Applying Zonation Methods and Tabu Search to Improve the Ground‐Water Modeling1

Abstract: An optimization procedure combining zonation methods with the Tabu Search method is proposed to identify the spatial distribution of hydraulic conductivity field. Three zonation methods, Voronoi diagram (VD), multiplicatively weighted Voronoi diagram (MWVD), and pattern zonation are adopted for the parameterization purposes. With the consideration of the homogeneity and the heterogeneity, there are four spatial distributions of hydraulic conductivity designed to test whether the parameter structure can be successfully identified. The fitting residual error is first considered to determine an adequate number of zones without over parameterization. Then, the parameter uncertainty is evaluated the decision of the number of zones. The results indicate that the MWVD performs better than other two methods because the MWVD has better flexibility in describing the zonal boundaries with small number of decision variables.     

SIMULATED ANNEALING WITH MEMORY AND DIRECTIONAL SEARCH FOR GROUND WATER REMEDIATION DESIGN1

ABSTRACT: Review of recent literature indicates an emergence in the use of combinatorial methods such as simulated annealing in ground water management during the past nine to ten years. While previous studies demonstrated the feasibility of using these methods, a general finding was that computational processing requirements were inordinately high relative to gradient‐based methods. An enhanced annealing algorithm was developed and used to demonstrate the potential for greatly improving the computational efficiency of simulated annealing as an optimization method for ground water management applications. The algorithm incorporates “directional search” and “memory” capabilities. Selecting search directions based on better understanding of the current neighborhood of the configuration space was shown to improve algorithm performance. Also, “memory” concepts derived from the Tabu Search Method show particular promise for improving the rate and quality of convergence. Performance of the enhanced annealing method was evaluated and the resultant management method was demonstrated using an example from the literature.     

TWO PRACTICAL APPROACHES FOR DETERMINING THE CONFIDENCE INTERVAL OF RAINFALL DEPTH PERCENTILES1

ABSTRACT: A simple simulation type approach and a statistical method are proposed for determining the confidence interval of the T‐year frequency rainfall percentiles (or precipitation extremes) for generalized extreme value (GEV) distributions. The former method is based on the Monte Carlo testing procedure. To generate realizations, the covariance structure of the three parameters of GEV is investigated using an observed information matrix of the likelihood function. For distributions with realistic parameters, the correlation between the location and the scale parameters is practically constant when the shape parameter varies around values close to its optimal value. The latter method is based on likelihood ratio statistics. In the case where the joint confidence surface for shape parameters and estimates is plotted with lines of best estimates, the region where the estimated best percentile value can be chosen as a possible estimate is part of the joint confidence surface. The projection of this bounded region on axis of percentile is defined as the effective confidence interval in this research. The use of this effective interval as the confidence interval of the percentile of T‐year frequency rainfall is particularly recommended because it is stable for T and it reflects variations in all three parameters of GEV appropriately.     

A conceptual framework of agricultural land use planning with BMP for integrated watershed management

Land use planning is an important element of the integrated watershed management approach. It not only influences the environmental processes such as soil and stream bed erosion, sediment and nutrient concentrations in streams, quality of surface and ground waters in a watershed, but also affects social and economic development in that region. Although its importance in achieving sustainable development has long been recognized, a land use planning methodology based on a systems approach involving realistic computational modeling and meta-heuristic optimization is still lacking in the current practice of integrated watershed management. The present study proposes a new approach which attempts to combine computational modeling of upland watershed processes, fluvial processes and modern heuristic optimization techniques to address the water-land use interrelationship in its full complexity. The best land use allocation is decided by a multi-objective function that minimizes sediment yields and nutrient concentrations as well as the total operation/implementation cost, while the water quality and the production benefits from agricultural exploitation are maximized. The proposed optimization strategy considers also the preferences of land owners. The runoff model AnnAGNPS (developed by USDA), and the channel network model CCHE1D (developed by NCCHE), are linked together to simulate sediment/pollutant transport process at watershed scale based on any assigned land use combination. The greedy randomized adaptive Tabu search heuristic is used to flip the land use options for finding an optimum combination of land use allocations. The approach is demonstrated by applying it to a demonstrative case study involving USDA Goodwin Creek experimental watershed located in northern Mississippi. The results show the improvement of the tradeoff between benefits and costs for the watershed, after implementing the proposed optimal land use planning.     

OPTIMAL WEIGHTING FUNCTION IN WATER QUALITY MODELING1

ABSTRACT: In an earlier paper [1], the invariant imbedding concept was applied to the dynamic modeling of stream quality. In this approach, a set of weighting functions is introduced. The initial conditions for these weighting functions must be estimated. It has been found that these initial conditions influence the convergence rate tremendously. In many water quality control situations, the number of experimental data points are limited. In order to obtain the best estimates with limited experimental data, the best convergence rate should be used. In this work, the least squares criterion combined with various optimization techniques is ued to obtain the optimal initial conditions for the weighting functions. It is shown that the proposed schemes greatly improve the convergence rate.     

ESTIMATION OF OPTIMAL YIELD IN YUN-LIN AREA OF TAIWAN USING DECISION ANALYSIS1

ABSTRACT: Ground water is a vital resource in the Yun-Lin area of Taiwan. A substantial amount is continuously extracted, creating adverse effects such as land subsidence and seawater intrusion. Minimizing these negative impacts depends on regulating the rate of groundwater withdrawal. An optimal yield must be determined to establish a sound water management policy. A wide range of safe yields for Yun-Lin have already been proposed based on constant hydrological and hydrogeological parameters. By extending the results of those investigations, this study presents a decision analysis model. The optimal yield concept is introduced as well. The proposed model incorporates a probability density function for rainfall recharge and a loss function, derived from fluctuations in the ground water table. Through decision analysis, the optimum yield is obtained by minimizing the expected value of the loss function. The optimal yield varies monthly because the probability density function is time dependent. Analysis results suggest that the cumulative optimum yield of ground water in the area is 1.26 × 10⁸ m³/year. If the probability distribution function for rainfall recharge is modified as new precipitation data become available, the above suggested yield may require revision in the future.     

A LUMPED APPROACH TO THE INVERSE PROBLEM IN GROUND WATER HYDROLOGY1

ABSTRACT: A solution procedure to solve the inverse problem in ground water, based on lumped approach, has been proposed. The method has the following advantages: 1) exact determination of the boundary conditions and the physical laws of flow through porous media is not required; 2) all errors of approximation in describing the boundary conditions, physical laws, and the aquifer properties are lumped into the surrogate parameters; and 3) the same mathematical model can be employed both in the identification process and in the subsequent management studies. The optimal values of the surrogate parameters are found by using a multidimensional unconstrained optimization code devised by Powell. The solution procedure and the convergence characteristics of the proposed algorithm have been illustrated by two hypothetical problems.     

ANALYSIS OF FIRM WATER SUPPLY UNDER COMPLEX INSTITUTIONAL CONSTRAINTS1

River basin computer simulation studies often do not properly include the complex legal and institutional factors governing water allocation. These factors include formal water rights and informal borrowing agreements among the basin water users. An attempt has been made in this study to show that such factors can be included. We also show that an optimal, integrated approach to reservoir operations in a river basin can do much to alleviate the burden of new demands placed on available water resources. The procurement of a firm water supply for a proposed coal fired power plant is analyzed as a case study. An efficient river basin simulation model is used to determine the viability of a scheme for providing an annual firm water supply to the plant, with consideration of the existing water storage and demands within the basin. Given the hydrologic sequence considered, the model results show that the proposed strategy is viable in that the required firm water supply can be realized without causing harm to decreed water users in the basin. However, integrated diversion and reservoir operations are required to assure a desirable uniform rate of delivery of reusable effluent to the power plant.     

An approach to optimise nutrient management in environmental sanitation systems despite limited data

The material flow analysis method can be used to assess the impact of environmental sanitation systems on resource consumption and environmental pollution. However, given the limited access to reliable data, application of this data-intensive method in developing countries may be difficult. This paper presents an approach allowing to develop material flow models despite limited data availability. Application of an iterative procedure is of key importance: model parameter values should first be assessed on the basis of a literature review and by eliciting expert judgement. If model outputs are not plausible, sensitive input parameters should be reassessed more accurately. Moreover, model parameters can be expressed as probability distributions and variable uncertainty estimated by using Monte Carlo simulation. The impact of environmental sanitation systems on the phosphorus load discharged into surface water in Hanoi, Vietnam, is simulated by applying the proposed approach.     

Optimal Location and Management of Waste Disposal Facilities Affecting Ground Water Quality1

ABSTRACT: Numerical simulation of ground water solute transport is combined with linear programming to optimize waste disposal. A discretized form of the equation governing solute transport is included as a set of constraints in a linear program. Two problems are described. First, the management model is used to maximize ground water waste disposal. The model constrains disposal activities so that the quality of local ground water supplies is protected. Parametric programming is shown to be important in evaluating waste disposal tradeoffs at the various facilities. Changes in the velocity field induced by waste water injection cause a nonlinearity in the solute transport equation which is dealt with by employing an iterative procedure. The second problem is aimed at identifying all sites which are suitable for waste disposal in the subsurface. The management model is manipulated so that the optimal value of the dual variables are “unit source impact indicators.” This physical interpretation is valuable in identifying feasible disposal sites. The joint simulation and optimization approach permits the management of complex ground water systems where the aquifer is used simultaneously for waste disposal and water supply.     

Optimal water quality monitoring network design for river systems

Typical tasks of a river monitoring network design include the selection of the water quality parameters, selection of sampling and measurement methods for these parameters, identification of the locations of sampling stations and determination of the sampling frequencies. These primary design considerations may require a variety of objectives, constraints and solutions. In this study we focus on the optimal river water quality monitoring network design aspect of the overall monitoring program and propose a novel methodology for the analysis of this problem. In the proposed analysis, the locations of sampling sites are determined such that the contaminant detection time is minimized for the river network while achieving maximum reliability for the monitoring system performance. Altamaha river system in the State of Georgia, USA is chosen as an example to demonstrate the proposed methodology. The results show that the proposed model can be effectively used for the optimal design of monitoring networks in river systems.     

Determining the robust optimal set of BMPs for urban runoff management in data-poor catchments

Mismanagement of urban runoff can result in inundation which causes serious problems in providing urban services. Best management practices (BMPs) are used for urban runoff management. In this study, a method is proposed to determine the robust optimal set of BMPs for runoff management in data-poor catchments in urban areas. This method includes five main steps: (1) Sensitivity analysis to determine effective parameters in rainfall-runoff simulation model, (2) Calibration of the rainfall-runoff model based on selected effective parameters, (3) Developing a multi-objective optimization model to obtain the optimal sets of BMPs, (4) Selecting the final solutions using the Nash approach for ranking, (5) Evaluation of the robustness of the selected solution using the Management Option Rank Equivalence method. The proposed method is examined in an urban basin located in the north of Tehran, Iran. The results show that the proposed approach provides reliable results for urban runoff management in data-poor areas.     

Design and operational parameters of a rooftop rainwater harvesting system: definition, sensitivity and verification

The appropriate design and evaluation of a rainwater harvesting (RWH) system is necessary to improve system performance and the stability of the water supply. The main design parameters (DPs) of an RWH system are rainfall, catchment area, collection efficiency, tank volume and water demand. Its operational parameters (OPs) include rainwater use efficiency (RUE), water saving efficiency (WSE) and cycle number (CN). The sensitivity analysis of a rooftop RWH system's DPs to its OPs reveals that the ratio of tank volume to catchment area (V/A) for an RWH system in Seoul, South Korea is recommended between 0.03 and 0.08 in terms of rate of change in RUE. The appropriate design value of V/A is varied with D/A. The extra tank volume up to V/A of 0.15～0.2 is also available, if necessary to secure more water. Accordingly, we should figure out suitable value or range of DPs based on the sensitivity analysis to optimize design of an RWH system or improve operation efficiency. The operational data employed in this study, which was carried out to validate the design and evaluation method of an RWH system, were obtained from the system in use at a dormitory complex at Seoul National University (SNU) in Korea. The results of these operational data are in good agreement with those used in the initial simulation. The proposed method and the results of this research will be useful in evaluating and comparing the performance of RWH systems. It is found that RUE can be increased by expanding the variety of rainwater uses, particularly in the high rainfall season.     

OPTIMUM STORAGE VOLUME OF ROOFTOP RAIN WATER HARVESTING SYSTEMS FOR DOMESTIC USE1

ABSTRACT: Major parameters and optimum storage volumes of rooftop rain water harvesting systems (RRWHSs) have not been investigated in detail in Taiwan. Accordingly, the four major parameters of RRWHSs were herein identified and elucidated using a simulation method. Because the performance of the RRWHSs is sensitive to the runoff coefficient, a field experiment was conducted to determine the runoff coefficient more precisely for various types of roofs. A simulation model including production theory was developed and employed to estimate the most cost effective combination of the roof area and the storage capacity that best supplies a specific volume of water. Consequently, the expansion path of optimum solutions for different volumetric reliability of water supply can be determined. Additionally, the method based on the marginal rate of substitution can be used for determining the rational volumetric reliability. The procedures developed herein constitute an effective tool for preliminarily estimating the most satisfactory storage capacity of any specific roof area and for determining the rational reliability of a corresponding water supply.     

A HYBRID OPTIMIZATION APPROACH TO THE ESTIMATION OF DISTRIBUTED PARAMETERS IN TWO-DIMENSIONAL CONFINED AQUIFERS1

ABSTRACT: In using non-linear optimization techniques for estimation of parameters in a distributed ground water model, the initial values of the parameters and prior information about them play important roles. In this paper, the genetic algorithm (GA) is combined with the truncated-Newton search technique to estimate groundwater parameters for a confined steady-state ground water model. Use of prior information about the parameters is shown to be important in estimating correct or near-correct values of parameters on a regional scale. The amount of prior information needed for an accurate solution is estimated by evaluation of the sensitivity of the performance function to the parameters. For the example presented here, it is experimentally demonstrated that only one piece of prior information of the least sensitive parameter is sufficient to arrive at the global or near-global optimum solution. For hydraulic head data with measurement errors, the error in the estimation of parameters increases as the standard deviation of the errors increases. Results from our experiments show that, in general, the accuracy of the estimated parameters depends on the level of noise in the hydraulic head data and the initial values used in the truncated-Newton search technique.     

Design and analysis of artificial bee-colony-based MPPT algorithm for DFIG-based wind energy conversion systems

In this article, the proposed maximum power point tracking (MPPT) method is designed by taking rotor speed as an optimization problem, which is solved by artificial bee colony (ABC) algorithm to generate the maximum power output. The main advantage of this algorithm is that its optimal solution is independent of the initial positions and requirement of lesser number of control parameters, which leads to simple and robust MPPT algorithm than other algorithm. Furthermore, the hill climb search and particle swarm optimization-based MPPT algorithm are also discussed and the results obtained by these are compared to verify the effectiveness of proposed algorithm. Simulations for MPPT control along with doubly fed induction-generator-based wind energy conversion system is carried out in MATLAB/Simulink environment. Three statistical methods are used to evaluate the accuracy of each MPPT algorithm. All results are analyzed and compared under randomly selected wind as well as real wind speed configuration. Comparison of both numerical and simulation results under two different varying wind speed conditions strongly suggest that the proposed ABC-based MPPT algorithm is superior than other two MPPT algorithms.     

Monograph on desilting basins sizes estimation for hydropower projects

At times, various analytical and empirical approaches used to estimate the initial sizing of a desilting basin in a hydropower project would give very different results and the designer has to take a call judiciously. The purpose of this study is to develop a monograph based on Teaching–Learning-Based Optimization and Gravitational Search algorithm for a practical range of depth of desilting basins. The parameters commonly used in hydropower projects for estimation of desilting basins sizing and its efficiency are used in this study. The outcome is further verified using a list of mega hydropower projects. This study will be useful in fixing the best optimized dimension of desilting basins.     

GROUND WATER DROUGHT MANAGEMENT BY A FEEDFORWARD CONTROL METHOD1

ABSTRACT: Management of a regional ground water system to mitigate drought problems at the multi‐layered aquifer system in Collier County, Florida, is the main topic. This paper developed a feedforward control system that consists of system and control equations. The system equation, which forecasts ground water levels using the current measurements, was built based on the Kalman filter algorithm associated with a stochastic time series model. The role of the control equation is to estimate the pumping reduction rate during an anticipated drought. The control equation was built based on the empirical relationship between the change in ground water levels and the corresponding pumping requirement. The control system starts with forecasting one‐month‐ahead ground water head at each control point. The forecasted head is in turn used to calculate the deviation of ground water heads from the monthly target specified by a 2‐in‐10‐year frequency. When the forecasted water level is lower than the target, the control system computes spatially‐varied pumping reduction rates as a recommendation for ground water users. The proposed control system was tested using hypothetical droughts. The simulation result revealed that the estimated pumping reduction rates are highly variable in space, strongly supporting the idea of spatial forecasting and controlling of ground water levels as opposed to a lumped water use restriction method used previously in the model area.     

Application of best subset method for river water quality modeling: A study on Godavari River,India

The utilization of water quality analysis to inform optimal decision-making is imperative to achieve sustainable management of river water quality. A multitude of research works in the past has focused on river water quality modeling. Despite being a precise statistical regression technique that allows for fitting separate models for all potential combinations of predictors and selecting the optimal subset model, the application of best subset method in river water quality modeling is not widely adopted. The current research aims to validate the use of best subset method in evaluating the water quality parameters of the Godavari River, one of the largest rivers in India, by developing regression equations for different combinations of its physicochemical parameters. The study involves in formulating best subset regression equations to estimate the concentrations of river water quality parameters while also identifying and quantifying their variations. A total of 17 water quality parameters are analyzed at 13 monitoring sites using 13 years (1993–2005) of observed data for the monsoon (June–October) period and post-monsoon (November–February) period. The final subset model is selected among model combinations that are developed for each year's dataset through widely used statistical criteria such as R², F value, adjusted R²_a, AIC_c, and RSS. The final best subset model across all parameters exhibits R² values surpassing 0.8, indicating that the models possess the ability to account for over 80% of the variations in the concentrations of dependent parameters. Therefore, the findings demonstrated the appropriateness of this method in evaluating the water quality parameters in extensive rivers. This work is very useful for decision-making and in the management of river water quality for its sustainable use in the study area.     

OPTIMUM USE OF PADDY FIELDS FOR FLOOD MITIGATION1

In Taiwan, the continuously increasing levels of rice imports are likely to result in surplus paddy fields. Hence, the surplus paddy fields may be developed into wetlands to increase ground water recharge, provide appropriate environments for wildlife, and most importantly, store flood water. This study developed a hydrological model incorporating the distributed rainfall‐runoff model based on the kinematics wave approach and the distributed tank model for simulation, respectively, in mountainous and flat areas. The hydrological model was found to simulate the rainfall‐runoff behavior well in the study area. Furthermore, a decision method based on the genetic algorithm concepts was proposed to give policy makers the optimal location and area size of paddy fields to construct wetlands for flood mitigation.