Alper Elçi

Evaluation of a conceptual model for the subsurface transport of plutonium involving surface mediated reduction of Pu(V) to Pu(IV)

A conceptual model is proposed to explain the transport behavior of plutonium in laboratory columns packed with a sandy coastal soil from the U.S. Department of Energy (DOE)s Savannah River Site. The column transport experiments involved the introduction of a finite step input of plutonium, predominately in the +5 oxidation state, into the columns followed by elution with a low-carbonate solution of 0.02 M NaClO4 at pH 3, 5, and 8. Total plutonium concentrations were measured in the effluent as a function of time. These elution profiles suggest at least two distinct physical/chemical forms of plutonium, each with a different mobility. To explain the observed behavior, the following conceptual model was evaluated: [1] equilibrium partitioning of plutonium (V) and plutonium (IV) between the aqueous and sorbed phases as defined by pH-dependent, oxidation-state specific distribution coefficients and [2] kinetic reduction of plutonium (V) to plutonium (IV) in the sorbed phase. The conceptual model was applied to the column experiments through a one-dimensional advective/dispersive mathematical model, and predictions of the mathematical model were compared with the experimental data. Overall, the model was successful in predicting some of the major features observed in the experiments. It also yielded quantitative estimates of the rate constant for surface mediated reduction of plutonium (V) to plutonium (IV) that were of the same order (10(-4) to 10(-5) s(-1)) as those calculated from batch data both for this soil and for goethite.

Statistical Analysis of Causes of Death (2005–2010) in Villages of Simav Plain, Turkey, With High Arsenic Levels in Drinking Water Supplies

The purpose of this research was to compare the causes of death in 5 villages situated in Simav Plain, Turkey, during 2005–2010 where different arsenic levels were detected in drinking water supplies. Since groundwater in Simav Plain had arsenic concentrations that ranged between 7.1 and 833.9 ppb, a two-phase research was formulated. In the first phase, public health surveys were conducted with 1,003 villagers to determine the distribution of diseases. In the second phase, verbal autopsy surveys and official death records were used to investigate the causes of death. In total, 402 death cases were found in the study area where cardiovascular system diseases (44%) and cancers (15.2%) were major causes. Cancers of lung (44.3%), prostate (9.8%), colon (9.8%), and stomach (8.2%) were comparably higher in villages with high arsenic levels in drinking water supplies. Furthermore, the majority of cases of liver, bladder, and stomach cancers were observed in villages with high arsenic levels.

Assessment of the statistical significance of seasonal groundwater quality change in a karstic aquifer system near Izmir-Turkey

The main objective of this study was to statistically evaluate the significance of seasonal groundwater quality change and to provide an assessment on the spatial distribution of specific groundwater quality parameters. The studied area was the Mount Nif karstic aquifer system located in the southeast of the city of Izmir. Groundwater samples were collected at 57 sampling points in the rainy winter and dry summer seasons. Groundwater quality indicators of interest were electrical conductivity (EC), nitrate, chloride, sulfate, sodium, some heavy metals, and arsenic. Maps showing the spatial distributions and temporal changes of these parameters were created to further interpret spatial patterns and seasonal changes in groundwater quality. Furthermore, statistical tests were conducted to confirm whether the seasonal changes for each quality parameter were statistically significant. It was evident from the statistical tests that the seasonal changes in most groundwater quality parameters were statistically not significant. However, the increase in EC values and aluminum concentrations from winter to summer was found to be significant. Furthermore, a negative correlation between sampling elevation and groundwater quality was found. It was shown that with simple statistical testing, important conclusions can be drawn from limited monitoring data. It was concluded that less groundwater recharge in the dry period of the year does not always imply higher concentrations for all groundwater quality parameters because water circulation times, lithology, quality and extent of recharge, and land use patterns also play an important role on the alteration of groundwater quality.

The combined use of MODFLOW and precipitation-runoff modeling to simulate groundwater flow in a diffuse-pollution prone watershed

A numerical modeling case study of groundwater flow in a diffuse pollution prone area is presented. The study area is located within the metropolitan borders of the city of Izmir, Turkey. This groundwater flow model was unconventional in the application since the groundwater recharge parameter in the model was estimated using a lumped, transient water-budget based precipitation-runoff model that was executed independent of the groundwater flow model. The recharge rate obtained from the calibrated precipitation-runoff model was used as input to the groundwater flow model, which was eventually calibrated to measured water table elevations. Overall, the flow model results were consistent with field observations and model statistics were satisfactory. Water budget results of the model revealed that groundwater recharge comprised about 20% of the total water input for the entire study area. Recharge was the second largest component in the budget after leakage from streams into the subsurface. It was concluded that the modeling results can be further used as input for contaminant transport modeling studies in order to evaluate the vulnerability of water resources of the study area to diffuse pollution.

Groundwater Recharge Rate and Zone Structure Estimation Using PSOLVER Algorithm

The quantification of groundwater recharge is an important but challenging task in groundwater flow modeling because recharge varies spatially and temporally. The goal of this study is to present an innovative methodology to estimate groundwater recharge rates and zone structures for regional groundwater flow models. Here, the unknown recharge field is partitioned into a number of zones using Voronoi Tessellation (VT). The identified zone structure with the recharge rates is associated through a simulation-optimization model that couples MODFLOW-2000 and the hybrid PSOLVER optimization algorithm. Applicability of this procedure is tested on a previously developed groundwater flow model of the Tahtalı Watershed. Successive zone structure solutions are obtained in an additive manner and penalty functions are used in the procedure to obtain realistic and plausible solutions. One of these functions constrains the optimization by forcing the sum of recharge rates for the grid cells that coincide with the Tahtalı Watershed area to be equal to the areal recharge rate determined in the previous modeling by a separate precipitation-runoff model. As a result, a six-zone structure is selected as the best zone structure that represents the areal recharge distribution. Comparison to results of a previous model for the same study area reveals that the proposed procedure significantly improves model performance with respect to calibration statistics. The proposed identification procedure can be thought of as an effective way to determine the recharge zone structure for groundwater flow models, in particular for situations where tangible information about groundwater recharge distribution does not exist.

Application of the Hybrid HS–Solver Algorithm to the Solution of Groundwater Management Problems

This chapter presents a state-of-the-art procedure to solve groundwater management problems. The procedure integrates the MODFLOW, which is a modular, finite difference based groundwater flow model, solution of a given groundwater system with the hybrid HS–Solver optimization algorithm in an optimization framework. HS–Solver is a recently proposed hybrid optimization algorithm where the heuristic harmony search (HS) algorithm and a spreadsheet called “Solver” are used. The main advantage of using the HS–Solver algorithm is that HS and Solver work mutually by feeding each other in terms of initial and subinitial solution points to avoid local optima. According to our current knowledge, the implementation of the hybrid HS–Solver algorithm for the solution of groundwater management models has not been proposed elsewhere and is novel in the area of groundwater hydrology. The performance of the proposed simulation–optimization procedure is evaluated on two examples. Identification results indicate that the proposed simulation–optimization approach produces identical or better results than the other solution approaches and may be effectively used in the sustainable management of real aquifer systems.

Assessing the Impact of Climate Change on Groundwater Resources Using Groundwater Flow Models

Climate change is a potential stressor of groundwater resources and its effects on the availability of groundwater need to be understood and determined. The impacts of climate change on groundwater systems are conceptually known, however in the context of climate change impact assessment there has been little research conducted on groundwater compared to surface water resources. One of the tools used to quantify the effects of climate change is to use groundwater flow models in conjunction with downscaled GCM (global circulation model) results and groundwater recharge estimation. The purpose of this study is to present an overview of groundwater modeling approaches to assess the impacts of climate change on groundwater resources. Basic requirements, challenges and different approaches to overcome them are presented. The principal challenge of any climate change impact study is the downscaling of GCM results to the basin scale. Furthermore, the estimation of the impacted groundwater recharge is particularly important in groundwater modeling studies. A summary of case studies demonstrating the various methodologies are provided, following with an overview of a recent climate change impact study conducted for Tahtali stream basin in Turkey.

The Health Risk Associated with Chronic Diseases in Villages with High Arsenic Levels in Drinking Water Supplies

This study is intended to compare and assess the distribution and possible causes of current chronic diseases in villages with high arsenic levels in drinking water supplies. It is a cross-sectional epidemiological research that analyzes the frequency and underlying risk factors of chronic diseases in villages with varying levels of arsenic exposure through drinking water. Sample space of study included 1003 individuals, 614 of whom were from villages with high arsenic levels in drinking water and remaining 389 were from two control villages with below-limit arsenic levels in drinking water. While nutritional habits and living environments of two groups were similar, cigarette smoking and alcohol use were higher in villages with low arsenic levels. Mini mental state examination test results in 60+ age group were lower in villages with high arsenic levels. Although no statistically significant differences were detected in chronic disease occurrence between the groups, the number of cases was higher in villages with higher percentage of cigarette smoking and alcohol use. Moreover, cases of lung, colon, and stomach cancers were higher in villages with high arsenic levels in drinking water supplies.

Evaluation of nutrient retention in vegetated filter strips using the SWAT model

Nutrient fluxes in stream basins need to be controlled to achieve good water quality status. In stream basins with intensive agricultural activities, nutrients predominantly come from diffuse sources. Therefore, best management practices (BMPs) are increasingly implemented to reduce nutrient input to streams. The objective of this study is to evaluate the impact of vegetated filter strip (VFS) application as an agricultural BMP. For this purpose, SWAT is chosen, a semi-distributed water quality assessment model that works at the watershed scale, and applied on the Nif stream basin, a small-sized basin in Western Turkey. The model is calibrated with an automated procedure against measured monthly discharge data. Nutrient loads for each sub-basin are estimated considering basin-wide data on chemical fertilizer and manure usage, population data for septic tank effluents and information about the land cover. Nutrient loads for 19 sub-basins are predicted on an annual basis. Average total nitrogen and total phosphorus loads are estimated as 47.85 t/yr and 13.36 t/yr for the entire basin. Results show that VFS application in one sub-basin offers limited retention of nutrients and that a selection of 20-m filter width is most effective from a cost-benefit perspective.

Calibration of groundwater vulnerability mapping using the generalized reduced gradient method

Groundwater vulnerability assessment studies are essential in water resources management. Overlay-and-index methods such as DRASTIC are widely used for mapping of groundwater vulnerability, however, these methods mainly suffer from a subjective selection of model parameters. The objective of this study is to introduce a calibration procedure that results in a more accurate assessment of groundwater vulnerability. The improvement of the assessment is formulated as a parameter optimization problem using an objective function that is based on the correlation between actual groundwater contamination and vulnerability index values. The non-linear optimization problem is solved with the generalized-reduced-gradient (GRG) method, which is numerical algorithm based optimization method. To demonstrate the applicability of the procedure, a vulnerability map for the Tahtali stream basin is calibrated using nitrate concentration data. The calibration procedure is easy to implement and aims the maximization of correlation between observed pollutant concentrations and groundwater vulnerability index values. The influence of each vulnerability parameter in the calculation of the vulnerability index is assessed by performing a single-parameter sensitivity analysis. Results of the sensitivity analysis show that all factors are effective on the final vulnerability index. Calibration of the vulnerability map improves the correlation between index values and measured nitrate concentrations by 19%. The regression coefficient increases from 0.280 to 0.485. It is evident that the spatial distribution and the proportions of vulnerability class areas are significantly altered with the calibration process. Although the applicability of the calibration method is demonstrated on the DRASTIC model, the applicability of the approach is not specific to a certain model and can also be easily applied to other overlay-and-index methods.