top of page
Search
  • Writer's pictureAnnabelle Dempsey

Susceptibility of Cookeville, Tennessee to Runoff based on a Three-Hour Rainfall Event

Updated: May 5, 2020

Susceptibility of Cookeville, Tennessee to Runoff based on a Three-Hour Rainfall Event was calculated taking into account impervious surfaces, precipitation data, and soil survey data.






In order to calculate potential flooding, a runoff model must first be run. The model is expressed as the following formula (2);

R = P - F  

Where:

 R = Runoff
 P = Cumulative Rainfall expressed as cubic feet  
 F = Cumulative Infiltration 

The study upon which this methodology is based uses a modified form of the Runoff Model, expressed as the following formula;

R = P - q 

Where;

R = Runoff
P = Cumulative Rainfall expressed as cubic feet

Calculation of q

An adjustment Index was first calculated for each impervious surface layer using a modified Green-Ampt Model, as per Lindberg, Joakim (2).This formula estimates the influence of landuse on infiltration by applying an adjustment index to impervious surfaces, based on the percentage of impervious surface area in each cell of the study area.


This new impervious surface raster is calculated using the following formula;


Green-Ampt Model

Q = 1 - U

Where:

Q = Impervious Surface Adjustment Index 
U =  percentage impervious surface

This was accomplished through the following workflow;


  1. Use Create Random Raster

  • Extent and resolution must be the same as the Impervious Surface rasters

  • Cell size = 30

  • Raster type = 8 bit unsigned

  • Band number = 1

  • Distribution = uniform

  • The minimum value is set to 1

  • The maximum value is set to 1

  • Output coordinate system: Albers Conical Equal Area

Run the tool to create RasterValue1


2. Use Raster Calculator

  • Impervious Surface - RasterValue1

The result is the Impervious Surface Adjustment Index (Q) for each Impervious Surface Raster used in calculations (for the purpose of this report, years 2006, 2011, and 2016).







The variable F was estimated based upon Web Soil Survey data and the aid of Table 1, Morgan (2005).





Figure 1: Estimated infiltration rates for three different soils. The graph is adapted after Morgan (2005)


Clay was estimated to have an infiltration rate of 6.25 mm/h (20mm/h /3.20t).

Loam was estimated to have an infiltration rate of 10.94 mm/h (35mm/h /3.20t).

Sand was estimated to have an infiltration rate of 17.19 mm/h (55 mm/h /3.20t).


These values were then appended to their respective soil groups in the soil survey layer.

Polygon to Raster was then ran on this layer and the resulting raster acted as the variable F.




Raster Calcuator was then used to calculate Adjusted Infiltration for each Impervious Surface raster through the following formula;

q = F * Q

Where;

q = Adjusted Infiltration  
F = Cumulative Infiltration  
Q = Impervious Surface Adjustment Index

The expression used to accomplish this was F * ImperviousSurfaceAdjustmentIndex.


The end results, q2006, q2011, and q2016 were then set aside until after P had been calculated.







Calculation of P


P or Cumulative Rainfall, per the study referenced, was based off a three-hour rainfall event for the study area. Data to determine this was collected from The National Oceanic and Atmospheric Administration using their Advanced Hydrological Prediction data portal, The data the study referenced used fifteen-minute intervals which were not available for Cookeville, TN. Data from the closest existing station in Monterey, TN was substituted. This date ranged from 1/1/2006-1/1/2014, the closest approximation to the ten year study period as covered by the impervious surface layers.


The mean and max (shown below histogram) were calculated for the dataset to find a suitable three-hour rainfall event.



The max for the dataset was 2.52/QGAG (precipitation expressed as inches).


This max value resides in the portion of the dataset that took place on 2011-11-28 during the hours of 12:30 AM and 10:00 PM.


P was then calculated using this time range until the three hour mark was researched. The results can be seen in Table 2;



Table 2: Cumulative Rainfall for three-hour event occurring on 2011-11-28


Red denotes the time, precipitation level, and cumulative rain in inches as they were when the three-hour mark was reached. However, due to the sampling times within this subset, the actual event time was 3.15 hours.


F, 9.3, was then appended to a new raster using the following workflow;


  1. Use Create Random Raster

  • Extent and resolution must be the same as the Impervious Surface rasters

  • Cell size = 30

  • Raster type = 8 bit unsigned

  • Band number = 1

  • Distribution = uniform

  • The minimum value is set to 9.3

  • The maximum value is set to 9.3

  • Output coordinate system: Albers Conical Equal Area

Run the tool to create P_3_Hour_Event .


Proceed, using P and q, to calculate the Modified Runoff Formula



Modified Runoff Formula

R = P - q 

Where;

R = Runoff
P = Cumulative Rainfall expressed as cubic feet

Use Raster Calculator to subtract q(Year) from P_3_Hour_Event for each impervious surface.


The end result of these steps is the following maps which show areas at risk of forming runoff during a three-hour event similar to the one that occurred on 2011-11-28.






-------------------------------------------------------------------------------------------------- References


A GIS-based model for urban flood inundation - ScienceDirect. (n.d.). https://www.sciencedirect.com/science/article/pii/S0022169409002546


Lindberg, Joakim. "Locating potential flood areas in an urban environment using remote sensing and GIS, case study Lund, Sweden."Student thesis series INES(2015).


National Centers for Environmental Information, N. (n.d.). Monterey, Tennessee Precipitation 15 Minute Station Details.


NCLD Urban Imperviousness 2006, 2011, 2016. (n.d.).





48 views0 comments
bottom of page