19 Ekim 2024 Konferans bildirisi Açık Erişim

Kaçar, Furkan Sencer; Ergün, Enes; Avcuoğlu, Muhammet Bahattin; Yılmaz, Selahattin Utku; Demirel, Mehmet Cüneyd

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        "affiliation": "T\u00fcrk-Alman \u00dcniversitesi, \u0130stanbul Teknik \u00dcniversitesi", 
        "name": "Ka\u00e7ar, Furkan Sencer", 
        "orcid": "0009-0000-1764-8207"
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        "affiliation": "\u0130stanbul Teknik \u00dcniversitesi", 
        "name": "Erg\u00fcn, Enes"
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        "affiliation": "Devlet Su \u0130\u015fleri Genel M\u00fcd\u00fcrl\u00fc\u011f\u00fc", 
        "name": "Avcuo\u011flu, Muhammet Bahattin", 
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        "name": "Y\u0131lmaz, Selahattin Utku", 
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        "name": "Demirel, Mehmet C\u00fcneyd", 
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    "description": "<p>Hidrolojik modeller, su kaynaklar\u0131n\u0131 fiziksel bir b&uuml;t&uuml;nl&uuml;k &ccedil;er&ccedil;evesinde say\u0131sal bir ortamda benzerinin olu\u015fturulmas\u0131d\u0131r. Hidrolojik modeller ta\u015fk\u0131n ve kurakl\u0131k tahmininde, iklim de\u011fi\u015fikli\u011finin se&ccedil;ilen havzaya etkilerinin tahmininde kullan\u0131lan &ouml;nemli ara&ccedil;lard\u0131r. Bu modeller yap\u0131sal a&ccedil;\u0131dan kara kutu modeller, toplu kavramsal modeller (gri kutu modelleri) ve fiziksel tabanl\u0131 yay\u0131l\u0131 modeller (beyaz kutu modelleri) olmak &uuml;zere &uuml;&ccedil; gruba ayr\u0131l\u0131r. Bu &ccedil;al\u0131\u015fman\u0131n amac\u0131 iki farkl\u0131 toplu (GR4J ve TUW model) ve bir yay\u0131l\u0131 (mHM) hidrolojik modeli karstik &Ccedil;ak\u0131tsuyu Havzas\u0131nda kurup debi performans\u0131n\u0131 k\u0131yaslamakt\u0131r. Bu ama&ccedil;la 2000-2020 y\u0131llar\u0131 aras\u0131nda g&uuml;nl&uuml;k veriler kullan\u0131larak modeller kurulmu\u015f ve model parametre kalibrasyonu yap\u0131lm\u0131\u015ft\u0131r. GR4J ve TUW modellerinin parametrelerinin kalibrasyonunda Diferansiyel Geli\u015fim Algoritmas\u0131 (DEoptim); mHM parametrelerinin kalibrasyonunda ise model koduna entegre halde bulunan Dynamically Dimensioned Search (DDS) algoritmas\u0131 kullan\u0131lm\u0131\u015ft\u0131r. Model parametrelerinin optimizasyonunda ama&ccedil; fonksiyonu olarak Nash-Sutcliffe Efficiency (NSE) metri\u011fi maksimize edilmi\u015f; model sonu&ccedil;lar\u0131 ayr\u0131ca Kling-Gupta Efficiency (KGE) ve R2&nbsp;ile de\u011ferlendirilmi\u015ftir. TUW model ve mHM 0.69 NSE ile gayet iyi sonu&ccedil;lar verirken; GR4J modelin g&uuml;nl&uuml;k verilere dayanarak hesaplanm\u0131\u015f 0.27 NSE ile performans\u0131n\u0131n yetersiz oldu\u011fu g&ouml;r&uuml;lm&uuml;\u015ft&uuml;r. Bunun sebebi olarak GR4J modelinde kar erimesi mod&uuml;l&uuml;n&uuml;n olmamas\u0131 ve 4 parametre ve 2 tank yap\u0131s\u0131n\u0131n havzan\u0131n heterojenli\u011fini temsil edemedi\u011fi d&uuml;\u015f&uuml;n&uuml;lmektedir. Sonraki &ccedil;al\u0131\u015fmalarda &Ccedil;ak\u0131tsuyuna ba\u011flanan kaynak debisi &ouml;l&ccedil;&uuml;mlerinin de (D18A056) kalibrasyona dahil edilmesi planlanmaktad\u0131r.</p>", 
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    "title": "Toplu ve Yay\u0131l\u0131 Hidrolojik Modellerin Karstik Havzada Kalibrasyon Performanslar\u0131n\u0131n Kar\u015f\u0131la\u015ft\u0131r\u0131lmas\u0131: \u00c7ak\u0131tsuyu Havzas\u0131 \u00d6rne\u011fi"
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