Entrepreneurship-based Optimal Inter-sectorial Allocation of Water Resources in Megacity-dominated Area

Location

Eccles Conference Center

Event Website

http://water.usu.edu

Start Date

4-1-2014 7:00 PM

End Date

4-1-2014 7:05 PM

Description

Unemployment is a significant problem in numerous megacities. Because new entrepreneurship and development requires water resources, addressing unemployment is particularly challenging in arid regions suffering from water shortage. For such regions, water allocation among user sectors can benefit from entrepreneurship-based optimization. This research, presents a novel optimization model for maximizing the numbers of jobs produced for the main economic sectors. The objective function includes a nonlinear job-production function for agriculture, a nonlinear job-production function for industry, and a linear job-production function for service. Reallocation is optimized for three employment-change scenarios: limited change, acceptable change and unlimited change. Scenario results show that total jobs can be increased 1.84, 7.27 and 12.94 times current employment, respectively. Implementing the optimal allocations will increase scenario net benefits as much as 1.33, 1.89 and 15.17 times, respectively. Assuming other social and economic impacts can be acceptable, results argue for the benefit of allowing unlimited change in megacity-dominated arid zone reallocation.

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Apr 1st, 7:00 PM Apr 1st, 7:05 PM

Entrepreneurship-based Optimal Inter-sectorial Allocation of Water Resources in Megacity-dominated Area

Eccles Conference Center

Unemployment is a significant problem in numerous megacities. Because new entrepreneurship and development requires water resources, addressing unemployment is particularly challenging in arid regions suffering from water shortage. For such regions, water allocation among user sectors can benefit from entrepreneurship-based optimization. This research, presents a novel optimization model for maximizing the numbers of jobs produced for the main economic sectors. The objective function includes a nonlinear job-production function for agriculture, a nonlinear job-production function for industry, and a linear job-production function for service. Reallocation is optimized for three employment-change scenarios: limited change, acceptable change and unlimited change. Scenario results show that total jobs can be increased 1.84, 7.27 and 12.94 times current employment, respectively. Implementing the optimal allocations will increase scenario net benefits as much as 1.33, 1.89 and 15.17 times, respectively. Assuming other social and economic impacts can be acceptable, results argue for the benefit of allowing unlimited change in megacity-dominated arid zone reallocation.

https://digitalcommons.usu.edu/runoff/2014/2014Posters/2