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Compaction and salinization of soils reduce croplands fertility, affect natural ecosystems, and are major concerns worldwide. Soil compaction alters soil structure and affects the soil's hydraulic properties, and it therefore may have a significant impact on evaporation and solute transport processes in the soil. In this work, we investigated the combined processes of soil compaction, bare soil evaporation, and salt precipitation. X-ray computed microtomography techniques were used to study the geometrical soil pore and grain parameters influenced by compaction. The impact of compaction on evaporation and salt precipitation was studied using column experiments. We found that compaction reduced the average grain size and increased the number of grains, due to the crushing of the grains and their translocation within the compacted soil profile. Changes in pore and grain geometry and size were heterogeneously distributed throughout the soil profile, with changes most apparent near the source of compaction, in our case, at the soil surface. The column experiments showed that the presence of small pores in the upper layer of the compacted soil profile leads to higher evaporation loss and salt precipitation rates, due to the increase of hydraulic connectivity to the soil surface and the prolongation of the first stage of evaporation.

Declining soil-saturated hydraulic conductivity (Ks) as a result of saline and sodic irrigation water is a major cause of soil degradation. While it is understood that the mechanisms that lead to degradation can cause irreversible changes in Ks, existing models do not account for hysteresis between the degradation and rehabilitation processes. We develop the first model for the effect of saline and sodic water on Ks that explicitly includes hysteresis. As such, the idea that a soil's history of degradation and rehabilitation determines its future Ks lies at the center of this model. By means of a “weight” function, the model accounts for soil-specific differences, such as clay content. The weight function also determines the form of the hysteresis curves, which are not restricted to a single shape, as in some existing models for irreversible soil processes. The concept of the weight function is used to develop a reversibility index, which allows for the quantitative comparison of different soils and their susceptibility to irreversible degradation. We discuss the experimental setup required to find a soil's weight function and show how the weight function determines the degree to which Ks is reversible for a given soil. We demonstrate the feasibility of this procedure by presenting experimental results showcasing the presence of hysteresis in soil Ks and using these results to calculate a weight function. Past experiments and models on the decline of Ks due to salinity and sodicity focus on degradation alone, ignoring any characterization of the degree to which declines in Ks are reversible. Our model and experimental results emphasize the need to measure “reversal curves”, which are obtained from rehabilitation measurements following mild declines in Ks. The developed model has the potential to significantly improve our ability to assess the risk of soil degradation by allowing for the consideration of how the accumulation of small degradation events can cause significant land degradation.

We study the reclamation process of a sodic soil by irrigation with water amended with calcium cations. In order to explore the entire range of time-dependent strategies, this task is framed as an optimal control problem, where the amendment rate is the control and the total rehabilitation time is the quantity to be minimized. We use a minimalist model of vertically averaged soil salinity and sodicity, in which the main feedback controlling the dynamics is the nonlinear coupling of soil water and exchange complex, given by the Gapon equation. We show that the optimal solution is a bang–bang control strategy, where the amendment rate is discontinuously switched along the process from a maximum value to zero. The solution enables a reduction in remediation time of about 50%, compared with the continuous use of good-quality irrigation water. Because of its general structure, the bang–bang solution is also shown to work for the reclamation of other soil conditions, such as saline–sodic soils. The novelty in our modeling approach is the capability of searching the entire “strategy space” for optimal time-dependent protocols. The optimal solutions found for the minimalist model can be then fine-tuned by experiments and numerical simulations, applicable to realistic conditions that include spatial variability and heterogeneities.

Human societies are increasingly altering the water and biogeochemical cycles to both improve ecosystem productivity and reduce risks associated with the unpredictable variability of climatic drivers. These alterations, however, often cause large negative environmental consequences, raising the question as to how societies can ensure a sustainable use of natural resources for the future. Here we discuss how ecohydrological modeling may address these broad questions with special attention to agroecosystems. The challenges related to modeling the two-way interaction between society and environment are illustrated by means of a dynamical model in which soil and water quality supports the growth of human society but is also degraded by excessive pressure, leading to critical transitions and sustained societal growth-collapse cycles. We then focus on the coupled dynamics of soil water and solutes (nutrients or contaminants), emphasizing the modeling challenges, presented by the strong nonlinearities in the soil and plant system and the unpredictable hydroclimatic forcing, that need to be overcome to quantitatively analyze problems of soil water sustainability in both natural and agricultural ecosystems. We discuss applications of this framework to problems of irrigation, soil salinization, and fertilization and emphasize how optimal solutions for large-scale, long-term planning of soil and water resources in agroecosystems under uncertainty could be provided by methods from stochastic control, informed by physically and mathematically sound descriptions of ecohydrological and biogeochemical interactions.