R. C. Peralta

Optimal design of aquifer cleanup systems under uncertainty using a neural network and a genetic algorithm

We present a methodology to account for the stochastic nature of hydraulic conductivity during the design of pump-and-treat systems for aquifer cleanup. The methodology (1) uses a genetic algorithm to find the global optimal solution and (2) incorporates a neural network to model the response surface within the genetic algorithm. We apply the methodology for a real example and different optimization scenarios. The employed optimization formulation requires few hydraulic conductivity realizations. The presented approach produces a trade-off curve between reliability and treatment facility size.

Comparison of a genetic algorithm and mathematical programming to the design of groundwater cleanup systems

We present and apply a new simulation/optimization approach for single- and multiple-planning period problems in groundwater remediation. Instead of the traditional control locations for contaminant concentrations, we use an L∞ norm as a global measure of aquifer contamination (CMAX). We use response-surface constraints to represent CMAX within the optimization model. We compare the performance of formal mixed integer nonlinear programming and a genetic algorithm for several optimization scenarios.

Integrated embedding optimization applied to Salt Lake Valley aquifers

The embedding optimization modeling approach is adapted to aid sustainable groundwater quantity and quality management of complex nonlinear multilayer aquifers. Implicit block-centered finite difference approximations of the quasi three-dimensional unsteady flow equation and Galerkin finite element approximations of the two-dimensional advection-dispersion transport equation are embedded directly as constraints in the model. Also used are nonlinear constraints describing river-aquifer interflow, evapotranspiration, and vertical flow reduction due to unconfinement. These circumvent use of large numbers of integer variables. The use of both linear and nonlinear formulations in a cyclical manner reduces execution time and improves confidence in solution optimality. The methodology is demonstrated for Salt Lake valley where groundwater quantity and quality management are needed, the proportion of pumping cells and cells needing head constraint is large, and many flows are described by discrete nonlinear or piece wise linear functions.

Maximizing conjunctive use of surface and ground water under surface water quality constraints

Abstract A simulation/optimization (s/o) model is presented to address the increasingly common conflicts between water quantity and quality objectives. The model can assist water resources analysts in selecting compromise strategies for stream/aquifer systems in which the stream gains water from the aquifer. The water quantity objective is to maximize steady conjunctive use of groundwater and surface water resources. The water quality objective is to maximize waste loading from a sewage treatment plant (STP) to the stream without violating downstream water quality beyond acceptable limits. The STP discharge is proportional to human population. The two objectives conflict because an increase in groundwater extraction reduces dilution of the stream water contaminants. The result is a decrease in the STP waste loading to the stream and the waste-producing human population that can be supported. The trade-off between objectives is illustrated graphically via sets of noninferior solutions. The sets of noninferior solutions are prepared using the E-constraint method and assuming different upstream flow rates. The s/o model includes superposition expressions describing head and flow responses to decision variables (pumping, diversion, and loadings) and regression expressions describing contaminant concentration responses to these decision variables. Modeled contaminants include: 5-day biochemical oxygen demand, dissolved oxygen, nitrogen (organic, ammonia, nitrite, and nitrate), organic and dissolved phosphorus, total dissolved solids, and chlorophyll-a.

Optimizing separate phase light hydrocarbon recovery from contaminated unconfined aquifers

Abstract A modeling approach is presented that optimizes separate phase recovery of light non-aqueous phase liquids (LNAPL) for a single dual-extraction well in a homogeneous, isotropic unconfined aquifer. A simulation/regression/optimization (S/R/O) model is developed to predict, analyze, and optimize the oil recovery process. The approach combines detailed simulation, nonlinear regression, and optimization. The S/R/O model utilizes nonlinear regression equations describing system response to time-varying water pumping and oil skimming. Regression equations are developed for residual oil volume and free oil volume. The S/R/O model determines optimized time-varying (stepwise) pumping rates which minimize residual oil volume and maximize free oil recovery while causing free oil volume to decrease a specified amount. This S/R/O modeling approach implicitly immobilizes the free product plume by reversing the water table gradient while achieving containment. Application to a simple representative problem illustrates the S/R/O model utility for problem analysis and remediation design. When compared with the best steady pumping strategies, the optimal stepwise pumping strategy improves free oil recovery by 11.5% and reduces the amount of residual oil left in the system due to pumping by 15%. The S/R/O model approach offers promise for enhancing the design of free phase LNAPL recovery systems and to help in making cost-effective operation and management decisions for hydrogeologists, engineers, and regulators.

Modeling for Optimal Management of Agricultural and Domestic Wastewater Loading to Streams

A simulation(optimization (S/O) model to aid managing multiobjective wastewater loading to streams while maintaining adequate downstream water quality is presented. The conflicting objectives are to maximize the human and dairy cattle populations from which treated wastewater can be discharged to the river system. Nonindustrial municipal (domestic) wastewater undergoes primary and secondary treatment by a sewage treatment plant (STP) before entering as a steady point source. Dairy wastewater is treated by overland flow (OLF) land treatment before entering the stream as a controlled steady diffuse source. Maximum dual-source loading strategies which do not degrade downstream water quality beyond specified limits are developed. For each computed loading strategy, an optimal OLF system design is also determined. The E constraint method is used to obtain sets of noninferior solutions. Sets of noninferior solutions are represented graphically to show the trade-off between human and bovine populations that can be maintained. Each set is computed for a different upstream flow rate to illustrate sensitivity to nondeterministic upstream flow rates. The nonlinear constraints utilized restrict downstream concentrations of 5-day biochemical oxygen demand, dissolved oxygen, nitrogen (organic, ammonia, nitrite, and nitrate), organic and dissolved phosphorus, and chlorophyll a. Concentrations are described via regression equations. The new regression expressions, surrogates for the complex advective-dispersive equation, permit rapid and feasible solutions by this unique S/O model.

Interactive computer graphics-based multiobjective decision-making for regional groundwater management

This paper presents a comprehensive set of procedures by which decision-makers can select a single strategy from a set of alternative strategies. Application of these procedures in developing a regional conjunctive water management strategy for an important rice producing area in Arkansas, U.S.A., is described. The importance of interactive decision-making and efficient presentation of information through interactive graphics and computations is also demonstrated. The optimization model considers two different objectives: minimization of the total cost of water use (including opportunity cost due to the loss in agricultural production caused by non-availability of water); and maximization of total withdrawal (pumping) from the aquifer. Application of the surrogate worth tradeoff method together with interactive computer graphics display of relevant information is presented as part of the procedures for selecting a regional sustained groundwater withdrawal strategy.

Optimal perennial yield planning for complex nonlinear aquifers: Methods and examples

Abstract Optimal perennial groundwater yield pumping strategies were computed for a complex multilayer aquifer with: (i) confined and unconfined flow, and (ii) many flows typically described by piecewise-linear (nonsmooth) equations. The latter flows account for over 50% of the aquifer discharge from the test area, the eastern shore of the Great Salt Lake in Utah. Normally utilized response matrix (RM) and embedding (EM) simulation/optimization modelling procedures did not converge to optimal solutions for this area; they diverged or oscillated. However, the newly presented linear RM and EM approaches satisfactorily addressed the nonlinearities posed by over 2000 piecewise-linear constraints for evapotranspiration, discharge from flowing wells, drain discharge, and vertical interlayer flow reduction due to desaturation of a confined aquifer. Both presented modelling approaches converged to the same optimal solution. Superposition was applied to the nonlinear problem by: making a cycle within the RM analogous to an iteration in a simulation model (such as MODFLOW); and using a modified MODFLOW to develop influence coefficients. The EM model contained about 40 000 nonzero elements and 12 000 single equations and variables, demonstrating its suitability for large scale planning.

Maximizing reliable crop production in a dynamic stream/aquifer system

ABSTRACT Aprocedure for planning the optimal spatial distri-bution of crops to be reliably irrigated by conjunctive use of water resources is presented. The implicitly stochastic procedure utilizes a simulation/optimization model of a stream/aquifer system. The model utilizes linear optimization, hydrologic influence coefficients and time-varying crop water production functions. It appropriately simulates the time variant, interdependent responses of groundwater levels, stream stages and stream/aquifer interflow to groundwater pumping and diversion of river water to nonriparian lands. It determines the temporally and spatially varying distribution of groundwater and diverted river water that should be utilized in order to maximize annual crop yield in a water management district. The diversion of river water to nonriparian land and stream/aquifer interflow are constrained such that effluent from the district through the river satisfies downstream requirements. The model can be used to develop optimal seasonal water use strategies that are in harmony with long-term water use and agricultural development strategies. In that case it represents a suboptimization model applicable for either a period of regional potentiometric surface evolution or a steady-state era. If applied during an era in which the potentiometric surface is maintained at relatively constant elevations, groundwater pumping and recharge are managed such that groundwater levels return to their initial elevations by the end of a one-year simulation period. Thus, if the initial elevations are satisfactory, the optimal strategy is a safe sustained yield conjunctive water management strategy

Stepwise pumping approach to improve free phase light hydrocarbon recovery from unconfined aquifers

Abstract A stepwise, time-varying pumping approach is developed to improve free phase oil recovery of light non-aqueous phase liquids (LNAPL) from a homogeneous, unconfined aquifer. Stepwise pumping is used to contain the floating oil plume and obtain efficient free oil recovery. The graphical plots. The approach uses ARMOS