On the Calibration of Multigene Genetic Programming to Simulate Low Flows in the Moselle River

Yıl 2016, Cilt 21, Sayı 2, 365 - 376, 16.12.2016

Ali DANANDEH MEHR Mehmet Cüneyd DEMİREL

https://doi.org/10.17482/uumfd.278107

Cited By: 5

Öz

The aim of this paper is to calibrate a data-driven model to simulate Moselle River flows and compare the performance with three different hydrologic models from a previous study. For consistency a similar set up and error metric are used to evaluate the model results. Precipitation, potential evapotranspiration and streamflow from previous day have been used as inputs. Based on the calibration and validation results, the proposed multigene genetic programming model is the best performing model among four models. The timing and the magnitude of extreme low flow events could be captured even when we use root mean squared error as the objective function for model calibration. Although the model is developed and calibrated for Moselle River flows, the multigene genetic algorithm offers a great opportunity for hydrologic prediction and forecast problems in the river basins with scarce data issues.

Anahtar Kelimeler

Low flows, calibration, genetic programming, ANN, HBV and GR4J

MOSELLE NEHRİ’NDEKİ DÜŞÜK DEBİLERİN BENZETİMİ İÇİN ÇOKLU GENETİK PROGRAMLAMA MODELİNİN KALİBRE EDİLMESİ

Öz

Bu çalışmanın amacı Moselle nehrinin düşük debilerini çoklu genetik programlama modeli ile benzetmek ve ayarı yapılan modelin performansini daha önceki modellerle kiyaslamaktir. Tutarlılık için aynı performans kriterleri ve model girdi çıktı düzenekleri kullanılmıştır. Tek değişen, model yapısıdır. Yağiş, buharlaşma ve nehir debisi için dünkü değerler kullanilarak bugünku nehir debisi benzetilmeye çalışılmıştır. Sonuçlar önerilen genetik programlama modelinin dört model arasında en iyi sonuçlar verdiğini göstermektedir. Az görülen düşük akımların zamanlama ve seviyesi amaç fonksiyonu etkin değerler seçildiğinde dahi başariyla benzetilebilmektedir. Bu geliştirilen ve önerilen model yapısı her ne kadar Moselle nehri için olsa da çoklu genetik programlama algoritmasi genel olarak tüm nehir tahmin modelleri icin bir alternatif sunmaktadır.

Anahtar Kelimeler

Düşük debi, model ayarlanma, çoklu genetik programlama, ANN, HBV ve GR4J

Kaynakça

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