A Neuro-Fuzzy Model for the Ecological Risk

Assessment in Wetlands

William Andrés Ocampo Duque (PhD Student)

Dr. Marta Schuhmacher (Supervisor)

 Rovira I Virgili University

School of Chemical and Process Engineering

Outline

• Motivation

• Problem Definition

• Objectives

• Work Plan

• Lack of information about wetlands pollution

• Constrained budgets for Environmental Information

• Colombia has more than 200000 km2 of Wetlands; only 3 with International Importance.

Motivation

Pressures:•Agriculture•Industry•Transport •Cities

A Watershed

Potential threats ...

Pilot Study: Ebro Delta

Characteristics

•Surface: 320 km² •Flow: 430m3/s •Humid zone of international interest

(Category A)•Wide diversity of bird species

(300 species)•Important economic zone:

•Rice-growing area, vegetable crops and fruits•Fishing•A growing tourist industry

Main Problems

• Hydrologic deficit - Low flow

• Coastal Erosion.

• Deficit of Sediments.

• Salinity of Inland Waters.

• Excess of Nutrients.

• Pesticides and Heavy Metals in Waters.

• Poor Water Quality.

• Politic Stress.

Unsustainable Management !!!

Possible Solutions

• A good definition of indicators.• Improve quality of environmental data.• Develop good tools for making-decisions.• Ecological Awareness.

Objectives

• Develop a model for the ecological risk assessment in wetlands (Eco-Risk).

• Validate the model with a pilot study.

• Produce a tool for Making-decisions and Management.

Work Plan

ProblemIdentification

EffectsIdentification

Extent of Exposure

Identification

Risk Identification

Risk Management/ Risk Reduction

Monitoring

Direct and riverine inputs of metals and organic substances in the NE Atlantic Ocean

Indicators

Indicator: Loads of hazardous substances to coastal waters (2004.05)

Policy issue:Are direct and riverine loads to seas decreasing?

Why Neuro-Fuzzy tools?

• Ability to manipulate no-numerical and uncertain variables.

• Ability to generalise solutions.• Ability to classify and quantify environmental effects

of subjective nature.• Ability to deal with missing data.• Ability to integrate “scientific information” with

“common knowledge”

Example of Fuzzy1. Define water-quality parameters

IF "Dissolved Oxygen is higher than 2.0"AND "pH is higher than 6.0" AND “pH is lower than 9.0” AND “BOD5 is lower than 100”

THEN "Water can be used for irrigation”

2. Define Classification Rules (Membership functions)

3. A “robust decision analysis”A Water SupplyB FisheriesC Industrial SupplyD IrrigationE Environmental protection

Acknowledgements

• Programme Alban, the European Union Programme of High Level Scholarships for Latin America.

• Pontificia Universidad Javeriana.

Questions?