Abstract. Topographic data, such as digital elevation models (DEMs), are essential input in flood inundation modelling. DEMs can be derived from several sources either through remote sensing techniques (spaceborne or airborne imagery) or from traditional methods (ground survey). The Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER), the Shuttle Radar Topography Mission (SRTM), the light detection and ranging (lidar), and topographic contour maps are some of the most commonly used sources of data for DEMs. These DEMs are characterized by different precision and accuracy. On the one hand, the spatial resolution of low-cost DEMs from satellite imagery, such as ASTER and SRTM, is rather coarse (around 30 to 90 m). On the other hand, the lidar technique is able to produce high-resolution DEMs (at around 1 m), but at a much higher cost. Lastly, contour mapping based on ground survey is time consuming, particularly for higher scales, and may not be possible for some remote areas. The use of these different sources of DEM obviously affects the results of flood inundation models. This paper shows and compares a number of 1-D hydraulic models developed using HEC-RAS as model code and the aforementioned sources of DEM as geometric input. To test model selection, the outcomes of the 1-D models were also compared, in terms of flood water levels, to the results of 2-D models (LISFLOOD-FP). The study was carried out on a reach of the Johor River, in Malaysia. The effect of the different sources of DEMs (and different resolutions) was investigated by considering the performance of the hydraulic models in simulating flood water levels as well as inundation maps. The outcomes of our study show that the use of different DEMs has serious implications to the results of hydraulic models. The outcomes also indicate that the loss of model accuracy due to re-sampling the highest resolution DEM (i.e. lidar 1 m) to lower resolution is much less than the loss of model accuracy due to the use of lowcost DEM that have not only a lower resolution, but also a lower quality. Lastly, to better explore the sensitivity of the 1-D hydraulic models to different DEMs, we performed an uncertainty analysis based on the GLUE methodology.
Abstract. Topographic data, such as digital elevation models (DEMs), are essential input in flood inundation modelling. DEMs can be derived from several sources either through remote sensing techniques (space-borne or air-borne imagery) or from traditional methods (ground survey). The Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER), the Shuttle Radar Topography Mission (SRTM), the Light Detection and Ranging (LiDAR), and topographic contour maps are some of the most commonly used sources of data for DEMs. These DEMs are characterized by different precision and accuracy. On the one hand, the spatial resolution of low-cost DEMs from satellite imagery, such as ASTER and SRTM, is rather coarse (around 30–90 m). On the other hand, LiDAR technique is able to produce a high resolution DEMs (around 1m), but at a much higher cost. Lastly, contour mapping based on ground survey is time consuming, particularly for higher scales, and may not be possible for some remote areas. The use of these different sources of DEM obviously affects the results of flood inundation models. This paper shows and compares a number of hydraulic models developed using HEC-RAS as model code and the aforementioned sources of DEM as geometric input. The study was carried out on a reach of the Johor River, in Malaysia. The effect of the different sources of DEMs (and different resolutions) was investigated by considering the performance of the hydraulic models in simulating flood water levels as well as inundation maps. The outcomes of our study show that the use of different DEMs has serious implications to the results of hydraulic models. The outcomes also indicates the loss of model accuracy due to re-sampling the highest resolution DEM (i.e. LiDAR 1 m) to lower resolution are much less compared to the loss of model accuracy due to the use of low-cost DEM that have not only a lower resolution, but also a lower quality. Lastly, to better explore the sensitivity of the hydraulic models to different DEMs, we performed an uncertainty analysis based on the GLUE methodology.
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