hydrological Processes, 27(22): 3139-3149.
  23. Mahour, M., A. Stein, A. Sharifi and V. Tolpekin. 2015. Integrating super resolution mapping and SEBS modeling for evapotranspiration mapping at the field scale. Precision Agriculture, 16(5): 571-586.
  24. McCabe, M.F. and E.F. Wood. 2006. Scale influences on the remote estimation of evapotranspiration using multiple satellite sensors. Remote Sensing of Environment, 105(4): 271-285.
  25. Pakparvar, M., W. Cornelis, L. Pereira, D. Gabriels, H. Hosseinimarandi, M. Edraki and S. Kowsar. 2014. Remote sensing estimation of actual evapotranspiration and crop coefficients for a multiple land use arid landscape of southern Iran with limited available data. Journal of Hydroinformatics, 16(6): 1441-1460.
  26. Parlange, M.B., W.E. Eichinger and J.D. Albertson. 1995. Regional scale evaporation and the atmospheric boundary layer. Reviews of Geophysics, 33(1): 99-124.
  27. Perrin, C. and L. Oudin. 2007. Impact of stream flow data on the efficiency and the parameters of rainfall–runoff models. Hydrological Sciences Journal, 52: 25-38.
  28. Roerink, G., Z. Su and M. Menenti. 2000. S-SEBI: a simple remote sensing algorithm to estimate the surface energy balance. Physics and Chemistry of the Earth, Part B: Hydrology, Oceans and Atmosphere, 25(2): 147-157.
  29. Su, Z. 2002. The Surface Energy Balance System (SEBS) for estimation of turbulent heat fluxes. Hydrology and Earth System Sciences, 6(1): 85-99.
  30. Su, Z., A. Yacob, J. Wen, G. Roerink, Y. He, B. Gao, H. Boogaard and C. van Diepen. 2003. Assessing relative soil moisture with remote sensing data: theory, experimental validation and application to drought monitoring over the North China Plain. Physics and Chemistry of the Earth, 28(1): 89-101.
  31. Singh, B. and D. Singh. 1995. Agronomic and physiological responses of sorghum, maize and pearl millet to irrigation. Field Crops Research, 42(2): 57-67.
  32. Singh, R. and G. Senay. 2015. Comparison of four different energy balance models for estimating evapotranspiration in the Midwestern United States. Water, 8(1): 9-24.
  33. Tabari, H., M. Grismer and S. Trajkovic. 2013. Comparative analysis of 31 reference evapotranspiration methods under humid conditions. Irrigation Science, 31(2): 107-117.
  34. Tang, R. and Z. Li. 2017. An improved constant evaporative fraction method for estimating daily evapotranspiration from remotely sensed instantaneous observations. Geophysical Research Letters, 44(5): 2319-2326.
  35. Tokar, A.S. and M. Markus. 2000. Precipitation-runoff modeling using artificial neural networks and conceptual models. Journal of Hydrologic Engineering, 5(2): 156-161.
  36. van der Kwast, J., W. Timmermans, A. Gieske, Z. Su, A. Olioso, L. Jia, J. Elbers, D. Karssenberg, and S. de Jong. 2009. Evaluation of the Surface Energy Balance System (SEBS) applied to ASTER imagery with flux-measurements at the SPARC 2004 site (Barrax, Spain). Hydrology and Earth System Sciences, 13(7): 1337-1347.
  37. Wagle, P., N. Bhattarai, P. Gowda and V. Kakani. 2017. Performance of five surface energy balance models for estimating daily evapotranspiration in high biomass sorghum. ISPRS Journal of Photogrammetry and Remote Sensing, 128: 192-20.
  38. Wildhaber, M.L., C.K. Wikle, E.H. Moran, C.J. Anderson, K.J. Franz and R. Dey. 2015. Hierarchical stochastic modelling of large river ecosystems and fish growth across spatio-temporal scales and climate models: the Missouri River endangered pallid sturgeon example. Geological Society of London Special Publications, 408: 119-145.
Watershed Engineering and Management
Volume 13, Issue 1
April 2021
Pages 81-97
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