This is a text-only version of the document "Spruce No 1 Mine - Recommended Determination - Appendix 2 - 2010". To see the original version of the document click here.

---

APPENDIX 2
Impacts to Water Quality and Wildlife ASE? 2 4 EW

Abstract

Additional mining would be likely to degrade instream water chemistry and biology in
the Coal River sub-basin. Many streams occurring in the Spruce Fork sub-watershed are
already listed by West Virginia Department of Environmental Protection (WVDEP) as
impaired. Results from existing mines show that additional mining would be likely to
increase adverse impacts to water quality and wildlife, especially from salts (e. g.
magnesium, bicarbonate, and sulfate) and selenium. It is notable that several stream
reaches inand around the Spruce No. l site (e. g., Oldhouse Branch, Pigeonroost Branch,
and White Oak Branch) are still judged to have high quality, based on biological and
water quality monitoring results. Valley fills and mining impacting these streams will not
only destroy some of the few remaining high quality streams in these watersheds, they
will reduce the input of freshwater that is currently mitigating the impacts of mine
effluent from elsewhere in the watershed to the Spruce Fork mainstem.

A2.1 Current Water Quality Impairments based on the 303(d) listings

Using the WVDEP 2008 West Virginia lmpaired by Pollutant GIS data, percent and total
stream impairments were calculated for the Coal River Sub-basin (HUC 8) and sub-
watersheds (HUC 12) that comprise the sub-basin( These stream impairments represent
segments that are on the 303(d) list, have a TMDL or need a TMDL, or are a Category
4(c) type and include all years for which data are available. ln Table 1, approximately
33% ofthe streams in the Coal River Sub-basin are considered impaired. The percentage
of streams that is impaired among sub-watersheds in the Coal River Sub-basin ranges
from 21% to 45%. Specifically, in the Headwaters Spruce Fork sub-Watershed, where
Spruce No. li is located, approximately 34% of the stream miles are impaired.


The streams in the headwaters of the Spruce Fork sub-watershed are listed as impaired
for biology, fecal, iron, and selenium (see Table 2). It should be noted that historically,
WVDEP has not consistently listed waters as impaired for ionic toxicity, even though
conductivity and associated salts are elevated in many streams (see further discussion
below). Please note that some sections of stream are listed for more than one type of
impairment. Furthermore, the 2008 West Virginia Integrated Water Quality Monitoring
and Assessment Report lists the causes for the most recent 303(d) listings as mining or
unknown and Category 4(0) as coal mining. For more details, see
http://www.dep.wv.gov/WW'E/WATERSHED/IR/Pages/default.aspx












Table 1. Impaired Waters in the Coal River Sub-basin (HUC 12 Scale)
Subwatershed{Namex   ; HtiG412=; aaea   aeaeae aeaa 3    aaa ea’a f i lmpaired.MiIes e»aa j Stream.Miles/4(NHDj.1_;24R)‘=. percentslmpaired:l;f
Headwaters Clear Fork
Outlet Clear Fork
Stephens Lake
Upper Marsh Fork
Middle Marsh Fork
Lower Marsh Fork
Spruce Laurel Fork
Headwa ters Spruce Fork
Outlet Spruce Fork
Upper Pond Fork
West Fork
Middle Pond Fork
Lower Pond Fork
Big Horse Creek
Upper Littte Coal River
Lower Little Coal River
White Oak Creek
Laure|Creek
Joes Creek-Big Coal River
Drawdy Creek-Big Coal River
Brier Creek
Fork Creek-Big Coal River
Smith Creek-Coal River
Browns Creek-Coal River
Coal
050500090101
050500090102
050500090201
050500090202
050500090203
050500090204
050500090301
050500090302
050500090303
050500090401
050500090402
050500090403
050500090404
050500090501
050500090502
050500090503
050500090601
050500090602
050500090603
050500090604
050500090605
050500090606
050500090607
050500090608
Su3hbasinName iss/ . isdr  KTQHUC..8>;1ifa rii"i  
05050009
30 51
27 27
25 19
61 61
41 31
29 60
24 51
39 55
47 61
17 83
33 32
19 39
25.49
21.76
53,99
22.63
13.00
42.20
46.18
36.99
8.96
18.90
38.97
16.44
743. 21
107 68
73 05
63 17
186 41
116 53
87 59
77 03
116 19
92 53
63 25
99 87
57 30
85.94
88.02
173.17
64.32
52.54
128.04
133.71
103.23
36.31
88.84
85.04
52.51
2232.27
28 33
37 33
39 ee
33 05
35 45
33 79
31 82
34 04
51 45
28 20
33 36
33 84
29.66
24.72
31.18
35.19
24.75
32.96
34.54
35.83
24.67
21.28
45.82
31.30
33.29


Table 2. Impairment type for waters in the Coal River sub-basin (HUC 12 Scale)






Subwatershed
Headwaters Clear Fork
Outlet Clear Fork
Stephens Lake
Upper Marsh Fork
Mnddle Marsh Fork
Lower Marsh Fork
Spruce Laurel Fork
Headwaters Spruce Fork
Outlet Spruce Fork
Upper Pond Fork
West Fork
Mnddle Pond Fork
Lower Pond Fork
Blg Horse Creek
Upper Luttle Coal Rlver
Lower Lnttle Coal Rlver
Whnte Oak Creek
Laurel Creek
Huc12
050500090101
050500090102
050500090201
050500090202
050500090203
§050500090204
050500090301
050500090302
5050500090303
3050500090401
050500090402
050500090403
1050500090404
3050500090501
050500090502
1050500090503
7§050500090601
050500090602
Joes Creek Bug Coal Ruver 050500090603
Drawdy Creek Blg Coal R|ver 050500090604
Brner Creek
Fork Creek Blg Coal R|ver
Sm|th Creek Coal R|ver
Browns Creek Coal Rnver
E050500090605
§_Q§0500090606
4 050500090607
1050500090608
117‘
lmpaurments (mules of streams)
|o Fecal LowFlow
164
0
102
206
59
52
20
29
6
4
7
57
79
47
24 8
3
146
449
9
207
490
66
206
296
342
5
390
64
305
228
239
440
3475
296
395;
284
32
2441
86
255
218
1
130
421
267
19 31
74
161;
175
2
Total
626
68
433
1138
706
477
305
662
845
3 8
630
426
3 6
54
860
226
260
837
776
649
79
89
506
222
Totals 27 4 223 4
*streams may have more than one impairment resulting in higher total calculations
456 5
481 3
336
203 337
12811












A2.2. TDS/Conductivity Data and Projections


2.2.1 Historical WI/DEP data describing water quality in the vicinity ofthe proposed
project area: ‘


Table 3 lists average conductivity and sulfate values for selected WVDEP sampling sites
on Spruce Fork, Pond Fork and the Little Coal River, including data for the streams
located at the proposed project area. These data indicate that levels of conductivity on
the mainstem of Spruce Fork, Pond Fork and the Little Coal River exceeded 500 |,LS/cm
almost every time WVDEP sampled these sites in 1997, 2002-2003, 2005 and 2008. A
recent study found that elevated conductivity greater than 500 |,tS/cm caused by alkaline
mine effluents was strongly associated with high probability of impairment to native
biota (Pond et al. 2008).




The US Army Corps of Engineers Huntington District (USACE) also reported
conductivity values as part of the baseline Water quality for Spruce Fork upstream and
downstream of the proposed project area in the EIS, for the proposed project (U.S. Army
Corps of Engineers Huntington District 2006, DEIS Spruce No. 1 Mine). The DEIS
reported that the minimum, average and maximum conductivity levels for Spruce Fork
upstream of the propose project area were 112, 656 and 1130 |,LS/cm at that time, `
indicating that on average the conductivity in Spruce Fork was already elevated to > 500
US/CID, and maximum conductivity levels exceeded twice that level.


Because mining has continued in these watersheds since sampling, the extent of mined
areas and the related pollutant inputs have probably continued to increase. Therefore,
these data, although somewhat dated, are likely representative of water quality in the
unmined tributaries. However, they may underestimate levels of pollutants on the
mainstems of Spruce Fork, Pond Fork and the Little Coal River, because more mining
has occurred in other tributaries since these data were collected.




The data also indicate that conductivity and sulfate levels of the streams draining the
proposed project area (i.e., Pigeonroost, Oldhouse Branch and White Oak Branch)
represent good to excellent water quality, and that pollutant levels of the streams draining
the nearby Dal-tex mine (i.e., Rockhouse Creek, Beech Creek, Left Fork Beech Creek,
Trace Branch) represent severely degraded water quality. The proposed project will
degrade the streams draining the project area, as well as contribute additional pollutants
to Spruce Fork, causing unacceptable adverse impacts to water quality and Wildlife
habitat.




















Table 3. Conductivity and sulfate values for selected sites on Spruce Fork, Pond Fork
and the Little Coal River (WVDEP data 1997-2003).
James Branch (at mouth)
Ellls Creek at mouth
Rockhouse Creek mile O 8
Tone Fork (at mouth)
Buffalo Fork at mouth)
Left Fork Beech Creek at mouth
Sen Creek (at mouth)
Avera e
Trlbs to Spruce Fork draining
S ruce No 1
Sen  Cam  Creek at mouth
Pl eonroost Branch (mile O 8)
Oldhouse Branch atmouth
Whlte Oak Branch m|le 0 5
nearb mmed areas
Rockhouse Creek (mile 0 8
same site as above)
Beech Creek at mouth
Left Fork Beech Creek (at mouth
same site as above
Trace Branch (at mouth)
Adkins Fork at mouth
S ruce Fork mainstem sites
S ruce Fork m|le O 3
S ruce Fork mlle O 5
S ruce Fork mile 4 6
Spruce Fork (mile 6)
Jul O2 l\/la O3
Jul O2 l\/la O3
Jul O2 Jun O3
Jun O2 l\/la O3
Jun O2 Ma O3
Jul O2 Jun O3
Jul O2 l\/la O3
Jul O2 l\/la O3
Jul O2 l\/la 03
Jul 02 l\/la 03
Jul 00 Dec OO
Jul 02 Jun O3
Jul 02 Jun O3
Jul O2 Jun O3
Jul O2 l\/la O3
Sep 97 Jul O2
l\/la O3
Sep 97 Jul O2
l\/la O3
l\/la O5
Sep 97 Jul 02 Jun
Jun O2
Stream Name (mile point) Period of Record n Cond/ Avg. Avg.
n Sulfate Conductivity Sulfate
(|.|S/cm) (mgll)
Tribs where WVDEP ndentsfied ionic f0XIClt as rima stressor
20
12/11
12/11
12/11
11/11
12/11
11/14
09
26
11/11
12/11
12/11
12/11
6
13/11
Q
12/12
12/13
1068
1012
1050
1226
2426
1012
1432
2426
4
1019
4
1019
_ 
 -Q 
 -- 
 - 
-_ _- 
Q Q 
 Q- 
_ 
 _ 
 _ 
 1 
Spruce Fork m|le 9 6
l\/la O8
1/1






Spruce Fork mile 11.4
Spruce Fork mile 14.4
Spruce Fork (mlle 17 2
Spruce Fork mlle
Spruce Fork mlle 18 5
Spruce Fork (mule 18 6
Spruce Fork mule 23 7
Pond Fork malnstem sltes
Pond Fork mlle O 3
Pond Fork (m|le O 4)
Pond Fork mlle 4 9
Pond Fork mule 6 3
Pond Fork (mule 9 0)
Pond Fork mule 12 6
Pond Fork mule 15 8
Pond Fork (mule 21 6)
Pond Fork mlle 24 4
Pond Fork mlle 26 6
Pond Fork (mlle 32 3)
Llttle Coal malnstem sltes
Llttle Coal Rlver (mule 0 2)
Little Coal Rlver mlle 3 6
Llttle Coal R|ver (mule 4 7)
Llttle Coal Rlver mule O 2
Llttle Coal Rlver mlle 16 5
Llttle Coal Rlver (mlle
Llttle Coal Rlver mlle 7 2
Llttle Coal Rlver mlle 7 8
Llttle Coal Rlver (mule 21 7)
Llttle Coal Rlver mlle 25 2
Jul-02-Jun-03
Jul-02-Jun-03
Sep 97
Au  O2 Ma O3
Se»97
Jul O2
Jul O2 Ma 03
Jul O2 Ma 03
Sep 97
Se  97
Jul O2 Ma O3
Sep 97
Jul O2 Ma O3
Jul O2 Ma O3
Jul O2 Ma O3
S60 97
Jul O2 Ma O3
Jul O2 Ma O3
Jul O2 Apr O3
Se 97
Jul O2 Apr 03
Jul 02 Ma O3
Jul O2 A r O3
Sep 97
Auv 02
Jul 02 A r 03
Jul 02 Apr 03
Jul O2 A r O3
12/12
12/11
11/10
12/11
11/11
11/11
0
12/11
12/11
12/11
12/11
0
0
0
0
0
20
11/0
685 196
1016
1028
1037
1114
1 030
1111
1165
n Cond/n Sulfate lndlcates the number of samples used to calculate the average values for
conductlvlty and sulfate
NA no VVVDEP data avallable for that Slte
Seng Camp Branch IS approx at Spruce Fork RM 17 5
Plgeonroost Branch IS approx at Spruce Fork RM 20 8
Oldhouse Branch IS approx at Spruce Fork RM 21 5
Whlte Oak Branch IS approx at Spruce Fork RM 24 6
 _ 
 ! 
 _ 
 _ 
 _ 
 _ 
 _ 
 H 
 _ 
 _ 
 _ 
 Q 
 _ 
 1 
 _ 












A2. 2.2 Predictions ofconductivity changes in Spruce Fork due to proposed project




The USACE reported baseline surface water quality sampling results for several mining
related water quality parameters, including conductivity and sulfate, on the main stem of
Spruce Fork upstream and downstream of the project area, and in the tributaries on the
proposed project area in the EIS for the proposed project (USACE 2006). Johnson et al.
(2010, in press) described a model to predict conductivity downstream of the confluence
of two tributaries using watershed area as a tributary weighting factor and conductivity


data from the two tributaries and validated this model using conductivity data from mined
Watersheds in southern W V.  


The weighted model incorporates watershed area and conductivity values from two
confluent tributaries such that: »
A Yij = di * Xa /(di + dj) + dj * X1/(<1i+ dj)




Where: y = downstream water chemistry value, i and j = contributing tributaries, xi =
water chemistry measurement on tributary i, di = drainage area of tributary i, xj = Water
chemistry measurement on tributary j, dj = drainage area of tributary j.


This model was used to predict pre-mining average and maximum conductivity levels in
Spruce Fork, downstream of the three tributaries on the project area, using measured
average and maximum pre-mining conductivity values for Spruce Fork upstream of the
project area, Oldhouse Branch, Pigeonroost Branch and Seng Camp Creek. These values
were obtained from the project baseline water quality data provided in the EIS, with the
exception of Oldhouse Branch (see Table 4). The pre-mining maximum conductivity
value reported for Oldhouse Branch (649 uS/cm) in the EIS seemed high based on the
premining values reported for Pigeonroost (318 uS/cm) and EPA and WVDEP historical
data for Cldhouse Branch. In order to prevent over estimation of the post-mining
conductivity level, we used a lesser value 159 uS/cm for the pre-mining maximum
conductivity level in Oldhouse Branch. This value is the maximum value for conductivity
at the mouth of Oldhouse of the 2002-2003 WVDEP data. The modeled pre-mining
average and maximum conductivity levels in Spruce Fork, downstream of Seng Camp
Creek, were compared to the actual measured average and maximum values at that
location to determine how well the model predicted pre-mining conductivity. The relative
percent difference (RPD) was calculated to quantify the difference between the measured
and predicted average and maximum values. RPD is calculated as the absolute difference
between the measured and predicted value divided by the average of the two values,
multiplied by 100:


Where ABS =
Post-mining cc


RPD = (ABS(X1 - X2))/((X1 +X2)/2))* 100


absolute value, X1 is the measured value, and X2 is the predicted value


mductivity was predicted using the measured pre-mining value for Spruce














Fork, upstream of Oldhouse Branch, and then estimating likely post-mining conductivity
values for the mined streams. We used 500 and 1000 |,LS/cm as post-mining average
values and 1000 and 1500 uS/cm for post-mining maximum values for the filled
tributaries as a conservative estimate of post-mining conductivity levels. These values
are conservative and likely underestimate the post-mining conductivity values. For _
example, when compared to Left Fork Beech Creek, which is completely mined and
filled, the average and maximum conductivity values are 2426 and 3000 uS/cm. In
Beech Creek, which is partially mined and filled, the average and maximum conductivity
values are 1432 and 1776 |,LS/cm (average and maximum values based on 2002-2003
WVDEP data).


We estimated watershed areas for the proposed project area for this model using GIS
techniques. Watersheds were delineated using the l:24,000 scale National Hydrography
Dataset (N HD) flowline stream segments between stream contluences and elevation data
depicted in a digital elevation model (DEM) for the National Elevation Dataset (NED),
following established practices and mapped segment level watersheds through various
hydrological modeling tools available in ArcGIS. The NHD segment-based tabular
stream tlow data were used to develop a network of the watershed’s flow connectivity, to
assign attributes to the watersheds based on the stream’s NHD reach code, and to
construct a watershed-based flow table to approximate the tlow network between
watersheds. These datasets allow for the analysis of many watershed network-based
analyses, including identification of watersheds upstream or downstream from a given
location. This information is packaged in an ArcGlS toolbox which was used to calculate
the upstream contributing areas of the points of interest (Strager et al. 2009).


Johnson et al. (2010, in press) noted that model error for conductivity showed a general
increase with increasing conductivity and error tended to be greater for mined
contluences where conductivity values were greater than 1000 uS/cm. USEPA observed
(Green et al. 2000) and hydrologic studies by the U.S. Geological Survey confirmed that
valley-filled streams have higher flows when compared to unmined streams in West
Virginia (Messinger and Paybins, 2003; Wiley et al., 2001). This increase in basetlow
may introduce error inrthese post mining conductivity estimates since We assume the
watershed areas (a surrogate for stream flows) remain constant pre and post mining. If
flows increase post mining, the total loading of pollutants could also increase out of the
mined Watersheds, and the modeled downstream conductivity predictions may actually
underestimate the true post mining conductivity levels. Accordingly, the model
prediction is conservative.


The modeled and measured pre-mining average (555 |,tS/cm modeled, 570 uS/cm
measured) and maximum (961 |.LS/cm modeled, 1080 uS/cm measured) conductivity
values in Spruce Fork, downstream of Seng Camp Creek, were similar. The RPD fort
average values was 2.7% and the RPD for the maximum values was l1.7%. The
modeled values underestimated the measured values, and the RPD was larger for the


maximum values compared to the average values


Post-mining conductivity levels in Spruce Fork downstream of the project area were














modeled using two post-mining average (500 and 1000 uS/cm) and maximum (1000 and
1500 uS/cm) conductivity values for Oldhouse Branch, Pigeonroost Branch and Seng
Camp Creek post mining. Based on the in-stream conductivity levels in Left Fork Beech
Creek and Beech Creek these values are conservative (see above). In every case, since
the measured conductivity levels in Spruce Fork are already greater than 500 uS/cm pre-
mining, the modeled post-mining conductivity values are also greater than 500 uS/cm
(see Table 4 and Figure l). ’


Construction of valley fills, sediment ponds, and other discharges authorized by DA
Permit No. 199800436-3 (Section l0: Coal River) will likely further degrade the water
quality of the mainstem of Spruce Fork. Even if the post-mining conductivity is managed
to be 500 uS/cm in the three tributaries located on the project area, which is the scenario
with lowest conductivity levels presented here, the conductivity levels in the mainstem of
Spruce Fork downstream of the project area will increase from 555 uS/cm on average
pre-mining to 615 uS/cm on average post-mining.


Table 4. |\/|<>de|ed <%
Spruce Fork upstream of
Oldhouse Branch
Oldhouse Branch
Pi eonroost Branch
Sen  Cam  Branch
Spruce Fork downstream
of Sen  Cam  Branch
Spruce Fork upstream of
Oldhouse Branch
Oldhouse Branch
Pi eonroost Branch
Sen  Cam  Branch
Spruce Fork downstream
of Sen  Camp Branch


juctivity downstream of propeeé
minin 
Pre Nlmm  Pre l\A|n|n 
Modeled Measured
Av S/cm
Max pS/om
1130
Conductivit * Conductivit *
_
Ill
_
  `;`, ",` ' _ '~_V  
   .1   1080




E project area




Post Mining


Conductivity


  Nlodeled




“ Avg HS/cm


'__




  500


   5oo 


  500




I;


|\/|a>aJ§Z:m


1130


1000


0 1000


1000 


 09 f?L




pre & post




Post mining


Conductivity


Modeled


_____,_______


[”AU§Q§Iéhi




1 OOO
1 O00


7999
 




Max US/cm


1130


1 500


'I 500


  1500


 






* Measuredvaiues taken from Spruce
monitoring data.
** This maximum value was taken from


Input value - measured except where
noted**






No. 1 EIS baseline water quality


2002-2003 vv\/DEP data for Oldhouse Branch




 ! 
 












































Figure 1. Maps indicating modeled average and maximum pre and post-mining
conductivity in Spruce Fork, downstream of Seng Camp Creek. Blue values were
measured values taken from the Spruce EIS. Green values were modeled values. Yellow
values were inputs to the model to estimate post-mining conductivity in the tributaries.


A. shows average conductivity pre~mining. B. shows maximum conductivity pre-mining
C. shows average conductivity post mining assuming 500 uS/cm average in the filled
tributaries. D. shows maximum conductivity post mining assuming 1500 uS/cm
maximum in the filled tributaries.


L N
Spruce No 1 Mme Nl-\D24kHydro
A Average Conductlvlty pre mmmg
@»f~f»_»;,@~»>5, ;¢¢~¢. ,V A/ 'ee/' \
<“°”3f5” Q3 ,ef ef”
,gf "2 /;}¢j“,@ “www
%~f% /TQ »=  ”@">§ »,
W@“€“§»ff5 “f;`;§§éS ag % "5 rf “aw” W
(6 £&§& / *’§§""£'~£f'$%$e $5 *Q* %'>@a?“’
,»
-ff, e g ge f ”f§"3€§i%  re:    §§\* ,mf ,ei § a
we ,gsx be °#’t/,,¢_¢%¢p§¢!/@4x»_<;‘§=~ff$;0 yew'
3% we QW ef' >"é§/g, §Q see ,.-
5 ‘”2;’£¢;, ‘fév # ® ~§»?';;§°é"   /( $321 Q
ef, fe -°>,~§"' Q fe ef
e f  e ; »; ir iie hi  “ fe w M2  5% *H Q
Kiev fee?/z‘*§)  2555? f e f/?;e\
WW /  Qéd ff  J§”%~»?4§£* §‘§§f`§<»é§<’~§’
Y$a@,,   ;;g§¢1,®”"’§§7§§@>r' ‘~‘Y L?
K if ef @~ ®é§>»e»
"?"~y/#if  x W *se W5'/I
 »e'§»;,~ f*e§@‘if“  eaw
1/  w  ‘,§,§»»  iégéz gég
ie “Q  2¢ f “ggi
QQ if/k ”/@’% /1 § éxe
V
W  £6 J§§ f »§&
>@©  ef ee EW  i m
www
4 ,yy M ,
W  w wf; e§§§;» , ,ey
gw,  ,fé w 45,-»  52
‘W
>§’4‘>§i¥§i°f<”" & W 
ee @§@» 
W MW
Tra ce Brangh
Oldhouse Branch
\
x
Ifélometers 1 1
0 D 5 1 2 ,
Mxies
\
Q Q
af , ,» Dal Tex Mme Complex *w WV Countzes
, x
‘ /
‘§§‘
J s
>
ei
P59520
flrgost
Bran L_
h
Whlte Oak Branch
»
\
~..
»@?3e\»,A
Bonne (`o
lnqan Co
Spruce
No 1 Mme
-`
/
\" >
2/
f /\
l//§