Marjan van den Belt and Roelof M Boumans

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The Development of an Integrated, Ecosystem Service Modeling Tool to support decision making in the Manawatu River Watershed. Marjan van den Belt and Roelof M Boumans. Site description of the Manawatu River:. Content: What are the Natural resources and what are the issues? - PowerPoint PPT Presentation

Transcript of Marjan van den Belt and Roelof M Boumans

The Development of an Integrated, Ecosystem Service Modeling Tool to

support decision making in the Manawatu River Watershed

Marjan van den Beltand

Roelof M Boumans

Site description of the Manawatu River:

• Content: What are the Natural resources and what are the issues?

• Space: Location Size and distribution of uses• Time: Pre, post and future settlement

dynamics (story)

Manawatu land cover: Pre- and Post Settlement

Source: Landcare Research. Complements of Anthony Cole

Methods

1.Scoping model 2.Research model3.Management model

How do Modelling Tools support Planning and Adaptive Management?

Source: van den Belt, 2009

Methods Integrated Freshwater Solutions (IFS)

1.Scoping: Mediated Modeling

2.Research model – FIT, Manawatu Model

3.Management model - MIMES

ScopingDefine scoping

Mediated Modelling for Integrated Freshwater Solutions:

A case study of the Manawatū Catchment

Research

• Define research• FIT• Manawatu River, New Zealand• Multi-scale Integrated Modelling for

Ecosystem Services (MIMES) to support science-policy dialogue:

Management Model

• Define Management model• Management options suggested by the IFS

process executed under the MIMES research model context.

Results

• IFS• Manawatu MIMES base case scenario• Manawatu MIMES simulating:

– IFS (stakeholder dialogue based) scenarios: • erosion control, • nutrient management, • riparian planting

– Contribution of Economic and Ecosystem Services supplied and requested, when following the market or non-market values.

IFS – value context• Overall participants believed sedimentation, nutrient runoff,

wastewater discharge and aquatic habitat were the main issues. • On the 16 of March 2011 these issues were verified by an

expert science panel who discuss the underlying scientific questions.– Verification of the base case scenario. – Validation through calibration of model output.– Identifying Probability ranges for the non-controlable factors. – Identifying controllable factors of use in management scenarios.

• Value context of issues (MRLF Accord Goals): Mana and Pride, Human Health, Economic Prosperity, Direct utility.

IFS-MM overview

Ecosystem Service Valuationstarting framework

Natural Capital Ecosystem Services

ValuesActions

Ecosystem functions: The capacity of natural processes and components to provide goods and services that satisfy human needs. (de Groot, 1992)Ecosystem Services: Valued Ecosystem Functions.

R.S. de Groot et al. / Ecological Economics 41 (2002) 393–408

IFS-MM ResultLand Use / Land CoverForest, Wetland, Riparian, River/Lake, Urban, Dairy, Sheep&Beef, Horticulture

Ecosystem ServicesFunctioning index (slider)

ValuesCost of actionsBenefit Transferred ESStakeholder dialogue

ActionsErosion control (SLUI)Nutrient managementRiparian PlantingWaste Water TreatmentRestoration

Impacts of Erosion, Nutrient runoff and habitat loss

Natural Capital (and changes in land use)•Forest•Wetlands•Rivers and Streams •Estuary and coast •Dairy•Beef & Sheep•Horticulture•Urban

Ecosystem Services•Storm protection•Food•Habitat provision•Nutrient cycling•Climate regulation and carbon cycling•Recreation

(E)Valuation•Stakeholder participation•National, regional and local funding sources for actions.•CBA, EIA and CEA.•Cultural and spiritual values•Perceived or non-perceived benefits •Changes over time and time delays

Action Plan•Fencing of Streams and riparian planting•SLUI and reforestation•Wetland restoration•Nitrogen management and herd homesPoint source reduction

Impacts •Erosion and sedimentation•Nutrient runoff and eutrophication•Aquatic habitat

IFS scoping model integrates important drivers, as identified by stakeholders

• Erosion and sedimentation• Nitrogen runoff/leaking and eutrophication• Habitat and biodiversity

Sediment loading in tonnes per year

1990 2000 2013 2020 2030 2040

5 Million

3 Million

1 Million

Sediment loading in tonnes per year

1990 2000 2013 2020 2030 2040

5 Million

3 Million

1 Million

Sediment loading in tonnes per year

1990 2000 2013 2020 2030 2040

5 Million

3 Million

1 Million

blue line- 1: WITH SLUIred line -2: Without SLUI pink line -3: Reaching SLUI goals in 2020 instead of 2030

Nitrogen loading in tonnes per year

1990 2000 2013 2020 2030 2040

10,000

5,000

0

Impact of SLUI on Nitrogen loading smaller than on Sediment loading

Nitrogen loading in tonnes per year

1990 2000 2013 2020 2030 2040

10,000

5,000

0

blue line- 1: base line under business-as-usual

Nitrogen loading in tonnes per year

1990 2000 2013 2020 2030 2040

10,000

5,000

0

Blue line- 1: base line under business-as-usualRed line- 2: stock exclusion $300,000

Nitrogen loading in tonnes per year

1990 2000 2013 2020 2030 2040

10,000

5,000

0

Blue 1: Base line under business-as-usualRed 2: Full effluent managementPink 3: Stock exclusion / fencing ($300,000)Green 4: Herd homes (40% N reduction)

Nitrogen loading in tonnes per year

1990 2000 2013 2020 2030 2040

10,000

5,000

0

Blue 1: Base line under business-as-usualRed 2: Currently funded and implemented Non-Point Source measuresPink: 25% reduction in Point Source waste water

Phosphorus loading in tonnes per year

1990 2000 2013 2020 2030 2040

300

150

0

Blue 1: Base line under business-as-usualRed 2: 50% reduction in Point Source waste water

Cows per hectare (1990 – 2040)

IFS management scenarios

MIMES boundaries

• Manawatu is modelled as a closed system• 49 sub-watersheds• Daily time step + yearly aggregated outputs• Time extent 1995 – 2011 (weather data)• 2012 – 2100 (climate change scenarios)

Scenario plan

Human-Environment Interaction Matrix – Full systems accounting

Supply of ES from LandCover

• Forest gives a mix of ES

Production Econ Goods and Services

• Cobb Douglas including ES from Land.• Land use use change, changes distribution of

ES production• Distribution of ES drives production of Econ

Goods and Services.• Production of Econ GS creates externalities by

changing the ability of landcover to produce ES.

Scenarios

1) Erosion control 2) Nutrient Management3) Riparian planting4) Wastewater management5) Restoration of Forest and wetland

Manawatu MIMES - Qualitative overview

CatchmentsCatchments

Hydrological model

Land cover

Demographics coefficients

Land use

Demographics:Built capital

Water routing

Land environments

Land cover

Land use:N loadingWater

Land use

Demographics: population effect

Rain

Ecosystem goods and services

model Conversion

EcosystemServices

Water quality standards

Catchments

Manawatu MIMES – Data base links

CatchmentsCatchments

WATYIELD

The New Zealand Land Cover Database

Demographics By ANZSIC 2006 – industry classification

Land use change as emergent behavior

Input for local investment scenarios

FENZ

13 underlying climate, landform and soil variables

8 Land covers

7 land uses

7x7 Land use change

Demographics: 1 Population effect2 Business as Usual3 Restoration

cliflo@niwa.co.nz

Dynamics in goods and

service trade-offs

Emergent dynamics in EcosystemServices (see output slide 17)

Resource Management Act 1991

Freshwater Ecosystems of New Zealand (FENZ GIS)

Land Environments of New Zealand (LENZ)Database

8 user groups

Input for land use change scenarios

Simulated flooding – base case

Emergent dynamics of 8 (of X potential) Ecosystem Services

The Management Modelbased on IFS (stakeholder generated)

Watershed Scenario Analyses

Manawatu MIMES – Data base links – Best Management Practices scenarios

CatchmentsCatchments

WATYIELD

The New Zealand Land Cover Database

Demographics By ANZSIC 2006 – industry classification

Land use change as emergent behavior

Input for local investment scenarios

FENZ

13 underlying climate, landform and soil variables

8 Land covers

7 land uses

7x7 Land use change

Demographics: 1 Population effect2 Business as Usual3 Restoration

cliflo@niwa.co.nz

Dynamics in goods and

service trade-offs

Emergent dynamics in EcosystemServices (see output slide 17)

Resource Management Act 1991

Freshwater Ecosystems of New Zealand (FENZ GIS)

Land Environments of New Zealand (LENZ)Database

8 user groups

Input for land use change scenarios

Parameters derived from LENZ

Level 2 LENZ Classification1 F1`2 C13 NULL_4 H15 B16 F77 P48 J49 C210 C311 P812 F413 I2

SLUI

Manawatu MIMES – Data base links – Land Use change scenarios

CatchmentsCatchments

WATYIELD

The New Zealand Land Cover Database

Demographics By ANZSIC 2006 – industry classification

Land use change as emergent behavior

Input for local investment scenarios

FENZ

13 underlying climate, landform and soil variables

8 Land covers

7 land uses

7x7 Land use change

Demographics: 1 Population effect2 Business as Usual3 Restoration

cliflo@niwa.co.nz

Dynamics in goods and

service trade-offs

Emergent dynamics in EcosystemServices (see output slide 17)

Resource Management Act 1991

Freshwater Ecosystems of New Zealand (FENZ GIS)

Land Environments of New Zealand (LENZ)Database

8 user groups

Input for land use change scenarios

IFS trends in Land use change Scenarios

Manawatu MIMES – Data base links

CatchmentsCatchments

WATYIELD

The New Zealand Land Cover Database

Demographics By ANZSIC 2006 – industry classification

Land use change as emergent behavior

Input for local investment scenarios

FENZ

13 underlying climate, landform and soil variables

8 Land covers

7 land uses

7x7 Land use change

Demographics: 1 Population effect2 Business as Usual3 Restoration

cliflo@niwa.co.nz

Dynamics in goods and

service trade-offs

Emergent dynamics in EcosystemServices (see output slide 17)

Resource Management Act 1991

Freshwater Ecosystems of New Zealand (FENZ GIS)

Land Environments of New Zealand (LENZ)Database

8 user groups

Input for land use change scenarios

Hydrological RoutingData uploaded in “connect to” informsCond3 on what watershed (here) is connected to what watershed (there).Only those Surface water flow will be calculated for where watershed are connected (cond3 is true)Flows are based on water head differences and the speed of the water flow through the watersheds .The hydrological routing routine doublesto also account for Nitrogen exchanges among the watersheds

Manawatu MIMES – Data base links

CatchmentsCatchments

WATYIELD

The New Zealand Land Cover Database

Demographics By ANZSIC 2006 – industry classification

Land use change as emergent behavior

Input for local investment scenarios

FENZ

13 underlying climate, landform and soil variables

8 Land covers

7 land uses

7x7 Land use change

Demographics: 1 Population effect2 Business as Usual3 Restoration

cliflo@niwa.co.nz

Dynamics in goods and

service trade-offs

Emergent dynamics in EcosystemServices (see output slide 17)

Resource Management Act 1991

Freshwater Ecosystems of New Zealand (FENZ GIS)

Land Environments of New Zealand (LENZ)Database

8 user groups

Input for land use change scenarios

1) Needs and wants by demographics for Labor, Capital, economic and ecological services

IFS scenarios:1) Link to Environmental Impact. Days in watershed 3) Sector growth rate relative to economic prosperity

Demographics by economic sector characteristics

The Management Modelbased on IFS (stakeholder generated)

Watershed Scenario Analyses

Defining the interface to communicate scenarios; Organizing Model output spatial displays variables (25 variables for 49 sub-catchments)1) Upload of watershed polygon coordinates2) Inclusion of output variables to display3) Inclusion of graphical input variables

Zooming in on a sub-catchment: Model output graphical displays

User control parameter to be used in the user interface to allow a choice for the first year for analyses.

Based on the IFs model Year also informs the growth rate of the Dairy industry

Functionality to sample year relevant time series data. In this case there is a choice between measured data at Wanganui

Spriggens Park (choice scenario) or rainfall predicted by one of the GCC scenarios (Base scenario). Science – Policy

communication

The Management Modelbased on IFS (stakeholder generated)

Watershed Scenario Analyses

Spatial Dynamic Simulations

Characterization of the WatershedLENZ attributes are weighted by Land Environment distribution in the subwatershed. Further weighting occurs when attributes are landcover; landuse within landcover; or demographics within landuse within landcover specific.Scenarios on Best management practices specific to the land environments (water requirements and Nitrogen loading) can be specified by variations to the demographics within landuse within landcover within Land Environment attributes.

HydrologyThe Hydrology based on WATYIELD simulates the changes in water storage in the soils, the ground water and the surface water . Added to the hydrology are the dynamics in Dissolved Inorganic Nitrogen to monitor the effects of changes in nutrient loadings to facilitate the IFS loading scenarios:1) SLUI, 2) Riparian planting, 3) wastewater management,4) Urban Stormwater Management, 5) Restoration of Forest and wetland, 6) Sustainable Farm Nutrient

Management

Similar dynamics on Suspended sediments and E coli are not yet implemented

Establish watershed flooding conditions

The water level submodel in the hydrology establishes the hypsometrical curve of the watershed and is used to flag flooding conditions.

Watershed wide estimates in the availability of ecosystem services.

Translation of what is produced by the ecosystem to what is demanded by the demographic groups

Demographics and economic efficiency of ecosystem service users in the sub watersheds.

This sub model attributes people and what they do to the sub-watershed.This sub-model is to facilitate scenarios for local capital investments (e.g. expending, or decreasing dairy farming in a sub watershed). The sub model calculates the efficiency of each of the sectors based on capital investment and services available (to include those of the ecosystems). It specifies the number of people in the watershed associated with each of the economic sectors. The number of people together with the land environment specific effect on the N loading and waters use determines the ecological impacts

Land use land cover changesThe watershed submodel to accomodate the land cover change simulations. While ecosystem services are associated with the landcovers, they are the landuses that are changed with population pressures and economic investments.

The Scenario variables: Conditions for riparian restoration and, Restoration to reduce erosion from highlands are introduced for place based planning.

Landcover Change User Interface

Design of the SLUI scenarios in IFS

• Nr of Highly erodible farms targeted by year

• Expedient targeting• What SLUI action means:

– Reduction in Sheep and Beef N Loads

– Reduction in Sheep and Beef SS loads

Design of SLUI Scenarios in Spatial IFs

• Highly erodible farms are Sheep and beef investments in watersheds with land environments characterized as highly erodible.

• Stategies for Expedient targeting can be designed to implement SLUI in those subwatersheds charaterized by highly erodable land environment and high concentrations of Sheep and beef production

• What SLUI action means:– Land cover change from pasture to forests on the steep slopes, for the

trade-off from grazing to Ecosystem Service benefits associated with Forests

– Reduction in Sheep and Beef N and SS Loads• How is SLUI best implemented?

Design of the Farm Nutrient mgt improvement

IFSThe trade-offs between yes or no herd homes or

stock exclusions versus nutrient loadings and economic loss (gain)

Manawatu MIMES: The trade-offs between yes or no herd homes or stock exclusions in environmental sensitive areas (hot spot approach) versus nutrient loadings and economic loss (gain)

Design of the Town and Industrial Waste water Nutrient removal

• IFs watershed wide• Spatial IFs Time and space specific based on Land

Environments and spatial context to neighboring watersheds.– Water requirements and Nutrient loadings are specific to

Demographic groups (Urbanites, farmers, Iwi etc) within a land Use (Pasture, cropland residential, conservation etc) within a landcover (Forest, Grassland) within a Land Environment (Steep slopes, fertile soils etc).

– Failure to limit nutrient removal will record as impact water quality changes in watersheds down stream.

Design of the Restoration Scenarios

• IFs : Riparian planting, wetlands, Infiltration areas

LocationsBiosphere

Earth Surfaces

NutrientCycling

Hydrosphere Lithosphere Atmosphere

Anthroposphere

Cultures

Biodiversity

EcosystemServices

Water by

Reservoir

Geological Carbon

Ores

Earth Energy

Gasses

ExchangesBetweenLocations

Social Capital

Human Capital

Economie

MIMES organization and Interaction Matrix

Ontologies

Ecosystems/

Land cover

Cropland

Desert

Forest

Grassland

Lakes Rivers

Urban

Wetland

Demographic Groups /Econ Sectors and Quality of Life MIX

MiningForestryFisheriesAgricultureManufacturingTourismResearch/EducationHouseholdsTransportation In-Export

Services (7)Aesthetics

Biological regulation

Climate regulation

Cultural heritage

Genetic

Inorganic resources

Natural Hazard Mitigation

Navigational surface

Organic resources

Shelter

Soil retention

Spiritual Artistic Inspiration

Waste absorption

Water quality

Water quantity

Scenarios

1) Erosion control 2) Nutrient Management3) Riparian planting4) Wastewater management5) Restoration of Forest and wetland

Scenarios roel – exogenous drivers

• Land use changes (BAU + population of people attracted by business, more urban areas)

• Decision point for restoration rates for whole watershed

Scenarios Roel endogenous per sub-catchment

• IF $ for erosion control allocated to highly erodable areas THEN future map shows 1. $ spent in watersheds 2a. land cover effect of change from pasture to forest (in ES) 2b. Land use effect in total animals per sub-catchment (sheep units). 3. effect on farm income per sub-watershed 4. effect on non-market values.

Out put variables for display

The Manuwatu MIMES User Interface for Scenario ModelingThe Introduction Page

Interface for the design of Erosion Control scenarios

Interface for the Design of Nutrient Management Scenarios

Interface for the Design of Fencing and Riparian Planting Scenarios

Interface for the Design of Waste Water Treatment Scenarios

Interface for the Design of Scenarios concerning the Investment into Natural Capital