Akademik Veri Yönetim Sistemi
Tezin Türü: Yüksek Lisans
Tezin Yürütüldüğü Kurum: Orta Doğu Teknik Üniversitesi, Fen Edebiyat Fakültesi, Biyolojik Bilimler Bölümü, Türkiye
Tezin Onay Tarihi: 2004
Tezin Dili: İngilizce
Öğrenci: Mustafa Gökmen
Danışman: MERYEM BEKLİOĞLU
Özet:In this study, yearly and seasonally nitrogen retention dynamics of reed beds surrounding Lake Mogan were investigated by comparing surface aerial nitrogen load and in-lake concentrations. The analyses were performed separately for nitrate-N, ammonium-N and dissolved inorganic nitrogen (sum of nitrate-N and ammonium-N) to reveal differences between them in terms of retention dynamics. 1998, 1999 and 2002 were relatively high-load years in terms of DIN-input to reed beds surrounding Lake Mogan, compared with the DIN-loadings of 1997, 2000 and 2001. A significant difference was observed between NO3-N input and output for the relatively high-load years to Lake Mogan reed beds indicating significantly high NO3-N retention rates for that periods, while no significant difference was observed in the relatively low-load years. Also, a clear linear relationship (R2 = 0.975) was found between amount of NO3-N retention and amount of NO3-N input to the system. NH4-N input and output were not significantly different in none of the study years. Then, a dynamic أWetland Nitrogen Modelؤ was utilized to model dissolved inorganic nitrogen removal capacity of the reed beds surrounding Lake Mogan. The model was firstly calibrated and validated using data sets of different study years and then used for prediction under wet and dry year scenarios. The model predictions revealed that NO3-N retention efficiency was distinctively higher in wet rather than the dry year conditions since the reed beds might have limited denitrification capacity in dry years due to unavailability of enough NO3-N load. Finally, the land-use changes occurred in the closer catchment of Lake Mogan and the potential risk areas for non-point nitrogen input to Lake Mogan were determined using aerial photos of the region and Geographical Information Systems (GIS). It was observed that highest potential risk area for