Menderes River Research Articles

Assessment of artificial aquifer recharge potential in the Kucuk Menderes River Basin, Turkey

The Kucuk Menderes River Basin in western Turkey has been facing continuous groundwater-level decline for decades. Previous studies have suggested that, to avoid aquifer depletion in the basin, artificial recharge structures should be constructed. To assess artificial aquifer recharge potential in one of the subbasins, a two-dimensional (2-D) groundwater model was set up using SEEP/W software. The material functions and parameters used in the model for both saturated and unsaturated conditions were taken from previous studies. The model has been calibrated under transient conditions. The excess runoff volume that could be collected in the recharge basins was estimated from flood frequency analysis. Various scenarios were simulated to observe the change in groundwater level and storage with respect to different exceedance probabilities. Simulation results suggest that a significant increase in groundwater storage is achieved by applying surface artificial-recharge methods. In addition to the recharge basins, to reinforce the effect of artificial recharge, simulations are repeated with underground dam construction at the downstream side of the basin. Although groundwater storage is increased with the addition of the dam, the increase in groundwater storage was not sufficient to warrant the construction.

Concentrations of 137Cs in Sediment and Waters of Buyuk Menderes River and Dilek Peninsula Buyuk Menderes Delta

In this study were determined the concentrations of 137 Cs in sediment and waters collected from Buyuk

Concentrations of trace elements aluminum, boron, cobalt and tin in various wild edible mushroom species from Buyuk Menderes River Basin of Turkey by ICP-OES

Concentrations of trace elements aluminum, boron, cobalt and tin in various wild edible mushroom species from Buyuk Menderes River Basin of Turkey by ICP-OES

Effects of boron pollution in the lower buyuk menderes basin (Turkey) on agricultural areas and crops

AbstractThe aim of this study is to study the effects of Boron (B) pollution in Buyuk Menderes river on planted crops and agricultural areas constructed in the irrigation schemes by the State Hydraulic Works (DSI) of the Lower Buyuk Menderes basin, Turkey. The studied irrigation schemes in the basin are Saraykoy, Pamukkale, Nazilli, Aydin, Sultanhisar, Koçarli, and Soke. Mean B concentrations of river water used in the irrigation schemes ranged from 0.10 to 0.43 mgB L−1 for the period of 2008 to 2009. A total of 100,556 ha of the agricultural area and the basin groundwater resources are under the influence of B pollution from the Buyuk Menderes river. The amount of B accumulating in soils and seepage in the groundwater due to the used irrigation water was 18,495,350 and 9153 kgB yr−1, respectively. B accumulating in the irrigated area ranged from 670 to 4521 gB ha−1 yr−1. In total, 19,410,650 kg yr−1 of B have negatively affected the agricultural areas, groundwater resources, and environmental conditions. Nazilli and Sultanhisar irrigation areas are under the threat of wastewater discharges originating from the Kizildere geothermal power plant and Tekke thermal spring. Particularly, fruit crops such as citrus, peach, plum, fig, olive, and wheat, strawberry, sunflower are to be negatively affected by the present B concentrations in the irrigation water. © 2010 American Institute of Chemical Engineers Environ Prog, 2011

PCB pollution and macromolecular damage in Cyprinus carpio in Buyuk Menderes River: From ecotoxicology to risk assessment

PCB pollution and macromolecular damage in Cyprinus carpio in Buyuk Menderes River: From ecotoxicology to risk assessment

Groundwater Quality Degradation in the Buyuk Menderes River Coastal Wetland

A baseline hydrogeochemical investigation was carried out as a contribution to the inventory of wetlands in Buyuk Menderes River (BMR) coastal wetland which is the most important wetland in Turkey that is protected as “Natural Park” by government. In addition to the wetland values, agricultural activities are also important at this delta. From inland to coastal zone, the groundwater type is changed from Ca–HCO3 to Na–Cl. Perfect correlation of Cl with Na and SO4 indicated the mixing process between saline and fresh water. The seawater intrusion and “winter-leaching” is the main causes of salinization. Minor ions as B, Br, and Li versus Cl relationship also showed the marine influence at the BMR coastal wetland. The δ18O and δD composition of the waters are range between −8.11‰ and −1.65‰ and −49.2‰ and 8.1‰, respectively. Isotope values show the seawater mixing line and also dissolution of salts in the BMR coastal wetland. Weathering of aluminosilicates in the Paleozoic schist and clays resulted in the release of silica to the water. Due to the organic activity, iron concentrations reached to the tolerance limits. On the other hand, the use of phosphate fertilizers increases the phosphorus content in the water. The high value of As (from 0.6 to 134 μg/l) can be resulted as an evaporation process in the study area.

Analysis of spatial and temporal variation in the levels of microbial fecal indicators in the major rivers flowing into the Aegean Sea, Turkey

River watersheds in the western part of Turkey (Aegean Sea) are anthropogenically impacted areas, due to the high population density, intensive agricultural and/or industrial activities. The aim of the present survey was to assess the microbiological quality of river waters using indicators of fecal contamination. Five rivers (Meric, Bakircay, Gediz, Kucuk Menderes and Buyuk Menderes) were sampled as seasonally from 2006 to 2008 for fecal coliforms, and fecal streptococci. In order to determine the number of fecal indicator bacteria, membrane filtration method was used. The minimum fecal coliforms and fecal streptococci were counted from the samples taken from the Buyuk Menderes River (5 × 10 1–3 × 10 1 CFU/100 ml) especially in the spring and autumn. The highest fecal coliform result was obtained in winters (1.3 × 10 6 CFU/100 ml) while maximum fecal streptococci value was detected in autumns (6.3 × 10 4 CFU/100 ml) in the Kucuk Menderes River during 2006–2008. Additionally, the relationships between the fecal indicator bacteria and physico-chemical parameters (temperature, conductivity and pH) were also evaluated, but no significant relationships were observed between the fecal indicator bacteria and environmental parameters. Considering the findings of these studies, it can be said that there is fecal pollution in the rivers reaching the Aegean Sea. The results show that there are a great number of microbial pollution sources in the areas where the river passes through and thus, in order to implement strategies to improve water quality in these rivers, monitoring of these rivers should continue.

Potential use of the oligochaete Limnodrilus profundicola V., as a bioindicator of contaminant exposure

Cholinesterase (ChE) and ethoxyresorufin-O-deethylase (EROD) were of special interest to this study as these biochemical tools have been widely used for the determination of exposure to pollutants. In this study, the freshwater oligochaete Limnodrilus profundicola was tested for its potential as a bioindicator of freshwater pollution. For this purpose, the ChE and EROD activities of L. profundicola and the level of polycyclic aromatic hydrocarbons (PAH) of water samples collected from different sites along the Curuksu stream on the Menderes River (the ancient Meander) running through south-western Turkey were studied. First, these activities were characterized using, as model substrates, acetylthiocholine (ATC), propionylthiocholine (PTC), and butyrylthiocholine (BTC). Then, the in vivo effects of insecticides and pollutants on these activities were investigated. L. profundicola were exposed to various doses of methyl-parathion, methomyl, and deltamethrin. Although significant inhibition of ChE was detected with each of the insecticides, the highest level of inhibition was observed with methyl-parathion. In addition to the inhibition of ChE, the activity of EROD was induced by exposure to oil-contaminated sediments. Thus, although L. profundicola has a reputation for being very resistant to pollution (although it is not insensitive to it), we demonstrated that it may potentially be used as a bioindicator species for contaminant exposure when ChE and EROD are used as biomarkers.

EROD and metallothionein in Limnodrilus profundicola (Oligochaeta: Tubifi cidae) as an indicator of pollution exposure in the Curuksu stream of Menderes river, Denizli–Turkey

In this study, pollution in Curuksu Stream of Menderes River has been followed by measuring the chemical and biological parameters on five predetermined stations for about 20 mon. Our previous studies have shown that Limnodrilus profundicola, Eristalis sp. and Chironomus thummi taxa are valuable bioindicators for the Curuksu stream and Limnodrilus profundicola Metallo-Thionein (MT) and EthoxyResorufi n-O-deEthylase (EROD) levels are valuable and useful biomarkers for biomonitoring heavy metals and PAHs pollutions, respectively. Cu-, Cr-, Cd- and Pb-type pollution was detected in all sediment samples taken from all of the stations, including reference station. Pollution source of these heavy metals are considered to be industrial wastewater, atmosphere and soil. Similarly, PAHs level was found to be considerably higher for Curuksu and Guzelkoy stations than other stations. These heavy metal- and PAHs-pollution were also confirmed with elevated MT and EROD levels measured with Limnodrilus profundicola sampl...

Polycyclic Aromatic Hydrocarbons in Water from the Menderes River, Turkey

This study was undertaken to determine the possibility of potential impact of PAHs on the aquatic biota. First, we had developed a new method for measuring 13 different priority pollutant PAHs in waste water samples. Then, eight different water samples collected from different sites along the Menderes River were analysed by this method involving SPE extraction and reverse-phase HPLC. The method presented here is suitable for rapid and accurate determination of PAH in surface waters and the PAH recoveries are practically quantitative. The levels of PAH in the analyzed samples range from 1.8μg/L to 24.9μg/L and industrialized areas were found to be highly polluted.

Results of the struggle at ancient Ephesus: natural processes 1, human intervention 0

Abstract Coastal areas have been prime locations for habitation and commerce. Early authors such as Pausanias (second century CE), and Strabo (64 or 63 BCE–24 CE) noted the impacts of shoreline changes. Geomorphological and subsurface geological data, combined with archaeological excavation and ancient texts, indicate a long interplay between natural processes of estuarine infilling by sediments from the Küçük Menderes River (ancient Cayster River) and multiple attempts of human intervention to preserve the harbours of Ephesus. Strabo noted that harbour engineering efforts there, such as the construction of a mole to prevent siltation, instead created a sediment trap that made things worse. The pre-Holocene river valley was inundated by Holocene sea-level rise that formed the ancient Gulf of Ephesus. Extensive palaeogeographical studies, based on sediment coring, geomorphology, archaeology and history, have provided details of the problems the inhabitants faced in keeping vital harbours in operation. Dating and analysis of sedimentary deposits has allowed the description of shifting river courses, floodplain changes, human intervention, and anthropogenic deposits at Ephesus. During and following Classical times sediment deposition rapidly began to fill in the embayment, requiring the inhabitants to regularly shift the harbours westward. Ultimately, it was to no avail.

A Study on the Pollution and Water Quality Modeling of the River Buyuk Menderes, Turkey

AbstractThe aim of the study was to determine the effects of existing and planned facilities on the water quality, and to propose some measures for the protection and improvement of water quality in the basin. For this purpose, the water quality was monitored on the river itself during the last 2 years 2008–2009. After the evaluation of the data collected by using computerized methods, water quality map was prepared, and the MODQUAL mathematical model was applied to the basin to determine the probable effects of different scenarios on the water quality of the river. The simulated water quality variables were: NH3–N, NO3–N, NO2–N, BOD5, DO, o‐PO4, and COD. At the end of the study, it was determined that water quality of Büyük Menderes river and its effluent presents generally polluted water quality in terms of various observed parameter groups. Values obtained by modeling in irrigation season are presented comparatively with analytically measured values. Analytical and modeling results of six of those parameters – except NO3–N – presented regular consistency. In winter season, a general consistency was provided in modeling of all parameters. It was purposed that the waste water originated from domestic and industrial activities should be treated before discharging them to the water bodies, and amount of fertilizer and pesticides used in agriculture should be under strict control throughout the basin in order to protect the water quality and prevent pollution of the water resources.

An Approach to Support Learning from International Experience with Water Policy

International experiences with water policy and governance arrangements are shared through various international meetings and reports. The underlying assumption is that these experiences provide useful information to policy makers who are looking for ways to improve water resources management in their home country or region. However, little has been written about analytical support for these potentially interested policy makers. They have to reach informed decisions about whether or not to initiate a process of policy transfer, about which foreign experiences to consider and about what parts of those experiences to copy, adapt, or reject. Providing such analytical support is complicated by the involvement of multiple actors in water resources management, who do not necessarily agree on these decisions. This paper outlines an approach to offer analytical support to these multiple actors in the initial phase of a policy transfer process. The approach is applied to the case of the Buyuk Menderes river basin in Turkey, where local policy makers were engaged in a policy transfer process related to the EU Water Framework Directive. It is concluded that the outlined approach can be used to inform local policy makers, as it yielded new and valid information in the case. In the absence of overriding political concerns, such information would lead to different decisions in various phases of policy transfer, when compared to a process that lacks this analytical support.

Discussion of “Regional Flood Frequency Analysis Using L Moments for the Buyuk and Kucuk Menderes River Basins of Turkey” by B. Saf

Discussion of “Regional Flood Frequency Analysis Using L Moments for the Buyuk and Kucuk Menderes River Basins of Turkey” by B. Saf

Application of linear stochastic models for drought forecasting in the Büyük Menderes river basin, western Turkey

In the present study, a seasonal and non-seasonal prediction of the Standardized Precipitation Index (SPI) time series is addressed by means of linear stochastic models. The methodology presented here is to develop adequate linear stochastic models known as autoregressive integrated moving average (ARIMA) and multiplicative seasonal autoregressive integrated moving average (SARIMA) to predict drought in the Buyuk Menderes river basin using SPI as drought index. Temporal characteristics of droughts based on SPI as an indicator of drought severity indicate that the basin is affected by severe and more or less prolonged periods of drought from 1975 to 2006. Therefore, drought prediction plays an important role for water resources management. ARIMA modeling approach involves the following three steps: model identification, parameter estimation, diagnostic checking. In model identification step, considering the autocorrelation function (ACF) and partial autocorrelation function (PACF) results of the SPI series, different ARIMA models are identified. The model gives the minimum Akaike Information Criterion (AIC) and Schwarz Bayesian Criterion (SBC) is selected as the best fit model. Parameter estimation step indicates that the estimated model parameters are significantly different from zero. Diagnostic check step is applied to the residuals of the selected ARIMA models and the results indicated that the residuals are independent, normally distributed and homoscedastic. For the model validation purposes, the predicted results using the best ARIMA models are compared to the observed data. The predicted data show reasonably good agreement with the actual data. The ARIMA models developed to predict drought found to give acceptable results up to 2 months ahead. The stochastic models developed for the Buyuk Menderes river basin can be employed to predict droughts up to 2 months of lead time with reasonably accuracy.

Depositional properties and geochemistry of Holocene perched springline tufa deposits and associated spring waters: a case study from the Denizli Province, Western Turkey

Abstract The Güney waterfall area is a perched springline tufa site developed on the southeast slope of the Büyük Menderes River near Güney town, in the Denizli province, Western Turkey. The site is 12 km away from Güney and 72 km from the city centre of Denizli. The spring waters emerge from the boundary between Palaeozoic marble and micaschist and precipitated tufa deposits downslope at the altitudes ranging from 220 to 400 metres. The tufa deposits cover an area of about 20 hectares. Flat upper surfaces of the deposits are indicative of mature stage. The waters are of the Ca–HCO 3 type and supersaturated with respect to CaCO 3 . The stable isotope values of the spring waters are −49.94 for δ 2 H and −7.15 for δ 18 O. The δ 13 C and δ 18 O values of active and passive tufa samples are in the range from −9.13 to −6.0‰, and from −8.44 to −7.40‰, respectively. These isotopic values are typical for fresh water tufa. The passive tufas give the 14 C age in the range from 2000 to 5800 yr BP. According to the 14 C age data, passive tufas are not older than Holocene. The stable isotope composition is similar south European examples.

Effects of climate change on water resources of the Büyük Menderes river basin, western Turkey

Temperature and rainfall changes are both significant components of climate change. This study characterizes the effects of climate change on water resources in the Büyük Menderes river basin in western Turkey, based on hydrology, temperature, and rainfall data from the past 45 years (1963-2007). When analyzed with the Mann-Whitney test, the temperature and precipitation time series exhibited obvious step changes with a 5% level of significance. Both the parametric t-test and nonparametric Mann-Kendall statistical test results showed an increasing trend of the temperature. Over the past 45 years, the temperature increased just about 1 °C. The long-term trend of annual precipitation demonstrated a decreasing trend; however, it was not found to be statistically significant. The spatial distribution of the precipitation pattern showed that the precipitation amount had an increasing trend in the 1970s, especially in the Aydın region, with a value of 5.8%. The precipitation amount started to decrease in the 1980s, especially in the Afyon and Uşak regions, with a value of -6.8%. Serious water scarcity began to appear in the 1990s, especially in the Aydın region, with a value of -14.4%. The streamflow of the Çine and Akçay rivers showed a decreasing trend, especially during the period of 1985-1998. The decreasing trend of the streamflow in the tributaries had a strong correlation with changes in temperature and precipitation. An increasing trend in temperature and decreasing trends in precipitation and streamflow in the Büyük Menderes river basin may be interpreted as climate change.

Assessment of the effects of discordant sites on regional flood frequency analysis

Flood observations in hydrological data sets contain frequently outliers, and this causes problems for water resource researchers and planners if not addressed correctly. This study analyses how outliers affect the identification of regional probability distributions using L-moment methods. The main objective of the study is to assess the effect(s) of discordancy detection measures on regional flood probability types and the accuracy of the estimates based on the regional analysis. The classical and robust discordancy measures for discordant site identification are used to determine regional probability distributions in order to identify the effects of discordant sites on the regional probability distribution in a region of the Menderes River Basins in Turkey. The other objective is to show whether a probability model type and flood estimation based on the model is reliable if discordancy sites in the region are not detected. In the study, the homogeneity of the basin was tested using the L-moments based on the heterogeneity for two discordancy measures, assessed by carrying out 500 simulations using the four parameter Kappa distribution. Based on these tests, two sub-regions are defined, the Upper-Menderes and Lower-Menderes sub-regions, that have different numbers of sites for both discordancy measures. According to the L-moments goodness of statistic criteria, the generalized extreme value distribution was determined as the best-fit distribution for the Upper-Menderes and Lower-Menderes sub-regions based on the classical discordancy measure. The generalized extreme value distribution was also found to be the best-fit distribution for the Upper-Menderes sub-region for the robust discordancy measure, while the Pearson Type 3 distribution was the best for the Lower-Menderes sub-region based on the robust measure. To appraise the results for the sub-regions, the relative root mean square error and relative bias were employed. The results show that the homogeneous region determined from the robust discordancy measure is more accurate than the region identified using the classical robust measure. This means that the classical robust detection measure of flood frequency analysis needs to be improved.

A hybrid neural network and ARIMA model for water quality time series prediction

Accurate predictions of time series data have motivated the researchers to develop innovative models for water resources management. Time series data often contain both linear and nonlinear patterns. Therefore, neither ARIMA nor neural networks can be adequate in modeling and predicting time series data. The ARIMA model cannot deal with nonlinear relationships while the neural network model alone is not able to handle both linear and nonlinear patterns equally well. In the present study, a hybrid ARIMA and neural network model is proposed that is capable of exploiting the strengths of traditional time series approaches and artificial neural networks. The proposed approach consists of an ARIMA methodology and feed-forward, backpropagation network structure with an optimized conjugated training algorithm. The hybrid approach for time series prediction is tested using 108-month observations of water quality data, including water temperature, boron and dissolved oxygen, during 1996–2004 at Büyük Menderes river, Turkey. Specifically, the results from the hybrid model provide a robust modeling framework capable of capturing the nonlinear nature of the complex time series and thus producing more accurate predictions. The correlation coefficients between the hybrid model predicted values and observed data for boron, dissolved oxygen and water temperature are 0.902, 0.893, and 0.909, respectively, which are satisfactory in common model applications. Predicted water quality data from the hybrid model are compared with those from the ARIMA methodology and neural network architecture using the accuracy measures. Owing to its ability in recognizing time series patterns and nonlinear characteristics, the hybrid model provides much better accuracy over the ARIMA and neural network models for water quality predictions.

Stochastic approaches for time series forecasting of boron: a case study of Western Turkey

In the present study, a seasonal and non-seasonal prediction of boron concentrations time series data for the period of 1996-2004 from Büyük Menderes river in western Turkey are addressed by means of linear stochastic models. The methodology presented here is to develop adequate linear stochastic models known as autoregressive integrated moving average (ARIMA) and multiplicative seasonal autoregressive integrated moving average (SARIMA) to predict boron content in the Büyük Menderes catchment. Initially, the Box-Whisker plots and Kendall's tau test are used to identify the trends during the study period. The measurements locations do not show significant overall trend in boron concentrations, though marginal increasing and decreasing trends are observed for certain periods at some locations. ARIMA modeling approach involves the following three steps: model identification, parameter estimation, and diagnostic checking. In the model identification step, considering the autocorrelation function (ACF) and partial autocorrelation function (PACF) results of boron data series, different ARIMA models are identified. The model gives the minimum Akaike information criterion (AIC) is selected as the best-fit model. The parameter estimation step indicates that the estimated model parameters are significantly different from zero. The diagnostic check step is applied to the residuals of the selected ARIMA models and the results indicate that the residuals are independent, normally distributed, and homoscadastic. For the model validation purposes, the predicted results using the best ARIMA models are compared to the observed data. The predicted data show reasonably good agreement with the actual data. The comparison of the mean and variance of 3-year (2002-2004) observed data vs predicted data from the selected best models show that the boron model from ARIMA modeling approaches could be used in a safe manner since the predicted values from these models preserve the basic statistics of observed data in terms of mean. The ARIMA modeling approach is recommended for predicting boron concentration series of a river.