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(UNESCO / Japan Young Researchers' fellowships programme)

A multi-objective optimization and conflict resolution model for metropolises’ water allocation in comparison of evolutionary optimization methods; case study: Tehran Mega-City

Summary of research carried out: 
A multi-objective optimization and conflict resolution model for metropolises’ water allocation in comparison of evolutionary optimization methods; case study: Tehran Mega-City

Allocating water to different competitive users has been always challenging. Population growth and limited water resources are among the most crucial and important issues in Tehran Mega-City and the surrounding countryside. Despite the growing water crisis in Tehran, accurate estimation and forecasting of water supply and demand and striking a balance between them are still lacking. Existing methods are usually limited to classic optimization methods and include only one goal function without any conflict resolution and meta-heuristic multi-optimization aspects. Allocating water in such a mega-city as Tehran has different dimensions and complexities. The most important dimension is the exploitation of water from different sources so that other consumers using the same will not encounter any problems, or at least so that a compromise can be reached. For this reason, different variables such as domestic, industry, agriculture and environment consumption from Tehran dams and also the amount of water taken from groundwater storage should be analysed so as to meet basic demands, prevent conflict among users, minimize water deficits in all sectors, minimize the cost of water supply, and maximize the benefits.

Finding an optimal water allocation by minimizing the water prices and water deficits in each sector and considering conflict resolution was the aim of this research. In this regard, the study confronted a multi-objective water allocation problem. First of all, water consumption in 2030 was forecast, considering the impacts of climate change, using different models, to reach a more precise prediction. Both surface and groundwater resources were simulated by the VENSIM model. By applying the genetic algorithm and determining the main stakeholders, goals and constraints of the multi-objective model, the optimal water allocation from different resources to different sectors was determined. Since classic optimization methods usually do not reach an absolute minimization or maximization and there is no special model focusing on non-linear multi-objective and conflict-resolution methods, the proposed model would be constructed so that, by applying a “win-win” game theory, optimal water allocation can be reached.

To sum up, this research would be more accurate through the use of prediction, simulation, optimization and conflict-resolution models for water allocation from surface and groundwater resources. This model can help decision-makers and managers to adopt appropriate strategies in water-resources management.

 

Critical review for migration modelling due to water security and food stresses

 

Migration becomes part of local culture, which makes it more and more accessible to all levels of the population. The growing body of work in the development of migration models over the past decades shows the importance of this subject in the research community. However, several challenges and opportunities for further research still remain. The main goals of this paper were to critically review the theories, qualitative structural modelling and mathematical modelling of migration.

The models analysed in this paper included some of these variables. Migration theories can be classified according to the level they focus on; macro-level, micro-level and meso-level. Macro-level theories including neoclassical, world system, Zelinkey’s hypothesis, and dual labour market theory mostly focusing on economic, social, employment, capitalism, political, globalization, modernization and demographic variables. Micro-level theories such as Lee’s push and pull theory, human capital theory, neoclassical micro-level theories, new economics of migration (NEM) theory, and the new economics of labour migration (NELM) consider variables similar to the macro level but in individual choices. The meso-level theories, which are between the micro and macro levels, relate to theoretical and practical interplay between social structure and human agency. Dual labour market, world system, and cumulative and circular causation models are in this category.

Various forms of qualitative structural modelling were reviewed and grouped as Immigration and acculturation, conceptual modelling of migration by E-R diagram, models of migration for adaptation and response in climate change, links between climate change and migration, and a conceptual framework for the “drivers of migration”. However, as the literature is still fairly sparse, each model focused on different variables. Generally, cultural, political, economic, social, education, employment, political, demographic, environmental and climate variables were applied in these conceptual models.

Mathematical models of migration were analysed in the context of variables of type of the equations. Both the modified gravity model and migration modelling relating to regional labour markets have a logarithm type of equation. The modified gravity model includes variables such as: population, distance, income, unemployment, urbanization, climatological variables and taxes. As for migration modelling regarding regional labour markets, labour market, wage, unemployment, and distance variables are covered by this model. Three models were of integral/differential types such as: migration modelling based on climate change adaptation, and economic, statistical and time series models. Migration modelling based on climate change adaptation involves vulnerability, adaptive capacity, frequency, longevity, and climate factors. Economic models emphasize monetary and non-monetary factors, psychological costs, distance, income, unemployment, educational, population, urbanization, and human capital investment variables. Statistical time series models consider wage, unemployment, population density, and crop production factors. The migration model relating to adaptation to rainfall change includes a variety of variables such as adaptation behaviours, subjective norms, perceived behavioural control, rainfall assets, livestock assets, occupation, experience and general information about migration, age, gender, marital status, rainfall conditions, and migration information considerations. Markov chain models establish links between perpetuation of migration and population flows and are of a matrix type. The human capital model highlights the role of variables such as the labour market, wages, mobility costs, age, education and marital status on migration modelling and involves the economic type of equations. The last type of optimization models allows for return migration but also concentrates on age, assets and GDP parameters.

The synthesis showed that there is no unanimity over the modelling of migration. One of the reasons for the absence of a single global migration model is the lack of a unified theory of migration, which could become a basis for modelling, and of a common approach in migration terminology. Comparing and contrasting all the above, a combination of economic models and models of adaptation to rainfall change seems to offer a better way of modelling migration involving climate factors, education, marriage status, social, economic and technology variables. Only political issues should be added as a supplementary variable, so in this regard the developed model can cover all the aforementioned causes of migration simultaneously and become a comprehensive migration model.