Energy, Water, Food Nexus Decision-Making for Sustainable …
207
is one of the most stressing issues tackled by the EWF nexus literature, encompasses numerous studies adopting ABMs. Wens et al. developed a risk adaptation
framework to simulate drought adaptation behaviours in agricultural sector. The
purpose of the study was to determine the impact of adopting adaption measures on
the drought risk profile in a semi-arid environment [89]. Considering food security
from a social perspective, Joyita developed a framework that fosters food donation
through enhancing the collaboration within lucrative entities known as food pantries.
The ABM-based approach simulates the supply and demand profiles on food and
the network facilitating the flow of food between different pantries, with an aim to
enhance collaboration amongst them and alleviate food insecurity [90]. ABM was
also used to enhance the economic and environmental efficiency of food systems by
assessing diverse production and supply scenarios. Namany et al. proposed a flexible decision-making framework that predicts strategies of a food sector comprised
of local production and international trade systems. Three scenarios were developed
to investigate the food supply profile under water restrictions constraint and deployment of forward contracts opportunity. The methodology developed was illustrated
by tomato crop, yet it can accommodate diverse crop type. It fosters the importance
of considering the virtual water concept as part of the water resources in arid regions,
and it serves as a decision-making guideline to improve the performance of the food
sector while respecting resources scarcities and economic limitations [91].
4.2 Risk and Uncertainty Assessment and Prediction
The world today is subjected to the increasing emergence of social, economic, and
environmental challenges. Climate change, political instability, natural disasters, and
demographic growth are only but a few examples of the myriad of turbulences that can
threaten the stability and prosperity of mankind. However, the demand for products
and resources to maintain the current operations in all sectors necessitates the need
to overcome instabilities and cope with current and unforeseen uncertainties either
through mitigation or adaptation strategies. In order to develop mitigation plans, risks
should be first identified and quantified to capture the influence they may exert on
diverse systems.
In the previous Sect. 4.1, simulation methods were explained, and their importance
in depicting real-life problems was highlighted. However, in order to have a comprehensive and realistic representation of current issues, risks and uncertainties should
be embedded within existing models to accurately mimic systems interactions and
dynamics since real problems are rarely deterministic, and mostly involve stochasticity and randomness. There exists a wide variety of risk quantification models and
techniques that are either used independently or jointly with the aforementioned
simulation models. In the context of resource management, the focus in this chapter
will be mainly on common techniques used to quantify and predict risks as part of
the food insecurity alleviation goal and building a resilient food sector.
207
is one of the most stressing issues tackled by the EWF nexus literature, encompasses numerous studies adopting ABMs. Wens et al. developed a risk adaptation
framework to simulate drought adaptation behaviours in agricultural sector. The
purpose of the study was to determine the impact of adopting adaption measures on
the drought risk profile in a semi-arid environment [89]. Considering food security
from a social perspective, Joyita developed a framework that fosters food donation
through enhancing the collaboration within lucrative entities known as food pantries.
The ABM-based approach simulates the supply and demand profiles on food and
the network facilitating the flow of food between different pantries, with an aim to
enhance collaboration amongst them and alleviate food insecurity [90]. ABM was
also used to enhance the economic and environmental efficiency of food systems by
assessing diverse production and supply scenarios. Namany et al. proposed a flexible decision-making framework that predicts strategies of a food sector comprised
of local production and international trade systems. Three scenarios were developed
to investigate the food supply profile under water restrictions constraint and deployment of forward contracts opportunity. The methodology developed was illustrated
by tomato crop, yet it can accommodate diverse crop type. It fosters the importance
of considering the virtual water concept as part of the water resources in arid regions,
and it serves as a decision-making guideline to improve the performance of the food
sector while respecting resources scarcities and economic limitations [91].
4.2 Risk and Uncertainty Assessment and Prediction
The world today is subjected to the increasing emergence of social, economic, and
environmental challenges. Climate change, political instability, natural disasters, and
demographic growth are only but a few examples of the myriad of turbulences that can
threaten the stability and prosperity of mankind. However, the demand for products
and resources to maintain the current operations in all sectors necessitates the need
to overcome instabilities and cope with current and unforeseen uncertainties either
through mitigation or adaptation strategies. In order to develop mitigation plans, risks
should be first identified and quantified to capture the influence they may exert on
diverse systems.
In the previous Sect. 4.1, simulation methods were explained, and their importance
in depicting real-life problems was highlighted. However, in order to have a comprehensive and realistic representation of current issues, risks and uncertainties should
be embedded within existing models to accurately mimic systems interactions and
dynamics since real problems are rarely deterministic, and mostly involve stochasticity and randomness. There exists a wide variety of risk quantification models and
techniques that are either used independently or jointly with the aforementioned
simulation models. In the context of resource management, the focus in this chapter
will be mainly on common techniques used to quantify and predict risks as part of
the food insecurity alleviation goal and building a resilient food sector.