Semester Project Final Report Logan River Flood Plain Analysis Using ArcGIS, HEC-GeoRAS, and HEC-RAS Kedric Curtis, Josh Hogge, Jordan Jarrett, Jared Justensen May 6, 2016 CEE 6190 GIS for Civil Engineers Dr. Jeff Horsburgh
Logan River Floodplain Analysis Using ArcGIS, HEC-GeoRAS, and HEC-RAS Kedric Curtis a, Josh Hogge a, Jordan Jarrett a, Jared Justensen a a Utah Water Research Laboratory (curtiskw@gmail.com, joshua.r.hogge@aggiemail.usu.edu, jordan.c.jarrett@gmail.com, jared.justensen@aggiemail.usu.edu) Abstract: Mapping of river floodplains is used by many organizations to determine if areas near a river are at risk of flooding. Motivated by recent flooding this study was performed to map the floodplains of the Logan River between First Dam and Center Street using ArcGIS. This was accomplished by creating river geometry in ArcMap, running a hydraulics model using the Hydrologic Engineering Center s River Analysis System (HEC-RAS), analyzing the results, and creating floodplain maps in ArcMap. It was determined that many homes and a preschool would be inundated in the event of a 3500 cfs flood. Keywords: floodplain; ArcGIS; HEC-RAS; HEC-GeoRAS; LIDAR; 1 INTRODUCTION The Logan River flows through a highly populated area in the middle of Logan, Utah surrounded by schools, homes, and businesses. Due to recent flooding in 2011, where significant damage was caused, questions have been asked about the areas surrounding the river and the flood danger risk associated with them. The potential for loss of property and life in the areas near the river is a problem that needs to be examined. According to the Utah Natural Hazards Handbook, each year more deaths occur due to flooding than from any other weather related hazard. The flood risk for many areas of Utah are undetermined and the absence of information can lead local officials to assume that no flood risk exists. The lack of information can lead officials to not participation in flood insurance. This results in much of Utah s flood loss being unreported. Evidence of this can be seen in the nearly thirty-year span, between January 1978 and October 2008, the National Flood Insurance Program (NFIP) paid only a little over 5.3 million dollars to 797 claims in Utah (Utah Natural Hazards Handbook 2008). Although loss of life is the worst result, damage to property can be significant in the event of a flood. Flood risk is important to many organizations and is particularly important for local governments to make decisions and to be aware of the areas at risk during a flood event for flood mitigation. By evaluating different flood plains for the Logan River, it was determined which areas of surrounding homes and buildings are most at risk for flood damage. The objective of this project was to develop floodplain maps for a section of the Logan River between First Dam and Center Street as seen in Figure 1. The study was performed using the functionality of ArcGIS to improve the floodplain results obtained using only the Hydrologic Engineering Center s River Analysis System (HEC-RAS). This will be done by mapping the extents of the Logan River floodplain at different flood flow rates. Four floodplains were mapped associated with flow rates of 1000, 2000, 2500, and 3500 cfs, which includes the historical peak flow rate of approximately 2500 cfs. LIDAR data for the study area were obtained and used throughout the study to develop, analyze and create the floodplain maps. The software used in this study for floodplain mapping was ESRI s ArcMap and the HEC-GeoRAS extension. The US Army Corps of Engineers (USACE) has developed a GIS extension for ArcMap called HEC-GeoRAS, which was used to prepare the geospatial information for the hydraulic model and process the results. Preparation of the LIDAR data included defining the river geometry and creating river cross sections to be used by the hydraulic model. The hydraulic models were calculated using the USACE river analysis software (HEC-RAS 5.0). Ultimately, the analysis was used to create maps with ArcMap that visually show the reach of the floodplains, illustrating the potential areas affected. 1
Figure 1. Logan River Floodplain Mapping Study Area. Credits: Shapefiles for roads, rivers, schools, and state boundary were downloaded from the Utah AGRC website. 2 METHODS The general method for creating floodplain maps for a river has three major stages: Preprocessing, processing, and post processing of the data. These stages will be described in depth in subsequent sections. Figure 2 illustrates the three stages for floodplain mapping used in this study along with the main tasks accomplished within those stages. This study was specific to a section of the Logan River, but the method used is applicable to floodplain mapping for any river system. The floodplain mapping for this study was done with ArcGIS, HEC-GeoRAS, and HEC-RAS. The Preprocessing stage consisted mostly of model input data preparation and was done in ArcGIS using the HEC-GeoRAS extension. The processing stage was done completely within HEC-RAS using the river geometry prepared in the previous stage. The final stage consists of analyzing the results from the HEC-RAS model within ArcMap. HEC-GeoRAS helps in creation of the data needed for the HEC-RAS model and the transfer of data between ArcGIS and HEC-RAS. 2
Figure 2. General method for modeling floodplains using ArcGIS, HEC-GeoRAS, and HEC-RAS. 2.1 Pre-processing The first stage in determining floodplains for the Logan River was Preprocessing. The preprocessing stage consisted mostly of collecting and preparing data for the hydraulic model. To begin, a section of Logan River was defined as the study area. Once the study area was defined, shapefiles for the area were obtained from the Utah Automated Geographic Reference Center (AGRC) for features or infrastructure that might be affected in the event of flooding. Shapefiles for parcels, roads, schools, and churches were downloaded in order to evaluate the potential damage and risks for each flood analyzed. In order to create the necessary river geometry for HEC-RAS, elevation data were needed. High resolution LIDAR digital elevation model data for the Logan River was obtained from Dr. Jeff Horsburgh at the Utah Water Research Laboratory (UWRL). The LIDAR data were converted to a triangulated irregular network (TIN) elevation model by Caleb Buahin at the UWRL. The next step was to create the river geometry in ArcGIS. The HEC-GeoRAS extension was used to set up the necessary features that would be needed for the HEC-RAS model (i.e., stream centerline, bank lines, cross sections, etc.). HEC- RAS uses these features to obtain an accurate layout of the river and to establish the cross-sectional elevations of the potential floodplains. The cross sections must extend far enough to ensure that all water from the flood is contained within the cross-sectional area. Methods for setting up the model using HEC-GeoRAS were taken from the HEC-GeoRAS user manual (USACE, 2009). The river geometry was digitized using the ArcGIS editing features. Figure 3 shows the digitized river features on top of the TIN. 3
Figure 3. River geometry created in ArcGIS overlaying the TIN. HEC-GeoRAS uses the line features in conjunction with the TIN to extract elevations for the cross sections and flow profile. In addition to elevations, Manning s roughness coefficient values were applied to the cross sections using land cover data obtained from the National Land Cover Dataset (NLCD). The Manning s roughness values represent the roughness of the channel surface, which can influence the overall flow rates and velocities in the channel. The land cover data for the study area were downloaded and converted from a raster to a polygon shapefile. A value of Manning s roughness was assigned to each land cover category based on the research done by Kalyanapu et al. (2009). Table 1 shows the Manning s roughness coefficient for the NLCD land cover categories. 4
Table 1. Manning s roughness values. Land Cover Description Manning s n 21 Developed, open space 0.0404 22 Developed, low intensity 0.0678 23 Developed, medium intensity 0.0678 24 Developed, high intensity 0.0404 31 Barren land 0.0113 41 Deciduous forest 0.3600 42 Evergreen forest 0.3200 43 Mixed forest 0.4000 52 Shrub/scrub 0.4000 71 Grassland/herbaceous 0.3680 81 Pasture/Hay 0.3250 90 Woody wetlands 0.0860 95 Emergent herbaceous wetlands 0.1825 Using the land cover polygons, HEC-GeoRAS extracts values for Manning s roughness for each cross section. Each cross section ends up having multiple Manning s roughness values depending on which land cover polygons intersect the cross section line. Figure 4 shows the land cover polygons (derived from 30-m NLCD raster) with the river cross sections and centerline. Once all the data had been prepared, HEC-GeoRAS was used to prepare export files to be used in the HEC-RAS model. Figure 4. Manning s roughness polygons created using a land cover raster. 5
2.2 Processing The geometry data created in ArcMap were exported into HEC-RAS. Once in HEC-RAS, it was necessary to modify and correct the designated left and right banks of the river. The left and right banks defined in ArcMap using the HEC-GeoRAS extension didn t match the actual left and right banks. The error occurred because the left and right banks were visually selected using the geography data provided by the LIDAR data. The solution to this problem was to use the cross section editor in HEC- RAS and manually select the left and right banks based off of the cross section geometry. After correcting the geometry, a steady flow analysis was used to route four flows of 1000, 2000, 2500, and 3500 cfs through the river. This range was chosen because it represents flood stage flow magnitudes (1000, 2000 cfs) (US Department of Commerce 2016), historic high flow magnitudes (2500 cfs) (Berwick), and extreme flow magnitudes (3500 cfs). The steady flow analysis produced water surface profiles and the extents of each floodplain. An example of the HEC-RAS model solution for 3500 cfs is presented in Figure 5. Figure 5. Results from HEC-RAS for 3500 cfs. 6
2.3 Post processing The results from the HEC-RAS model were then imported back into ArcMap using the HEC-GeoRAS tool. After importing the results into ArcMap it was clear it was necessary to correct errors in the extents of the flood plains. The error seen in the HEC-RAS model results was flooding being shown in ineffective flow areas. Ineffective flow areas are areas of low elevation that do not connect with the main floodplain area. If not defined, HEC-RAS will route water through these areas in the simulation. The solution to this problem was to use the cut tool in ArcMap, and remove the erroneous results. 3 RESULTS 3.1 Floodplain Maps The purpose of this study was to produce floodplain maps for a section of the Logan River at various flow rates. Four flow rates were analyzed, and the resulting floodplains were mapped using ArcMap (Figure 6). In order to more accurately analyze the floodplains and affected areas, the floodplain areas were mapped with specific shapefile features such as roads, parcels, and schools within the study area. Figure 7 shows a map of the schools and parcels of land that were affected by the highest modeled flow rate. It can be seen that there are many land parcels including Riverside preschool, that would be inundated with water during a flood event of this magnitude. Figure 6. Floodplains for four different flow rates on the Logan River. 7
Figure 7. Vulnerable land parcels affected by floodplain at 3500 cfs. 3.2 Possible Errors While completing the analysis of the Logan River and its floodplains, efforts were made to reduce the potential errors that were introduced into the data and results. However, as with all digital sources of data, there are accuracy limits by which the results are constrained. The possible errors that were seen throughout this project are enumerated in this section to identify shortcomings and areas of potential future improvement to the models. One of the first steps that was taken in the beginning of this project was obtaining LIDAR data of our study area. While this data acquisition method represents the terrain and elevation changes in specified areas, there are still potential errors and misrepresentations that can be seen. One of the team s main focuses with the LIDAR data was to extract accurate river cross-sectional geometries that could be used to model various flow rates in HEC-RAS. However, because of large trees and thick vegetation near the river, as well as the water flowing in the river during the time of data collection, there could have been errors introduced into the data. It is possible that the trees, vegetation, and water could have interfered with the lidar technology and therefore misrepresented the elevation data that was produced. Also, the Logan River has recently experienced river restoration efforts in some locations. Fortunately, the LIDAR data that were used in this project were obtained after the river restoration efforts were completed and therefore accurately represent the major changes to the river geometry. After the LIDAR data were obtained for the study area of interest, and before HEC-RAS could be used to run the model, HEC-GeoRAS was used in conjunction with ArcMap to create cross sections of the river, define the main river channel and bank lines, and overbank locations. One of the difficult parts of this process was determining how many cross sections to include and an appropriate distance between each consecutive cross section to capture the changes in channel geometry. This is another potential source of error if there weren t sufficient cross sections created. Also, since the cross sections must be created perpendicular to the direction of flow, it is possible that the resulting floodplains were not accurate because of the errors in the creation of the original cross sections. 8
In order to run a model in HEC-RAS, the Manning's roughness values must be specified. To determine these values, a land cover raster with 30-m resolution was used to create polygons of specific Manning s n values based on the land cover at all locations along the river cross section. In theory, this method should appropriately reflect the changes in channel roughness along each channel cross section. However, due to differences between the present day land cover and that from the land cover raster file, as well as potential inaccuracies in the polygon shapes, the channel roughness values used in the model could be affected. Using a land cover raster with a higher resolution would likely also improve the accuracy of the Manning s roughness polygons. Occasionally there are locations near the Logan River that are similar or lower in elevation than the main river channel but are not part of the river system. In these cases, the locations outside of the main channel must be designated as ineffective flow areas because water does not flow in those areas unless the water in the main channel has overtopped the banks. If these ineffective flow areas are not designated, HEC-RAS falsely thinks that water from the river is flowing in those locations. This affects the resulting floodplains because the total amount of flow is not accurately represented in the main channel. Errors may be seen in the floodplains if too many or too few ineffective flow areas were designated. In order to mitigate these issues, a tool was used in ArcMap to cut out the portions of the flood plains that were obviously representing ineffective flow areas. To eliminate ineffective flow areas in future models, HEC-RAS can be used to designate locations in each cross section that should be considered ineffective flow areas. This will eliminate the need to cut out portions of the resulting flood plains in ArcMap. 4 CONCLUSIONS The purpose of this study was to map the floodplains of the Logan River using ArcGIS. The members of the group learned how to use and incorporate the functions of various software programs to produce the desired floodplains. It was found from the analysis that there are many land parcels and public access locations that could potentially be inundated by water in the event of large flows in the Logan River, specifically in the area near Riverside Preschool. The results from this study provide useful information to both Logan City and local residents near the Logan River. Logan City will be able to use the floodplain study to be aware of which land parcels, homes, and public locations may be affected if a flood were to occur. Knowing this information beforehand will allow the city to take the appropriate precautions during wet seasons. Also, the residents who have homes within the floodplains or attend the churches and schools near the river will be safer if they are aware of the potential hazards that could occur during times of flooding. ACKNOWLEDGMENTS We would like to thank Dr. Horsburgh and Caleb Buahin for providing our group with the LIDAR data and for showing us how to use HEC-GeoRAS. REFERENCES Kalyanapu, A., Burian, S., and McPherson, T. (2009). "Effect of land use-based surface roughness on hydrologic model output". Journal of Spatial Hydrology, 9(2). US Army Corps of Engineers,. (2009). HEC-GeoRAS: GIS Tools for Support of HEC-RAS using ArcGIS. Utah Division of Homeland Security,. (2008). Utah Natural Hazards Handbook. 62. US Department of Commerce, N. (2016). National Weather Service Advanced Hydrologic Prediction Service. Water.weather.gov,<http://water.weather.gov/ahps2/hydrograph.php?gage=lgnu1&wfo=slc> (Apr. 20, 2016). Berwick, V. K. (1962). Floods in Utah, Magnitude and Frequency. United States Department of the Interior. 9