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The familiarity of mankind with gypsum and its simple composition are in contrast with the frequent mistakes reported for its behavior and role in nature. Gypsum has been studied as a raw material, as a rock constituent, as an indicator of geological and archaeological conditions, and from other points of view. However, its role in Earth surface processes, its relationship to life through calcium in the equilibrium of carbonates and its structural water molecules, seems overlooked. Moreover, errors of gypsum formulation, analysis, and behavior obscure some of its roles within nature. The semi‐solubility of gypsum explains its actions in many soils. The softness, fragility, and crystal water of gypsum are often not considered. Routinely drying at 105°C and pulverizing samples for lab analyses casts suspicion on all analytical results because gypsum becomes anhydrite and/or bassanite at this temperature. Specific physicochemical models are needed to predict the behavior of soils mainly composed of gypsum.

5Soil degradation from salt accumulation, sodication, or both, is a threat or a fact in 6 many irrigated lands. Salinization has often been assessed from changing cropping 7 patterns over time, and often the trends in salinization have not been quantified. Our Thus, soil salinity in the upper meter of soil has decreased during the last 24 years.

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Electromagnetic induction surveys are often used in practice to estimate field‐scale soil salinity patterns, and to infer changing salinity conditions with time. We developed a statistical monitoring strategy that uses electromagnetic induction data and repetitive soil sampling to measure changing soil salinity conditions. This monitoring approach requires (i) the estimation of a conditional regression model that is capable of predicting soil salinity from electromagnetic (EM) survey data, and (ii) the acquisition of new soil samples at two or more previously established survey sites, so that formal tests can be made on the differences between the predicted and observed salinity levels. We examined two test statistics in detail: a test for detecting dynamic spatial variation in the new salinity pattern and a test for detecting a change in the field median salinity level with time. We applied this monitoring and testing strategy to two EM survey‐soil salinity data sets collected at multiple points in time from the saline irrigation district of Flumen, Spain, Our results demonstrate that this monitoring approach was successfully able to quantify the temporal changes in the soil salinity patterns occurring within these two fields.