Run-off Prediction for Pineview Reservoir

Term Project For

Geographical Information Systems in Water Recourses– Utah State University

Created By

Bryan Heiner

Created For

Dr. David G. Tarboton, Dr. David R. Maidment, and Dr. Ayse Irmak

Date

October 28, 2008

Contents

Proposal: 3

Procedure and Results: 4

Discussion: 12

Conclusion: 13

References: 13

Proposal:

Pineview reservoir is a high hazard dam located near Huntsville Utah (Figure 1). This reservoir is used to provide hydroelectric power and to supply water to agricultural users nearby. Having a reservoir capacity of 110,150 ac-ft there is a great risk for loss of life or land if the dam were to overtop. Approximately 6 miles downstream of Pineview reservoir is Ogden City, which is one of the larger cities in the state. To date, Pineview reservoir has provided safe and efficient delivery of power and water to its users with no storm events causing downstream flooding. To help Pineview operate their reservoir in such a way that flooding Ogden never happens, it is essential that the run-off entering Pineview be predicted for a certain rain event.

Figure 1 - Pineview Reservoir

This project will use GIS to predict run-off that contributes to Pineview reservoir from precipitation data. In order to complete this project a base map will need to be created. Initial searches for data have been conducted and an outline of Pineview reservoir has been found from the AGRC website. Subbasins, catchments, USGS stream gauges, flowlines and flowline attributes can be obtained online from National Hydrography Dataset Plus (NHDPlus). In addition a digital elevation model (DEM) can be found in 1/3 arc second resolution from the USGS seamless server (USGS). Precipitation for the area needs to be collected and may be found online from NOAA, USU Climate Data Center, or DAYMET. After the creation of a base map a model will be produced to determine the amount of runoff created by a particular storm. The model will be calibrated from historical data which will provide confidence in the model.

Procedure and Results:

Datasets were downloaded from the above mentioned sites. Pineview reservoir is only a small portion of the Great Basin Hydrologic Region 16. The Nation Hydrography Dataset Plus data is downloaded as all of region 16. Because of this the dataset was trimmed to size by several processes. First, all of the subbasins and water bodies in the Great Basin were added as layers to the map. The outline of Pineview Reservoir and the subbasins that are make up its watershed selected and exported as a new layer within a Geodatabase. Selection by location was done to crop flowlines, catchments and USGS stream gauges that are contained in the watershed of interest (Figure 2). The DEM gives elevation in meters was then cropped to fit the previous data by using the GIS toolbox, Extract by Mask (Figure 3). After the data was added to the base map as feature classes and cropped to the appropriate size, object classes were joined where available. Flowline attributes were added to the streams to give the min, max and average stream flows.

Figure 2 - Layout of Pineview Reservoir, Catchments, Flowlines and Stream Gauges

Figure 3 - Layout of Cropped DEM Elevations are given in Meters

In order to obtain average precipitation over the contributing watersheds rain gauges must be located. Due to the limited availability of rain gauges it is proposed that 12 rain gauges be installed in the area. Figure 4 shows the recommended locations for the new precipitation gauges.

Figure 4 - Layout of Proposed Precipitation Gauges, Elevation in Meters

For each precipitation gauge the 100 year 60 minute flood event was obtained (NOAA, 2008). Table 1 contains the latitude, longitude and rainfall in inches for the 12 proposed precipitation gauges. These values were input into an excel spreadsheet and then were added as a data layer to GIS using “Display X & Y Data”.

Table 1 – Input Spreadsheet

After the precipitation gauges and data were added to GIS a raster of the precipitation was obtained. Using the Spline tool of the Spatial Analyst toolbar creates the raster as shown in Figure 5.

Figure 5 - Precipitation Raster Created by Spline Values are in Inches

The new precipitation raster was then extracted by mask to only have values contained within the contributing watersheds. Figure 6 shows the precipitation data after the extraction was complete.

Figure 6 - Raster of Precipitation given in Inches after Extraction by Mask

Zonal statistics were then used to find the average precipitation over the watershed. Using the GIS model builder allows users to create, extract and get the zonal statistics in one step. The model that was created is shown in Figure 7.

Figure 7 - Model to Obtain the Zonal Statistics

The average precipitation intensity for the storm event was determined as 2.11 in/hr fell across the contributing watershed. This value was used with the Rational Method to calculate the peak discharge as described in Equation 1 below (McCuen, 2005).

Equation 1

Where q_p is the peak runoff flow in cubic feet per second (cfs), C is a unit less runoff coefficient, i is the rainfall intensity in inches/hour (in/hr), and A is area of the catchment in acres that is being drained. The contributing area in acres was obtained from GIS as 190,719 acres. The reservoir occupies 2,870 acres when full, this amount to under 2 percent of the watershed. Precipitation falling directly into the reservoir should be added as 100 percent runoff but the this effect has been ignored due to its small amount. It was assumed that the area had a runoff coefficient of 0.16 across the entire watershed. Table 2 contains typical runoff coefficients.

Table 2 – Land use with corresponding runoff coefficients (Illinois 2007)

Table 3 contains the area (A), intensity (i), runoff coefficient (C), and the peak runoff (q_p) as calculated by Equation A1 for the watershed.

Table 3 – Summary of Area, Intesity, C and q_p for Pineviews Catchment and 100 yr, 60 min Storm

Land Type	Area	Intesity i	C	qp
	(ac)	(in/hr)		(cfs)
Unimproved	190,719	2.11	0.16	64,387

Next the time of concentration (t_c) was calculated using the Equation 2 below provided by the Soil Conservation Service (SCS) (McCuen, 2005). This approach to solve for the time of concentration was selected because it takes into account land use, allowing for an accurate estimation of the time of concentration.

Equation 2

Where t_c is the time of concentration in minutes (min), L is the longest length of the runoff producing area in feet (ft), S is the average slope of the area, and CN is the curve number associated with the land use. A curve number of 55 was selected from Table 4 below for wooded area with soil type B.

Table 4 - Curve Numbers for Different Land Use Descriptions (Perdue 2004)

Table 5 contains the length (L), slope (S), curve number (CN), and time of concentration (t_c) for the pre-development. The length was determined using Arc Hydro9 tools in GIS by tracing the streams upstream of the reservoir to find the maximum distance water could travel across the proposed development (150,000 ft). The average slope of the catchment was determined in GIS and Equation 2 was used to find the time of concentration (1913.4 minutes).

Table 5 – Summary of Length, Slope, Curve Number, and Time of Concentration for Catchment

Land Type	Length L	Slope S	CN	tc
	(ft)	(ft/ft)		(min)
Unimproved	150000	0.0322	55	1913.4

The next step was to find the lag time (t_l), recession time (t_r) and time to peak (t_p) for the design storm event. Equations 3 – 5 are used to solve for these values (McCuen, 2005).

Equation 3

Where t_l is the lag time in minutes and t_c is the time of concentration in minutes.

Equation 4

Where t_r is the recession time in minutes and t is the duration of the design storm even in minutes.

Equation 5

Where t_p is the time to peak in minutes with t_r and t_l as previously defined. Table 6 contains the solution to Equations 3 –5 for the watershed.

Table 6 – t_l, t_r and t_p for Pre-developed Site

Variable	Result (min)
tl =	1145.7
tr =	50.0
tp =	1170.7

Using the National Resources Conservation Services (NRCS) dimensionless unit hydrograph (DUH) an inflow hydrograph was created for the catchment. Table 7 shows the inflow hydrograph that was created. Columns (1) and (2) represent the NRCS DUH. Column 3 is the time in minutes and is found by multiplying column (1) of the same time step by the time to peak (t_p) as found by Equation A5. The time in hours is calculated in column (4) by dividing column (3) by 60 minutes. Column (5) is calculated by multiplying column (4) of the same time step by the peak inflow (q_p) as found with Equation 1.

Table 7 – Creation of Pre-Development Hydrograph using NRCS Dimensionless Unit Hydrograph

t/tp	q/qp	t	t	q
		(min)	(hours)	(cfs)
(1)	(2)	(3)	(4)	(5)
0.0	0.000	0	0	0.00
0.2	0.100	234	3.90	6438.67
0.4	0.310	468	7.80	19959.89
0.6	0.660	702	11.71	42495.24
0.8	0.930	937	15.61	59879.66
1.0	1.000	1171	19.51	64386.73
1.2	0.930	1405	23.41	59879.66
1.4	0.780	1639	27.32	50221.65
1.6	0.560	1873	31.22	36056.57
1.8	0.390	2107	35.12	25110.83
2.0	0.280	2341	39.02	18028.29
2.2	0.207	2576	42.93	13328.05
2.4	0.147	2810	46.83	9464.85
2.6	0.107	3044	50.73	6889.38
2.8	0.077	3278	54.63	4957.78
3.0	0.055	3512	58.54	3541.27
3.2	0.040	3746	62.44	2575.47
3.4	0.029	3980	66.34	1867.22
3.6	0.021	4215	70.24	1352.12
3.8	0.015	4449	74.15	965.80
4.0	0.011	4683	78.05	708.25
4.2	0.008	4917	81.95	515.09
4.4	0.006	5151	85.85	386.32
4.6	0.004	5385	89.76	257.55
4.8	0.002	5620	93.66	128.77
5.0	0.000	5854	97.56	0.00

After in inflow hydrograph was created an elevation-storage and elevation-discharge relationship were obtained from a GENRES model (Adams 1992). The design storm was then routed through the reservoir using the Modified Puls Method and detailed instructs on the use of this method can be found in McCuen’s book Hydrologic Analysis and Design. Figure 8 shows the inflow hydrograph from the design storm and the discharge outflow from the proposed detention basin. The discharge from the reservoir reaches 1171 cfs. A storm event similar to the 100 year 60 minute storm occurred on May 05, 1997, this storm event produced discharge from the reservoir of 1230 cfs. These is a slight discrepancy between the model and the actual storm event because the rainfall intensity wasn’t exactly the same. Another reason is that reservoir operations do not remain constant resulting in a changing elevation discharge relationship.

Figure 8 - Routed Hydrograph Inflow and Outflow

Discussion:

The model predicts the runoff from Pineview reservoir fairly well. Several items could contribute to the slight errors that are occurring and steps can be taken to improve the accuracy of the model. The first step that could improve the accuracy of the model is obtaining land use and coverage maps from the AGRC Utah Information Portal. These maps would allow the watershed to split into many different areas and assigned runoff coefficients based on the actual land use instead of using an assumed value of 0.16 for the whole watershed. This will improve accuracy by giving a more realistic inflow hydrograph. A second step that can be done to improve the accuracy is to tweak the runoff coefficients. The range of runoff coefficients for wooded areas is from 0.05 to .25. Adjusting the coefficient in the model changes the peak outflow from 927 (C = 0.05) to 1279 (C=0.25) cfs which is around 15 percent different from the outflow given by the 0.16 assumption. A third step that could improve the accuracy of the model is to use a different method to round the hydrograph.

Conclusion:

This project used GIS to predict run-off that contributes to Pineview reservoir from precipitation data. The model involved creating a base map from data available in online datasets and cropping them to only contain information for the contributing watershed and catchments. A tool was created in ArcMap that allows precipitation data to be added, transformed into a raster, cropped and then calculates zonal statics to find the average precipitation over the entire watershed. After the average precipitation data was found an inflow hydrograph was created using the Rational Method and was routed through Pineview reservoir using the Modified Puls Method. The discharge from the model was compared to historical data and was found to be accurate within 5 percent. Addition ideas were given that could be implemented to increase the models accuracy.

References:

Adams, Todd D., Cole, David B., Miller, Craig W., Stauffer, Norman E Jr., 1992. “GENRES, A Computer Program System for Reservoir Operation with Hydropower”, manual, Utah Division of Water Resources.

Finnemore, E. John., & Franzini, Joseph B., (2006). “Fluid Mechanics with Engineering Applications.” Ed: 10, McGraw-Hill Companies, Inc., New York, NY.

Illinois, University of. (2007) “Values of Runoff Coefficient (C) for Rational Formula.” http://agrabilityunlimited.org/classes/tsm352/lectures/runoffcoeffs.html (accessed Nov. 02, 2008)

Inc., Upper Saddle River, New Jersey: Pearson Prentice Hall.

McCuen, Richard H., (2005). “Hydrologic Analysis and Design.” Ed 3, Pearson Education

NHDPlus (National Hydrography Dataset Plus). http://www.horizon-systems.com/nhdplus/HSC-wth16.php. (accessed Oct. 16, 2008)

NOAA (National Oceanic and Atmospheric Administration). “Hydro-meteorological Design Studies Center.” http://hdsc.nws.noaa.gov/hdsc/pfds/. (accessed Oct. 26, 2008)

Perdue Research Foundation. (2004) “SCS Curve Number Method.” West Lafayette, Indiana. http://www.ecn.purdue.edu/runoff/documentation/scs.htm (accessed Nov. 06, 2008)

USGS (United States Geological Survey). The National Map Seamless Server. http://seamless.usgs.gov/website/seamless/viewer.htm. (accessed Oct. 16, 2008)