Browsing by Author "Soyupak, S"

Now showing 1 - 9 of 9

Citation - WoS: 5
Citation - Scopus: 5
Assessment of Nitrogen Excess in an Agricultural Area Using a Nitrogen Balance Approach
(I W A Publishing, 2005) Muhammetoglu, H; Muhammetoglu, A; Soyupak, S
A pilot study has been initiated to develop an approach for quantification of nitrogen excesses from agricultural activities that involve greenhouse farming in Kumluca Plain, Turkey. Detailed calculations utilizing the nitrogen balance method (NBM) were carried out at nine different locations within the plain over a time period of one year. The major contributing factors and governing operative mechanisms taken into consideration were nitrogen application rates both as organic and chemical fertilizers, irrigation water to application practices, and nitrogen uptake by plants. The adopted approach yielded valuable information such as plant nitrogen uptake efficiencies, excess nitrogen, leaching rates and leachate nitrogen concentrations. Further, a site specific multiple linear regression model has been developed to estimate the ratio (N-leachate/N-groundwater) as a function of independent variables: farming age, excess nitrogen application and SEEPAGE Index Number. The negative sign of the model parameters implies that the ratio (N-leachate/N-groundwater) decreases as values of the independent variables increase. The adopted approach and the obtained results can beneficially be applied to similar sites to establish basic parameters of irrigation and fertilizer application operations.
Citation - WoS: 5
Citation - Scopus: 3
Evaluation of Efficiencies of Diffuse Allochthonous and Autochthonous Nutrient Input Control in Restoration of a Highly Eutrophic Lake
(I W A Publishing, 2002) Muhammetoglu, A; Muhammetoglu, H; Soyupak, S
Mogan Lake is an important recreational area for Metropolitan Ankara-Turkey. It is a shallow eutrophic lake with a dense growth of macrophytes. The main contributors of nutrients and other pollutants to the lake are the creeks carrying the runoff water from the watershed and upland farming land, in addition to the domestic and industrial wastewater discharges from a nearby town and industries. Hydrodynamic and water quality modeling techniques were used to determine the optimum management schemes for the lake restoration and diffuse pollution control. Management scenarios were devised and tested to control allochthonous and autochthonous nutrient inputs to the lake. Phosphorus and nitrogen load reductions were the main test elements for the control of allochthonous nutrient inputs. The scenario analysis revealed that reduction of phosphorus and nitrogen loads from diffused sources will have a marginal effect on controlling eutrophication if macrophyte growth is left uncontrolled. Scenarios employing macrophyte harvesting and sediment dredging have been evaluated for autochthonous nutrient input control. Sediment dredging alone has been shown to yield the most favorable conditions for water quality improvement in Mogan Lake. Further, control of diffuse pollution was an essential final step to achieve an acceptable long-term sustainable water quality improvement in the lake.
Citation - WoS: 14
Citation - Scopus: 14
Fuzzy Logic Model To Estimate Seasonal Pseudo Steady State Chlorophyll-A Concentrations in Reservoirs
(Springer, 2004) Soyupak, S; Chen, DG
A fuzzy logic model is developed to estimate pseudo steady state chlorophyll-a concentrations in a very large and deep dam reservoir, namely Keban Dam Reservoir, which is also highly spatial and temporal variable. The estimation power of the developed fuzzy logic model was tested by comparing its performance with that from the classical multiple regression model. The data include chlorophyll-a concentrations in Keban lake as a response variable, as well as several water quality variables such as PO4 phosphorus, NO3 nitrogen, alkalinity, suspended solids concentration, pH, water temperature, electrical conductivity, dissolved oxygen concentration and Secchi depth as independent environmental variables. Because of the complex nature of the studied water body, as well as non-significant functional relationships among the water quality variables to the chlorophyll-a concentration, an initial analysis is conducted to select the most important variables that can be used in estimating the chlorophyll-a concentrations within the studied water body. Following the outcomes from this initial analysis, the fuzzy logic model is developed to estimate the chlorophyll-a concentrations and the advantages of this new model is demonstrated in model fitting over the traditional multiple regression method.
Citation - WoS: 26
Citation - Scopus: 31
Impact Assessment of Different Management Scenarios on Water Quality of Porsuk River and Dam System - Turkey
(Springer, 2005) Muhammetoglu, A; Muhammetoglu, H; Oktas, S; Ozgokcen, L; Soyupak, S
Porsuk Dam Reservoir (PDR), which is located on Porsuk River, is the main drinking water resource of Eskisehir City-Turkey. Both the river and the reservoir are under the threat of several domestic and industrial point sources and land-based diffuse pollution. The river water quality is very poor with high concentrations of nitrogen and phosphorus compounds at the entrance to Porsuk Reservoir. The reservoir shows symptoms of a hypertrophic lake. The expected responses of the whole river and reservoir system under different pollution control scenarios were estimated to develop plausible water quality management strategies. The adopted scenarios assumed different levels of treatment for the major domestic point sources that include conventional treatment and tertiary treatment. The contemporary Turkish Allowable Discharge Limits (ADLs) and the best available technology choices were the investigated treatment options for the major industries. The expected improvements of water quality characteristics under the management scenario options have been estimated by means of mathematical models. The model choices were the QUAL2E for the river and BATHTUB for the reservoir. Recommendations for different levels of treatment were derived in order to improve the water quality both within the river and in the reservoir.
Citation - WoS: 3
Citation - Scopus: 3
Modeling Chlorine Decay in Drinking Water Distribution Network: Case Study of Antalya, Turkey
(Parlar Scientific Publications (p S P), 2005) Tiryakioglu, O; Muhammetoglu, A; Muhammetoglu, H; Soyupak, S
The well known hydraulic and water quality network simulation model, EPANET, is applied to the drinking water distribution network of Baris District in Antalya City, Turkey. Nine measurement and sampling stations were chosen to represent the study area. The water pressure at the pumping station was recorded during the field measurements while two different sets of water samples were analyzed in the field for chlorine residual at all the stations. Additional water samples were collected at some stations and analyzed for many physical, chemical and biological water quality parameters. Moreover, the bottle chlorine bulk decay coefficient was determined in the lab as 4.3434 day(-1). The two different field measurement sets are used to calibrate and verify the model. The calibration process resulted in a wall reaction coefficient equal to 0.025 m day(-1). In addition to predicting the chlorine residual levels along the network, the model also predicts many hydraulic characteristics such as pressure, velocity and flow rates in the network.
Citation - WoS: 44
Citation - Scopus: 49
A Neural Network-Based Approach for Calculating Dissolved Oxygen Profiles in Reservoirs
(Springer London Ltd, 2003) Soyupak, S; Karaer, F; Gürbüz, H; Kivrak, E; Sentürk, E; Yazici, A
A Neural Network (NN) modelling approach has been shown to be successful in calculating pseudo steady state time and space dependent Dissolved Oxygen (DO) concentrations in three separate reservoirs with different characteristics using limited number of input variables. The Levenberg-Marquardt algorithm was adopted during training. Pre-processing before training and post processing after simulation steps were the treatments applied to raw data and predictions respectively. Generalisation was improved and over-fitting problems were eliminated: Early stopping method was applied for improving generalisation. The correlation coefficients between neural network estimates and field measurements were as high as 0.98 for two of the reservoirs with experiments that involve double layer neural network structure with 30 neurons within each hidden layer. A simple one layer neural network structure with 11 neurons has yielded comparable and satisfactorily high correlation coefficients for complete data set, and training, validation and test sets of the third reservoir.
Citation - WoS: 22
Citation - Scopus: 21
Predicting dominant phytoplankton quantities in a reservoir by using neural networks
(Springer, 2003) Gurbuz, H; Kivrak, E; Soyupak, S; Yerli, SV
The Levenberg-Marquardt algorithm was used to train artificial neural networks to predict the abundance of Cyclotella ocellata Pant. and Cyclotella kutzingiana Thwaites using time, depth, temperature, pH, dissolved oxygen, and electrical conductivity as input parameters for the oligo-mesotrophic Kuzgun Dam Reservoir, Turkey. The data were collected in monthly intervals during two ice-free seasons: between April 2000-November 2000 and April 2001-November 2001. To reduce over-fitting of the neural network based models, we employed single hidden layer networks with early stopping of training. Correlation coefficients, of neural network predictions with measurements of abundance of Cyclotella ocellata Pant. and Cyclotella kutzingiana Thwaites were 0.88 and 0.86, respectively.
Citation - WoS: 4
Citation - Scopus: 6
Seasonal Changes in Phytoplankton Community Structure in a High Mountain Reservoir, Kuzgun Reservoir, Turkey
(Taylor & Francis inc, 2004) Gürbüz, H; Kivrak, E; Soyupak, S
Seasonal changes in phytoplankton community structure of Kuzgun reservoir, a high mountain reservoir, were studied during the ice-free period in 2000 and 2001. Bacillariophyta was the dominant group, followed by Chlorophyta and Dinophyta. The dominant species were Synedra delicatissima, Asterionella formosa, Fragilaria crotonensis, Cyclotella kidzingiana, Cyclotella ocellata, Oocystis borgei, Staurastrum longiradiatum, Ankistrodesmus falcatus, Ceratium hirundinella, and Peridinium cinctum. Maximum phytoplankton density was observed in late spring.
Citation - WoS: 12
Vulnerability of groundwater to pollution from agricultural diffuse sources: a case study
(I W A Publishing, 2002) Muhammetoglu, H; Muhammetoglu, A; Soyupak, S
Kumluca, near Antalya in Turkey, is an important plain with its intensive agricultural activities employing greenhouses. The chemical fertilizer application practices caused excessive increases of the nitrogen, phosphorus and salinity within groundwater. A study has been initiated to assess the present state of the groundwater pollution problem of Kumluca Plain. A total of nine measurement and sampling stations have been selected to represent different depths groundwater table, different types of agricultural activities and different soil types. The magnitudes of the parameters: temperature, salinity and conductivity, nitrate, nitrite, ammonia, orthophosphate and fecal coliform were determined for groundwater. Soil samples collected from the stations have been analyzed for several parameters such as texture, total salinity, total nitrogen, and total phosphorus. The measurement and analyses results of the groundwater showed wide spatial variations depending on factors such as the quality of irrigation water, depth groundwater, soil characteristics, type and age of agriculture and hydrology. Groundwater vulnerabilities to pollution have been analyzed using the SEEPAGE Model approach. Furthermore the soil, aquifer and groundwater characteristics, which will be utilized to establish "cause" and "effect" relationships in future, have been clarified.