Use of interactive multisensor snow and ice mapping system snow cover maps (IMS) and artificial neural networks for simu
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ORIGINAL PAPER
Use of interactive multisensor snow and ice mapping system snow cover maps (IMS) and artificial neural networks for simulating river discharges in Eastern Turkey Musa Ataṣ 1 & Ahmet Emre Tekeli 2,3 & Senayi Dönmez 3 & Hesham Fouli 2
Received: 24 December 2014 / Accepted: 10 September 2015 / Published online: 24 February 2016 # Saudi Society for Geosciences 2015
Abstract Basins located in Eastern Turkey are largely fed by snowmelt runoff during spring and early summer seasons. This study investigates the efficiency of artificial neural networks (ANNs) in snowmelt runoff generation. Although ANNs have been used for streamflow simulating/forecasting in the last two decades, using satellite-based snow-covered area (SCA) maps and meteorological observations as inputs to ANN provides a novel basis for estimating streamflow. The proposed methodology is implemented over Upper Euphrates River Basin in Eastern Turkey. SCA data was acquired from Interactive Multisensor Snow and Ice Mapping System (IMS) for an 8year period from February 2004 to September 2011. Meteorological observations including daily cumulative precipitation and daily average air temperatures were obtained from Turkish State Meteorological Services. The simulation results are promising with coefficient of correlation varying from 0.67 to 0.98 among proposed models. Past days discharge was found to substantially improve the forecast accuracy. The
* Ahmet Emre Tekeli [email protected] Musa Ataṣ [email protected] Senayi Dönmez [email protected] Hesham Fouli [email protected]
1
Computer Engineering Department, Siirt University, Siirt, Turkey
2
Civil Engineering Department, King Saud University, Riyadh, Kingdom of Saudi Arabia
3
Civil Engineering Department, Çankırı Karatekin University, Çankırı, Turkey
paper presents the expected basin discharge for 2011 water year based on meteorological observations and SCA input. Keywords Artificial neural network simulation . IMS snow cover maps . Snowmelt . Streamflow prediction . Upper Euphrates
Introduction Hydroelectric power production has recently gained more emphasis in Turkey and is expected to be the dominant power production sector as the planned hydroelectric dams will be completed. Snowmelt runoff is expected to be the major contributor to hydroelectric power production for snow precipitation-dominant basins. Forecasting water amounts accurately in these basins will improve joint and sustainable management of water resources, which is very important for many areas such as the following: dam operation, flood mitigation, drinking water supply, and drainage water handling (Salas 1993; Yadav et al. 2011) and which eventually will increase hydroelectric production efficiency. Such accurate forecasting can be achieved through suitable hydrological models. However, the main challenge in developing any hydrological model is the data availability, which is neither reliable nor continuous for many study regions. Especially in mountainous regions where snowmelt runoff is do
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