Integrated Hydrologic Modeling and GIS in Water Resources Management

The integration of a physically-based distributed model with a geographic information system (GIS) in watershed-based water resources management is presented, and an example watershed is chosen to demonstrate the spatial database and modeling system developed in this study. The spatial data is first processed by GIS. The model is then used to simulate runoff hydrographs. It operates at a daily time step on 1 × 1 km grid squares and simulates important hydrologic processes including evapotranspiration, snowmelt, infiltration, aquifer recharge, ground-water flow, and overland and channel runoff. Finally, the model result is displayed by using GIS. This study demonstrates that the integration of a physically based distributed model and GIS may successfully and efficiently implement the watershed-based water resources management. Not only does this process facilitate examination of a wider range of alternatives that would be impossible by using conventional methods, but it also provides a living management that could be modified and updated by water managers once the watershed condition is changed.     

New Strategy for Optimizing Water Application under Trickle Irrigation

The determination of water application parameters for creating an optimal soil moisture profile represents a complex nonlinear optimization problem which renders traditional optimization into a cumbersome procedure. For this reason, an alternative methodology is proposed which combines a numerical subsurface flow model and artificial neural networks (ANN) for solving the problem in two, fully separate steps. The first step employs the flow model for calculating a large number of wetting profiles (output), obtained from a systematic variation of both water application and initial soil moisture (input). The resulting matrix of corresponding input/output values is used for training the ANN. The second step, the application of the fully trained ANN, then provides the irrigation parameters which range from a specified initial soil moisture to a desired crop-specific soil moisture profile. In order to avoid substantial disadvantages associated with the common feedforward backpropagation approach, a self-organizing topological feature map is implemented to perform this task. After a comprehensive sensitivity analysis, the new methodology is applied to the outcome of an irrigation experiment. The convincing results recommend the new methodology as a positive contribution towards an improved irrigation efficiency.     

Site Characterization Model Using Artificial Neural Network and Kriging

In this paper, the problem of site characterization is treated as a task of function approximation of the large existing data from standard penetration tests (SPTs) in three-dimensional subsurface of Bangalore, India. More than 2,700 field SPT values (N) has been collected from 766 boreholes spread over an area of 220-km2 area in Bangalore, India. To get N corrected value (Nc), N values have been corrected for different parameters such as overburden stress, size of borehole, type of sampler, length of connected rod. In three-dimensional analysis, the function Nc = Nc(X,Y,Z), where X, Y, and Z are the coordinates of a point corresponds to Nc value, is to be approximated with which Nc value at any half-space point in Bangalore, India can be determined. An attempt has been made to develop artificial neural network (ANN) model using multilayer perceptrons that are trained with Levenberg-Marquardt back-propagation algorithm. Also, a geostatistical model based on ordinary kriging technique has been adopted. The knowledge of the semivariogram of the Nc values is used in the ordinary kriging method to predict the Nc values at any point in the subsurface of Bangalore, India where field measurements are not available. The results obtained show that ANN model is fairly accurate in predicting Nc values. In case of ordinary kriging, a new type of cross-validation analysis shows that it is a robust model for prediction of Nc values. A comparison between the ANN and geostatistical model demonstrates that the ANN model is superior to Geostatistical model in predicting Nc values in the subsurface of Bangalore, India.     

Solution for Flow Rates across the Wellbore in a Two-Zone Confined Aquifer

A closed-form solution for transient flow rates across the wellbore in a confined aquifer is derived from a two-zone radial ground-water flow equation subject to the boundary condition of keeping a constant head at the well radius. An aquifer may be considered as a two-zone system if the formation properties near the wellbore are significantly changed due to the well construction and/or well development. An efficient numerical approach is used to evaluate this newly derived solution. Values of the transient flow rate are provided in a tabular form and compared with those obtained by numerical inversion for the Laplace-domain solution. The results show that the two solutions are in good agreement. This newly derived solution can be used not only for predicting the transient flow rate across the wellbore but also for identifying the effects of a skin with a finite thickness on the estimation of transient flow rates in a ground-water system with two different formation properties.     

Aldicarb Transport in Subsurface Environment: Comparison of Models

In this paper, two different pesticide transport simulation models are presented and compared to carry out preliminary analysis on the applicability of those models in determining ground-water vulnerability to aldicarb contamination. The first model is a physically based analytical model that simulates 1D pesticide movement in soils, based on the concept of complete mixing and 2D advective-dispersive transport in the aquifer. The second model is a numerical simulation model that links the existing numerical codes PRZM2, MODFLOW, and MT3D to simulate pesticide transport in the subsurface. The concentrations of aldicarb residues in soil and in the aquifer calculated by the two models are found to be in good agreement. However, the analytical model tends to produce an earlier arrival of the peak concentration in each year due to the assumption of complete mixing. It is also found that the infiltrating water following aldicarb application plays a significant role on the leaching potential of aldicarb, which is also affected by various meteorological and hydrological factors as well as by agricultural practices.     

Considerations for Monitoring Permeable Ground-Water Treatment Walls

Permeable ground-water treatment walls (PTWs) have been implemented as a means by which innovative ground-water treatment technologies can be applied in-situ. Though not widely addressed in the technical literature, the ground-water monitoring program for a PTW at a commercial site should consider several factors including: (1) design elements of the PTW; (2) the remediation process to be implemented through the PTW; (3) the distribution of contaminants in the affected aquifer; (4) ground-water sampling methods; and (5) regulatory issues. Also, the compliance monitoring well network within the PTW and sampling plan should be designed to assure that (1) design ground-water residence time goals within the PTW are achieved prior to sampling; (2) the uniformity of ground-water flow through the PTW is accounted for; and (3) ground-water samples are collected using techniques (e.g., micropurging) that reduce the potential for collecting nontreated ground water from down- or upgradient of the PTW. A case study illustrates the concepts used to develop a ground-water monitoring program for a PTW that was accepted by regulatory agencies for a commercial site.     

Utility of Column Lysimeter for Design of Soil Aquifer Treatment System for Wastewater Renovation Using Artificial Neural Networks

An artificial neural network (ANN) model is developed to study the correlation of data with reference to various wastewater pollution parameters (biochemical oxygen demand, chemical oxygen demand, suspended solids, NH4, PO4) using two scales of experiments viz. column lysimeter and a pilot soil aquifer treatment (SAT) system for wastewater renovation in India. A unique feature of the study is that the primary treated wastewater was directly applied to SAT system for renovation in contrast to the secondary treated effluent used in most of the other studies that have been reported. The analysis of data using ANN as a tool indicates that the column lysimeter data are useful for design of SAT systems and it is possible to predict the effluent quality for SAT system based on the inputs from lysimeter experiments. The study highlights the utility of column lysimeter studies for evolving design parameters for a full-scale SAT system thereby obviating the need for pilot SAT studies which are site specific, time consuming, and expensive. Thus, the study suggests that the experimental data from lysimeter studies at a particular site can be used to predict performance of field-scale SAT systems without going in for actual experimentation. Further, the field data from one site could be utilized for design of SAT systems at other locations provided the climatic and hydrogeological conditions viz. soil matrix characteristics and wastewater characteristics, etc., are similar.     

Analytical Modeling of Nitrogen Dynamics in Soils and Ground Water

An analytical model, known as RISK-N, is developed to simulate nitrogen cycling in soils, and nitrate transport and fate in soils and ground water. The soil is separated into upper-root, lower-root, and intermediate-vadose zones, each with uniform properties. Transport in each soil zone is modeled on the basis of complete mixing. Transport in the aquifer, however, is modeled using a two-dimensional advection-dispersion transport equation. A simulation is made with a hypothetical corn plot, using meteorological, soil, hydrologic, and hydrogeological data for the South Platte River region of northeastern Colorado. Sensitivity analyses are performed on model parameters. This study shows that the RISK-N model is capable of simulating nitrate leaching rates, as well as ground-water concentrations, that are consistent with those obtained by numerical models, while requiring fewer input variables.     

Prediction of tribological behaviour of rice husk ash reinforced aluminum alloy matrix composites using artificial neural network

Artificial Neural Network (ANN) model was developed to predict the wear rate and coefficient of friction for the Rice Husk Ash (RHA) reinforced aluminum alloy composite. The composite was fabricated using the stir cast route and their tribological behavior was tested using Pin-on-Disc wear tester. The experiments were conducted based on Orthogonal array (L₂₇) generated through the Taguchi Technique and their results were used to train the ANN model. The input parameters assigned to develop an ANN model are applied load, sliding speed, RHA particle size and weight percentage of RHA reinforcement. A four layer perception network having 4-7-8-2 architecture was found to be the optimum network. Finally, confirmation test was done to verify the predictive model with the experimental results and also the wear surface morphology of the wear pin was analyzed using the scanning electron microscope.     

Infiltration Considerations for Ground-Water Recharge with Waste Effluent

Water reuse and ground-water recharge can be used to meet the growing demands for water, particularly in arid regions. Ground-water recharge using fresh water or treated wastewater is most often accomplished by infiltration from surface basins. The water percolates through the unsaturated soil region to an underlying aquifer for storage and future use. In the case of wastewater, additional treatment occurs as the effluent flows through the soil. The system hydraulics of recharge basins have been examined through a combination of field and laboratory investigations. These studies indicate that infiltration rates and soil aquifer treatment of wastewater are influenced by soil type and soil profile characteristics, surface clogging material, pond depth, and wetting∕drying cycle times. The surface-clogging layer was found to be susceptible to consolidation and to associated reduction in hydraulic conductivity under seepage forces.     

Large-Scale Tracing of Ground Water with Sulfur Hexafluoride

Sulfur hexafluoride (SF6) was injected into a 9 km reach of the Santa Ana River in Orange County, CA, over a period of two weeks. The entire flow of this river, which averaged 2.8 m3 s?1, percolated into the ground in the field area. The tracer was monitored at wells near the river to determine subsurface flow patterns and flow times with an accuracy much greater than could be achieved using numerical simulations of ground-water flow. During the experiment, SF6 effectively tagged 3.7 × 106 m3 of water. The tracer plume was mapped in the subsurface for 18 months and indicates that linear ground-water velocities averaged about 2 km year?1. The tracer reached two wells adjacent to the river (about 200 m away) within three weeks, giving evidence that SF6 was not retarded significantly relative to the ground-water flow. This is in agreement with previous laboratory experiments.     

Continuous Plume Monitoring Using Wireless Sensors: Proof of Concept in Intermediate Scale Tank

The current practice for monitoring of subsurface plumes involves the collection of water samples from sparsely distributed monitoring wells and laboratory analysis to determine chemical concentrations. In most field situations, cost and time constraints limit the number of samples that could be collected and analyzed for continuous monitoring of large, transient plumes. With the development of wireless sensor networks (WSNs), that allow sensors to be incorporated into a distributed wireless communication and processing system, the potential exists to develop new, efficient, economical, large-scale subsurface data collection and monitoring methods. This paper presents a proof-of-concept study conducted in a two-dimensional synthetic aquifer constructed in an intermediate scale test tank to demonstrate the feasibility of using WSN for subsurface plume monitoring. The tank was packed to represent a heterogeneous aquifer, and a sodium bromide tracer was used to create a plume. A set of ten wireless sensor nodes (motes) equipped with conductivity probes to measure electrical conductivity formed the network. Software for automated data acquisition was developed and tested. Results of two experiments conducted using this test system are presented. The lessons learned from the first experiment were used to make modifications to the way the sensors were placed, how they were calibrated and how the sensors were interfaced with the data acquisition system. The findings are used to identify future research directions and issues that need to be addressed before field implementations of a WSN based data collection system for plume monitoring.     

Reducing Uncertainty in Site Characterization Using Bayes Monte Carlo Methods

A Bayesian uncertainty analysis approach is developed as a tool for assessing and reducing uncertainty in ground-water flow and chemical transport predictions. The method is illustrated for a site contaminated with chlorinated hydrocarbons. Uncertainty in source characterization, in chemical transport parameters, and in the assumed hydrogeologic structure was evaluated using engineering judgment and updated using observed field data. The updating approach using observed hydraulic head data was able to differentiate between reasonable and unreasonable hydraulic conductivity fields but could not differentiate between alternative conceptual models for the geological structure of the subsurface at the site. Updating using observed chemical concentration data reduced the uncertainty in most parameters and reduced uncertainty in alternative conceptual models describing the geological structure at the site, source locations, and the chemicals released at these sources. Thirty-year transport projections for no-action and source containment scenarios demonstrate a typical application of the methods.     

Removal of Dissolved- and Free-Phase Benzene Pools from Ground Water Using In Situ Air Sparging

This paper presents the results of a laboratory investigation performed to study the use of air sparging to remediate dissolved-phase and free-phase [or non-aqueous-phase liquid (NAPL)-phase] benzene pools from ground water. The specific objectives of the study were (1) to assess how air injection rate affects the mass transfer and transport of dissolved- and NAPL-phase pools; and (2) to determine the effect of ground-water flow on the removal of dissolved- and NAPL-phase pools during the application of air sparging. A total of five 2D physical model tests were performed in a homogeneous coarse sand profile subjected to both static ground water and ground-water flow conditions. Three different air injection rates were used in a static ground-water condition, and two different air flow rates were used in soil profiles subjected to ground-water flow (hydraulic gradient = 0.011). All tests were performed with similar initial dissolved- and NAPL-phase benzene conditions. Injected air traveled within a parabolic zone of influence (in channel mode) when subjected to both static ground water and ground-water flow conditions, indicating that ground-water flow (for the ground-water velocities tested) did not affect the injected air zone of influence. An increase in air injection rate led to faster contaminant removal; however, at higher air injection rates, a threshold rate of removal was reached above which further increases in injection rate are a waste of effort. Additionally, air injected into the soil profile reduced the hydraulic conductivity within the zone of influence. This in turn led to lower ground-water flow rates, allowing for effective interception and treatment of a migrating NAPL plume. Higher air injection rates led to further reductions in hydraulic conductivity, allowing for substantial control of the NAPL plume in the downgradient direction. Overall, this study showed that air sparging can be used to effectively remediate dissolved- and NAPL-phase benzene.     

Development of a Web-GIS Based Geotechnical Information System

The construction industry benefits greatly if all the existing three-dimensional (3D) geotechnical subsurface information of a city/country can be accessed at any time using the Internet. The geographic information system (GIS) is well suited for such problems; however, GIS was originally developed for two-dimensional planes. Recently, some 3D capabilities for GIS have been developed, but these capabilities in their present form alone are not suitable for storing and presenting three-dimensional geotechnical data. One way to overcome the limitation of data storage is integration of GIS with a relational database management system (RDBMS). A Web-based geotechnical information system that can perform online spatial queries, generation of professional borelogs, and various geotechnical analyses was developed. The system has been developed as a national geotechnical information system (GeoInfoSys) for Singapore. The system provides easy-to-use functions to: (1) locate and purchase boreholes of interest; (2) view borelogs and cross sections that are generated online; (3) provide downloadable data in a standard format for downstream analysis; and (4) perform geotechnical queries using a geotechnical search engine (GSE). The geotechnical information was stored in a digital format rather than as static images; this provides many opportunities to explore the data, and these opportunities are discussed herein.     

Hybrid Neural Network—Finite Element River Flow Model

Results obtained from a hybrid neural network—finite element model are reported in this paper. The hybrid model incorporates artificial neural network (ANN) nodes into a numerical scheme, which solves the two-dimensional shallow water equations using finite elements (FE). First, numerical computations are carried out on the entire numerical model, using a larger mesh. The results from this computation are then used to train several preselected ANN nodes. The ANN nodes model the response for a part of the entire numerical model by transferring the system reaction to the location where both models are connected in real time. This allows a smaller mesh to be used in the hybrid ANN-FE model, resulting in savings in computation time. The hybrid model was developed for a river application, using the computational nodes located at the open boundaries to be the ANN nodes for the ANN-FE hybrid model. Real-time coupling between the ANN and FE models was achieved, and a reduction is CPU time of more than 25% was obtained.     

Rule-Based Fuzzy System for Assessing Groundwater Vulnerability

Parallel to industrial growth and ever increasing use of agrichemicals, environmental resources have been affected and deteriorated by generated pollutants. Groundwater, an important source of fresh water, has not been immune from contamination. Recognition of groundwater vulnerability to pollution will help in managing groundwater quality conflicts. The DRASTIC model (where D=depth to groundwater; R=net recharge; A=aquifer media; S=soil type; T=topography; I=impact of vadose zone; and C=hydraulic conductivity of the aquifer) has been used extensively for assessing the vulnerability of groundwater. It employs a linear combination of some intrinsic properties of aquifers to develop a vulnerability index. As there is no clear boundary for the set of vulnerable aquifers, groundwater vulnerability can be addressed through fuzzy set theory instead of classical set theory. In this study, benefiting from a fuzzy system and a conscious knowledge base, a regional-scale model is developed for groundwater vulnerability assessment that employs DRASTIC parameters. A comparison between the output of the fuzzy model and the DRASTIC index is accomplished. The ability of the fuzzy system to cope with the modeling of a nonlinear system and presentation of the output of the fuzzy system in the framework of a geographical information system are highlighted.     

NAPL Pool Dissolution in Stratified and Anisotropic Porous Formations

A two-dimensional numerical model is developed to study contaminant transport resulting from the dissolution of single- and multicomponent dense nonaqueous-phase liquid (DNAPL) pools in heterogeneous porous media. The aqueous-phase concentration of each dissolved component is assumed to undergo first-order decay as well as sorb under local equilibrium conditions. Pool shrinkage is accounted for by modeling the progressive reduction of the DNAPL pool surface area as a time-dependent boundary. Multicomponent pool dissolution is modeled using an effective solubility (or equilibrium aqueous solubility) relationship, where the nonaqueous-phase activity coefficient for each constituent is evaluated at each and every time step. Subsurface heterogeneities are depicted by an ideally stratified porous formation and by a statistically anisotropic aquifer. In the stratified formation, a multicomponent DNAPL pool is assumed to be formed at the interface between a sand layer and a clay layer, where DNAPL dissolution occurs simultaneously in both strata. The ground-water velocity inside the sand stratum is uniform in the longitudinal direction whereas the interstitial liquid in the aquitard is stagnant. In the statistically anisotropic aquifer, a single-component DNAPL pool is assumed to be formed on top of an impermeable bedrock, where DNAPL dissolution occurs in the aquifer only. Results from several model simulations indicate that dissolved contaminant concentrations in aquifers are reduced significantly in the presence of aquitards, and most importantly, the transfer of dissolved contaminants along the pool-water interface is slower within statistically anisotropic than within homogeneous aquifers.     

Simulated Micromechanical Models Using Artificial Neural Networks

A new method, termed simulated micromechanical models using artificial neural networks (MMANN), is proposed to generate micromechanical material models for nonlinear and damage behavior of heterogeneous materials. Artificial neural networks (ANN) are trained with results from detailed nonlinear finite-element (FE) analyses of a repeating unit cell (UC), with and without induced damage, e.g., voids or cracks between the fiber and matrix phases. The FE simulations are used to form the effective stress-strain response for a unit cell with different geometry and damage parameters. The FE analyses are performed for a relatively small number of applied strain paths and damage parameters. It is shown that MMANN material models of this type exhibit many interesting features, including different tension and compression response, that are usually difficult to model by conventional micromechanical approaches. MMANN material models can be easily applied in a displacement-based FE for nonlinear analysis of composite structures. Application examples are shown where micromodels are generated to represent the homogenized nonlinear multiaxial response of a unidirectional composite with and without damage. In the case of analysis with damage growth, thermodynamics with irreversible processes (TIP) is used to derive the response of an equivalent homogenized damage medium with evolution equations for damage. The proposed damage formulation incorporates the generalizations generated by the MMANN method for stresses and other possible responses from analysis results of unit cells with fixed levels of damage.     

Transient Flow into a Partially Penetrating Well during the Constant-Head Test in Unconfined Aquifers

This study derives a semianalytical solution for drawdown distribution during a constant-head test at a partially penetrating well in an unconfined aquifer. The constant-head condition is used to describe the boundary along the screen. In addition, a free-surface condition is used to delineate the upper boundary of the unconfined aquifer. The Laplace-domain solution is then derived using separation of variables and Laplace transform. This solution can be used to identify the aquifer parameters from the data of the constant-head test when integrated with an optimization scheme or to investigate the effects of vertical flow caused by the partially penetrating well and free-surface boundary in an unconfined aquifer.