Physicochemical and Hydraulic Characterization of Soilless Greenhouse Substrates and Modeling of Flow and Transport in Soilless Substrate Growth Modules with High Performance Computing

Abstract

Because of the urgent need to secure and sustain the food and water supply for an ever-growing human population, especially in underdeveloped arid and semiarid regions of the world, and an increasing demand for out-of-season fruits, vegetables, and ornamentals in the industrial world, there is a momentous incentive to shift from soil-based crop production to more resource-efficient containerized soilless culture production systems. Mineral and organic substrates are commonly mixed to establish an optimal rhizosphere environment for soilless crop production. Soilless substrates exhibit major advantages over soils. Besides the alleviated risk for spreading soilborne pathogens, the physicochemical properties of soilless substrates can be controlled within narrow margins, which commonly leads to healthier plants and higher yields than in soil-based production, while conserving water resources. Although there is considerable recent empirical and theoretical research devoted to specific issues related to the control and management of soilless culture production systems, a comprehensive approach that quantitatively considers all relevant physicochemical processes within the growth substrates is lacking. An important first step towards the advancement of soilless culture management strategies is a comprehensive characterization of hydraulic and physicochemical substrate properties. In course of my dissertation research, I have applied state-of-the-art measurement techniques to characterize six soilless substrates and mixtures including coconut coir, perlite, volcanic tuff, perlite/coconut coir (50/50 vol.-%), tuff/coconut coir (70/30 vol.-%), and foamed glass (Growstone®)/coconut coir (50/50 vol.-%), all of which are commonly used in commercial soilless culture production. The measured properties include water retention characteristics, saturated hydraulic conductivity, packing and particle densities, as well as phosphorus and ammonium adsorption isotherms.Although economic and environmental considerations are important when selecting suitable soilless substrates, their physicochemical and hydraulic properties are the most imperative performance indicators. While the chemistry of soilless substrate systems can be manipulated and managed to a large extent during the growth season, there is little opportunity for altering the hydraulic properties, which implies the crucial importance of initial plant-specific substrate selection. While the substrate water characteristic (SWC), which defines the relationship between water content and matric potential and governs the storage and release of water, is essential for precise irrigation and fertilization management, its measurement is very laborious. In soilless culture production, it is common practice to test growth substrates via costly and time-consuming trial and error experiments. To provide a scientifically sound basis for a priori elimination of substrate mixtures with unfavorable water retention and associated aeration characteristics, as part of my dissertation, I have developed a new model for the estimation of water retention properties of two-component soilless substrate mixtures with arbitrary mixing ratios based on the water characteristics of their pure constituents. A comparison of mixture SWCs measured with cutting-edge laboratory methods and estimated with my new model revealed a very good agreement for the tuff/coconut coir, perlite/coconut coir, and foamed glass/coconut coir mixtures. The new model can be applied in conjunction with numerical simulations to tailor soilless substrate mixtures for specific crop physiological traits and aid with the design of growth modules and the selection of optimal irrigation and fertigation practices. To advance numerical simulations of three-dimensional water flow and solute transport in containerized variably saturated soilless substrates, the final part of my dissertation research has been focused on the adaptation and validation of the open-source ParSWMS numerical code for High Performance Computing (HPC). Numerical simulation of three-dimensional water flow and solute transport in containerized variably saturated soilless substrates with complex hydraulic properties and boundary conditions necessitates high-resolution discretization of the spatial and temporal domains, which commonly leads to several million nodes requiring numerical evaluation. Even today’s computing prowess of workstations is not adequate to tackle such problems within a reasonable timeframe, especially when numerous realizations are desired to optimize the geometry, substrate properties, and irrigation and fertigation management of soilless plant growth modules. Hence, the parallelization of the numerical code and the utilization of HPC are essential. In course of my dissertation research, I have adapted and applied the open-source ParSWMS parallelized code that is amenable to solving the 3D Richards equation for water flow and the convection-dispersion equation (CDE) for solute transport subject to linear solute adsorption. The code was modified to allow for nonlinear equilibrium solute adsorption with new boundary conditions and applied to simulate water flow and nitrogen and phosphorus transport in containerized soilless substrates. Multi-solute transport simulations with the modified Linux ParSWMS code were first performed on a workstation and referenced to the Windows-based HYDRUS (2D/3D) numerical code. After confirming the agreement between the modified ParSWMS code and HYDRUS (2D/3D), various preconditioners and iterative solvers were evaluated to find the computationally most efficient combinations. The performance of the modified ParSWMS code and its stability were compared to HYDRUS (2D/3D) simulations for three soilless substrates consisting of horticultural perlite, volcanic tuff, and a volcanic tuff/coconut coir mixture. Considering the solute mass balance error as a stability measure, ParSWMS outperformed HYDRUS (2D/3D). Moreover, simulations with the modified ParSWMS code were about 22% faster than simulations with HYDRUS (2D/3D) on the workstation. Tests of ParSWMS on two HPC clusters with 28 and 94 cores revealed a potential 94% simulation speedup relative to the HYDRUS (2D/3D) simulations performed on the workstation.