An increasing population and limited arable land area endanger sufficient and variegated food supplies worldwide. Greenhouse cultivation enables highly intensive plant production and thereby enables the production of abundant fresh vegetables and fruits. The salient benefits of greenhouse cultivation are supported by ingenious management of crop environments, assisted by fossil fuel and grid electricity supplies. To reduce dependence on traditional energy resources, various studies have investigated exploitation of renewable energies for greenhouse environment management. Among them, solar photovoltaic (PV) technologies are anticipated to feed electrical energy to greenhouse appliances for microclimate control. This study proposes a venetian-blind-type shading system consisting of semi-transparent PV modules as blind blades based on micro-spherical solar cell technology to achieve greenhouse shading and electricity production concurrently. In response to the solar irradiance level, the PV blind inclination was altered automatically using a direct current (DC) motor driven by electrical energy generated by the PV blind itself. The PV blind was operated continuously during a five-month test period without outage. Moreover, the PV blind generated surplus electrical energy of 2125 kJ for blind system operations during the test period. The annual surplus energy calculated under the present experimental condition was 7.8 kWh m⁻² year⁻¹, suggesting that application of the PV blind to a greenhouse roof enables sunlight level control and electrical appliance operations in the greenhouse with a diminished fuel and grid electricity supply, particularly in high-insolation regions.

A simplified stochastic control model for optimization of logistic dynamics with the control-dependent carrying capacity, which is motivated by a recent algae population management problem in the river environment, is presented. Solving the optimization problem reduces to finding a solution to a non-local first-order differential equation called tt–Jacobi–Bellman (HJB) equation. It is shown that the HJB equation has a unique viscosity solution and that the solution can be approximated with a finite difference scheme. Asymptotic estimates of the solution and the optimal control are derived and compared with numerical solutions. Finally, parameter dependence of the optimal control is examined numerically with implications to river environmental management.

An integrated hydrological-hydraulic model employing the 2-D local inertial equation as the core is established for effective numerical simulation of surface water flows in a great lake and its floodplain. The model is a cascade of validated hydrological and hydraulic sub-models. The model was applied to simulating the surface water flows of the Tonle Sap Lake and its floodplain in Cambodia using the roughness coefficient value calibrated comparing with a remote-sensing data set. The resulting model reasonably handles backwater flows during the rainy season and simulates the propagations of wet and dry interfaces without numerical instability, owing to a proper setting of time step supported by a novel numerical stability analysis. Sensitivity analysis of the surface water dynamics focusing on the setting of roughness coefficient and the backwater effect was also carried out. Overall, utilizing the 2-D local inertial equation in the assessment of lake water dynamics is a new modelling approach, which turns out to be an efficient simulation tool.