Jessy Van Horn Experimental and Methods



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Jessy Van Horn
Experimental and Methods

03/19/2014



MethodsStudy Area and Data

Daily discharge data (ft3/s) was are gathered from the United States Geological Survey (waterdata.usgs.gov) for the Santa Fe River near Fort White, Florida Florida (29°50'55" N, 82°42'55" W, gauge height 6.4 a.m.s.1), from 1932 to 2012. The river drains 2634 km2 of the rural landscape in north central Florida (figure), dominated by forestry and agriculture (Fernald and Patton 1984). The basin possesses little relief (almost entirely below 60 m), and lies on Tertiary limestones and clastics overlain by Quaternary sands. The groundwater component of stream flow is large, the river being fed by many natural springs, including several first magnitude springs (Florida Geological Survey, 2004) from the unconfined Floridan aquifer closer to the gauge point, which reflect regional as well as basin inputs. No hydraulic structures are present upstream of the gauge. Precipitation is almost exclusively rainfall, averaging about 1270 mm annually. Two principal rainy seasons (figure) result from mid-latitude cyclonic activity in winter and early spring (December through March), and convection and tropical cyclones in summer (June to September). These seasonal inputs are reflected in a general bimodal pattern of stream flow (figure). Although the cold season rainfall is considerably less than that of the warm, the spring flow peak attain levels comparable to those of summer because of high evapotranspiration losses in the latter.


Interannual variability in winter rains is closely linked to El Niño-Southern Oscillation (ENSO), (see for example, Kahya and Dracup, 1993, Schmidt et al., 2001, Chiew and MacMahon, 2002) and summer variability is related to the uncertain nature of the contributions from tropical cyclones. Although the phase of ENSO is an important variable in determining the number of tropical storms and cyclones in the North Atlantic basin (see Pielke and Landsea, 1999, Webster et al., 2005, Emmanual, 2005), the comparative rarity of the events and the respective sizes of the drainage basin and North Atlantic basin make any such signal difficult to detect in regional streamflow. In the longer run, there is evidence that the Atlantic Multidecadal Oscillation (AMO) influences annual precipitation in this region (Enfield, Mestas-Nuñez and Trimble, 2001). A warm phase of the AMO existed from the early 1930 until 1960, before switching to a cold phase and reverting to warm in the late 1990s.
Although the water year is generally considered to commence on October 1 in Florida, examination of historic daily flows (figure) showed that the Santa Fe at this station reached their historic minima, with the lowest interannual variability, at the beginning of December, while October 1 coincided with high mean flows and considerable variabilityIt was determined that the appropriate water year for the Santa Fe River was December 1 to November 30 based off the timings of stream flow maxima and minima.

Figure. Upper) Box and whisker plot of monthly precipitation totals at High Springs, 1944-2010, located within the drainage basin. (Lower) mean daily precipitation +/- one standard deviation of the Santa Fe River near Fort White (1932-2012)



Monthly precipitation data from 1932 to 2010 are obtained from the Southeast Regional Climate Center (www.sercc.com) for stations within the drainage basin and in the general region of north central Florida. (figure and table 1). Only two stations lie within the topographically defined basin limits, however, given the low relief of the region, the annual scale of aggregation, the regional significance of the Floridan aquifer, and the spatially and temporally discontinuous nature of individual station records, these stations provide a reasonable indication of regional precipitation and likely annual basin inputs (both surface and subsurface).




Station

Lat.

Lon.

First

Last

Percent







(°.' N)

( °.' W)

Year

Year

Complete

1

Cedar Key

29.08

83.02

1932

1974

62.8

2

Crescent City

29.26

81.31

1932

2009

64.1

3

Cross City

29.39

83.10

1948

2010

54.0

4

Daytona Beach

29.11

81.03

1949

2010

96.8

5

Deland

29.04

81.17

1932

2010

73.4

6

Federal Point

29.44

81.32

1932

2010

64.6

7

Fernandina Beach

30.39

81.28

1932

2009

76.9

8

Gainesville Aiport

29.41

82.16

1961

2010

66.0

9

Gainesville UF

29.39

82.21

1932

1962

83.9

10

Glen St Marys

30.16

82.11

1932

2010

48.1

11

Hastings

29.43

81.30

1978

2010

90.9

12

High Springs

29.50

82.36

1944

2009

71.2

13

Island Grove

29.27

82.06

1947

1976

86.7

14

Jacksonville Airport

30.30

81.42

1954

2010

91.2

15

Jacksonville Beach

30.17

81.24

1944

2010

79.1

16

Jasper

30.31

82.57

1950

2010

85.2

17

Lake City

30.11

82.36

1932

2009

82.1

18

Live Oak

30.17

82.58

1952

2010

69.5

19

Madison

30.32

83.26

1932

2010

77.2

20

Mayo

30.03

83.10

1949

2009

82.0

21

Ocala

29.11

82.08

1932

2010

86.1

22

Palatka

29.39

81.39

1932

2001

55.7

23

Perry

30.08

83.34

1932

2010

72.2

24

St. Augustine

29.54

81.19

1932

2010

77.2

25

Starke

29.56

82.06

1958

1983

53.8

26

Steinhatchee

29.43

83.18

1964

1995

53.1

27

Usher Tower

29.25

82.49

1956

2008

79.2

Table 1. Precipitation recording stations in north central Florida indicating first and last years of complete annual records and the percentage of complete years within that period.

***** Note we are going to need to get a map somehow *******



The percentage of available precipitation stations in north central Florida returning complete annual records 1932-2010.

METHODS

Mean annual discharges, annual maxima and their dates, and annual minima and their dates are extracted from the daily discharge records following adjustments for the newly defined water year. Annual basin precipitation input is calculated by means of a modified isohyetal approach. In each year, a Krieged regional surface is fit to the available station estimates (figure) using Surfer (Golden Software, 2013. Only those portions of the regional surface within the basin limits are extracted, the volume of the resultant figure is computed and divided through by basin surface area.



In order to identify any monotonic trends, aA t-test was is runran to determine whether the slope of the best-fit straight line to each of the hydrometeorological time series if there was a change in stream flow is significantly different from zero. After the test for the mean and minima flows returned significant evidence to reject the null hypothesis of the slope equaling zero, we needed to determine the breaking point in the data. Discrete A breaks in mean, minima, and maxima stream flows wasare found by using the non-parametric Mann-Whitney U test. First, a moving twenty- year window is passed over the series was used, testing for a difference in populations summed ranks of the former and latter decadesten years. The twenty-year window was employed because of the noted 3-7 year pseudo periodicity of ENSO and its known regional impacts. (Note to selves- remember to talk about problem of sliding windows as they induce artificial periodicities in the M-W U). Following identification of potential discrete break points, the test is then reapplied to the pre- and post- periods

The Mann-Whitney is merely a rank-sum test. A second non-parametric test which can be used to identify which particular levels (historic percentiles) of the hydrometeorologic variables are particular sensitive to the break points is provided by the hypergeometric probability distribution. This test has been extensively used in detecting associations between levels of above median rainfalls and phases of ENSO (Ropelewski and Halpert, 1998, Grimm et al., 2000, Gaughan and Waylen, 2012). In this paper, the approach is modified to detect significant differences from random in the number of occasions (years) that each hydrometeorological variable falls above or below various historically defined percentiles ( 5th to 95th in steps of 5%), before and after the purported breaks in the series.

Next, a forty year window was used in order to smooth out the results and clearly see the break. Hypergeometric analysis was also done for the mean, minima, and maxima flow data to find how many events exceeded a certain percentile before and after the computed break. A t-test and Mann-Whitney U test were ran on daily precipitation data for rain gauges surrounding the Santa Fe river basin to look for a similar pattern seen in stream flow. The data was collected from Southeast Regional Climate Center (www.sercc.com) and the following gauges were used: Usher Tower, Island Grove, Lake City, Glenn Saint Mary, Ocala, High Springs, Starke, and Gainesville Airport.

Chiew, F. H., and McMahon, T. A., 2002. Global ENSO-streamflow teleconnection, streamflow forecasting and interannual variability. Hydrological Sciences Journal, 47(3), 505-522.


Emanuel, K. 2005. Increasing destructiveness of tropical cyclones over the past 30 years. Nature, 436(7051), 686-688.
Florida Geological Survey, 2004. “Springs of Florida”, T.M. Scott, G. H. Means, R.P. Meegan, R.C. Means, S. B. Upchurch, R. E. Copeland, J. Jones, T. Roberts and A. Willet. Bulletin 66, Tallahassee, Florida. 658p.
Gaughan, A. E., and Waylen, P. R., 2012. Spatial and temporal precipitation variability in the Okavango–Kwando–Zambezi catchment, southern Africa. Journal of Arid Environments, 82, 19-30.
Grimm, A. M., Barros, V. R., and Doyle, M. E., 2000. Climate Variability in Southern South America Associated with El Niño and La Niña Events. Journal of climate, 13(1).
Kahya, E., and Dracup, J. A. 1993. US streamflow patterns in relation to the El Niño/Southern Oscillation. Water Resources Research, 29(8), 2491-2503.
Pielke Jr, R. A., and Landsea, C. N., 1999. La Niña, El Niño and Atlantic Hurricane Damages in the United States. Bulletin of the American Meteorological Society, 80(10), 2027-2033.
Ropelewski, C. F., and Halpert, M. S.1987. Global and regional scale precipitation patterns associated with the El Niño/Southern Oscillation. Monthly weather review, 115(8), 1606-1626.
Schmidt, N., Lipp, E. K., Rose, J. B., and Luther, M. E. 2002. ENSO influences on seasonal rainfall and river discharge in Florida. Journal of Climate, 14(4), 615-628.
Webster, P. J., Holland, G. J., Curry, J. A., & Chang, H. R. 2005. Changes in tropical cyclone number, duration, and intensity in a warming environment. Science, 309(5742), 1844-1846.
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