EcoService Models Library (ESML)
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EM: ACRU (Agricultural Catchments Research Unit), South Africa (EM-84)
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EM Identity and Description
EM Identification
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EM ID
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EM-84 |
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EM Short Name
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ACRU, South Africa |
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EM Full Name
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ACRU (Agricultural Catchments Research Unit), South Africa |
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EM Source or Collection
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None |
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EM Source Document ID
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271 |
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Document Author
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Egoh, B., Reyers, B., Rouget, M., Richardson, D.M., Le Maitre, D.C., and van Jaarsveld, A.S. |
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Document Year
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2008 |
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Document Title
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Mapping ecosystem services for planning and management |
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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
| Not applicable | |
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Contact Name
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Roland E Schulze |
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Contact Address
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School of Bioresources Engineering and Environmental Hydrology, University of Natal, South Africa |
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Contact Email
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schulzeR@nu.ac.za |
EM Description
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Summary Description
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AUTHOR'S DESCRIPTION (Doc ID 272): "ACRU is a daily timestep, physical conceptual and multipurpose model structured to simulate impacts of land cover/ use change. The model can output, inter alia, components of runoff, irrigation supply and demand, reservoir water budgets as well as sediment and crop yields." AUTHOR'S DESCRIPTION (Doc ID 271): "We define the range of ecosystem services as areas of meaningful supply, similar to a species’ range or area of occupancy. The term ‘‘hotspots’’ was proposed by Norman Myers in the 1980s and refers to areas of high species richness, endemism and/or threat and has been widely used to prioritise areas for biodiversity conservation. Similarly, this study suggests that hotspots for ecosystem services are areas of critical management importance for the service. Here the term ecosystem service hotspot is used to refer to areas which provide large proportions of a particular service, and do not include measures of threat or endemism…The total benefit to people of water supply is a function of both the quantity and quality with the ecosystem playing a key role in the latter. However, due to the lack of suitable national scale data on water quality for quantifying the service, runoff was used as an estimate of the benefit where runoff is the total water yield from a watershed including surface and subsurface flow. This assumes that runoff is positively correlated with quality, which is the case in South Africa (Allanson et al., 1990)…In South Africa, water resources are mapped in water management areas called catchments (vs. watersheds) where a catchment is defined as the area of land that is drained by a single river system, including its tributaries (DWAF, 2004). There are 1946 quaternary (4th order) catchments in South Africa, the smallest is 4800 ha and the average size is 65,000 ha. Schulze (1997) modelled annual runoff for each quaternary catchment. During modelling of runoff, he used rainfall data collected over a period of more than 30 years, as well as data on other climatic factors, soil characteristics and grassland as the land cover. In this study, median annual simulated runoff was used as a measure of surface water supply. The volume of runoff per quaternary catchment was calculated for surface water supply. The range (areas with runoff of 30 million m^3 or more) and hotspots (areas with runoff of 70 million m^3 or more) were defined using a combination of statistics and expert inputs due to a lack of published thresholds in the literature." |
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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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Semi-arid environment. Rainfall varies geographically from less than 50 to about 3000 mm per year (annual mean 450 mm). Soils are mostly very shallow with limited irrigation potential. |
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EM Scenario Drivers
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No scenarios presented |
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 |
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New or Pre-existing EM?
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Application of existing 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-272 ?Comment:Doc ID 272 was also used as a source document for this EM |
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EM ID for related EM
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None |
EM Modeling Approach
EM Relationship to Time
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EM Temporal Extent
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1950-1993 |
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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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Geopolitical |
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Spatial Extent Name
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South Africa |
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Spatial Extent Area (Magnitude)
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>1,000,000 km^2 |
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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Distributed by catchments with average size of 65,000 ha |
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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No |
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Model Goodness of Fit Reported?
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No |
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Goodness of Fit (metric| value | unit)
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None |
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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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-30 |
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Centroid Longitude
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25 |
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Centroid Datum
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WGS84 |
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Centroid Coordinates Status
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Estimated |
Environments and Scales Modeled
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EM Environmental Sub-Class
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Rivers and Streams | Ground Water | Terrestrial Environment (sub-classes not fully specified) |
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Specific Environment Type
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Not reported |
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EM Ecological Scale
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Ecological scale is coarser than that of 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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| Average Annual Precipitation |
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)
fegs2Help
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EM Variable Names (and Units)
Predictor
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Intermediate
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Intermediate (Computed) Variables (and Units)
view details (1 variable)
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Response
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Observed Response Variables (and Units)
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None |
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Computed Response Variables (and Units)
view details (3 variables)
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