Marc Stieglitz

Georgia Institute of Technology, Atlanta, Georgia, United States

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Publications (92)230.76 Total impact

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    ABSTRACT: While river-borne materials are recognized as important resources supporting coastal ecosystems around the world, estimates of river export from the North Slope of Alaska have been limited by a scarcity of water chemistry and river discharge data. This paper quantifies water, nutrient, and organic matter export from the three largest rivers (Sagavanirktok, Kuparuk, Colville) that drain Alaska's North Slope and discusses the potential importance of river inputs for biological production in coastal waters of the Alaskan Beaufort Sea. Together these rivers export ~297,000 metric tons of organic carbon and ~18,000 metric tons of organic nitrogen each year. Annual fluxes of nitrate-N, ammonium-N, and soluble reactive phosphorus are approximately 1750, 200, and 140 metric tons per year respectively. Constituent export from Alaska's North Slope is dominated by the Colville River. This is in part due to its larger size, but also because constituent yields are greater in the Colville watershed. River-supplied nitrogen may be more important to productivity along the Alaskan Beaufort Sea coast than previously thought. However, given the dominance of organic nitrogen export, the potential role of river-supplied nitrogen in support of primary production depends strongly on remineralization mechanisms. Although rivers draining the North Slope of Alaska make only a small contribution to overall river export from the pan-arctic watershed, comparisons with major arctic rivers reveal unique regional characteristics as well as remarkable similarities among different regions and scales. Such information is crucial for development of robust river export models that represent the arctic system as a whole.
    02/2014; 50(2). DOI:10.1002/2013WR014722
  • Sopan Patil, Marc Stieglitz
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    ABSTRACT: Rainfall–runoff modelling at ungauged catchments often involves the transfer of calibrated model parameters from ‘donor’ gauged catchments. However, in any rainfall–runoff model, some parameters tend to be more sensitive to the objective function, whereas others are insensitive over their entire feasible range. In this paper, we analyse the effect of selectively transferring sensitive versus insensitive parameters on streamflow predictability at ungauged catchments. We develop a simple daily time-step rainfall–runoff model [exponential bucket hydrologic model (EXP-HYDRO)] and calibrate it at 756 catchments within the continental USA. Nash–Sutcliffe efficiency of sqrt Q (NS) is used as the objective function. The model simulates satisfactorily at 323 catchments (NS > 0.6), most of which are located in the eastern part of the USA, along the Rocky Mountain Range, and near the western Pacific coast. Of the six calibration parameters, only three parameters are found to be sensitive to NS. Two of these parameters control the hydrograph recession behaviour of a catchment, and the third parameter controls the snowmelt rate. We find that when only sensitive parameters are transferred, model performance at ungauged catchments is almost at par with that of transferring all six parameters. Conversely, the transfer of only insensitive parameters results in a significant deterioration in model performance. Results suggest that streamflow predictability at ungauged catchments using rainfall–runoff models is largely dependent on the transfer of a small subset of parameters. We recommend that, in any modelling framework, such parameters should be identified and further characterized to better understand the information controlling streamflow predictability at ungauged catchments.
    Hydrological Processes 01/2014; 28(3):1159-1169. DOI:10.1002/hyp.9660 · 2.70 Impact Factor
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    ABSTRACT: We used a new ecohydrological model, Visualizing Ecosystems for Land Management Assessments (VELMA), to analyze the effects of forest harvest on catchment carbon and nitrogen dynamics. We applied the model to a 10 ha headwater catchment in the western Oregon Cascade Range where two major disturbance events have occurred during the past 500 years: a stand-replacing fire circa 1525 and a clear-cut in 1975. Hydrological and biogeochemical data from this site and other Pacific Northwest forest ecosystems were used to calibrate the model. Model parameters were first calibrated to simulate the postfire buildup of ecosystem carbon and nitrogen stocks in plants and soil from 1525 to 1969, the year when stream flow and chemistry measurements were begun. Thereafter, the model was used to simulate old-growth (1969-1974) and postharvest (1975-2008) temporal changes in carbon and nitrogen dynamics. VELMA accurately captured observed changes in carbon and nitrogen dynamics before and after harvest. The interaction of hydrological and biogeochemical processes in the model provided a means for interpreting these changes. Results show that (1) losses of dissolved nutrients in the preharvest old-growth forest were generally low and consisted primarily of organic nitrogen and carbon; (2) following harvest, carbon and nitrogen losses from the terrestrial system to the stream and atmosphere increased as a result of reduced plant nitrogen uptake, increased soil organic matter decomposition, and high soil moisture; and (3) the rate of forest regrowth following harvest was lower than that after fire because post-clear-cut stocks and turnover of detritus nitrogen were substantially lower than after fire.
    Water Resources Research 03/2013; 49(3):1292-1313. DOI:10.1029/2012WR012994 · 3.71 Impact Factor
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    ABSTRACT: Background/Question/Methods The effectiveness of riparian forest buffers and other green infrastructure for reducing nitrogen export to agricultural streams has been well described experimentally, but a clear understanding of process-level hydrological and biogeochemical controls can be difficult to ascertain from data alone. We previously applied a new ecohydrological model, Visualizing Ecosystems for Land Management Assessments (VELMA), to further elucidate how riparian forest buffers reduce stream inputs of dissolved nitrogen in runoff from upland agricultural practices in an intensively studied catchment in the Rhode River Watershed along the western shore of Chesapeake Bay, USA. Simulated and observed daily stream flow and export of ammonium and nitrate were in generally good agreement over the period of record (2000-2003) for which complete daily stream flow and chemistry data were available. For the present study we used sensitivity analysis to explore the model’s potential for extending the experimental data to identify upland and riparian best management practices (BMPs) that most effectively reduce stream nitrogen loads. Candidate BMPs considered the sensitivity of nitrogen reduction to the timing and rate of upland fertilization and to green infrastructure extent (buffer width), type (forest or grass) and management (stand age). Results/Conclusions The model suggests that riparian forest buffers are more effective than grass buffers in reducing stream nitrogen loads. Greater buffer width and stand age increase nitrogen reductions, but gains in effectiveness diminish asymptotically for both variables. Green infrastructure solutions alone may be insufficient for achieving water quality standards where riparian flow paths are predominantly deep or where upland fertilization approaches rates often used for intensive agriculture. The model also quantitatively describes the trade-off between agronomic production and nitrogen export to surface waters and the relative importances of denitrification and plant uptake in reducing nitrogen export under different upland and riparian management scenarios.
    97th ESA Annual Convention 2012; 08/2012
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    Feifei Pan, Robert B. McKane, Marc Stieglitz
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    ABSTRACT: The accuracy of six combined methods formed by three commonly-used soil hydraulic functions and two methods to determine soil hydraulic parameters based on a soil hydraulic parameter look-up table and soil pedotransfer functions was examined for simulating soil moisture. A novel data analysis and modelling approach was used that eliminated the effects of evapotranspiration so that specific sources of error among the six combined methods could be identified and quantified. By comparing simulated and observed soil moisture at six sites of the USDA Soil Climate Analysis Network, we identified the optimal soil hydraulic functions and parameters for predicting soil moisture. Through sensitivity tests, we also showed that adjusting only the soil saturated hydraulic conductivity, Ks, is insufficient for representing important effects of macropores on soil hydraulic conductivity. Our analysis illustrates that, in general, soil hydraulic conductivity is less sensitive to Ks than to the soil pore-size distribution parameter.Editor D. Koutsoyiannis; Associate editor D. HughesCitation Pan, F., McKane, R.B. and Stieglitz, M., 2012. Identification of optimal soil hydraulic functions and parameters for predicting soil moisture. Hydrological Sciences Journal, 57 (4), 1–15.
    Hydrological Sciences Journal/Journal des Sciences Hydrologiques 05/2012; DOI:10.1080/02626667.2012.674642 · 1.25 Impact Factor
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    S. Patil, M. Stieglitz
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    ABSTRACT: Prediction of streamflows at ungauged catchments requires transfer of hydrologic information (e.g., model parameters, hydrologic indices, streamflow values) from gauged (donor) to ungauged (receiver) catchments. One of the most reliable metrics for selection of ideal donor catchments is the spatial proximity between donor and receiver catchments. However, it is not clear whether information transfer among nearby catchments is suitable across a wide range of climatic and geographic regions. We examine this issue using the data from 756 catchments within the continental United States. Each catchment is considered ungauged in turn and daily streamflow is simulated through distance-based interpolation of streamflows from neighboring catchments. Results show that distinct geographic regions exist in US where transfer of streamflow values from nearby catchments is useful for retrospective prediction of daily streamflow at ungauged catchments. Specifically, the high predictability catchments (Nash-Sutcliffe efficiency NS > 0.7) are confined to the Appalachian Mountains in eastern US, the Rocky Mountains, and the Cascade Mountains in the Pacific Northwest. Low predictability catchments (NS < 0.3) are located mostly in the drier regions west of Mississippi river, which demonstrates the limited utility of gauged catchments in those regions for predicting at ungauged basins. The results suggest that high streamflow similarity among nearby catchments (and therefore, good predictability at ungauged catchments) is more likely in humid runoff-dominated regions than in dry evapotranspiration-dominated regions. We further find that higher density and/or closer distance of gauged catchments near an ungauged catchment does not necessarily guarantee good predictability at an ungauged catchment.
    Hydrology and Earth System Sciences Discussions 02/2012; 16(2):551-562. DOI:10.5194/hess-16-551-2012 · 3.59 Impact Factor
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    Feifei Pan, Marc Stieglitz, Robert B Mckane
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    ABSTRACT: 1] Digital elevation model (DEM) data are essential to hydrological applications and have been widely used to calculate a variety of useful topographic characteristics, e.g., slope, flow direction, flow accumulation area, stream channel network, topographic index, and others. Except for slope, none of the other topographic characteristics can be calculated until the flow direction at each pixel within a DEM is determined. However, flow direction cannot be accurately calculated until depressions and flat areas within a DEM have been rectified. This is a routine problem in hydrologic modeling, because virtually all DEMs contain flat and sink pixels, both real and artifactual, that if left untreated will prevent accurate simulation of hydrologic flow paths. Although a number of algorithms are available for rectifying flat and sink pixels in DEM data, treatment of flat areas and depressions and calculation of flow direction remain problematic for reasons of complexity and uncertainty. A new algorithm that effectively rectifies flat and sink pixels was developed and tested. The approach is to use linear interpolation between low elevation grid cells on the edge of each flat area or depression defined as outlets and higher elevation grid cells on the opposite side defined as inflow pixels. The implementation requires an iterative solution to accommodate the irregular geometry of flat areas or depressions and exceptions that arise. Linear interpolation across flat areas or depressions provides a natural way to scale elevation adjustments based on the vertical scale of the surrounding topography, thereby avoiding the addition or subtraction of arbitrary small numbers that we regard as a disadvantage in some prior techniques. Tests for two virtual terrains and one real terrain show that our algorithm effectively rectifies flat areas and depressions, even in low-relief terrain, and produces realistic patterns of flow accumulation and extracted channel networks., An algorithm for treating flat areas and depressions in digital elevation models using linear interpolation, Water Resour. Res., 48, W00L10, doi:10.1029/2011WR010735.
    Water Resources Research 01/2012; 48(6). DOI:10.1029/2011WR010735 · 3.71 Impact Factor
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    ABSTRACT: The effects of riparian vegetation on the reduction of agricultural nitrogen export to streams have been well described experimentally, but a clear understanding of process-level hydrological and biogeochemical controls can be difficult to ascertain from data alone. We apply a new model, Visualizing Ecosystems for Land Management Assessments (VELMA), to further elucidate how riparian forest buffers reduce stream inputs of dissolved nitrogen in runoff from upland agricultural practices in an intensively studied catchment in the Rhode River Watershed along the western shore of Chesapeake Bay, USA. VELMA is a spatially distributed eco-hydrology model that links hydrological and biogeochemical processes within watersheds. Simulated and observed daily stream flow and export of nitrogen (ammonium, nitrate and organic nitrogen) are in generally good agreement for the period of record (2000-2003) for which complete daily stream flow and chemistry data were available. A sensitivity analysis of the model demonstrates its potential for isolating specific hydrologic and biogeochemical controls on attenuation of dissolved nitrogen within the riparian forest zone, and for identifying upland and riparian best management practices concerning water quality. The results indicate that subsurface flow pathways, forest buffer design (width), and management (stand age) have a significant influence on stream nitrogen loads. However, forest buffers alone may be insufficient for achieving water quality standards, particularly where upland fertilization rates approach those often used for intensive agriculture. These insights include a quantitative description of the trade-off between agronomic production and nitrogen export to surface waters, and the relative importance of denitrification in reducing nitrogen export under different upland and riparian management scenarios.
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    ABSTRACT: Linear increase in stream discharge with increasing harvest areaLarge absolute fall changes and large relative summer changes in streamflowChanges in streamflow were strongly sensitive to harvest location
    Water Resources Research 09/2011; 47(9). DOI:10.1029/2010WR010165 · 3.71 Impact Factor
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    Patil S, Stieglitz M
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    ABSTRACT: An assessment of regional similarity in catchment stream response is often needed for accurate predictions in ungauged catchments. However, it is not clear whether similarity among catchments is preserved at all flow conditions. We address this question through the analysis of flow duration curves for 25 gauged catchments located across four river basins in the northeast United States. The coefficient of variation of streamflow percentiles is used as a measure of variability among catchments across flow conditions. Results show that similarity in catchment stream response is dynamic and highly dependent on flow conditions. Specifically, within each of the four basins, the coefficient of variation is high at low flow percentiles and gradually reduces for higher flow percentiles. Analysis of the inter-annual variation in streamflow percentiles shows a similar reduction in variability from low flow to high flow percentiles. Greater similarity in streamflows is observed during the winter and spring (wet) seasons compared to the summer and fall (dry) seasons. Results suggest that the spatial variability in streamflow at low flows is primarily controlled by the dominance of high evaporative demand during the warm period. On the other hand, spatial variability at high flows during the cold period is controlled mostly by the increased dominance of precipitation input over evapotranspiration. By evaluating variability over the entire range of streamflow percentiles, this work explores the nature of hydrologic similarity from an inter-seasonal perspective.
    Hydrology and Earth System Sciences 03/2011; 15(3):989-997. DOI:10.5194/hess-15-989-2011 · 3.59 Impact Factor
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    Yiwei Cheng, Marc Stieglitz, Greg Turk, Victor Engel
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    ABSTRACT: Wetland ecosystems are often characterized by distinct vegetation patterns. Various mechanisms have been proposed to explain the formation of these patterns; including spatially variable peat accumulation and water ponding. Recently, short-range facilitation and long-range competition for resources (a.k.a scale dependent feedback) has been proposed as a possible mechanism for pattern formation in wetland ecosystems. We modify an existing, spatially explicit, advection-reaction-diffusion model to include for a regional hydraulic gradient and effective anisotropy in hydraulic conductivity. This effective anisotropic hydraulic conductivity implicitly represents the effect of ponding: a reduction in the long-range inhibition of vegetation growth in the direction perpendicular to the prevailing hydraulic gradient. We demonstrate that by accounting for effective anisotropy in a simple modeling framework that encompasses only a scale dependent feedback between biomass and nutrient flow, we can reproduce the various vegetation patterns observed in wetland ecosystems: maze, and vegetation bands both perpendicular and parallel to prevailing flow directions. We examine the behavior of this model over a range of plant transpiration rates and regional hydraulic gradients. Results show that by accounting for the effective x-y anisotropy that results from biomass-water interaction (i.e., ponding) we can better understand the mechanisms that drive ecosystem patterning.
    02/2011; 38(4). DOI:10.1029/2010GL046091
  • A. G. Abdelnour, M. Stieglitz, R. McKane, F. Pan
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    ABSTRACT: The potential interacting effects of climate change and future land-use on hydrological and biogeochemical dynamics rarely have been described at the catchment level and are difficult or impossible to capture through experimentation or observation alone. We apply a new model, Visualizing Ecosystems for Land Management Assessment (VELMA), to the H.J. Andrews (HJA) Experimental Forest in western Oregon, USA, to simulate the effects of multiple, future climate and land-use scenarios on catchment hydrology and soil C and N dynamics. VELMA is a spatially distributed eco-hydrology model that links hydrological and biogeochemical processes within watersheds. The model simulates daily to century-scale changes in soil water infiltration and redistribution, evapo-transpiration, surface and subsurface runoff, carbon (C) and nitrogen (N) cycling in plants and soils, and the transport of dissolved forms of carbon and nitrogen from the terrestrial landscape to streams. VELMA was previously calibrated and validated for the HJA based on long-term data (1975-2008) describing daily to decadal changes in stream discharge and chemistry, soil and plant carbon, and nitrogen dynamics in response to climate, harvest and fire. That exercise demonstrated that the same set of model parameters accurately simulates hydro-biogeochemical dynamics at multiple spatial scales at HJA, from a small (10-ha) catchment to the 64 km2 HJA basin. Here we use this validated VELMA model to (1) explore the effects of climate change scenarios on catchment hydro-biogeochemical dynamics, and (2) examine forest harvest effects (clearcutting) across climate scenarios on catchment hydro-biogeochemical dynamics in this old growth forest of the Pacific Northwest.
  • M. Stieglitz, S. Patil
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    ABSTRACT: Predictions of streamflow in ungauged basins are required in many regions of the world and across a wide range of environmental settings. However, the physiographic and climatic conditions that favor better predictability at ungauged catchments are still not fully known. In this study, we use the data from 806 gauged catchments across the continental United States to simulate daily streamflow at ungauged catchments using the distance-weighted average of streamflow values from neighboring gauged catchments. Results show that 308 (~ 38%) catchments have Nash-Sutcliffe efficiency (NS) of simulation greater than 0.7, with the median NS value of 0.61. High predictability catchments (NS > 0.7) are mostly located along the Appalachian Mountains in Eastern US, the Rocky Mountains, and the Cascade Mountains in the Pacific Northwest of US. On the other hand, low predictability catchments (NS < 0.3) are located mostly along the drier regions of the US to the west of Mississippi river. Further analysis of physiographic and hydrologic properties of individual catchments shows that no strong relationships exist between catchment attributes and their NS values. The observed geographic patterns of NS values suggest that the climate-induced competition between energy and water limitation in the water balance of catchments is the main controlling factor on predictability. Regions in which the water balance of catchments is energy limited (humid) are more likely to have high predictability than those in which the water balance of catchments is water-limited (arid).
  • Yiwei Cheng, Marc Stieglitz, Feifei Pan
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    ABSTRACT: The Simple Land-Interface Model (SLIM) was modified to evolve daily ground temperatures from surface air temperatures (SAT) in snow-dominated areas. Daily ground surface temperature (GST) was modeled as a function of daily surface air temperature and snow depth. Analytical solution to the 1-D thermal diffusion equation was then used to simulate subsequent propagation of the GST signals into the subsurface. Time dependent apparent thermal diffusivity was modeled as a simple sinusoid and incorporated into the framework to account for the effects of seasonal latent heat and nonconductive heat transfer processes. The model was tested in snow-dominated sites such as Barrow, Council and Ivotuk in Alaska, and Reynolds Creek Experimental Watershed in Idaho. The model captured much of the seasonal dynamics of the ground thermal regime at all sites. It underestimated the fall ground temperatures in Barrow and Ivotuk in some years and overestimated spring ground temperatures in Council.
    Journal of Hydrometeorology 12/2010; DOI:10.1175/2010JHM1240.1 · 3.57 Impact Factor
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    ABSTRACT: The interactions between vegetation and hydrology in mountainous terrain are difficult to represent in mathematical models. There are at least three primary reasons for this difficulty. First, expanding plot-scale measurements to the watershed scale requires finding the balance between computational intensity and physical significance. Second, parameters that affect soil, plant and hydrologic processes are distributed heterogeneously across mountain landscapes, and these patterns and processes may be spatially connected. Third, temporal variation in water availability (particularly in seasonal rainfall climates) may involve a ``topographical memory'' that may be expressed as ``lags'' between biological and hydrological processes. A unique opportunity for examining the implications of scaling and spatio-temporal variability on ecohydrological models exists at the H.J. Andrews Experimental Forest (HJA) in Blue River, Oregon. HJA is a National Science Foundation Long Term Ecological Research (LTER) site, and has been monitoring climate, stream, and vegetation characteristics of small watersheds for more than 50 years. A recent LIDAR (Light Detection and Ranging) reconnaissance has produced watershed scale estimations of vegetation and soil surface parameters at a very high spatial resolution, allowing spatially-explicit expansion of long-term data. An ecohydrological model, Visualizing Ecosystems for Land Management Assessments (VELMA) developed by the Stieglitz lab at Georgia Tech in collaboration with EPA has also been calibrated specifically for watershed topographies in HJA. VELMA is a coupled ecohydrological model that simulates the cycling and transport of water and nutrients in three dimensions by specific parameterization of hydrological and biogeochemical functions. It contains submodels for plant, soil, and water processes including surface and sub-surface flow on a daily time step. We are using the VELMA model to explore three sequential and fundamental questions in ecohydrological modeling in mountainous terrain. 1) How does the topographical structure of mountains (elevation, slope, and aspect) impact hydrological parameters such as temperature, rainfall, soil depth, canopy structure, and airflow? 2) To what degree are the model results from high-resolution, spatially-explicit parameterization different from results based on broadly distributed means, and when different, on what scale(s) are the discrepancies most pronounced? 3) Is there an optimal scale for the process-based ecohydrological modeling, and if so, what are the computational limits at this scale? This poster will present our overall experimental plan and initial findings. Experimentation on and establishment of a standard procedure for spatial and temporal partitioning in ecohydrological models is a fundamental step from which advancement towards more comprehensive, dynamic models can be developed.
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    ABSTRACT: Background/Question/Methods The U.S. Environmental Protection Agency recently established the Ecosystem Services Research Program to help formulate methods and models for conducting comprehensive risk assessments that quantify how multiple ecosystem services interact and respond in concert to environmental changes. A major goal is to assess how alternative land use and climate scenarios will simultaneously affect food and fiber production, water quality and quantity, regulation of greenhouse gases, and other ecosystem services. Essential to this goal are highly integrated models that can be used to define policy and management strategies for entire ecosystems, not simply individual components of the ecosystem. In this context, an ideal model is one that (1) can unambiguously link effects to causes by identifying key processes that control ecosystem service tradeoffs, (2) can be applied to a wide variety of ecosystems and regions, (3) can be implemented using readily available data, (4) can efficiently map “bundles” of ecosystem services across wide spatial and temporal scales, and (5) can provide a decision support framework for assessing outcomes of alternative policies and management decisions. We developed an eco-hydrologic modeling framework that aims to meet these emerging risk assessment objectives more closely than other currently available models. Results/Conclusions VELMA (Visualizing Ecosystems for Land Management Assessments) is a spatially-distributed eco-hydrologic model that links a land surface hydrologic model with a terrestrial biogeochemistry model for simulating the integrated responses of vegetation, soil, and water resources to interacting stressors. Here we describe a proof-of-concept application of VELMA to the H.J. Andrews Experimental Forest, a forested 64 km2 headwater basin and LTER site in the Cascade Range of Oregon. We used VELMA to simulate the effects of three different land use scenarios (100% old-growth, 100% clearcut harvest, and present-day land cover consisting of 45% old-growth and 55% harvested) on changes in five ecosystem services: timber production, carbon sequestration, greenhouse gas regulation, water quantity, and water quality. Compared to the old-growth simulation, over a 60-year period the clearcut simulation reduced total ecosystem carbon stocks by 40%, increased total stream discharge by 15%, increased stream nitrogen export by almost 300%, and increased total CO2 and N2O radiative forcing by over 200%. The simulation for present-day land cover resulted in intermediate values in most cases. Ongoing work is focused on model validation tests for several other LTER sites (Konza Prairie, Hubbard Brook, arctic tundra), and regional applications for Oregon’s Willamette River Basin and Central Plains rangelands.
    95th ESA Annual Convention 2010; 08/2010
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    ABSTRACT: Continuous time-series estimates of net ecosystem carbon exchange (NEE) are routinely made using eddy covariance techniques. Identifying and compensating for errors in the NEE time series can be automated using a signal processing filter like the ensemble Kalman filter (EnKF). The EnKF compares each measurement in the time series to a model prediction and updates the NEE estimate by weighting the measurement and model prediction relative to a specified measurement error estimate and an estimate of the model-prediction error that is continuously updated based on model predictions of earlier measurements in the time series. Because of the covariance among model variables, the EnKF can also update estimates of variables for which there is no direct measurement. The resulting estimates evolve through time, enabling the EnKF to be used to estimate dynamic variables like changes in leaf phenology. The evolving estimates can also serve as a means to test the embedded model and reconcile persistent deviations between observations and model predictions. We embedded a simple arctic NEE model into the EnKF and filtered data from an eddy covariance tower located in tussock tundra on the northern foothills of the Brooks Range in northern Alaska, USA. The model predicts NEE based only on leaf area, irradiance, and temperature and has been well corroborated for all the major vegetation types in the Low Arctic using chamber-based data. This is the first application of the model to eddy covariance data. We modified the EnKF by adding an adaptive noise estimator that provides a feedback between persistent model data deviations and the noise added to the ensemble of Monte Carlo simulations in the EnKF. We also ran the EnKF with both a specified leaf-area trajectory and with the EnKF sequentially recalibrating leaf-area estimates to compensate for persistent model-data deviations. When used together, adaptive noise estimation and sequential recalibration substantially improved filter performance, but it did not improve performance when used individually. The EnKF estimates of leaf area followed the expected springtime canopy phenology. However, there were also diel fluctuations in the leaf-area estimates; these are a clear indication of a model deficiency possibly related to vapor pressure effects on canopy conductance.
    Ecological Applications 07/2010; 20(5):1285-301. DOI:10.1890/09-0876 · 4.13 Impact Factor
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    ABSTRACT: Feedbacks between water use, biomass and infiltration capacity in semiarid ecosystems have been shown to lead to the spontaneous formation of vegetation patterns in a simple model. The formation of patterns permits the maintenance of larger overall biomass at low rainfall rates compared with homogeneous vegetation. This results in a bias of models run at larger scales neglecting subgrid-scale variability. In the present study, we investigate the question whether subgrid-scale heterogeneity can be parameterized as the outcome of optimal partitioning between bare soil and vegetated area. We find that a two-box model reproduces the time-averaged biomass of the patterns emerging in a 100 x 100 grid model if the vegetated fraction is optimized for maximum entropy production (MEP). This suggests that the proposed optimality-based representation of subgrid-scale heterogeneity may be generally applicable to different systems and at different scales. The implications for our understanding of self-organized behaviour and its modelling are discussed.
    Philosophical Transactions of The Royal Society B Biological Sciences 05/2010; 365(1545):1449-55. DOI:10.1098/rstb.2009.0309 · 6.31 Impact Factor
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    Yiwei Cheng, Marc Stieglitz, Greg Turk, Victor Engel
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    ABSTRACT: It has long been a challenge to theoretical ecologists to describe vegetation pattern formations such as the "tiger bush" stripes and "leopard bush" spots in Niger, and the regular maze patterns often observed in bogs in North America and Eurasia. To date, most of simulation models focus on reproducing the spot and labyrinthine patterns, and on the vegetation bands which form perpendicular to surface and groundwater flow directions. Various hypotheses have been invoked to explain the formation of vegetation patterns: selective grazing by herbivores, fire, and anisotropic environmental conditions such as slope. Recently, short distance facilitation and long distance competition between vegetation (a.k.a scale dependent feedback) has been proposed as a generic mechanism for vegetation pattern formation. In this paper, we test the generality of this mechanism by employing an existing, spatially explicit, advection-reaction-diffusion type model to describe the formation of regularly spaced vegetation bands, including those that are parallel to flow direction. Such vegetation patterns are, for example, characteristic of the ridge and slough habitat in the Florida Everglades and which are thought to have formed parallel to the prevailing surface water flow direction. To our knowledge, this is the first time that a simple model encompassing a nutrient accumulation mechanism along with biomass development and flow is used to demonstrate the formation of parallel stripes. We also explore the interactive effects of plant transpiration, slope and anisotropic hydraulic conductivity on the resulting vegetation pattern. Our results highlight the ability of the short distance facilitation and long distance competition mechanism to explain the formation of the different vegetation patterns beyond semi-arid regions. Therefore, we propose that the parallel stripes, like the other periodic patterns observed in both isotropic and anisotropic environments, are self-organized and form as a result of scale dependent feedback. Results from this study improve upon the current understanding on the formation of parallel stripes and provide a more general theoretical framework for future empirical and modeling efforts.
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    ABSTRACT: Fluxes of nutrients and organic matter from watersheds to the coastal ocean are tightly coupled with climate variables that control the water balance as well as biological and geochemical activity. Consequently, major changes in nutrient and organic matter export from rivers are expected to accompany global climate change. These changes in river export may significantly alter biological production in coastal waters. In densely populated regions of the world, these linkages are confounded by many additional anthropogenic influences (such as land-use and fisheries). However, climate remains the dominant control over river export in many regions of the Arctic. This presentation will focus on nutrient and organic matter export from the Sagavanirktok, Kuparuk, and Colville rivers to the Alaskan Beaufort Sea. Together these three rivers capture most of the runoff from the North Slope of Alaska. Data from intensive field efforts in 2006 and 2007 will be used as a basis for discussion of potential watershed contributions to coastal productivity and changes that may be expected as climate and the landscape of Alaska's North Slope change. River-borne contributions of nutrients and organic matter to coastal waters of the Alaskan Beaufort Sea are highly seasonal, with the majority of export occurring during the spring snowmelt period. Organic matter quality (as demonstrated by stable isotope values of particulate organic matter as well as lability assays) also changes dramatically between seasons. Potential effects of changing seasonality will be given particular attention in this presentation.
    AGU Fall Meeting Abstracts; 12/2009

Publication Stats

2k Citations
230.76 Total Impact Points

Institutions

  • 2004–2014
    • Georgia Institute of Technology
      • • School of Civil & Environmental Engineering
      • • School of Earth and Atmospheric Sciences
      Atlanta, Georgia, United States
  • 2005
    • Harvard University
      • Department of Earth and Planetary Sciences
      Cambridge, Massachusetts, United States
  • 1999–2005
    • Lamont - Doherty Earth Observatory Columbia University
      New York City, New York, United States
  • 1997–2004
    • Columbia University
      • • Department of Earth and Environmental Sciences
      • • Lamont-Doherty Earth Observatory
      New York, New York, United States