Page 2 - Discussion Paper: Modelling Urban Carrying Capacity and Measuring Quality of Life using System Dynamics
P. 2
Discussion Paper
Anthropocentric Dynamic Carrying Capacity: The attractiveness or becomes unattractive, inflows would fall
degree of human activity that the environment and while outflows would increase. In this model, there are five
ecosystems within an area can support without degrading attractiveness factors.
or damaging quality of life of its people.
Attractiveness Factors
Research Approach
1 Labour force-to-jobs ratio: This is the ratio of
The current model is based upon the structures of Urban employable population against jobs available.
Dynamics (Forrester 1969), WORLD2 (Forrester 1971),
WORLD3 (Meadows et al. 1974) models. The model is 2 Pollution density: This is the level of environmental
populated using data of Surat as a sample city. pollution against a base value (taken at the 2010 levels).
This study is not intended to provide a forecast or 3 Ratio of water available against water required
prediction but to demonstrate the need for a planning tool per capita: This is the ratio between how much water
where complex interactions could be better understood is available per capita and how much water is required
and policies tested using simulations. The model works as (kept at current supply per capita).
a template that can be customized for any urban area, to
gain insights about its future possibilities. 4 Ratio of water consumed to water requirement
per capita: This is the ratio between the actual water
The paper presents the model description, simulation consumption per capita and how much water is required
results, and highlights insights generated from them. It also (kept at current supply per capita).
makes a case for measuring and monitoring the quality of
life (QoL) as a lead indicator for holistic management of a 5 Ratio of available against required land per capita:
city and well-being of its people. This gains policy relevance This is a ratio between available open land and open
in light of the growing focus on the development of smart land required per capita.
cities and the emphasis being given to QoL.
The model consists of eight sectors: Population,
Research Methodology Business, Land, Water, Solid Waste, Energy and
Emissions, Environmental Pollution, and QoL. These are
Urban systems are complex and composed of various sectors, detailed below.
such as population, businesses, environmental resources,
waste generation, and pollution. These are interconnected, Population Sector
interrelated, interdependent of each other, and closely related
by multiple cause and effect relationships and feedbacks. This sector consists of the stock of population living in the
Such complex systems may be best understood using urban area. The stock changes through flows of births,
dynamic simulation techniques (Casti 1997). SD is one such deaths, in-migration, and out-migration. These flows have
approach, suited to understand the non-linear behaviour of normal flow rates, which are multiplied by functions of
complex systems over time using stocks and flows, internal the various attractiveness factors giving rise to dynamic
feedback loops, and time delays (MIT n.d.). Pioneered by flow rates during simulation. For example, the flow for
Jay W Forrester at MIT in the late 1950s (Forrester 1961), in- migration in a year would be Population stock ×
SD is able to unveil the counterintuitive nature of complex Normal migration rate × Function of labour force to
systems and uncover relationships between variables that job-based attractiveness × Function of pollution-based
are responsible for behaviour of the system. Further, being attractiveness × Function of water-based attractiveness ×
transparent, it provides the reader with an opportunity to go Function of open land-based attractiveness; considering a
through the model structure and study the linkages (Gallati product with all the relevant functions. A similar equation
& Wiesmann 2011). is used for the business sector described later. These
attractiveness functions are described below:
Model Description Impact of jobs on in-migration: When the labour
A brief description of the model structure is given in this force-to-jobs ratio has a value of 1, this function has
section. The detailed model structure and equations can no impact on in-migration. It increases when the
be found here. labour force-to-jobs ratio falls (signifying availability of
employment) and reduces when the ratio increases
The model uses the principle of attractiveness (signifying excess employable population and
(Forrester 1969) to govern the flows of stocks of population fewer jobs).
and active businesses. As long as an area is attractive, Impact of jobs on out-migration: This function
inflows would remain high while if the region loses its increases when the labour force-to-jobs ratio increases
above 1 (signifying excess employable population and
2 FEBRUARY 2016
Anthropocentric Dynamic Carrying Capacity: The attractiveness or becomes unattractive, inflows would fall
degree of human activity that the environment and while outflows would increase. In this model, there are five
ecosystems within an area can support without degrading attractiveness factors.
or damaging quality of life of its people.
Attractiveness Factors
Research Approach
1 Labour force-to-jobs ratio: This is the ratio of
The current model is based upon the structures of Urban employable population against jobs available.
Dynamics (Forrester 1969), WORLD2 (Forrester 1971),
WORLD3 (Meadows et al. 1974) models. The model is 2 Pollution density: This is the level of environmental
populated using data of Surat as a sample city. pollution against a base value (taken at the 2010 levels).
This study is not intended to provide a forecast or 3 Ratio of water available against water required
prediction but to demonstrate the need for a planning tool per capita: This is the ratio between how much water
where complex interactions could be better understood is available per capita and how much water is required
and policies tested using simulations. The model works as (kept at current supply per capita).
a template that can be customized for any urban area, to
gain insights about its future possibilities. 4 Ratio of water consumed to water requirement
per capita: This is the ratio between the actual water
The paper presents the model description, simulation consumption per capita and how much water is required
results, and highlights insights generated from them. It also (kept at current supply per capita).
makes a case for measuring and monitoring the quality of
life (QoL) as a lead indicator for holistic management of a 5 Ratio of available against required land per capita:
city and well-being of its people. This gains policy relevance This is a ratio between available open land and open
in light of the growing focus on the development of smart land required per capita.
cities and the emphasis being given to QoL.
The model consists of eight sectors: Population,
Research Methodology Business, Land, Water, Solid Waste, Energy and
Emissions, Environmental Pollution, and QoL. These are
Urban systems are complex and composed of various sectors, detailed below.
such as population, businesses, environmental resources,
waste generation, and pollution. These are interconnected, Population Sector
interrelated, interdependent of each other, and closely related
by multiple cause and effect relationships and feedbacks. This sector consists of the stock of population living in the
Such complex systems may be best understood using urban area. The stock changes through flows of births,
dynamic simulation techniques (Casti 1997). SD is one such deaths, in-migration, and out-migration. These flows have
approach, suited to understand the non-linear behaviour of normal flow rates, which are multiplied by functions of
complex systems over time using stocks and flows, internal the various attractiveness factors giving rise to dynamic
feedback loops, and time delays (MIT n.d.). Pioneered by flow rates during simulation. For example, the flow for
Jay W Forrester at MIT in the late 1950s (Forrester 1961), in- migration in a year would be Population stock ×
SD is able to unveil the counterintuitive nature of complex Normal migration rate × Function of labour force to
systems and uncover relationships between variables that job-based attractiveness × Function of pollution-based
are responsible for behaviour of the system. Further, being attractiveness × Function of water-based attractiveness ×
transparent, it provides the reader with an opportunity to go Function of open land-based attractiveness; considering a
through the model structure and study the linkages (Gallati product with all the relevant functions. A similar equation
& Wiesmann 2011). is used for the business sector described later. These
attractiveness functions are described below:
Model Description Impact of jobs on in-migration: When the labour
A brief description of the model structure is given in this force-to-jobs ratio has a value of 1, this function has
section. The detailed model structure and equations can no impact on in-migration. It increases when the
be found here. labour force-to-jobs ratio falls (signifying availability of
employment) and reduces when the ratio increases
The model uses the principle of attractiveness (signifying excess employable population and
(Forrester 1969) to govern the flows of stocks of population fewer jobs).
and active businesses. As long as an area is attractive, Impact of jobs on out-migration: This function
inflows would remain high while if the region loses its increases when the labour force-to-jobs ratio increases
above 1 (signifying excess employable population and
2 FEBRUARY 2016
