Study Area and Data
Jessy Van Horn
Experimental and Methods
03/19/2014
Daily discharge data are gathered from the United States Geological Survey waterdata.usgs.gov)
for the Santa Fe River near Fort White, Florida (29°50'55" N, 82°42'55" W, gauge height 6.4
a.m.s.1), from 1932 to 2012The 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.
Jessy Van Horn
Experimental and Methods
03/19/2014
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
400
300
200
100
Monthly
Precipitation (mm)
flows and considerable variability.
0
J
D
F
M
A
M
J
J
A
S
O
N
Daily Discharge (m 3 s -1 )
70
60
50
40
30
0
30
60
90
120 150 180 210 240 270 300 330 360
Days since Dec. 1
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).
Jessy Van Horn
Experimental and Methods
03/19/2014
Station
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
Cedar Key
Crescent City
Cross City
Daytona Beach
Deland
Federal Point
Fernandina Beach
Gainesville Aiport
Gainesville UF
Glen St Marys
Hastings
High Springs
Island Grove
Jacksonville Airport
Jacksonville Beach
Jasper
Lake City
Live Oak
Madison
Mayo
Ocala
Palatka
Perry
St. Augustine
Starke
Steinhatchee
Usher Tower
Lat.
(°.' N)
29.08
29.26
29.39
29.11
29.04
29.44
30.39
29.41
29.39
30.16
29.43
29.50
29.27
30.30
30.17
30.31
30.11
30.17
30.32
30.03
29.11
29.39
30.08
29.54
29.56
29.43
29.25
Lon.
( °.' W)
83.02
81.31
83.10
81.03
81.17
81.32
81.28
82.16
82.21
82.11
81.30
82.36
82.06
81.42
81.24
82.57
82.36
82.58
83.26
83.10
82.08
81.39
83.34
81.19
82.06
83.18
82.49
First
Year
1932
1932
1948
1949
1932
1932
1932
1961
1932
1932
1978
1944
1947
1954
1944
1950
1932
1952
1932
1949
1932
1932
1932
1932
1958
1964
1956
Last
Year
1974
2009
2010
2010
2010
2010
2009
2010
1962
2010
2010
2009
1976
2010
2010
2010
2009
2010
2010
2009
2010
2001
2010
2010
1983
1995
2008
Percent
Complete
62.8
64.1
54.0
96.8
73.4
64.6
76.9
66.0
83.9
48.1
90.9
71.2
86.7
91.2
79.1
85.2
82.1
69.5
77.2
82.0
86.1
55.7
72.2
77.2
53.8
53.1
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 *******
100
80
60
40
20
2010
2000
1990
1980
1970
1960
1950
0
1940
Percent Stations Operating
Jessy Van Horn
Experimental and Methods
03/19/2014
Year
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, a t-test is runto determine whether the slope of the best-fit straight
line to each of the hydrometeorological time series is significantly different from zero. Discrete breaks are
found by using the non-parametric Mann-Whitney U test. First, a moving twenty-year window is passed
over the series testing for a difference in summed ranks of the former and latter decades. The twenty-year
Jessy Van Horn
Experimental and Methods
03/19/2014
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.
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.
Jessy Van Horn
Experimental and Methods
03/19/2014
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, 1930.
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.