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## Piñon Ridge Made by 

## GG Job No 

## 073

- 81694

Water Balance Calculation Checked by 

## KFM Date 

## 5/7/2010

Tailings Cell Approved by 

## KFM Sheet No 

## 1 of 7

INTRODUCTION

Golder Associates Inc. (Golder) has prepared this revision of the Tailings Cell Water Balance for Energy

Fuels Resources Corporation (EFRC) for the Piñon Ridge Project located in Montrose County, Colorado.

Calculations in this document were based on the water balance originally submitted as a part of the tailings

cell design by Golder (2008a) for Tailings Cell A (see Figure B -1)

. For completeness, input parameters and

assumpti ons used by Golder (2008 a ) as well as more recent modifications to the design parameters are

summarized below.

ASSUMPTIONS AND WATER BALANCE COMPONENTS

Since three tailings cells (A, B, C) of approximately equal tailings storage volume and dimensions have been

designed for the Piñon Ridge Project to meet a total capacity of approximately 7.3 million tons, the

probabilistic water balance has been performed for Tailings Cell A only (see Fig ure B

- 1). The water balance

for Tailings Cells B and C will be similar to that of Tailings Cell A. Each of the tailings cells is designed for

approximately 14 years based on a milling capacity of 500 tons per day (tpd).

T he following water balance components were considered: (1) the amount of water entering Tailings Cell A

from the mill [ revised quantities were 

## developed by CH2M Hill (200 9 ) and are summarized in Figure B

2] ; (2) water entering the system through meteoric precipitation; (3) the amount of water released to the

atmosphere through evaporation; (4) the amount of water returning to the mill from Tailings Cell A (as

provided by 

## CH2M Hill and summarized in Figure B -2 ); and (5) the excess water available to be pumped

from the tailings cell. 

## As sh own in Figure B -2 , the volume of raw water entering the process plant

averages 130 gpm. This flow rate is less than the total of 141 gpm required for operations, which

also include non-processing uses such as dust suppression and truck washing.

Precipitation values are likely to exhibit the largest variations, and were therefore treated as stochastic inputs

(i.e., probabilistic), while the other parameters were treated as deterministic variables. Water balance

calculations were performed using the computer program Goldsim TM. The water balance model was run for

a time of operation of 14 years assuming a milling rate of 500 tpd.

The water balance model was based on the following equation:

∆ S = (Q + P)

– (E + RW + EW)

where:

∆ S = change in stored solution volume

Q = inflow from the mill

P = precipitation collected within the lined footprint of the tailings cell

E = evaporation from the tailings cell surface

RW = reclaimed water from the tailings cell pumped back to the mill

EW = excess water not required by the mill but available to be pumped from the tailings

cell

INPUT PARAMETERS

Water balance assumptions and sources of input data are summarized in Table 1.c:\ users \ kglaspey \ appdata \ local \microsoft\ windows \ temporary internet files \ content.outlook \ s56hzgbq \ attachment b text

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## Piñon Ridge Made by 

## GG Job No 

## 073

- 81694

Water Balance Calculation Checked by 

## KFM Date 

## 5/7/2010

Tailings Cell Approved by 

## KFM Sheet No 

## 2 of 7

Table 1 . Water Balance Model Assumptions

Property Value Source Comment/Assumptions

Dimensions for

Tailings Cell A 725 feet (ft) x

1,847 ft

(maximum

dimensions) See Figure B

- 1 Designed as two cells within Tailings Cell A

with a divider berm constructed at elevation

5,500 ft and with two independent leak

collection and recovery systems (L CR S) and

tailings underdrain systems. Internal side

slopes of 3H:1V with minimum base grade of

one percent (%) and 3 ft of dry freeboard.

Watershed Area for

Tailings Cell A 32.5 acres Golder (2008 a ) Golder design assumptions. The watershed

area includes the lined area and the area for

the access road (due to slope inward toward

cell)

. Tailings Disposal

Rate 500 tpd CH2M Hill

(2009)

(see Note 2 and

Figure B -2) Use disposal rate of approximately 500 tpd

(41,500 lb/hr) to achieve design flow of 252

gpm (tailings + raffinate)

.

Specific Gravity of

Solids 2.69 CH2M Hill

(2009)

(Note 1)

Solids Content 27.3% CH2M Hill

(2009)

(Note 1)

Average In

- Place

Tailings Dry Density 95 pounds per

cubic foot (pcf) Golder (2008 a )

Beach Slope 2 and 0.5 % Golder (2008 a ) Compound slope with 2% for approximately

500 ft in the perimeter sand zone and 0.5% in

the slimes zone.

Pumping Rate (from

Tailings Cell A to

mill) 187 gpm CH2M Hill

(2009)

(see Note 2 and

Figure B

- 2 ) Design return volume flow from Tailings

Cell A to the mill

Percentage of

Tailings Beach that is

wet 100% CH2M Hill

(2009) & Two

Lines (2009)

(Note 2) Water sprays used in summer months to

maintain saturation.

Percentage of

Tailings Area

Covered With Bird

Balls 50% CH2M Hill

(2009) & Two

Lines (2009)

(Note 2)

Climate Data Varies Attachment 1 Use climate date for Uravan

(NCDC No. 058560)

Annual Pan

Evaporation 55 to 60 inches See Attachment 1

– Figure 10 Use pan factor of 0.7 to estimate Tailings

Cell A evaporation

Notes:

1. Based on CH2M Hill (200 9).

2. Based on CH2M Hill (200 9 ) and Two Lines (2009).c:\ users \ kglaspey \ appdata \ local \microsoft\ windows \ temporary internet files \ content.outlook \ s56hzgbq \ attachment b text

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## KFM Date 

## 5/7/2010

Tailings Cell Approved by 

## KFM Sheet No 

## 3 of 7

The evaluation of climate data conducted by Golder for nearby weather stations indicates that the Uravan

weather station is likely to provide reasonable precipitation estimates ( s ee Attachment 1). The average

monthly precipitation values for the Uravan weather station are summarized in Table 2.

The Hargreaves (1985) method, as discussed in Allen et al. (1998), was used to estimate monthly evaporation

value s at the Piñon Ridge site, based on the available climate data from the Uravan weather station (i.e.,

precipitation, air temperature, etc.). The calculated pan evaporation values were scaled by a factor of 0.7 to

represent tailings cell evaporation. Monthly evaporation values used for the water balance calculations are

summarized in Table 2

.

Table 2. Monthly Precipitation and Evaporation Values

Month Average*

Precipitation

(inches) Minimum*

Precipitation

(inches) Maximum*

Precipitation

(inches) Tailings Cell A

Evaporation

(inches)

January 0.88 0 3.19 0.8

February 0.76 0 2.05 1.2

March 1.03 0 3.43 2.2

April 1.01 0.03 2.68 3.3

May 0.94 0 2.85 4.8

June 0.48 0 1.65 5.8

July 1.19 0.09 3.54 6.3

August 1.36 0.18 3.32 5.4

September 1.5 0.06 4.78 3.8

October 1.51 0 5.89 2.5

November 1.05 0 2.39 1.2

December 0.88 0.03 3.55 0.7

* Precipitation values obtained for Uravan weather station from 1961 to 2007

.



### Based on design

- level process water balance information provided by CH2M Hill (2009) and summarized in

Table 1 and Figure B -2 ( with average flow values correspond ing to a milling rate of 500 tpd), the design

mass of solids discharging from the mill to the tailings cell is approximately 41,500 lb/hr.

As described in Table 1 , Tailing Cell A has been designed as essent ially two ponds (Cells A1 and A2) within

a pond (Figure B- 1). For simplicity in modeling, the tailings cell water balance was developed assuming that

Cell A2 will be filled first to its maximum storage capacity prior to initiating tailings slurry discharg e flow to

Cell A1. Once both sub

- cells are filled to the mid

- height bench level, tailings slurry will then be discharged

into the entire tailings cell. Tailings slurry will be discharged from several positions around the perimeter of

the tailings cells.

Per the design criteria, it was assumed that 3 ft of dry freeboard will be maintained at all times to avoid

overflow of the tailings cell solution. Solution will only be reclaimed from the tailings cell pool and returned

to the mill when water pool dep th is 5 ft or greater (the lowest assumed water depth for barge pumping

operation)

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## Piñon Ridge Made by 

## GG Job No 

## 073

- 81694

Water Balance Calculation Checked by 

## KFM Date 

## 5/7/2010

Tailings Cell Approved by 

## KFM Sheet No 

## 4 of 7

DEVELOPMENT OF STOCHASTIC PRECIPITATION PARAMETERS

In order to develop the stochastic precipitation input for the Goldsim model, continuous probability

distributions were calibrated against the available monthly precipitation data from the Uravan weather

station. The Weibull distribution was selected due to its flexibility to represent a wide range of values. The

distribut ion is truncated at its lower end and has a long tail to the upper end, making it well

- suited to

modeling extreme positive values, such as precipitation events with longer return periods. Separate Weibull

distributions were fitted to non

- zero precipitatio n records collected for each month. A moment estimation

method was used to determine distribution parameters resulting in fitting coefficients summarized in Table 3.

Table 3 . Weibull Distribution Parameters

Month Slope Parameter

(-) Mean Minus Minimum*

(inch/month)

January 1.49 0.78

February 1.35 0.71

March 1.27 0.97

April 1.32 0.93

May 1.13 0.89

June 0.98 0.44

July 1.57 1.09

August 1.51 1.28

September 1.28 1.39

October 1.25 1.46

November 1.75 0.98

December 1.48 0.76

* Minimum monthly precipitation was set to 0.1 inches per month for all Goldsim simulations.



### To verify the adopted probability distributions, a precipitation model was constructed in Goldsim TM and

allowed to run for a 1

- year period using Monte

- Carlo sampling with 1,000 realizations. Goldsim results are

compared against recorded values for the Uravan weather station in Figures B -3 to B-14 for the months of

January through December, respectively, with annual totals in Figure B-15

. Goldsim results show favorab le

agreement between the measured and calculated extreme values on both a monthly and an annual basis.

WATER BALANCE RESULTS

The adequate pool volume and additional volume of water available for reclaim were evaluated at different

stages of Tailings Cell A development assuming a maximum time of operation of 14 years corresponding to

a milling rate of 500- tpd. Goldsim calculations were based on the stochastic monthly precipitation records

generated using Weibull’s distribution parameters pres ented in Table 3 , and illustrated in Figures B -3

through B-14.c:\ users \ kglaspey \ appdata \ local \microsoft\ windows \ temporary internet files \ content.outlook \ s56hzgbq \ attachment b text

- wbcalc

- 07may2010 (2).docx Subject 

## Piñon Ridge Made by 

## GG Job No 

## 073

- 81694

Water Balance Calculation Checked by 

## KFM Date 

## 5/7/2010

Tailings Cell Approved by 

## KFM Sheet No 

## 5 of 7

The 1 in 1,000 year reoccurrence storm event was modeled to estimate the pool volume and additional

volume of water available for reclaim as follows:



# ( ) n 

### pyprobabilit Cumulative

−−= 11

,

where

p = annual probability of occurrence

n = number of years to evaluate

Thus, the probability that the 1,000

- year storm event will occur during the 14

- year tailings disposal period

for a 500- tpd milling rate is approximately 1.4%. Based on this probability of occurrence, t he estimated pool

volume capacity for Tailings Cell A was estimated for the 98.6 th 

### percentile probability . A Monte

- Carlo

simulation with 5,000 realizations (due to relatively high target probabilities in Monte Carlo simulations) was

used to evaluate the 98.6 th 

### percentile quantities after 1, 2, 5, 7 and 14 years of operation.

Table 4 summarizes the probabilistic tailings cell pool volume during operations for the median and 98.6 th



### percentile results at various points in time. As shown, the difference between the median value and the 98.6 th



### percentile result is small , with the pool volume generally increasing during production

. The reason for the

increase in tailings pool volume is directly related to the increase in tailings area durin g operations, with the

tailings beach main tain ing saturation and the minimum depth of water over tailings to enable pumping ( set to

a constant value of 5 feet). These results are illustrated graphically in Figure B -16.

Table 4 . Probabilistic Tailings Ce ll Pool Volumes

Probability Unit Tailings Cell Pool Volume at Different Times of Operation

Year 1 Year 2 Year 5 Year 7 Year 14

98.6 th



### percentile ft 3 

### 1,140,490 1,767,720 3,636,150 5,200,970 7,990,870

Acre

- ft 26.2 40.6 83.5 119.4 183.4

Median ft 3 

### 1,140,490 1,767,720 2,811,930 4,584,920 7,697,730

Acre

- ft 26.2 40.6 64.6 105.2 176.7

* The model was run for a time of operation of 14 years and a milling rate of 500 tpd.



### Table 5 presents data for the probabilistic cumulative excess water volume available during operations for

the median and 98.6 th 

### percentile res ults at various points in time. These results are shown graphically in

Figure B -19

. Based on the median results, a nominal increase in excess water occurs until the beginning of

Year 5 ( approximately 50 months) , from which point the excess volume of water is relatively constant.c:\ users \ kglaspey \ appdata \ local \microsoft\ windows \ temporary internet files \ content.outlook \ s56hzgbq \ attachment b text

- wbcalc

- 07may2010 (2).docx Subject 

## Piñon Ridge Made by 

## GG Job No 

## 073

- 81694

Water Balance Calculation Checked by 

## KFM Date 

## 5/7/2010

Tailings Cell Approved by 

## KFM Sheet No 

## 6 of 7

Table 5 . Probabilistic Cumulative Excess Water Volumes Available from the Tailings Cell

* The model was run for a time of operation of 14 years and a milling rate of 500 tpd.



### Table 6 summarizes the probabilistic average excess pumping rate from the tailings cell (above the design

rate of 187 gpm) during operations for the median and 98.6 th 

### percentile results at various points in time. This

information is presented graphically in Figure B -18

. T he volume of water available as excess decreases to

nearly negligible amounts by Year 3 based on the median and 98.6 th 

### percentile results

. Due to the smaller

footprint of tailings placed early on during operations, the volume of water available for pumping is likely

greater as it takes less water to achieve increased water depth (above 5 feet)

.

Table 6 . Probabilistic Average Excess Pumping Rates

Probability Unit Probabilistic Average Excess Pumping Rates at Different Time

Intervals of Operation

Years 0 -1 Years 0 -2 Years 3 -5 Years 6 -7 Years 8 -14

98.6 th



### percentile gpm 16.4 16.4 1.7 1.8 1.2

Acre

- ft /yr 26.5 26.5 2.7 2.9 1.9

Median gpm 2.1 2.1 0.6 0.0 0.0

Acre

- ft /yr 3.4 3.4 1.0 0.0 0.0

SUMMARY

The stochastic water balance model for the 500- tpd milling rate indicates that a maximum tailings cell pool

volume of approximately 7 .99 million ft 3 

### (Mft 3 

### ) (i.e., 183.4 acre

- ft) is obtained for the 98 .6 th 

### percentile (i.e.,

1,000- year storm occurs during deposition), with a median pool volume of 7.70 Mft 3 

### (176.7 acre

- ft) (Figure

B-16) . At all times during operations, a minimum excess volume capacity of 3.94 Mft 3 

### (90.4 acre

- ft) of

freeboard volume (corresponding to 3 ft of dry freeboard) will be available to prevent overtopping during

tailings deposition.

As demonstrated on Figure s B-18 and B-19 , the volume of excess water available as make

- up (in excess of

the design return volume flow to the mill) is essentially negligible after approximately 4 years (50 months)

. The average excess pumping rates available to pump excess water from the tailings cell at different time

intervals of the operation are summarized in Table 5 . Results were estimated assuming that the mill will

have a pumping rate of 187 gpm available to pump back reclaimed water from the tailings cell to the mill

(per CH2M Hill [2009] as illustrated in Figure B -23 ), and that the available excess water can be: ( 1) pumped

back to the mill where the water could be used as make -up water; or (2) discharged into the evaporation pond

system. It should be noted that the design raffinate flow rate to the evaporation ponds, provided by CH2M

Probability Unit Probabilistic Cumulative Excess Water Volumes Available from the

Tailings Cell at Different Times of Operation

Year 1 Year 2 Year 5 Year 7 Year 14

98.6 th



### percentile ft 3 

### 740,432 1,561,560 6,291,930 8,015,720 14,640,000

Acre

- ft 17.0 35.8 144.4 184.0 336.1

Median ft 3 

### 305,920 761,941 4,064,210 4,064,210 4,535,010

Acre

- ft 7.0 17.5 93.3 93.3 104.1c:\ users \ kglaspey \ appdata \ local \microsoft\ windows \ temporary internet files \ content.outlook \ s56hzgbq \ attachment b text

- wbcalc

- 07may2010 (2).docx Subject 

## Piñon Ridge Made by 

## GG Job No 

## 073

- 81694

Water Balance Calculation Checked by 

## KFM Date 

## 5/7/2010

Tailings Cell Approved by 

## KFM Sheet No 

## 7 of 7

Hill, is an average value which already accounts for this potential excess flow from the tailings cells durin g

discrete time intervals.

As shown on Figure B-17 , a design return volume flow of 187 gpm might not be achievable at some time

intervals over the design life of the tailings cell. The excess water available from the tailings cell during wet

times, ther efore, can be used to accommodate this need during the dry times. As demonstrated by the water

balance, the mill is designed to maximiz e reclaim and re -use of water to the mill for processing.

A separate water balance has been developed to size the evaporation pond system (i.e., aerial extent) for the

Piñon Ridge Project, as presented in Golder (2008b) . The evaporation pond water balance was performed

based on a design process water inflow (raffinate from the mill) to the evaporations ponds of 63 gpm for 500

tpd milling operations. As shown in Figure B -2 , the design flow rate to the evaporation ponds has reduced

nominally to 53 gpm. In effect, the volume of raffinate flowing from the mill to the evaporation ponds will

be disposed of via evaporation.

REFERENCES

Allen, R.G., Pereira, L.S., Raes, D. and Smith, M., 1998, “ FAO Irrigation and Drainage Paper No. 56

– Crop Evapotranspiration ” (latest revision 2002)

.



## CH2M Hill Engineers, Inc

. (CH2M Hill) , 2009, “ Basic Engineering Report and Cost Estimates,

Piñon Ridge Project, Naturita, Colorado .” 4 February 2009.

Hargreaves, G.L., Hargreaves, G.H., and Riley, J.P., 1985, "Agricultural benefits for Senegal River Basin",

Journal of Irrigation and Drainage Engrg , ASCE 111:113-124.

Golder Associates Inc. (Golder), 2008 a, “ Tailings Cell Design Report

, Piñon Ridge Project

, Montrose

County, Colorado ,” October.

Golder Associates Inc. (Golder), 2008b, “ Evaporation Pond Design Report, Piñon Ridge Project, Montrose

County, Colorado ,” October.



## Two Lines, Inc., 2009, “ Estimation of Radiation Doses to Members of the Public from the Piñon

Ridge Mill ,” Report prepared for Energy Fuels Resources Corporation, November.

### May 2010 073-81694

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## FIGURESProcessPlant12gpmVENTS130gpmRAWWATER53gpmVANADIUMSXRAFFINATEEVAPORATIONPONDSTAILINGSCELLS252gpmTAILINGSPLUSVANADIUMSXRAFFINATE187gpmRETURNWATER65gpm53gpmEVAPORATIONEVAPORATIONGG May-10 073-81694KFM AS SHOWN N/AKFMFiguresB-rev6May2010.xlsmFIGURE B-2BALANCE FLOW RATES FOR 500-TPD PRODUCTIONENERGY FUELS RESOURCES CORPORATIONPIÑON RIDGE PROJECTProcessPlant12gpmVENTS130gpmRAWWATER53gpmVANADIUMSXRAFFINATEEVAPORATIONPONDSTAILINGSCELLS252gpmTAILINGSPLUSVANADIUMSXRAFFINATE187gpmRETURNWATER65gpm53gpmEVAPORATIONEVAPORATIONBALANCELEGEND:NOTES:1. Balanceflowsprovidedarefor500tpd operationsandareaveragevalues.2. RefertofigureB‐2foreffectsofprecipitationonthewaterbalance.3. FlowvaluesfromCH2MHill(2009).0 050.10.150.20.250.3

Probability DensityJanuary Data Histograms withWeibull DistributionFit to Uravan Historical PrecipitationDataWeibull DistributionGoldisim ValuesData ValuesGG May-10 073-81694KFM AS SHOWN N/AKFM FIGURE B-3ENERGY FUELS RESOURCES CORPORATIONPIÑON RIDGE PROJECTURAVAN DATA, GOLDSIM RESULTS AND WEIBULL DISTRIBUTION FORJANUARY00.050.10.150.20.250.3 -0.13 0.13 0.38 0.63 0.88 1.13 1.38 1.63 1.88 2.13 2.38 2.63 2.88 3.13 3.38 3.63 3.88 4.13 4.38 4.63 4.88 5.13 5.38 5.63 5.88 6.13 6.38 6.63 6.88 7.13 7.38 7.63 7.88 8.13 8.38 8.63

Probability DensityData ValueJanuary Data Histograms withWeibull DistributionFit to Uravan Historical PrecipitationDataWeibull DistributionGoldisim ValuesData Values0.050.10.150.20.250.3

Probability DensityFebruary Data Histograms with WeibullDistribution Fit to Uravan HistoricalPrecipitation DataWeibull DistributionGoldisim ValuesData ValuesGG May-10 073-81694KFM AS SHOWN N/AKFMFiguresB-rev6May2010.xlsmFIGURE B-4URAVAN DATA, GOLDSIM RESULTS AND WEIBULL DISTRIBUTION FORFEBRUARYENERGY FUELS RESOURCES CORPORATIONPIÑON RIDGE PROJECT00.050.10.150.20.250.3 0.00 0.25 0.50 0.75 1.00 1.25 1.50 1.75 2.00 2.25 2.50 2.75 3.00 3.25 3.50 3.75 4.00 4.25 4.50 4.75 5.00 5.25 5.50 5.75 6.00 6.25 6.50 6.75 7.00 7.25 7.50 7.75 8.00 8.25 8.50 8.75

Probability DensityData ValueFebruary Data Histograms with WeibullDistribution Fit to Uravan HistoricalPrecipitation DataWeibull DistributionGoldisim ValuesData Values0.050.10.150.20.25

Probability DensityMarch Data Histograms with Weibull Distribution Fit to Uravan HistoricalPrecipitation DataWeibull DistributionGoldisim ValuesData ValuesGG May-10 073-81694KFM AS SHOWN N/AKFMFiguresB-rev6May2010.xlsmFIGURE B-5URAVAN DATA, GOLDSIM RESULTS AND WEIBULL DISTRIBUTION FORMARCHENERGY FUELS RESOURCES CORPORATIONPIÑON RIDGE PROJECT00.050.10.150.20.25 0.00 0.25 0.50 0.75 1.00 1.25 1.50 1.75 2.00 2.25 2.50 2.75 3.00 3.25 3.50 3.75 4.00 4.25 4.50 4.75 5.00 5.25 5.50 5.75 6.00 6.25 6.50 6.75 7.00 7.25 7.50 7.75 8.00 8.25 8.50 8.75

Probability DensityData ValueMarch Data Histograms with Weibull Distribution Fit to Uravan HistoricalPrecipitation DataWeibull DistributionGoldisim ValuesData Values0.040.060.080.10.120.140.160.180.2

Probability DensityApril Data Histograms with Weibull Distribution Fit to Uravan HistoricalPrecipitation DataWeibull DistributionGoldisim ValuesData ValuesGG May-10 073-81694KFM AS SHOWN N/AKFMFiguresB-rev6May2010.xlsmFIGURE B-6URAVAN DATA, GOLDSIM RESULTS AND WEIBULL DISTRIBUTION FORAPRILENERGY FUELS RESOURCES CORPORATIONPIÑON RIDGE PROJECT00.020.040.060.080.10.120.140.160.180.2 0.00 0.25 0.50 0.75 1.00 1.25 1.50 1.75 2.00 2.25 2.50 2.75 3.00 3.25 3.50 3.75 4.00 4.25 4.50 4.75 5.00 5.25 5.50 5.75 6.00 6.25 6.50 6.75 7.00 7.25 7.50 7.75 8.00 8.25 8.50 8.75

Probability DensityData ValueApril Data Histograms with Weibull Distribution Fit to Uravan HistoricalPrecipitation DataWeibull DistributionGoldisim ValuesData Values0.050.10.150.20.25

Probability DensityMay Data Histograms with Weibull Distribution Fit to Uravan HistoricalPrecipitation DataWeibull DistributionGoldisim ValuesData ValuesGG May-10 073-81694KFM AS SHOWN N/AKFMFiguresB-rev6May2010.xlsmFIGURE B-7URAVAN DATA, GOLDSIM RESULTS AND WEIBULL DISTRIBUTION FORMAYENERGY FUELS RESOURCES CORPORATIONPIÑON RIDGE PROJECT00.050.10.150.20.25 0.00 0.25 0.50 0.75 1.00 1.25 1.50 1.75 2.00 2.25 2.50 2.75 3.00 3.25 3.50 3.75 4.00 4.25 4.50 4.75 5.00 5.25 5.50 5.75 6.00 6.25 6.50 6.75 7.00 7.25 7.50 7.75 8.00 8.25 8.50 8.75

Probability DensityData ValueMay Data Histograms with Weibull Distribution Fit to Uravan HistoricalPrecipitation DataWeibull DistributionGoldisim ValuesData Values0.10.150.20.250.30.350.40.45

Probability DensityJune Data Histograms with Weibull Distribution Fit to Uravan Historical PrecipitationDataWeibull DistributionGoldisim ValuesData ValuesGG May-10 073-81694KFM AS SHOWN N/AKFMFiguresB-rev6May2010.xlsmFIGURE B-8URAVAN DATA, GOLDSIM RESULTS AND WEIBULL DISTRIBUTION FOR JUNEENERGY FUELS RESOURCES CORPORATIONPIÑON RIDGE PROJECT00.050.10.150.20.250.30.350.40.45 0.00 0.25 0.50 0.75 1.00 1.25 1.50 1.75 2.00 2.25 2.50 2.75 3.00 3.25 3.50 3.75 4.00 4.25 4.50 4.75 5.00 5.25 5.50 5.75 6.00 6.25 6.50 6.75 7.00 7.25 7.50 7.75 8.00 8.25 8.50 8.75

Probability DensityData ValueJune Data Histograms with Weibull Distribution Fit to Uravan Historical PrecipitationDataWeibull DistributionGoldisim ValuesData Values0.050.10.150.20.25

Probability DensityJuly Data Histograms with Weibull Distribution Fit to Uravan HistoricalPrecipitation DataWeibull DistributionGoldisim ValuesData ValuesGG May-10 073-81694KFM AS SHOWN N/AKFMFiguresB-rev6May2010.xlsmFIGURE B-9URAVAN DATA, GOLDSIM RESULTS AND WEIBULL DISTRIBUTION FORJULYENERGY FUELS RESOURCES CORPORATIONPIÑON RIDGE PROJECT00.050.10.150.20.25 0.00 0.25 0.50 0.75 1.00 1.25 1.50 1.75 2.00 2.25 2.50 2.75 3.00 3.25 3.50 3.75 4.00 4.25 4.50 4.75 5.00 5.25 5.50 5.75 6.00 6.25 6.50 6.75 7.00 7.25 7.50 7.75 8.00 8.25 8.50 8.75

Probability DensityData ValueJuly Data Histograms with Weibull Distribution Fit to Uravan HistoricalPrecipitation DataWeibull DistributionGoldisim ValuesData Values0.040.060.080.10.120.140.16

Probability DensityAugust Data Histograms withWeibull Distribution Fit to Uravan HistoricalPrecipitation DataWeibull DistributionGoldisim ValuesData ValuesGG May-10 073-81694KFM AS SHOWN N/AKFMFiguresB-rev6May2010.xlsmFIGURE B-10URAVAN DATA, GOLDSIM RESULTS AND WEIBULL DISTRIBUTION FORAUGUSTENERGY FUELS RESOURCES CORPORATIONPIÑON RIDGE PROJECT00.020.040.060.080.10.120.140.16 0.00 0.25 0.50 0.75 1.00 1.25 1.50 1.75 2.00 2.25 2.50 2.75 3.00 3.25 3.50 3.75 4.00 4.25 4.50 4.75 5.00 5.25 5.50 5.75 6.00 6.25 6.50 6.75 7.00 7.25 7.50 7.75 8.00 8.25 8.50 8.75

Probability DensityData ValueAugust Data Histograms withWeibull Distribution Fit to Uravan HistoricalPrecipitation DataWeibull DistributionGoldisim ValuesData Values0.040.060.080.10.120.140.16

Probability DensitySeptember Data Histograms with WeibullDistribution Fit to Uravan HistoricalPrecipitation DataWeibull DistributionGoldisim ValuesData ValuesGG May-10 073-81694KFM AS SHOWN N/AKFMFiguresB-rev6May2010.xlsmFIGURE B-11URAVAN DATA, GOLDSIM RESULTS AND WEIBULL DISTRIBUTION FORSEPTEMBERENERGY FUELS RESOURCES CORPORATIONPIÑON RIDGE PROJECT00.020.040.060.080.10.120.140.16 0.00 0.25 0.50 0.75 1.00 1.25 1.50 1.75 2.00 2.25 2.50 2.75 3.00 3.25 3.50 3.75 4.00 4.25 4.50 4.75 5.00 5.25 5.50 5.75 6.00 6.25 6.50 6.75 7.00 7.25 7.50 7.75 8.00 8.25 8.50 8.75

Probability DensityData ValueSeptember Data Histograms with WeibullDistribution Fit to Uravan HistoricalPrecipitation DataWeibull DistributionGoldisim ValuesData Values0.040.060.080.10.120.140.160.18

Probability DensityOctober Data Histograms with Weibull Distribution Fit to Uravan HistoricalPrecipitation DataWeibull DistributionGoldisim ValuesData ValuesGG May-10 073-81694KFM AS SHOWN N/AKFMFiguresB-rev6May2010.xlsmFIGURE B-12URAVAN DATA, GOLDSIM RESULTS AND WEIBULL DISTRIBUTION FOROCTOBERENERGY FUELS RESOURCES CORPORATIONPIÑON RIDGE PROJECT00.020.040.060.080.10.120.140.160.18 0.00 0.25 0.50 0.75 1.00 1.25 1.50 1.75 2.00 2.25 2.50 2.75 3.00 3.25 3.50 3.75 4.00 4.25 4.50 4.75 5.00 5.25 5.50 5.75 6.00 6.25 6.50 6.75 7.00 7.25 7.50 7.75 8.00 8.25 8.50 8.75

Probability DensityData ValueOctober Data Histograms with Weibull Distribution Fit to Uravan HistoricalPrecipitation DataWeibull DistributionGoldisim ValuesData Values0 050.10.150.20.250.3

Probability DensityNovember Data Histograms with Weibull Distribution Fit to Uravan HistoricalPrecipitation DataWeibull DistributionGoldisim ValuesData ValuesGG May-10 073-81694KFM AS SHOWN N/AKFMFiguresB-rev6May2010.xlsmFIGURE B-13URAVAN DATA, GOLDSIM RESULTS AND WEIBULL DISTRIBUTION FORNOVEMBERENERGY FUELS RESOURCES CORPORATIONPIÑON RIDGE PROJECT00.050.10.150.20.250.3 0.00 0.25 0.50 0.75 1.00 1.25 1.50 1.75 2.00 2.25 2.50 2.75 3.00 3.25 3.50 3.75 4.00 4.25 4.50 4.75 5.00 5.25 5.50 5.75 6.00 6.25 6.50 6.75 7.00 7.25 7.50 7.75 8.00 8.25 8.50 8.75

Probability DensityData ValueNovember Data Histograms with Weibull Distribution Fit to Uravan HistoricalPrecipitation DataWeibull DistributionGoldisim ValuesData Values0.10.150.20.250.30.35

Probability DensityDecember Data Histograms with Weibull Distribution Fit to Uravan HistoricalPrecipitation DataWeibull DistributionGoldisim ValuesData ValuesGG May-10 073-81694KFM AS SHOWN N/AKFMFiguresB-rev6May2010.xlsmFIGURE B-14URAVAN DATA, GOLDSIM RESULTS AND WEIBULL DISTRIBUTION FORDECEMBERENERGY FUELS RESOURCES CORPORATIONPIÑON RIDGE PROJECT00.050.10.150.20.250.30.35 0.00 0.25 0.50 0.75 1.00 1.25 1.50 1.75 2.00 2.25 2.50 2.75 3.00 3.25 3.50 3.75 4.00 4.25 4.50 4.75 5.00 5.25 5.50 5.75 6.00 6.25 6.50 6.75 7.00 7.25 7.50 7.75 8.00 8.25 8.50 8.75

Probability DensityData ValueDecember Data Histograms with Weibull Distribution Fit to Uravan HistoricalPrecipitation DataWeibull DistributionGoldisim ValuesData Values0.040.060.080.10.120.140.160.18

Probability DensityAnnual Data Histograms with Weibull Distribution Fit to Uravan Historical PrecipitationDataWeibull DistributionGoldisim ValuesData ValuesGG May-10 073-81694KFM AS SHOWN N/AKFMFiguresB-rev6May2010.xlsmFIGURE B-15URAVAN DATA, GOLDSIM RESULTS AND WEIBULL DISTRIBUTION FORANNUAL PRECIPITATIONENERGY FUELS RESOURCES CORPORATIONPIÑON RIDGE PROJECT00.020.040.060.080.10.120.140.160.18 0.00 1.00 2.00 3.00 4.00 5.00 6.00 7.00 8.00 9.00 10.00 11.00 12.00 13.00 14.00 15.00 16.00 17.00 18.00 19.00 20.00 21.00 22.00 23.00 24.00 25.00 26.00 27.00 28.00 29.00 30.00 31.00 32.00 33.00 34.00 35.00

Probability DensityData ValueAnnual Data Histograms with Weibull Distribution Fit to Uravan Historical PrecipitationDataWeibull DistributionGoldisim ValuesData Values1.0E+062.0E+063.0E+064.0E+065.0E+066.0E+067.0E+068.0E+069.0E+06

Pool Volume (ft

3 )GG May-10 073-81694KFM AS SHOWN N/AKFMFiguresB-rev6May2010.xlsmFIGURE B-16TAILINGS CELL POOL VOLUME FOR 500-TPD MILLING RATEENERGY FUELS RESOURCES CORPORATIONPIÑON RIDGE PROJECT0.0E+001.0E+062.0E+063.0E+064.0E+065.0E+066.0E+067.0E+068.0E+069.0E+060 20 40 60 80 100 120 140 160 180

Pool Volume (ft

3 )Time (month)MeanLeast Result5%25%Median75%95%Greatest Result110120130140150160170180190200

Pumping Rate (gpm)GG May-10 073-81694KFM AS SHOWN N/AKFMFiguresB-rev6May2010.xlsmFIGURE B-17PUMPING RATE AVAILABLE TO RETURN RECLAIMED WATERTO MILL FOR 500-TPD MILLING RATEENERGY FUELS RESOURCES CORPORATIONPIÑON RIDGE PROJECT1001101201301401501601701801902000 20 40 60 80 100 120 140 160 180

Pumping Rate (gpm)Time (month)MeanMedian95%Greatest Result24681012141618

Pumping Rate (gpm)GG May-10 073-81694KFM AS SHOWNN/AKFMFiguresB-rev6May2010.xlsmFIGURE B-18EXCESS PUMPING RATE FOR 500-TPD MILLING RATEENERGY FUELS RESOURCES CORPORATIONPIÑON RIDGE PROJECT0246810121416180 20 40 60 80 100 120 140 160 180

Pumping Rate (gpm)Time (month)MeanMedian95%Greatest Result5.0E+061.0E+071.5E+072.0E+072.5E+07

Excess Volume (ft

3 )GG May-10 073-81694KFM AS SHOWNN/AKFMFiguresB-rev6May2010.xlsmFIGURE B-19AVAILABLE EXCESS MAKE-UP WATER VOLUMEFOR 500-TPD MILLING RATEENERGY FUELS RESOURCES CORPORATIONPIÑON RIDGE PROJECT0.0E+005.0E+061.0E+071.5E+072.0E+072.5E+070 20 40 60 80 100 120 140 160 180

Excess Volume (ft

3 )Time (month)MeanLeast Result5%25%Median75%95%Greatest Result

### May 2010 073-81694

C: \ Users \ kglaspey \ AppData \ Local \ Microsoft \ Windows \ Temporary Internet Files \ Content.Outlook \ S56HZGBQ \ Attachment B Text

- WBCalc

- 07May2010 (2).docx 

## ATTACHMENT 1 TO APPENDIX B

WEATHER DATA ANALYSISS ÑO GENERGY FUELS RESOURCES CORPORATIONPIÑON RIDGE PROJECTSITE VIEW PIÑON RIDGEEF1/16/2008N.T.SFIGURE.PPT073-81694N/A1KFMGGUravanS O OC O SENERGY FUELS RESOURCES CORPORATIONPIÑON RIDGE PROJECTWEATHERSTATION LOCATIONSEF1/16/2008N.T.SFIGURE.PPT073-81694N/A2GGKFM1618Nucla1214

in]Grand Junction AirportMontroseUravan81012

P recipitation [46

Total021999 2000 2001 2002 2003 2004 2005 2006 2007O C O CO SOYearENERGY FUELS RESOURCES CORPORATIONPIÑON RIDGE PROJECTTOTAL ANNUAL PRECIPITATIONCOMPARISON1999 TO 2007EF1/16/2008N.T.SFIGURE.PPT073-81694N/A3GGKFM58006000Nucla54005600

t )MontrosePiñon Ridge Project Elevation EL. 5,480 ft480050005200

E levation (f tGrand JunctionUravan420044004600

EGrand Junction 6ESE400042008 9 10 11 12 13MeanAnnual Precipitation(in)VARIATION IN ANNUAL PRECIPITATION vs ELEVATION FORAnnualPrecipitation(in)ENERGY FUELS RESOURCES CORPORATIONPIÑON RIDGE PROJECTEF1/16/2008N.T.SFIGURE.PPT073-81694N/A4VARIATIONINANNUALPRECIPITATIONvs.ELEVATIONFORREGIONAL METEOROLOGICAL STATIONSGGKFM3URAVAN 196522.5

[in]URAVAN 198911.5

Precipitation00.5MonthMONTHLY PRECIPITATION FOR DRIEST AND WETTESTENERGY FUELS RESOURCES CORPORATIONPIÑON RIDGE PROJECTMONTHLYPRECIPITATIONFORDRIESTANDWETTESTYEAR FOR URAVAN SITEEF1/16/2008N.T.SFIGURE.PPT073-81694N/A5GGKFM3URAVAN 196522.5

in]URAVAN1965Grand Junction Airport 196511.5

P recipitation [0.50O C O CO SO OMonthENERGY FUELS RESOURCES CORPORATIONPIÑON RIDGE PROJECTEF1/16/2008N.T.SFIGURE.PPT073-81694N/A6MONTHLY PRECIPITATIONCOMPARISON FORURAVAN AND GRAND JUNCTION FOR YEAR 1965GGKFM2.5URAVAN 19891 52

[in]Grand Junction Airport 198911.5

Precipitation00.5MonthO CO SOENERGY FUELS RESOURCES CORPORATIONPIÑON RIDGE PROJECTEF1/16/2008N.T.SFIGURE.PPT073-81694N/A7MONTHLY MAXIMUM TEMPERATURECOMPARISONFOR URAVAN AND GRAND JUNCTIONGGKFM7476Nucla7072

]Grand Junction AirportUravanMontrose666870

m Temperature [°F ]6264

Maximu m5860199920002001200220032004200520062007CO SO199920002001200220032004200520062007YearENERGY FUELS RESOURCES CORPORATIONPIÑON RIDGE PROJECTEF1/16/2008N.T.SFIGURE.PPT073-81694N/A8ANNUAL MAXIMUM TEMPERATURECOMPARISON1999 TO 2007GGKFM6000Nucla540056005800MontrosePiñon Ridge Project Elevation EL. 5,480 ft480050005200

e vation (ft)Grand JunctionUravan440046004800

El eGrand Junction 6ESE4000420040 50 60 70 80 90Mean Annual Maximum Temperature (oF)VARIATION IN ANNUAL MAX TEMPERATURE vs ELEVATION FORENERGY FUELS RESOURCES CORPORATIONPIÑON RIDGE PROJECTEF1/16/2008N.T.SFIGURE.PPT073-81694N/A9VARIATIONINANNUALMAX.TEMPERATUREvs.ELEVATIONFORREGIONAL METEOROLOGICAL STATIONSGGKFMCOLORADOPiñon Ridge siteG O O ( C S) O S OENERGY FUELS RESOURCES CORPORATIONPIÑON RIDGE PROJECTEF1/16/2008N.T.SFIGURE.PPT073-81694N/A10AVERAGE ANNUAL EVAPORATION(INCHES)FROMSHALLOWLAKESGGKFMO O S O OOENERGY FUELS RESOURCES CORPORATIONPIÑON RIDGE PROJECTEF1/16/2008N.T.SFIGURE.PPT073-81694N/A11MONTHLY EVAPOTRANSPIRATION AND PAN EVAPORATIONGGKFM>>>><<<<CDCDCDCDCD0OQOQ00OQCDCDCDCD0—OO_.0)8aQCD=0w00-JU0I-.ào30000CC-01’).itJCDCDI-C3•00UI-j-‘U1CC<______-II-.-I0ZU,CDC—I-UICDCU,I-.J0000vOQ0)CDUIwUIIU-J•ClCD.—I-1CUI•0C•••-CDClCDC-vCDCDCDCD-.—-.0WOO)0000000.COrDeD0-I,CD0Id’CDI.W1.01.00II.’)wI-“300pt.w:a0p;‘‘JJ1O•obzogCIm‘IiIllI(0.>:-‘w•.jc0z•0W—I.fl00000o°ào•&013W4•Cwc•’00JuoocCLflC(NC(N4U>to6dLqo•00jbC.Co.-’(NCNCO.rIinCoinC•cN•00(Ndc.Dioe‘o’iC.cóN.0Cr.l-lin(N-I2oo-l(C.-(CEEo-oUX(CCCW(Cowwww-oo-CWWWW.-iirmmCD04r-Lflr’40000000.NNWdc°Olfl00U000N00‘.D0NLflIAr-0OD0z2—00uDWNdOII(0ii=NO(0(0_____<U)II—I_w.10)(0z0zz—.Dm00o’-0DIA00o6NmmN002—-r.i‘-IDinEEoUa)4-o0)0)0)0)00000000.20)0)0)0)>>>>0.CCibm4;>tocn,-0)r.u•OIflacF-.Ocoin-I.DDCOIn-o—COIn0CZoIInIndo44______‘1InIz_______0.°InmCOF—00(‘1ID2oo-IEEo‘I(010a)o00000000oWa)0)0)>c 

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