Analysis of Lifecycle Water Requirements of
Transportation Fuels: Corn- based Ethanol
- Model Description
By
Gouri Shankar Mishra ( gouri. mishra@ gmail. com)
Sonia Yeh ( slyeh@ ucdavis. edu)
June, 2010
Version 1.1
Report Number: UCD- ITS- RR- 10- 12
Institute of Transportation Studies
University of California, Davis
  1
 
A B S T R A C T . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2  
A C K N O W L E D G E M E N T . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3  
N O T A T I O N . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4  
M O D E L   O B J E C T I V E S . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5  
S Y S T E M   B O U N D A R Y . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6  
W A T E R   R E Q U I R E M E N T S   C O N S I D E R E D . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6  
F E E D S T O C K S   C O N S I D E R E D . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1 0  
G E O G R A P H I C A L   R E G I O N S   C O N S I D E R E D . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1 0  
F U N C T I O N A L   U N I T S . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1 1  
M E T H O D O L O G Y . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1 2  
S T E P   1 :   E S T I M A T E   C R O P   W A T E R   R E Q U I R E M E N T . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1 2  
S T E P   2 :   E S T I M A T E   A P P L I C A T I O N   L O S S E S . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1 3  
S T E P   3 :   A C C O U N T   F O R   C O N V E Y A N C E   L O S S E S . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1 4  
S T E P   4 :   A L L O C A T E   E S T I M A T E D   W A T E R   B E T W E E N   C O R N   G R A I N   A N D   C O B . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1 4  
E s t i m a t e   g r a i n   a n d   c o b   y i e l d s . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1 4  
A c c o u n t   f o r   b i o m a s s   s t o r a g e   l o s s e s . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1 5  
A l l o c a t i o n   p r o c e d u r e s . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1 5  
S T E P   5 :   B I O - R E F I N E R Y   W A T E R   R E Q U I R E M E N T S   A N D   C O - P R O D U C T   C R E D I T I N G . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1 7  
S T E P   5 A :   E t h a n o l   f r o m   c o r n   g r a i n   ( G r a i n   p a t h w a y ) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1 7  
S T E P   5 B :   E t h a n o l   f r o m   C o r n   C o b . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2 0  
O N S I T E   E N E R G Y   C O N S U M P T I O N . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2 1  
R E F E R E N C E S . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2 3  
A P P E N D I X   A 1 :   S T A T E W I D E   A V E R A G E   V A L U E S   O F   K E Y   I N P U T   P A R A M E T E R S . . . . . . . . . . . . . . . . . . . . . 2 8  
A P P E N D I X   A 2 :   W A T E R   I N T E N S I T Y   O F   P R O D U C T S   D I S P L A C E D   B Y   C O - P R O D U C T S   O F  
E T H A N O L   F R O M   C O R N   G R A I N   P A T H W A Y . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 0  
A P P E N D I X   A 3 :   T H E R M O E L E C T R I C   W A T E R   C O N S U M P T I O N   A N D   W I T H D R A W A L . . . . . . . . . . . . . . . . . 1  
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Abstract
This document describes the methodology and data sources for the “ Analysis of lifecycle
water requirements of transportation fuel: corn based ethanol – model version 1.1”. The
model estimates water requirements for ethanol from corn grain and corn cob ( crop residue)
based on default or user inputs of crop evapotranspiration, pre- irrigation water requirements
for salt leaching and crop establishment, irrigation methods and the efficiencies of conversion
technologies, and projected crop yields. Water requirements also depend upon procedures
adopted for calculating co- product credits at various stages of the lifecycle. The model
characterizes water requirements in terms of withdrawal and consumption; and source –
ground water, surface water, precipitation, and soil moisture.
The spreadsheet based model is available at http:// www. its. ucdavis. edu/ download/ UCD-ITS-
RR- 10- 11. xls
The model is part of a series exploring water footprint of future transportation fuels including
bio- fuels and electricity. Other models currently under development examine the lifecycle
water requirements of electricity from geothermal resources and concentrated solar power.
  3
Acknowledgement
The research effort is funded by the California Air Resources Board, the Energy Foundation
and the David & Lucile Packard Foundation.
We thank all those who have offered ideas, data, information, and comments on the model
including Richard Snyder, Steve Kaffka, Nathan Parker, Mark Delucchi, and Alissa Kendall
from UC Davis; and Lorraine White from California Energy Commission.
  4
Notation
AE Application efficiency of irrigation system
AWR Applied water requirement
BR Bio- refinery water requirements
CWR Crop water requirements
CIMIS California Irrigation Management Information System
CUP Consumptive Use Program
ET Evapotranspiration ( inches)
ET o Reference evapotranspiration ( inches)
ET c Crop specific evapotranspiration ( inches)
ET a Applied or irrigation water portion of crop specific evapotranspiration ( inches)
E e Embodied water of energy inputs
EtOH Ethanol
IWR Irrigation water requirements
K c Crop coefficient
P s Portion of crop specific evapotranspiration met by precipitation during crop
growing season
P os Portion of crop specific evapotranspiration met by soil moisture ( which is related
to precipitation during off season)
PI Pre- irrigation water requirements
SBM Soyabean meal
SO Soyabean oil
L a Irrigation application losses
L c Conveyance losses
USDA US Department of Agriculture
USGS US Department of Geological Survey
VMT Vehicle miles traveled
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Model objectives
The “ Model for lifecycle water analysis of corn- based ethanol” ( model) estimates the
following:
   Water requirements to produce ethanol from corn grain.
   Water requirements if the cob portion of corn is also used to produce ethanol.
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System boundary
The model adopts a lifecycle perspective and considers water requirements from corn
cultivation, feedstock storage and transport, ethanol production at the bio- refinery, to ethanol
distribution. The following figure summarizes water requirements included in this study:
Water requirements considered
Figure 1: Water requirements of ethanol from corn
Our model calculates both total water withdrawal and consumption. Water withdrawal
represents the total water taken from freshwater sources – precipitation, soil moisture,
groundwater or surface water. Water consumption represents the amount of water withdrawal
that is not returned to the source. This water is removed from the hydrological cycle due to
either evaporation or percolation to deep salt sink. The water requirements considered in
Figure 1 are described below.
   Crop evapotranspiration ( ET c )
ET c constitutes the greatest proportion of water requirements for bio- ethanol production. ET c
is computed in a two steps. First, reference evapotranspiration ( ET o ) is computed using the
daily Penman- Monteith equation. ET o measures the evaporative demand of the atmosphere
and is independent of crop type and crop development. It depends upon four climatic
parameters: solar radiation, ambient temperature, dew point temperature or relative humidity,
and wind speed. Crop specific evapotranspiration ( ET c ) accounts for differences in leaf
anatomy, stomatal characteristics, aerodynamic properties and albedo, all of which cause the
crop evapotranspiration to differ from the reference crop evapotranspiration under the same
climatic conditions. Further, due to variations in the crop characteristics throughout its
C o r n  
C u l t i v a t i o n
F e e d s t o c k  
S t o r a g e   a n d  
D i s t r i b u t i o n
E t h a n o l  
P r o d u c t i o n
E t h a n o l
D i s t r i b u t i o n
E T a P I
P s
P o s
L a L c B R E e
S u r f a c e   /  
G r o u n d
S o u r c e
P r e c i p i t a t i o n
( I n   s e a s o n )
S o i l   M o i s t u r e
( P r e c i p i t a t i o n  
o f f   s e a s o n )
R e q u i r e m e n t s
Crop evapo-transpiration
( ET c )
Pre- Irrigation
Water
Application
losses
Conveyance
losses
Bio- refinery
water
Embodied
Water of
energy inputs
at all stages
Grey Water
footprint
G
  7
growing season, ET c changes from sowing till harvest. The model uses a crop coefficient ( K c )
to calculate ET c using the following relationship:
ET c = K c x ET o ( Equation 1)
where,
ET c is crop specific evapotranspiration
K c is crop specific coefficient
ET o is reference evapotranspiration
Demand for crop evapotranspiration is met through three sources:
ET c = P s + P os + ET a ( Equation 2)
where,
P s is precipitation during the crop growing season
P os is the water available from soil profile
ET a is irrigation water applied
The extent of evapotranspiration requirements met through soil moisture content ( P os )
depends upon ( i) the moisture holding capacity of the soil. For example, silt loams and silty
clay loams can hold around 2 inches of water per foot of depth while sandy soils can hold less
than 1 inch per foot of depth; and ( ii) the root depth of the crop concerned. 1 The source of
soil moisture is from precipitation during off- season.
P s captures “ effective” precipitation which is equal to total precipitation during the season
minus any losses due to runoff or percolation.
   Pre- irrigation water requirements ( PI)
Prior to spring planting of corn, pre- irrigation water is often applied to flush excess salts
through the soil ( Wichelns et al 1987, Wichelns et al 1996), and to avoid crop stress during
growing season. The amount of water required for pre- irrigation depends upon precipitation,
the irrigation technology and corresponding distribution uniformity, and soil profile. Per
Jensen ( 2007), about 5– 10% more irrigation water than that consumed in ET is required to
control soil salinity in places where leaching by precipitation is insignificant. The excess water
helps control salinity by moving the salts below the root zone and to natural and constructed
drains. Cost and return studies conducted by the University of California Cooperative
Extension for corn grown in the southern San Joaquin Valley indicates that pre- irrigation
water requirements are nearly 20% of crop water requirements ( UCCE 2008). We assume
water withdrawal for salt leaching and crop establishment will be returned back to the source
therefore water consumption of PI = 0.
   Irrigation application losses ( L a )
This accounts for inefficiencies in the irrigation system installed to meet the ET a portion of
the crop evapotranspiration.
                                                                                                 
1 A detailed description of water from soil profile is available at Broner 2005.
  8
L a = ET a x ( 1- AE) ( Equation 3)
where,
L a is excess water that needs to be applied over and above ET a
AE is the application efficiency and lies between 0% and 100%.
There are a number of performance measures ( Burt et al 1997) and these measures are defined
differently in the literature. The application efficiency ( AE) measure adopted by us is based on
Howell ( 2003). Solomon ( 1988) has identified various sources of water losses as enunciated
below. Over- watering is the most significant cause of water loss in any irrigation system. The
major losses associated with surface irrigation systems are direct evaporation from the wet soil
surface, runoff losses, and seepage losses from water distribution ditches. The losses
associated with sprinkler irrigation ( other than those due to over- watering) are direct
evaporation from wet soil surfaces, wind drift and evaporation losses from the spray, system
drainage and leaks. Leaks are also responsible for losses from drip irrigation.
Application efficiency depends upon the spatial boundary selected for analysis with
efficiencies increasing as we move from field and farm to a water district or water basin. The
difference arises due to two reasons. First, excess water runoff from a farm can be beneficially
used in a downstream farm. Second, water released from a farm through runoff or deep
percolation might have environmental benefits and hence cannot be considered a loss. As a
result, Jensen ( 2007) questions the use of the term " efficiency" and proposes use of alternative
terms like " coefficient" or " fraction." Thus, unlike ET c which is " consumed" and no longer
available in the hydrological cycle, this model treats the entire water withdrawn in excess of
CWR as " released" and thus available for other potential uses ( i. e. water consumption of L a =
0).
   Conveyance losses ( L c )
L c accounts for losses from water supply conveyance systems due to evaporation and
evapotranspiration by vegetation in and near canals; and due to deep percolation to salt sink
during conveyance. As a result, we consider conveyance losses as consumed.
C r o p ,   A p p l i c a t i o n   a n d   I r r i g a t i o n   w a t e r   r e q u i r e m e n t s   ( C W R ,   A W R   a n d   I W R )    
 
C r o p   w a t e r   r e q u i r e m e n t   i s   t h e   s u m   o f   c r o p   e v a p o t r a n s p i r a t i o n   a n d   p r e - i r r i g a t i o n   w a t e r   f o r   s a l t  
l e a c h i n g   a n d   c r o p   e s t a b l i s h m e n t  
C W R     =   E T c   +   P I                 ( E q u a t i o n   4 )  
  =   E T a   +   P s   +   P o s   +   P I    
 
A W R   i s   t h e   a p p l i e d   w a t e r   r e q u i r e m e n t   a n d   i s   t h e   t o t a l   w a t e r   t h a t   n e e d s   t o   b e   d e l i v e r e d   t o   t h e  
f i e l d   o r   f a r m  
A W R   =   E T a   +   P I   +   L a                 ( E q u a t i o n   5 )  
 
I r r i g a t i o n   w a t e r   r e q u i r e m e n t   i s   t h e   t o t a l   w a t e r   t h a t   n e e d s   t o   b e   c o n v e y e d   f r o m   t h e   s o u r c e   g i v e n  
t h e   c r o p   e v a p o t r a n s p i r a t i o n   r e q u i r e m e n t   n o t   m e t   b y   p r e c i p i t a t i o n   o r   s o i l   m o i s t u r e   ( E T a ) ,  
a p p l i c a t i o n   i n e f f i c i e n c i e s   ( L a   )   a n d   c o n v e y a n c e   l o s s e s   ( L c )  
I W R     =   A W R   +   L c                 ( E q u a t i o n   6 )  
  =   E T a   +   P I   +   L a   +   L c      
  9
We do not consider conveyance water attributed to agriculture that seeps through channels
and returns as surface flow in another hydrological region. Neither do we account for the
portion of agricultural conveyance water that seeps through channels and returns to
groundwater. This water is not consumed and available for use including agricultural use. Such
seepage is of similar volume as that of conveyance losses.
   Bio- refinery water ( BR)
Process and cooling water is required during conversion of feedstock to ethanol. BR gr and
BR cb represent bio- refinery water for conversion to ethanol of corn grain and corn cob
respectively.
   Embodied water of energy inputs at all stages ( E e )
While the focus of our LCA model is onsite " first- level" water requirements, i. e. direct water
inputs during corn cultivation and ethanol production; we also consider " second- level" water
requirements as a result of onsite energy inputs. For example, we account for diesel used for
corn harvesting and biomass transportation, and electricity and natural gas consumed at the
bio- refinery. The corresponding water requirements of these fuels are included to calculate
total requirements. We do not, however, consider water requirements for production of
materials and equipments, such as fertilizers, pesticides, manufacturing of farm equipment,
acids and enzymes for ethanol conversion; nor do we consider the corresponding water
requirements for the embodied energy for their production.
For simplicity, we only account for water consumption intensity of energy inputs ( water
consumed per unit energy input required) and ignore water withdrawal intensity ( water
withdrawn per unit energy input required). This simplification does not affect the results in a
significant way because of two reasons. First, such “ second level” water requirements
constitute less than 1% of total water requirements because of low water intensity of
conventional fuels. Second, the only energy input with a large difference between water
withdrawal and consumption intensity is electricity - 16 gallons/ kWh of withdrawal versus 0.5
gallons / kWh for consumption ( USGS 1998, USGS 2009). However, electricity consumption
is only around 9% of total lifecycle energy consumption for ethanol from dry mill plants; and
around 2% for ethanol from wet mill plants ( GREET 2010).
   Grey water footprint
Grey water is an indicator of the degree of freshwater pollution that occurs during the entire
lifecycle. It is defined as the volume of freshwater that is required to assimilate the load of
pollutants based on existing ambient water quality standards. It is calculated as the volume of
water that is required to dilute pollutants to such an extent that the quality of the ambient
water remains above agreed water quality standards ( Gerbens- Leenes et al 2009). We do not
consider grey water footprint in the current version of the model.
The following table summarizes water requirements included and excluded.
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Table 1: Water requirements - inclusions and exclusions
Inclusions Exclusions
Corn cultivation
- Crop evapotranspiration - Water (& energy) required at nursery
- Pre- irrigation water for salt leaching and crop
establishment
- Water (& energy) required to produce
fertilizers and pesticides
- Additional water application to account for
irrigation efficiencies
- Water (& energy) required to produce farm
equipment
- Irrigation water conveyance Losses
- Water required to produce diesel and
electricity used in cultivation*
Feedstock transportation and distribution
- Water required to produce diesel used for
transportation*
- Water (& energy) required to produce
transportation & distribution equipment
- Water required to produce electricity used
during storage*
Biorefinery
- Process water - Water (& energy) required to produce various
inputs like acid & enzymes
- Cooling water
- Water required to produce diesel and
electricity ( net) used in biorefinery*
Ethanol transportation and distribution
- Water required to produce diesel used for
transportation*
Notes: * represents " second- level" water requirement, which only considers water consumption but
not water withdrawals.
For the following components, we assumed that the entire water withdrawn is consumed -
ET c , L c , BR and E e . For PI and L a , we assumed that the entire water withdrawn is released ( i. e.
water consumption = 0).
Feedstocks considered
In addition to ethanol from corn grain, we also analyze water intensity of ethanol from corn
stover. A review of recent literature highlighted a number of shortcomings in using the entire
corn stover to produce ethanol. These are in the areas of ( i) soil protection ( Wilhelm et al
2007, Wilhelm et al 2004), ( ii) transportation and logistics of feedstock ( Atchison &
Hettenhaus 2004), ( iii) harvesting of feedstock ( Atchison & Hettenhaus 2004). H a r v e s t i n g  
o n l y   t h e   c o b   p o r t i o n   o f   s t o v e r   a n d   e x c l u d i n g   t h e   s t a l k   a n d   l e a v e s   a v o i d s   t h e   a b o v e  
m e n t i o n e d   s h o r t c o m i n g s .
Geographical regions considered
The model can be used for corn production anywhere in the country.
  11
For the location specific parameters, the model assumes default values applicable to corn
grown in the San Joaquin agricultural district. For example, the default crop
evapotranspiration values pertain to two meteorological stations in the region - Fresno
( CIMIS 2 Station # 1) and Manteca ( CIMIS Station # 70). Both stations are both located in the
San Joaquin agricultural district which accounted for 55% of California's corn production in
2007 ( USDA 2010). Two other key location specific variables are conveyance losses and
proportion of ground water to total irrigation water. Default values for these variables were
taken for the San Joaquin River hydrological region - one of the 10 regions for which
California Department of Water Resources provides detailed water balance statements.
We have also suggested values for these variables for states in the US Corn Belt – Indiana,
Iowa, Illinois, Minnesota and Nebraska.
Functional units
Estimates of water intensity is presented in two forms: ( i) gallons of water ( withdrawn or
consumed) per gallon of denatured ethanol produced, and ( ii) gallons of water ( withdrawn or
consumed) per vehicle mile traveled ( VMT). For the later, we used vehicle energy efficiency
estimates ( BTU per VMT) from GREET ( 2010).
                                                                                                 
2 CIMIS stands for California Irrigation Management Information System ( CIMIS). The system is an integrated
network of over 125 automated active weather stations located throughout California and is managed by
California Department of Water Resources ( DWR).
  12
Methodology
In this section we discuss our five step process to assess the water intensity of ethanol from
corn grain and corn cob.
STEP 1: Estimate crop water requirement
Crop evapotranspiration is an input to our model and can be assessed by using either the
Consumptive Use Program ( CUP) developed by California Department of Water Resources
and the University of California, Davis to determine ET c ( Orang et al 2005, CA- DWR 2010);
or the CROPWAT model developed by United Nation's Food and Agricultural Organization
( FAO 2010). The two models use different values for crop coefficient K c for corn - for
example the growing season K c is 1.05 for the CUP and 1.20 for the CROPWAT model. We
adopted the K c suggested by the CUP model ( based on personal communications with Dr.
Richard Snyder). The crop seasons – planting and harvesting dates – were taken from USDA
( 1997).
The ET c estimated here assumes standard conditions i. e. disease- free, well- fertilized crops,
grown in large fields, under optimum soil water conditions, and achieving full production
under the given climatic conditions ( FAO 1998). In actual practice, presence of pests and
diseases, soil salinity, low soil fertility, and water shortage or water- logging ( a situation
associated with excessive irrigation on poorly drained soils) is in turn may reduce crop yields
and the evapotranspiration rate below ET c .
E T   +  
S a l t   L e a c h i n g
I r r i g a t i o n
R a i n
A p p  
L o s s e s
C o n v e y  
L o s s e s
1 2 3
C r o p   w a t e r  
r e q u i r e m e n t s
A d d   w a t e r  
a p p l i c a t i o n  
l o s s e s
A d d  
c o n v e y a n c e  
l o s s e s
C o r n   G r a i n
C o r n   C o b
A l l o c a t e  
b e t w e e n  
g r a i n   &   c o b
4
A l l o c a t i o n
E t h a n o l C o - p r o d u c t s
5 A
E t h a n o l E l e c t r i c i t y
5 B
E s t i m a t e  
p r o c e s s  
w a t e r
A l l o c a t e  
b e t w e e n  
e t h a n o l   &  
c o - p r o d u c t s
Figure 2: Methodology adopted for lifecycle analysis
  13
In addition to ET c , the two models give the amount of crop evapotranspiration met through
in- season precipitation ( P s ), through soil moisture content ( P os ) based on selected soil type,
and finally the requirement for irrigated water ( ET a ).
STEP 2: Estimate application losses
Applied water requirements depends upon the application efficiency ( AE) of the irrigation
system adopted. A range of efficiency levels were reported in the literature; we adopted the
following values reported by Salas et al ( 2006) in a report prepared for the California Energy
Commission.
Table 2: Irrigation systems - application efficiency and market shares in CA
Type of Irrigation System
Application
Efficiency (%) ( 1)
Market Share (%) ( 3)
Surface irrigation
- Basin 85% 0.2%
- Border 78% 13.6%
- Furrow 68% 67.0%
- Wild flooding 60% 5.3%
- Gravity 75%
- Average of Surface irrigation 73%
Sprinkler
- Hand move or portable 70% 1.0%
- Center Pivot and Linear
Move
83% 0.6%
- Solid Set or Permanent 75% 0.2%
- Side roll sprinkler 70%
- Lepa ( low energy precision
application)
90%
- Average sprinkler 78%
Drip / micro irrigation
- Surface drip 88%
- Buried drip 90%
- Subirrigation 90%
- Average drip/ micro 88%
Sub- surface irrigation 70% ( 2) 12.1%
Notes: ( 1) Based on Salas et al ( 2006)
( 2) Based on Howell ( 2003)
( 3) Based on % of irrigated land planted with corn in 2001 in California ( Orang et al
2005)
Observed efficiencies ( AE) of any irrigation system may differ widely from the maximum
potential AE. System design and implementation, and management determine real world
efficiencies. Thus installing a drip system does not always result in higher irrigation efficiencies.
As reported by Wolf et al. ( 1995, as cited by Jensen 2007), unless a drip system is properly
maintained and operated, the irrigation efficiency achieved may be no better than that
achieved with a traditional surface system. Similarly, Lewis et al ( 2008) found that vineyards
using drip irrigation systems varied widely in the amount of water applied per acre ( from 0.2
  14
acre- feet to 1.3 acre- feet) suggesting that management practices are an important determinant
of applied water. Edkins ( 2006) reports wide variability in observed application efficiencies in
a study of irrigation system performance in New Zealand.
Table 3: Variability of water application efficiencies in a New Zealand survey
Type of sprinkler system
Number of
measurements
Avg. application
efficiency (%)
Observed
efficiency range
- Hand move or Portable 2 89% 88%- 91%
- Linear move 13 89% 80%- 93%
- Center pivot 7 88% 85%- 94%
- Side roll sprinkler 8 90% 86%- 92%
Notes: Based on Edkins ( 2006)
Irrigation systems in various states in the US Corn Belt are summarized in Table A1.1.
STEP 3: Account for conveyance losses
In this step we account for losses from water supply conveyance systems due to evaporation
and evapotranspiration by vegetation in and near canals; and due to deep percolation to salt
sink during conveyance. These losses are treated as withdrawn and consumed. For states in
the US Corn Belt, the average conveyance loss as a percentage of total water withdrawn for
irrigation is based on USGS ( 1998). For California we depended upon CA DWR's water
portfolio statements for both statewide averages and for the San Joaquin River hydrological
region for the years 1998, 2000 and 2001 ( CA DWR 2005).
Conveyance losses are negligible for states like Iowa and Illinois. We believe this is because
groundwater, upon which irrigation nearly always depends upon, is extracted locally and hence
does not need to be conveyed. The conveyances losses constitute 12% of total water
withdrawn for irrigation in Nebraska and 3.6% in California ( USGS 1998) ( Table A1.1.).
STEP 4: Allocate estimated water between corn grain and cob
Total water estimated at end of step 3 ( viz. ET c + PI + L a + L c ) is allocated between grain and
cob: Embodied water of energy used in agriculture is also allocated between corn and grain
Water allocated to grain = ET c
gr
+ PI gr + L a
gr + L c
gr + E e
gr ( Equation 7)
Water allocated to cob = ET c
cb
+ PI cb + L a
cb + L c
cb + E e
cb ( Equation 8)
The allocation is based on the following sub- steps: ( i) estimation of dry tons of corn grain and
cob harvested based on corn yields and corn- cob yield ratio, ( ii) account for losses in dry
matter as a result of storage, ( iii) allocate water based on alternative allocation procedures
Estimate grain and cob yields
  15
The model allows users to enter corn grain yield. Average crop yields were taken from USDA
2010. Corn grain yield in 2007 in California was 182.2 bushels per acre while the national
average was 180 bushels per acre ( USDA 2010). This corresponds to 5.10 tons/ acre ( national:
5.04) when considered at 15.5% moisture level. Without moisture, the average California and
national yields were 4.31 and 4.26 dry tons per acre respectively. Statewide average yields of
other states are given in Table A1.1.
To analyze cob yields, we reviewed the literature for corn- cob yield ratios. Based on field
studies in Colorado and Texas, Halvorson and Johnson ( 2009) reported a cob- grain mass ratio
of 0.14 where the grain was considered at 15.5% moisture content and cob was oven dried.
This corresponds to a ratio of 0.17 when both are oven dried. The field studies were
conducted with multiple N fertilizer treatments, varying tillage systems, and different growing
seasons. Based on field studies in Tennessee, Pordesimo et al ( 2005) found a corn- grain mass
ratio of 0.18 where both grain and cob were oven dried; and measurements were undertaken
at the time of grain physiological maturity, which occurred at 118 days after planting. The
mass ratios before and after were different, albeit in a small way. Schwietzke et al ( 2009)
reported similar cob- grain yield ratio. This model assumes a default value of 0.18 for the cob-grain
yield ratio.
Based on average California corn yield, cob yields will be 0.79 dry tons / acre.
Account for biomass storage losses
Grain and cob are cultivated and harvested seasonally, but have to support year round ethanol
production. This necessitates storage of feedstock which is subject to dry matter losses largely
due to microbial activity. Losses are largely dependent upon storage conditions - outdoor
versus indoor storage, type of ventilation system, and use of fungicides and insecticides. Based
on field tests at Wisconsin, Shinners et al ( 2007) found that after eight months, dry matter
losses were 3.3% for dry stover bales stored indoors and 18.1% stored outdoors. Smith et al
( 1985 as cited by Zych 2008) found similar dry matter losses for cobs stored outside from
winter to summer. However, cobs in the interior of the piles which were well ventilated had
lower losses. Perlack and Turhollow ( 2002) assumed a 10% loss in stover dry matter due to
storage and handling for their calculation of logistics costs of corn stover.
The model assumes a conservative default storage loss of 2% in both grain and cob dry
matter. It is likely that most of dry matter losses due to microbial activity is in the sugars
rather than other biomass components like ash and lignin. This implies a more than 2%
reduction in ethanol yield. In the version of our model, we have not accounted for such
differences.
Allocation procedures
The model allows allocation on the basis of mass and energy content, best case ethanol yield,
and system expansion methods.
   Mass and energy basis
  16
Under the mass basis for allocation, water may be allocated proportional to the relative mass
of corn and cob. The relative masses of corn and cob were discussed earlier. Similarly, energy
basis of allocation will allocate water based on relative energy content ( BTU / lb) of corn
grain and cob. Based on Pordesimo et al ( 2005), we assume that the energy content of grain
and cob are equal. Hence, the two allocation methods will yield the same result.
   Maximum potential ethanol yield
We have also considered allocation based on maximum potential ethanol yield. This takes the
reported values of dry matter weight fraction of polymeric sugars in corn cob and uses US
DOE's ( 2010) Theoretical Ethanol Yield Calculator to calculate the maximum possible
ethanol yield assuming 100% efficiency in the conversion process 3 . It is thus independent of
state of conversion technology. The comparison of the values used in this study with the
others is shown in Table 4.
Table 4: Maximum potential ethanol yield from grain and cob
Estimated best case ethanol yield ( gal/ dry ton)
Corn grain Cob Stover
Schwietzke et al ( 2009) 135 128 108
US DOE ( 2010) 124 113
Aden et al ( 2002) 113
Sheehan et al ( 2004) 113
Values used in this study 130 128 112
   Commercial value basis
Allocation based on market value was not considered. Today cob has limited market value
because cellulosic ethanol production process has not yet been commercialized.
   System expansion basis
System expansion method is recommended by Kim et al. ( 2009) and Wu et al. ( 2006) to
examine environmental burdens of ethanol from stover. In this allocation method, only the
incremental environmental burden resulting from harvesting of cob ( stover) will be allocated
to cob ( stover). In our context, this includes increased soil water evaporation due to removal
of biomass, increase in fuel consumption and corresponding increase in second- level offsite
water consumption, and finally additional nutrient requirements and hence incremental water
for salt leaching. Wu et al ( 2006) suggest that baseline environmental burdens may be allocated
to ethanol from stover after it is established on a commercial scale.
Kim et al ( 2009) estimate incremental fossil energy requirements due to cob harvesting in six
different locations in the US Corn Belt. Additional energy is required for harvesting of stover,
                                                                                                 
3 The tool uses the following factors to calculate yield: 1.11 pounds of C6 sugar per pound of polymeric sugar;
and 1.136 pounds of C5 sugar per pound of C5 polymeric sugar. Each pound of sugar yields a maximum of 0.51
pounds of ethanol, and there are 6.55 pounds of ethanol per gallon.
  17
additional nutrients ( agrochemicals) in the subsequent growing season, and drying of cob.
Corn cob is assumed to enter the combine, and harvested simultaneously with grain using an
additional wagon. The study reports an average incremental fossil energy input of 400 BTU/
dry lb ( 0.93 MJ/ kg) of cob. Kim et al ( 2009) assumed cob- grain yield ratio of 0.17; implying
energy allocation to corresponding grain is 5320 BTU/ dry lb ( 12.35 MJ/ kg).
We do not have information on moisture loss and need for incremental nutrients due to cob
harvesting; however we expect them to be negligible given that cob constitutes less than 20%
of the residue biomass. Our system expansion model considers only the embodied water of
the incremental fossil energy expended.
STEP 5: Bio- refinery water requirements and co- product crediting
In this step, we first estimate water required for conversion to ethanol of corn grain and corn
cob in a bio- refinery represented by BR gr
and BR cb . This gives the total water required for both
the corn and cob pathways. Further, the E e
gr ( E e
cb ) is expanded to include energy used in corn
grain ( cob) storage and transportation; and subsequent conversion of the grain ( cob) to
ethanol.
TWR gr = ET c
gr
+ PI gr + L a
gr + L c
gr + BR gr + E e
gr ( Equation 9)
TWR cb = ET c
cb
+ PI cb + L a
cb + L c
cb + BR cb + E e
cb ( Equation 10)
where,
TWR gr is the total water required in the corn grain pathway
TWR cb is the total water required in the cob pathway
TWR for each of the pathways is subsequently allocated between ethanol and co- products.
TWR gr- EtOH = TWR gr - TWR gr- cp ( Equation 11)
TWR cb- EtOH = TWR cb - TWR cb- cp ( Equation 12)
where,
TWR gr- EtOH represents the portion of TWR gr that is allocated to ethanol from corn
grain
TWR gr- cp represents the portion of TWR gr that is allocated to co- products produced
during conversion of corn grain to ethanol
TWR cb- EtOH represents the portion of TWR cb that is allocated to ethanol from corn cob
TWR cb- cp represents the portion of TWR cb that is allocated to co- products produced
during conversion of corn cob to ethanol
STEP 5A: Ethanol from corn grain ( Grain pathway)
The following table gives the ethanol yields and water requirements for dry mill and wet mill
bio- chemical conversion plants. The default values assumed by the model are also indicated.
  18
Table 5: Ethanol yields and process & cooling water requirements – grain pathway
Ethanol yield ( gal/ bu
grain)
Water requirement
( gal/ gal EtOH)
Dry mill Wet mill Dry mill Wet mill
Current / near term technology
Wu et al ( 2006) 2.72 2.62
Shapouri & Gallagher 2005 2.66 4.70
Shapouri, Gallagher & Graboski 2002 ( 1) 24.44
This study 2.69 2.62 4.70 24.44
Forecasted improvement ( 2015 - 2020)
Wu et al ( 2006) 2.85 2.75
This study ( 2) 2.85 2.75 4.44 23.28
Notes: ( 1) Based on Shapouri, Gallagher & Graboski 2002, wet mills water requirements are 5.2 times
that of dry mills
( 2) Based on improved ethanol yields.
The model can credit ethanol for various co- products based on three different approaches:
energy allocation method, market value allocation method, and displacement method.
The displacement method follows a four- step process ( General Motors 2001). First, the
amount of co- products produced in an ethanol plant is estimated. Second, the products to be
displaced by these co- products in marketplace are identified. Third, the displacement ratios
between co- products and the displaced products are determined. Finally, environmental
burdens in terms of water withdrawal and consumption of producing the amount of displaced
products are estimated. The estimated amounts of environmental burdens are subtracted from
total environmental burdens of ethanol pathway.
For the first three steps, we take values from available literature. Subsequently, we estimate the
water use of identified products being displaced by co- products of corn grain ethanol.
   Co- products produced
The co- products of dry and wet mill ethanol plants are given in the following table
Table 6: Corn grain ethanol production - co- product yields
Dry Mill Wet Mill
Distiller’s grain solubles ( DGS) 5.99 lb / gal of EtOH
Corn gluten meal or CGM 0.992 lb / gal of EtOH
Corn gluten feed or CGF 4.275 lb / gal of EtOH
Corn oil 0.794 lb / gal of EtOH
Notes:
( 1) Source: GREET 2010
( 2) CA- GREET assumes 5.34 lb of DGS per gal of EtOH ( CA- ARB 2009)
   Displaced products and displacement ratios
The following table identifies displaced products and displacement ratios adopted by GREET
version 1.8c ( GREET 2010), and CA- GREET (( CA- ARB 2009).
  19
Table 7: Displacement ratios assumed by various studies / models
1 lb of Co- product
CA- GREET ( 2009) GREET 1.8c ( 2010)
Dry Mill
DGS Displaces 1 lb of feed corn Displaces 0.992 lbs of corn,
0.306 lbs of SBM and 0.022 lbs
of N2 in Urea
Wet Mill
CGM Displaces 1.529 lbs of corn and
0.023 lbs of N2 in Urea
Displaces 1.529 lbs of corn and
0.023 lbs of N2 in Urea
CGF Displaces 1 lbs of corn and
0.015 lbs of N2 in Urea
Displaces 1 lbs of corn and
0.015 lbs of N2 in Urea
Corn oil Equal mass of soyabean oil Equal mass of soyabean oil
The model defaults to displacement ratios used in GREET 1.8c; although the user can modify
to parameters to adopt ratios used in RFS or CA- GREET or use input values.
   Water consumption
The model assumes that corn displaced by the various co- products for animal feed is grown in
the same region as the corn used for ethanol production. Water withdrawal and consumption
figures estimated in Steps 1 through 4 are used to calculate the water intensity of displaced
feed corn.
To estimate water consumption of soyabean meal and oil, we adopt a lifecycle basis similar to
corn to estimate water requirements of soyabean crop. Based on user inputs of crop
evapotranspiration, precipitation during crop season, and finally portion crop ET met through
soil moisture, the model estimates the total water required by soyabean crop.
Water required by soyabean crop = ETa
soy + Ps
soy + Pos
soy + PI soy + L a
soy + L c
soy
= ETc
soy + PI soy + L a
soy + L c
soy ( Equation 13)
The model defaults to the application efficiency assumed for corn grown as ethanol feedstock
– since soyabean is rotated with corn it will depend upon the same irrigation system as corn.
The same justification also applies behind assumption of conveyance losses. For places like
California, where soyabean is not grown, the user may use water requirement values applicable
for a different state.
Soyabean is crushed to produce oil ( SO), meal ( SBM), and some waste material. Water
requirements for crushing operations ( CR) are assumed to be 0.79 gallons of water per ton of
soybeans ( NREL 1998).
TWR soy = ETc
soy + PI soy + L a
soy + L c
soy + CR soy ( Equation 14)
  20
The model defaults to a SO yield of 11.39 pounds and a SBM yield of 43.9 pounds per bushel
of soyabean – the average US yields in 2002- 03 ( Pradhan 2009). Lifecycle water requirements
estimated for soyabean crop is allocated to SO and SBM on a mass basis.
Water intensity ( gallons H20 per lb) calculated for corn, SBM and SO is then multiplied with
appropriate displacement ratios to calculate environmental burden of displaced products
which are then credited to the system to give the water intensity of ethanol from corn grain.
Table A2.1 summarizes the water intensity of the displaced products.
The water requirement of the other displaced products, specifically N2 in Urea, is ignored in
this analysis. Further, we do not include the embodied water of on- site energy inputs at
various stage of SO and SBM production in our estimate of TWR soy . Both the above values
are likely to be small.
The following table summarizes the effect of the method adopted for crediting ethanol for
various co- products:
Table 8: Net water allocated to ethanol after adjusting for credit for co- products
Method Dry milling plant Wet milling plant
Energy content based( a) 61% of TWRgr 57% of TWRgr
Market value based( a) 76% of TWRgr 70% of TWRgr
Displacement method( b) ~ 33% of TWRgr ~ 50% of TWRgr
Notes: ( a) Source: GREET ( 2010) and Wang ( 2005)
( b) Source: Our model. Results may vary between states.
STEP 5B: Ethanol from Corn Cob
Wu et al ( 2009) report multiple conversion technologies using either biochemical conversion
( BC) or thermo- chemical conversion ( TC). However, none of them are in commercial
operation and data about ethanol yield and water consumption are likely to be uncertain. We
have modeled BC technology which consists of the following four steps: ( i) pretreatment
including physical sizing and prehydrolysis of the lignocellulosic biomass using dilute aid; ( ii)
cellulose hydrolysis via enzymatic hydrolysis; ( iii) fermentation; ( iv) purification/ distillation of
ethanol. Water is required both as process water and cooling water in all the four steps. The
only co- product of the BC process is electricity through the combustion of lignin residue.
Electricity demands of the bio- refinery process are met internally and the surplus is exported
to the grid.
Table 7: Ethanol yields and process & cooling water requirements for the cob portion
Ethanol yield
( gallons/ dry ton) Water required
Electricity
produced
Stover Cob ( 1)
( gal/ gal
EtOH)( 2)
( kWh/ dry
ton)( 3)( 4)
Current / near term technology
- Wu et al ( 2009) 9.80
- Wooley ( 1999) 66.70 76.43 8.90
  21
- Sheehan et al ( 2004) 67.36 77.19
- This study 76.81 9.35 200.25
Forecasted improvement ( 2020)
- Aden et al ( 2002) 87.00 99.70 5.90
- Wooley ( 1999) 99.00 113.45 6.00
- Wu et al ( 2006) 90.00 103.13 215.50
- Sheehan et al ( 2004) 89.82 102.93 185.00
- This study 91.45 104.80 5.95 200.25
Notes: ( 1) Estimated based on same level of conversion efficiency and maximum theoretical ethanol
yield calculated in Step 4
( 2) The water requirements are based on stover as feedstock. Denatured ethanol is assumed
( 3) Net electricity generated
( 4) Electricity produced is based on stover feedstock. We do not expect this value to change for cob
because of similar fraction of mass constituted by lignin
Since electricity is the only co- product, the model allows users to choose energy based
allocation. However, this method allocates water volumes to electricity on a gallon per kWh
basis is absurdly higher than electricity generated from conventional feedstocks. The model
uses system displacement method as the default option whereby credit available to cob
ethanol is based on the state’s average water footprint of thermoelectric electricity ( USGS
1998).
Onsite energy consumption
Energy is required at various stages of ethanol production. Diesel is required for farm
equipment operation, transportation of feedstock to bio- refineries, and distribution of ethanol;
electricity, coal and natural gas are used for bio- refinery operations. Because cellulosic ethanol
production is a net electricity generator, no energy inputs need to be considered in the bio-refinery
stage of the ethanol from cob pathway.
Table 8: Energy requirements for ethanol production
Fuel Farming Ethanol from grain
Ethanol from
cob(++)
Transp. Wet mill Dry mill Transp.
Units Per Bushel Per Bushel Per Gallon Per Gallon Per Dry Ton
Diesel/ Gasoline Gallons 0.06 0.04 1.83
Natural Gas ft3 1.96 29.48 27.62
Coal tons 0.00 0.00
Electricity kWh 0.20 1.09
Notes:
- Source: Energy requirements are based on GREET 2010. Energy requirements are in terms of units
defined in second column of this table. Thus diesel/ gasoline consumption during farming is 0.06
gallons per bushel of grain.
++ Values for corn stover
  22
For simplicity, we consider only the water consumption of various fuels. The default water
consumption values for various fuels assumed by the model are given below:
Table 9: Embodied water of various fuels
Water Consumption Sources Notes
Diesel/ Gasoline 5 gal / gal gasoline Wu et al ( 2009),
Gleick ( 1994)
Includes extraction and refining of
crude oil.
Natural Gas 5 gal / thousand cubic
feet of NG
Gleick ( 1994) Includes extraction, processing and
pipeline operations
Coal 50 gallons / ton of
coal
Gleick ( 1994),
Lovelace ( 2009)
Includes mining ( average of surface
and underground), refinement and
transportation
Electricity 0.45 gallons / kWh of
power generated
USGS ( 1998) National average of freshwater
consumption. State averages may be
used for regional analysis. See Table
A1.1 and A3.1
  23
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Appendix A1: Statewide average values of key input parameters
Table A1.1: Statewide average values of key input parameters
Region
Average
corn yields
( bu/ acre)
( 2)
Average
soyabean
yields
( bu/ acre) ( 2) Irrigation
system ( 3)
Share of
ground
water ( 4)
Average
conveyance
losses ( 5)( 6)
Thermo-electric
water
consumption
( gal/ kWh)
( 6)( 7)
California - San
Joaquin ( 1)
33% 4.6%
California -
entire state
182 -- Sprinkler ( 16%),
Surface ( 55%),
Micro ( 29%)
35% 3.6% 0.05
Illinois 175 47 Sprinkler ( 100%) 95% 0% 1.01
Indiana 166 45 Sprinkler ( 100%) 64% 0% 0.40
Iowa 183 47 Sprinkler ( 100%) 95% 0% 0.11
Minnesota 175 40 Sprinkler ( 99%) 88% 0% 0.42
Nebraska 178 47 Sprinkler ( 70%),
Surface ( 29%)
86% 12% 0.18
Notes:
( 1) Data for California San Joaquin Hydrological Region is from CA DWR ( 2005)
( 2) Source: USDA ( 2010). Average yields for the year 2009.
( 3) Source: USGS ( 2009). Irrigation system for entire state and across all crops.
( 4) Source: USGS ( 2009). Ground water as the percentage of total water withdrawn for irrigation.
( 5) Conveyance losses as a percentage of total irrigation water withdrawn
( 6) Source: USGS ( 1998).
( 7) Fresh water consumption only
Appendix A2: Water intensity of products displaced by co- products of ethanol from corn grain pathway
Table A2.1: Water intensity ( gallons H20 / lbs of product) of displaced products grown in various states
CA IN IA MN NE
Feed
Corn
Soya
bean
SBM /
SO
Feed
Corn
Soya
bean
SBM /
SO
Feed
Corn
Soya
bean
SBM /
SO
Feed
Corn
Soya
bean
SBM /
SO
Feed
Corn
Soya
bean
SBM /
SO
Withdrawn
- Ground
water
49 19 18 14 33 31 19 45 43 27 49 46 40 84 79
- Precip-itation
18 145 137 65 141 133 65 148 140 62 179 169 59 128 121
- Surface
Water
104 68 64 8 33 31 1 16 15 4 25 23 7 47 44
Used 115 207 195 81 192 182 81 196 185 86 237 224 91 231 218
Released 55 25 24 5 14 14 4 13 13 7 16 15 15 27 26
Notes:
1.   Water intensity of feed corn, soyabean crop and SBM are in terms of gallons H20 per oven dry lbs of the product
2.   Model assumes that feed corn and soyabean displaced are grown in the same region as the corn grown for ethanol production;
except in case of California. For CA, the model assumes that the displaced soyabean is grown in US Midwest.
3.   Above results assumed loamy soil for both soyabean and feed corn; and are based on parameter values given in Table A1.1
For a dry mill plant, the water requirements ( in gallons H20 per gallon of denatured EtOH
produced) of products displaced by DGS ( co- product) are given below
Table A2.2: Displaced water for ethanol from a dry mill
gallons H20 / gallons EtOH produced
CA IN IA MN NE
Feed
corn
SBM Feed
corn
SBM Feed
corn
SBM Feed
corn
SBM Feed
corn
SBM
Withdrawn
- Ground
water
290 34 81 56 112 78 161 85 236 145
- Precip-itation
104 250 384 244 387 257 367 311 352 222
- Surface
Water
617 117 46 57 6 28 26 43 43 81
Used 683 358 484 333 479 340 513 410 544 400
Released 328 43 28 25 26 23 41 28 87 48
Notes:
( 1) Displacement ratio: One lbs of DGS displaces 0.992 lbs of corn and 0.306 lbs of SBM.
( 2) 5.99 lbs of DGS produced per gallon of EtOH.
A wet mill plant produces multiple co- products – CGM, CGF and SO. Based on co- product
yields given in Table 6 and displacement ratios given in table 7, it can be shown that 5.79 lbs
of feed corn and 0.79 gallons of SO are displaced. The displaced water requirements are
summarized below:
Table A2.2: Displaced water for ethanol from a wet mill
gallons H20 / gallons EtOH produced
CA IN IA MN NE
Feed
corn
SO
Feed
corn
SO
Feed
corn
SO
Feed
corn
SO
Feed
corn
SO
Withdrawn
- Ground
water
283 15 79 24 110 34 157 37 230 63
- Precip-itation
101 108 375 106 377 111 358 135 343 96
- Surface
Water
601 51 45 25 6 12 26 18 42 35
Used 666 155 472 144 467 147 500 178 530 173
Released 320 19 27 11 25 10 40 12 85 21
  1
Appendix A3: Thermoelectric water consumption and withdrawal
Table A3.1: Fresh water consumption and withdrawal
Gallons / kWh
Consumption
( 1)
Withdrawal
( 2)
Consumption
( 1)
Withdrawal
( 2)
Alabama 0.14 26.46 Montana 0.92 1.79
Arizona 0.30 0.40 Nebraska 0.18 42.65
Arkansas 0.27 17.64 Nevada 0.54 0.60
California 0.05 2.24 New Hampshire 0.11 6.22
Colorado 0.49 1.18 New Jersey 0.07 7.65
Connecticut 0.08 2.45 New Mexico 0.60 0.61
Delaware 0.01 15.64 New York 0.82 20.94
D . C 1.54 21.32 North Carolina 0.22 26.02
Florida 0.14 1.24 North Dakota 0.35 12.88
Georgia 0.57 8.02 Ohio 0.91 22.21
Hawaii 0.04 0.00 Oklahoma 0.49 1.23
Idaho 0.87 Oregon 0.79 0.37
Illinois 1.01 24.01 Pennsylvania 0.52 11.63
Indiana 0.40 18.32 Rhode Island 0.00 0.01
Iowa 0.11 24.02 South Carolina 0.25 26.38
Kansas 0.56 3.71 South Dakota 0.01 0.68
Kentucky 1.05 13.51 Tennessee 0.00 40.59
Louisiana 1.50 37.01 Texas 0.42 14.02
Maine 0.28 3.51 Utah 0.54 0.59
Maryland 0.03 3.92 Vermont 0.33 32.69
Massachusetts 0.00 1.09 Virginia 0.06 20.30
Michigan 0.48 28.61 Washington 0.27 8.38
Minnesota 0.42 19.62 West Virginia 0.56 14.93
Mississippi 0.38 3.46 Wisconsin 0.47 44.51
Missouri 0.29 25.18 Wyoming 0.47 1.75
US Average 0.45 16.05
Notes ( 1) Source USGS ( 1998). Data for 1995
( 2) Source USGS ( 2009). Data for 2005