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EM: VELMA (visualizing ecosystems for land management assessments) hydro, Oregon, USA (EM-375)
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EM Identity and Description
EM Identification
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EM ID
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EM-375 |
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EM Short Name
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VELMA hydro, Oregon, USA |
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EM Full Name
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VELMA (visualizing ecosystems for land management assessments) hydro, Oregon, USA |
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EM Source or Collection
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US EPA |
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EM Source Document ID
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13 |
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Document Author
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Abdelnour, A., Stieglitz, M., Pan, F. and McKane, R. B. |
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Document Year
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2011 |
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Document Title
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Catchment hydrological responses to forest harvest amount and spatial pattern |
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Document Status
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Peer reviewed and published |
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Comments on Status
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Published journal manuscript |
Software and Access
| Bob McKane, VELMA Team Lead, USEPA-ORD-NHEERL-WED, Corvallis, OR (541) 754-4631; mckane.bob@epa.gov | |
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Contact Name
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A. Abdelnour |
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Contact Address
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Dept. of Civil and Environmental Engineering, Goergia Institute of Technology, Atlanta, GA 30332-0335, USA |
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Contact Email
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abdelnouralex@gmail.com |
EM Description
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Summary Description
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AUTHOR'S DESCRIPTION: "VELMA uses a distributed soil column framework to simulate the movement of water and nutrients (NH4, NO3, DON, DOC) within the soil, between the soil and the vegetation, and between the soil surface and vegetation to the atmosphere. The soil column model consists of three coupled submodels: (1) a hydrological model that simulates vertical and lateral movement of water within soil, losses of water from soil and vegetation to the atmosphere, and the growth and ablation of the seasonal snowpack, (2) a soil temperature model that simulates daily soil layer temperatures from surface air temperature and snow depth, and (3) a plant-soil model that simulates C and N dynamics. (Note: for the purposes of this paper we describe only the hydrologic aspects of the model.) Each soil column consists of n soil layers. Soil water balance is solved for each layer (equations (A1)–(A6)). We employ a simple logistic function that is based on the degree of saturation to capture the breakthrough characteristics of soil water drainage (equations (A7)–(A9)). Evapotranspiration increases exponentially with increasing soil water storage and asymptotically approaches the potential evapotranspiration rate (PET) as water storage reaches saturation [Davies and Allen, 1973; Federer, 1979, 1982; Spittlehouse and Black, 1981] (equation (A12)). PET is estimated using a simple temperature-based method [Hamon, 1963] (equation (A13)). An evapotranspiration recovery function is used to account for the effects of changes in stand-level transpiration rates during succession, e.g., after fire or harvest (equation (B2)). Snowmelt is estimated using the degree-day approach [Rango and Martinec, 1995] and accounts for the effects of rain on snow [Harr, 1981] (equation (A10)). [15] The soil column model is placed within a catchment framework to create a spatially distributed model applicable to watersheds and landscapes. Adjacent soil columns interact with each other through the downslope lateral transport of water (Figures A1 and A2). Surface and subsurface lateral flow are routed using a multiple flow direction method [Freeman, 1991; Quinn et al., 1991]. As with vertical drainage of soil water, lateral subsurface downslope flow is modeled using a simple logistic function multiplied by a factor to account for the local topographic slope angle (equation (A16))… The model is forced with daily temperature and precipitation. Daily observed streamflow data is used to calibrate and validate simulated discharge." "Model calibration is needed to accurately capture the pre- and postharvest dynamics at WS10. This model calibration consists of two simulations: an old-growth simulation for the period 1969-1974 and a post-harvest simulation for the period 1975-2008." Two additional sets of VELMA simulations examining changes in streamflow are presented in the paper, but not included here. Twenty simulations were conducted varying the location across the watershed of a 20% har |
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Specific Policy or Decision Context Cited
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None identified |
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Biophysical Context
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Basin elevation ranges from 430 m at the stream gauging station to 700 m at the southeastern ridgeline. Near stream and side slope gradients are approximately 24o and 25o to 50o, respectively. The climate is relatively mild with wet winters and dry summer. Mean annual temperature is 8.5 oC. Daily temperature extremes vary from 39 oC in the summer to -20 oC in the winter. Mean annual precipitation is 2300 mm and falls primarily as rain between October and April. Total rainfall during June– September averages 200 mm. Snow rarely persists longer than a couple of weeks and usually melts within 1 to 2 days. Average annual streamflow is 1600 mm, which is approximately 70% of annual precipitation. Soils are of the Frissel series, classified as Typic Dystrochrepts with fine loamy to loamy-skeletal texture that are generally deep and well drained. These soils quickly transmit subsurface water to the stream. Prior to the 1975 100% clearcut, WS10 was a 400 to 500 year old forest dominated by Douglas-fir (Pseudotsuga menziesii), western hemlock (Tsuga heterophylla), and western red cedar (Thuja plicata). The dominant vegetation of WS10 today is a 35 year old mixed Douglasfir and western hemlock stand. |
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EM Scenario Drivers
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Stand age; old-growth (pre-harvest), and harvested (postharvest) |
EM Relationship to Other EMs or Applications
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Method Only, Application of Method or Model Run
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Method + Application (multiple runs exist) View EM Runs |
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New or Pre-existing EM?
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New or revised model |
Related EMs (for example, other versions or derivations of this EM) described in ESML
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Document ID for related EM
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Doc-317 |
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EM ID for related EM
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EM-379 | EM-380 | EM-605 | EM-884 | EM-883 | EM-887 |
EM Modeling Approach
EM Relationship to Time
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EM Temporal Extent
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1969-2008 |
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EM Time Dependence
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time-dependent |
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EM Time Reference (Future/Past)
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future time |
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EM Time Continuity
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discrete |
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EM Temporal Grain Size Value
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1 |
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EM Temporal Grain Size Unit
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Day |
EM Spatial Extent
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Bounding Type
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Watershed/Catchment/HUC |
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Spatial Extent Name
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H. J. Andrews LTER WS10 |
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Spatial Extent Area (Magnitude)
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10-100 ha |
Spatial Distribution of Computations
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EM Spatial Distribution
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spatially distributed (in at least some cases) |
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Spatial Grain Type
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other (specify), for irregular (e.g., stream reach, lake basin) |
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Spatial Grain Size
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30 m x 30 m surface pixel and 2-m depth soil column |
EM Structure and Computation Approach
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EM Computational Approach
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Numeric |
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EM Determinism
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deterministic |
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Statistical Estimation of EM
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Model Checking Procedures Used
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Model Calibration Reported?
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Yes |
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Model Goodness of Fit Reported?
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Yes |
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Goodness of Fit (metric| value | unit)
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Model Operational Validation Reported?
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No |
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Model Uncertainty Analysis Reported?
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No |
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Model Sensitivity Analysis Reported?
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No |
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Model Sensitivity Analysis Include Interactions?
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Not applicable |
EM Locations, Environments, Ecology
Location of EM Application
Terrestrial location (Classification hierarchy: Continent > Country > U.S. State [United States only])
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Marine location (Classification hierarchy: Realm > Region > Province > Ecoregion)
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| None |
Centroid Lat/Long (Decimal Degree)
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Centroid Latitude
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44.15 |
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Centroid Longitude
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-122.2 |
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Centroid Datum
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WGS84 |
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Centroid Coordinates Status
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Provided |
Environments and Scales Modeled
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EM Environmental Sub-Class
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Rivers and Streams | Ground Water | Forests |
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Specific Environment Type
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400 to 500 year old forest dominated by Douglas-fir (Pseudotsuga menziesii), western hemlock (Tsuga heterophylla), and western red cedar (Thuja plicata). |
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EM Ecological Scale
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Ecological scale corresponds to the Environmental Sub-class |
Scale and taxa of organisms modeled
Scale of differentiation of organisms modeled
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EM Organismal Scale
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Not applicable |
Taxonomic level and name of organisms or groups identified
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| None Available |
EnviroAtlas URL
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| GAP Ecological Systems, Average Annual Precipitation, Average Annual Daily Potential Wind Energy |
EM Ecosystem Goods and Services (EGS) potentially modeled, by classification system
CICES v 4.3 - Common International Classification of Ecosystem Services (Section > Division > Group > Class)
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(Environmental Subclass > Ecological End-Product (EEP) > EEP Subclass > EEP Modifier)
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| None |
EM Variable Names (and Units)
Predictor
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Intermediate
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Intermediate (Computed) Variables (and Units)
view details (4 variables)
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Response
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Observed Response Variables (and Units)
view details (1 variable)
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Computed Response Variables (and Units)
view details (1 variable)
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