in this paper, a modeling tool for risk assessment analysis of the movement of hydrocarbon contaminants in the vadose zone and mass flux of contamination release into the groundwater table was developed. also, advection-diffusion-reaction equations in combination with a three-phase equilibrium state between trapped air, soil humidity, and solid particles of unsaturated soil matrix were numerica...

background: groundwater nitrate pollution is an important environmental problem in water resources management. in this regard, specific measures aiming at prevention of water pollution will be helpful to managers and decision-makers. identification of aquifers’ vulnerable areas and determination of groundwater protection zones using most widely used models, such as drastic and cd, are one of th...

The unsaturated zone consists of a complex arrangement of solid, liquid, and gaseous phases, most of them interconnected. The spatial distribution and geometrical arrangement of each phase, and the partitioning of solutes between phases, are controlled by physical, chemical, and biological processes. Since the upper part of the vadose zone is the most dynamic region, and controls the further do...

RESEARCH OBJECTIVE The objective of this study is to to characterize and analyze in-situ flow and transport within the vadose zone during a mid-scale hydrologic infiltration experiment. This project has employed numerical and experimental tools developed under a previously funded EMSP proposal (project number 55332) to provide 3-D unsaturated hydrologic property distributions. In the present pr...

A VDEAL (V is the lithology of the vadose zone, D is the groundwater depth, E is the degree of groundwater exploitation, A is the aquifer characteristics and L is the land use pattern.) model, which is suitable for a vulnerability evaluation of the groundwater in arid inland areas, and that is based on the GOD (G is the groundwater status, O is overburden feature and D is groundwater depth) met...

Artificial intelligence (AI) and machine learning (ML) have been recently applied extensively in various disciplines of vadose zone hydrology. However, not much attention has paid to their database-dependent accuracy uncertainty, reproducibility, delivery, which undermines applications real-world problems. We discuss lessons from the past emphasize need for lack fundamental protocols (i.e., det...