Are there universal soil responses to cover cropping? A systematic review.

Cover cropping is commonly acknowledged to promote soil health in agriculture. However, contradictory findings on the benefits of cover crops for soil health, crop productivity, economic and ecological factors, as well as the influence of inherent soil parameters on such benefits exist in the scientific literature. Here, we critically assessed evidence of cover crop benefits through a systematic review of the published literature.

Coupling time-lapse ground penetrating radar surveys and infiltration experiments to characterize two types of non-uniform flow.

Understanding linkages between heterogeneous soil structures and non-uniform flow is fundamental for interpreting infiltration processes and improving hydrological simulations. Here, we utilized ground-penetrating radar (GPR) as a non-invasive technique to investigate those linkages and to complement current traditional methods that are labor-intensive, invasive, and non-repeatable. We combined time-lapse GPR surveys with different types of infiltration experiments to create three-dimensional (3D) diagrams of the wetting dynamics.

Assessing Effects of Salinity on the Performance of a Low-Cost Wireless Soil Water Sensor.

Low-cost, accurate soil water sensors combined with wireless communication in an internet of things (IoT) framework can be harnessed to enhance the benefits of precision irrigation. However, the accuracy of low-cost sensors (e.g.

Dynamic Bayesian Networks to Assess Anthropogenic and Climatic Drivers of Saltwater Intrusion: A Decision Support Tool Toward Improved Management.

Saltwater intrusion (SWI) is a global coastal problem caused by aquifer overpumping, land-use change, and climate change impacts. Given the complex pathways that lead to SWI, coastal urban areas with poorly monitored aquifers are in need of probabilistic-based decision support tools that can assist in better understanding and predicting SWI, while exploring effective means for sustainable aquifer management. In this study, we develop a Bayesian Belief Network (BBN) to account for the complex interactions of climatic and anthropogenic processes leading to SWI, while relating the severity of SWI to associated socioeconomic impacts and possible adaptation strategies.

Detecting infiltrated water and preferential flow pathways through time-lapse ground-penetrating radar surveys.

The objective of this paper was to identify the incidence and extent of preferential flow at two experimental areas located in Lyon, France. We used time-lapse ground-penetrating radar (GPR) surveys in conjunction with automatized single-ring infiltration experiments to create three-dimensional (3D) representations of infiltrated water. In total we established three 100 cm × 100 cm GPR grids and used differenced radargrams from pre- and post-infiltration surveys to detect wetting patterns.

Transdisciplinary interventions for environmental sustainability.

This paper presents a case study of a transdisciplinary research based on an ex-post assessment of the environmental and socio-behavioral contexts of solid waste management in Lebanese peri-urban communities. Lessons learned are compiled into the Transdisciplinary Interventions for Environmental Sustainability conceptual framework. The approach starts with building a team of researchers and non-academic partners, continues with co-creating solution-oriented knowledge, and ends by integrating and applying the produced knowledge.

Nutrient pollutant loading and source apportionment along a Mediterranean river.

Rivers are increasingly being subjected to increased anthropogenic pollution stresses that undermine their designated uses and negatively affect sensitive coastal regions. The degradation of river water quality is attributed to both point and nonpoint sources of pollution. In this study, we determine the relative contribution of point and nonpoint pollutant loads in the Beirut River basin, a poorly monitored seasonal Mediterranean river.

Data-Worth Assessment for a Three-Dimensional Optimal Design in Nonlinear Groundwater Systems.

Groundwater model predictions are often uncertain due to inherent uncertainties in model input data. Monitored field data are commonly used to assess the performance of a model and reduce its prediction uncertainty. Given the high cost of data collection, it is imperative to identify the minimum number of required observation wells and to define the optimal locations of sampling points in space and depth.

Performance optimization and validation of ADM1 simulations under anaerobic thermophilic conditions.

In this study, two experimental sets of data each involving two thermophilic anaerobic digesters treating food waste, were simulated using the Anaerobic Digestion Model No. 1 (ADM1). A sensitivity analysis was conducted, using both data sets of one digester, for parameter optimization based on five measured performance indicators: methane generation, pH, acetate, total COD, ammonia, and an equally weighted combination of the five indicators.