K.Fedra ‘97 Environmental modeling application domains anoverview of environmental topics and domains

K.Fedra ‘97 Modeling Domains Atmospheric systemsAtmospheric systems Hydrologic systemsHydrologic systems Land surface and subsurfaceLand surface and subsurface Biological and ecological systemsBiological and ecological systems Risks and hazardsRisks and hazards Technological systemsTechnological systems Management and policy modelsManagement and policy models Atmospheric systemsAtmospheric systems Hydrologic systemsHydrologic systems Land surface and subsurfaceLand surface and subsurface Biological and ecological systemsBiological and ecological systems Risks and hazardsRisks and hazards Technological systemsTechnological systems Management and policy modelsManagement and policy models

K.Fedra ‘97 Modeling Domains Atmospheric systems weather forecastingweather forecasting climate modelsclimate models air pollution: industry, traffic, domestic sources, accidental releases (hazardous substances)air pollution: industry, traffic, domestic sources, accidental releases (hazardous substances) Atmospheric systems weather forecastingweather forecasting climate modelsclimate models air pollution: industry, traffic, domestic sources, accidental releases (hazardous substances)air pollution: industry, traffic, domestic sources, accidental releases (hazardous substances)

K.Fedra ‘97 Modeling Domains Atmospheric systems weather forecastingweather forecasting climate modelsclimate models air pollution: industry, traffic, domestic sources, accidental releases (hazardous substances)air pollution: industry, traffic, domestic sources, accidental releases (hazardous substances) Atmospheric systems weather forecastingweather forecasting climate modelsclimate models air pollution: industry, traffic, domestic sources, accidental releases (hazardous substances)air pollution: industry, traffic, domestic sources, accidental releases (hazardous substances)

K.Fedra ‘97 Modeling Domains climate models: attempt to analyse the effects of greenhouse gas emissions on the global climate, global climate, energy balance, energy balance, sea level rise, sea level rise, water resources, water resources, vegetation and vegetation and wildlife, human wildlife, human health, etc. health, etc. climate models: attempt to analyse the effects of greenhouse gas emissions on the global climate, global climate, energy balance, energy balance, sea level rise, sea level rise, water resources, water resources, vegetation and vegetation and wildlife, human wildlife, human health, etc. health, etc.

K.Fedra ‘97 Modeling Domains climate models: global circulation models GCMs use a coarse resolution (between 3 to 6 deg. lat.long, 6 deg. lat.long, and a few vertical and a few vertical layers. layers. Comparison with Comparison with long-term climate long-term climate measurements measurements (30 year average (30 year average July temperatures). July temperatures). climate models: global circulation models GCMs use a coarse resolution (between 3 to 6 deg. lat.long, 6 deg. lat.long, and a few vertical and a few vertical layers. layers. Comparison with Comparison with long-term climate long-term climate measurements measurements (30 year average (30 year average July temperatures). July temperatures).

K.Fedra ‘97 Modeling Domains climate models: scenario assumptions usually are based on an increase in atmospheric CO 2 atmospheric CO 2 Example: UKMO Example: UKMO current CO 2 levels. current CO 2 levels. climate models: scenario assumptions usually are based on an increase in atmospheric CO 2 atmospheric CO 2 Example: UKMO Example: UKMO current CO 2 levels. current CO 2 levels.

K.Fedra ‘97 Modeling Domains climate models: scenario assumptions usually are based on an increase in atmospheric CO 2 atmospheric CO 2 Example: UKMO Example: UKMO doubled CO 2 levels. doubled CO 2 levels. climate models: scenario assumptions usually are based on an increase in atmospheric CO 2 atmospheric CO 2 Example: UKMO Example: UKMO doubled CO 2 levels. doubled CO 2 levels.

K.Fedra ‘97 Modeling Domains Air pollution modeling estimation of the source term:estimation of the source term: – rate and duration of release – source size, location –initial buoyancy and momentum Air pollution modeling estimation of the source term:estimation of the source term: – rate and duration of release – source size, location –initial buoyancy and momentum

K.Fedra ‘97 Modeling Domains estimation of the source term: embedded expert embedded expert system with an system with an object data base. object data base. estimation of the source term: embedded expert embedded expert system with an system with an object data base. object data base.

K.Fedra ‘97 Modeling Domains Air pollution modeling pollutant transportpollutant transport – advection by wind – turbulent and molecular diffusion – buoyancy effects (gases, particles) – deposition, chemical reactions, radioactive decay radioactive decay Air pollution modeling pollutant transportpollutant transport – advection by wind – turbulent and molecular diffusion – buoyancy effects (gases, particles) – deposition, chemical reactions, radioactive decay radioactive decay

K.Fedra ‘97 Modeling Domains pollutant pollutant transport transport Gaussian Gaussian 2D model 2D model (USEPA ISC) (USEPA ISC) pollutant pollutant transport transport Gaussian Gaussian 2D model 2D model (USEPA ISC) (USEPA ISC)

K.Fedra ‘97 Modeling Domains Air pollution modeling impacts and hazardsimpacts and hazards – human end environmental exposure – damage through explosion and fire – damage through chemical reactions (corrosion) (corrosion) Air pollution modeling impacts and hazardsimpacts and hazards – human end environmental exposure – damage through explosion and fire – damage through chemical reactions (corrosion) (corrosion)

K.Fedra ‘97 Modeling Domains impacts and hazards: estimated by overlays of overlays of long-term air long-term air quality values quality values (simulated with (simulated with ISC-LT model) ISC-LT model) and land use and land use or population or population maps. maps. impacts and hazards: estimated by overlays of overlays of long-term air long-term air quality values quality values (simulated with (simulated with ISC-LT model) ISC-LT model) and land use and land use or population or population maps. maps.

K.Fedra ‘97 Modeling Domains Hydrologic systems hydrological cycle, rainfall-runoffhydrological cycle, rainfall-runoff river flow and floodingriver flow and flooding water distribution and allocationwater distribution and allocation reservoir operationsreservoir operations water quality, eutrophication,water quality, eutrophication, waste allocation waste allocation groundwater systemsgroundwater systems Hydrologic systems hydrological cycle, rainfall-runoffhydrological cycle, rainfall-runoff river flow and floodingriver flow and flooding water distribution and allocationwater distribution and allocation reservoir operationsreservoir operations water quality, eutrophication,water quality, eutrophication, waste allocation waste allocation groundwater systemsgroundwater systems

K.Fedra ‘97 Modeling Domains hydrological cycle, rainfall-runoff

K.Fedra ‘97 Modeling Domains rainfall-runoff model: describes the outflow from a catchment as a function of basin data basin data (orography, soils (orography, soils land cover, land cover, drainage) drainage) precipitation, precipitation, temperature. temperature. rainfall-runoff model: describes the outflow from a catchment as a function of basin data basin data (orography, soils (orography, soils land cover, land cover, drainage) drainage) precipitation, precipitation, temperature. temperature.

K.Fedra ‘97 Modeling Domains rainfall-runoff model scenario of landuse change: scenario of landuse change: forested forested area 65% area 65% rainfall-runoff model scenario of landuse change: scenario of landuse change: forested forested area 65% area 65%

K.Fedra ‘97 Modeling Domains rainfall-runoff model scenario of landuse change: scenario of landuse change: forested forested area 0% area 0% rainfall-runoff model scenario of landuse change: scenario of landuse change: forested forested area 0% area 0%

K.Fedra ‘97 Modeling Domains water distribution and allocation dynamic network model with supply and demand nodes water distribution and allocation dynamic network model with supply and demand nodes

K.Fedra ‘97 Modeling Domains water distribution and allocation: generic generic network network with geo- with geo- referenced referenced nodes nodes water distribution and allocation: generic generic network network with geo- with geo- referenced referenced nodes nodes

K.Fedra ‘97 Modeling Domains water distribution and allocation: the network editor links to the GIS data bases water distribution and allocation: the network editor links to the GIS data bases

K.Fedra ‘97 Modeling Domains water quality, waste allocation: a dynamic a dynamic multi-segment multi-segment model (DO-BOD) model (DO-BOD) linked to the linked to the river network river network through nodes and through nodes and reaches. reaches. water quality, waste allocation: a dynamic a dynamic multi-segment multi-segment model (DO-BOD) model (DO-BOD) linked to the linked to the river network river network through nodes and through nodes and reaches. reaches.

K.Fedra ‘97 Modeling Domains Coastal waters and oceans currents and energy balance (climate modeling)currents and energy balance (climate modeling) coastal water qualitycoastal water quality nutrient cycles, eutrophicationnutrient cycles, eutrophication fisheries (sustainable yield)fisheries (sustainable yield) Coastal waters and oceans currents and energy balance (climate modeling)currents and energy balance (climate modeling) coastal water qualitycoastal water quality nutrient cycles, eutrophicationnutrient cycles, eutrophication fisheries (sustainable yield)fisheries (sustainable yield)

K.Fedra ‘97 Modeling Domains coastal water quality: simulation of ocean outfalls with a 2D vertically integrated flow and flow and transport transport particle particle tracking tracking model model coastal water quality: simulation of ocean outfalls with a 2D vertically integrated flow and flow and transport transport particle particle tracking tracking model model

K.Fedra ‘97 Modeling Domains Land surface and subsurface erosion, soil processeserosion, soil processes vegetation, land covervegetation, land cover groundwater (unsaturated and saturated zones, links to the hydrological domain)groundwater (unsaturated and saturated zones, links to the hydrological domain) Land surface and subsurface erosion, soil processeserosion, soil processes vegetation, land covervegetation, land cover groundwater (unsaturated and saturated zones, links to the hydrological domain)groundwater (unsaturated and saturated zones, links to the hydrological domain)

K.Fedra ‘97 Modeling Domains groundwater modeling: dynamic 2D (vertically integrated) flow and transport and transport model (finite model (finite element scheme) element scheme) Scenarios of Scenarios of landfills and landfills and aquifer aquifer restoration restoration groundwater modeling: dynamic 2D (vertically integrated) flow and transport and transport model (finite model (finite element scheme) element scheme) Scenarios of Scenarios of landfills and landfills and aquifer aquifer restoration restoration

K.Fedra ‘97 Modeling Domains Biological and ecological systems population models, predator-prey systems, food chainspopulation models, predator-prey systems, food chains ecosystem models (multi- compartment combining physical and biological elements)ecosystem models (multi- compartment combining physical and biological elements) Biological and ecological systems population models, predator-prey systems, food chainspopulation models, predator-prey systems, food chains ecosystem models (multi- compartment combining physical and biological elements)ecosystem models (multi- compartment combining physical and biological elements)

K.Fedra ‘97 Modeling Domains Agriculture and Forestry agricultural productionagricultural production livestock and grazing modelslivestock and grazing models forest models (stands, growth, yield, deforestation and reforestation)forest models (stands, growth, yield, deforestation and reforestation) Agriculture and Forestry agricultural productionagricultural production livestock and grazing modelslivestock and grazing models forest models (stands, growth, yield, deforestation and reforestation)forest models (stands, growth, yield, deforestation and reforestation)

K.Fedra ‘97 Modeling Domains Technological systems transportationtransportation energy systemsenergy systems industrial impactsindustrial impacts waste managementwaste management Technological systems transportationtransportation energy systemsenergy systems industrial impactsindustrial impacts waste managementwaste management

K.Fedra ‘97 Modeling Domains Risks and hazards floods and droughtsfloods and droughts erosion, desertificationerosion, desertification spills and accidental releasesspills and accidental releases epidemiological models (pests, infectious diseases)epidemiological models (pests, infectious diseases) Risks and hazards floods and droughtsfloods and droughts erosion, desertificationerosion, desertification spills and accidental releasesspills and accidental releases epidemiological models (pests, infectious diseases)epidemiological models (pests, infectious diseases)

K.Fedra ‘97 Modeling Domains spills and accidental releases: hazardous hazardous and toxic and toxic gas spills: gas spills: chemical chemical plants or plants or transportation transportation accidents accidents spills and accidental releases: hazardous hazardous and toxic and toxic gas spills: gas spills: chemical chemical plants or plants or transportation transportation accidents accidents

K.Fedra ‘97 Modeling Domains Management and policy models all of the above, but containing explicit representation of control and decision variablesall of the above, but containing explicit representation of control and decision variables economic evaluation economic evaluation  decision support systems Management and policy models all of the above, but containing explicit representation of control and decision variablesall of the above, but containing explicit representation of control and decision variables economic evaluation economic evaluation  decision support systems