


By Scott T. Prinos

Open-File Report 2004-1412

Correlation Analysis of a Ground-Water Level Monitoring Network

Analytical Considerations

	Spatial Relations
	Seasonal Water-Level Variation
	Temporal Changes in Correlation Between Monitoring Wells
	Evaluating Correlation of Water-Level Data

Analysis Methodology

Analysis Results

References Cited

Appendixes I & II

image of Duval County, Florida

CORRELATION ANALYSIS OF A GROUND-WATER LEVEL MONITORING NETWORK

Analytical Considerations

The results of a correlation analysis between two continuous variables, although technically correct, could be misleading under several circumstances. First, data that correlate may not be identical. For example, strongly associated water levels at two different stations may not have the same mean value. Water-level monitoring networks often are used to assess the slope of the potentiometeric surface as well as the variability of water levels. Therefore, even wells with strongly associated water levels, may provide additional water-level information that is needed. If the data are strongly associated, assessing the relation in greater detail will help to determine whether the data are redundant.

A second consideration is that if the two continuous variables consist of time-series data, then temporal variation in either the short or long term could result in misinterpretation of the results. For example, the seasonal variation in rainfall and hydrology could result in seasonal changes in correlation that may not be understood unless specifically considered in the analysis. Additionally, periodic or gradual declines in the degree of correlation caused by droughts, climatological cycles, or changes to the hydrologic system could both result in data that in the short term are substantially less correlated than indicated by a purely long-term analysis of correlation. With this in mind, a correlation analysis of data from a ground-water level monitoring network was considered for both the short and long term.

Another previously discussed consideration is that the correlation analysis of two continuous variables does not establish causality. To understand the association, the data must be examined in greater detail. The ground-water level monitoring network in Miami-Dade County is influenced by recharge from canals, operation of canal flow regulation structures, evapotranspiration, precipitation, and withdrawals for municipal water supply. Each of these factors can be represented spatially. Therefore, spatial examination of the correlation analysis results was used to help determine which correlations could have been influenced by the same causal factors.

Next: Spatial Relations

Figures: Click on a caption to view the figure.

Figure 1. Map showing location of continuous ground-water level monitoring network wells in Miami-Dade County, Florida.

Figure 2. Map showing water-supply and water-management systems in Miami-Dade County.

Figure 3. Maps showing lines of equal rainfall in Miami-Dade County during (a) Hurricane Irene on October 14-16, 1999, and an (b) unnamed storm on October 2-3, 2000.

Figure 4. Graphs showing seasonal variation in mean water levels and variation in monthly standard deviation of mean water levels for wells G-620, G-864, G-1183, and S-18.

Figure 5. Hydrograph showing variation in water levels at wells G-3 and G-1368A along with estimated average daily pumpage based on annual pumpage totals during water years 1974-2000.

Figure 6. Hydrograph showing variation in water level at well G-1502 during water years 1974-2000.

Figure 7. Map showing grouping of wells based on average correlation of water-level data during the wet season.

Figure 8. Map showing grouping of wells based on average correlation of water-level data during the dry season.

Figure 9. Map showing grouping of wells based on average correlation of water-level data during both the wet and dry seasons.

Figure 10. Map showing grouping of wells near the West Well Field based on average correlation of water-level data during both wet and dry seasons.

Figure 11. Graph showing temporal variation in seasonal correlation between water-level data from well G-1487 and that of well G-855 during water years 1974-2000.

Figure 12. Hydrographs showing water-level elevations from wells G-855 and G-1487 during the 1986 and 1998 water years.

Figure 13. Map showing grouping of wells near the Hialeah-Miami Springs Well Field based on average correlation of water-level data during both the wet and dry seasons.

Figure 14. Graph showing temporal variation in seasonal correlation between water-level data from well G-3466 and that of wells G-3465, S-19, and S-68 during water years 1988-2000.

Figure 15. Hydrographs showing water-level elevations from wells G-3465, G-3466, S-19, and S-68 during the 1990 and 1996 water years.

Figure 16. Hydrograph showing water-level elevations from wells G-3465, G-3466, S-19, and S-68 during water years 1988-99.

Figure 17. Graph showing temporal variation in seasonal correlation between censored and uncensored water-level data from well G-3466 and that of wells G-3465, S-19, and S-68 during water years 1988-2000.

Figure 18. Graph showing temporal variation in seasonal correlation between water level data from well G-1362 and that of well G-757A during water years 1974-2000.

Figure 19. Hydrograph showing water-level elevations from wells G-757A and G-1362 during the 1989 and 1997 water years.

Figure 20. Graph showing temporal variation in seasonal correlation between water-level data from well G-864 and that of well G-864A during water years 1974-2000.

Figure 21. Hydrograph showing water-level elevations from wells G-864 and G-864A during the 1990 and 2000 water years.