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Estimation of Flow Duration Curve for Ungauged Catchments using Adaptive Neuro Fuzzy Inference System and Map Correlation Method A Case Study from Turkey
Date
2015-12-13
Author
Doğulu, Nilay
Kentel Erdoğan, Elçin
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In Turkey the experience and data required for a hydrological model setup is limited and very often not available. Moreover there are many ungauged catchments where there are also many planned projects aimed at utilization of water resources including development of existing hydropower potential. This situation makes runoff prediction at locations with lack of data and ungauged locations where small hydropower plants, reservoirs, etc. are planned an increasingly significant challenge and concern in the country. Flow duration curves have many practical applications in hydrology and integrated water resources management. Estimation of flood duration curve (FDC) at ungauged locations is essential, particularly for hydropower feasibility studies and selection of the installed capacities. In this study, we test and compare the performances of two methods for estimating FDCs in the Western Black Sea catchment, Turkey: (i) FDC based on Map Correlation Method (MCM) flow estimates. MCM is a recently proposed method (Archfield and Vogel, 2010) which uses geospatial information to estimate flow. Flow measurements of stream gauging stations nearby the ungauged location are the only data requirement for this method. This fact makes MCM very attractive for flow estimation in Turkey, (ii) Adaptive Neuro-Fuzzy Inference System (ANFIS) is a data-driven method which is used to relate FDC to a number of variables representing catchment and climate characteristics. However, it`s ease of implementation makes it very useful for practical purposes. Both methods use easily collectable data and are computationally efficient. Comparison of the results is realized based on two different measures: the root mean squared error (RMSE) and the Nash-Sutcliffe Efficiency (NSE) value. Ref: Archfield, S. A., and R. M. Vogel (2010), Map correlation method: Selection of a reference streamgage to estimate daily streamflow at ungaged catchments, Water Resour. Res., 46, W10513, doi:10.1029/2009WR008481.
Subject Keywords
1914 Data mining
,
Informatics
,
1918 Decision analysis
,
1942 Machine learning
URI
https://hdl.handle.net/11511/81450
https://ui.adsabs.harvard.edu/abs/2015AGUFM.H33A1559K/abstract
Conference Name
Estimation of Flow Duration Curve for Ungauged Catchments using Adaptive Neuro Fuzzy Inference System and Map Correlation Method A Case Study from Turkey", 2015 AGU Fall Meeting, San Francisco, California, USA. 14-18 December
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Department of Civil Engineering, Conference / Seminar
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N. Doğulu and E. Kentel Erdoğan, “Estimation of Flow Duration Curve for Ungauged Catchments using Adaptive Neuro Fuzzy Inference System and Map Correlation Method A Case Study from Turkey,” presented at the Estimation of Flow Duration Curve for Ungauged Catchments using Adaptive Neuro Fuzzy Inference System and Map Correlation Method A Case Study from Turkey”, 2015 AGU Fall Meeting, San Francisco, California, USA. 14-18 December, California, USA, 2015, Accessed: 00, 2021. [Online]. Available: https://hdl.handle.net/11511/81450.
