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-275 ![]() |
EM-938 | EM-993 |
EM Short Name
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SWAT, Aixola watershed, Spain | OpenNSPECT v. 1.2 | Velma- 6PPD-Q concentrations, Seattle, WA |
EM Full Name
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SWAT (Soil and Water Assessment Tool), Aixola watershed, Spain | OpenNSPECT v. 1.2 | VELMA: 6PPD-Quinone stormwater concentrations , Seattle, Washington |
EM Source or Collection
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None | None | US EPA |
EM Source Document ID
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295 | 431 | 465 |
Document Author
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Zabaleta, A., Meaurio, M., Ruiz, E., and Antigüedad, I. | Eslinger, David L., H. Jamieson Carter, Matt Pendleton, Shan Burkhalter, Margaret Allen | Halama JJ, McKane RB, Barnhart BL, Pettus PP, Brookes AF, Adams AK, Gockel CK, Djang KS, Phan V, Chokshi SM, Graham JJ, Tian Z, Peter KT and Kolodziej,EP |
Document Year
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2014 | 2012 | 2024 |
Document Title
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Simulation climate change impact on runoff and sediment yield in a small watershed in the Basque Country, Northern Spain | “OpenNSPECT: The Open-source Nonpoint Source Pollution and Erosion Comparison Tool.” NOAA Office for Coastal Management, Charleston, South Carolina. Accessed (11/2022) at https://coast.noaa.gov/digitalcoast/tools/opennspect.html | Watershed analysis of urban stormwater contaminant 6PPD-Quinone hotspots and stream concentrations using a process-based ecohydrological model |
Document Status
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Peer reviewed and published | Peer reviewed and published | Peer reviewed and published |
Comments on Status
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Published journal manuscript | Webpage | Published journal manuscript |
EM ID
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EM-275 ![]() |
EM-938 | EM-993 |
http://swat.tamu.edu/software/arcswat/ | https://coast.noaa.gov/digitalcoast/tools/opennspect.html | Not reported | |
Contact Name
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Ane Zabaleta | Not reported | Jonathan Halama |
Contact Address
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Hydrogeology and Environment Group, Science and Technology Faculty, University of the Basque Country, 48940 Leioa, Basque Country (Spain) | NOAA Coastal Services Center, 2234 South Hobson Avenue Charleston, South Carolina 29405-2413 | U.S. Environmental Protection Agency, Corvallis, OR |
Contact Email
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ane.zabaleta@ehu.es | Not reported | Halama.Jonathan@epa.gov |
EM ID
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EM-275 ![]() |
EM-938 | EM-993 |
Summary Description
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ABSTRACT: "We explored the potential impact of climate change on runoff and sediment yield for the Aixola watershed using the Soil and Water Assessment Tool (SWAT). The model calibration (2007–2010) and validation (2005–2006) results were rated as satisfactory. Subsequently, simulations were run for four climate change model–scenario combinations based on two general circulation models (CGCM2 and ECHAM4) under two emissions scenarios (A2 and B2) from 2011 to 2100." AUTHOR'S DESCRIPTION: "The results were grouped into three consecutive 30-yr periods (2011-2040, 2041-2070, and 2071-2100) and compared with the values simulated for the baseline period (1961-1990)." | "This open-source version of the Nonpoint Source Pollution and Erosion Comparison Tool is used to investigate potential water quality impacts from climate change and development to other land uses. The downloadable tool is designed to be broadly applicable for coastal and noncoastal areas alike. Tool functions simulate erosion, pollution, and the accumulation from overland flow. OpenNSPECT uses spatial elevation data to calculate flow direction and flow accumulation throughout a watershed. To do this, land cover, precipitation, and soils data are processed to estimate runoff volume at both the local and watershed levels. Coefficients representing the contribution of each land cover class to the expected pollutant load are also applied to land cover data to approximate total pollutant loads. These coefficients are taken from published sources or can be derived from local water quality studies. The output layers display estimates of runoff volume, pollutant loads, pollutant concentration, and total sediment yield. Requires MapWindow GIS v.4.8.8 (open source software)" | ABSTRACT: "Coho salmon (Oncorhynchus kisutch) are highly sensitive to 6PPD-Quinone (6PPD-Q). Details of the hydrological and biogeochemical processes controlling spatial and temporal dynamics of 6PPD-Q fate and transport from points of deposition to receiving waters (e.g., streams, estuaries) are poorly understood. To understand the fate and transport of 6PPD and mechanisms leading to salmon mortality Visualizing Ecosystem Land Management Assessments (VELMA), an ecohydrological model developed by US Environmental Protection Agency (EPA), was enhanced to better understand and inform stormwater management planning by municipal, state, and federal partners seeking to reduce stormwater contaminant loads in urban streams draining to the Puget Sound National Estuary. This work focuses on the 5.5 km2 Longfellow Creek upper watershed (Seattle, Washington, United States), which has long exhibited high rates of acute urban runoff mortality syndrome in coho salmon. We present VELMA model results to elucidate these processes for the Longfellow Creek watershed across multiple scales–from 5-m grid cells to the entire watershed. Our results highlight hydrological and biogeochemical controls on 6PPD-Q flow paths, and hotspots within the watershed and its stormwater infrastructure, that ultimately impact contaminant transport to Longfellow Creek and Puget Sound. Simulated daily average 6PPD-Q and available observed 6PPD-Q peak in-stream grab sample concentrations (ng/L) corresponds within plus or minus 10 ng/L. Most importantly, VELMA’s high-resolution spatial and temporal analysis of 6PPD-Q hotspots provides a tool for prioritizing the locations, amounts, and types of green infrastructure that can most effectively reduce 6PPD-Q stream concentrations to levels protective of coho salmon and other aquatic species. " |
Specific Policy or Decision Context Cited
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Transport of solids for characterizing rivers in the European Water Framework Directive (WFD) | None identified | Not reported |
Biophysical Context
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The Aixola watershed drains into the Aixola reservoir, which has a cpacity of 2.73 x 10^6 m^3, and is used for water supply. The elevation ranges from 340 m at the outlet of the watershed to 750 m at the highest peak, with a mean elevation of 511 m a.s.l. Most slopes in the watershed are less than 30%. The region is characterized by a humid and temperate climate. The mean annual precipitation is about 1480 mm, distributed fairly evenly throughout the year.; the mean annual temperature is 12 degrees C; and the mean annual discharge is 600 mm (around 0.092 m^3 s^−1). Autochthonus vegetation is limited to small patches, and commercial foresty, mostly evergreen stands composed mainly of Pinus radiata (Monterey pine), occupies more than 80% of the watershed. The lithology is highly homogenous, with most of the bedrock (94%) consisting of impervious Upper Cretaceous Calcareous Flysch. The main types of soils are relatively deep cambisols and regosols, with depths ranging from 0.8 to 10 m and a silt-loam texture. During the 2003-2008 period, mean suspended sediment yield calculated for the watershed was 36 t km^-2. | No additional description provided | 6PPD deposition from vehicle tire wear particles. |
EM Scenario Drivers
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Four future climate change scenarios combining two IPCC SRES scenarios and two GCMs | No scenarios presented | N/A |
EM ID
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EM-275 ![]() |
EM-938 | EM-993 |
Method Only, Application of Method or Model Run
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Method + Application (multiple runs exist) View EM Runs | Method Only | Method + Application |
New or Pre-existing EM?
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Application of existing model | New or revised model | Application of existing model |
Related EMs (for example, other versions or derivations of this EM) described in ESML
EM ID
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EM-275 ![]() |
EM-938 | EM-993 |
Document ID for related EM
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None | None | Doc-366 | Doc-423 | Doc-430 |
EM ID for related EM
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None | EM-940 | None |
EM Modeling Approach
EM ID
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EM-275 ![]() |
EM-938 | EM-993 |
EM Temporal Extent
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1961-2100 | Not applicable | 9/2020-6/2021 |
EM Time Dependence
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time-dependent | time-stationary | time-dependent |
EM Time Reference (Future/Past)
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future time | Not applicable | past time |
EM Time Continuity
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continuous | Not applicable | discrete |
EM Temporal Grain Size Value
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Not applicable | Not applicable | 1 |
EM Temporal Grain Size Unit
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Not applicable | Not applicable | Day |
EM ID
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EM-275 ![]() |
EM-938 | EM-993 |
Bounding Type
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Watershed/Catchment/HUC | Not applicable | Watershed/Catchment/HUC |
Spatial Extent Name
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Aixola watershed | Not applicable | Longfellow creek |
Spatial Extent Area (Magnitude)
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1-10 km^2 | Not applicable | 1-10 km^2 |
EM ID
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EM-275 ![]() |
EM-938 | EM-993 |
EM Spatial Distribution
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spatially distributed (in at least some cases) | spatially distributed (in at least some cases) | spatially lumped (in all cases) |
Spatial Grain Type
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area, for pixel or radial feature | area, for pixel or radial feature | Not applicable |
Spatial Grain Size
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Average size 0.2 km^2 | 30 m | Not applicable |
EM ID
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EM-275 ![]() |
EM-938 | EM-993 |
EM Computational Approach
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Analytic | Analytic | Analytic |
EM Determinism
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deterministic | deterministic | deterministic |
Statistical Estimation of EM
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EM ID
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EM-275 ![]() |
EM-938 | EM-993 |
Model Calibration Reported?
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Yes | Not applicable | Yes |
Model Goodness of Fit Reported?
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No | Not applicable | No |
Goodness of Fit (metric| value | unit)
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None | None | None |
Model Operational Validation Reported?
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Yes | Not applicable | Yes |
Model Uncertainty Analysis Reported?
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No | Not applicable | Unclear |
Model Sensitivity Analysis Reported?
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Yes | Not applicable | Unclear |
Model Sensitivity Analysis Include Interactions?
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No | Not applicable | Not applicable |
EM Locations, Environments, Ecology
Terrestrial location (Classification hierarchy: Continent > Country > U.S. State [United States only])
EM-275 ![]() |
EM-938 | EM-993 |
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None |
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Marine location (Classification hierarchy: Realm > Region > Province > Ecoregion)
EM-275 ![]() |
EM-938 | EM-993 |
None | None | None |
Centroid Lat/Long (Decimal Degree)
EM ID
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EM-275 ![]() |
EM-938 | EM-993 |
Centroid Latitude
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43 | Not applicable | 47.55 |
Centroid Longitude
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-1 | Not applicable | 122.37 |
Centroid Datum
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WGS84 | Not applicable | None provided |
Centroid Coordinates Status
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Provided | Not applicable | Provided |
EM ID
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EM-275 ![]() |
EM-938 | EM-993 |
EM Environmental Sub-Class
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Rivers and Streams | Forests | Barren | Aquatic Environment (sub-classes not fully specified) | Near Coastal Marine and Estuarine | Terrestrial Environment (sub-classes not fully specified) | Rivers and Streams |
Specific Environment Type
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Forested watershed used for commercial forestry | Coastal and non-coastal | small stream |
EM Ecological Scale
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Ecological scale is finer than that of the Environmental Sub-class | Ecological scale is finer than that of the Environmental Sub-class | Ecological scale is finer than that of the Environmental Sub-class |
Scale of differentiation of organisms modeled
EM ID
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EM-275 ![]() |
EM-938 | EM-993 |
EM Organismal Scale
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Not applicable | Not applicable | Species |
Taxonomic level and name of organisms or groups identified
EM-275 ![]() |
EM-938 | EM-993 |
None Available | None Available |
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EnviroAtlas URL
EM-275 ![]() |
EM-938 | EM-993 |
National Hydrography Dataset Plus (NHD PlusV2), Average Annual Precipitation | Average Annual Precipitation | Carbon Storage by Tree Biomass |
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-275 ![]() |
EM-938 | EM-993 |
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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-275 ![]() |
EM-938 | EM-993 |
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None |
Comment:Model identifies toxicant concentrations relative to the known LC50 for coho juveniles which is 95ng/L (Spromber and Scholz, 2011; |