Unsaturated Zone Model Research Articles

A Review of Advances in Groundwater Evapotranspiration Research

Groundwater evapotranspiration (ETg) is an important component of the hydrological cycle in water-scarce regions and is important for local ecosystems and agricultural irrigation management. However, accurate estimation of ETg is not easy due to uncertainties in climatic conditions, vegetation parameters, and the hydrological parameters of the unsaturated zone and aquifers. The current methods for calculating ETg mainly include the WTF method and the numerical groundwater model. The WTF method often requires data supplementation from the numerical unsaturated model to reduce uncertainty; in addition, it relies on point-monitoring data and cannot solve the spatial heterogeneity of ETg. The ETg calculation module of the numerical groundwater model is set up too simply and ignores the influence from the unsaturated zone and surface cover. Subsequent research breakthroughs should focus on the improvement of WTF calculation theory and the setting up of an aquifer water-table fluctuation monitoring network. The numerical groundwater model should couple the surface remote sensing data with the unsaturated zone model to improve the accuracy of ETg calculation.

Hydrodynamics of the Vadose Zone of a Layered Soil Column

Getting into the heart of the water movement into the vadose zone is essential due to the direct impact on the aquifer recharge, the flood hazards, the irrigation planning and the water resources management in general. Since soil profiles in nature appear in layers, the present study accomplishes a deep investigation of the water’s motion through soil layers with different hydraulic properties. A series of experiments were conducted in the laboratory where infiltration, tension, soil moisture and hydraulic conductivity data were collected and analyzed. In particular, a transparent column was filled with two soils (loamy sand over sand), and TDR probes, along with ceramic capsules connected to pressure transducers, were set to the column. Using the experimental data and the unsaturated zone modeling, hydraulic parameters were obtained, along with water motion simulation and prediction. An investigation into the drainage, imbibition, infiltration, soil water characteristic curves and, in general, the hydrodynamics of the vadose zone of the soil layers has been achieved. The results of the current study suggest a method to estimate the crucial hydraulic parameters that are involved in the soil-water interaction and have an impact on infiltration, runoff, aquifer horizon recharge, water management and water saving.

Stochastic Assessment of Groundwater Contamination Risks From Onshore Gas Development Using Computationally Efficient Analytical and Numerical Transport Models

Regulators require the gas industry to assess the risks of unintentional release of chemicals to the environment and implement measures to mitigate it. Industry standard models for contaminant transport in aquifers do not explicitly model processes in the unsaturated zone and groundwater models often require long run times to complete simulation of complex processes. We propose a stochastic numerical-analytical hybrid model to overcome these two shortcomings and demonstrate its application to assess the risks associated with onshore gas drilling in the Otway Basin, South Australia. The novel approach couples HYDRUS-1D to an analytical solution to model contaminant transport in the aquifer. Groundwater velocities and chemical trajectories were derived from a particle tracking analysis. The most influential parameters controlling solute delivery to the aquifer were the soil chemical degradation constant and the hydraulic conductivity of a throttle soil horizon. Only 18% of the flow paths intercepted environmental receptors within a 1-km radius from the source, 87% of which had concentrations of <1% of the source. The proposed methodology assesses the risk to environmental assets and informs regulators to implement measures that mitigate risk down to an acceptable level.

Vadose zone modeling to identify controls on groundwater recharge in an unconfined granular aquifer in a cold and humid environment with different meteorological data sources

Groundwater recharge (GR) is a complex process that is difficult to quantify. Increasing attention has been given to unsaturated zone modeling to estimate GR and better understand the processes controlling it. Continuous soil-moisture time series have been shown to provide valuable information in this regard. The objectives of this study were to (i) analyze the processes and factors controlling GR in an unconfined granular aquifer in a cold and humid environment and (ii) assess the uncertainties associated with the use of data from different sources. Soil moisture data monitored over three years at three experimental sites in southern Quebec (Canada) were used to calibrate the HYDRUS-1D model and to estimate ranges of possible GR in a region where groundwater is increasingly used as a source of fresh water. The simulations identified and quantified important factors responsible for the near-surface water balance that leads to GR. The resulting GR estimates from 2016 to 2018 showed marked differences between the three sites, with values ranging from 347 to 735 mm/y. Mean GR for the three sites was 517 mm/y for 2016–2018 and 455 mm/y for the previous 12-year period. GR was shown to depend on monthly variations in precipitation and on soil textural parameters in the root zone, both controlling soil-water retention and evapotranspiration. Monthly recharge patterns showed distinct preferential GR periods during the spring snowmelt (38–45% of precipitation) and in the fall (29% of precipitation). The use of different meteorological datasets was shown to influence the GR estimates.

Estimation of groundwater recharge in a shallow sandy aquifer using unsaturated zone modeling and water table fluctuation method

Quantification of groundwater recharge is one of the most important issues in hydrogeology, especially in view of the ongoing changes in climate and land use. In this study, we use numerical models of 1D vertical flow in the vadose zone and the water table fluctuation (WTF) analysis to investigate local-scale recharge of a shallow sandy aquifer in the Brda outwash plain in northern Poland. We show that these two methods can be jointly used to improve confidence in recharge estimation. A set of preliminary numerical simulations based on soil water content measurements from 4 grassland and pine forest profiles provided a wide range of recharge estimates (263 mm to 839 mm for a 3-year period). Additional simulations were performed with the lower boundary condition specified as a functional relationship between the groundwater table elevation and the rate of groundwater outflow from the vertical profile (horizontal drains boundary condition). In this way, we could reproduce the water table fluctuations resulting from recharge and lateral discharge to nearby lakes. The agreement between simulated and observed groundwater levels differed depending on the specific set of parameters characterizing vadose zone flow, which allowed us to find the most representative parameter sets and refine the range of plausible recharge estimates (501 mm to 573 mm per 3 years). The recharge rates from WTF (410 mm to 606 mm per 3 years) were in good agreement with numerical simulations, providing that the effect of the natural recession of groundwater table due to lateral outflow was considered (master recession curve method). Our results show that: (i) the proposed approach combining 1D vadose zone modeling and WTF improves recharge estimation, (ii) multiple types of observations, including groundwater table positions, are needed to calibrate and validate vadose zone flow models, and (iii) extended periods of observations and simulations are necessary to capture year-to-year variability in the recharge rates.

Coupling saturated and unsaturated flow: comparing the iterative and the non-iterative approach

Abstract. Fully integrated three-dimensional (3D) physically based hydrologic models usually require many computational resources. For many applications, simplified models can be a cost-effective alternative. The 3D models of subsurface flow are often simplified by coupling a 2D groundwater model with multiple 1D models for the unsaturated zone. The crucial part of such models is the coupling between the two model compartments. In this work we compare two approaches for the coupling. One is iterative where the 1D unsaturated zone models go down to the impervious bottom of the aquifer, and the other one is non-iterative and uses a moving lower boundary for the unsaturated zone. In this context we also propose a new way of treating the specific yield, which plays a crucial role in linking the unsaturated and the groundwater model. Both models are applied to three test cases with increasing complexity and analyzed in terms of accuracy and speed compared to fully integrated model runs. The non-iterative approach is faster but does not yield a good accuracy for the model parameters in all applied test cases, whereas the iterative one gives good results in all cases. Which strategy is applied depends on the requirements: computational speed vs. model accuracy.

Unsaturated zone model complexity for the assimilation of evapotranspiration rates in groundwater modelling

Abstract. The biophysical processes occurring in the unsaturated zone have a direct impact on the water table dynamics. Representing these processes through the application of unsaturated zone models of different complexity has an impact on the estimates of the volumes of water flowing between the unsaturated zone and the aquifer. These fluxes, known as net recharge, are often used as the shared variable that couples unsaturated to groundwater models. However, as recharge estimates are always affected by a degree of uncertainty, model–data fusion methods, such as data assimilation, can be used to inform these coupled models and reduce uncertainty. This study assesses the effect of unsaturated zone models complexity (conceptual versus physically based) to update groundwater model outputs, through the assimilation of actual evapotranspiration rates, for a water-limited site in South Australia. Actual evapotranspiration rates are assimilated because they have been shown to be related to the water table dynamics and thus form the link between remote sensing data and the deeper parts of the soil profile. Results have been quantified using standard metrics, such as the root mean square error and Pearson correlation coefficient, and reinforced by calculating the continuous ranked probability score, which is specifically designed to determine a more representative error in stochastic models. It has been found that, once properly calibrated to reproduce the actual evapotranspiration–water table dynamics, a simple conceptual model may be sufficient for this purpose; thus using one configuration over the other should be motivated by the specific purpose of the simulation and the information available.

Feasibility of Improving Groundwater Modeling by Assimilating Evapotranspiration Rates

AbstractWater table dynamics are linked to the atmosphere through evapotranspiration and recharge. The assimilation of observed evapotranspiration values should thus improve groundwater model results. This paper presents a method for assimilating evapotranspiration data into a coupled unsaturated zone and groundwater model using the ensemble Kalman filter. The method is tested for a synthetically generated losing stream system in climatic conditions common in South Australia. The study focused on areas with a deep (recharge area) and a shallow (extraction area) water table and an intermediate area showing seasonal variations between these two (transition area). The data assimilation algorithm consistently improved the model states in the three areas when the ensemble spread was adequate. Improvements were also obtained in the calculation of net recharge and modeled actual evapotranspiration. The results indicate the potential to improve groundwater models using remote sensing observations of actual evapotranspiration values.

Simulating deep drainage and nitrate leaching on a regional scale: implications for groundwater management in an intensively irrigated area

Groundwater management in irrigation areas requires a comprehensive understanding of the interactions between agricultural management practices and the underlying groundwater resource. Unsaturated zone modelling can be used to predict rates of water and solute movement through the soil profile. By incorporating expert knowledge and measured data, it is possible to investigate the relative influence of management vs environmental factors on water and solute movement. The Agricultural Production Systems sIMulator (APSIM) has been applied to simulate the impacts of both environmental factors and agricultural management factors on deep drainage and nitrate leaching in the Lower Burdekin, North Queensland, Australia. Based on the results of this modelling, predicted annual average deep drainage rates were found to be controlled primarily by soil properties, irrigation scheduling, and, to a lesser extent, annual rainfall. The key factors which were found to control nitrate leaching were: irrigation water quality, fertilizer application rates, soil type, crop management, and irrigation scheduling. However, increases in the concentrations of nitrate in irrigation water resulted in a 64-fold increase in predicted nitrate-leaching rates, compared with a 22-fold increase in predicted nitrate-leaching rates associated with increased fertilizer application rates. As significant quantities of nitrate are predicted to be leached below the root zone, the immediate priority should be to increase monitoring of groundwater quality with a focus on quantifying the transport of nutrients to sensitive receptors.

The development of a managed aquifer recharge project with recycled water for Chihuahua, Mexico

The groundwater supply of the city of Chihuahua, Mexico, is currently unsustainable: demand exceeds replenishment in this area of relatively low precipitation and periodic droughts. The Chihuahua basin hydrologic analysis reflects only two areas of opportunity to increase water supply: water reuse and managed aquifer recharge with treated wastewater. This paper presents the results of project studies carried out by the Institute of Engineering of the UNAM (Universidad Nacional Autónoma de México—National Autonomous University of Mexico) to define the best method for managed aquifer recharge (MAR) with treated wastewater and to identify suitable locations. The work was conducted in accordance with the Mexican guidelines for aquifer recharge with treated wastewater (NOM-014; CONAGUA NOM-014-Requisitos para la recarga artificial de acuíferos con agua residual tratada, 2007) and includes geophysical surveys and unsaturated zone modeling to design a pilot test for intermittent infiltration which will subsequently inform the feasibility and design of a large scale system to recharge 25 Mm3/year.

Utilizing unsaturated soil zone models for assessing managed aquifer recharge

Managed aquifer recharge (MAR) is increasingly used to balance out the divergence between natural groundwater recharge and overexploitation of groundwater resources. As testing and design of recharge facilities can be cost and time-intensive, modeling tools hold great potential to design field investigations as well as to augment and extrapolate from their results. Focusing on unsaturated soil zone models, this study first reviews 16 previous modeling studies showing their range of model types and applications. The review is accompanied by an example of the use of HYDRUS 2D/3D, an unsaturated zone model, to design a novel small-scale infiltration basin. The basin is going to be established as part of a field and laboratory research facility for MAR in Pirna, Germany. Modeling results assisted in determining the dimensions of the infiltration unit as well as the placement of measurement devices and experimental scenario planning. Finally, the strengths and constraints of this modeling approach for MAR assessment are discussed.

Soil moisture prediction with the ensemble Kalman filter: Handling uncertainty of soil hydraulic parameters

Abstract For predicting flow in the unsaturated zone, an adequate choice of the model parameters, especially the soil hydraulic parameters, is essential. It is difficult to determine these parameters, as the parameter estimation problem easily becomes ill-posed, e.g. due to pseudo-correlations among two or more of the unknown parameters. In the field, this problem is strongly related to the available observations which, in monitoring networks, are not optimized to be used for parameter estimation. In this paper, we investigate the potential of data assimilation using the ensemble Kalman filter (EnKF) with unsaturated zone models under conditions where model parameters are highly uncertain and not identifiable. Different ways of dealing with the parameter uncertainty, such as parameter updates and bias correction, are discussed and compared. It is shown that jointly updating all uncertain parameters and states is the best method to account for the error induced by parameter uncertainty.

Modeling nitrate from land surface to wells' perforations under agricultural land: success, failure, and future scenarios in a Mediterranean case study

Abstract. Contamination of groundwater resources by nitrate leaching under agricultural land is probably the most troublesome agriculture-related water contamination worldwide. Contaminated areas often show large spatial variability of nitrate concentration in wells. In this study, we tried to assess whether this spatial variability can be characterized on the basis of land use and standard agricultural practices. Deep soil sampling (10 m) was used to calibrate vertical flow and nitrogen-transport numerical models of the unsaturated zone under different agricultural land uses. Vegetable fields (potato and strawberry) and deciduous orchards (persimmon) in the Sharon area overlying the coastal aquifer of Israel were examined. Average nitrate–nitrogen fluxes below vegetable fields were 210–290 kg ha−1 yr−1 and under deciduous orchards were 110–140 kg ha−1 yr−1. The output water and nitrate–nitrogen fluxes of the unsaturated-zone models were used as input data for a three-dimensional flow and nitrate-transport model in the aquifer under an area of 13.3 km2 of agricultural land. The area was subdivided into four agricultural land uses: vegetables, deciduous orchards, citrus orchards, and non-cultivated. Fluxes of water and nitrate–nitrogen below citrus orchards were taken from a previous study in the area. The groundwater flow model was calibrated to well heads by changing the hydraulic conductivity. The nitrate-transport model, which was fed by the above-mentioned models of the unsaturated zone, succeeded in reconstructing the average nitrate concentration in the wells. However, this transport model failed in calculating the high concentrations in the most contaminated wells and the large spatial variability of nitrate concentrations in the aquifer. To reconstruct the spatial variability and enable predictions, nitrate fluxes from the unsaturated zone were multiplied by local multipliers. This action was rationalized by the fact that the high concentrations in some wells cannot be explained by regular agricultural activity and are probably due to malfunctions in the well area. Prediction of the nitrate concentration 40 years in the future with three nitrogen-fertilization scenarios showed that (i) under the business as usual fertilization scenario, the nitrate concentration (as NO3−) will increase on average by 19 mg L−1; (ii) under a scenario of 25 % reduction of nitrogen fertilization, the nitrate concentration in the aquifer will stabilize; (iii) with a 50 % reduction of nitrogen fertilization, the nitrate concentration will decrease on average by 18 mg L−1.

Review: Current and emerging methods for catchment-scale modelling of recharge and evapotranspiration from shallow groundwater

A review is provided of the current and emerging methods for modelling catchment-scale recharge and evapotranspiration (ET) in shallow groundwater systems. With increasing availability of data, such as remotely sensed reflectance and land-surface temperature data, it is now possible to model groundwater recharge and ET with more physically realistic complexity and greater levels of confidence. The conceptual representation of recharge and ET in groundwater models is critical in areas with shallow groundwater. The depth dependence of recharge and vegetation water-use feedback requires additional calibration to fluxes as well as heads. Explicit definition of gross recharge vs. net recharge, and groundwater ET vs. unsaturated zone ET, in preparing model inputs and reporting model results is necessary to avoid double accounting in the water balance. Methods for modelling recharge and ET include (1) use of simple surface boundary conditions for groundwater flow models, (2) coupling saturated groundwater models with one-dimensional unsaturated-zone models, and (3) more complex fully-coupled surface-unsaturated-saturated conceptualisations. Model emulation provides a means for including complex model behaviours with lower computational effort. A precise ET surface input is essential for accurate model outputs, and the model conceptualisation depends on the spatial and temporal scales under investigation. Using remote sensing information for recharge and ET inputs in model calibration or in model–data fusion is an area for future research development. Improved use of uncertainty analysis to provide probability bounds for groundwater model outputs, understanding model sensitivity and parameter dependence, and guidance for further field-data acquisition are also areas for future research.

Modeling Wet Bulb and Soil Moisture Under Drip Irrigation in of the Bolivian Highlands, Through Dimensional Analysis and Multiple Correlation

Agricultural areas of the Bolivian highlands are located between 3200-4000 meters above sea level, where soils are shallow and show great variability, which hinders the proper application of drip irrigation, as these systems are designed to achieve high efficiencies, however, technology by itself does not guarantee that. Therefore it is necessary consider in the design the wet bulb geometry and soil moisture. In this sense, the objective was to conduct mathematical modeling of wet bulb and humidity under surface drip irrigation, to soil from the highlands of Bolivia. Physical and hydrological characteristics of soil and water dynamics under drip irrigation were determined. For this we used a point source. Mathematical modeling was carried out for saturated and unsaturated zone. In the first case modeling was done using dimensional analysis, obtaining a quadratic equation for the maximum diameter of wet, reaching 28 cm for a flow rate of 1 l/h and 8 hours of irrigation, while the observed value field was 29 cm. In the unsaturated zone modeling was done by the method of multiple correlation, determining a maximum depth of 21 cm for a flow rate of 5 l/h and 4 hours of irrigation, in field a value of 20 cm was observed. Regarding the volumetric soil moiture, modeling was performed using matrix equations, observed that for high flow rates and high time irrigation, the simulated moisture was 0.52 and the observed was 0.54. In general the simulated and observed data of the three parameters had a proper fit.

Modeling Wet Bulb and Soil Moisture Under Drip Irrigation in of the Bolivian Highlands, Through Dimensional Analysis and Multiple Correlation

Agricultural areas of the Bolivian highlands are located between 3200-4000 meters above sea level, where soils are shallow and show great variability, which hinders the proper application of drip irrigation, as these systems are designed to achieve high efficiencies, however, technology by itself does not guarantee that. Therefore it is necessary consider in the design the wet bulb geometry and soil moisture. In this sense, the objective was to conduct mathematical modeling of wet bulb and humidity under surface drip irrigation, to soil from the highlands of Bolivia. Physical and hydrological characteristics of soil and water dynamics under drip irrigation were determined. For this we used a point source. Mathematical modeling was carried out for saturated and unsaturated zone. In the first case modeling was done using dimensional analysis, obtaining a quadratic equation for the maximum diameter of wet, reaching 28 cm for a flow rate of 1 l/h and 8 hours of irrigation, while the observed value field was 29 cm. In the unsaturated zone modeling was done by the method of multiple correlation, determining a maximum depth of 21 cm for a flow rate of 5 l/h and 4 hours of irrigation, in field a value of 20 cm was observed. Regarding the volumetric soil moiture, modeling was performed using matrix equations, observed that for high flow rates and high time irrigation, the simulated moisture was 0.52 and the observed was 0.54. In general the simulated and observed data of the three parameters had a proper fit.

Influence of model conceptualisation on one-dimensional recharge quantification: Uley South, South Australia

Model conceptualisation is a key source of uncertainty in one-dimensional recharge modelling. The effects of different conceptualisations on transient recharge predictions for the semi-arid Uley South Basin, South Australia, were investigated. One-dimensional unsaturated zone modelling was used to quantify the effect of variations of (1) lithological complexity of the unsaturated zone, and (2) representation of preferential flow pathways. The simulations considered ranges of water-table depths, vegetation characteristics, and top soil thicknesses representative for the study area. Complex lithological profiles were more sensitive to the selected vegetation characteristics and water-table depth. Scenarios considering runoff infiltration into, and preferential flow through sinkholes resulted in higher and faster recharge rates. A comparison of modelled and field-based recharge estimates indicated that: (1) the model simulated plausible recharge rates, (2) only the models with preferential flow correctly reproduced the timing of recharge, and (3) preferential flow is probably redistributed in the unsaturated zone rather than passing to the water table directly. Because different but equally plausible conceptual models produce widely varying recharge rates, field-based recharge estimates are essential to constrain the modelling results.

Using a bias aware EnKF to account for unresolved structure in an unsaturated zone model

[1] When predicting flow in the unsaturated zone, any method for modeling the flow will have to define how, and to what level, the subsurface structure is resolved. In this paper, we use the Ensemble Kalman Filter to assimilate local soil water content observations from both a synthetic layered lysimeter and a real field experiment in layered soil in an unsaturated water flow model. We investigate the use of colored noise bias corrections to account for unresolved subsurface layering in a homogeneous model and compare this approach with a fully resolved model. In both models, we use a simplified model parameterization in the Ensemble Kalman Filter. The results show that the use of bias corrections can increase the predictive capability of a simplified homogeneous flow model if the bias corrections are applied to the model states. If correct knowledge of the layering structure is available, the fully resolved model performs best. However, if no, or erroneous, layering is used in the model, the use of a homogeneous model with bias corrections can be the better choice for modeling the behavior of the system.

Plot-scale modeling of soil water dynamics and impacts of drought conditions beneath rainfed maize in Eastern Nebraska

Intermittent drought periods pose major challenges to the management of rainfed agricultural systems because their productivity is sensitive to water stress during crop development. The objective of this study was to assess soil water dynamics and crop stress patterns during the drought year of 2012, which was among the most severe on record in the US Corn Belt. The study utilized a continuous matric potential profile monitoring record from June 2008–December 2012 beneath a rainfed corn plot in Eastern Nebraska to provide a direct comparison of the 2012 growing season with moderate to relatively wet periods within 2008–2011. The analysis was based on a transient unsaturated zone model that was calibrated with laboratory-measured water retention functions and matric potential measurements from heat dissipation sensors. In each year of the model simulation, soil water storage volumes steadily decreased during the growing season and increased episodically following precipitation events outside of the growing season. Precipitation during the 2012 growing season was <50% of the mean for growing seasons 2009–2012 consequently, soil water storage loss during 2012 was ∼14% of initial storage in comparison to 8–9% in 2009–2011. Model results suggest that the 2012 soil water deficit was partially buffered by upward flux of deep soil moisture, with approximately 17% of root water uptake in 2012 deriving from moisture redistributed from below the root zone. Nevertheless, root zone matric potentials exceeded the crop wilting point (ψ=−8000cm) in 2012 for the first time within the monitoring record. These results highlight the need for heightened attention to drought resilience of rainfed cropping systems given future climate predictions that involve increase rainfall intermittency.

Parameter and predictive outcomes of model simplification

Simplification is an unavoidable aspect of model usage. Even complex, physically based models are simplifications of reality. More profound simplification is required to construct the “lumped parameter” models of semiphysical basis that are often employed for simulation of large‐scale processes operative over one or many watersheds. Simplification can lead to model predictive error beyond that which would be expected on the basis of study‐area information deficits alone. Building on a recently developed mathematical description of the model simplification process, this work employs linear subspace methods to analyze in detail the nature and ramifications of that process when applied to a 1‐D, Richards equation‐based unsaturated zone model used to predict recharge to a groundwater system. Two simplified versions of this model are examined. The first achieves simplification through assuming vertical parameter uniformity. The second achieves simplification through use of a lumped parameter model in place of the Richards equation‐based model. Relationships between parameters employed by the complex model and those used by each of the simplified models are analyzed. The nature of predictive errors incurred through simplification is explored. Also explored is the ability of the calibration process to decrease the propensity for model error in making some predictions, while increasing the propensity for model error in the making of others (an outcome that may be considered counterintuitive from a Bayesian perspective, but which is a natural consequence of suboptimal simplification).