```AUXILIARY MATERIAL
1. Recurrence interval calculation
We used two different approaches to calculate the recurrence interval of Hurricane Irene,
and conclude that the hurricane was potentially a 200-yr event. The first method utilized the
Extreme Precipitation Model [http://precip.eas.cornell.edu] for the region, which calculates the
24-hour intensity of a 200-yr event to be about 8 inches (Figure S1). The 24-hour rainfall
recorded on 28 August, 2012 at our study watershed was 21.9 cm or 8.6 inches.
Figure S1. 200-yr interval precipitation intensity for the study watershed – The observed
precipitation for 28 August was 8.6 inches.
The second method is flood recurrence interval calculation. This method is based on
rankings of annual peak discharges, and is not limited by the length of historic data. When we
apply the peak discharge observed during Hurricane Irene (29,283 cfs or 829 m3s-1) to the
recurrence interval regression line based on all previous peak discharges (Figure S2), we can
estimate that the studied event has a recurrence interval of 269 years.
Observed Annual Peak Discharge (1951-2010)
Annual Peak Discharge (cfs)
25000
y = 5199.4ln(x) + 190.88
R² = 0.9272
20000
15000
10000
5000
0
0
10
20
30
40
50
60
Recurrence Interval (yr)
Figure S2. Annual discharge vs recurrence interval regression for the sampling point. Recurrence
interval R is calculated as (N+1)/M, where R is recurrence interval, N is total observation, and M
is discharge rank in ascending order.
2. Sampling conditions
Below table lists the sample numbers and hydrologic conditions of the six storm events
monitored for this study as well as the number of monthly USGS samples that were collected
from 1993-2001. As it can be clearly seen from the range of discharge covered by our samples
and USGS samples, neither periodic sampling nor representative sampling for regular events can
provide adequate data set for predicting change in water chemistry during extreme events (Table
S1).
Table S1. Sample numbers and the observed discharge range of each monitored during this study.
Note that even the highest discharge seen from the regular event sampling (63.5 m-3 in May) is
less than 10% of the maximum discharge observed during Hurricane Irene (27 Aug – 31 Aug).
*Some post-storm samples were collected 5-8 hours after last samples in their auto-sampling
program.
Number of samples
16 May – 22 May
38 (DOC, TDN)
Discharge range
during sampling (in m3
s-1)
4.12 – 63.5
23 June – 27 June
18 (DOC, TDN)
1.37 – 4.43
4.5
18 July – 19 July
6 (DOC, TDN)
1.29 – 1.33
3
6 Aug – 10 Aug
20 (DOC, TDN)
0.99 – 1.17
4
2.5 – 829
3.5
27 Aug – 31 Aug
23 (DOC, TDN, DON)
Sampling
interval (in
hr)*
3
23 Nov – 25 Nov
7 (DOC, TDN)
2.83 – 8.95
4
Baseflow samples
10 (DOC, TDN)
2.72 -9.83
N/A
43 (TDN, DON), 25
0.16 – 21.8
N/A
USGS monthly
samples
(DOC)
3. Detailed description of the flux estimation model.
a.
Model 1 – This model simply interpolated between the 23 [DOC] and [DON]
measurements made during Irene to assign a concentration for each fifteen minute interval flow
measurement. The resulting concentrations were multiplied by the flow measurements then
summed to yield the five day flux. This flux estimate is considered to be most accurate and
serves as a reference to the other models.
b.
Model 2 – This model utilized LoadRunner with all available DOM concentrations
except the values recorded during Hurricane Irene as data input. All sub-daily concentrations
were converted into volume-weighted daily averages prior to running the model, and the
resulting regression model calculated daily fluxes of both DOC and DON based on the observed
daily average discharge. The premise of Model 2 and its data selection is in simulating a flux
estimation for an extreme event with historic data only. The following table shows the estimated
daily average concentrations of DOC and DON, and the daily discharge used for Model 2
Table S2. Daily discharge and estimated DOM concentrations used for Model 2. The
27 Aug,
2012
28 Aug,
2012
29 Aug,
2012
30 Aug,
2012
31 Aug,
2012
Avg. daily discharge in m3s-1
2.66
282
51.2
25.8
21.2
Estimated daily average [DOC]
in mg C L-1
Estimated daily average
[DON] in mg N L-1
1.23
1.89
1.62
1.52
1.50
0.081
0.06
0.074
0.078
0.078
c.
Model 3 – Model 3 used a log-linear regression that expresses flux as a function of
discharge, and incorporated all DOC and DON measurements made in 2011 and available
through USGS. This model is based on more measurements as it includes all sub-daily
concentrations, rather than the average daily values used in Model 2. However, Model 3 fails to
take account for any seasonality in flux-discharge relationship.
4. DOM flux to Ashokan Reservoir
Downstream from our sampling site, Esopus creek has an underground portal that connects
Schoharie reservoir with Ashokan reservoir. The water from the portal has been suspected as a source of
higher turbidity in downstream areas. Since our sampling site is upstream from the portal, our flux
calculation does not account for all DOC fluxes into the reservoir. In addition to the 165 km2 of our
forested study watershed, the reservoir also receives DOC flux from another 496 km2 of mostly forested
watersheds. Although we do not have water chemistry data to predict the DOC flux from these areas and
the portal, we here present a first order estimate of the total DOC flux to Ashokan Reservoir. The
presented estimate was calculated by applying the per-area DOC flux of our study watershed to the entire
catchment. Please note that this is a first-order estimate and only presented to portray the magnitude of the
5. Annual average discharge and DOM fluxes: 1993-2011
Figure S3. Annual average discharge and DOM fluxes for Esopus Creek, calculated by summing
all daily fluxes given by LoadRunner (incorporating all available [DOM] data including the
samples collected during Hurricane Irene)
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