Evidence-based Decision-making using Fuzzy Cognitive Maps: Lessons from the Global South

BY

ARVIND LAKSHMISHA

SENIOR PROGRAM OFFICERPUBLIC AFFAIRS CENTRE

STUDY SUPPORTED BYEMPRI

Presented at workshop on

Communicating Climate Change

10-11 November 2016

Overview

Introduction

Methodology

Study Findings

Outcomes

2

Introduction

3

Introduction to the study

Short study to assess water insecurities caused due to climate

change and urbanization in peri-urban areas of Bangalore

Approach: Climate Change Scorecard (CCSC)

Bottom-up inclusive knowledge generation tool

Convergence of multiple voices into a single perspective

Creates an interactive platform for constructive engagement

through knowledge sharing and citizen empowerment

Citizens Environment Governance Resources

4

Peri-urban areas

No proper definition to the term

Landscape interface between urban and rural areas

Bi-directional flow unique characteristics of the area

unique environmental problems

Water Scarcity Water Insecurity

PERI-URBAN AreasURBAN Areas

WASTE

WATER

5

Delhi √

Hyderabad √

Chennai √

Bangalore ?

Investigating Peri-Urban water security in

Bangalore

6

Investigating Peri-Urban water security

Bangalore

Need to understand how the double injustice on water resources,

due to Unplanned Urbanisation and Climate Variability

Environmental management of peri-urban areas to address the

specific environment, social, economic and institutional aspects

First step in addressing water security is to first assess if and how

water security is being perceived

Accessibility

Quality

Quantity

7

Study Area8

8 villages – Manchanayakanahalli GP – Ramanagara Taluk

2489 HHs, 9905 Individuals

81% working population in non-agricultural activities

Methodology

9

Methodology - CCSC

Exploratory Phase

• Time Series Analysis (1901-2012)

•475 Surveys – Household Drinking Water security

• Interviews with Industry and GP representatives

Analytical Phase

•240 Fuzzy Cognitive Maps – urbanisation, rainfall variation, temperature increase

•Water Sample Analysis

Synthesis Phase

•Evidence-based Policy Simulations

10

Cognitive Scinece used to capture uncertain and hazy

knowledge

Develop qualitative impact models of water security in Peri-

urban Areas

Model causal relationships between variables

Methodology - CCSC 11

Methodology - CCSC

240 Fuzzy Cognitive maps (30 maps per village)

Interview Based

individuals

groups of people

Each group drew three maps identifying the impact of climate variations and urbanisation on water security

12

42

25

22

46

2321 21 21

0

5

10

15

20

25

30

35

40

45

50

Farmers Agriculture labourers Industrial Labourers Livestock Herders

Nu

mb

er

of

Pa

rtic

ipa

nts

Women

Men

Methodology - CCSC

Stakeholders decide important variables and relationships in the map

Variables

physical quantities (amount of precipitation or % of vegetation cover)

complex aggregate and abstract ideas

Number between -1 and 1to indicate the relative strength of relation ship

Developed Social Cognitive Maps

Analyse the outcomes of cognitive maps using neural network computation

Simulate different policy options through neural network computation

13

Map for

Urbanisation

and Water

Security

14

Map for

Rainfall

Variation and

Water

Security

15

Map for

Increase in

Temperature

and Water

Security

16

Study Findings

17

Water Security – Accessibility and QuantityC

om

mu

nity •73% - tap @

home

•24% - public tap

•90% drinking water –purification units

•Private bore wells GP

me

mb

ers •Groundwater

•Purification plants

•Tanker supply

•Water tanks

•Decrease in groundwater (450 800 feet)

Ind

ust

ry

•Groundwater

•Recycling waste water

18

Water Security - Quality

Co

mm

un

ity • Contaminated

• High salt content

GP

me

mb

ers • Fluoride

contamination

• Groundwater unsafe for drinking

Seven water samples collected

5 groundwater

2 purification plants

2 samples are acidic (Low PH content)

3 samples are muddy

1 sample has metal corrode

19

Ensuring Water Security C

om

mu

nity

• 56% Unaware of rainwater harvesting

GP

me

mb

ers • Check dams

and bunds

• Keen to pursue and expand rainwater harvesting

Ind

ust

ry

• Undertaking rainwater harvesting

• Reusing waste water

• Common effluent treatment plants

20

Drivers of Water Security

Economic Conditions

Forest Cover

Pollution

Sewage Water

Industrial Effluents

Rainfall Variation

Migration

Conversion of Agricultural Land

21

Findings - Policy Simulations

Improving Water Security

+ Sale of Land

+ Slum areas

- Pollution

- Sewage Water

Strong Positive Change – Drinking Water and Surface Water

22

-1

-0.8

-0.6

-0.4

-0.2

0

0.2

0.4

0.6

0.8

1

Scenario 1

Scenario 2

Model

Assumptions

Positive

Change

Supplement

ary Change

Outcomes

23

Based on our Recommendations

Detailed analysis of the RO plants

Common effluent treatment plant in the Industrial

estate

Awareness on rainwater harvesting at GP levels

Structures under MGNREGA Scheme

Training Activities to enhance interaction between

industry and gram panchayat representatives

24

25

Visit us @ www.pacindia.org

Drop in @

No.15, KIADB Industrial Area

Jigani - Bommasandra Link Road

Bangalore – 560105

India

Phone:+91-80-27839918/19/20

Email: arvindlsha@pacindia.org

Thank You