Liang-Cheng Chang

Optimal time-varying pumping rates for groundwater remediation: Application of a constrained optimal control algorithm

A numerically efficient procedure is presented for computing optimal time-varying pumping rates for remediation of contaminated groundwater described by two-dimensional numerical models. The management model combines a pollutant transport model with a constrained optimal control algorithm. The transport model simulates the unsteady fluid flow and transient contamination dispersion-advection in a two-dimensional confined aquifer. A Galerkins finite element method coupled with a fully implicit time difference scheme is applied to solve the groundwater flow and contaminant transport equations. The constrained optimal control algorithm employs a hyperbolic penalty function. Several sample problems covering 5-15 years of remediation are given to illustrate the capability of the management model to solve a groundwater quality control problem with time-varying pumping policy and water quality constraints. In the example, the optimal constant pumping rates are 75% more expensive than the optimal time-varying pumping rates, a result that supports the need to develop numerically efficient optimal control-finite element algorithms for groundwater remediation. 28 refs., 7 figs., 10 tabs.

Applying Multiobjective Genetic Algorithm to Analyze the Conflict among Different Water Use Sectors during Drought Period

Water deficits often occur during the drought season and may cause water conflicts among various water use sectors. The reservoir rule curve operation is commonly used to avoid extreme water shortage during droughts in Taiwan. When applying the rule curve operation, the water supply discounting ratio for different sectors implies a trade-off of water deficit impact among sectors. This study therefore develops a multiobjective water resource management model to evaluate the trade-off curve of water deficit impact between irrigation and public sectors to facilitate negotiation between the sectors for obtaining acceptable discounting ratios. The study uses the shortage index to assess water deficit impact. The proposed model integrates operating rules, the stepwise optimal water allocation model, and the convex hull multiobjective genetic algorithm to solve the multiobjective regional water allocation planning problem. The computed trade-off curve, noninferior solutions, provides relevant information to faci...

Optimal remediation design in groundwater systems by intelligent techniques

This research develops an optimal planning model for pump-treat-inject based groundwater remediation systems. Optimizing the design of the pump-treat-inject system is a nonlinear, dynamic and discrete optimization problem. This study integrates the Genetic Algorithm (GA) and Differential Dynamic Programming (DDP) to solve this highly complex problem. The proposed model considers both the cost of installing wells (fixed cost) and the operating cost of pumping, injection and water treatment. Minimizing the total cost and meeting the water quality constraints, the model computes the optimal number and location of wells, as well as the associated optimal pumping and injection schemes. This work also investigates many factors that affect the optimal design of a remediation system, such as, various numerical cases revealing the time-varying pumping and injection rate, and the requirement to balance the total volume between pumping and injection that can significantly influence the optimal design.

Integration of Optimal Dynamic Control and Neural Network for Groundwater Quality Management

This study integrates an artificial neural network (ANN) and constrained differential dynamic programming (CDDP) to search for optimal solutions to a nonlinear time-varying groundwater remediation-planning problem. The proposed model (ANN-CDDP) determines optimal dynamic pumping schemes to minimize operating costs and meet water quality requirements. The model uses two embedded ANNs, including groundwater flow and contaminant transport models, as transition functions to predict groundwater levels and contaminant concentrations under time-varying pumping. Results demonstrate that ANN-CDDP is a simplified management model that requires considerably less computation time to solve a fine mesh problem. For example, the ANN-CDDP computing time for a case involving 364 nodes is 1/26.5 that of the conventional optimization model.

A fuzzy inference system for the conjunctive use of surface and subsurface water

This study develops the water resources management model for conjunctive use of surface and subsurface water using a fuzzy inference system (FIS). The study applies the FIS to allocate the demands of surface and subsurface water. Subsequently, water allocations in the surface water system are simulated by using linear programming techniques, and the responses of subsurface water system with respect to pumping are forecasted by using artificial neural networks. The operating rule for the water systems is that themore abundant water system supplies more water. By using the fuzzy rule, the FIS conjunctive usemodel easily incorporates expert knowledge and operational polices into water resources management. The result indicates that the FISmodel ismore effective and efficient when compared with the decoupled conjunctive use and simulation-optimizationmodels. Furthermore, the FIS model is an alternative way to obtain the conjunctive use policies between surface and subsurface water.

Optimizing Capacity-Expansion Planning of Groundwater Supply System between Cost and Subsidence

This work solves an optimal capacity-expansion planning problem with land subsidence constraints using a hybrid algorithm that combines the genetic algorithm (GA) and constrained differential dynamic programming (CDDP). The main structure of the hybrid algorithm is the GA, in which each chromosome represents a possible network design and its expansion schedule. The present fixed cost of each chromosome is computed easily using the GA, and CDDP is then used to solve the optimal pumping rates and compute the optimal present operating costs associated with the chromosome. Simulation results indicate that the well network has lower total present cost with the capacity-expansion system instead of installing the full system capacity at the beginning. However, the well network designed by the capacity-expansion model without considering land subsidence may induce more local land subsidence than that determined by the conventional model demonstrating the necessity of considering land subsidence constraints in the...

The assessment of high recharge areas using DO indicators and recharge potential analysis: a case study of Taiwan’s Pingtung plain

Identifying high groundwater recharge areas is important for the conservation of groundwater quality and quantity. A common practice used by previous studies is to estimate groundwater recharge potential (GRP) using recharge potential analysis (RPA) under different environments. These studies use the estimated GRP to identify the high potential groundwater recharge sites. However, the RPA parameters are subjectively defined for these previous studies. To remove the supposition, this study proposes a systematic approach that defines the RPA parameter values based on the theory of parameter identification. This study uses dissolved oxygen (DO) indicators to calibrate the RPA parameters. This calibration improves the correlation coefficient between the DO indicators and computed GRP values from 0.63 to 0.87. By comparing the initial values, these results indicate that the estimated RPA parameters better represent the field infiltration characteristic. This result also indicates that defining the RPA parameter values based on DO indicators is necessary and important for accuracy. These calibrated parameters are used to estimate the GRP distribution of Taiwan’s Pingtung Plain. The GRP values are delineated into five levels. High and excellent GRP areas are defined as high recharge areas, which compose about 26.74 % of the study area. Based on the proposed method, the estimated GRP distribution can accurately represent the study area’s field recharge characteristics. These study results can be a good reference for groundwater recharge analyses, specifically if well data is limited or difficult to obtain.

Effects of liquid layers and distribution patterns on three-phase saturation and relative permeability relationships: a micromodel study

In the current study, we used micromodel experiments to study three-phase fluid flow in porous media. In contrast to previous studies, we simultaneously observed and measured pore-scale fluid behavior and three-phase constitutive relationships with digital image acquisition/analysis, fluid pressure control, and permeability assays. Our results showed that the fluid layers significantly influenced pore-scale, three-phase fluid displacement as well as water relative permeability. At low water saturation, water relative permeability not only depended on water saturation but also on the distributions of air and diesel. The results also indicate that the relative permeability–saturation model proposed by Parker et al. (1987) could not completely describe the experimental data from our three-phase flow experiments because these models ignore the effects of phase distribution. A simple bundle-of-tubes model shows that the water relative permeability was proportional to the number of apparently continuous water paths before the critical stage in which no apparently continuous water flow path could be found. Our findings constitute additional information about the essential constitutive relationships involved in both the understanding and the modeling of three-phase flows in porous media.

Using a hybrid approach to optimize experimental network design for aquifer parameter identification.

This research develops an optimum design model of groundwater network using genetic algorithm (GA) and modified Newton approach, based on the experimental design conception. The goal of experiment design is to minimize parameter uncertainty, represented by the covariance matrix determinant of estimated parameters. The design problem is constrained by a specified cost and solved by GA and a parameter identification model. The latter estimates optimum parameter value and its associated sensitivity matrices. The general problem is simplified into two classes of network design problems: an observation network design problem and a pumping network design problem. Results explore the relationship between the experimental design and the physical processes. The proposed model provides an alternative to solve optimization problems for groundwater experimental design.

System Dynamics Modeling of the Conjunctive-Use of Surface and Subsurface Water

The conjunctive use of surface and subsurface water is used commonly for offering stable supplies in water resources management. Conventionally, the process of supply distribution model development can be classified as simulation method, describing system behaviors and operating rules directly, and optimization method, describing system behaviors by constraint equation and imitating operating rules by objective function. Owing to the allocation is spatial dependency and operating rules is temporal dependency, many researches prefer to construct conjunctive use models by “optimization method” then by “simulation method”. However, subject to the selected optimal methodology, such as linear programming or dynamic programming, modelers need to hypothesize or simplify the system. Hence, this study provides a powerful object oriented simulation modeling, system dynamics, alternative to optimization method for representing complex systems and analyzing their dynamics behavior. In system dynamics, the relation between structure and behavior is based on the concept of stock-flow diagrams. The process of model development, combining program flowchart with spatial system configuration, provokes modeler can build model easily. In this study, we also consider system expansion such as increasing new supply sources, and capacity expansion such as water treatment plant. We attempt to demonstrate this approach is a suitable methodology for constructing the complex