A Comparative Study of Statistical Methods for Daily Streamflow Estimation at Ungauged Basins in Turkey

Abstract

In this study, a comparative evaluation of the statistical methods for daily streamflow estimation at ungauged basins is presented. The single donor station drainage area ratio (DAR) method, the multiple-donor stations drainage area ratio (MDAR) method, the inverse similarity weighted (ISW) method, and its variations with three different power parameters (1, 2, and 3) are applied to the two main subbasins of the Euphrates Basin in Turkey to estimate daily streamflow data. Each station in each basin is considered in turn as the target station where there are no streamflow data. The donor stations are selected based on the physical similarities between the donor and target stations. Then, streamflow data from the most physically similar donor station(s) is transferred to the target station using the statistical methods. In addition, the effect of data preprocessing on the estimation performance of the statistical methods is investigated. The preprocessing discussed in this study is streamflow data smoothing using the two-sided moving average (MA). Three statistical methods using the smoothed data by the MA, named as DAR-MA, MDAR-MA, and ISW-MA, are proposed. The estimation performance of the statistical methods is compared by using daily streamflow data with preprocessing and without preprocessing. The Nash-Sutcliffe efficiency (NSE), the ratio of the root mean square error (RMSE) to the standard deviation of the observed data (RSR), the percent bias (PBIAS), and the coefficient of determination (R 2 ) are used to evaluate the performance of the statistical methods. The results show that MDAR and ISW give improved performances compared to DAR to estimate daily streamflow for 7 out of 8 target stations in the Middle Euphrates Basin and for 4 out of 7 target stations in the Upper Euphrates Basin. Higher NSE values for both MDAR and ISW are mostly obtained with the three most physically similar donor stations in the Middle Euphrates Basin and with the two most physically similar donor stations in the Upper Euphrates Basin. The best statistical method for each target station exhibits slightly greater NSE when the smoothed data by the MA is used for all target stations in the Middle Euphrates Basin and for 6 out of 7 target stations in the Upper Euphrates Basin.

Regionalization of hydrological modeling for predicting streamflow in ungauged catchments: A comprehensive review

“…Kanishka and Eldho (2017) used the Isomap nonlinear dimensionality reduction technique along with the nonlinear principal component analysis, principal component analysis, and k‐means cluster analysis to improve the efficiency of watershed classification. Apart from more comprehensive classification analysis, researches on physical similarity regionalization are not only aiming at regionalizing hydrological model parameters, but also more targets such as flow regimes (Solans & Mellado‐Diaz, 2015), observed streamflow (Agarwal et al, 2016; Choubin et al, 2019; Yilmaz & Onoz, 2020), and hydrological signatures (Chouaib, Alila, & Caldwell, 2019; Elesbon et al, 2015; Papageorgaki & Nalbantis, 2016; Westerberg et al, 2016).…”

Special Issue “Multiscale Impacts of Anthropogenic and Climate Changes on Tropical and Mediterranean Hydrology”

“…The topics studied cover a large panel of hydrological questions. Many of them deal with the study of time series variability, rainfall [16], discharges [19,20], sediment transport [11][12][13]21], recession coefficient [22,23], climate change impacts [17,24], or anthropogenic impacts [2,11,20,21]. Drought is also a topic of notable interest in Mediterranean and tropical areas [23][24][25].…”

“…The sole frequency analysis is insufficient in drought studies unless it is numerically related to other factors, such as the se-verity, duration, and intensity. Yilmaz et al [19] use statistical methods for daily streamflow estimation at ungauged basins in Turkey. The single donor station drainage area ratio (DAR) method, the multiple-donor stations drainage area ratio (MDAR) method, the inverse similarity weighted (ISW) method, and its variations with three different power parameters (1, 2, and 3) are applied to the two main sub-basins of the Euphrates basin in Turkey to estimate daily streamflow data.…”

Hydrological Modeling: A Better Alternative to Empirical Methods for Monthly Flow Estimation in Ungauged Basins

“…Another popular method is transposition of gauged streamflow data to ungauged sites. One of them is the Drainage Area Ratio (DAR) method [16] [17]. It is based on the assumption that the streamflow at the ungauged site can be estimated by multiplying the ratio of the drainage area for this site and the drainage area for the gauging site by the streamflow of the gauging site [17].…”

“…It is based on the assumption that the streamflow at the ungauged site can be estimated by multiplying the ratio of the drainage area for this site and the drainage area for the gauging site by the streamflow of the gauging site [17]. As it needs only catchments areas and the observed streamflow of the gauged station, it is considered one of the easiest methods of flow prediction and therefore popularly used in the past [16]. One of the variants of the DAR method is MDAR (Multiple gauging stations Drainage Area Ratio).…”