İstanbul metropoliten alanından boşalan drenaj suları atık yüklerinin model kullanarak hesabı

Abstract

Son 20 - 25 senedir Dünya'da gelişmiş ülkelerin pek çoğu alıcı ortam olarak kullanılan yüzeysel su kaynaklarının kirliliğinin önlenmesi için büyük çaba sarf etmektedirler. Bu çabaların çoğu noktasal kaynaklardan ileri gelen kirlenmenin önlenmesine veya etkisinin azaltılmasına yönelik olmaktadır. Ancak özellikle son on yıldır yoğunlaşan araştırmalar, yayılı kaynaklardan ileri gelen kirlenmelerin kontrolünde herhangi bir iyileşme olmaksızın, sadece noktasal kaynakların kontrolüyle alıcı ortam kalitesinde ancak sınırlı iyileşme sağlanabildiğini göstermiştir. Bu durum özellikle yağışların akışa geçerek büyük miktarlarda drenaj suları debi ve yüklerinin oluştuğu kentlerde son derece önemlidir ve bu nedenle dünyanın pek çok kentinde drenaj suları kontrolü için önemli yatırımlar yapılmaktadır. İstanbul Mertopolitan alanında atık suların toplanması ve uzaklaştırılması için gerçekleştirilecek projelerin yaklaşık 4 milyar $ mertebesinde olacağı (IMC, 1995) tahmin edilmektedir. Buna göre, bu yatırımların gerekçesini oluşturan Marmara Denizi'ni koruma hedefinin yalnızca noktasal kaynakların kontrolü ile sağlanıp sağlanamayacağının bilimsel olarak cevabının verilmesi ve doğrulanması büyük önem taşımaktadır. Ancak yapılan çalışmaların bu cevabı vermekten çok uzak olduğu saptanmıştır. Bu çalışmanın kapsamını; İstanbul Metropolitan alanına düşen yağışlardan kaynaklanan drenaj suları debi ve atık yüklerinin bu suları toplayan ve taşıyan derelerin drenaj havzaları bazında hesabı için bir modelin geliştirilmesi ve geliştirilen model için bir bilgisayar programının hazırlanması; modelin gerektirdiği meteorolojik, hidrolojik ve arazi kullanımlarına ait bilgi ve verilerin elde edilmesi ve bunların analizi, son olarak modelle hesap edilen yüklerin drenaj havzaları bazında noktasal kaynak yükleriyle karşılaştırılması ve değerlendirilmesi oluşturmaktadır. Bu değerlendirmeler, Marmara Denizi'nde beklenen kalitenin sağlanması için, drenaj suları kontrolünün gerekliliğini ortaya çıkaracaktır. Çalışmada geliştirilen modelin yurdumuzun diğer kentleri içinde uygulanmasını temin etmek üzere, tezin ilgili bölümlerinde modelin kullanımı ve verilere analiz yöntemleri hakkında gerekli bilgiler verilmiştir.

The pollutant characteristics of drainage water in urban areas are defined by activities of the urban population. The main pollution factors are traffic, solid wastes, atmospheric loads, industrial wastes, lawn and garden chemicals and chemicals released when ice melts. The importance of runoff is emphasized by the increase in urbanisation, changes in the life styles of people and increasing requirement for better stormwater systems There are two main approaches used for calculating runoffs, namely the Rational Method approach and the Hydrograph methods. The first bases runoff calculations on the frequency factor, while the second consists in calculating the flow which remains after all losses. The studies carried out in foreign countries to determine the pollution loads caused by runoff reveal that land use patterns considerably affect the pollution concentrations in runoff. Metals, organic materials, pathogens and suspended solids have been found to be the most significant pollutants. The major mechanisms which affect the quality of runoff are build-up, wash- off, erosion, catchment area characteristics and the rainfall itself. While conceptualisation of the quality processes is not very difficult, ensuring the reliability of the simulation of quality parameters is quite difficult. Studies carried out in Istanbul to determine runoff and sewage loads include either the existing conditions or introduce measures to control loads. In the ScandiaConsult Report, a Rational Method form was developed for measuring the stormwater drainage system because of the specific topographical structure of Istanbul. According to this report, the receiving water which was most affected by polluting materials in the stormwater runoff was the Golden Horn. Changing the Istanbul sewerage network, which was constructed as a combined system, to a separate system was investigated in the Damoc and Camp Tekser studies, and the pollution impacts of the stormwater overflows caused by the combined system were explained. It was concludedsd that loading into the Golden Horn and the Marmara Sea would lead to a more severe impact on the Golden Horn, while impacts in the Marmara Sea would be less significant due to dilution and transfer. xviiiIn the Istanbul Master Plan Report prepared by IMC, the conceptual analysis of the combined sewer overflows was performed based on the saturated condition of the year 2032. Based on values of 100 and 200 kg/ha/year for the pollution loads conveyed by runoffs such as BOD5 and SS, average concentrations were found to be about 28 and 56 mg/l; the BOD5 and SS concentrations found in dry weather sewage were 200 and 233 mg/l, and the amount of loading per unit catchment area was 8.76 and 10.22 tons/ha/year, respectively. The models used in calculating the waste loads from non-point sources and the model properties were assessed. Structures of the ILLUDAS, MOUSE, STORM, SWMM and other models which are most commonly used, were examined. The two properties which were assessed were the runoff amount and the quality components. The runoff amount model simulates the runoff characteristics of a drainage area for a given rain model. With the help of sub-programs, it calculates the hydrographs and the depth and flow of the running water. By performing an interpolation between the storm hietograph values, it provides the rainfall intensity for the calculation period, and also calculates infiltration and surface buildup. Numbers and selection of the SWMM Quality components are defined in accordance with the needs of the user. Land use data, buildup formulation, washoff formulation, street cleaning, modelling approach of the gulley buckets and the mathematical relations to determine quality components are provided with options. The tables for the results of the international studies indicate the limits within which the quality components are realized. It is known that the urban erosion is often one of the major problems related to urban runoff and contributes to both negative water quality of the receiving water and to settlement in sewers. Erosion impact is taken into consideration with the Universal Soil Loss Equation (USLE). Land use, channel length, gulley buckets and the component loads are defined in developing the sub-catchment area quality data. The data analysis for calculating the runoff with the model was performed on an overall basis for the DRY Model using the Rational Method and the SWMM Method, and these data were evaluated on the Istanbul Metropolitan Area. Meteorological data was based on DMI records and time-intensity- frequency analysis were formed. The land use data for the saturated situation of the year 2032 and the associated runoff coefficients were determined. XIXThe program access data were prepared for both methods. Pollution loads of sewage (point source) and stormwater runoff (non-point source) from the Istanbul Metropolitan Area were calculated by both models mentioned above. An analysis on the differences between the two methods was based on access data. Comparisons of pollution loads of Wastewater, prepared by IMC (1995), and stormwater quantity and quality results, calculated in this study, were carried out for each creek drainage area, which were themselves grouped by several different representative catchment characteristics (Table 1). Grouping decreases the amount of effort required in the modelling of all the creeks in the entire Metropolitan Area of Istanbul As opposed to an individual approach for each creek, this method extrapolates the total quantity and quality of water represented by several selected creeks that have been modeled beforehand (Table 2). Relative comparisons of the calculated amounts for the saturated situation of year 2032 were made for each creek drainage area. Table 1 SWMM Simulation Groups Representing the Creeks and Their Basins Since the regional and local receiving water characteristics of the Marmara Sea vary, it is believed that the degree of contribution and impacts of the discharge conditions on catchment areas can estimated. Thus, determining the waste loads per unit area is a key element to supplying the preliminary estimation on non-point source loads for any specifed sub-basin upstream to a treatment and/or discharge infrastructure within the Istanbul Metropolitan Area. These unit loads for the Istanbul Metropolitan Area, and the simulated creeks, are represented inTable 3. xxTable 2 Total Runoff Quality Characteristics According to SWMM Computation Results Based on the Selected Representative Creeks Table 3 Total Runoff Unit Loads According to SWMM Computation Results Based on the Selected Representative Creeks Both literature and calculated values for the toxic metal loads, which are in both sewage and in stormwater runoff, are provided in this study. XXIAs a result of all these assessments, a summary comparison of the sewage and stormwater pollution loads from the Istanbul Metropolitan area has been submitted. Comparison of the sewage loading impacts were carried out by both models for situations without treatment and with 85% treatment (Tables 4 and 5). Table 4 Comparison of Domestic Wastewater Loads Estimated For the Year 2032, and Runoff Loads Computed By DRY Model, Based on the Selected Representative Creeks Table 5 Comparison of Domestic Wastewater Loads Estimated For the Year 2032, and Runoff Loads Computed By SWMM, Based on the Selected Representative Creeks With regards to a scenario which assumes an 85% treated sewage disposal into the Marmara Sea, SWMM results for the ratio of runoff pollution loading to treated water for Total Suspended Solids, Biological Oxygen Demand, Nitrogen and Phosphorus loads would be; 118%, 20%, 42%, and 42%, respectively. When the same analysis is implemented by the DRY Model, results for Total Suspended Solids, Biological Oxygen Demand, Nitrogen and Phosphorus loads are as follows: 104%, 7%, 38% and 19%.