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-321 ![]() |
EM-968 |
EM Short Name
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Erosion prevention by vegetation, Portel, Portugal | EPA Stormwater Manamgement Model |
EM Full Name
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Soil erosion prevention provided by vegetation cover, Portel municipality, Portugal | Storm Water Management Model User's Manual Version 5.2 |
EM Source or Collection
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EU Biodiversity Action 5 | US EPA |
EM Source Document ID
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281 | 452 |
Document Author
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Guerra, C.A., Pinto-Correia, T., Metzger, M.J. | Rossman, L. A., M., Simon |
Document Year
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2014 | 2022 |
Document Title
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Mapping soil erosion prevention using an ecosystem service modeling framework for integrated land management and policy | Storm Water Management Model User's Manual Version 5.2 |
Document Status
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Peer reviewed and published | Not peer reviewed but is published (explain in Comment) |
Comments on Status
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Published journal manuscript | Published EPA report |
EM ID
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EM-321 ![]() |
EM-968 |
Not applicable | https://www.epa.gov/water-research/storm-water-management-model-swmm | |
Contact Name
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Carlos A. Guerra | David Burden |
Contact Address
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Instituto de Ciências Agrárias e Ambientais Mediterrânicas, Universidade de Évora, Pólo da Mitra, Apartado 94, 7002-554 Évora, Portugal | U.S. EPA Research Center for Environmental Solutions and Emergency Response (CESER) Mail Drop: 314 P.O. Box #1198 Ada, OK 74821-1198 |
Contact Email
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cguerra@uevora.pt | burden.david@epa.gov |
EM ID
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EM-321 ![]() |
EM-968 |
Summary Description
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ABSTRACT: "We present an integrative conceptual framework to estimate the provision of soil erosion prevention (SEP) by combining the structural impact of soil erosion and the social–ecological processes that allow for its mitigation. The framework was tested and illustrated in the Portel municipality in Southern Portugal, a Mediterranean silvo-pastoral system that is prone to desertification and soil degradation. The results show a clear difference in the spatial and temporal distribution of the capacity for ecosystem service provision and the actual ecosystem service provision." AUTHOR'S DESCRIPTION: "To begin assessing the contribution of SEP we need to identify the structural impact of soil erosion, that is, the erosion that would occur when vegetation is absent and therefore no ES is provided. It determines the potential soil erosion in a given place and time and is related to rainfall erosivity (that is, the erosive potential of rainfall), soil erodibility (as a characteristic of the soil type) and local topography. Although external drivers can have an effect on these variables (for example, climate change), they are less prone to be changed directly by human action. The actual ES provision reduces the total amount of structural impact, and we define the remaining impact as the ES mitigated impact. We can then define the capacity for ES provision as a key component to determine the fraction of the structural impact that is mitigated…Following the conceptual outline, we will estimate the SEP provided by vegetation cover using an adaptation of the Universal Soil Loss Equation (USLE)." |
EPA Storm Water Management Model (SWMM) is a dynamic rainfall-runoff simulation model used for single event or long-term (continuous) simulation of runoff quantity and quality from primarily urban areas. The runoff component of SWMM operates on a collection of subcatchment areas that receive precipitation and generate runoff and pollutant loads. The routing portion of SWMM transports this runoff through a system of pipes, channels, storage/treatment devices, pumps, and regulators. SWMM tracks the quantity and quality of runoff generated within each subcatchment, and the flow rate, flow depth, and quality of water in each pipe and channel during a simulation period comprised of multiple time steps. Running under Windows, SWMM 5 provides an integrated environment for editing study area input data, running hydrologic, hydraulic and water quality simulations, and viewing the results in a variety of formats. These include color coded drainage area and conveyance system maps, time series graphs and tables, profile plots, and statistical frequency analyses. This user’s manual describes in detail how to run SWMM 5.2. It includes instructions on how to build a drainage system model, how to set various simulation options, and how to view results in a variety of formats. It also describes the different types of files used by SWMM and provides useful tables of parameter values. Detailed descriptions of the theory behind SWMM 5 and the numerical methods it employs can be found in a separate set of reference manuals. ?Comment:The variables used for this ESML entry were derived from the quick tutorial section of the SWMM manual. |
Specific Policy or Decision Context Cited
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None identified | NA |
Biophysical Context
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Open savannah-like forest of cork (Quercus suber) and holm (Quercus ilex) oaks, with trees of different ages randomly dispersed in changing densities, and pastures in the under cover. The pastures are mostly natural in a mosaic with patches of shrubs, which differ in size and the distribution depends mainly on the grazing intensity. Shallow, poor soils are prone to erosion, especially in areas with high grazing pressure. | NA |
EM Scenario Drivers
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Different land management practices as represented by the comparison of different grazing intensities (i.e., livestock densities) in the whole study area and in three Civil Parishes within the study area | NA |
EM ID
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EM-321 ![]() |
EM-968 |
Method Only, Application of Method or Model Run
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Method + Application (multiple runs exist) View EM Runs | Method Only |
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-321 ![]() |
EM-968 |
Document ID for related EM
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Doc-282 | Doc-283 | Doc-284 | Doc-285 | None |
EM ID for related EM
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None | EM-971 |
EM Modeling Approach
EM ID
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EM-321 ![]() |
EM-968 |
EM Temporal Extent
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January to December 2003 | Not applicable |
EM Time Dependence
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time-dependent | time-dependent |
EM Time Reference (Future/Past)
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future time | both |
EM Time Continuity
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discrete | continuous |
EM Temporal Grain Size Value
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1 | Not applicable |
EM Temporal Grain Size Unit
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Month | Not applicable |
EM ID
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EM-321 ![]() |
EM-968 |
Bounding Type
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Geopolitical | No location (no locational reference given) |
Spatial Extent Name
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Portel municipality | Not applicable |
Spatial Extent Area (Magnitude)
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100-1000 km^2 | Not applicable |
EM ID
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EM-321 ![]() |
EM-968 |
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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area, for pixel or radial feature | area, for pixel or radial feature |
Spatial Grain Size
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250 m x 250 m | mm |
EM ID
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EM-321 ![]() |
EM-968 |
EM Computational Approach
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Analytic | Analytic |
EM Determinism
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deterministic | deterministic |
Statistical Estimation of EM
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EM ID
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EM-321 ![]() |
EM-968 |
Model Calibration Reported?
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No | Not applicable |
Model Goodness of Fit Reported?
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No | Not applicable |
Goodness of Fit (metric| value | unit)
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None | None |
Model Operational Validation Reported?
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No | Not applicable |
Model Uncertainty Analysis Reported?
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No | Not applicable |
Model Sensitivity Analysis Reported?
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No | Not applicable |
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-321 ![]() |
EM-968 |
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None |
Marine location (Classification hierarchy: Realm > Region > Province > Ecoregion)
EM-321 ![]() |
EM-968 |
None | None |
Centroid Lat/Long (Decimal Degree)
EM ID
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EM-321 ![]() |
EM-968 |
Centroid Latitude
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38.3 | Not applicable |
Centroid Longitude
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-7.7 | Not applicable |
Centroid Datum
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WGS84 | Not applicable |
Centroid Coordinates Status
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Estimated | Not applicable |
EM ID
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EM-321 ![]() |
EM-968 |
EM Environmental Sub-Class
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Terrestrial Environment (sub-classes not fully specified) | Forests | Agroecosystems | Scrubland/Shrubland | Terrestrial Environment (sub-classes not fully specified) |
Specific Environment Type
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Silvo-pastoral system | User-defined catchments |
EM Ecological Scale
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Ecological scale is coarser than that of the Environmental Sub-class | Other or unclear (comment) |
Scale of differentiation of organisms modeled
EM ID
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EM-321 ![]() |
EM-968 |
EM Organismal Scale
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Not applicable | Not applicable |
Taxonomic level and name of organisms or groups identified
EM-321 ![]() |
EM-968 |
None Available | None Available |
EnviroAtlas URL
EM-321 ![]() |
EM-968 |
Average Annual Precipitation | None Available |
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-321 ![]() |
EM-968 |
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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-321 ![]() |
EM-968 |
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