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The pore-solid interface and its characteristics play a key role in chemical interactions between minerals in the solid soil matrix and the liquid in pore space and, consequently, solute transport in soils. Specific surface area (SSA), typically measured to characterize the pore-solid interface, depends not only on the particles size distribution, but also particle shapes and surface roughness. In this note, we investigate the effects of surface roughness and probing molecule size on SSA estimation, employ concepts from fractals, and theoretically estimate specific surface area from particle size distribution and water retention curve (WRC). The former is used to characterize the particle sizes and the latter to approximately quantify the pore-solid interface roughness by determining the surface fractal dimension Ds. To evaluate our approach, we use five Washington and twenty one Arizona soils for which both particle size distributions and water retention curves were accurately measured over a wide range of particle sizes and matric potentials. Comparison with the experiments show that the proposed method estimates the SSA reasonably well with root mean square error RMSE = 16.8 and 30.1 m2/g for the Washington and Arizona datasets, respectively., Comment: 4 figures, 3 tables

Proximal soil sensors are taking hold in the understanding of soil hydrogeological processes involved in precision agriculture. In this context, permanently installed gamma ray spectroscopy stations represent one of the best space-time trade off methods at field scale. This study proved the feasibility and reliability of soil water content monitoring through a seven-month continuous acquisition of terrestrial gamma radiation in a tomato test field. By employing a 1 L sodium iodide detector placed at a height of 2.25 m, we investigated the gamma signal coming from an area having a ~25 m radius and from a depth of approximately 30 cm. Experimental values, inferred after a calibration measurement and corrected for the presence of biomass, were corroborated with gravimetric data acquired under different soil moisture conditions, giving an average absolute discrepancy of about 2%. A quantitative comparison was carried out with data simulated by AquaCrop, CRITeRIA, and IRRINET soil-crop system models. The different goodness of fit obtained in bare soil condition and during the vegetated period highlighted that CRITeRIA showed the best agreement with the experimental data over the entire data-taking period while, in presence of the tomato crop, IRRINET provided the best results., Comment: 18 pages, 9 Figures, 3 Tables