Estimation Of Hydraulic Parameters Research Articles

Reconstruction of Nearshore Surface Gravity Wave Heights From Distributed Acoustic Sensing Data

AbstractDistributed Acoustic Sensing (DAS) is a photonics technology converting seafloor telecommunications and optical fiber cables into dense arrays of strain sensors, allowing to monitor various oceanic physical processes. Yet, several applications are hindered by the limited knowledge of the transfer function between geophysical variables and DAS measurements. This study investigates the quantitative relationship between surface gravity DAS‐recorded wave‐generated strain signals along the seafloor and the pressure at a colocated sensor. A remarkable linear correlation is found over various sea conditions allowing us to reliably determine significant wave heights from DAS data. Utilizing linear wave potential theory, we derive an analytical transfer function linking cable deformation and wave kinematic parameters. This transfer function provides a first quantification of the effects related to surface gravity waves and fiber responses. Our results validate DAS's potential for real‐time reconstruction of the surface gravity wave spectrum over extended coastal areas. It also enables the estimation of waves hydraulic parameters at depth without the need from offshore deployments.

Examining innovative unsupervised learning techniques for automated characterization of complex groundwater systems

This research proposes an innovative approach utilizing geophysical well logging data analyzed with multiple machine learning (ML) methods including, self-organizing maps (SOMs), k-means cluster analysis (CA), and most frequent value-assisted cluster analysis (MFV-CA), to automatically identify lithological variation within a complex groundwater system. The MFV method is introduced to enhance cluster center identification. In MFV, an automatedly weighted Euclidean distance is applied in which closer data points are assigned higher weights that emphasize their proximity within clusters. This method proved to be efficient, however, to ensure robustness, an innovative histogram-based selection method is employed for initial cluster center positioning to minimize the risk of choosing an inappropriate starting value. The proposed methodology is tested on the Quaternary aquifer system in the Debrecen area, Eastern Hungary which is known for its high lithological heterogeneity. The results were evaluated in both 1D and 2D to reveal the vertical and horizontal distribution of the lithofacies. Accordingly, the histogram-based MFV-CA demonstrated exceptional noise rejection capabilities and efficient recognition of lithological clusters. Moreover, the continuous estimation of hydraulic parameters including hydraulic conductivity and critical flow velocity along the hydrostratigraphical units showed a close agreement with the identified lithological units.

Semi-Analytical Modeling of Transient Stream Drawdown and Depletion in Response to Aquifer Pumping.

Analytical and semi-analytical models for stream depletion with transient stream stage drawdown induced by groundwater pumping are developed to address a deficiency in existing models, namely, the use of a fixed stream stage condition at the stream-aquifer interface. Field data are presented to demonstrate that stream stage drawdown does indeed occur in response to groundwater pumping near aquifer-connected streams. A model that predicts stream depletion with transient stream drawdown is developed based on stream channel mass conservation and finite stream channel storage. The resulting models are shown to reduce to existing fixed-stage models in the limit as stream channel storage becomes infinitely large, and to the confined aquifer flow with a no-flow boundary at the streambed in the limit as stream storage becomes vanishingly small. The model is applied to field measurements of aquifer and stream drawdown, giving estimates of aquifer hydraulic parameters, streambed conductance, and a measure of stream channel storage. The results of the modeling and data analysis presented herein have implications for sustainable groundwater management.

High-Resolution Estimation of Soil Saturated Hydraulic Conductivity via Upscaling and Karhunen–Loève Expansion within DREAM(ZS)

Quantification of the soil hydraulic conductivity is key to the study of water flow and solute transport in unsaturated soils. Rapid advances in measurement technology have provided a large number of observations at different scales, offering unprecedented opportunities and challenges for the estimation of hydraulic parameters. This paper proposes an inverse estimation method for downscaling of observations on coarse scales to estimate hydraulic parameters on high-resolution scales. Due to the significant spatial heterogeneity, the inversion faces the problems of dynamics-based integration of data at different scales, model uncertainty due to hundreds and thousands of parameters, and computational consumption due to the large number of forward simulations. To overcome these problems, this paper uses an efficient Bayesian optimization DREAM(ZS) as an inverse framework, and incorporates an analytical upscaling method and Karhunen–Loève (KL) expansion to infer finer-scale saturated hydraulic conductivity distribution conditioned on coarse-scale measurements. The efficient upscaling method is used to link measurements and hydraulic parameters at different scales, and Karhunen–Loève (KL) expansion is incorporated to greatly reduce the dimension of the parameter to be estimated. To further improve the efficiency of the inversion, a locally one-dimensional (LOD) algorithm is used to solve the multidimensional water flow model at coarse scales. The proposed inverse model is applied in a series of numerical experiments to demonstrate its applicability and effectiveness under different flow boundary conditions, different levels of ratio between coarse- and fine-scale grids, different densities of observation points, and different degrees of statistic heterogeneity of soil mediums.

Uncertainty assessment of aquifer hydraulic parameters from pumping test data

Data from pumping tests is a noisy process, and therefore, performing the pumping test numerous times will not get the same drawdown values. As a consequence, various pumping experiments lead to different values for aquifer parameter estimates. The data of pumping tests are usually analyzed using traditional methods (aquifer tests and AQtesolv software), which depend on trial and error technique. During these methods, non-unique values of hydraulic parameters are selected, which usually have a high level of uncertainty. Uncertainty must be taken into account in determining aquifer parameters, especially when using groundwater models for decision makers. The main goal of this study is to build a comprehensive tool for quantifying uncertainty associated with hydraulic parameter estimation from different pumping test conditions for fully penetrating wells in confined and semi-confined aquifers. To achieve the previous objective, a FORTRAN code was developed to apply the Markov Chain Monte Carlo (MCMC) algorithm using different likelihood functions (exponential, inverse, and log). This developed tool can be used to detect the most probable range of aquifer parameters that are consistent with pumping test data with a high degree of confidence. The tool was successfully used to several hypothetical cases to demonstrate the uncertainty in the quantification of aquifer parameters and compare the findings to the standard method's results. Also, the concept was verified numerically (using Modflow program) with satisfactory results using a hypothetical case with well-known aquifer parameters. Finally, the tool was applied for actual pumping test data with good results.

A new analytical method for estimating hydraulic parameters of a nonlinear consolidated aquitard with variable drawdown in adjacent aquifers

Estimation of hydraulic parameters and groundwater depletion of aquitards is necessary to evaluate the groundwater resources and land subsidence. In this study, an analytical solution for water release from a nonlinear consolidated aquitard was derived by approximating the drawdown history as a continuous piecewise linear drawdown function (PLD) with several stages, while the water level in adjacent aquifers varies arbitrarily over time. According to dimensionless and parameter sensitivity analyses, groundwater depletion of an aquitard increases with an increase in compression index, aquitard thickness, and water drawdown rate in adjacent aquifers, decreases with an increase in initial void ratio and effective stress, and is not affected by the consolidation coefficient. In addition, we proposed a type-curve fitting method to calculate the hydraulic parameters of the aquitard under the condition of PLD in adjacent aquifers. The proposed method was applied to estimate the hydraulic parameters of aquitards at two field sites in the Yangtze River Delta in China, i.e., Changzhou and Shanghai. Results show that the compression index of the aquitards in Changzhou and Shanghai are 0.074 and 0.24, respectively, while the consolidation coefficients are 7.62 × 10-7 m2/s and 2.16 × 10-6 m2/s, respectively. The hydraulic conductivity and specific storage estimated by the proposed method are in good agreement with previous studies and the results of the geological method of Konikow and Neuzil (2007). The proposed analytical method for estimating hydraulic parameters and groundwater depletion of aquitards will contribute to the sustainable management of groundwater resources in multi-layer aquifer systems.

Evaluation of aquifer parameters through integrated approach of geophysical investigations, pumping test analysis and Dar-Zarrouk parameters in the central part of Bari Doab, Punjab, Pakistan.

In the central part of Bari Doab in Punjab Province of Pakistan, the factors such as sporadic rainfall pattern, decrement of water in rivers, subsurface salinity and excessive mining of groundwater have badly affected the hydrogeology and recharge system of aquifer. The present research work is an endeavour to evaluate the characteristics and potential of aquifer for its future sustainable availability within the study area of central part of Bari Doab. The geophysical studies, pumping tests data, borehole logs and Dar-Zarrouk parameters were used integrally to evaluate the aquifer hydraulic and hydrologic parameters in the study area. VES technique of geophysical investigations using Schlumberger electrodes configuration was carried out at sparsely distributed 435 locations. Litho-logs and VES results altogether decipher that the subsurface alluvial succession is primarily composed of intermixed layers of sand, gravel, clay, silt and some kankar inclusions. The VES data allied with pumping test analysis of test wells in the study area were used to evaluate the aquifer hydraulic properties. Comparatively low values of discharge rate, hydraulic conductivity and transmissivity were evaluated in two wells whilst relatively higher values of these parameters were evaluated in rest of six wells. The results of hydrologic parameters also confirm the results of hydraulic parameters in the wells. Finally, the Dar-Zarrouk parameters were used for the estimation of hydraulic parameters for whole study area and the aquifer zones of relatively high and low potential were delineated.

Stiff, Smooth, and Solid? Complex Fracture Hydraulics' Imprint on Oscillatory Hydraulic Testing

AbstractFractured bedrock aquifers, especially deep aquifers, represent increasingly common targets for waste storage and alternative energy development, necessitating detailed quantitative descriptions of fracture hydraulic properties, geometry, and connectivity. Yet, multi‐scale characterization of the physical properties that govern fluid flow through and storage in fractured bedrock remains a fundamental hydrogeologic challenge. Oscillatory hydraulic testing, a novel hydraulic characterization technique, has been showing promise in field experiments to characterize the effective hydraulic properties of bedrock fractures. To date, these characterization efforts utilize simplified diffusive analytical models that conceptualize a non‐deforming, parallel‐plate fracture embedded within impermeable host rock, and have found that the returned fracture hydraulic parameter estimates exhibit an apparent period‐dependence. We conduct synthetic experiments using three different numerical models to examine proposed mechanisms that might contribute to the observed period‐dependence including heterogeneous flow and storage within the fracture (i.e., aperture heterogeneity), fracture‐host rock fluid exchange, and fracture hydromechanics. This work represents the first systematic analysis that seeks to understand the process(es) occurring within a bedrock fracture that might be contributing to this apparent period‐dependence. Our analysis demonstrates that all investigated mechanisms generate period‐dependent effective hydraulic parameter estimates, each with their own potentially diagnostic trends; however, fracture hydromechanics is the only explored mechanism that consistently reproduces period‐dependent trends in parameter estimates that are consistent with existing field investigations. These results highlight the need to develop more complex numerical modeling approaches that account for this hydromechanical behavior when characterizing fractured bedrock aquifers.

A Novel Analytical Solution for Ponded Infiltration With Consideration of a Developing Saturated Zone

AbstractPonding at the soil surface exerts profound impacts on infiltration. However, the effects of ponding depth on infiltration, especially the development of a saturated zone below the soil surface, have yet to be considered in present infiltration models. A new general Green‐Ampt model solution (GAMS) was derived for a one‐dimensional vertical infiltration problem under a uniform initial moisture distribution with ponding on its surface. An expression was included in the new solution for simulating the saturated layer developed below the soil surface as long as the pressure head at the surface is sufficiently high to saturate the soil. The GAMS simulates the infiltration processes closer to the numerical solution by HYDRUS‐1D than the traditional and the recently improved Green‐Ampt model. Moreover, an inversion method to improve the estimates of soil hydraulic parameters from one‐dimensional vertical infiltration experiments that is based on the GAMS was suggested. The effect of ponding depth (hp), initial soil moisture content, soil texture, and hydraulic soil properties (saturated hydraulic conductivity Ks, water‐entry suction hd and shape coefficient n of soil water retention curve) in the saturated zone was also evaluated. The results indicate that the saturated zone length increased at a comparable rate with the unsaturated wetted zone length during infiltration. Generally, a larger saturated zone was found for soils with higher initial soil moisture contents, coarser texture, higher Ks values, greater n, and lower −hd. Our findings reveal that including the saturated zone in the infiltration model yields a better estimate of the soil hydraulic parameters. The proposed GAMS model can improve irrigation design and rainfall‐runoff simulations.

An in-depth analysis of Markov-Chain Monte Carlo ensemble samplers for inverse vadose zone modeling

This study elucidates the behavior of Markov-Chains Monte Carlo ensemble samplers for vadose zone inverse modeling by performing an in-depth comparison of four algorithms that use Affine-Invariant (AI) moves or Differential Evolution (DE) strategies to approximate the target density. Two Rosenbrock toy distributions, and one synthetic and one actual case study focusing on the inverse estimation of soil hydraulic parameters using HYDRUS-1D, are used to compare samplers in different dimensions d. The analysis reveals that an ensemble with N=d+1 chains evolved using DE-based strategies converges to the wrong stationary posterior, while AI does not suffer from this issue but exhibits delayed convergence. DE-based samplers regain their ergodic properties when using N≥2d chains. Increasing the number of chains above this threshold has only minor effects on the samplers’ performance, while initializing the ensemble in a high-likelihood region facilitates its convergence. AI strategies exhibit shorter autocorrelation times in the 7d synthetic vadose zone scenario, while DE-based samplers outperform them when the number of soil parameters increases to 16 in the actual scenario. All evaluation metrics degrade as d increases, thus suggesting that sampling strategies based only on interpolation between chains tend to become inefficient when the bulk of the posterior lays in increasingly small portions of the parameters’ space.

Turbulence Kinetic Energy and High-Order Moments of Velocity Fluctuations of Flows in the Presence of Submerged Vegetation in Pools

The flow in arid and semi-arid regions changes significantly during seasons, letting many vegetation patches develop in different parts of rivers. In the presence of aquatic plants in streams, different flow structures have resulted. When the water level increases in these rivers, the presence of vegetation patches influences the turbulent flow structures, which may considerably change the estimation of key hydraulic parameters. The results of earlier investigations indicated that a wide range of submerged and non-submerged vegetation influences the hydrodynamic features of flows in rivers and streams. In the present investigation, two pools with various slopes of entry and exit sections were used to conduct eight independent experiment runs. In addition, a vegetation patch over the entire pool section has been set up to investigate the effects of the vegetation patch on flow structures in pools. The effect of two slopes of 5 and 10 degrees for both entrance and exit of the pools on flow structure has been investigated. Considering two aspect ratios of 2.0 and 2.7, the distributions of flow velocity, Reynolds normal and shear stresses, turbulence intensities, turbulent kinetic energy (TKE), quadrant analysis, and spectral analysis have been studied at the trailing edge of the vegetation patch along an artificial pool. Results show that, for large entrance and exit slopes (10 degrees), the TKE distribution profiles have no specific form. However, the TKE values have a convex-shaped distribution pattern with the maximum TKE value near the bed when the slopes of the entrance and exit sections of the pool are small (5 degrees). Results showed that both ejections and sweeps govern the turbulence structures and coherent motions at the trailing edge of the vegetation patch along the pool. The geometry, entrance, and exit slopes of the pool have no effect on the validation of power spectral function compared to the presence of a vegetation patch in a flatbed.

Three‐Dimensional Steady‐State Hydraulic Tomography Analysis With Integration of Cross‐Hole Flowmeter Data at a Highly Heterogeneous Site

AbstractHydraulic tomography (HT) has been shown to be a robust approach for the high‐resolution characterization of subsurface heterogeneity. However, HT can yield smooth estimates of hydraulic parameters when pumping tests and drawdown measurements are sparse, thus limiting the utility of characterization results in predicting groundwater flow and solute transport. To overcome this issue, this study integrates cross‐hole flowmeter measurements with HT analysis of steady‐state pumping/injection test data for the three‐dimensional (3‐D) characterization of hydraulic conductivity (K) at a highly heterogeneous glaciofluvial deposit site, which has not been previously attempted. Geostatistical inverse analyses of cross‐hole flowmeter data are conducted to yield preliminary estimates of K distribution, which are then utilized as initial K fields for steady‐state HT analysis of head data. Four cases combining three data types (geological information, cross‐hole flowmeter measurements, and steady‐state head data) for inverse modeling are performed. Model calibration and validation results from all cases are compared qualitatively and quantitatively to evaluate their performances. Results from this study show that (a) geostatistical inverse analysis of cross‐hole flowmeter data is capable in revealing vertical distributions of K at well locations and major high/low K zones between wells, (b) cross‐hole flowmeter data carry non‐redundant information of K heterogeneity compared to geological information and steady‐state head data, and (c) integration of flowmeter data improves characterization results in terms of revealing K heterogeneity details and predicting independent hydraulic test data. Therefore, this study demonstrates the usefulness of cross‐hole flowmeter data in augmenting HT surveys for improved K characterization in 3‐D.

Reduce uncertainty in soil hydrological modeling: A comparison of soil hydraulic parameters generated by random sampling and pedotransfer function

Numerical simulation of unsaturated soil hydrology relies on calibrated soil hydraulic parameters, which are subject to uncertainty due to imperfect information during the inverse modelling. This study investigates the effectiveness of reducing parameter uncertainty using the recently developed Rosetta 3 pedotransfer function. The GLUE method was employed for numerical modeling using the Darcy-Richards equation under two strategies for sampling Mualem-van Genuchten (MvG) parameters: the first uses conventional random generation of MvG parameters (GLUE-random), while the second adopts Rosetta 3 to transfer soil particle composition to MvG parameter (GLUE-Rosetta). Both approaches were used for inverse modeling of 9 typical soils, each with a recommended parameter set defined as true values and associated soil moisture dynamics as observations. The posterior parameters selected with both GLUE-random and GLUE-Rosetta show an equifinality phenomenon. GLUE-random fails to provide well-constrained posterior parameters to recover the pre-defined true values, and its posterior results of soil water characteristic curve (SWCC) and soil hydraulic conductivity function (HCF) are poorly constrained. In contrast, GLUE-Rosetta significantly improves the accuracy of the inversely-estimated soil hydraulic parameters, and the ensemble of posterior SWCC and HCF also encompasses the predefined true curves. The results demonstrate the effectiveness of using Rosetta 3 to reduce the dimensionality of the optimization problem, which results in reliable estimation of soil hydraulic parameters and soil particle compositions. Moreover, GLUE-Rosetta outperforms GLUE-random in predicting soil moisture dynamics under different rainfall intensities. Overall, it is recommended to integrate Rosetta 3 with existing optimization tools to reduce the uncertainty of soil parameters and support more reliable modeling of unsaturated soil hydrology.

Effect of different underlying surfaces on hydraulic parameters of overland flow

The estimation of hydraulic parameters is the basis for establishing soil erosion models. However, the underlying surfaces greatly influence the hydraulic parameters of the overland flow. Since sediment flow and slope surface resistance interact, exploring the mechanism of overland flow movement in relation to different underlying surfaces is essential. A potential relationship between hydrodynamic parameters and slope gradient and flow discharge was investigated by carrying out overland flow experiments, which used four types of non-erosion slope surfaces (stem cover, brown soil, frozen soil, and organic glass), four slope gradients (3°, 6°, 9°, and 12°), and four flow discharges (0.35, 0.45, 0.55, and 0.65 L s–1). The results showed that the hydraulic parameters (i.e., mean flow velocity, flow depth, Froude number, Reynolds number, shear stress, drag coefficient, stream power, and unit stream power) differed with the increased slope gradients and flow discharges. The mean flow velocity of the stem cover slope was lower than that of the frozen soil slope, brown soil slope, and organic glass slope by 33%, 40%, and 50%, respectively. The stem cover slope drag coefficient was higher than the frozen soil slope, brown soil slope, and organic glass slope by 201%, 323%, and 630%, respectively. The critical flow states of the underlying surface were different under different slope gradients and flow discharge conditions. The flow on frozen soil slopes was mainly laminar and transitional, while the other three were transitional. These results help us understand the hydrodynamic mechanisms of the sediment transport process during overland flow. The results of the study provide a scientific basis for understanding the hydrodynamic mechanism of the dynamic changes of the sediment transport on the slope, deepening the understanding of the soil erosion mechanism and improving the prediction accuracy of the soil erosion process model.

Ant-Inspired Metaheuristic Algorithms for Combinatorial Optimization Problems in Water Resources Management

Ant-inspired metaheuristic algorithms known as ant colony optimization (ACO) offer an approach that has the ability to solve complex problems in both discrete and continuous domains. ACOs have gained significant attention in the field of water resources management, since many problems in this domain are non-linear, complex, challenging and also demand reliable solutions. The aim of this study is to critically review the applications of ACO algorithms specifically in the field of hydrology and hydrogeology, which include areas such as reservoir operations, water distribution systems, coastal aquifer management, long-term groundwater monitoring, hydraulic parameter estimation, and urban drainage and storm network design. Research articles, peer-reviewed journal papers and conference papers on ACO were critically analyzed to identify the arguments and research findings to delineate the scope for future research and to identify the drawbacks of ACO. Implementation of ACO variants is also discussed, as hybrid and modified ACO techniques prove to be more efficient over traditional ACO algorithms. These algorithms facilitate formulation of near-optimal solutions, and they also help improve cost efficiency. Although many studies are attempting to overcome the difficulties faced in the application of ACO, some parts of the mathematical analysis remain unsolved. It is also observed that despite its popularity, studies have not been successful in incorporating the uncertainty in ACOs and the problems of dimensionality, convergence and stability are yet to be resolved. Nevertheless, ACO is a potential area for further research as the studies on the applications of these techniques are few.

Estimation of Hydraulic Parameters from the Soil Water Characteristic Curve

Soil water characteristic curve (SWCC) is one of the most essential hydraulic properties that play fundamental role in various environmental issues and water management. SWCC gives important information for water movement, soil behavior, infiltration, and drainage mechanism, affecting the water circle and the aquifer recharge. Since most of the world’s freshwater withdrawals go for irrigation uses, decoding SWCC is beneficial, as it affects water saving through irrigation planning. Estimation of crucial parameters, such as field capacity (FC) and permanent wilting point (PWP) is the key solution for water saving. Modelling of the SWCC and hydraulic parameters estimation are of great importance, since the laboratory experimental procedures and the experiments in the field are often time-consuming processes. In the present study, the SWCC along with FC and PWP of two soil types were obtained via specific experimental procedures in the laboratory. In order to simulate the SWCC and estimate FC and PWP, the experimental data were approximated with van Genuchten’s model. Results showed that using SWCC to estimate FC gives excellent results, while the method rationally overestimates the PWP. Hence, the presented method leads to estimation of crucial hydraulic parameters that can be used in irrigation planning and water saving practices.

Scale Effect on Hydraulic Properties of Pore-Fissure Deep Rock Formations and Its Importance for the Mining Shaft-Sinking Process

The problem of hydraulic parameters estimation lies in the depth: the deeper the rock formation, the more expensive and difficult the field tests and samples acquisition, and the more challenging the technical issues. The article assesses the Triassic sandstone’s drainage potential at the stage of shaft sinking. It focuses on parameter analysis in varied scales, from drill-core sample laboratory testing, through a single well drawing test, to long-term pumping and recovery tests in the well with observation piezometers. The obtained results are compared to the values estimated in the past using different methods. Finally, the paper states whether it is reliable to forecast pore-fissure sandstone drainage potential based only on core samples’ laboratory tests. This research proved that lab tests underestimate pore-fissure rocks’ hydraulic parameters (mean hydraulic conductivity k = 9.79 × 10−8 m/s) tenfold more than long-term pumping tests (mean k = 4.45 × 10−7 m/s). However, it can be concluded that the group of so-called “witness samples”, 10% of all core samples with a top value of the hydraulic conductivity tested in the laboratory, can be representative of the aquifer and comparable to the values obtained in pumping tests. With this in mind, we recommend using the highest values of hydrogeological parameters from laboratory tests based on the worst-case scenario. Therefore, it is possible to forecast inflows to the shafts reliably. This methodology is recommended only for rocks of porous and pore-fissure character.

Estimation of mechanical and hydraulic parameters of bentonite-soil mixtures in oedometer condition with index properties

Estimation of mechanical and hydraulic parameters of bentonite-soil mixtures in oedometer condition with index properties

Joint Estimation of Adsorptive Contaminant Source and Hydraulic Conductivity Using an Iterative Local Updating Ensemble Smoother with Geometric Inflation Selection

The joint estimation of groundwater contaminant source characteristics and hydraulic conductivity is of great significance for reactive contaminant transport models in heterogeneous subsurface media. The accurate determination of the sorption parameters of such contaminants is also a key prerequisite for estimating the parameters of the groundwater system. In this study, to investigate the impact of the sorption parameter field on the accuracy of hydraulic conductivity and source characteristics estimation, numerical experiments were conducted in a synthetic aquifer considering the contaminant sorption process in groundwater models with varying sorption parameter settings. Iterative local updating ensemble smoother with geometric inflation selection (ILUES-GEO) was employed to assimilate hydraulic head and contaminant concentration data to jointly estimate the contaminant source information and hydraulic conductivity in a heterogeneous aquifer. The results indicated that the ILUES-GEO successfully recovers contaminant source information simultaneously with hydraulic conductivity, and its performance improves as more accurate sorption parameters are introduced. Furthermore, the influence of the ILUES algorithm parameters and ensemble size is investigated to improve the estimation accuracy. Additionally, the characterization of contaminant sources and hydraulic conductivity fields is influenced by the number and locations of measurements. This study can help to understand the significance of sorption parameter setting for the joint estimation of reactive contaminant source and hydraulic parameters.

Estimation of hydraulic parameters in a heterogeneous low‐lying farmland near Venice

AbstractEstimating the hydraulic properties of the vadose zone is essential to understand soil‐water dynamics and achieving appropriate water management in agricultural lands. Inverse modelling methods are commonly used to estimate hydraulic properties from field observations. Unlike the extensively applied local search methodologies, data assimilation techniques can fully account for multiple uncertainties and are becoming a widely used tool for estimating hydraulic parameters. However, only few applications on real field tests are available. The main objective of this study was to estimate the van Genuchten‐Mualem (VGM) parameters and the saturated hydraulic conductivity () of a heterogeneous low‐lying farmland at the margin of the Venice Lagoon, Italy, characterized by high peat content, sandy drifts, and a very shallow water table. To this end, two methods were tested, that is, the Ensemble Smoother (ES) and the Levenberg–Marquardt (LM) algorithm associated with hydrological modelling performed with Hydrus‐1D. Volumetric water content (VWC) observations were collected at three monitoring sites from May to September 2011. Results on parameters highlighted that the ES technique effectively reduced the uncertainty of and , but it was less effective on and . The results on VWC showed that the ES efficiency decreased with the increasing non‐linearity of the system (e.g., higher sand content) and when the variability of the experimental data was lower (e.g., deepest soil layers where saturation remained permanently close to 1). Both LM and ES allowed to reproduce the VWC observations in the calibration and validation phases, with the former and the latter performing better in the case of sandy and peat soils, respectively. As concerns the method applicability, the ES was less time‐demanding as it efficiently updated all the parameters at once and was less dependent on the user choices. Finally, the paper points out the importance of previous knowledge of the VGM parameters (e.g., from lab hydraulic analyses) in defining the constraints for the optimization.