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Comparison and Evaluation of Flood Simulation Under Different Scenarios in Kashkan River and Missouri Basins Using Hec-Ras and Lisflood-Fp, and Development of a Method for Downscaling of Flood Discharge

Ahmadi, Mohammad | 2021

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  1. Type of Document: M.Sc. Thesis
  2. Language: Farsi
  3. Document No: 54060 (09)
  4. University: Sharif University of Technology
  5. Department: Civil Engineering
  6. Advisor(s): Moghim, Sanaz
  7. Abstract:
  8. This study consists of two parts. In the first part, the performance of the LISFLOOD-FP model, which is raster-based, and the HEC-RAS model, are compared and evaluated. This work studied different scenarios under various digital models in two study areas, the Kashkan study basin with mountainous topography and the basin in Nebraska, which has a plain surface. The flood events are among the most severe floods in both study areas that occurred in March and April 2019. This study showed that in mountain topography, the performance of both models is good even with the 30 m high digital models. Although two models perform well, in the Nebraska basin, the performance of the two models in the 30-meter digital elevation models decreased, and the sensitivity of two models increased so that under the errors resulting from the SRTM digital elevation model with a 30-meter resolution, the model lost its stability. Results showed that the computational speed in the LISLFOOD-FP model was several times faster than the HEC-RAS model. In addition to the digital elevation model, which is the most critical parameter in LISFLOOD-FP and HEC-RAS, mesh dimensions are also crucial in HEC-RAS.In the second part of this study, the downscaling of flood discharge from 3-hour scale to an hourly one at the Poldakhtar hydrometric station was discussed. A probability-based method for statistical downscaling of flood discharge was proposed. In this method, the collected data of flood events from 2009 to 2019 were divided into two parts: calibration and validation. Based on the calibration data that are divided into two categories including rising limb and falling limb, the best probability density functions using two goodness-of-fit tests were selected. Then by applying the increasing/decreasing conditions for sampling, we sampled 200 times for each event and calculated the error of the estimated discharge relative to the observed ones for all 200 sets. A set of samples with the smallest error is the best-downscaled discharge set. Results showed that this method has high accuracy in downscaling of flood discharge. The downscaled discharge can follow the changes in the hydrograph trend of flood events well
  9. Keywords:
  10. Random Sampling ; Remote Sensing ; Statistical Downscaling ; Discharge ; Flood Zoning ; Satellite Imagery ; Hydrologic Engineering Center-River Analysis System (HEC-RAS)Model ; Probabilistic Methods ; Nebraska Watershed (United State of American) ; Kadhkan Watershed (Lorestan) ; LISFLOOD-FP Model

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