Data-Driven Modeling of Flows of Antalya Basin and Reconstruction of Missing Data
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RESEARCH PAPER
Data‑Driven Modeling of Flows of Antalya Basin and Reconstruction of Missing Data Fatih Dikbas1 · Mutlu Yasar1 Received: 9 May 2018 / Accepted: 20 December 2019 © Shiraz University 2020
Abstract The length and completeness of any hydrologic observation series increase the reliability of the results obtained by methods using the series. But the observed series generally contain gaps caused by many factors. Therefore, the imputation of missing data with appropriate methods is an important step in hydrologic analysis. This paper presents the implementation of the frequency-based imputation method in the estimation of 385 missing and 5543 observed total flow values of 23 stations in Antalya basin, Turkey. The data-driven method calculates the estimations for missing values based on the temporal and quantitative associations in existing observations by considering the frequencies of the observed value ranges. The observations of the stations in the basin show significant variations in climatic behavior. The correlations between the estimations of the frequency-based imputation method and the observations for each station vary between 0.62 and 0.98, while 87% of the correlations are higher than 0.80 and 65% of them are higher than 0.9. The obtained high correlations show that the frequency-based imputation method can be used reliably in estimating streamflow in Southern Turkey within the Mediterranean climate zone. Other statistical measures (Nash–Sutcliffe efficiency coefficient, normalized root-mean-square error and mean absolute scaled error) and the comparison with the kriging method also validate the success or the obtained results. Keywords Antalya basin · Data-driven modeling · Frequency-based imputation · Missing data · River flow
1 Introduction Determination of the spatial, temporal and quantitative variations of river flows in a basin plays an important role in hydrologic analysis, agricultural applications and design and operation of water resources systems. Long-term and complete flow observation data sets contribute considerably to the reliable determination of water budgets to satisfy the water supply demands in the basins. The river flow observations generally do not cover long periods, and the existing data series might have gaps due to various reasons. These deficiencies have negative influences on the scientific and administrative works in the areas of agriculture, hydrology and water resources. Therefore, the missing observations should be estimated by using appropriate methods and the * Fatih Dikbas [email protected] Mutlu Yasar [email protected] 1
Civil Engineering Department, Pamukkale University, Denizli, Turkey
observation series with short duration should be extended by using the observed values of the neighboring stations. The consecutive observations in a hydrologic data set are usually associated with each other, and they are generally not independent from the existing observations. The conventional hydraulic and hydrologic models are supported or being replaced
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