Browsing by Author "Denning, A. Scott, advisor"
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Item Open Access A social-ecological approach to managing agricultural ammonia emissions and nitrogen deposition in Rocky Mountain National Park(Colorado State University. Libraries, 2017) PiƱa, Aaron Joshua, author; Denning, A. Scott, advisor; Ojima, Dennis S., advisor; Schumacher, Russ S., committee member; Baron, Jill S., committee member; Ham, Jay M., committee memberAtmospheric nitrogen (N) deposition is harmful to nutrient-limited mountain ecosystems. Annual wet deposition of total inorganic N in Rocky Mountain National Park (RMNP) is dominated by ammonium, which primarily comes from agricultural sources. The most wet N deposition events between 1980 and 2015 occurred during summer months. The confluence of summertime mountain meteorology and the location of pollution sources are a perfect combination that leads to high values of wet N deposition in RMNP. In Chapter 2, we tested the importance of convection as a N transport mechanism in addition to large-scale east winds, typically associated with the summertime mountain-valley circulation on the eastern plains of Colorado. We characterized the meteorological transport by using the Weather Research and Forecasting model at 4/3-km horizontal resolution. We used passive tracers as a simplified representation of emissions from a single agricultural source in eastern Colorado during three summer precipitation events where wet N deposition values in RMNP were among the highest recorded in all summers between 1980 and 2015. In all three cases, anticyclones in north-central United States and monsoonal flow associated with the North American Monsoon brought together the necessary conditions for deep convection over RMNP. Output from our simulations suggested large-scale winds were responsible for slow and steady transport whereas convection was a rapid and intermittent form of transport. This chapter showed two scales of transport had an additive effect that led to high deposition of N in RMNP during the afternoon/evening hours of three case studies. Chapter 3 discusses the development of a pilot early warning system (PEWS) for agricultural operators to voluntarily and temporarily minimize emissions of NH3 during periods of upslope winds. The PEWS was created using trajectory analyses driven by outputs from an ensemble of numerical weather forecasts together with the climatological expertise of human forecasters. In this study, we discuss the methods for the PEWS and offer a preliminary analyses of 21 months of the PEWS based on deposition data from two sites in RMNP as wells as voluntary responses from agriculture managers and producers after warnings were issued. Results from this study showed that the PEWS accurately predicted 5 of 7 high N deposition weeks at the lower-elevation observation site, but only 3 of 8 high N deposition weeks at the higher-elevation observation site. With the higher-elevation site receiving pollution from sources both west and east of the Continental Divide, sources west of the Continental Divide would need to be included in the PEWS to capture all of the sources leading to deposition at the higher-elevation site. Sixty agricultural producers and managers from 39 of Colorado's agricultural operations volunteered for the PEWS, and a two-way line of communication between the producers and the scientists was formed. An average of 21 voluntary responses (s.d. 4.9) per warning occurred, with over 75% of the PEWS participants altering their practices after an alert. Solving a broad and complex social-ecological problem requires both a technological approach, such as the PEWS, and collaboration and trust from all participants, including agricultural producers, university researchers, and environmental agencies. Chapter 4 applies a systems approach that explores the actors involved in a complex social-ecological problem that deals with the competing interests of an unadulterated environment and the contribution towards feeding the global population. Agricultural operations in northeastern Colorado are among the densest in the world. The demand of a growing global population has put pressure on the agricultural community to provide large quantities of food in a short amount of time. The cost for higher yields means more water, nutrients, and energy, and the result is environmental degradation in the forms of atmospheric and water pollution. The problem becomes more complex when we mix bottom-up and top-down management approaches. That is, agricultural producers are asked to work together with state and federal agencies on reducing emissions from their operations. A pilot early warning system employed in Colorado since 2014 helped bring together the actors to work towards the common goal of reducing nitrogen deposition in Rocky Mountain National Park. Our goal in this chapter was to organize the problem using a conceptual, social-ecological framework. The case studies and pilot early warning system from Chapters 1 and 2 document starting points for how institutional decisions can incorporate agricultural stakeholders in a mix of bottom-up and top-down management approaches under current and future climatic conditions.Item Open Access Applying two binned methods to the simple biosphere model (SiB) for improving the representation of spatially varying precipitation and soil wetness(Colorado State University. Libraries, 2011) Medina, Isaac D., author; Denning, A. Scott, advisor; Randall, David A., committee member; Ramirez, Jorge A., committee memberRepresenting subgrid-scale variability is a continuing challenge for modelers, but is crucial for accurately calculating the exchanges of energy, moisture, and momentum between the land surface and atmospheric boundary layer. Soil wetness is highly spatially variable and difficult to resolve at grid length scales (~100 km) used in General Circulation Models (GCMs). Currently, GCMs use an area average precipitation rate that results in a single soil wetness value for the entire grid area, and due to the nonlinear relationship between soil wetness and evapotranspiration, significant inaccuracies arise in the calculation of the grid area latent heat flux. Using a finer GCM resolution will not solve this problem completely and other methods of modeling need to be considered. For this study, the binned and alternative binned method of Sellers et al. (2007) are applied to the Simple Biosphere Model (SiB) for improving the representation of spatially varying precipitation, soil wetness and surface-atmosphere fluxes. The methods are tested in a dry, semi-arid, and wet biome for two off-line precipitation distribution experiments, and results are compared to an explicit method, which is ideal for resolving subgrid-scale variability, and the bulk method (area averaged), which is currently in use with GCMs. Results indicate that the alternative binned method better captures the spatial variability in soil wetness and grid area flux calculations produced by the explicit method, and deals realistically with spatially varying precipitation at little additional computational cost to the bulk method.Item Open Access Biophysical behavior in tropical South America(Colorado State University. Libraries, 2011) Baker, Ian Timothy, author; Denning, A. Scott, advisor; Randall, David, committee member; Coughenour, Michael, committee member; Gao, Wei, committee member; Estep, Donald, committee memberTo view the abstract, please see the full text of the document.Item Open Access Impacts of drought on grassland productivity across the wet-dry gradient in the U.S. Great Plains in 2010-2012(Colorado State University. Libraries, 2016) Curry, Renee A., author; Denning, A. Scott, advisor; Smith, Melinda, committee member; Peek, Lori, committee memberSevere, prolonged droughts are predicted to occur more frequently due to global climate change. Since grasslands already grow in regions that are water limited, they are particularly vulnerable to changes in precipitation. Climate models are used to investigate how grasslands will respond to climate change; however, current land surface models have difficulty in simulating grasslands and their response to drought. The main objective of this research project was to investigate the dominant relationships between grassland productivity and precipitation and to see if this behavior could be predicted in a model. To do this, we focused on both climate (dry to wet gradient) and drought (climate anomalies) using a combination of data and the Simple Biosphere Model Version 4 (SiB4). In order to have a better understanding of the relationship between grassland productivity and precipitation on a regional scale, this research studies nine sites across the U.S. Great Plains over which there is a significant precipitation gradient. In addition to the climatic gradient in precipitation, we took advantage of a natural experiment from 2010 through 2012, during which a significant drought occurred in this region. Observed west-to-east gradients in grassland productivity were generally well-captured by the model: there was an increase in leaf area index (LAI) with increasing precipitation, with a nearly identical linear relationship in both the observations and the model. SiB4 overestimated the magnitude of the seasonal-mean LAI; however, this bias was constant across the precipitation gradient. The drought decreased grassland productivity: both the observations and the model showed reduced LAI and a shorter growing season due to drought, and an analysis of the standardized anomalies in LAI and precipitation demonstrated that both the observations and the model have a nearly identical linear response to drought (difference in slope < 10%). Although SiB4 has a bias in the magnitude of seasonal-mean LAI, it has the same precipitation responses as seen in the data, thus showing the ability to capture the behavior of grasslands both across a dry-wet gradient and for a specific drought event.Item Open Access Importance of boundary layer entrainment for surface fluxes over land(Colorado State University. Libraries, 2011) McGrath-Spangler, Erica L., author; Denning, A. Scott, advisor; Randall, David A., committee member; Heald, Colette, committee member; Zupanski, Dusanka, committee member; Hoeting, Jennifer A., committee memberAn idealized experiment examined the impacts of entrainment in a coupled ecosystem-atmosphere model by implementing an enhanced entrainment parameterization based on the assumption that the heat flux at the top of the PBL is negatively proportional to the heat flux at the surface. This experiment found that entrainment produced a warmer, drier, and deeper PBL and that the surface fluxes of heat and moisture were modified by the vegetative response to the altered atmospheric conditions. A realistic simulation for the summer of 1999 found that enhanced entrainment produced stronger early morning growth of the PBL and a deeper midday depth. This better captured the monthly mean diurnal cycle of PBL depth from observations by a radar sounding system in northern Wisconsin. Additionally, the complex land-atmosphere interactions produced a time-mean spatial CO2 gradient of 7 ppm over 1000 km. A sensitivity analysis performed for June 2007 to the strength of the PBL-top entrainment flux found subtle spatial variations in the time mean. The addition of entrainment from overshooting thermals weakened the Bermuda high circulation and weakened the spatial gradients between the warm, dry semiarid southwestern United States and cooler, moister locations in eastern North America. These subtle variations produced a 3.5 ppm CO2 change in the time mean across 280 km. One possible explanation for these more subtle results is that additional changes to the coupled model resulted in persistent cloud cover that produced relatively cold and dark conditions. In order to evaluate and improve model simulations, PBL depth has been estimated using the backscatter from the LIDAR onboard the Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observation (CALIPSO) satellite. Using an automated method, millions of estimates have been derived to which model results can be compared. This method evaluates the maximum vertical variance of the backscatter in order to identify backscatter features associated with the top of the PBL and helps to identify the vertical extent of turbulent mixing. This analysis sheds some light on the spatial heterogeneity of boundary layer processes. The derived depths are shallower over water than over land and show a local minimum along the Mississippi River valley. Deeper features are found over the desert Southwest and deeper than expected values are retrieved over the Boreal forests.Item Open Access Investigating causes of regional variations in atmospheric carbon dioxide concentrations(Colorado State University. Libraries, 2008) Corbin, Katherine D., author; Denning, A. Scott, advisorAtmospheric CO2 concentrations are rapidly increasing due to anthropogenic activities; however, only about half of the emissions have accumulated in the atmosphere, and the fate of the remaining half remains uncertain. Since atmospheric CO2 concentrations contain information regarding carbon sources and sinks, it is important to understand CO2 variability. This study investigated causes of atmospheric CO2 variability, focusing on the relationship between CO2 concentrations and clouds, the impact of heterogeneous land cover and agricultural production, and the effect of redistributing fossil fuel emissions. Due to global coverage and sheer data volume, satellite CO2 concentrations will be used in inverse models to improve carbon source and sink estimates. Satellite concentrations will only retrieve CO2 measurements in clear conditions, and it is important to understand how CO2 concentrations vary with cloud cover in order to optimally utilize these data. This study evaluated differences between clear-sky and mean concentrations on local, regional, and global scales. Analyses of in situ data, regional model simulations, and global model output all revealed clear-sky differences that were regionally coherent on sub-continental scales and that varied both with time and location. In the mid-latitudes, clear-sky CO2 concentrations were systematically lower than on average, and these differences were not due to biology, but rather to frontal convergence of large-scale gradients that were covered by clouds. Instead of using satellite data to represent temporal averages, inverse models and data assimilation systems that use satellite data to calculate carbon sources and sinks must be sampled consistently with the observations, including precise modeling of winds, clouds, fronts, and frontal timing. Just as CO2 concentrations vary with cloud cover, variability in atmospheric CO2 concentrations is also caused by heterogeneity in land cover and surface fluxes. This study focused on the impacts of land-cover heterogeneity and the effects of agricultural production on regional variations of atmospheric CO2 concentrations. Including sub-grid scale land cover heterogeneity improved simulated atmospheric CO2 concentrations by ~ 1 ppm. Implementing a crop-phenology model that explicitly simulated corn and soybeans into a coupled ecosystem-atmosphere model dramatically improved CO2 fluxes and concentrations over the mid-continent, with reductions in CO2 concentration root mean square errors of nearly 50% (over 10 ppm at some locations). Both the model and observations showed concentrations as low as 340 ppm over central Iowa, and a regional gradient of over 30 ppm in ~ 200 km occurred due to a combination of fluxes and meteorology. Since corn and soybeans have such a significant impact on both carbon fluxes and atmospheric concentrations, it is essential to model these crops accurately. In addition to biological surface fluxes, surface emissions due to fossil fuel combustion also cause variability in regional atmospheric CO2 concentrations. Using high-resolution fossil fuel emissions caused differences of over 10 ppm near the surface; and including temporal variability in the emissions impacted regional CO2 concentrations on monthly timescales, causing seasonal differences of more than 20 ppm in some locations. Using coarse spatial distributions and unaccounting for temporal variability in fossil fuel emissions created biases in the atmospheric CO2 concentrations and thus may cause significant errors in source and sink estimates from atmospheric inversions.Item Open Access Moist synoptic transport of CO2 along midlatitude storm tracks, transport uncertainty, and implications for flux estimation(Colorado State University. Libraries, 2011) Parazoo, Nicholas C., author; Denning, A. Scott, advisor; Randall, David, committee member; Maloney, Eric, committee member; Kawa, Randy, committee member; Paustian, Keith, committee memberMass transport along moist isentropic surfaces on baroclinic waves represents an important component of the atmospheric heat engine that operates between the equator and poles. This is also an important vehicle for tracer transport, and is correlated with ecosystem metabolism because large-scale baroclinicity and photosynthesis are both driven seasonally by variations in solar radiation. In this research, I pursue a dynamical framework for explaining atmospheric transport of CO2 by synoptic weather systems at middle and high latitudes. A global model of atmospheric tracer transport, driven by meteorological analysis in combination with a detailed description of surface fluxes, is used to create time varying CO2 distributions in the atmosphere. Simulated mass fluxes of CO2 are then decomposed into a zonal monthly mean component and deviations from the monthly mean in space and time. Mass fluxes of CO2 are described on moist isentropic surfaces to represent frontal transport along storm tracks. Forward simulations suggest that synoptic weather systems transport large amounts of CO2 north and south in northern mid-latitudes, up to 1 PgC/month during winter when baroclinic wave activity peaks. During boreal winter when northern plants respire, warm moist air, high in CO2, is swept upward and poleward along the east side of baroclinic waves and injected into the polar vortex, while cold dry air, low in CO2, that had been transported into the polar vortex earlier in the year is advected equatorward. These synoptic eddies act to strongly reduce seasonality of CO2 in the biologically active mid-latitudes by 50% of that implied by local net ecosystem exchange while correspondingly amplifying seasonality in the Arctic. Transport along stormtracks is correlated with rising, moist, cloudy air, which systematically hides this CO2 transport from satellite observing systems. Meridional fluxes of CO2 are of comparable magnitude as surface exchange of CO2 in mid-latitudes, and thus require careful consideration in (inverse) modeling of the carbon cycle. Because synoptic transport of CO2 by frontal systems and moist processes is generally unobserved and poorly represented in global models, it may be a source of error for inverse flux estimates. Uncertainty in CO2 transport by synoptic eddies is investigated using a global model driven by four reanalysis products from the Goddard EOS Data Assimilation System for 2005. Eddy transport is found to be highly variable between model analysis, with significant seasonal differences of up to 0.2 PgC, which represents up to 50% of fossil fuel emissions. The variations are caused primarily by differences in grid spacing and vertical mixing by moist convection and PBL turbulence. To test for aliasing of transport bias into inverse flux estimates, synthetic satellite data is generated using a model at 50 km global resolution and inverted using a global model run with coarse grid transport. An ensemble filtering method called the Maximum Likelihood Ensemble Filter (MLEF) is used to optimize fluxes. Flux estimates are found to be highly sensitive to transport biases at pixel and continental scale, with errors of up to 0.5 PgC/year in Europe and North America.Item Open Access Seasonal greening in grasslands(Colorado State University. Libraries, 2013) Orescanin, Biljana, author; Denning, A. Scott, advisor; Randall, David A., committee member; Paustian, Keith H., committee memberGrasslands cover about one quarter of the Earth's land and are currently considered to act as carbon sinks, taking up an estimated 0.5 Gt C per year. Thus, robust understanding of the grassland biome (e.g. representation of seasonal cycle of plant growth and the amount of green mass, often referred to as phenology, in global carbon models) plays a key role in understanding and predicting the global carbon cycle. The focus of this research is on improvement of a grassland biome representation in a biosphere model, which sometimes fails to correctly represent the phenology of vegetation. For this purpose, as a part of Simple Biosphere model (SiB3), a phenology model is tested and improved to provide more realistic representation of plant growth dependence on available moisture, which along with temperature and light controls plant growth. The new methodology employs integrated soil moisture in plant growth simulation. This new representation addresses the nature of the plants to use their root system to access the water supply. At same time it represents the plant's moisture recourses more accurately than the currently used vapor pressure method, which in grasslands is often non-correlated with soil conditions. The new technique has been developed and tested on data from the Skukuza flux tower site in South Africa and evaluated at 6 different flux tower sites around the world covering a variety of climate conditions. The technique is relatively easy and inexpensive to implement into the existing model providing excellent results capturing both the onset of green season and greening cycle at all locations. Although the method is developed for grasslands biome its representation of natural plant processes provides a good potential for its global use.Item Open Access The effects of long term nitrogen fertilization on forest soil respiration in a subalpine ecosystem in Rocky Mountain National Park(Colorado State University. Libraries, 2016) Allen, Jordan, author; Denning, A. Scott, advisor; Baron, Jill, advisor; Ryan, Mike, committee member; Bowser, Gillian, committee memberAnthropogenic activities contribute to increased levels of nitrogen deposition and elevated CO2 concentrations in terrestrial ecosystems. The response of soil respiration to nitrogen fertilization in an on going 18- year field nitrogen amendment study was conducted from July 2014 to October 2014. The focus of this study was to determine the effects of nitrogen fertilization on soil carbon cycling, via respiration. Our objectives were to (1) test the hypothesis that N additions would increase soil respiration in Rocky Mountain National Park, and (2) understand the impacts of N additions on carbon flows in subalpine forests. A LiCor LI-820 infrared gas analyzer (IRGA) was used to quantify soil respiration rates. We compared soil respiration from fertilized forest plots (30 x 30 m) with soil respiration from control forests plots (30 x 30 m) that receive only ambient nitrogen deposition (3-5 kg/ N/ha-1/yr-1) during the 2014-growing season. Our results shows that mean soil respiration measurements were not significantly different in the control plots (3.14 Āµmol m-2 sec-1) than in the fertilized plots (3.02 Āµmol m-2 sec-1). Treatment was insignificant in influencing soil respiration (p-value greater than 0.5), allowing us to reject our primary hypothesis: that nitrogen additions would lead to an increase in soil respiration. Our results confirm previous research in these plots Advani (2004). The statistically identical soil respiration rates between the control and fertilized plots may result from nitrogen saturation due to elevated levels of ambient N deposition, microbial suppression due to very high levels of N additions in the fertilized plots, or some combination of the two.Item Open Access Transport of pollutants from eastern Colorado into the Rocky Mountains via upslope winds(Colorado State University. Libraries, 2013) PiƱa, Aaron J., author; Denning, A. Scott, advisor; Schumacher, Russ S., committee member; Ham, Jay, committee memberThe confluence of mountain meteorology and major pollution sources come together to transport pollutants across the Front Range, especially nitrogen species (NH3, NH4+, orgN, NO3-, and HNO3) from agricultural and urban regions, into the Rocky Mountains. The focus of this study was to examine the meteorological conditions in which atmospheric wet deposition of inorganic nitrogen in the Rocky Mountains was anomalously high. We analyzed 19 years (1994-2013) of precipitation and concentrations of wet inorganic nitrogen data from three National Atmospheric Deposition Program (NAPD) sites in the Rocky Mountains: Beaver Meadows (CO19), Loch Vale (CO98), and Niwot Ridge (CO02). Beaver Meadows (2477 m), Loch Vale (3159 m), and Niwot Ridge (3520 m) are all within 40 km but differ in elevation, resulting in different seasonal precipitation composition and totals. The North American Regional Reanalysis (NARR) was used to observe synoptic conditions that influenced two high wet deposition events from August 18-20, 2006 and July 6-8, 2012. Interestingly, anti-cyclones in southern Canada and high precipitable water values associated with monsoonal flow played significant roles in initiating convection that caused high values of wet deposition of inorganic nitrogen in the Rocky Mountains. The Advanced Research WRF model was then used to simulate the meteorology at a high spatial and temporal resolution for the two time periods to examine the contribution of cloud-scale convection to wet nitrogen deposition in the Rocky Mountains. A mesoscale mountain circulation caused by differential heating between mountains slopes and the plains was the main driver of the slow westward transport towards the mountains while cloud-scale convection contributed greatly to the transport of nitrogen along the Colorado Front Range.Item Open Access Using remotely sensed fluorescence and soil moisture to better understand the seasonal cycle of tropical grasslands(Colorado State University. Libraries, 2017) Smith, Dakota Carlysle, author; Denning, A. Scott, advisor; Smith, Melinda, committee member; O'Dell, Christopher, committee member; Kummerow, Christian, committee memberSeasonal grasslands account for a large area of Earth's land cover. Annual and seasonal changes in these grasslands have profound impacts on Earth's carbon, energy, and water cycles. In tropical grasslands, growth is commonly water-limited and the landscape oscillates between highly productive and unproductive. As the monsoon begins, soils moisten providing dry grasses the water necessary to photosynthesize. However, along with the rain come clouds that obscure satellite products that are commonly used to study productivity in these areas. To navigate this issue, we used solar induced fluorescence (SIF) products from OCO-2 along with soil moisture products from the Soil Moisture Active Passive satellite (SMAP) to "see through" the clouds to monitor grassland productivity. To get a broader understanding of the vegetation dynamics, we used the Simple Biosphere Model (SiB4) to simulate the seasonal cycles of vegetation. In conjunction with SiB4, the remotely sensed SIF and soil moisture observations were utilized to paint a clearer picture of seasonal productivity in tropical grasslands. The remotely sensed data is not available for every place at one time or at every time for one place. Thus, the study was focused on a large area from 15Ā° E to 35Ā° W and from 8Ā°S to 20Ā°N in the African Sahel. Instead of studying productivity relative to time, we studied it relative to soil moisture. Through this investigation we found soil moisture thresholds for the emergence of grassland growth, near linear grassland growth, and maturity of grassland growth. We also found that SiB4 overestimates SIF by about a factor of two for nearly every value of soil moisture. On the whole, SiB4 does a surprisingly good job of predicting the response of seasonal growth in tropical grasslands to soil moisture. Future work will continue to integrate remotely sensed SIF & soil moisture with SiB4 to add to our growing knowledge of carbon, water, and energy cycling in tropical grasslands.Item Open Access Wetland extent from a topographic index, wetland's impact on land surface fluxes and a model of CH4 exchange(Colorado State University. Libraries, 2011) Kraus, Parker Mayo, author; Denning, A. Scott, advisor; von Fischer, Joe, committee member; Heald, Colette L., committee memberA method of estimating wetland extent is developed for use in the land surface components of climate/atmospheric models. The approach is developed within the Simple Biosphere Model, SiB, but is intended as a flexible framework applicable to other models. It uses the topographic index, ln(a/tanĪ²), to calculate wetland area as a function of regional hydrologic characteristics and model water content. The calculation of the index is discussed, alternatives to the formally required depression-less DEM are investigated and an approach utilizing a smoothed DEM is adopted. Modeled water content is used to establish a point of saturation on the histogram of topographic index, which varies as modeled water content varies, providing estimates of the wetland fraction over time. This relationship is parameterized for the WLEF-TV tower in northern Wisconsin, and tested at locations in Florida and Louisiana. The method of parameterization is found to be acceptable, but site specific parameterization is desirable. Applications of the model are developed. Sensible and latent heat fluxes and net ecosystem exchange modeled with SiB2.5 at the WLEF site are reevaluated with SiB3 and compared to observations. The wetland area model is used to scale SiB3 estimates of these fluxes using a saturated, "wetland," version of the model. Scaling improves estimates, but is overshadowed by errors introduced to the model by changes in the method by which water stress is calculated in SiB. A simple model of methanogenesis and methanotrophy employing predictions of wetland area is proposed and incorporated in SiB. The dynamics of this model are explored in relation to the temperature dependence, Q10, of methanogenic respiration and conditions of equilibrium. Inspection of the model suggests a seasonal cycle of methane flux with summertime emission and fall and springtime consumption. Estimates from the model are compared with Modified Bowen Ratio, MBR, estimates of methane flux based on observations at WLEF site. Observed fluxes offer some empirical constraint on methanogenic Q10, but uncertainties in the methane flux preclude assessment of the variability of wetland area. Methane consumption is overrepresented in the predicted seasonal cycle of methane flux due to the simplified representation of methanotrophy in the model, but the essential expected behavior is confirmed. Verification of model parameters beyond the WLEF is necessary, though the feasibility of modeling variable wetland extent using the topographic index is demonstrated. Applications of the calculation for representing sub-grid scale soil moisture variability and saturated zone biogeochemistry appear promising for use in atmosphere-coupled regional or global model runs.