Many arid and semiarid regions of the world face serious water shortages that are projected to have significant adverse impacts on irrigated agriculture and create unprecedented challenges for providing food and water security for the rapidly growing human population in a changing global climate. Consequently, there is a momentous incentive to shift to more resource-efficient soilless greenhouse production systems. Though there is considerable empirical and theoretical research devoted to specific issues related to control and management of soilless culture systems, a comprehensive approach that quantitatively considers relevant physicochemical processes within containerized soilless growth modules is missing. An important first step towards development of advanced soilless culture management strategies is a comprehensive characterization of hydraulic and physicochemical substrate properties. In this study we applied state-of-the-art measurement techniques to characterize six soilless substrates and substrate mixtures [i.e., coconut coir, perlite, volcanic tuff, perlite/coconut coir (50/50 vol.-%), tuff/coconut coir (70/30 vol.-%), and Growstone®/coconut coir (50/50 vol.-%)] that are used in commercial production in Israel and the United States. The measured substrate properties include water retention characteristics, saturated hydraulic conductivity, packing and particle densities, as well as phosphorus and ammonium adsorption isotherms. In addition, integral water availability and integral energy parameters were calculated to compare investigated substrates and provide valuable information for irrigation and fertigation management.

Measurements of the soil water characteristic (SWC) and unsaturated hydraulic conductivity [K(h)] curves, which are at the core of modeling flow and transport processes in porous media, are laborious and prone to experimental errors. To overcome some of the current experimental limitations, we examined the potential feasibility of shortwave infrared (SWIR) imaging of water imbibition into dry soil during a controlled laboratory experiment in conjunction with inverse numerical modeling to determine the wetting SWC and the K(h) function. To generate time series of highresolution surface moisture maps, the imaged surface reflectance was converted to surface soil moisture via a recently developed physical radiative transfer model. The moisture time series were then used to parameterize the HYDRUS 2D/3D numerical code for forward simulations. The optimization was performed with simulated annealing in MATLAB that was linked to HYDRUS 2D/3D to automate the inversion process. The obtained SWC wetting curves were subsequently compared with Tempe cell and Dewpoint PotentiaMeter measurements. Although further research and refinements of the proposed method are needed, the results of this exploratory study obtained for a broad range of soil textures are promising and demonstrate the potential feasibility of the proposed approach for rapid estimation of soil hydraulic properties.

Saline playas in arid and semiarid regions of the world are significant sources of unconsolidated sediments susceptible to aeolian transport. Lake Urmia in Iran, one of the largest saltwater lakes on Earth, has waned to approximately 18% of its original size due to groundwater pumping and surface water diversions. This has led to ecosystem degradation, accelerated desertification and frequent dust storms, causing public health problems. In this paper we introduce a new framework for delineation of dust source zones and estimation of dust occurrence probability based on remotely sensed land surface properties (soil moisture and vegetation cover), soil texture, wind speed, and measured dust frequencies. Observations from the Moderate Resolution Imaging Spectroradiometer (MODIS) for the Urmia Lake basin were utilized to determine the Normalized Difference Vegetation Index (NDVI) and to estimate surface soil moisture with a recently introduced optical trapezoid model. The soil textures extracted from the SoilGrids database and wind speeds obtained from local weather stations together with the estimated surface soil moisture were found to be highly correlated with dust emission probability. When the surface soil moisture is low, wind speed is the major determinant for dust occurrence. With increasing surface soil moisture, the dust occurrence probability decreases. Soil moisture effects are more pronounced at high wind speeds. While at low wind speeds the dust occurrence probabilities for the investigated soil textures loam, clay loam and sandy clay loam are similar, at higher wind speeds the sandy clay loam texture exhibits the highest susceptibility to dust generation. Core Ideas A remote sensing framework for delineation of dust source zones is introduced. Surface soil moisture and soil texture are correlated with dust emission frequency. Dust occurrence probability is highest for low moisture conditions and sandy soils.