High-resolution electrical resistivity tomography (ERT) with electrode spacing of 1 m proved to be an effective methodology to characterize ephemeral, sparse, and discontinuous freshwater lenses within the almost completely salinized shallow aquifer of the low coastal zone near Ravenna. ERT profiles with a vertical resolution of 0.25–0.5 m, once calibrated with groundwater data (water table depth and electrical conductivity) collected in multi-level sampler systems at the same spatial resolution, are reliable and provide repeatable measurements in time. The ERT methodology allows for fast data acquisition over large areas and it also permits the study of the evolution in time of freshwater availability in coastal zones, which is important for local ecosystems and soil resources. This makes high-resolution ERT a valid tool to aid local stakeholders and decision makers to effectively manage freshwater lenses, and guarantee their preservation or augmentation by means of managed aquifer recharge.

Modeling of water vapor transport through a dry soil layer (DSL), typically formed in the top soil during dry seasons in arid and semi‐arid areas, is still problematic. Previous laboratory experiments in controlled environments showed that the only vapor transport process through the DSL is by Fick's law of diffusion. However, field experiments exhibited consistently higher evaporation rates than predicted by diffusion flow only. Some proposed reasons for the mismatch were: (a) daily cycles of condensation and evaporation in the DSL due to changes in solar radiation; (b) wind effects on air movement in the DSL; (c) atmospheric pressure fluctuations; (d) nonlinear influence of the DSL thickness on the evaporation process. To link the laboratory experiments with field observations, we performed soil column experiments in the laboratory with thick (>50 cm) DSL, and with different wind speeds, two radiative lamp schedules (continuous and 12 h daily cycles) and different thicknesses of DSL. Atmospheric pressure, air temperature and humidity were measured continuously. The results show that the evaporation rates observed are larger than those predicted by diffusion flow only. We found that it was possible to model the evaporation rates as a function of atmospheric pressure fluctuations. In conclusion, atmospheric pressure fluctuations can induce evaporation rates in DSL larger than estimated by diffusion flow only, possibly explaining the discrepancy between laboratory and field evaporation rates.

During droughts, soil evaporation is often constrained by water vapor transport through an air‐dry soil layer (DSL). Fick's water vapor diffusion is widely regarded as the only process for such transport; however, field studies conducted in arid and semi‐arid conditions showed measured evaporation rates higher than those predicted by diffusion. Therefore, transport processes other than diffusion could be relevant. To study the evaporation through a DSL, the same lysimeter column with 70 cm thick DSL as earlier applied in laboratory in Balugani et al. (2021), was installed in the field in Spain applying an original weighing setup to measure evaporation. The correlation between the measured evaporation and possible drivers of the water vapor transport were evaluated. With the DSL thickness of 70 cm in 2012 and 12 cm in 2015, the lysimeter recorded similar groundwater evaporation rates: 1.25 and 1.05 mm days ⁻¹ , respectively; these rates were much larger than the laboratory recorded rates (0.3 mm days ⁻¹ ) and those estimated in this study using Hydrus1D accounting for non‐isothermal liquid water fluxes and water vapor diffusion. The main forcing driver of the field lysimeter evaporation was the soil profile temperature fluctuation, which concealed other less important forcing factors, that is, atmospheric pressure fluctuations and diffusion. A multivariate regression model to estimate evaporation was proposed, based on the profile temperature fluctuation, that, when added to the atmospheric pressure fluctuations, yielded reliable estimates of the cumulative evaporation measured in both 2012 and 2015.

Biochar production and application as soil amendment is a promising carbon (C)-negative technology to increase soil C sequestration and mitigate climate change. However, there is a lack of knowledge about biochar degradation rate in soil and its effects on native soil organic carbon (SOC), mainly due to the absence of long-term experiments performed in field conditions. The aim of this work was to investigate the long-term degradation rate of biochar in an 8-year field experiment in a poplar short-rotation coppice plantation in Piedmont (Italy), and to modify the RothC model to assess and predict how biochar influences soil C dynamics. The RothC model was modified by including two biochar pools, labile (4 % of the total biochar mass) and recalcitrant (96 %), and the priming effect of biochar on SOC. The model was calibrated and validated using data from the field experiment. The results confirm that biochar degradation can be faster in field conditions in comparison to laboratory experiments; nevertheless, it can contribute to a substantial increase in the soil C stock in the long term. Moreover, this study shows that the modified RothC model was able to simulate the dynamics of biochar and SOC degradation in soils in field conditions in the long term, at least in the specific conditions examined.

The mulching of agricultural soils has been identified as a viable solution to sequester carbon into the soil, increase soil health, and fight desertification. This is why it is a promising solution for carbon farming in Mediterranean areas. Models are used to project the effects of agricultural practices on soil organic carbon in the future for various soil and climatic conditions, and to help policy makers and farmers assess the best way to implement carbon farming strategies. Here, we modified the widely used RothC model to include mulching practices and their direct and indirect effects on soil organic matter input, soil temperature changes, and soil hydraulic balance. We then calibrated and tested our modified RothC (RothC_MM) using the dataset collected in two field mulching experiments, and we used the tested RothC_MM to estimate the expected soil carbon sequestration due to mulching by the year 2050 for the Valencian Community (Spain). Our results show that RothC_MM improved the fit with the experimental data with respect to basic RothC; RothC_MM was able to model the effects of mulch on soil temperature and soil water content and to predict soil organic carbon (SOC) and CO₂ observations taken in the field.