A Discussion of Groundwater Modeling and Climate Change

By Leslie Llado
GEO 377P – Yang

November 30, 2006

ABSTRACT
With continued urbanization and increased dependence on limited natural resources, it is important to understand climate change and the ways that it will affect the planet.  Extensive modeling has given scientists an idea of the relationship between the atmosphere and the land surface.  However, the majority of land surface models ignore a crucial component: groundwater.
Global climate change will inevitably affect the availability of water.  Although many parts of the world have long relied on groundwater sources, the depletion of above ground water sources makes an understanding of groundwater even more important.  This knowledge can be difficult to obtain because the extent of groundwater recharge and pathways by which recharge occur differ very greatly between groundwater systems and are affected by a number of natural and external factors.  Once a groundwater system is modeled, it can be difficult to determine a relationship between climate and groundwater systems.
The majority of studies linking groundwater and climate modeling are fairly recent.  This paper discusses three different models, each with a different method of quantifying the relationship between groundwater and climate.  In each case, the models show that land surface modeling that includes groundwater analysis is more accurate than models that ignore groundwater.

	

INTRODUCTION
Interest in climate change continues to grow, and numerous climate change studies have been performed.  A significant component of climate change is the overall warming trend that has progressed since the early twentieth century.  This warming trend not only increases temperature and the occurrence of severe weather phenomena; it also affects the availability of water.  Thus, with climate change, it is increasingly important to understand the relationship between climate and groundwater.  Scientists have done extensive work relating the atmosphere and land surface, but little work has been done to relate these models to groundwater systems.  
Water is a limited natural resource that is necessary to sustain life.  Groundwater is the primary source of water for more than 1.5 billion people worldwide and over fifty-percent of the United States population (Alley etal, 1985).  Due to increasing population and diminishing water supplies, researchers are placing more emphasis on groundwater analysis.  In order to manage resources, knowledge of groundwater recharge mechanisms is necessary.  It is important to understand the pathways through which water recharges due to location or conditions.  Groundwater systems change constantly in response to human activity and climatic stresses, making groundwater modeling difficult.
An understanding of the impact of climate change on groundwater is essential; the implications of climate change directly impact sustainability.  The definition of sustainability is imprecise; it differs according to the source and that source’s motive.  Most definitions assess the resources necessary to support present and future generations and focus on a “reasonable” standard of living. However, this reasonable standard is impossible to define since standards of livings can change based on culture, location, age, race, and other factors.   In 2002, the United Nations World Summit emphasized that sustainability must deal with the eradication of poverty, protection of natural resources, and alteration of consumption patterns (UN Department of Economic and Social Affairs, 2006).  With emphasis on the protection of natural resources, groundwater recharge must be assessed.  By understanding groundwater processes in different types of environments, water sustainability can be better determined.

MODELING COMPONENTS
Factors Affecting Groundwater Modeling
Groundwater systems can be difficult to quantify due the variety of factors affecting them.  The factors emphasized differ between studies due to the purpose of the study and available data.  An analysis of the factors affecting groundwater recharge can be split into two categories: the “natural” and “urban” groundwater recharge system components.  The natural system includes the basic components of the hydrologic cycle: precipitation, evaporation, transpiration, sublimation, runoff, infiltration, recharge, and baseflow (Sharp 2006).  Groundwater is the third largest source of water on earth and is therefore greatly impacted by the hydrologic cycle fluxes (Figure 1).  Furthermore, the natural system must account for the heterogeneity of geological structures, local vegetation, and weather conditions.  These components can be extremely tedious to measure and nearly impossible to model.  If measured, data are only available for a limited period of time and data availability varies between regions.  Of these, precipitation data is probably the easiest to access and has the greatest longevity.  The urban system takes the natural factors into account and also considers human impact on the hydrologic cycle.  The impact of urban factors is difficult to estimate and data can be difficult to quantify.  

Climate Change and Groundwater
Climate has only recently been incorporated into groundwater modeling and groundwater recharge studies.  The effect of climate on a groundwater system depends on the natural and urban groundwater components.   Intensity of climate change, seasonal variations, groundwater table depth, soil properties, vegetation, and a variety of other factors can affect the extent to which climate influences groundwater. 
For instance, Thailand’s Bangkok Basin is very susceptible to climate change.  The groundwater system that supplies the Bangkok Basin is very sluggish; with seasonal variations, the travel time through the system changes significantly (Alley etal, 2002).  Long term climatic effects must be considered when analyzing groundwater systems over long periods of time.  Climate change can affect geologic processes such as digenesis, ore mineralization, and petroleum accumulation (Alley etal, 2002).  Climate change also impacts regional hydrologic systems; it potentially alters runoff, soil moisture storage, lake levels, aquifer levels, streamflow, and water quality (York etal, 2002).  Changes in groundwater availability can affect municipal or agricultural water availability, water quality, pumping costs, and frequency of flooding or low water conditions (York etal, 2002).

Extreme Weather Phenomena
The amount of available groundwater also varies according to the quantity of water that passes through the natural hydrologic cycle.  Groundwater storage and discharge vary with drought or increased precipitation.  With drought, available water decreases, resulting in decreased streamflow.  Conversely, increased precipitation results in increased streamflow.  In general, dry years, in which precipitation is less than average precipitation, are more common than wet years, with precipitation higher than average.  Drought is especially of concern in the Southwest, where precipitation is less than 85% of the mean one third of the time (Thomas, 1964).  Recent data from the National Oceanic and Atmospheric Administration (NOAA) assesses current drought conditions in the southwestern United States.  NOAA reports that the United States is currently experiencing warmer than average temperatures, with the Southwest experiencing drought conditions ranging from abnormally dry to exceptionally dry on NOAA’s drought intensity scale (Figure 2).  
During drought conditions, surface water sources may dry up, increasing dependence on groundwater sources.  With climate change, extreme weather phenomena such as droughts are becoming more common, increasing dependence on groundwater sources. 

Incorporating Climate into Groundwater Modeling
Existing models that emphasize natural and urban groundwater components are used to hypothesize future conditions based on climate trend data.  Groundwater modeling is used to solve a variety of current problems and hypothesize future responses of groundwater systems to a variety of stresses.  Groundwater recharge estimation incorporates geophysics, tracers, water budgets, and simulation models.  However, the effects of climate and climate change are difficult to assess.  Little numerical information is available to describe past climates.  Some sources of information on past climates could include areas of low or high recharge or ancient groundwater, and while useful, this data can be difficult to quantify.  Studies of recharge rates during past climatic periods have been attempted in isolated arid regions, such as the western United States, where recharge rates dating 15000 years back were approximately twenty times current recharge rates (Alley etal, 2002). Typically, analysis of a groundwater system will involve a maximum of a couple of decades of data.  While climate variations over this time period can be studied, long term climate, relative to past climates, is difficult to determine.  For this reason, analysis of groundwater systems has typically ignored the effect of climate.  
General circulation models (GCMs) can simulate changes in climate by changing certain boundary conditions or parameters, such as solar constant or gas concentrations (Figure 3).  GCMs that account for land surface models (LSMs) produce more accurate climate simulations.  While these models can attempt to simulate soil moisture conditions, humidity, and precipitation changes, they cannot assess the relationship between changing soil, vegetation, and topography; ultimately, GCMs do not provide a coherent simulation of groundwater conditions (York etal, 2002).  By incorporating an aquifer system into the model, the interaction between global climate systems can be interpreted based on specific watershed parameters.  When analyzing groundwater and climate change, it is important to note that an aquifer might take years to decades to respond to climate change, while the atmosphere has a much quicker response time.
New research incorporates groundwater data into existing LSMs to more accurately simulate climate conditions.  An LSM considers the surface heat balance equation, a surface moisture equation, and a variable to represent snow cover (Hartmann 264).  Although LSM accounts for land topography, it usually does not consider groundwater conditions.  In locations where groundwater is close to the land surface, soil moisture is higher, resulting in a cooler land surface.  Since groundwater-surface interactions can significantly alter LSM results, it is necessary to consider the effects of groundwater.

DISCUSSION OF CLIMATE-GROUNDWATER MODELING STUDIES

	A number of recent studies have incorporated the effects of climate change into groundwater modeling.  This following is an overview and discussion of three such studies and the different methods used to quantify the impact of groundwater on climate models.

CLASP II Simulation
York, etal developed a coupled land-atmosphere simulation (CLASP II) to analyze the decadal timescale impact of global climate change on groundwater.  CLASP II incorporates 3-D physical groundwater data into a LSM-atmosphere system.  ATMOS, the atmospheric model, consists of a single data column, instead of using historic atmospheric data.  The model operates like a single GCM gridbox and utilizes the basic equations of conservation of momentum, thermodynamic energy, mass, and water vapor.  VOS-MOD, the vegetation-overland flow-soil model, represents soil vegetation zones with MODFLOW, a commonly used groundwater modeling program issued by the United States Geological Society.  Soil vegetation zones are laterally distributed in a finite-grid difference sequence.  The type of soil and vegetation is specified, and properties for the specific type are accounted for.  Soil vegetation zones interact with the atmosphere through sensible and latent heat momentum flux.  MODFLOW is also used for the groundwater model in the same 3-D finite-grid difference sequence used for the soil vegetation.  Aquifer properties are simulated by incorporating numerical aquifer characteristics and the equations for heterogeneous, anisotropic media.  An approximate streamflow is calculated based on streamflow averages.  The relationship between the ATMOS, VOS-MOD, and MODFLOW systems is shown below (Figure 4).

CLASP II was tested for the Mill Creek Watershed in Northeastern Kansas.  Using historic data from 1985-1993, an eight-year simulation was modeled for the catchment area.  Researchers chose this time period because it represented very wet and very dry periods, simulating extreme climate change.  The simulation was performed with and without an aquifer to gauge the model’s sensitivity to different groundwater conditions.  The results obtained from CLASP II correlated with the known groundwater trends for the time period.  In wet years, approximately five-percent of evapotranspitation was drawn from the aquifer, while in dry years, 20% was drawn from the aquifer.  The model showed that the aquifer’s response to climate change was slight; it could take hundreds of years for groundwater levels to decrease.  

Three-layer Variable Infiltration Capacity Model (VIC-3L):

	The VIC-3L, improved upon by Liang and Xie, is a hydrological LSM that simulates the effect of different types of vegetation on water and energy budgets.  Improvements to the existing VIC model include analysis of excess infiltration runoff by including subgrid soil heterogeneity and accounting for surface-groundwater interactions and resulting effects on soil moisture.  Additionally, the model considers surface-groundwater interactions and the resulting effect on moisture, recharge rate, and evapotranspiration.  This is achieved by accounting for one vegetation layer with bare soil evapotranspiration, an upper soil layer where soil moisture is derived from rainfall, and a lower soil layer that accounts for seasonal soil moisture.  Fast and slow runoff is also considered, with fast runoff at the surface and slow runoff at the subsurface.  
	Two experiments were performed to test the sensitivity of the VIC-3L model and correctly simulate total runoff and groundwater table position.  The first experiment tested infiltration formulas between two configurations of the VIC model, called Philip (VIC-Philip1) and Horton (Horton).  The second experiment ran the same data using only the Philip infiltration formula.  Results from an old version of VIC (VIC-Old1) that did not consider infiltration excess runoffs are also included (Figure 5).  Infiltration, surface runoff, evapotranspiration, and subsurface runoff were computed.  A mass-lumped finite element was used to update soil moisture at each layer at each point in time, with two to three iterations of the formula necessary to achieve realistic data.
	Liang and Xie’s version of VIC-3L successfully simulated the groundwater table position and total runoff.  Ultimately, the difference in total runoff and soil moisture was much smaller for the first experiment, which used the Philip and Horton configurations.  Comparison of the VIC-Philip1 and VIC-Old1 curves show that the new version of VIC-3L more correctly represents precipitation for the area.  Results emphasize the importance of incorporating infiltration and saturation into simulation.  The model correctly represented water budgeting among the soil layers, evapotranspiration, and recharge rate.  It also showed that if surface-groundwater interactions are considered, evapotranspiration will be higher.

Soil Hydrological Model
          Chen and Hu created a soil hydrological model that considers the effect of groundwater as a soil water source.  The model considered the water exchange between the unsaturated zone and groundwater using a soil-surface model where soil water is the result of groundwater and precipitation.  A surface vegetation layer overlies four soil layers, ranging from shallow to deep at 0.1, 0.15, 0.25, and 0.5 meters from the surface (Figure 6).  Diffusive fluxes exist between each of the five layers.

              Saturation hydraulic conductivity varies in a vertical distribution, accounting for the decrease in soil permeability with increasing depth.  Richard’s equation is used to calculate soil moisture and is integrated and further manipulated to consider the four soil layers (Equation 1).  In the equation, θ is the soil moisture content (m^3 m^-3), t equals time, z is the vertical coordinate, F(t, θ) represents sources and sinks, K equals unsaturated hydraulic conductivity, and D = soil water diffusivity.  Both K and D are functions of θ.  Water flow for the root zone is vertical, and is thus represented in one dimension.  A non-zero hydraulic diffusivity is used represent the effect of groundwater on shallow soil and the root zone.

            This method is then added to a revised version of Penn State’s NCAR MM5 soil hydrological model to show the groundwater effect on soil moisture and surface evaporation.  A simulation was run for a station in the Nebraska Sand Hills, where groundwater is a major contributor to the soil moisture due to the Ogallala aquifer.  Using measured data for hourly average temperature, relative humidity, wind speed and direction, global solar radiation, and hourly precipitation, soil moisture variations were assessed for three periods from 1998-2000.  
             Upon comparison, the hydrologic soil model produced an average evaporation that was almost double the evaporation for a model of the same area without groundwater.  Additionally, in the first meter from the surface, soil moisture content in the model that included groundwater was twenty-one percent higher than soil moisture content in the model without groundwater.  All tests confirmed the idea that with a lower groundwater table, the influence of groundwater on soil moisture decreases.  Therefore, in an area with a lower groundwater table, climate change will have a less impact on groundwater supply.  The soil hydrological model successfully represents the effect of groundwater on soil moisture and Chen and Hu recommend that it be implemented for LSM.  

CONCLUSION
Analysis of the impact of climate change on groundwater is difficult and imprecise.  While a model might accurately reflect the climate-groundwater relationship for one area, it could be entirely ineffective in another location.  Overall, the three studies discussed showed that groundwater systems were relatively unaffected by climate change over short periods of time, such as ten to twenty years.  It would be useful to apply the same models to a longer period of time, perhaps a hundred or two hundred years.  However, based on the longevity of most data sets, this may not be possible for some time.  
Although it can be difficult to assess climate change, the effect of aquifer geometry and properties obviously influence the storage of water.  Extreme weather phenomena, such as floods or drought, clearly affect the groundwater levels.  Comparison of LSMS run with and without aquifers or groundwater parameters shows that LSMs that include groundwater better simulate actual land surface conditions.  Ultimately, analysis of the impact of climate change on groundwater depends on location and types of model boundary conditions, the model scale, and calibration.  Further research should allow for analysis of groundwater-climate interactions on a larger scale and may give a more accurate idea of the changes in groundwater levels.

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