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

Year 2016, Volume: 21 Issue: 2, 365 - 376, 16.12.2016

Ali Danandeh Mehr , Mehmet Cüneyd Demirel

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

Cited By: 6

Abstract

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.

Keywords

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

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

Abstract

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.

Keywords

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

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