GIS in Water resources: CEE 6440

Using GIS to show the temporal –spatial variation of Phosphorus in Wellsville City Sewage Lagoons as simulated by a water quality model

Background and justification of study

The Little Bear River TMDL identifies Wellsville City Sewage Lagoons as a point source for Total phosphorus on the river’s segment below the Hyrum reservoir to the East Fork Little Bear confluence. As a result of the increased P loadings from the lagoons, this segment of the LBR is impaired for its Class 3A beneficial use. In order to improve the receiving water quality, the State in 2007 issued a UPDES permit to Wellsville City Lagoons limiting the total P discharges from the Lagoons to 72 kg of TP /season (warm season, June – September) and 360 kg of TP/season (cool season, October – May).

Since discharge from the lagoons is determined by the operators, it is important for them to know which cell has the least P and when this occurs so that they can maximum discharge from the Lagoon without violating the limit. This process would optimize the performance of the lagoons and at the same time preserve the environment.

A water quality model helps describe and simulate complex dynamic processes that are occurring within a water system. The modeling process can however be greatly enhanced by the use of GIS which has very powerful tools for spatial discretization and visualization of data. 

Figure 1: Wellsville City Wastewater Treatment Facility schematic by J.U.B engineers

 

Objective

To determine and show the amount and distribution of phosphorus in the Wellsville City Lagoons

Methodology

 

 


Process model

In order to model P in the lagoons, a number of assumptions were made;

1.      Each lagoon was assumed to be completely mixed reactor

2.      Non point sources into the lagoon were considered negligible

3.      P  was only taken out of the water column by  precipitation/attachment to sediment and discharge into LBR

4.      Volume in each reactor was considered constant

5.      First order settling rate and settling velocity was assumed to be 10 m/yr (Chapra, 2007)

6.      No P recycle from sediments

Model set up

 

 

 

 

Reactor 1                                                         Reactor 2

                    

Reactor 3                                                         Reactor 4

                      

Where: C-concentration of P (mg/m3), t-time (day), Q-discharge (m3/d), h-time step (day), Vs-settling velocity (md-1),

Excel and GIS

The model was run in excel using numerical methods (Heun’s method) and the results obtained exported into GIS and displayed for analysis and interpretation.

Data used

Table 1: Hydro-geometric properties of the Lagoons from J.U.B engineers report

Lagoon

Cell

Lagoon

 SA (acres)

Depth

(ft)

Volume

 (Mgal)

1

15.6

6

29.1

2

20.1

6

37.6

3

11.2

6

20.6

4

9.6

6

17.7

Total

56.5

105

 

Field effluent phosphorus values, discharge values from operators monthly report for the years 2004 – 2007, Bear River Watershed data, and NHDPlus data. Temporal visualization was done by use of Tracking Analyst tool, and Time slider.

Model output from excel and input into arcGIS

From the operators’ report, only monthly effluent P concentrations, daily inflow and outflow discharge values were available. Consequently, the discharge values were averaged to monthly values inorder to have a uniform time step for the model. The model was used to predict the P concentrations in each of the lagoons based on the known effluent concentration. The model output was tabulated and exported to arcGIS as a table containing the temporal P data. This was done by using a table to table tool that converted the excel table into a geodatabase table.

It is important to note that the model used was not very accurate because of the inherent assumptions but it did give reasonable results for the purpose at hand. Also I could not verify the results obtained because a lack of P data for the three lagoon cells (P values are recorded for only the effluent out of the 4th lagoon cell).

The Study area is found within the Little Bear River watershed specifically the Logan –Bear segment.  Using the Bear River Watershed and NHDPlus data, a shape file of the lagoons was created and Little Bear River located as shown in Figure 2. 

Figure 2: Wellsville City Sewage Lagoons and the discharge point into the LBR

The attribute table for the lagoon cells shape file contained the spatial reference data. A cell ID field was added to the both tables containing the temporal data and spatial data and used as a unique identifier to join the two tables in ARCGIS. Given that the join had a one - many relationship, the make query table command was used to successfully execute the join.

Table 2: Illustration of the one- many relationship

Visualizing temporal data

Two types of data were displayed in ArcGIS i.e. time instant data (variation of P for each month within each lagoon cell) and time extent data (Average P values for each season with in each lagoon cell) using the tracking analyst tool and the time slider respectively. This was done as an illustration on how the two tools work.

Using tracking analyst tool

The query table containing both the spatial and temporal data was exported into the geodatabase as a layer. The add button on the tracking analyst toolbar was used to open the add data wizard and input the spatial –temporal data contained in the layer. The symbology of the event (TP) was changed to graduated colors for better visualization. The play back manager properties were set to one month and the visualization enabled using the play button.

Using the time slider

The query table was exported into the geodatabase as a table. The time properties in the table were enabled by checking “Enable time on this layer” under the time tab in the layer properties. The time extent was set by specifying the start and end time. I used 3 months for each season (winter, spring, summer and fall) for uniformity and simplicity. The time slider was opened and its options changed accordingly to give the desired output. Visualization was enabled by the play button.

Results

Figure 3 illustrates the use of tracking analyst tool to show P variation in the different lagoon cells for the month of April 2004.

Figure 3: Temporal –spatial variation of P (mg/L) within ponds for 04/30/2004 using tracking analyst tool

 

The graphs below illustrate the use of the time slider to show the variation of P in the lagoons for the year 2004 in kg/season. Discharge is from the fourth lagoon cell; therefore in an ideal situation it should always have the lowest P concentration. This is not always the case as shown in Figure 5. If the lagoon operators are provided such information on a seasonal basis then it would be easy for them to determine the quantity of P discharge required and from what cell. This information can be provided by modifying the model to predict P concentrations given the desired effluent limit, incoming P concentrations and discharge values. The lagoon piping system already has the capacity to bypass effluent from the preceding cells to cell 4.

 

Figure 4: Temporal –spatial variation of P (kg/season) within lagoon cells for winter 2004

Figure 5: Temporal-spatial variation of P (kg/season) within lagoon cells for spring 2004

 

Figure 6: Temporal-spatial variation of P (kg/season) within lagoon cells for summer 2004

 

 

Figure 7: Temporal - spatial variation of P (kg/season) within lagoon cells for fall 2004

 

Conclusions

GIS tools can be used to enhance visualization of data from process models

Recommendations

Other than the demonstrated use, spatial temporal visualization of data in ArcGIS can enable scientists or researchers who have years of data to visualize how the data evolved or trace progression trends. The tracking analyst tool is also a useful for real time data.

References

NHDPlus http://www.horizon-systems.com/NHDPlus/

Watershed boundary Dataset http://www.ncgc.nrcs.gov/products/datasets/watershed/

TMDL Little Bear River

J.U.B. Engineers Report: Wellsville City Wastewater Treatment Facilities Plan (2008)

Chapra S.  (2007): Surface Water Quality modeling

ArcGIS professional library help (Tracking Analyst tool)

ESRI video: Working with temporal data in ArcGis http://video.esri.com/watch/93/working-with-temporal-data-in-arcgis assessed on 11/01/2010.