Liangping Li

Liangping Li
South Dakota School of Mines and Technology | SDSM&T · Department of Geology and Geological Engineering

PhD

About

58
Publications
9,548
Reads
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1,491
Citations
Citations since 2016
30 Research Items
1078 Citations
2016201720182019202020212022050100150200
2016201720182019202020212022050100150200
2016201720182019202020212022050100150200
2016201720182019202020212022050100150200
Additional affiliations
August 2015 - present
South Dakota School of Mines and Technology
Position
  • Professor (Assistant)
January 2012 - June 2015
University of Texas at Austin
Position
  • PostDoc Position
Education
October 2007 - September 2009
Universitat Politècnica de València
Field of study
  • Groundwater
October 2007 - December 2011
Universitat Politècnica de València
Field of study
  • Hydrogeology
September 2007 - December 2011

Publications

Publications (58)
Article
Parameter identification is an essential step in constructing a groundwater model. The process of recognizing model parameter values by conditioning on observed data of the state variable is referred to as the inverse problem. A series of inverse methods has been proposed to solve the inverse problem, ranging from trial-and-error manual calibration...
Article
The Ensemble Kalman Filter (EnKF) has been commonly used to assimilate real time dynamic data into geologic models over the past decade. Despite its various advantages such as computational efficiency and its capability to handle multiple sources of uncertainty, the EnKF may not be used to reliably update models that are characterized by curvilinea...
Article
The ensemble Kalman filter (EnKF) has been widely applied to assimilate dynamic data such as hydraulic head in geologic models for improved predictions over the past decade. It has various advantages such as the capability of handling multiple sources of uncertainty and ease of coupling with forward simulators involving complex physics; however, it...
Article
Inverse method can be used to fill the gap between huge amount of data from sensors and complex groundwater model. The iterative Ensemble Smoother (iES) is one of the most efficient algorithms applied to groundwater modeling for data assimilation. However, the iES only works for multi-Gaussian fields, because two-point statistics are used to estima...
Article
Full-text available
In this study, a sand-tank model as a physical analog of a real-world aquifer is presented for groundwater instruction. The sand tank is used for introducing flow nets and quantifying groundwater flow, for groundwater modeling and calibration via a spreadsheet, and for dye-transport modeling. Students learn from the sand tank through interaction an...
Article
Groundwater modeling is an important tool for water resources management and aquifer remediation. However, the inherent strong heterogeneity of the subsurface and scarcity of observed data pose major challenges for groundwater flow and contaminant transport modeling. Data assimilation such as the Ensemble Smoother with Multiple Data Assimilation (E...
Article
Fe-rich (>0.3 mg/L) groundwater is generally present in areas where organic matter-rich fluvial, lacustrine, or marine sedimentary environments occur. The Pearl River Delta (PRD) that marine sediments is common, where a large scale of Fe-rich groundwater was distributed but disappearing in recent decade. This study aims to investigate the change of...
Article
Full-text available
Assessing natural background levels (NBLs) of groundwater chemical components is useful to the identification of geochemical factors controlling the origin of high levels of chemical components in groundwater. This study assessed the NBLs of phosphate in various groundwater units in the Pearl River Delta (PRD) where urbanization is a large-scale by...
Article
Establishment of natural background levels (NBL) of groundwater in urbanized areas such as the Pearl River Delta (PRD) is challenging. Pre-selection methods are the most common approaches for NBL assessment, but it will overestimate (or underestimate) contaminated groundwater in urbanized areas by using present pre-selection methods with empirical...
Article
Parameter estimation with uncertainty quantification is essential in groundwater modeling to ensure model quality; however, parameter estimation, especially for non-Gaussian distributed parameters in highly heterogeneous aquifers, is still a great challenge. The ensemble smoother with multiple data assimilation (ES-MDA) is one of the most popular a...
Article
Dynamic data such as hydraulic head and concentration data can be integrated into the groundwater flow and contaminant transport model to improve its predictive ability for groundwater resource management and aquifer remediation. Ensemble Smoother with Multiple Data Assimilation (ES-MDA) has gained popularity for data assimilation in the field of h...
Article
When designing a well field for efficiently extracting groundwater or petroleum, it is common for designers to rely on computational optimization meth- ods to determine the optimal placement of wells. The goal of these methods is to find a well field solution that maximizes the value of a defined objective function, and to do so while utilizing the...
Article
Iodine-rich groundwater is a cause for concern because it is harmful to human health, and determining the sources of groundwater iodine in coastal urbanized areas is complicated. This study aims to delineate the spatial distribution of groundwater iodide in various shallow and unconfined aquifers, as well as in areas with different urbanization lev...
Article
Ground Penetrating Radar (GPR) has been widely used for shallow subsurface exploration in recent decades. The Ensemble Smoother with Multiple Data Assimilation (ES-MDA) was proposed and has been proved as one of the most efficient algorithms for data assimilation in variational fields. In this paper, ES-MDA is first applied as the assimilation sche...
Article
Predicting the fate and transport of solutes in aquifers is challenging, and sometimes hardly possible. Everybody seems to agree that uncertainty about the underground is the main culprit. Let it be uncertainty about the heterogeneous distributions of parameters controlling the underlying physico-chemical processes, or uncertainty about the process...
Article
Reliable inversion of spatial heterogeneity of hydraulic conductivity is crucial to understand subsurface fluids migration. The Ensemble Smoother – Direct Sampling method (ES-DS) has proven to be an effective method to identify non-Gaussian hydraulic conductivity distributions by incorporating a variety of traditional hydrodynamic measurements, e.g...
Article
Well placement design refers to finding the optimal well locations to install with a set of constraints. This is important for both petroleum engineering and water resource management. This study presents a novel optimization method for well placement design in groundwater management. The proposed method, EO-WPP, is based on the Extremal Optimizati...
Article
Full-text available
In this study, field investigation and numerical modeling using Particle Flow Code (PFC) were conducted to investigate deposit characteristics and their implications for the fragmentation mechanisms of the 2009 Jiweishan rock avalanche in Wulong, China. The results show that average grain-size distribution of the debris diminishes both from the pro...
Article
A growing population accompanied by urbanization has increased groundwater resource demands in the Pearl River Delta (PRD) area, southern China, and a comprehensive understanding of the groundwater chemistry in the PRD is necessary. The aims of this study were to investigate the groundwater chemistry in various aquifers in the PRD on a regional sca...
Preprint
Groundwater modeling calls for an effective and robust data integrating method to fill the gap between the model and observation data. The Ensemble Kalman Filter (EnKF), a real-time data assimilation method, has been increasingly applied in multiple disciplines such as petroleum engineering and hydrogeology. In this approach, a groundwater model is...
Article
Full-text available
Accurate modeling of hydraulic properties such as transmissivity and interbed specific storages is significant for reliable predictions of land subsidence modeling. Calibration of land subsidence model is a challenge because of the strong non-linearity of groundwater flow equation especially when it accounting for the interbed drainage process. Pum...
Article
Full-text available
Water and gas, as the two most common uids and primary geologic forces, are crucial components in various geological processes. Gas-water-rock interactions play indispensable roles in the evolution of geoenvironmental issues. For example, the accurate prediction of groundwater ow and contaminant transport requires a profound understanding of physic...
Article
Aging affects arsenic (As) bioaccessibility in soils. This study focuses on the influences of particle size and redox potential on As(V) aging in irrigated soils. The results showed that the variation of As fractions, except the loosely adsorbed fraction in fine particles, was larger than that in coarse particles over time. Anoxic conditions decrea...
Article
The application of interferometric synthetic aperture radar (InSAR) has been increasingly used to improve capabilities to model land subsidence in hydrogeologic studies. A number of investigations over the last decade show how spatially detailed time-lapse images of ground displacements could be utilized to advance our understanding for better pred...
Chapter
The EnKF has been extensively used for real-time data assimilation in areas such as reservoir/groundwater modeling. One of the big challenges of the EnKF is how to handle the non-Gaussianity of aquifer properties, particularly for channelized aquifers where preferred flow conduits are encountered. EnPAT is a pattern-based inverse method and was dev...
Chapter
Land subsidence modeling has been developed for reliable modeling and prediction in the last several decades. Calibration of hydraulic properties such as transmissivity and elastic and inelastic specific storages using observation data is a challenge because of the strong nonlinearity of groundwater flow equation especially when it accounted for th...
Article
Methods based on two-point geostatistics have been routinely used to interpolate random variables such as groundwater level and concentration and to estimate their values at un-sampled locations. These methods use the observed data to analyze spatial two-point correlations and ignore the higher order moments that may play a key role in the characte...
Conference Paper
Inverse modeling is an essential step for reliable modeling of subsurface flow and transport, which is important for groundwater resource management and aquifer remediation. Multiple-point statistics (MPS) based aquifer modeling algorithms, beyond traditional two-point statistics-based methods, offer an alternative to simulate complex geological fe...
Conference Paper
The Ensemble Kalman Filter (EnKF) has been commonly used to assimilate real time dynamic data into geologic models over the past decade. Despite its various advantages such as computational efficiency and capability to handle multiple sources of uncertainty, the EnKF cannot be used to update model that are characterized by curvi-linear geometries s...
Article
Inverse modeling is an essential step for reliable modeling of subsurface flow and transport, which is important for groundwater resource management and aquifer remediation. Multiple-point statistics (MPS) based reservoir modeling algorithms, beyond traditional two-point statistics-based methods, offer an alternative to simulate complex geological...
Conference Paper
Full-text available
Inverse modeling is essential for generating reliable subsurface flow and transport models that can inform groundwater resource management and aquifer remediation efforts. Multiple point statistics (MPS) based models, beyond the traditional two-point statistics based methods, offer an alternative to simulate complex geological features and pattern,...
Chapter
Steady-state piezometric head data have always been regarded as containing only information about the major patterns of variability of hydraulic conductivity, but not about specific features, such as channels, or local scale heterogeneity. We have attempted to characterize a channeled aquifer using only steady-state piezometric head without success...
Article
Methods based on multiple-point statistics (MPS) have been routinely used to characterize complex geological formations in the last decade. These methods use the available static data (for example, measured conductivities) for conditioning. Integrating dynamic data (for example, measured transient piezometric head data) into the same framework is c...
Data
Assessment of uncertainty due to inadequate data and imperfect geological knowledge is an essential aspect of the subsurface model building process. In this work, a novel methodology for characterizing complex geological structures is presented that integrates dynamic data. The procedure results in the assessment of uncertainty associated with the...
Conference Paper
In complex geological systems such as fluvial aquifers, carbonate systems and naturally fractured aquifers, multiple-point statistics (MPS) based modeling methods are required to characterize complex, curvilinear features. History matching with MPS calls for an effective inverse method that can not only honor the observed dynamic data, but also pre...
Article
The localized normal-score ensemble Kalman filter (NS-EnKF) coupled with covariance inflation is used to characterize the spatial variability of a channelized bimodal hydraulic conductivity field, for which the only existing prior information about conductivity is its univariate marginal distribution. We demonstrate that we can retrieve the main pa...
Data
The ensemble Kalman filter (EnKF) is nowadays recognized as an excellent inverse method for hydraulic conductivity characterization using transient piezometric head data. Its implementation is well suited for a parallel computing environment. A parallel code has been designed that uses parallelization both in the forecast step and in the analysis s...
Article
The localized normal-score ensemble Kalman filter is shown to work for the characterization of non-multi-Gaussian distributed hydraulic conductivities by assimilating state observation data. The influence of type of flow regime, number of observation piezometers, and the prior model structure are evaluated in a synthetic aquifer. Steady-state obser...
Article
Real-time data from on-line sensors offer the possibility to update environmental simulation models in real-time. Information from on-line sensors concerning contaminant concentrations in groundwater allow for the real-time characterization and control of a contaminant plume. In this paper it is proposed to use the CPU-efficient Ensemble Kalman Fil...
Article
Uncertainty in model predictions is caused to a large extent by the uncertainty in model parameters, while the identification of model parameters is demanding because of the inherent heterogeneity of the aquifer. A variety of inverse methods has been proposed for parameter identification. In this paper we present a novel inverse method to constrain...
Article
The ensemble Kalman filter (EnKF) is now widely used in diverse disciplines to estimate model parameters and update model states by integrating observed data. The EnKF is known to perform optimally only for multi-Gaussian distributed states and parameters. A new approach, the normal-score EnKF (NS-EnKF), has been recently proposed to handle complex...
Article
Full-text available
The normal-score ensemble Kalman filter (NS-EnKF) is tested on a synthetic aquifer characterized by the presence of channels with a bimodal distribution of its hydraulic conductivities. This is a clear example of an aquifer that cannot be characterized by a multiGaussian distribution. Fourteen scenarios are analyzed which differ among them in one o...
Article
The ensemble Kalman filter (EnKF) is coupled with upscaling to build an aquifer model at a coarser scale than the scale at which the conditioning data (conductivity and piezometric head) had been taken for the purpose of inverse modeling. Building an aquifer model at the support scale of observations is most often impractical since this would imply...
Article
The ensemble Kalman filter (EnKF) is nowadays recognized as an excellent inverse method for hydraulic conductivity characterization using transient piezometric head data. Its implementation is well suited for a parallel computing environment. A parallel code has been designed that uses parallelization both in the forecast step and in the analysis s...
Article
Full-text available
The normal-score ensemble Kalman filter (NS-EnKF) is tested on a synthetic aquifer characterized by the presence of channels with a bimodal distribution of its hydraulic conductivities. Fourteen scenarios are analyzed which differ among them in one or various of the following aspects: the prior random function model, the boundary conditions of the...
Article
The ensemble Kalman filter (EnKF) is a commonly used real-time data assimilation algorithm in various disciplines. Here, the EnKF is applied, in a hydrogeological context, to condition log-conductivity realizations on log-conductivity and transient piezometric head data. In this case, the state vector is made up of log-conductivities and piezometri...
Article
Simple averaging, simple-Laplacian, Laplacian-with-skin, and non-uniform coarsening are the techniques investigated in this comparative study of three-dimensional hydraulic conductivity upscaling. The reference is a fine scale conditional realization of the hydraulic conductivities at the MAcro-Dispersion Experiment site on Columbus Air Force Base...
Article
A methodology for transport upscaling of three-dimensional highly heterogeneous formations is developed and demonstrated. The overall approach requires a prior hydraulic conductivity upscaling using an interblock-centered full-tensor Laplacian-with-skin method followed by transport upscaling. The coarse scale transport equation includes a multi-rat...
Article
We present a new 3D steady-state saturated groundwater-flow forward-simulator with full conductivity tensors using a 19-points block-centered finite-difference method. Hydraulic conductivity tensors are defined at the block interfaces eliminating the need to average conductivity tensors at adjacent blocks to approximate their values at the interfac...
Article
The main point of this paper is to propose a non-local three-dimensional hydraulic conductivity full tensor upscaling algorithm and code. The algorithm is capable of transforming very refined cell conductivity models into coarse block conductivity models for quick and accurate solution of the groundwater flow equation. Flow rate and hydraulic head...
Conference Paper
In a companion paper we present a technique that is capable to upscale 3D hydraulic conductivity fields at a fine scale onto a coarse model of 3D hydraulic conductivity tensors. These tensors do not have to have their principal directions aligned with the Cartesian axes, nor they all have to have their principal directions parallel to each other. M...
Conference Paper
No matter how powerful computer codes become, there will always be a discrepancy between the scale at which we can characterize the medium and the scale at which we will run our numerical models. This discrepancy calls for an upscaling technique that is capable of accounting for the fully tensorial nature of the upscaled conductivity. We propose a...
Article
Thermal groundwater occurs in bedrock aquifers consisting of the dolomite of the Wumishan Group of the Jixianin System and the Cambrian carbonate in the Xiaotangshan geothermal field near the northern margin of the North China Plain, China. The hot water in the geothermal field of basin-type discharges partly in the form of the Xiaotangshan hot spr...

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