Managing agricultural water and land resources with tradeoff between economic, environmental, and social considerations: A multi-objective non-linear optimization model under uncertainty

Li, Mo; Fu, Qiang; Singh, Vijay P.; Liu, Dong; Li, Tianxiao; Zhou, Yi

doi:10.1016/j.agsy.2019.102685

Cited by 142 publications

(41 citation statements)

References 31 publications

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“…Where is the original data， is the processed data. Entropy weight method was used to obtain the competitiveness of each indicator and the subsystem weight by using equation (4) to (7).…”

Section: Entropy Weight Methodsmentioning

confidence: 99%

Regional Agriculture Coupling Coordination Analysis Based on Sustainable Development: A Case Study of Sichuan, China

2021

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As a basic industry for national development, the development of agriculture will reduce food insecurity, get rid of resource dependence and achieve broader development. This paper constructs a four-dimensional measurement system of food production, economic development, ecological protection, and social progress by considering food security. Comprehensive agricultural development in Sichuan Province from 2004 to 2018 was evaluated by using improved entropy method and coupling coordination degree model (CCD). The study found that: (1) From 2004 to 2018, comprehensive development of the four subsystems in Sichuan agriculture are different, ecological protection (9.62%) > social progress (3.34%)> economic development (2.61%)> food production (-0.44%); (2) The comprehensive development level of agriculture in Sichuan Province had been continuously improved from 2004 to 2018, with obvious phase characteristics; (3) The coordination development among subsystems advanced in volatility, which is adjusted from the medium to the optimal level of coordination. Finally, based on the above conclusions, Sichuan agricultural sustainable development can be improved from the perspective of food production, economic development and social progress on the basis of ecological protection.

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“…Where is the original data， is the processed data. Entropy weight method was used to obtain the competitiveness of each indicator and the subsystem weight by using equation (4) to (7).…”

Section: Entropy Weight Methodsmentioning

confidence: 99%

Regional Agriculture Coupling Coordination Analysis Based on Sustainable Development: A Case Study of Sichuan, China

2021

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“…Кроме того, используемый аппарат классической теории оптимального управления требует от исследователя достаточно высокого уровня математической подготовки и может приводить к некорректным результатам применительно к стохастическим экономическим объектам. В работе [10] разработана многокритериальная многофакторная нечеткая модель частично целочисленного программирования для оптимизации распределения сельскохозяйственных водных и земельных ресурсов в условиях неопределенности. Подобное сочетание методов весьма эффективно для решения слабо формализуемых задач, однако требует разработки как специфического математического инструментария, так и программного обеспечения.…”

Section: обзор литературыunclassified

Finite-Difference Models Application for Short-Term Forecasting of the Natural Resource Potential of the Perm Region

Sirotina¹,

Kopoteva²,

Zatonskiy³

2021

CTAC&R

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The article is about a problem of mathematical modeling of the natural resource potential of the Perm Territory by 1st and 2nd order finite-difference models. Such models can obtain better forecasts of complex socio-economic processes in comparison with the traditionally used linear multiple regression models. A high quality model of the natural resource potential with forecast possibi¬lities is one of the necessary conditions for the effective management of the natural resources of the region in order to ensure its sustainable economic development. Purpose of work. Aim of this work is work construction of finite-difference models of a natural resource potential complex indicators and an assessment of their prognostic properties. Materials and methods. Our research is based on Perm region statistical data for the period from 2001 to 2018. A multiple linear regression model is used as a comparison base. The natural resource potential complex indicator is calculated as a weighted sum of particular criteria characterizing the natural resources of the region. First and second order finite difference models are obtained by adding autoregressive terms of the first and second orders, respectively, to the multiple linear regression model. An estimation of the unknown parameters of the equations is carried out by a modified least squares method, which preserves the signs of the coefficients with the factors the same as in the original linear model. At the same time, the selection of explanatory factors and the assessment of the quality of the models are carried out based on the accuracy of the predicted values of the studied indicator. The results of the study. Components and factors of the natural resource potential is obtained, and a procedure for constructing finite-difference models is performed for three different time intervals: 2001–2018, 2001–2008, and 2008–2018. These intervals are chooseen because changes in the methodology for generating statistical data nearly 2008. Discussion and conclusions. The number of calculated predicted values was 18, and only in 4 out of 18 cases (22,2%) their quality is worse than forecasts obtained by the linear multiple model. So proposed modification of the multiple linear regression model with the addition of autoregressive terms makes it possible to improve the forecasting quality of the complex indicator of the natural resource potential of the region and, therefore, to make more effective decisions when managing its level.

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“…(2) Benefit coefficient and cost coefficient of water supply [3,[6][7]. By selecting the benefit coefficient of water supply in nearby areas, the model can be more typical and representative.…”

Section: Parameter Acquisitionmentioning

confidence: 99%

Multi-objective optimal allocation of water resources in Yangchangwan mining area based on ecological priority

Zhang

2021

E3S Web Conf.

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With the development of mining area economy and the adjustment of industrial structure from traditional heavy industry to hightech industry, the supply and demand structure of water resources has changed significantly, and the ecological damage in mining area make the ecological water consumption increase significantly. This paper summarizes the water supply of surface water, groundwater, mine drainage and reclaimed water, as well as all kinds of water demand. Based on the principle of ecological priority, a multi-objective optimal allocation model for the coordinated development of ecological environment, social economy and water resources in Yangchangwan mining area was constructed. The results show that the multi-objective optimal allocation model well coordinated the social and economic development goals and resource saving goals, and the optimization scheme ensured that the water demand satisfaction of each water sector reached 100%. On the one hand, it can provide technical support for the mining area to realize the green water and green mountains pattern as soon as possible, on the other hand, it can also provide reference for water resources management in other similar areas.

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Managing agricultural water and land resources with tradeoff between economic, environmental, and social considerations: A multi-objective non-linear optimization model under uncertainty

Cited by 142 publications

References 31 publications

Regional Agriculture Coupling Coordination Analysis Based on Sustainable Development: A Case Study of Sichuan, China

Regional Agriculture Coupling Coordination Analysis Based on Sustainable Development: A Case Study of Sichuan, China

Finite-Difference Models Application for Short-Term Forecasting of the Natural Resource Potential of the Perm Region

Multi-objective optimal allocation of water resources in Yangchangwan mining area based on ecological priority

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