Food security is the basis of social stability and development. Maintaining sufficient amounts of arable land is essential for China's food security. In this paper, we consider the relationship between arable land demand to grain demand and production capacity. The changes in national population, grain production, and consumption from 2000 to 2015 are analyzed. Then, we forecast the respective possible changes in the future and accordingly forecast the arable land demand in different possible situations. The results show that the pressure to maintain sufficient amounts of arable land in 2030 may be greater than that in 2040.The higher pressure is due to larger population and lower production capacity. To ensure food security in China, we insist on maintaining 120 million ha of arable land, the "red line" for food security, and improve the arable land productivity to ensure domestic production and self-sufficiency. In addition, residents should be guided to cultivate sound food consumption habits in order to control per capita grain demand. Lastly, we should also make full use of international resources and markets to relieve the pressure on domestic resources and environments.
The rational allocation of water resources in the basin/region can be better assisted and performed using a suitable water resources allocation model. Rule-based and optimization-based simulation methods are utilized to solve medium-and long-term water resources allocation problems. Since rule-based allocation methods requires more experience from expert practice than optimization-based allocation methods, it may not be utilized by users that lack experience. Although the optimal solution can be obtained via the optimization-based allocation method, the highly skilled expert experience is not taken into account. To overcome this deficiency and employ the advantages of both rule-based and optimization-based simulation methods, this paper proposes the optimal allocation model of water resources where the highly skilled expert experience has been considered therein. The "prospect theory" is employed to analyze highly skilled expert behavior when decision-making events occur. The cumulative prospect theory value is employed to express the highly skilled expert experience. Then, the various elements of the cumulative prospect theory value can be taken as the variables or parameters in the allocation model. Moreover, the optimal water allocation model developed by the general algebraic modeling system (GAMS) has been improved by adding the decision reversal control point and defining the inverse objective function and other constraints. The case study was carried out in the Wuyur River Basin, northeast of China, and shows that the expert experience considered as the decision maker's preference can be expressed in the improved optimal allocation model. Accordingly, the improved allocation model will contribute to improving the rationality of decision-making results and helping decision-makers better address the problem of water shortage.2 of 17 establish a water resources allocation and management decision-making tool. Abolpour et al. [7] adopted an adaptive neuro-fuzzy reinforcement learning method to enhance the accuracy of optimized parameters in the water resources allocation model. Prasad et al. [8] proposed a linear programming method for finding the optimal irrigation-planning model by considering various growth stages of crops in the water resources allocation. An inaccurate two-stage water allocation model was utilized by Li et al. [9] to simulate the irrigation water requirements of multiple crops in the large-scale areas. Dai and Li [10] constructed a multi-stage irrigation water allocation model for different season water allocation policies. An inaccurate multi-stage stochastic optimization model was proposed by Li and Guo [11] to solve the mesoscale agricultural water resources planning problem. Recently, the rational allocation of water resources has been devoted to solving many difficulties encountered in practice. Kralisch et al. [12] proposed a neural network method to solve the allocation problem between urban living water and agricultural water. Wang et al. [13] proposed a water rights allocation m...
A tunable terahertz (THz) isolator based on a periodically structured semiconductor magneto plasmonics is proposed. The unique photonic band-gap and one-way transmission property of this structure with different magnetic fields and temperature are investigated in the THz regime. The numerical results show the proposed isolator has a bandwidth of 80 GHz with the maximum isolation of higher than 90 dB and a low insertion loss of 5%. The central operating frequency of this isolator can be broadly tuned from 1.4 to 0.9 THz by changing the external magnetic field from 0.6 to 1.6 Tesla at 195 K. This lowloss high isolation broadband nonreciprocal THz transmission mechanism has great potential applications in promoting the performances of THz application systems.Index Terms-Isolator, magneto surface plasmon, one-way waveguide, terahertz (THz).
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