EcoService Models Library (ESML)
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Compare EMs
Which comparison is best for me?EM Variables by Variable Role
One quick way to compare ecological models (EMs) is by comparing their variables. Predictor variables show what kinds of influences a model is able to account for, and what kinds of data it requires. Response variables show what information a model is capable of estimating.
This first comparison shows the names (and units) of each EM’s variables, side-by-side, sorted by variable role. Variable roles in ESML are as follows:
- Predictor Variables
- Time- or Space-Varying Variables
- Constants and Parameters
- Intermediate (Computed) Variables
- Response Variables
- Computed Response Variables
- Measured Response Variables
EM Variables by Category
A second way to use variables to compare EMs is by focusing on the kind of information each variable represents. The top-level categories in the ESML Variable Classification Hierarchy are as follows:
- Policy Regarding Use or Management of Ecosystem Resources
- Land Surface (or Water Body Bed) Cover, Use or Substrate
- Human Demographic Data
- Human-Produced Stressor or Enhancer of Ecosystem Goods and Services Production
- Ecosystem Attributes and Potential Supply of Ecosystem Goods and Services
- Non-monetary Indicators of Human Demand, Use or Benefit of Ecosystem Goods and Services
- Monetary Values
Besides understanding model similarities, sorting the variables for each EM by these 7 categories makes it easier to see if the compared models can be linked using similar variables. For example, if one model estimates an ecosystem attribute (in Category 5), such as water clarity, as a response variable, and a second model uses a similar attribute (also in Category 5) as a predictor of recreational use, the two models can potentially be used in tandem. This comparison makes it easier to spot potential model linkages.
All EM Descriptors
This selection allows a more detailed comparison of EMs by model characteristics other than their variables. The 50-or-so EM descriptors for each model are presented, side-by-side, in the following categories:
- EM Identity and Description
- EM Modeling Approach
- EM Locations, Environments, Ecology
- EM Ecosystem Goods and Services (EGS) potentially modeled, by classification system
EM Descriptors by Modeling Concepts
This feature guides the user through the use of the following seven concepts for comparing and selecting EMs:
- Conceptual Model
- Modeling Objective
- Modeling Context
- Potential for Model Linkage
- Feasibility of Model Use
- Model Certainty
- Model Structural Information
Though presented separately, these concepts are interdependent, and information presented under one concept may have relevance to other concepts as well.
EM Identity and Description
EM ID
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EM-97 | EM-945 |
EM Short Name
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AnnAGNPS, Kaskaskia River watershed, IL, USA | Air pollution removal by green roofs, Chicago, USA |
EM Full Name
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AnnAGNPS (Annualized Agricultural Non-Point Source Pollution Model), Kaskaskia River watershed, IL, USA | Air pollution removal by green roofs, Chigago, USA |
EM Source or Collection
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US EPA | None |
EM Source Document ID
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137 |
438 ?Comment:Document 439 is an additional source for this EM. |
Document Author
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Yuan, Y., Mehaffey, M. H., Lopez, R. D., Bingner, R. L., Bruins, R., Erickson, C. and Jackson, M. | Yang, J., Q. Yu and P. Gong |
Document Year
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2011 | 2008 |
Document Title
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AnnAGNPS model application for nitrogen loading assessment for the Future Midwest Landscape study | Quantifying air pollution removal by green roofs in Chicago |
Document Status
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Peer reviewed and published | Peer reviewed and published |
Comments on Status
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Published journal manuscript | Published journal manuscript |
EM ID
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EM-97 | EM-945 |
https://www.ars.usda.gov/southeast-area/oxford-ms/national-sedimentation-laboratory/watershed-physical-processes-research/docs/annagnps-pollutant-loading-model/ | Not applicable | |
Contact Name
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Yongping Yuan | Jun Yang |
Contact Address
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U.S. Environmental Protection Agency Office of Research and Development, Environmental Sciences Division, 944 East Harmon Ave., Las Vegas, NV 89119, USA | Department of Landscape Architecture and Horticulture, Temple University, 580 Meetinghouse Road, Ambler, PA 19002, USA. |
Contact Email
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yuan.yongping@epa.gov | juny@temple.edu |
EM ID
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EM-97 | EM-945 |
Summary Description
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AUTHORS' DESCRIPTION: "AnnAGNPS is an advanced simulation model developed by the USDA-ARS and Natural Resource Conservation Services (NRCS) to help evaluate watershed response to agricultural management practices. It is a continuous simulation, daily time step, pollutant loading model designed to simulate water, sediment and chemical movement from agricultural watersheds.p. 198" | ABSTRACT: "The level of air pollution removal by green roofs in Chicago was quantified using a dry deposition model. The result showed that a total of 1675 kg of air pollutants was removed by 19.8 ha of green roofs in one year with O3 accounting for 52% of the total, NO2 (27%), PM10 (14%), and SO2 (7%). The highest level of air pollution removal occurred in May and the lowest in February. The annual removal per hectare of green roof was 85 kg/ha/yr. The amount of pollutants removed would increase to 2046.89 metric tons if all rooftops in Chicago were covered with intensive green roofs. Although costly, the installation of green roofs could be justified in the long run if the environmental benefits were considered. The green roof can be used to supplement the use of urban trees in air pollution control, especially in situations where land and public funds are not readily available." |
Specific Policy or Decision Context Cited
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Not reported | None identified |
Biophysical Context
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Upper Mississipi River basin, elevation 142-194m, | No additional description provided |
EM Scenario Drivers
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Alternative agricultural land use (type and crop management (fertilizer application) towards a future biofuel target | No scenarios presented |
EM ID
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EM-97 | EM-945 |
Method Only, Application of Method or Model Run
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Method + Application | Method + Application |
New or Pre-existing EM?
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New or revised model | New or revised model |
Related EMs (for example, other versions or derivations of this EM) described in ESML
EM ID
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EM-97 | EM-945 |
Document ID for related EM
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Doc-142 | Doc-439 |
EM ID for related EM
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None | None |
EM Modeling Approach
EM ID
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EM-97 | EM-945 |
EM Temporal Extent
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1980-2006 | July 2006 to July 2007 |
EM Time Dependence
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time-stationary | time-dependent |
EM Time Reference (Future/Past)
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Not applicable | Not applicable |
EM Time Continuity
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Not applicable | discrete |
EM Temporal Grain Size Value
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Not applicable | 1 |
EM Temporal Grain Size Unit
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Not applicable | Month |
EM ID
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EM-97 | EM-945 |
Bounding Type
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Watershed/Catchment/HUC | Geopolitical |
Spatial Extent Name
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East Fork Kaskaskia River watershed basin | Chicago |
Spatial Extent Area (Magnitude)
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100-1000 km^2 | 100-1000 km^2 |
EM ID
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EM-97 | EM-945 |
EM Spatial Distribution
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spatially distributed (in at least some cases) | spatially distributed (in at least some cases) |
Spatial Grain Type
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length, for linear feature (e.g., stream mile) | other (specify), for irregular (e.g., stream reach, lake basin) |
Spatial Grain Size
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1 km^2 | plot (green roof) size |
EM ID
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EM-97 | EM-945 |
EM Computational Approach
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Numeric | Analytic |
EM Determinism
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deterministic | deterministic |
Statistical Estimation of EM
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EM ID
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EM-97 | EM-945 |
Model Calibration Reported?
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No | Unclear |
Model Goodness of Fit Reported?
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No | No |
Goodness of Fit (metric| value | unit)
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None | None |
Model Operational Validation Reported?
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Yes | No |
Model Uncertainty Analysis Reported?
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Yes | No |
Model Sensitivity Analysis Reported?
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Unclear | No |
Model Sensitivity Analysis Include Interactions?
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Not applicable | Not applicable |
EM Locations, Environments, Ecology
Terrestrial location (Classification hierarchy: Continent > Country > U.S. State [United States only])
EM-97 | EM-945 |
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Marine location (Classification hierarchy: Realm > Region > Province > Ecoregion)
EM-97 | EM-945 |
None | None |
Centroid Lat/Long (Decimal Degree)
EM ID
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EM-97 | EM-945 |
Centroid Latitude
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38.69 | 41.88 |
Centroid Longitude
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-89.1 | 87.65 |
Centroid Datum
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WGS84 | WGS84 |
Centroid Coordinates Status
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Provided | Provided |
EM ID
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EM-97 | EM-945 |
EM Environmental Sub-Class
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Agroecosystems | Created Greenspace |
Specific Environment Type
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Row crop agriculture in Kaskaskia river basin | urban green roofs |
EM Ecological Scale
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Ecological scale corresponds to the Environmental Sub-class | Ecological scale corresponds to the Environmental Sub-class |
Scale of differentiation of organisms modeled
EM ID
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EM-97 | EM-945 |
EM Organismal Scale
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Not applicable | Not applicable |
Taxonomic level and name of organisms or groups identified
EM-97 | EM-945 |
None Available | None Available |
EnviroAtlas URL
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)
EM-97 | EM-945 |
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<a target="_blank" rel="noopener noreferrer" href="https://www.epa.gov/eco-research/national-ecosystem-services-classification-system-nescs-plus">National Ecosystem Services Classification System (NESCS) Plus</a>
(Environmental Subclass > Ecological End-Product (EEP) > EEP Subclass > EEP Modifier)
EM-97 | EM-945 |
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None |