Ecological dimensions in the saf
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SPICOSA Training Support Pack. Ecological dimensions in the SAF. Why do we need the ecological dimension? Methodology and data inputs Outcomes of a study site application (SSA) Management implications. Presentation outline. Material produced by Jakob Walve ([email protected]).

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Ecological dimensions in the saf

SPICOSA Training Support Pack

Ecological dimensions in the SAF

Why do we need the ecological dimension?

Methodology and data inputs

Outcomes of a study site application (SSA)

Management implications

Presentation outline

Material produced by Jakob Walve ([email protected])


Why do we need the ecological dimension

SPICOSA Training Support Pack

Why do we need the ecological dimension?

- There is an environmental problem to be solved! In SPICOSA, problems related to e.g. eutrophication and declining fish stocks are addressed.

- We want to achieve sustainable development, with acceptable environmental impact and status, e.g. according to Water Framework Directive. In SPICOSA, e.g. the development of fisheries and mussel farming are explored.

Material produced by <name> <email > <organisation logo>


Methodology systems thinking is the key

SPICOSA Training Support Pack

Methodology: Systems thinking is the key

Issue resolution: What is the problem? What are the objectives?

System definition: System boundaries? Key ecological processes?

Data needs / availability: What data are available or can be made available? What will available data allow or restrict? What new data can be collected? -The main idea is to make better use of existing data.

Conceptual Model: description of relationships between system components, from expert knowledge. Forms the basis for the problem solving through numerical modelling. Often has to be simplified: problem scaling.

Formulation and Appraisal, i.e. Mathematical and Numerical modelling: Inputs from data are modulated by ecological transformation processes, described by mechanistic (process) or empirical (relational) knowledge, in a modelling software. Usually the objective is to determine the response of a few system properties to certain management options. Important steps are Calibration and Validation of the model using data from the studied system.


Ecological dimensions in the saf

SPICOSA Training Support Pack

Issue resolution and System Definition

Example of Policy Issue and important ecological processes illustrated with Overall Conceptual model:

Loch Fyne, a 60 km long fiordic sea loch on the west coast of Scotland

Example Policy Issue “Managing Loch Fyne so as to Maximize the Value of Ecosystem Goods and Services to the Local Economy”

From SPICOSA Deliverable D.3.2. SAF Protocol on CZ System Design (fig. 3.1)


Methodology systems thinking is the key1

SPICOSA Training Support Pack

Methodology: Systems thinking is the key

Conceptual Model: an example

Example of ”fuzzy” conceptual model of phytoplankton growth

The ”fuzzy” model has to be made more precise by identifying and distinguishing state variables (stocks), fluxes and their controls

From SPICOSA Deliverable D.3.2. SAF Protocol on CZ System Design


Methodology systems thinking is the key2

SPICOSA Training Support Pack

Methodology: Systems thinking is the key

Conceptual Model: example expanded to include a feedback loop

The conceptual model has been expanded to include a feedback loop: the recirculation of nutrients from grazers

From SPICOSA Deliverable D.3.2. SAF Protocol on CZ System Design


Methodology systems thinking is the key3

SPICOSA Training Support Pack

Methodology: Systems thinking is the key

Conceptual Model: expanded to include boundary conditions

The conceptual model is expanded to include boundary conditions

The boundary condition will be quantified inside a ‘convertor’ rather

than as a stock – because boundary conditions are outside the dynamic

model and should not be changed as a result of what happens inside the

model. Notice also that there has to be one exchange flow for every stock

in the model.

From SPICOSA Deliverable D.3.2. SAF Protocol on CZ System Design


Methodology systems thinking is the key4

SPICOSA Training Support Pack

Methodology: Systems thinking is the key

Data needs/availability: identifying the data needs in the conceptual model for phytoplankton

Identifying data needs in the conceptual model for phytoplankton.

In addition to this, there is need for calibration and validation data

From SPICOSA Deliverable D.3.2. SAF Protocol on CZ System Design


Methodology systems thinking is the key5

SPICOSA Training Support Pack

Methodology: Systems thinking is the key

Conceptual Model:simplified version

The model often has to be or can be simplified.

The model should be made as simple as possible, but still has to capture the essential dynamics of the system in relation to the objectives of the model

From SPICOSA Deliverable D.3.2. SAF Protocol on CZ System Design (fig. 8.2)


Methodology applied in a case study

SPICOSA Training Support Pack

Methodology applied in a case study

Issue resolution: Example Himmerfjärden SSA, Sweden

Problems: Reduced value due to relatively low water transparency, and loss of macrophytes. There is risk for cyanobacterial blooms if nitrogen loads are reduced. There is a general need to meet WFD requirements (ecological statsus is moderate to poor according to present classification). Export of nutrients to the Baltic Sea.

Specific ecological questions: What can be achieved by different measures (STP, agriculture). What will be the effect of improvements in the open Baltic Sea? What is the effect of moved STP discharge point (potentially affecting availability of nutrients in different parts of the estuary)?

Himmerfjärden: A brackish estuary in the Baltic Sea.

  • Water area 232 km2

  • Mean depth 17 m

  • Maximum depth ~52 m

  • Salinity 4-7

  • Freshwater from 9 brooks and diffuse runoff 10 m3 s-1

  • From Lake Mälaren 7 m3 s-1

  • From large sewage treatment plant (STP) 1.5 m3 s-1

10 km

Open Baltic Sea


Ecological dimensions in the saf

The model boundaries were defined according to the existing divisions into drainage basins.

System Definition: Example Himmerfjärden SSA, Sweden

We chose this area to simplify the model. This is the most impacted area. The black dot indicate sewage treatment plant (STP) discharge.

The boundaries for the ecological model are the shorelines, i.e we do not model drainage basin processes, but estimate load reductions according to various scenarios of land use

The main fresh water input comes from Lake Mälaren through the city of Södertälje (most of Lake Mälaren discharge is through Stockholm). The large drainage basin of L.Mälaren is not shown here.

The sea area was divided into three sub-basins according to natural dividers (sills) and available data (sampling stations shown as red dots)


Ecological dimensions in the saf

Hallsfjärden

Näslandsfjärden

Himmerfjärden pr.

Local runoff

Rain

Local runoff

Rain

Local runoff

Rain

STP

Lake Mälaren

runoff

HAs

NAs

HIs

316

43

123

0-7 m

0-7 m

0-10 m

Baltic Sea

5.23

4.57

5.87

HAm

NAm

54

HIm

25

197

7-13 m

7-13 m

10-20 m

5.77

5.51

6.00

HAb

NAb

49

HIb

47

17

13-37 m

20-43 m

13-38 m

5.81

6.03

6.35

The water exchange conceptual model for the three sub-basins was first divided into only two depth layers, but was later developed into a three-layer model. This gave a more realistic model reflecting the actual sill depths between the basins. Still, of course, it is a simplification of the real world.

Conceptual Model: Himmerfjärden example, water exchange

Legend for model:

Box name

Volume (Mm3)

depth

Salinity (avg. for 1997-2000)

The numerical water-exchange model is heavily data-dependent: Salinity data is used to calculate flows according to mass-balance.


Ecological dimensions in the saf

SPICOSA Training Support Pack

Conceptual Model: Himmerfjärden example, Ecology

Version 1:

Version 2:

This version was the initial ecological conceptual model of the System Design step

The link to water transparency Secchi depth was not shown, but was thought to be linked by empirical relationship with chlorophyll

This is how the model was actually developed as a first version. The first operational version was however further simplified (next slide...)


Ecological dimensions in the saf

SPICOSA Training Support Pack

Conceptual

Model version3:

Nitrogen loading

Total Nitrogen

concentration

Water exchange

Secchi depth

(water transparency)

Nitrogen retention

Secchi depth is estimated according to empirical relationship between nitrogen concentration and Secchi depth


Ecological dimensions in the saf

SPICOSA Training Support Pack

Conceptual

Model version3: with main links to socioeconomic model shown

Nitrogen loading

Total Nitrogen

concentration

Water exchange

Secchi depth

(water transparency)

Nitrogen retention

Cost estimation of load reductions

Secchi depth is estimated according to empirical relationship between nitrogen concentration and Secchi depth

Economic valuation of gains


Ecological dimensions in the saf

SPICOSA Training Support Pack

In practise: Overview of ExtendSim layout for Himmerfjärden Ecological model

WE Const.

WE Input data

FW inflow calculation

WE = Water exchange model

FW = Fresh water

Basin 1

Basin 3

Basin 2

Flow calculation

Water balance

Basin1

Salt balance

Salt balance

Example

Salinity error calculation

Nitrogen

input data

Nitrogen calibration

data

Nitrogen-data

export function

Nitrogen balance


Ecological dimensions in the saf

SPICOSA Training Support Pack

Extend layout for Ecological model


Ecological dimensions in the saf

SPICOSA Training Support Pack

Hindcast (validation) results: Himmerfjärden example

Loss of N during spring phytoplankton blooms

Variations in boundary conditions, nitrogen input and water exchange explain most of the variations in total nitrogen concentration.

The biology added is a loss of nitrogen during the spring bloom, seen as a sudden drop in modeled nitrogen concentration (blue line) in spring.

This model serves mainly one purpose: to calculate total nitrogen concentrations and from these the water transpareny (Secchi depth)


Ecological dimensions in the saf

SPICOSA Training Support Pack

Results of two scenario runs in the preliminary version

of the water-exchange/ecological model

1. Reference scenario: 10 mg nitrogen per liter from sewage treatment plant (STP)

2. Improved sewage treatment scenario: 4 mg N/ L from STP

Nitrogen loads to the model basin Himmerfjärden

Scenario 1

Scenario 2

STP

To Socio-economic model

Nitrogen load

Total nitrogen

concentration

Secchi depth

Total nitrogen reduced from 390 to 320 µg/l in Himmerfjärden, the largest basin

Load from STP reduced from 10 mg/l to 4 mg/l

Secchi depth increased from 2.8 to 3.5m

The model will have to be developed according to the Conceptual model version 2 (or some other idea with a simpler model) to anwer questions about nitrogen fixing cyanobacteria and chlorophyll concentrations


Ecological dimensions in the saf

SPICOSA Training Support Pack

Numerical modelling: Lessons learnt

  • Start simple: construct “Ball-park model” that works (is possible to run) and that is successively developed to a more advanced stage with tests at each stage

  • Save new versions, and document the changes (at least briefly)


Management implications

SPICOSA Training Support Pack

Management implications

The model can be an important tool, but since it is a simplification, and has certain objectives, it cannot answer everything. It may be more or less uncertain depending on how far scenarios are taken.

The model will most likely be one decision support tool among others! The most important “tool” is a good general and expert knowledge of the system! The model will not replace this!

The model may highlight certain data needs. The model may reduce data needs, but more likely it will be helpful in prioritizing which data to collect.

Model may give results that the model does not itself answer how to handle, e.g the costs for a Secchi depth improvement are higher than calculated gains, but may partly result from the fact that qualitative benefits may be difficult to value. Or that measures reducing eutrophication also decrease yield of fisheries. Or that banning of commercial fisheries in favour of tourist fishery may result in higher profits, but may be politically difficult.


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