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Different canopy resistance (rc) parameterization has been used in land surface models to simulate actual evapotranspiration (ETc) and soil hydraulic variable for crop fields. However, the influence of rc parameterization on evapotranspiration (ET) partitioning and soil water dynamics has not been fully investigated with consideration of the coupled soil water and vapor physics. This study investigated the influential mechanisms of five rc methods (viz., Jarvis, Katerji-Perrier, Massman, Kelliher-Leuning, and Farias) on ET partitioning and soil water contents in an irrigated maize field under a semiarid climate through a soil water and vapor transfer model. The Jarvis method presented the best ET results (R2 = 0.86 and RMSE = 0.71 mm·d-1). Different rc parameterization mainly altered the simulated amount of soil water contents, while not changed the response of soil water dynamics to irrigation events. By the integrated analysis of the ET partitioning and root-zone water budget, different rc methods varied in the choice of the optimum irrigation water use strategies. This study identified the direct and indirect impacts of rc on the ET partitioning and emphasizes the necessity of both the ET partitioning and water supply sources in the decision-making for irrigation water management in semiarid regions. [ABSTRACT FROM AUTHOR]

In order to solve the immaturity of decision-making methods in the regulation of winter heating in greenhouses, this study proposed a solution to the problem of greenhouse winter heating regulation using a dynamic programming algorithm. A mathematical model that included indoor environmental state variables, optimization decision variables, and outdoor random variables was established. The temperature is kept close to the expected value and the energy consumption is low. The model predicts the control solution by considering the cost function within the next 10 steps. The two-stage planning method was used to optimize the state of each moment step by step. The temperature control strategy model was obtained by training the relationship between indoor temperature, outdoor temperature, and heating time after optimization using a regression algorithm. Based on a typical Internet of Things (IoT) structure, the greenhouse control system was designed to regulate the optimal control according to the feedback of the current environment. Through testing and verification, the optimized control method could stabilize the temperature near the target value. Compared to the threshold control (threshold interval of 2.0°C) under similar weather conditions, the optimized control method reduced the temperature fluctuation range by 0.9°C and saved 7.83 kW·h of electricity, which is about 14.56% of the total experimental electricity consumption. This shows that the dynamic programming method is feasible for environmental regulation in actual greenhouse production, and further research can be expanded in terms of decision variables and policy models to achieve a more comprehensive, scientific, and precise regulation. [ABSTRACT FROM AUTHOR]

Nonuniform pressure of microirrigation systems negatively impacts crop productivity, water utilization, and nonpoint source pollution. However, achieving network pressure uniformity can be prohibitively expensive. This paper presents an economic optimization method that seeks to balance competing costs and benefits. A custom computer software script is developed to implement the method and an irrigation case study is presented. Regression analysis showed that the relationship between economic efficiency and Christiansen uniformity (CU) is a cubic function with an optimum uniformity (i.e., in reference to CU) at 0.78 for cotton and 0.86 for olive trees. The results also indicate that water cost is the most important factor influencing total cost and economic efficiency, and next is capital cost. Also, irrigation systems with a relatively small subunit size (0.1-0.42 ha for cotton and 0.72-2.16 ha for olive) commonly lead to a high economic efficiency. Finally, to guarantee adequate uniformity, the most efficient microirrigation system design will necessarily use the smallest possible size of the manifold. [ABSTRACT FROM AUTHOR]

We focus on the synchronization of a wide class of four-dimensional (4-D) chaotic systems. Firstly, based on the stability theory in fractional-order calculus and sliding mode control, a new method is derived to make the synchronization of a wide class of fractional-order chaotic systems. Furthermore, the method guarantees the synchronization between an integer-order system and a fraction-order system and the synchronization between two fractional-order chaotic systems with different orders. Finally, three examples are presented to illustrate the effectiveness of the proposed scheme and simulation results are given to demonstrate the effectiveness of the proposed method. [ABSTRACT FROM AUTHOR]

We focus on the synchronization of a wide class of four-dimensional (4-D) chaotic systems. Firstly, based on the stability theory in fractional-order calculus and sliding mode control, a new method is derived to make the synchronization of a wide class of fractional-order chaotic systems. Furthermore, the method guarantees the synchronization between an integer-order system and a fraction-order system and the synchronization between two fractional-order chaotic systems with different orders. Finally, three examples are presented to illustrate the effectiveness of the proposed scheme and simulation results are given to demonstrate the effectiveness of the proposed method. [ABSTRACT FROM AUTHOR]