Graduate Students, CEE-6190 Urban Storm Runoff Modeling Using GIS for EPA Storm Water Management Model (SWMM) Noha Hossam Muhammad Imran Graduate Students, CEE-6190 04/25/2016

Presentation Outline Introduction Objective Data Collection Methods Results Conclusion Questions

Introduction Objective Urban runoff generated from rain and snow which drains to streams, canals and rivers. This is one of the major source of water pollution. Environment Protection Agency - Storm Water Management Model (SWMM) is used for urban runoff modelling and to estimate pollutant loads associated with runoff Geographic Information System has strong spatial analysis function, which can be used to prepare the data for the SWMM Objective To prepare GIS based model with input parameter information that will be imported into SWMM for modelling of specific watershed in Logan SWMM will be used to compare its ability and strengths using high temporal and spatial data

Study Area The study area is Logan Northwest Field Canal watershed, with total area of 4.30 km2

Data Collection The data for this project was provided by Tony Melcher; in form shapefiles and digital elevation model The shapefiles were produced from LiDAR data obtained from Logan City Department using ArcHydro Tools The shapefiles comprises of watersheds, streets, buildings, future land use plan, monitoring locations and canals in Logan City Datasets are in projection NAD 1983 State Plane Utah North FIPS 4301 Feet

Methods Clipping The first step in the model building was clipping of spatial input parameters to the study area The reason for doing this step was to get data that is only covers the region of interest which is the study area/watershed shapefile. We clipped the files in ArcMap and saved in the geodatabase as a feature class Intersection Analysis Then intersect analysis was done among watershed and clipped shapefiles and saved as feature class in geodatabase The intersect operation combined data from bounding and data layer. Each resulting polygon in the output layer included attributes of both layers

Methods Shapefiles before clipping analysis Shapefiles after clipping analysis

Methods Statistical Analysis and Relationship After intersection analysis contribution of parameters in each watershed was calculated For this step, shapefiles generated after intersection analysis were used. Using watershed ID, areas were summarized and exported in form dbase table These tables were then joined to original watershed shapefile using spatial join feature Calculations/Analysis Percentage Impervious Land use composition Average slope

Methods Percentage Impervious The shapefiles of streets, buildings and demarcation of impervious region were separate. So, the areas of each of these input parameters in each watershed were calculated The areas of buildings, streets and impervious areas were added. Using field calculator in attribute table, total impervious area was divided by area of watershed and multiplied by hundred to get percentage values

Percentage Impervious Areas obtained after intersection analysis Percentage impervious area calculated in ArcGIS

Zonal histogram output table Methods Land Use Composition First, the shapefile obtained after intersection analysis between watershed and future land use shapefile was converted to raster from polygon on basis of land use description (LU Description) in attribute table In next step, zonal histogram analysis was done which created a table and a histogram graph showing the frequency distribution of cell values on the value input (LU description). Using this table fraction of each land use type was calculated to show the composition of each watershed and saved in form of table. Using spatial join relationship, fraction of each land use was linked to respective watershed ID Zonal histogram output table

Methods Average Slope To calculate the average slope of each watershed, we first calculated the slope in degrees of digital elevation model (DEM; 2 feet resolution) using the Slope tool in Spatial Analyst Then using the Zonal Statistic tool, mean values of slope were exported in table format, which was then spatially joined to watersheds using watershed ID

Results The final attribute table of watershed have the percentage of impervious area, average slope and land use composition These values will be used as input in SWMM for urban runoff modeling

Conclusion GIS performs complex calculations on large datasets and acts as an effective organizing system for our project. The GIS model that we developed is very important as the output data will be used in SWMM to calculate the pollution in any watershed. That will be useful for Logan City Department

Questions?