Understanding and Predicting Vadose Zone Processes

Vadose zone hydrologic and biogeochemical processes play a significant role in the capture, storage and distribution of contaminants between the land surface and groundwater. One major issue facing geoscientists in dealing with investigations of the unsaturated zone flow and transport processes is the evaluation of heterogeneity of subsurface media. This chapter presents a summary of approaches for monitoring and modeling of vadose zone dynamics in the presence of heterogeneities and complex features, as well as incorporating transient conditions. Modeling results can then be used to provide early warning of soil and groundwater contamination before problems arise, provide scientific and regulatory credibility to environmental management decision-making process to enhance protection of human health and the environment. We recommend that future studies target the use of RTMs to identify and quantify critical interfaces that control large-scale biogeochemical reaction rates and ecosystem functioning. Improvements also need to be made in devising scaling approaches to reduce the disconnect between measured data and the scale at which processes occur

Characterization of a Shallow Coastal Aquifer in the Framework of a Subsurface Storage and Soil Aquifer Treatment Project using Electrical Resistivity Tomography (Port de la Selva, Spain)

Water percolation through infiltration ponds is creating significant synergies for the broad adoption of water reuse as an additional non-conventional water supply. Despite the apparent simplicity of the soil aquifer treatment (SAT) approaches, the complexity of site-specific hydro-geological conditions and the processes occurring at various scales require an exhaustive under-standing of the system's response. The non-saturated zone and underlying aquifers cannot be considered as a black box, nor accept its characterization from few boreholes not well distribut-ed over the area to be investigated. The electrical resistivity tomography (ERT) is a non-invasive technology, highly responsive to geological heterogeneities that has demonstrated useful to provide the detailed subsurface information required for groundwater modeling. The relation-ships between the electrical resistivity of the alluvial sediments and the bedrock and the differ-ence in salinity of groundwater, highlight the potential of geophysical methods over other more costly subsurface exploration techniques. The results of our research show that ERT coupled with implicit modeling tools provides information that can significantly help to identify aquifer geometry and characterize the saltwater intrusion of shallow alluvial aquifers. The proposed approaches could improve the reliability of groundwater models and the commitment of stakeholders to the benefits of SAT procedures

Ground, Proximal, and Satellite Remote Sensing of Soil Moisture

Soil moisture (SM) is a key hydrologic state variable that is of significant importance for numerous Earth and environmental science applications that directly impact the global environment and human society. Potential applications include, but are not limited to, forecasting of weather and climate variability; prediction and monitoring of drought conditions; management and allocation of water resources; agricultural plant production and alleviation of famine; prevention of natural disasters such as wild fires, landslides, floods, and dust storms; or monitoring of ecosystem response to climate change. Because of the importance and wide‐ranging applicability of highly variable spatial and temporal SM information that links the water, energy, and carbon cycles, significant efforts and resources have been devoted in recent years to advance SM measurement and monitoring capabilities from the point to the global scales. This review encompasses recent advances and the state‐of‐the‐art of ground, proximal, and novel SM remote sensing techniques at various spatial and temporal scales and identifies critical future research needs and directions to further advance and optimize technology, analysis and retrieval methods, and the application of SM information to improve the understanding of critical zone moisture dynamics. Despite the impressive progress over the last decade, there are still many opportunities and needs to, for example, improve SM retrieval from remotely sensed optical, thermal, and microwave data and opportunities for novel applications of SM information for water resources management, sustainable environmental development, and food security

Stochastic inversion for soil hydraulic parameters in the presence of model error: An example involving ground-penetrating radar monitoring of infiltration

International audienceProxy forward solvers are commonly used in Bayesian solutions to inverse problems in hydrology and geophysics in order to make sampling of the posterior distribution, for example using Markov-chain-Monte-Carlo (MCMC) methods, computationally tractable. However, use of these solvers introduces model error into the problem, which can lead to strongly biased and overconfident parameter estimates if left uncorrected. Focusing on the specific example of estimating unsaturated hydraulic parameters in a layered soil from time-lapse ground-penetrating radar data acquired during a synthetic infiltration experiment, we show how principal component analysis, conducted on a suite of stochastic model-error realizations, can for some problems be used to build a sparse orthogonal basis for the model error arising from known forward solver approximations and/or simplifications. Projection of the residual onto this basis during MCMC permits identification and removal of the model error before calculation of the likelihood. Our results indicate that, when combined with an informal likelihood metric based on the expected behaviour of the -norm of the residual, this methodology can yield posterior parameter estimates exhibiting a marked reduction in bias and overconfidence when compared to those obtained with no model-error correction, at reasonable computational cost

Incorporating Physics-Based Patterns into Geophysical and Geostatistical Estimation Algorithms

Geophysical imaging systems are inherently non-linear and plagued with the challenge of limited data. These drawbacks make the solution non-unique and sensitive to small data perturbations; hence, regularization is performed to stabilize the solution. Regularization involves the application of a priori specification of the target to modify the solution space in order to make it tractable. However, the traditionally applied regularization model constraints are independent of the physical mechanisms driving the spatiotemporal evolution of the target parameters. To address this limitation, we introduce an innovative inversion scheme, basis-constrained inversion, which seeks to leverage advances in mechanistic modeling of physical phenomena to mimic the physics of the target process, to be incorporated into the regularization of hydrogeophysical and geostatistical estimation algorithms, for improved subsurface characterization. The fundamental protocol of the approach involves the construction of basis vectors from training images, which are then utilized to constrain the optimization problem. The training dataset is generated via Monte Carlo simulations to mimic the perceived physics of the processes prevailing within the system of interest. Two statistical techniques for constructing optimal basis functions, Proper Orthogonal Decomposition (POD) and Maximum Covariance Analysis (MCA), are employed leading to two inversion schemes. While POD is a static imaging technique, MCA is a dynamic inversion strategy. The efficacies of the proposed methodologies are demonstrated based on hypothetical and lab-scale flow and transport experiments

Geostatistical analysis of flows in the vadose zone

The thesis aims to evaluate the theoretical-applicative aspects related to the monitoring and forecasting of soil water dynamics at practical interest scale. The work is focused on the development of models for the description of water flow in homogeneous and heterogeneous soils and the resolution of them. The spatial variations of the hydraulic properties of the soil and of the solute concentration are a consequence of soil heterogeneity. Therefore, considering these variations as a consequence of a limited knowledge of the porous medium, methods will be developed that allow to estimate the mains tatistical indices of the transport process variables, namely: watercontent, pressure head, hydraulic conductivity and solute concentration. The validity of the predictions of mathematical models is linked not only to the correct schematisation adopted to describe the physical phenomena involved in the processes during the study, but also by their validation with reference to a typical case of study

Gravimetry for monitoring water mass movements in karstic areas

Karst aquifers represent a significant source of water for about 1/4 of the world\u2019s population. The water circulation in karst occurs mostly underground and it is mainly controlled by alternation of small conduits and large voids present in the rock massif. Such intricate void distribution combined with an irregular recharge provided by the rain results in fast and complex water flows with temporary accumulation of huge water volumes in the voids. The knowledge of the dynamics of such system is usually limited to the areas where a direct access to the vadose zone through speleological exploration is possible. Given the importance of such aquifers and their vulnerability it is important to have a detailed picture of the water dynamics and of the underground water paths. Gravimetry offers a valid complement to classical hydrologic measurements in order to monitor the recharge process. In this thesis, I show an innovative integration of gravimetric and hydrologic observations to constrain a hydrodynamic model of the \u160kocjan cave system (Slovenia). The \u160kocjan caves hydrology is mostly governed by the allogenic contribution of the Reka River, which during flood event causes the accumulation of several millions of m3 of water in the cave system for few hours. In 2018 I installed a continuous recording gravimeter nearby \u160kocjan which allowed the detection of several gravity transients related to the local hydrologic contribution. Gravity observations are sensitive to several other contributions apart the hydrology, such as Earth and marine tides, atmospheric mass redistribution, water mass variations in oceans. All these phenomena superpose their effects and should be carefully evaluated and removed before unveiling the local hydrology contribution. Before discussing the hydrologic gravity signals, the thesis illustrates the efforts in modelling and removing all the non-hydrologic related gravity contributions. The study area is close to the Adriatic Sea, hence global models of tidal and non-tidal ocean (NTO) gravity effects could be inadequate for the correction. I prove that while tidal models are sufficiently accurate to remove the marine tidal influence a dedicated correction of the NTO is required. This was fulfilled by modelling the gravity variations due to a 4D mass model of the NTO constrained by tide gauge observations. The gravity residuals, obtained after reducing the observations for all the non-hydrologic effects, revealed anomalies correlated to the Reka flooding; the transients lasted for 12-24 hours with amplitudes in the range 10-450 nm/s2. I focused my analysis on a large flood event in February 2019 that caused water level variations >90 m inside the caves and gravity variations >400 nm/s2. The gravity and the hydrologic data were used to constrain a hydraulic model of the cave system which approximated the cavity through a series of interconnected conduits with rectangular cross-section. I fitted hydrologic and gravity observations obtaining a 4D model of the water mass variations in the cave system; the model revealed that >3 106 m3 of water were temporary accumulated during the peak\u2019s flood. The inclusion of gravity observations improves water mass budget of the caves, which previously were based relying only on hydrological observations. Finally, the gravity data allowed to draw some general conclusions on the detectability of water storage variations in karst through gravimetry. I assessed the noise level of the \u160kocjan gravimeter which is about 10 nm/s2 in the diurnal spectral band and which can be taken as representative of the noise level of a typical spring based gravimeter. Relying on realistic water level variations I estimated the expected gravity signals on surface due to temporary water accumulation in other caves of the Classical Karst. For all the considered caves the gravity signal is above the noise threshold, suggesting that a remote monitoring of the storage variations is feasible.Karst aquifers represent a significant source of water for about 1/4 of the world\u2019s population. The water circulation in karst occurs mostly underground and it is mainly controlled by alternation of small conduits and large voids present in the rock massif. Such intricate void distribution combined with an irregular recharge provided by the rain results in fast and complex water flows with temporary accumulation of huge water volumes in the voids. The knowledge of the dynamics of such system is usually limited to the areas where a direct access to the vadose zone through speleological exploration is possible. Given the importance of such aquifers and their vulnerability it is important to have a detailed picture of the water dynamics and of the underground water paths. Gravimetry offers a valid complement to classical hydrologic measurements in order to monitor the recharge process. In this thesis, I show an innovative integration of gravimetric and hydrologic observations to constrain a hydrodynamic model of the \u160kocjan cave system (Slovenia). The \u160kocjan caves hydrology is mostly governed by the allogenic contribution of the Reka River, which during flood event causes the accumulation of several millions of m3 of water in the cave system for few hours. In 2018 I installed a continuous recording gravimeter nearby \u160kocjan which allowed the detection of several gravity transients related to the local hydrologic contribution. Gravity observations are sensitive to several other contributions apart the hydrology, such as Earth and marine tides, atmospheric mass redistribution, water mass variations in oceans. All these phenomena superpose their effects and should be carefully evaluated and removed before unveiling the local hydrology contribution. Before discussing the hydrologic gravity signals, the thesis illustrates the efforts in modelling and removing all the non-hydrologic related gravity contributions. The study area is close to the Adriatic Sea, hence global models of tidal and non-tidal ocean (NTO) gravity effects could be inadequate for the correction. I prove that while tidal models are sufficiently accurate to remove the marine tidal influence a dedicated correction of the NTO is required. This was fulfilled by modelling the gravity variations due to a 4D mass model of the NTO constrained by tide gauge observations. The gravity residuals, obtained after reducing the observations for all the non-hydrologic effects, revealed anomalies correlated to the Reka flooding; the transients lasted for 12-24 hours with amplitudes in the range 10-450 nm/s2. I focused my analysis on a large flood event in February 2019 that caused water level variations >90 m inside the caves and gravity variations >400 nm/s2. The gravity and the hydrologic data were used to constrain a hydraulic model of the cave system which approximated the cavity through a series of interconnected conduits with rectangular cross-section. I fitted hydrologic and gravity observations obtaining a 4D model of the water mass variations in the cave system; the model revealed that >3 106 m3 of water were temporary accumulated during the peak\u2019s flood. The inclusion of gravity observations improves water mass budget of the caves, which previously were based relying only on hydrological observations. Finally, the gravity data allowed to draw some general conclusions on the detectability of water storage variations in karst through gravimetry. I assessed the noise level of the \u160kocjan gravimeter which is about 10 nm/s2 in the diurnal spectral band and which can be taken as representative of the noise level of a typical spring based gravimeter. Relying on realistic water level variations I estimated the expected gravity signals on surface due to temporary water accumulation in other caves of the Classical Karst. For all the considered caves the gravity signal is above the noise threshold, suggesting that a remote monitoring of the storage variations is feasible

Review of soil salinity assessment for agriculture across multiple scales using proximal and/or remote sensors

Mapping and monitoring soil spatial variability is particularly problematic for temporally and spatially dynamic properties such as soil salinity. The tools necessary to address this classic problem only reached maturity within the past 2 decades to enable field- to regional-scale salinity assessment of the root zone, including GPS, GIS, geophysical techniques involving proximal and remote sensors, and a greater understanding of apparent soil electrical conductivity (ECa) and multi- and hyperspectral imagery. The concurrent development and application of these tools have made it possible to map soil salinity across multiple scales, which back in the 1980s was prohibitively expensive and impractical even at field scale. The combination of ECa-directed soil sampling and remote imagery has played a key role in mapping and monitoring soil salinity at large spatial extents with accuracy sufficient for applications ranging from field-scale site-specific management to statewide water allocation management to control salinity within irrigation districts. The objective of this paper is: (i) to present a review of the geophysical and remote imagery techniques used to assess soil salinity variability within the root zone from field to regional scales; (ii) to elucidate gaps in our knowledge and understanding of mapping soil salinity; and (iii) to synthesize existing knowledge to give new insight into the direction soil salinity mapping is heading to benefit policy makers, land resource managers, producers, agriculture consultants, extension specialists, and resource conservation field staff. The review covers the need and justification for mapping and monitoring salinity, basic concepts of soil salinity and its measurement, past geophysical and remote imagery research critical to salinity assessment, current approaches for mapping salinity at different scales, milestones in multi-scale salinity assessment, and future direction of field- to regional-scale salinity assessment