30 Mayıs 2025 Konferans bildirisi Açık Erişim

Taşkolu, İlteriş; Acar, Reşat; Çırağ, Burak

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        "name": "Ta\u015fkolu, \u0130lteri\u015f", 
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        "name": "Acar, Re\u015fat", 
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    "description": "<p>Kurakl\u0131k, yava\u015f geli\u015fen ancak etkileri uzun y\u0131llar boyunca hissedilebilen, geni\u015f co\u011frafyalar\u0131 etkisi alt\u0131na alan ve su kaynaklar\u0131, tar\u0131msal &uuml;retim ile ekosistemler &uuml;zerinde ciddi tehditler olu\u015fturan do\u011fal afetlerin ba\u015f\u0131nda gelmektedir. \u0130klim de\u011fi\u015fikli\u011fi, artan su talebi, n&uuml;fus yo\u011funlu\u011fundaki s&uuml;rekli art\u0131\u015f ve d&uuml;zensiz su y&ouml;netimi gibi &ccedil;e\u015fitli antropojenik ve &ccedil;evresel etkenler, kurakl\u0131k olaylar\u0131n\u0131n hem s\u0131kl\u0131\u011f\u0131n\u0131 hem de \u015fiddetini giderek art\u0131rmaktad\u0131r. T&uuml;rkiye de bu riskten muaf olmayan &uuml;lkeler aras\u0131nda yer almakta olup, &ouml;zellikle su kaynaklar\u0131n\u0131n yo\u011fun \u015fekilde kullan\u0131ld\u0131\u011f\u0131 Marmara Havzas\u0131 gibi b&ouml;lgelerde kurakl\u0131k tehdidi &ccedil;ok daha belirgin ve hissedilir d&uuml;zeydedir. Bu ba\u011flamda, &ccedil;al\u0131\u015fma kapsam\u0131nda Marmara Havzas\u0131 s\u0131n\u0131rlar\u0131 i&ccedil;erisinde yer alan G&ouml;&ccedil;beyli, Cihandiye, S&ouml;l&ouml;z ve &Ccedil;elikg&ouml;r&uuml; ak\u0131m g&ouml;zlem istasyonlar\u0131na ait uzun y\u0131llara dayanan ayl\u0131k ak\u0131m verileri kullan\u0131larak hidrolojik kurakl\u0131k analizi ger&ccedil;ekle\u015ftirilmi\u015ftir. Analizlerde, kurakl\u0131k seviyelerinin belirlenmesinde yayg\u0131n olarak kullan\u0131lan Standartla\u015ft\u0131r\u0131lm\u0131\u015f Ak\u0131m \u0130ndeksi (Streamflow Drought Index &ndash; SDI) y&ouml;ntemi tercih edilmi\u015ftir. Elde edilen SDI verileri, gelecekteki kurakl\u0131k e\u011filimlerini tahmin etmek amac\u0131yla makine &ouml;\u011frenmesi tabanl\u0131 XGBoost algoritmas\u0131 ve zaman serisi analizlerinde yayg\u0131n \u015fekilde kullan\u0131lan Prophet modeliyle de\u011ferlendirilmi\u015ftir. Yap\u0131lan kar\u015f\u0131la\u015ft\u0131rmal\u0131 model analizleri sonucunda, yaln\u0131zca G&ouml;&ccedil;beyli istasyonunda hafif d&uuml;zeyde hidrolojik kurakl\u0131k g&ouml;zlenmi\u015f, di\u011fer &uuml;&ccedil; istasyonda belirgin bir kurakl\u0131k sinyali tespit edilmemi\u015ftir. Model performanslar\u0131 kar\u015f\u0131la\u015ft\u0131r\u0131ld\u0131\u011f\u0131nda ise, XGBoost algoritmas\u0131n\u0131n RMSE, MAE ve MAPE gibi hata &ouml;l&ccedil;&uuml;tlerinde Prophet&rsquo;e k\u0131yasla daha d&uuml;\u015f&uuml;k de\u011ferlere sahip oldu\u011fu g&ouml;r&uuml;lm&uuml;\u015ft&uuml;r. Bu sonu&ccedil;lar, XGBoost&rsquo;un hidrolojik kurakl\u0131k tahmini konusunda y&uuml;ksek do\u011frulukta ve g&uuml;venilir &ouml;ng&ouml;r&uuml;ler sunabilen etkili bir y&ouml;ntem oldu\u011funu ortaya koymaktad\u0131r.</p>", 
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      "place": "Bursa/T\u00fcrkiye", 
      "session": "1", 
      "session_part": "5", 
      "title": "INTERNATIONAL YILDIRIM BAYEZID SCIENTIFIC RESEARCH AND INNOVATION SYMPOSIUM-I", 
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    "title": "Ak\u0131m Verilerine Dayal\u0131 Kurakl\u0131k Tahmini: Marmara Havzas\u0131'nda SDI ve Yapay Zeka Uygulamalar\u0131"
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