Journal of Water Resource and Protection, 2013, 5, 747-759 Published Online July 2013 (
Agricultural Water Conservation in the High Plains
Aquifer and Arikaree River Basin
Adam Prior1, Ramchand Oad1, Kristoph-Dietrich Kinzli2
1Department of Civil and Environment Engineering, Colorado State University, Fort Collins, USA
2Department of Environmental and Civil Engineering, Florida Gulf Coast University, Fort Myers, USA
Received April 27, 2013; revised May 28, 2013; accepted June 19, 2013
Copyright © 2013 Adam Prior et al. This is an open access article distributed under the Creative Commons Attribution License,
which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Yuma County is the top crop producing County in Colorado that is dependent on groundwater supplies from the High
Plains aquifer for irrigation. The Arikaree River, a tributary of the Republican River in eastern Colorado, is supplied
with water from the High Plains aquifer. The Arikaree River alluvium is also a habitat for many terrestrial invertebrates
and the threatened Hybognathus hankinsoni (Brassy Minnow). The constant demand on the High Plains aquifer has
created declining water levels at the linear rate of 0.183 m/year with the deepest pool in the Arikaree River drying up in
8 to 12 years. In addition to the demands for habitats, the surrounding irrigated agricultural lands require water for crop
production. These challenges are currently confronting farmers in eastern Colorado and this research presents possible
alternatives to meet these demands. This research presents a combination water balance model, water conservation
model, and water conservation survey results from farmers in eastern Colorado to identify alternatives to extend the life
of the Arikaree River. The first alternative was to examine the reduction in irrigation water from removing the 18 allu-
vial irrigation wells that could extend the Arikaree River pools from drying up for 30 years. The other scenario found
that water conservation practices with participation of 43%, 57%, and 62% of farmers would extend the drying time to
20, 30, and 40 years, respectively. The final alternative studied was the required participation in conservation practices
to stop the decline of the High Plains Aquifer. The analysis found that 77% participation of farmers in all conservation
alternatives or reducing pumping by 62.9% would be necessary to stabilize the High Plains Aquifer.
Keywords: Agriculture; Conservation; Groundwater; Irrigation; Pumping; Water Balance
1. Introduction
Throughout the United States, and especially in Colorado,
farmers confront the challenges of meeting water needs
for crop production, while trying to maintain natural ha-
bitats and conserve dwindling water supplies. The Arika-
ree River is a tributary of the Republican River on the
Great Plains of Eastern Colorado and is groundwater
dependent with flows from the underlying High Plains
aquifer. The river is characterized by an extensive gallery
of mature riparian cottonwoods (Populus deltoids), well-
developed refuge habitat for threatened fish species such
as the Brassy Minnow (Hybognathus hankinsoni), as
well as habitat for many terrestrial invertebrates sus-
tained by water from the High Plains aquifer. The ripar-
ian habitat areas along the Arikaree River are a critical
component of stream-riparian ecosystems in the Great
Plains [1]. In addition to the demands for the mainte-
nance of habitats, the surrounding irrigated agricultural
land requires water as well. The irrigation water supply is
groundwater pumped from the High Plains aquifer by
high-capacity pumps. In recent years, the river has be-
come a series of disconnected pools or has dried up en-
tirely during the late summer. To sustain both a precari-
ous regional agricultural economy and an aquatic/ripar-
ian ecosystem, both dependent on groundwater for exis-
tence, there must be tradeoffs to preserve this important
resource. The research presented here provides practical
guidelines for water conservation, water management
practices, and identified feasible and realistic conserva-
tion measures for farmers in Eastern Colorado.
1.1. Study Area
The research study area was located in Yuma County,
Colorado with the Yuma County border as the eastern
and western boundaries. The north and south boundaries
constitute the groundwater divide as shown in Figure 1
opyright © 2013 SciRes. JWARP
from geology and groundwater resources of Yuma Coun-
ty, Colorado, USGS water-supply paper 1539-J [2].
The Arikaree River has headwaters on the plains in
eastern Colorado that flow northeast through Kansas be-
fore joining the Republican River in the southwest corner
of Nebraska. The river is a fluctuating stream [4], pri-
marily sustained by inflow from springs or seeps from
the High Plains aquifer and by storm events. The average
annual stream flow from 1932 to 2009 has decreased
significantly as shown in Figure 2. After the introduction
of groundwater pumping in the 1960’s, there is a marked
decline in the average annual flows.
The High Plains aquifer is a part of the Ogallala Aqui-
fer, the largest aquifer in the United States. Colorado
only has 4% of the High Plains aquifer available for us-
able water [5,6]. Since the High Plains aquifer both feeds
and connects to the Arikaree River, the geomorphology
has a significant effect on flow regimes [7]. The Ogallala
Figure 1. The Arikaree River basin within southern Yuma
County [3].
Figure 2. Annual average stream flows in the Arikaree Ri-
ver at Haigler, Nebraska from 1932 to 2009 [12].
Formation overlies the Pierre Shale and is made of layers
of sand, gravel, clay, limestone, and sandstone [2].
Research has shown that the water table is declining
by about 0.25 m/yr near the Arikaree River [8] with the
average rate of decline of the water table at 0.34 m/yr [9].
Reference [10] determined an annual water table decline
of 0.3 m in the High Plains. Data collected by the Colo-
rado Division of Water Resources [11] found the average
water table decline of 2.08 m from 1988 to 2002 that
equaled a decline of 0.15 m per year.
The Arikaree Groundwater Management District has
reported a decline 1.14 m in saturated thickness from
1997 to 2004 or 0.16 m/year [13].
1.2. Water Conservation
Water conservation can be defined as long-term increase
in the productive use of a water supply without compro-
mising the desired water services. Water conservation in
terms of agricultural production can also mean more effi-
cient water use, transmission and distribution system effi-
ciency improvements, reduced evaporation and runoff,
and the production of crops with reduced water require-
ments. Opportunities to address the concurrent water
needs of irrigators and the stream flow requirements for
fish habitat are many and diverse. A comprehensive lit-
erature review was completed about the conservation
methods and practices used throughout the country and
in the arid western United States under conditions similar
to the High Plains aquifer and Arikaree River alluvium.
The water conservation alternatives were divided into
five different categories that included field conservation
practices, irrigation conservation practices, management
conservation practices, water conservation programs, and
lower consumptive use crop selection.
Field practices for water conservation increase the
amount of water stored in the soil profile by trapping or
holding rain where it falls, or where there is some small
movement as surface runoff [14]. Local farmers in a wa-
ter conservation survey identified the no-tillage field
practice as the most feasible conservation measure with
approximately 20% of the corn acres in produced in the
United States utilizing no-tillage practices.
No-till field management can save 10.2 to 12.7 cm of
water for corn in Kansas with the combined growing and
non-growing season [15]. In eastern Colorado from 2000
to 2004, corn crop residue also showed to have a signifi-
cant effect during the non-growing season (October to
April) by increasing stored soil water by 5.08 cm when
compared to conventional stubble mulch [16]. Wheat stu-
bble will increase soil water storage by 5.08 to 6.35 cm
when compared to bare soil [17]. Wheat straw and no-till
corn stover will save 6.35 to 7.62 cm of water from early
June to the end of the growing season [18]. In Akron,
Colorado, it was determined that no-till with wheat resi-
Copyright © 2013 SciRes. JWARP
due accumulated 11.68 cm of recharge over the fall, win-
ter, and spring compared to conventionally tilled wheat
residue that only had 6.35 cm of recharge for a total sav-
ings of 5.33 cm during the non-growing season [16].
Irrigated agriculture uses approximately 80% of all the
available water supplies in the Western United States
[19-22]. Center pivot sprinkler irrigation systems are the
most common form of irrigation used in the High Plains
of Colorado [22]. About 90% of the irrigation systems
use center pivots and pump from the High Plains aquifer
[23,24]. The development of multi-functional systems
such as low energy precision application (LEPA) allow
farmers to apply water and also practice precision appli-
cation of herbicides, pesticides, and fertigation [25]. The
LEPA systems are highly efficient and can achieve ap-
plication efficiencies in the 95% to 98% range [26] and
[27] while other research suggests efficiency ranges from
80% to 95% depending on management [22].
A common water saving upgrade of center pivots is to
reduce operating pressure and apply water within or be-
low the crop canopy. Upgrading sprinkler systems to low
pressure heads with drop tubes reduces evaporation from
the plant surface, especially for corn [28]. If properly uti-
lized, these improvements can result in water savings of
10% to 15% compared to traditional center pivot sprink-
ler applications [22].
In eastern Colorado, the climate is semi-arid requiring
some level of irrigation during drought years to maxi-
mize certain crop yields. Water conservation survey re-
sults of eastern Colorado farmers found that drought tol-
erant crops were the most preferred and feasible water
conservation alternative. Today’s best drought-tolerant
crop hybrids, developed through conventional breeding,
often yield within 75% to 80% of their average low-
stress yields under drought stress. Other research com-
paring hybrid yields for the last three decades showed
that genetic improvements have increased yields 2.6%
per year [29] due to hybrid water stress tolerance [30].
Reference [31] discovered a new corn hybrid that stress-
sed at 50% of crop required ET produced 27% higher
yields, but with adequate water, both hybrids produced
similar yields. Corn breeders have found a new germ-
plasm that can reduce water usage by 10% [32]. Xu and
Lascano [33] found new corn hybrids that produce the
same silage yield with a 75% crop water requirement
(CWR) [32].
A wide range of programs to conserve water through
state and national agencies exist in Colorado, in Yuma
County, and in the Arikaree River basin. The 2007 Cen-
sus of Agriculture in Yuma County Profile [23] said that
432 farms out of the 970 total farms in Yuma County par-
ticipated in agricultural conservation programs. The farm
participation in conservation programs increased from
28% in 2002 to 45% in 2007 [23]. Water conservation
survey results of eastern Colorado farmers found that
water use limits were considered a feasible water con-
servation alternative. Reference [34] conducted research
over a 10-year period showing that applying 15.2 cm per
crop using limited irrigation can achieve winter wheat
yields at 99%, corn yields at 86%, and soybean at 88% of
the full irrigation yields. With proper management of
25% - 50% water application reductions, the income re-
duces by only 10% - 20% [34]. Another successful water
use limit program by the Nebraska Upper Republican
Natural Resources District (URNRD) allows 184.2 cm
(36.8 cm/ year) of water in any five-year period [35]. The
water use limits have required farmers to be more re-
sourceful and creative in managing water allocations. Re-
search from 1986 to 1999 demonstrated that, if required,
farmers could survive with less water usage because they
were only using 80% of the allocated water for the five-
year period.
Low consumptive use crops can be cool season crops
that are subject to lower atmospheric demand that direct-
ly relates to lower ET rates. Switching to crops with
shorter growing seasons will reduce crop water and irri-
gation demands in order to conserve water. This research
has identified lower water use crops as any crop that has
a lower consumptive use than corn, because corn is the
dominant irrigated crop grown in eastern Colorado.
2. Materials and Methods
2.1. Water Balance
To address water shortages and impacts to the Arikaree
River, a water balance model was developed to compare
pre-development (before pumping), post-development
(after pumping), future conditions, and the possible im-
pacts of water conservation. This water balance does not
account for spatial and temporal variability in parameters
such as recharge, evapotranspiration, and pumping, but
provides the initial analysis in understanding and model-
ing the aquifer and river hydrologic system. The model
was broken into three distinctive model areas that include
the regional High Plains aquifer, the alluvium model, and
a complete model combining the High Plains aquifer and
alluvium. Figures 3 and 4 show the pre- and post-deve-
lopment model parameters used in the High Plains aqui-
fer and alluvial aquifer with their respective data sources.
Stream inflow from the aquifer was assumed to be
10% of the average stream flow data measured at USGS
gauging station #6821360 (Haigler, NE) from 1933 to
1960 based on previous research done by Squires [8].
Stream outflow was the average stream flow measured at
USGS gauging station #6821360 (Haigler, NE). The con-
stant flux boundaries specified at the upstream boundary
and at the downstream boundary of the alluvium estima-
tions came from the 1958 head contour map [2]. The hy-
Copyright © 2013 SciRes. JWARP
Ralluv = 1.88 × 107 m3 ETR = 8.10 × 10
ETG = 2.77 × 10
6 m3
7 m3
SFin = 2.30 ×
106 m3
(Qalluv)out =
1.03 × 106
SFout =2.30 ×
Area = 28,530 ha
Δ Storage 0
Qflux = 3.43 × 107 m3
(Qalluv)in =
4.45 × 106
RHPA = 3.73 × 107 m3
Ralluv = 1.88 × 107 m3
Rtotal = 5.61 × 107 m3
ETR = 8.10 × 10
ETG = 2.77 × 1
ETtotal = 3.58 ×
6 m3
07 m3
107 m3
(Qtotal)in =
8.23 × 106 m3
SFin = 2.30 ×
106 m3
Avg Q
= 2.02 × 10
= 3.73 × 10
(Qtotal)out =
7.80 × 106
SFout = 2.30 ×
Regi onal Aqu ifer
Area = 149,980 ha
Δ Storage 0
RHPA = 3.73 × 107
3 Qflux = 3.43 × 107 m3
(QHPA)in =
3.77 × 106
(QHPA)out =
6.77 × 106 m3
High Plains Aquifer
Area = 121,450 ha
Δ Storage 0
Figure 3. Initial water balance for the regional aquifer,
High Plains aquifer, and the alluvial aquifer (terms in Bold
solved in the pre-development water balance).
draulic conductivities used in the groundwater bounda-
ries and flows between hydraulic units were found by [36]
with the alluvium hydraulic conductivities being three
times higher than in the surrounding areas [2,36]. Ripar-
ian evapotranspiration research by [37] established an
average value of 89.2 cm in the 2006 growing season.
This riparian evapotranspiration value affected an area of
909 ha as delineated by [3]. The alluvium grass evapo-
transpiration was a calibration constant used to balance
the alluvial water balance. The alluvium grass evapo-
transpiration was assumed to be 10 cm/yr over the re-
mainder of alluvium (27621.5 ha). Reference [38] found
in Akron, Colorado that native grasses used 9 cm, 10.6
cm, and 19 cm respectively in 1966, 1966, and 1967. The
alluvium grass evapotranspiration area was the remaining
area in the alluvium outside the riparian area for a total
area of 27,621 ha (28,530 ha - 909 ha). Recharge to the
alluvium was determined to be approximately 15% from
research completed by [39] and the regional water bal-
ances [8]. For the alluvial aquifer, the estimation of the
3.77 × 10
High Plains Aquifer
Area = 121,450 ha
Δ Storage =4.15 cm/yr
6.77 × 10
= 6.45 × 10
= 1.88 × 10
= 8.10 × 10
Area = 28,530 ha
Δ Storage = 2.43 cm/yr
Avg Δy = 0.043 m/yr
(average from 1968-2010)
1.03 × 10
4.45 × 10
= 7.65 ×
= 7.65 ×
= 6.68 × 10
Avg Q
= 2.02 × 10
(average from 1968-2010)
Figure 4. Post-development water balance for the High
Plains aquifer and the alluvial aquifer (terms in bold Solved
for in post-development the water balance).
uniform recharge was to be 6.6 cm, 15% of the average
precipitation of 44 cm based on a lysimeter in the allu-
vium along the South Platte in Fort Morgan County,
Colorado [8,39]. Recharge to the High Plains aquifer was
determined to be approximately 7% of the average pre-
cipitation of 44 cm from 1932 to 1960 from research by
The specified constant flux boundaries at the upstream
boundary and at the downstream boundary of the High
Plains aquifer estimates came from the 1958 head con-
tour map [2]. Since the stream flow gauging station is
approximately 11,300 meters downstream of the Yuma
County boundary, the water balance did not use all of the
groundwater flow leaving the boundary. The [2] contours
shows the groundwater entering the river prior to the
gauging station so they were not used in calculations to
avoid double counting water flows. The groundwater flux
out of the High Plains aquifer and into the alluvial aqui-
fer was estimated from the pre-development calibrated
regional models to match well data and to balance each
A pre-development (1933-1960) water balance model
was created to determine model calibration groundwater
flux between the model boundaries Figure 3. The pre-
development water balance has negligible storage change
over time (ΔS = 0) for prior to 1960 [8]. A second water
Copyright © 2013 SciRes. JWARP
balance (1968-2009) was developed by utilizing the pre-
development water balance and current irrigation pum-
ping rates. The post-development water balance model
added average (2002-2006) irrigation well pumping out-
put of 71.2 million cubic meters [3,37,42,43].
Figure 4 illustrates the average water balance for the
post well-installation period (post-1968). It was assumed
that recharge for the alluvium will increase from 15% to
20% because of the increase capacity for infiltration in
the alluvium aquifer (1975 to 2010). This calibration was
to align the water balance model and the measured well
water elevation data. Historically, the main discharge out
of the basin was the stream flow that significantly de-
creased after the installation of irrigation wells. The addi-
tional water entering the alluvium represents recharge to
the aquifer or evapotranspiration out of the basin. There-
fore, the recharge was assumed to linearly increase from
1968 to 1974 to a recharge rate of 20%.
Figure 5 shows a two-dimensional diagram of the
HPA and the alluvial aquifer interaction with variables
used in Darcy’s Law calculations.
To estimate the groundwater flux into the alluvium
throughout time, a one-dimensional form of Darcy’s Law
calculated the flow in the x-direction per unit width as
shown in Equation (1):
 (1)
uvium Lt
=groundwater flux from the HPA to the all
at time t L
K=hydraulic conductivityL
=the saturated thickness of the aquifer at x
dhdx=hydraulic gradientLL
Equation (1) also assumed the Dupuit-Forcheimer as-
sumtions [44] are valid. Integrating Equation (1) with the
Figure 5. 2-D Schematic showing the relationship between
boundary conditions:
at x = 0, h(0,t) = h1
at x = L, h(L,t) = h2
Results in
flux2 1
Q=h h
2L (2)
gth of the transitional areaL
L = len
hx,t= h0,tsaturated thickness in the HPA at x
=0 at year t
=hL,tsaturated thickness in the alluvial aquifer at x
=L at year t
t=time in years,t=1933 to 2009
The hydraulic head in the High Plains aquifer is larger
he water table to-
ence in the changes in water table ele-
 
an in the alluvium because the High Plains aquifer has
a large recharge area in the dune sands north of the river
while the river and alluvium are discharge areas, particu-
larly in predevelopment. Hydraulic head in the High
Plains aquifer (h1) and hydraulic head in the alluvial aq-
uifer (h2) both change with time due to the change in
aquifer storage and precipitation levels. The decline in
the High Plains aquifer due to irrigation pumping will
result in a decreasing flux into the alluvium aquifer over
time. Application of Darcy’s law would suggest that the
change in groundwater flux from the High Plains aquifer
to the alluvium is not linear over time.
The analysis assumed the slope of t
ards the river in the alluvium and High Plains aquifer
was small to satisfy the Dupuit-Forcheimer assumptions
that all flows are horizontal and the hydraulic gradient
causing discharge is proportional to the slope of water
table [44]. The research assumed the changes in the allu-
vial water table elevation occurred uniformly across the
entire alluvium.
To have confid
tions over time, both Darcy’s law and the yearly water
balance had to be satisfied. For a yearly water balance:
Out In
Area Sya
low out of model boundary
was written so that a
Out = F
In = Flow into model boundary
Area = Area of model boundary
Sya = Specific yield of aquifer
For convenience, this equation
sitive value of
Δyt implies a decline in the water
table. For the High Plains aquifer:
the High Plains aquifer and the alluvial aquifer.
Copyright © 2013 SciRes. JWARP
Copyright © 2013 SciRes. JWARP
Calculations of the decline in water levels in the High
Plains aquifer using the method described above were
compared to measured well data. Figure 6 shows High
Plains aquifer water elevation data at Well #9380 and the
calculated water balance model water elevations. The
calculations of the water table elevations started at the
initial water table elevation that occurred at Well #9380.
This well was chosen for this research because it was
used in previous research by [8] and had water levels
elevations for the entire post-development modeling
(1968 to 2009).
  
out in
 (3)
The units in Equations (3) and (4) are m3/yr in the nu-
d the average Sya
erator and m2 in the denominator.
For the alluvial aquifer:
37] founResearch conducted by [8,
be 0.124, using storm events and groundwater model-
ing. In addition, wells were installed over a period of
years so that Qw for both the alluvium and the High
Plains aquifer increased from 60% in 1968 to the final
constant pumping value in 1975.
The water table elevation at the beginning of each
Results for the alluvial aquifer are more uncertain and
variable due to varying inputs from the High Plains aq-
uifer. Figure 7 shows the calculated water balance model
as compares to the actual measured water table levels in
three alluvium wells. Water level data was very limited
within the alluvium with only three wells with data and
ason was determined by subtracting the change from
the water table elevation at the beginning of the previous
season as shown:
t-1-Δyt (4a)
= saturated thickness in the HPA at time t
e t
halluv(t) = saturated thickness in the alluvium at tim
uEqations (1) through 4 were used to calculate yearl
ater table levels changes in the model region. In the
first year, the groundwater flux was from the initial water
balance and was entered into Equations (3) and (4) to
determine the water table elevation changes for the fol-
lowing year. Then the water table elevation changes were
entered into Equations (4a) and (4b) to determine the
saturated thickness in both aquifers. At that point, equa-
tion 2 was used to determine the new groundwater flux.
Introducing this new groundwater flux into the next
equation allowed for the calculation of water table
changes for the following year. Repeating this process for
each year from 1968 to 2010 resulted in a yearly ground-
water flux, yearly water table elevation in the High
Plains aquifer, and yearly water table elevation in the
alluvial aquifer. This water balance model was calibrated
to match alluvium well data and High Plains aquifer well
data. The water balance model projections beyond 2010
appear in future sections. The length of the transitional
area, L, in Equation (2) was unknown, but calibrated
based on Qflux from the water balance model. The planar
length on each side of the river where the High Plains
aquifer is in contact with the alluvial aquifer is approxi-
mately 12,940 m, that would correspond to the average
distance from the edge of the alluvium to the monitoring
wells in the High Plains aquifer.
Figure 6. Measured water elevation and calculated water
table elevation for one well in the High Plains aquifer.
1968 1973 1978 1983 1988 1993 1998 2003 2008
Alluvium Wat er Table Elev at ion, h
, (m )
Time (year)
lluv iu m W a te r Tab le
bottom of alluvium
Figure 7. Measured water elevations for the only three
Wells in the alluvium and calculated alluvium water eleva-
tions in Yuma County.
RGoutallumwalluvalluvin flux
out alluvin
Δyt 28,530Sya
 
only one well with data from the entire post development
time period. Alluvial well #10741 was utilized to cali-
brate the water balance model within the alluvium.
The measured water level data in the High Plains aq-
uifer and alluvial aquifer displayed nearly identical char-
acteristics to the water balance models. The Nash-Sut-
cliffe modeling efficiency statistic was utilized to com-
pare the measured and predicted water levels.
The Nash-Sutcliffe model evaluation statistic is widely
used to validate various models [45-47]. The Nash-Sut-
cliffe model efficiency statistic is defined in Equation (5).
In this equation Qo is an actual measu
model predicteue, and t
Q is actual measurement at
A water conservation model was created using data from
previous research [3,8,37,42,49]. Other dat
water conservation model was the current
local farmers in the noted conservation alternatives that
irrigation conserva-
ion practices, water
cused on
western United States and
emented in the Arikaree
rement, Qm is the
d val
e t. Nash–Sutcliffe efficiencies can range from −∞ to
11. An efficiency of one (E = ) corresponds to a perfect
match of modeled values toe measured data. An effi- th
ciency of zero (E = 0) indicates that the model predic-
tions are as accurate as the mean of the observed data.
Efficiency less than zero (E < 0) occurs when the ob-
served mean is a better predictor than the model [45]. In
general, a Nash-Sutcliffe efficiency of 0.70 indicates that
a model can adequately predict measured values. The
High Plains aquifer water balance model and measure
data from well #9380 have a Nash-Sutcliffe efficiency of
0.95 from 1968 to 2009. The alluvial aquifer and water
balance model has a Nash-Sutcliffe efficiency of 0.46
from 1968 to 2009. This value is much lower due the
variability and fluctuation of the water levels from 1968
to 1985. This variability is due to the annual hydrologic
conditions and aquifer water being released from storage.
The Nash-Sutcliffe efficiency is 0.68 from 1985 to 2009
due to the better correlation of the water balance model
and the alluvial well data.
Shallow alluvial groundwater stage directly relates to
pool depth across six pairs of wells and pools in the up-
stream segment from April through October 2007. As the
groundwater stage declined during the summer, pool
depths also declined. Falke, Fardel, and Griffin [42,49],
and [43] found a strong correlation between the alluvial
water table and the pool depths. These observations
showed a direct relationship between pool stages in the
Arikaree River and the alluvial groundwater levels [49].
The deepest pool in the upstream section in 2006 was 1.5
m. Therefore, for these modeling efforts we assume the
bottom of the pool was approximately 1.5 m below the
water table elevation in 2006.
2.2. Water Conservation Model
a used in the
participation of
include field conservation practices,
tion practices, management conservat
conservation programs, and lower consumptive use crop
selection. The final water conservation model parameter
was the possible future participation of local farmers in
water conservation that provides the constant for all al-
ternatives. Modifying this parameter determined what
impacts all the participation levels (1% to 100%) would
have on the groundwater balance models.
The crop water requirements were calculated by util-
izing a collection of reference ET data from the Colorado
Agricultural Meteorological Network (CoAgMet). Ref-
erence [48] is a network of automatic weather stations
distributed across Colorado with data since 1992. The
weather stations selected for this research were locations
throughout the research area characterized as an irriga-
tion area. The CoAgMet used the Kimberly-Monteith
method to estimate crop water use for corn and dry beans.
The crop water requirements were 64.2 cm for corn and
55.8 cm for dry beans. Reference [23] found that in
Yuma, County that approximately 52% of all the crops
harvested and 75% of all the irrigated crops were corn
providing the baseline for conservation measures. The
water conservation calculations in the irrigation practices,
management practices, programs, and crop selection used
corn as the baseline. Conservation irrigation practices
typically increase the application efficiency with the wa-
ter savings calculated based on the corn water require-
ments. The conservation management practices can re-
duce a percentage of the corn water requirements to cal-
culate the total water savings. The programs section and
the crop selection water savings calculations were based
on corn being grown throughout Yuma County.
2.3. Conservation Survey
A water conservation survey was developed from multi-
ple sources, including consultations with local agricul-
tural experts and a comprehensive literature review of
conservation methods. The literature review fo
research conducted in the arid
Colorado that could be impl
River basin. The purpose of the surveys was to identify
the most feasible conservation methods for farmers in
eastern Colorado. The surveys were critical to ensure that
the communities completely engage in the research in
order to successfully gain local insight into feasible con-
servation measures.
The survey was broken into seven sections: General
Farm Information, Field Practices, Irrigation System,
Management Practices, Programs, Crop Selection, and
Demographic Information. The water conservation sur-
Copyright © 2013 SciRes. JWARP
veys were distributed to 227 farmers in eastern Colorado,
41 surveys were returned for an 18% response rate. The
top feasible conservation alternatives identified by local
e from 1932 to 2009 of 0.44
1968 to 2009). The wa-
odel of the High Plains aquifer estimated
ecline was 0.242 m, which is similar to the
y 1985, the alluvium water table
87 to
gure 8). A possible
rmers include: no-tillage for the field practices; instal-
lation of low-pressure sprinkler packages for irrigation
systems; planting crops that use less water (i.e. drought
tolerant crops) for the management practices; utilization
of water limit incentive conservation programs; and
planting lower water use crop such as dry beans to re-
place the corn predominantly grown on approximately
52% of all croplands in Yuma County. These water con-
servation survey results directed the water conservation
analysis and water balance analysis on the High Plains
aquifer and alluvial aquifer.
The future water balance modeling utilized average or
constant values for all parameters projected into the fu-
ture. For example, the stream flow out was linearly de-
creased at a rate of 12,007 m3/year for the best-fit line of
the stream flow for the last 10 years. An average pa-
rameter used in the future water balance modeling was
the precipitation data averag
eters. The actual future water levels in the High Plains
aquifer fluctuated due to varying climatic conditions such
as droughts and wet years. All future modeling projec-
tions do not account for possible temporal climate
change. The water levels of the High Plains aquifer and
alluvial aquifer have significant impacts from recharge
that are directly proportional to precipitation. Since
large-scale agricultural irrigation began in Yuma County
during the 1960s, the volume of groundwater used for
irrigation has been relatively constant since 1975. In the
[23] the irrigated land in Yuma County showed a de-
crease of 0.7% from 2002 to 2007. The current irrigation
pumping rates within the Arikaree River basin were as-
sumed constant for forecasting.
3. Results
The results for the High Plains aquifer are relatively
straightforward, based on the measured data, and mod-
eled information. The existing irrigation well water levels
from this study indicate the High Plains aquifer is cur-
rently declining at 0.249 m/year (
ter balance m
groundwater d
measured decline rate (Figure 6). Although a straight
line can approximate the water table decline in the High
Plains aquifer, the water table decline in the alluvium
appears to be nonlinear.
The existing alluvium well data suggest that from
1968 to approximately 1985 there was a slight decline in
the alluvium water levels with fluctuations from climatic
patterns (Figure 7). This could indicate the water in the
alluvial aquifer was being released from the storage to
supplement the lack of water from the High Plains aqui-
fer flux. In approximatel
tablished new declining water table equilibrium in cor-
respondence to the declining High Plains aquifer.
The goal of the modeling was to match the alluvial de-
cline from 1985 to 2009. There were only 3 alluvial irri-
gation wells with water table data and only one well
(#10741) with data for the entire post-development mod-
eling. The other two wells only had water table data from
1987 to 2009 (Figure 7). The well data for #19371 and
#10741 have very similar linear declines from 19
09 so calibration of the model used these wells. The
well data from #11755 is believed to be flashier due to
the Pierre Shale geology located near the Colorado and
Kansas bounder. The fluctuations of the alluvial water
table directly related to the precipitation and stream flow
in the Arikaree River Basin. This knowledge about the
water table fluctuation leads to the conclusion that the
alluvium has had a steady decline in water levels since
1985. The average decline of the alluvial water table
from 1985 to 2009 was 0.079 m/year using data from
wells #10741 and #19371. Falke [49] took a census of all
refuge pool habitat within each of the three segments
during late July, the period of lowest connectivity, from
2005-2007. No pools were present in the downstream
segment during any of the surveys. In that time range,
there were 172 to 218 pools identified in the upstream
segment that contained water. The middle segment had
between 27 to 35 pools surveyed for habitat [49]. Overall,
the upstream segment contained significantly more fish
habitat pools than the middle segment during the driest
portion of 2005 to 2007 [49]. Given the higher incidence
of drying in the downstream and middle segments [50],
we chose to model only the upstream portion of the basin
where the alluvial aquifer directly connects to the High
Plains aquifer, and where essential habitats for fish are
most likely to persist into the future.
The first scenario examined the impacts of no changes
to the current water usage and pumping rates throughout
the High Plains aquifer and the alluvium. The High
Plains aquifer will continue to decline at a linear rate of
approximately 0.183 m/year (future projections). This
rate is a lower decline rate than the measured rate of
0.249 m/year from 1968 to 2009 (Fi
ason for this reduced decline is that the High Plains
aquifer saturated thickness is decreasing and therefore
the flow out of the High Plains aquifer is decreasing. The
alluvial aquifer decline starts out slowly throughout the
1960’s and 1970’s and increases with time (1985 to 2009)
because the alluvial aquifer is sensitive to changes in the
groundwater flux (Figure 9). When less water feeds the
alluvium, more water is taken from storage causing the
water table elevation to decline. The modeling data
matches well with water level data from well #10741.
The change in groundwater flux from the High Plains
Copyright © 2013 SciRes. JWARP
1140. 0 0
1142. 0 0
1144. 0 0
1146. 0 0
1148. 0 0
1150. 0 0
e El evatio n in the HP A (m )
HPA Water Table
Future HPA Model
y = -0.1832x + 1507.2
R² = 0.9997
1965 1975 1985 1995 2005 2015 2025 2035 2045 2055
Water Tab l
Time (y e ar )
1130. 0 0
1132. 0 0
1134. 0 0
1136. 0 0
1138. 0 0
Modeled (1968-2009)
Future Modeli ng (2010-2050 )
Linear (F uture M o de ling (2010-205 0))
Figure 8. Alluvium aquifer water balance model with no
changes and projected into the future to 2050.
vation in the a
1965 1975 1985 1995 2005 2015 2025 2035 2045 2055
Water Table Elelluvium , h
, (m)
Time (year)
Alluvium Water Table
Al l u v i u m M ode l
Alluvium Well #10741Future Model Pool Bot t o m
Figure 9. High Plains aquifer water balance model with no
changes and projected into the future to 2050.
aquifer to the alluvium is non-linear decline. The esti-
mated time-to-drying for the deepest pool in the upper
segment varies from approximately 8 to 12 years de-
pending on interactions of the riparian habit along the
he next model scenario examined the immediate im-
could have flows re-
nd alluvial aquifer were mod-
river, hydraulic parameters around the pool, and the High
Plains aquifer flux into the pools.
pact on the alluvial aquifer due to the elimination of 18
pumps in operation within the alluvial aquifer. The im-
mediate impact to the Arikaree River is due to the close
proximity and the direct impact that these wells have on
the river. The alluvial wells that are only approximately
1390 m (#10741) from the river
rned to the Arikaree River within 30 to 45 days. The
only impact on the High Plains aquifer is the change in
gradients between the aquifer due to the reduced decline
of the alluvial aquifer. This scenario creates a temporary
rise in the alluvial aquifer due to the sudden increase in
flows to the alluvium. The interaction of the High Plains
aquifer and alluvial systems in post-development has
equilibrium declining at 0.0791 m/year with constant
pumping. When the pumping is stops, it creates a tempo-
rary increase and then could create another equilibrium
decline at a rate of 0.0941 m/year according to the water
balance model. This scenario could potentially extend the
projected pool dry up time to approximately 30 years as
shown in Figure 10.
The next model scenario evaluates what level of par-
ticipation in the identified water conservation practices
would be required to stop the decline in the High Plains
aquifer (not including elimination of alluvial wells). The
model developed included the top conservation alterna-
tives from each of the five survey sections. The impacts
to the High Plains aquifer a
ed by reducing the quantity of water pumped to the
sum of 44.8 million cubic meters due to conservation
measures. It was determined that, in order to stop the
decline of the High Plains aquifer water tables it would
require 77% participation of local farmers in the project
area. Participation would require all participants to prac-
tice all five top identified conservation practices. At 77%
participation, there would need to be approximately 9446
ha implemented with the most feasible conservation al-
ternatives (no-till, low-pressure sprinkler package, drou-
ght tolerant crops, water use limits, and conversion to dry
beans). Based on the water balance model results, stop-
ping the decline of the High Plains aquifer would also
stop the decline of the alluvial aquifer (Figure 11). The
elimination of the High Plains aquifer decline will allow
a constant groundwater flux out of the High Plains aqui-
fer into the alluvial aquifer. This constant flux into the
alluvial aquifer will potentially bring the system back
into equilibrium. This equilibrium rate will be at a signi-
ficantly lower level than the pre-development equilibri-
um prior to irrigation pumping. 77% participation would
be difficult to achieve without mandatory implementation
levati on i n the all uviu m, h
, (m)
lluvium Water Table
1965 1975 1985 1995 2005 2015 2025 2035 2045 2055
Water Tabl e E
Time (year)
lluvium Model
lluvium Well #10741Future Model Poo l Botto m
Figure 10. Alluvium aquifer water balance model with re-
moval of alluvial wells and projected into future to 2050.
Copyright © 2013 SciRes. JWARP
1965 1975 1985 1995 2005 2015 2025
Water Table Elevatio n in the all uvium , h
, (m)
Alluvium Water Table
Time (ye a r)
Alluvium Model (1968-2009)Alluvium Well #10741
Future Model Pool Bottom
Figure 11. Alluvium aquifer water balance model with 77%
future local farmer participation and projected into future
to 2050.
throughout the basin. The water balance model demon-
strated that pumping would need to be reduced by at least
44.8 million cubic meters or 62.9% to maintain the cur-
rent High Plains aquifer water levels and alluvial aquifer.
This scenario examined what level of future farmer
participation would be required to delay the habitat pool
drying from the estimated current drying time of 10 years
to 20, 30, and 40 years (Figure 12). The required con-
servation participation to extend the pools another 20
years will require future participation of approximately
43%. Water conservation over the extended time of 30
tion at approximately 62% participation.
shows the potential water conservation savings for each
uifer and the alluvial aquifer affect
the river on different time scales. The withdrawals from
years would need 57% participation. The next extended
time period would be 40 years with compulsory water
conserva Table
conservation alternative based on the different level of
farmer participation. The water savings impacts for ex-
tending the habit pool drying by 20, 30, and 40 years are
shown in Table 2.
4. Conclusions
The relationship between the High Plains aquifer and the
alluvial aquifer is important when looking at long term
drying trends in the Arikaree River. The High Plains aq-
uifer is primarily recharged in the dune sands. Ground-
water flux that occurs from the High Plains aquifer to the
alluvium significantly affects the water balance and the
consequent water table elevation in the alluvium. The
groundwater flux between the High Plains aquifer and
alluvium aquifer was studied by combining the water
balance data and Darcy’s Law for groundwater flow.
Groundwater modeling examined flows at specific loca-
tions within the basin.
The High Plains aq
1965 19751985 1995 2005 2015 20252035 2045205
Water Table Elevation in the alluvi um, h
, (m)
Time (year)
lluvi um Wate r Tab le
Alluvium Model (1968-2009)Alluvium Well # 10741Future Model Pool Bottom
1965 19751985 1995 20052015 20252035 2045 2055
Water Table Elevation in the alluvium,
Time (ye ar)
, (m)
lluvium Water Table
Alluvium Model (1968-2009)Alluvium Well #10741Future Model Pool Bottom
1965 19751985 1995 20052015 2025 2035 20452055
Water Table Elevation in the alluvium, h
, (m)
Time (yea r)
Alluvium Water Table
Alluvium Model (1968-2009)Alluvium Well #10741Future Model Pool B ott om
Figure 12. Alluvium aquifer water balance model with 43%,
57%, and 62% future local farmer participation and pro-
jected into future to 2050.
the High Plains aquifer affect the river annually while
withdrawals from the alluvial aquifer due to irrigation
pumping and riparian use affect the river daily through-
out the growing season. The radius of influence of the
irrigation wells from the High Plains aquifer does not
intersect the river during one pumping season [8]. The
cone of depression of these wells fills in by a change in
storage in the High Plains aquifer. This change in storage
causes a relatively constant decline in the High Plains
aquifer water table elevation from year to year. As the
High Plains aquifer water table elevation declines, there
Copyright © 2013 SciRes. JWARP
Copyright © 2013 SciRes. JWARP
Table 1. Water savings of conservation alicipation.
77% Future Participation 62% Future P
ternatives with varying part
articipation57% Future Participation 43% Future Participation
Conservation Alternative Water Savings (m3/year) Water Savings (m3/year)Water Savings (m3/year) Water Savings (m3/year)
No-Tillage 3.72E+06 2.99E
Low Pressure Sprinkler
Package 5.46E+06 4.40E
Drought Tolerant Crops 6.35E+06 5.11E
Water Use Limits 2.07E+07 1.67E
Converting to Dry Beans 1.05E+07 8.42E
Total 4.67E+07 76E
+06 2.75E+06 2.08E+06
+06 4.05E+06 3.05E+06
+06 4.70E+06 3.54E+06
+07 1.53E+07 1.16E+07
+06 7.74E+06 5.84E+06
07 3.46E+07 2.61E+07 3.+
Table 2. Water savings and economic impacts of varying participation.
Conservation Action ear Water Saved Over Research Area (m3/year)
Water Conservation Arikaree River Habitat
Participation (%) Pool Drying (ys)
No Action 0% 2020 0E + 00
Removal of 18 Alluvial Wells 2040 6.68E + 06
Farmer 43% 2030 2.61E + 07
Participation by Local Farmer 57% 2040 3.46E + 07
mer 62% 2050 3.76E + 07
mer 77% 4.67E + 07
Participation by Local
Participation by Local Far
Participation by Local Far
is less groter flux from theins aquifer to
e alluvial aquifer. This reduction in groundwater flux
deficit water ba
duces the alluvial water table elevation and river stage at
the beginn in compa-
tions at the beginning of the previous seas
The Arikarone of the last strlds for
Colo Minnow (Hbognathus
hanki oundwaterdue to
irrigatio shown to hgative
effec aquatic eco in the
Arikaabitat areas athe Ari-
karee River are a critical component of stream-riparian
ecosy s [1]. Overeclining
lluvial groundwater levels will have far-reaching, nega-
River will
uma County ur of the Arikaree River. We
also would like to thank the Central Yuma County Ground-
conservation survey. Funding of this research was pro-
o A
[1] , J. H. Braatne and
y of Riparian Cottoneam Flow De-
ncy, Water Relations and,” Tree Physi-
, Vol. 23, No. 16, 2003, pp.
undwa High Pla in Y
causes a lance in the alluvium that re- water Management District for participation in the
ning of each seasoavrison to the ele
ee River is ongho
rado’s threatened Brassyy
nsoni). Declining alluvial gr
n pumping have been
ave ne
ts that extend beyond thesystem
ree River. The riparian hlong
stems in the Great Plainall, d
tive effects across both terrestrial and aquatic ecosystems
in the Arikaree River basin. The evidence presented here
indicates that unless there is immediate action taken to
counteract the decline in the High Plains aquifer, irriga-
tion operations within the High Plains aquifer will even-
tually terminate and flows in the Arikaree
5. Acknowledgements
We thank William Burnidge, a Northeast Colorado Pro-
ject Director for The Nature Conservancy for the use and
assistance of the Fox Ranch. Gregg Stults a local farmer
for his to
vided by Coloradgricultural Experiment Station.
S. B. Rood
F. M. R. Hughes, “Eco-
woods: Str
ology Restoration
. 1113-1124
doi:10 3
[2] W. G. Weist, “Geology and Grr Resources of
Yuma County, Colorado, USGS Water-Supply Paper 15-
39-J,” United States Government Printing Office, Wash-
ington DC, 1964, pp. 1-52.
[3] E. Wachob, “Irrigation Pumping, Riparian Evapotranspi-
ration, and the Arikaree River, Yuma County, Colorado,”
MS Thesis, Colorado State University, Fort Collins, 2006.
[4] J. A. Scheurer, K. D. Fausch and K. R. Bestgen, “Multi-
scale Processes Regulate Brassy Minnow Persistence in a
Great Plains River,” Transactions of the American Fish-
eries Society, Vol. 132, No. 5, 2003, pp. 840-855.
[5] US Geological Survey, “High Plains Regional Ground
Water Study,” 2008.
hite, “Groundwater Exploita-
[6] D. E. Kromm and S. E. W
tion in the High Plains,” University Press of Kansas,
[7] K. D. Fausch and K. R. Bestgen, “Global Biodiversity in
a Changing Environment: Ecology of Fishes Indigenous
to the Central and Southwestern Great Plains,” Springer-
Verlag, New York, 1997.
[8] A. Squires, “Groundwater Response Functions and Water
Balances for Parameter Estimation and Stream Habitat
Modeling,” MS Thesis, Colorado State University, Fort
Collins, 2007.
[9] M. P. Schaubls in the Northern
GS Water Data for th
e Organization, “Conservation in
Your Success in No-Till. In
n Sprinkler Irrigation Management,” Cen-
s, “Ground Water Leve
High Plains Designed Ground Water Basins 2007,” Colo-
rado Division of Water Resources, Denver, 2007.
[10] G. VanSlyke and J. Stevens, “Depletion to the Ogallala
Aquifer, Northern High Plains Designated Ground Water
Basin,” State Engineers Office, Colorado, 1990
[11] Colorado Division of Water Resources, “Ground Water
Levels, Northern High Plains Designated Ground Water
Basin,” State Engineers Office, Denver, 2002.
[12] US Geological Survey. “USe Na-
tion,” 2010.
[13] T. Davis and S. Richrath, “Republican River Conserva-
tion Reserve Enhancement Program,” Colorado Division
of Wildlife and Colorado Division of Water Resources,
State of Colorado, 2005.
[14] Food and Agricultur
Arid and Semi-Arid Zones,” Conservation Guide 3, Rome,
[15] N. L. Klocke, R. S. Currie and T. J. Dumler, “Water Sav-
ing from Crop Residue Management,” Proceedings of
Central Plains Irrigation Short Course and Exposition,
Greeley, 19-20 February 2008, pp. 71-79.
[16] D. C. Nielsen, “Crop Residue and Soil Water” Central
Plains Irrigation Conference & Exposition Proceedings,
Sterling, 16-17 February 2005, pp. 80-83.
[17] R. N. Klein, “Improving
Cover Your Acres Proceedings,” Kansas State Research
and Extension, Oberlin, 22-23 January 2008, pp. 22-26.
[18] N. L. Klocke, R. S. Currie and T. J. Dumler, “Effect of
Crop Residue o
tral Plains Irrigation Conference & Exposition Proceed-
ings, Colby, 21-22 February 2006, pp. 115-121.
[19] R. Oad, L. Garcia, K. Kinzli, D. Patterson and N. Shafike,
“Decision Support Systems for Efficient Irrigation in the
Middle Rio Grande Valley,” Journal of Irrigation and
Drainage Engineering, Vol. 135, No. 2, 2009, pp. 177-
185. doi:10.1061/(ASCE)0733-9437(2009)135:2(
on and Drainage
[20] R. Oad, and K. Kinzli, “SCADA Employed in Middle Rio
Grande Valley to Help deliver Water Efficiently,” Colo-
rado Water-Newsletter of the Water Center of
State University, Fort Collins, 2006.
[21] R. Oad and R. Kullman, “Managing Irrigated Agriculture
for Better River Ecosystems: A Case Study of the Middle
Rio Grande,” Journal of IrrigatiEngi-
neering, Vol. 132, No. 6, 2006, pp. 579-586.
[22] R. Barta, I. Broner, J. Schneekloth and R. Waskom, “Co-
lorado High Plains Irrigation Practices Guide: Water Sa-
Transactions of the
1959 to
. 1365-
ving Options for Irrigators in Eastern Colorado,” Colo-
rado Water Resources Research Institute, Special Report
No. 14, Colorado State University, Fort Collins, 2004.
[23] United States Department of Agriculture, “2007 Census
of Agriculture: Yuma County Profile,” 2010.
[24] W. M. Frasier, R. M. Waskom, D. L. Hoag and T. A.
Bauder, “Irrigation Management in Colorado: Survey Da-
ta Findings” Water Center at Colorado State University,
Fort Collins, 1999.
[25] L. New, A. Knutson and G. Fipps, “Chemigation wit
LEPA Center Pivots,” American Society of Agricultural
Engineers Publication 04-90, 1990, pp. 453-458.
[26] K. Hill, E. Segarra, R. T. Ervin and W. Lyle, “Low En-
ergy Precision Application Irrigation for Cotton Produc-
tion in the Texas Southern High Plains,” Texas Journal of
Agriculture and Natural Resources, Vol. 4, 1990, pp. 39-
[27] A. D. Schneider, “Efficiency and Uniformity of the LEPA
and Spray Sprinkler Methods,” Transactions of t
American Society of Agricultural Engineers, Vol. 43, No.
4, 2000, pp. 937-944.
[28] F. R. Lamm and H. L. Manges, “Partitioning of Sprinkler
Irrigation Water by a Corn Canopy,”
American Society of Agricultural Engineers, Vol. 4, No. 4,
2000, pp. 909-918.
[29] M. Tollenaar, “Genetic Improvement in Grain Yield of
Commercial Hybrids Grown in Ontario from
1988,” Crop Science, Vol. 29, No. 6, 1989, pp
[30] M. Tollenaar and J. Wu, “Yield Improvement in Temper-
ate Maize in Attributable to Greater Stress Tolerance,”
Crop Science, Vol. 39, No. 6, 1999, pp. 1597-1604.
[31] P. M. O’Neill, J. F. Shanahan, J. S. Schepers a
Caldwell, “Agronomic Responses of Corn Hybrids from
Different Eras to Deficit and Adequate Levels of Water
and N
nd B. C.
itrogen,” Agronomy Journal, Vol. 96, No. 6, 2004,
pp. 1660-1667. doi:10.2134/agronj2004.1660
[32] K. Ledbetter, “AgriLife Research Breeder Develops
Drought-Tolerant Corn,” 2008.
urces in the Pumpkin Creek Watershed,” Central
[33] W. Xu and R. Lascano, “New Stress Tolerant Corn Germ-
plasm for Higher Water Use Efficiency and Water Con-
servation,” 2010.
[34] G. W. Hergert, G. Stone, D. Yonts and J. Schild, “Lim-
ited Irrigation Cropping Systems for Conserving Water
Plains Irrigation Conference & Exposition Proceedings,
Greeley, 19-20 February 2008, pp. 46-52.
[35] D. D. Adelman, “A Successful Water Conservation Pro-
Copyright © 2013 SciRes. JWARP
Copyright © 2013 SciRes. JWARP
Region of Nebraska,” Journal of gram in a Semiarid
American Water Resources Association, Vol. 39, No. 5,
2003, pp. 1079-1092.
[36] R. G. Borman, J. B. Linder, S. M. Bryn and J. Rutledge,
and Akron,
sources of
R66-67DLR9,” Agricultural Engi-
of Hydrology
“The Ogallala Aquifer in the Northern High Plains of
Colorado-Saturated Thickness in 1980; Saturated Thick-
ness Changes, Predevelopment to 1980; Hydraulic Con-
ductivity; Specific Yield; and Predevelopment and 1980
Probable Well Yields, Hydrologic Investigation A
HA-671,” U.S. Geological Survey, 1983.
[37] L. Riley, “Finding the Balance: A Case Study of Irriga-
tion, Riparian Evapotranspiration, and Hydrology of the
Arikaree River Basin,” M.S. Thesis, Colorado State
versity, Fort Collins, 2009.
[38] R. J. Hanks, H. R. Gardner and R. L. Florian, “Evapo-
transpiration-Climate Relations for Several Crops in the
Central Great Plains,” Soil and Water Conservation Re-
search Division, Agricultural Research Service, United
States Department of Agriculture, Fort Collins
[39] Willard Owens Consultants, “Ground Water Re
the San Arroyo Creek Basin, Volume I Hydr
Computer Modeling, Conclusions and Recommenda-
tions,” Prepared for Morgan County Quality Water Dis-
trict, 1988.
[40] D. L. Reddell, “Distribution of Groundwater Recharge
Technical Report AE
neering Department, Colorado State University, Fort Col-
lins, 1967, p. 132.
[41] M. Sophocleous, “Groundwater Recharge Estimation and
Regionalization: The Great Bend Prairie of Central Kan-
sas and its Recharge Statistics,” Journal ,
Vol. 137, No. 1-4, 1992, pp. 113-140.
[42] L. Fardal, “Effects of Groundwater Pumping for Irriga-
tion on Stream Properties of the Arikaree River on the
rado State University, Fort Collins, 2004.
Colorado Plains,” M.S. Thesis, Colorado State University,
Fort Collins, 2003.
[43] S. Griffin, “Effect of Irrigation Practices on Stream De-
pletion in the Arikaree River, Eastern Colorado,” M.S.
Thesis, Colo
[44] D. B. McWhorter and D. K. Sunada, “Ground-Water Hy-
drology and Hydraulics,” Water Resources Publications,
Highlands Ranch, Colorado, 1977.
[45] R. H. McCuen, Z. Knight and A. G. Cutter, “Evaluation
of the Nash-Sutcliffe Efficiency Index,” Journal of Hy-
drologic Engineering, Vol. 11, No. 6, 2006, pp. 596-602.
[46] C. W. Downer and F. L. Ogden, “GSSHA: Model to Si-
mulate Diverse Stream Flow Producing Processes,” Jour-
nal Hydrologic Engineering, Vol. 9, No. 3, 2004, pp.
161-174. doi:10.1061/(ASCE)1084-0699(2004)9:3(161)
[47] S. Birikundavyi, R. Labib, H. T. Trung and J. Rousselle,
“Performance of Neural Networks in Daily Streamflow
Forecasting,” Journal Hydrologic Engineering, Vol. 7,
No. 5, 2002, pp. 392-398.
[48] Colorado Agricultural Meteorological Network, “About
CoAgMet,” 2010.
[49] J. A. Falke, “Effects of Groundwater Withdrawal and
Drought on Native Fishes and Their Habitats in the Ari-
karee River, Colorado,” Ph.D. Thesis, Colorado State
University, Fort Collins, 2009.
[50] J. A. Scheurer, K. R. Bestgen and K. D. Fausch, “Resol-
ving Taxonomy and Historic Distribution for Conserva-
tion of Rare Great Plains Fishes: Hybognathus (Teleostei:
Cyprinidae) in Eastern Colorado Basins,” Copeia, Vol. 1,
2003, pp. 1-12.