PROBABILISTIC RUNOFF MODELING APPROACH IN MOUNTAINOUS BASINS BASED ON SATELLITE SNOW DATA AND WAVELET NEURAL NETWORK

Year 2020, Volume: 25 Issue: 3, 1139 - 1154, 31.12.2020

Gökçen Uysal Aynur Sensoy

https://doi.org/10.17482/uumfd.787147

Abstract

Streamflow prediction is often a challenging issue for snow dominated basins where proper in-situ snow data might be limited and the snow physics is highly complex. The main aim of this study is to propose an alternative modeling solution by considering both accessibility of the inputs and simplicity of the model structure. We propose Wavelet Neural Network (WNN) model approach which takes probabilistic snow cover area in order to produce probabilistic streamflow in the mountainous basins. For the sake of the accessibility of the input data, snow probability maps are produced from cloud-free images of MODIS. The WNN model is trained and tested with observed hydro-meteorological data. Also, MultiLayer Perceptron Model (MLP) is used as a benchmark model. The approach is tested in a snow-dominated headwater (in altitude from 1559 to 3508 m) of Murat River which has a great importance as being one of the main tributaries of Euphrates River. According to the results, the approach is capable of detecting snow distribution in the area of interest and WNN is promising to generate probabilistic streamflow predictions. 

Keywords

Snowmelt modeling, Wavelet Neural Network, Euphrates River Basin, Streamflow forecasting, Satellite snow data

Supporting Institution

TÜBİTAK

Project Number

113Y075

Thanks

This study was partly funded by TÜBİTAK (The Scientific and Technical Research Council of Turkey) (Project No: 113Y075). The authors wish to thank General Directorate of Meteorology (MGM) and State Hydraulic Works (DSI) for data contribution.

Dağlık Havzalarda Uydu Kar Verisi ve Dalgacık Sinir Ağı Tabanlı Olasılıklı Akım Modelleme Yaklaşımı

Abstract

Kar baskın havzalardaki akarsu akım tahminleri, uygun arazi kar verilerinin sınırlı oluşu ve kar fiziğinin oldukça karmaşık olması nedeniyle genellikle zorlayıcı bir konudur. Bu çalışmanın temel amacı hem girdilerin erişilebilirliğini hem de model yapısının basitliğini göz önünde bulundurarak alternatif bir modelleme çözümü önermektir. Önerilen Dalgacık Sinir Ağı (DSA) modeli yaklaşımı, nehir akımları üretmek için olasılıklı karla kaplı alanları girdi alarak dağlık havzalarda olasılıklı akım tahminleri üretebilmektedir. Girdi verilerinin erişilebilirliği adına, MODIS'in bulutsuz görüntülerinden kar olasılığı haritaları üretilmektedir. DSA modeli, gözlenmiş hidro-meteorolojik verilerle eğitilmiş ve test edilmiştir. Ayrıca, Çok-Katmanlı Perseptron Modeli (ÇKPM) de kıyaslama modeli olarak kullanılmıştır. Yaklaşım, Fırat Nehri'nin ana kolu olarak büyük önem taşıyan Murat Nehri'nin kar baskın üst havzasında (1559 ila 3508 m yükseklikte) test edilmiştir. Sonuçlara göre, DSA yaklaşımı ilgi alanındaki kar dağılımını tespit ederek olasılıklı akım tahminleri üretme imkânı sağlamaktadır.

Keywords

Kar erimesi modelleme, Dalgacık Sinir Ağı, Fırat Nehri havzası, Akım tahmini, Uydu kar verisi

Project Number

113Y075

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