The impact of water policy on conserving the Ogallala Aquifer in Groundwater Management District 3 (GMD3) in southwestern Kansas is analyzed using a system-level theoretical approach integrating agricultural water and land use patterns, changing climate, economic trends, and population dynamics. In so doing, we (1) model the current hyper-extractive coupled natural–human (CNH) system, (2) forecast outcomes of policy scenarios transitioning the current groundwater-based economic system toward more sustainable paths for the social, economic, and natural components of the integrated system, and (3) develop public policy options for enhanced conservation while minimizing the economic costs for the region's communities. The findings corroborate previous studies showing that conservation often leads initially to an expansion of irrigation activities. However, we also find that the expanded presence of irrigated acreage reduces the impact of an increasingly drier climate on the region's economy and creates greater long-term stability in the farming sector along with increased employment and population in the region. On the negative side, conservation lowers the net present value of farmers' current investments and there is not a policy scenario that achieves a truly sustainable solution as defined by Peter H. Gleick. This study reinforces the salience of interdisciplinary linked CNH models to provide policy prescriptions to untangle and address significant environmental policy issues.
Our world faces a public policy conundrum. Crop yields on many varieties have
tripled over the past 50 years, with irrigated cropping practices accounting
for 40 % of the total increased level of production
The groundwater, population, and cash flow summary statistics for the 12 counties of Groundwater Management District 3. Created by Weston Koehn.
This is the case for the High Plains Aquifer in the US, also
referred to as the “Ogallala Aquifer” (see Fig.
Thus far, the scientific community has developed hydrological models that
confirm what we already know; that this natural system aquifer is already
past its peak groundwater depletion
The scope of this study is the 12 counties of Groundwater Management District no. 3
(GMD3) in southwestern Kansas (Fig.
Our framework for studying GMD3 is a coupled natural–human system approach.
CNH studies (1) take advantage of both social and natural system variables,
(2) are multidisciplinary in theoretical approach, (3) integrate research
methods across disciplines, and (4) are “context specific” while
understanding temporal dynamics
CNH model components and data flow diagram.
The integrated model is composed of independent disciplinary models that each
conform to and are linked within the Open Modeling Interface (OpenMI)
Standard
The socioeconomic impact model uses cash flow at time
To estimate the population impact of this employment, we conducted a cross
sectional time series analysis with panel-corrected standard errors (TSCS)
The crop choice component is an iterative positive mathematical programming (PMP)
model An annual horizon reflects the fact that farmers
competitively extract water from a common pool, leaving no individual
incentive to conserve stocks that can be withdrawn by other users in
future periods
A separate instance of the model was calibrated to data from each county in
the study region. Each county model simulated acreages for irrigated and
nonirrigated plantings of the five dominant in crops in the region: wheat,
corn, sorghum, soybeans, and alfalfa. Nonirrigated production of soybean and
alfalfa is unfeasible given regional hydroclimatology and so are only
included as irrigated crops. Thus, eight crop categories were modeled. The
models were calibrated to the 2006–2008 average of observed acreages, yields,
and prices for the eight crops by county, the most recent period for which
comprehensive county-level data are available from the National Agricultural
Statistics Service (NASS). Expected crop yields are simulated within the
model from water response functions in As noted above, the crop choice model is not
calibrated to a specific year, but rather to the mean outcome during the base
period. Calibrating to a specific year would “overfit” the model so that it
replicates that single year, but does a poor job with the years before or
after that one year. The mean approach does not give an exact fit for any
single year but makes the model match better with the data cloud.
There is a long history of increasing crop yields due to genetic improvements
in plant varieties
The crop production component projects grain yield and irrigated water by
using the erosion–productivity impact calculator (EPIC) model
We previously calibrated the model for use in western Kansas
Each simulated year's weather is determined by a random draw from
meteorological records between 1985 and 2012. We build the likelihood of
climate change into our simulation about the future of GMD3. ECHAM5 climate
change models for the High Plains region suggest future regional warming and
a gradual increase in extreme weather events, pointing toward a less suitable
climate and thus reduced yields for agricultural production
We compared the statistics of the original 27 years
of weather data the our 100-year simulation where the drier years gradually
became 25 % more likely. The average maximum temperature increased from
20.09 to 20.14
The groundwater modeling component provides estimates of groundwater storage
and the changes in storage due to pumping and natural hydrologic processes.
This model is linked to the crop production and economic crop choice model
using OpenMI
Specific steps used to prepare groundwater data follow. Storage is obtained
from groundwater observation wells, kriging across wells to give a surface of
saturated thickness, multiplying by specific yield to give water content, and
integrating across the aquifer area within a county It is important to note that the recharge
component is kept consistent throughout this study. Given the relatively
thick soil units throughout much of the region In the simulation, groundwater pumping is based upon an
annual decision for when to start pumping and when to stop, where the well is
traditionally left on throughout the growing season. Thus the dynamics are
drawdown throughout a growing season and recovery before the next pumping
cycle, where large drawdowns may occur when the wells actively pump
The baseline model predictions accurately reproduced the groundwater data
throughout the historical period. Model results were also compared to the
future predictions of a higher-resolution fishnet model of Seward County
This integrated model is used to develop point estimates for important
variables, as well as estimates of uncertainty, by simulating a policy scenario
100 times, where each policy scenario simulates a period of 100 years and
the parameter that was resampled each simulation was the weather year.
Figure
Baseline outcomes of current irrigation practices in GMD3:
100 simulations. Top row panels: the left graph shows the acreage planted for
dryland and irrigated crop varieties. Note the demise of irrigated corn and
the rise of dryland corn over the course of the simulation.
The right
graph depicts total water consumed in GMD3 by each irrigated crop. Middle row
panels: the left graph shows the average level of saturated thickness of the
Ogallala in each of the 12 counties over time. Note that only two of the
12 counties end the simulation with an average saturated thickness greater
than 15 m, 6 have averages less than 9 m. Generally, more than 9 m of
saturated thickness is needed to irrigate using center pivots. The right
graph sums the NPV across all 12 counties over time. Bottom row panels: the
left graph illustrates the predicted number of additional jobs created in a
simulated year due to the direct, indirect, and induced impacts of irrigation
and dryland crop production, respectively. Note that over time, the level of
variation in employment due to dryland crop production is exceptionally
large, reflecting the greater levels of uncertainty introduced by a gradually
warmer climate. The graph on the right depicts the number of additional
people who live in the GMD3 in that year because of irrigated and dryland
crop production. The population impact mirrors the level of variation shown
in the previous graph. The whiskers denoting the level of uncertainty
(2
Our holistic CNH model predicts an unsustainable outcome for the aquifer in
all counties if current conditions remain unabated, which is consistent with
similar results obtained using different methodological approaches
Even though
the average saturated thickness for most counties is low, there is much
variation among wells in each county. Thus, some wells may have more than 9 m
of saturated thickness, allowing these farmers enough water to irrigate
However, hidden behind these point estimates is much uncertainty that comes
from relying on dryland farming in the semiarid counties of GMD3. This is
the most apparent by examining the outputs of the socioeconomic model.
Although the CF
We have two points of caution regarding these findings. First, the accuracy
of any model of this nature declines as it forecasts into the future.
Thus, some of this uncertainty in dryland crop production is a function of
our modeling methodology. Second, farmers in the GMD3 and US mitigate the risk
from drought and other weather-related calamities with federally subsidized
crop insurance, administered by the Risk Management Agency of the USDA. In
the event of crop failure, insured farmers receive a settlement based
primarily on the price of the crop during harvest multiplied by the average
yield in that county over the past 10 years
Summary of major outcomes from each scenario (standard deviations in parentheses).
Our definition of sustainability parallels that of Peter H. Gleick, who
defines sustainability in terms of using water to allow “human society to
endure and flourish into the indefinite future without undermining the
integrity of the hydrological cycle or the ecological systems that depend on
it.” Even though some have suggested that it may be
possible to import water from the Missouri River basin in South Dakota, or
some other river, this solution is expensive and creates potentially
negative environmental consequence for the river from which the water is
drawn. None of the
scenarios are constrained to achieve a desired outcome.
The first two policy scenarios use two separate Kansas water conservation
statutes to model different policy approaches for achieving a 10 to 20 %
reduction in irrigation. The Kansas Groundwater Management District Act
contains provision K.S.A. 82a-1036, which allows the Chief Engineer to
designate an “Intensive Groundwater Use Control Area” (IGUCA) to implement
corrective control provisions reducing the permissible groundwater withdrawal
based upon relative dates of priority of such rights (this statute also
allows for a rotating schedule;
Table Scenarios 3–5 follow this same pattern.
Both scenarios improve the lifespan of the aquifer by 10 to 15 years, but
neither comes close to achieving aquifer sustainability given the very slow
rate of recharge in most of GMD3. Both approaches produce similar types of
outcomes for CF
Given that neither of first two policy options achieves sustainability, we
explore the relationship between water conservation and the associated
socioeconomic consequences for the farmers and communities in GMD3. To do so
we simulated the implementation of a LEMA across GMD3 that incrementally
increases the interval for irrigation by 3X (a 26 % reduction compared to
2014 usage), 4X (a 35 % reduction), and 6X (a 48 % reduction). We focus on
the LEMA policy approach because it is a theoretically more pleasing policy
prescription (see arguments above and Ostrom's work;
Tripling the irrigation interval for irrigated corn production gradually increases the acres in production from 300 000 ha in 2013 to a peak of 376 000 ha by 2071. Dryland corn, which in the baseline analysis becomes the most predominant crop after 2080, only surpasses irrigated corn in acres planted in 2110, at the end of the 3X simulation. Given the large variation in yields and revenues associated with dryland corn production, policies that reduce dependence on this high-risk crop are desirable. The 3X scenario tends to benefit the communities of GMD3, as the number of additional people employed due to the direct and indirect impacts of production agriculture increases from fewer than 1000 in 2013 to 1940 in 2112. Similarly, the number of people living in the region because of direct and indirect economic impacts from irrigation and dryland farming increases from 2000 in 2013 to 4200 in 2112.
Disappointingly, increasing the irrigation interval by 4X or 6X does not produce sustainable outcome for the aquifer. A total of 6 of the 12 counties under the 4X scenario and 2 of 12 counties under the 6X scenario still end the simulation with average saturation depths of 15 m or less. There is also an economic cost to irrigators to achieve this level of water savings. The NPV in 2060 shrinks to USD 9.5 billion for 4X scenario and USD 7.6 billion for the 6X scenario. On the positive side, after an initial decline in employment and population early in the simulation, both rebound to levels just above the baseline.
These results corroborate previous studies that show that conservation often
leads initially to an expansion of irrigation activities, as farmers use
their water application savings on more fields to increase their capital
returns
The two policy mechanisms discussed in this study, (1) senior versus junior water rights and (2) LEMA, represent policy tools that have thus far only been used in Kansas after the impacts of groundwater depletion have manifested. Thus, they are policy tools for managing a crisis. This begs the question whether one of these conservation enforcement tools or some other policy prescription can be brought to bear to conserve the aquifer before a crisis occurs?
Our scenarios demonstrate that any form of conservation enacted today lowers the income of agricultural production in the short and long term. The differential between what the income producers would have earned under the baseline model versus what they are likely to earn if conservation measures were enacted represents an opportunity cost. This opportunity cost is the major obstacle preventing the adoption of any conservation measures.
Policy analysts working for GMD3 in the early 2000s noted this opportunity
cost associated with conservation and promoted a crop subsidy to address this
differential If
such subsidies for irrigated crops were provided, policies may be needed to
require water savings to be left in the ground in exchange for the crop
subsidy. Without such restrictions, research clearly shows that water savings
have been used to expand their irrigation operations and maximize profits
Subsidies or other policy interventions need to define an outcome considered desirable to address the current situation. In our case, there are two major goals that potential policies could work towards. The first is implementing procedures to extend the current agricultural production regime as long as possible. In this case, addressing the opportunity costs requires an investment (the subsidies) with the expectation that the extended lifetime of the aquifer provides social and economic goods substantial enough to justify the investment before the inevitable pumping reductions imposed by low rates of groundwater recharge. This would provide opportunities for local communities to accumulate resources before that happens, relying on the market to determine how much can be accumulated. The second option is using policy tools to navigate the regional economy toward a different agricultural regime, such as a specific dryland agricultural system. In this case, the desired outcome would be facilitated by policies more directed toward that outcome, assuming that the region itself would be better off under those conditions. These choices reflect the age-old debate in policy making about helping communities accumulate resources to invest in any way they see fit, hoping for a sustainable regional economy to emerge, or provide assistance to move stakeholders along a specific path determined at the regional level. Regardless of which direction policy makers choose, the desired outcome must be clearly defined, as rudderless boats seldom reach their destinations no matter how low the water levels drop.
Perhaps the most important research outcome is that this study establishes the salience of interdisciplinary linked CNH models that seek to untangle and address significant environmental policy issues. Other studies of intensive water-use regions have been insightful, but none have incorporated the breadth of our model's components or have used an OpenMI framework. Our modular and holistic model, which includes the major variables of socioeconomic impact, crop choice, crop production, and groundwater supply, points toward the policies that can be implemented today to bring a more sustainable future to this region.
Additional research is necessary to refine this CNH model to (1) model the dynamic nature of the grain commodities market, (2) take into account new efforts by agri-industry and universities to double grain production levels over the next 15 years, and (3) take advantage of improved scientific models of climate change to more accurately portray the uncertainties that irrigators face and the additional demands for water that climate change may induce in this water-challenged region. Researchers in the future can adapt this holistic model to take account of these factors to build new models of sustainability from the wells that pump the water from the aquifer to the communities where people are affected.
The simulated data for the models are available in
To estimate the population impact of this employment, we conducted
a cross sectional time series analysis with panel-corrected standard errors
(TSCS) controlling for autocorrelation (AR 1)
Table
IMPLAN multiplier for crops in western Kansas.
Table
Historic yields in crop varieties (irrigated and dryland).
Table
Comparison of observed and simulated water withdrawals, GMD3 Total, 2013–2016. SD denotes standard deviation.
Sources:
The authors declare that they have no conflict of interest.
This article is part of the special issue “Assessing impacts and adaptation to global change in water resource systems depending on natural storage from groundwater and/or snowpacks”. It is not associated with a conference.
This research is funded by a grant from the National Science Foundation (NSF-CNH-0909515), with additional funding from the Ogallala Aquifer Project of the US Department of Agriculture's Agricultural Research Service. Edited by: David Pulido-Velazquez Reviewed by: two anonymous referees