Frequency analysis of low flows in intermittent and non-intermittent rivers from hydrological basins in Turkey

Eriş, Ebru; Aksoy, Hafzullah; Önöz, Bihrat; Çetin, Mahmut; Yüce, Mehmet; Selek, Bülent; Aksu, Hakan; Burgan, Halil İbrahim; Eşit, Musa; Yildirim, I Ilhan; Karakus, Ece Unsal

doi:10.2166/ws.2018.051

Cited by 45 publications

(24 citation statements)

References 18 publications

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“…Agwata [76] used an L-moments statistics approach to assess probability distributions in the Upper Tana Basin, and found that Pearson type 3 is not the best-fit model in the area, which is also reflected in this study. Elsewhere in the world, Eris, Aksoy [77] showed that the lognormal and Weibull distribution functions mostly conform to low flows in hydrological basins in Turkey [5]. Furthermore, using the maximum likelihood approach, Eris selected the Weibull function as the best probability distribution function suitable for the analysis of eight sites in the Niger Basin.…”

Section: Discussionmentioning

confidence: 99%

Identification of the Most Suitable Probability Distribution Models for Maximum, Minimum, and Mean Streamflow

Langat

Kumar

Koech

2019

Water

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Hydrological studies are useful in designing, planning, and managing water resources, infrastructure, and ecosystems. Probability distribution models are applied in extreme flood analysis, drought investigations, reservoir volumes studies, and time-series modelling, among other various hydrological studies. However, the selection of the most suitable probability distribution and associated parameter estimation procedure, as a fundamental step in flood frequency analysis, has remained the most difficult task for many researchers and water practitioners. This paper explains the current approaches that are used to identify the probability distribution functions that are best suited for the estimation of maximum, minimum, and mean streamflows. Then, it compares the performance of six probability distributions, and illustrates four fitting tests, evaluation procedures, and selection procedures through using a river basin as a case study. An assemblage of the latest computer statistical packages in an integrated development environment for the R programming language was applied. Maximum likelihood estimation (MLE), goodness-of-fit (GoF) tests-based analysis, and information criteria-based selection procedures were used to identify the most suitable distribution models. The results showed that the gamma (Pearson type 3) and lognormal distribution models were the best-fit functions for maximum streamflows, since they had the lowest Akaike Information Criterion values of 1083 and 1081, and Bayesian Information Criterion (BIC) values corresponding to 1087 and 1086, respectively. The Weibull, GEV, and Gumbel functions were the best-fit functions for the annual minimum flows of the Tana River, while the lognormal and GEV distribution functions the best-fit functions for the annual mean flows of the Tana River. The choices of the selected distribution functions may be used for forecasting hydrologic events and detecting the inherent stochastic characteristics of the hydrologic variables for predictions in the Tana River Basin. This paper also provides a significant contribution to the current understanding of predicting extreme hydrological events for various purposes. It indicates a direction for hydro-meteorological scientists within the current debate surrounding whether to use historical data and trend estimation techniques for predicting future events with issues of non-stationarity and underlying stochastic processes.

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Section: Discussionmentioning

confidence: 99%

Identification of the Most Suitable Probability Distribution Models for Maximum, Minimum, and Mean Streamflow

Langat

Kumar

Koech

2019

Water

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“…Models have to capture discontinuities in the flow regime during a substantial period of the year (Smith et al, 2010;Pumo et al, 2014;Gong et al, 2014;Eris et al, 2018). Models have to capture discontinuities in the flow regime during a substantial period of the year (Smith et al, 2010;Pumo et al, 2014;Gong et al, 2014;Eris et al, 2018).…”

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confidence: 99%

“…From a modelling perspective, simulation of intermittent catchments' response to rainfall is a challenging endeavour. Models have to capture discontinuities in the flow regime during a substantial period of the year (Smith et al, 2010;Pumo et al, 2014;Gong et al, 2014;Eris et al, 2018). Additionally, because streamflow is not continuous, a full picture of the catchment water balance is required, such that modelling groundwater storage changes becomes important for water management.…”

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confidence: 99%

Simulated response of an intermittent stream to rainfall frequency patterns

Azarnivand

Camporese

Alaghmand

et al. 2019

Hydrological Processes

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The response of intermittent catchments to rainfall is complex and difficult to model. This study uses the spatially distributed CATchment HYdrology (CATHY) model to explore how the frequency of daily rainfall ( ) can affect the hydrologic regime of intermittent catchments. After a multi-objective calibration and validation of CATHY against experimental measurements of streamflow and groundwater levels in a catchment used as a pasture, the role of in affecting streamflow characteristics was explored using different scenarios. With different values of for the dry and wet periods of the year, CATHY showed that a series of frequent rainfall events was often associated with incipient streamflow, independent of the season. Activation of streamflow during the wet season was related to multiple factors and was not often associated with the shallow groundwater levels near the outlet of the catchment.The interplay between rainfall depth and intensity acted as the most important factor for the generation of streamflow. Using the difference between accumulated rainfall and evapotranspiration as a measure of wetness, saturated subsurface flow mechanism generated streamflow in simulations with wetness at least three times larger than mean wetness of other simulations. Although groundwater uprise near the outlet did not effectively contribute to streamflow in the initial days of flow, it strongly correlated with the magnitude of the runoff coefficient. Values of close or equal to the maximum value in the wet season can sustain the connectivity between groundwater and streamflow in the riparian zone. This connectivity increases the catchment wetness, which consequently results in an increase of the generated streamflow. Our study showed that rainfall regimes characterized by different were able to identify distinct flow regimes typical of either intermittent, ephemeral, or nonflowing catchments. Decrease of in the wet season is likely associated with a reduction of streamflow, with a shift of flow regime from intermittent to ephemeral or no-flow.

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“…The basin is located between the north latitudes 36 • 33 to 38 • 44 , and the east longitudes 35 • 15 to 37 • 43 [39]. Mountains in the basin are as high as 2500 m [40]. The southern part of the basin stays in the Cukurova Plain, which is one of the most important agricultural production areas in Turkey [41].…”

Section: Study Area and Datamentioning

confidence: 99%

Monthly Flow Duration Curve Model for Ungauged River Basins

Burgan

Aksoy

2020

Water

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Flow duration curve (FDC) is widely used in hydrology to assess streamflow in a river basin. In this study, a simple FDC model is developed for monthly streamflow data. The model consists of several steps including the nondimensionalization and then normalization in case the monthly streamflow data do not fit the normal probability distribution function. The normalized quantiles are calculated after which a back transformation is applied to the normalized quantiles to return back to the original dimensional streamflow data. In order to calculate annual streamflow of the river basin, an empirical regression equation is proposed using the drainage area and the annual total precipitation only as the input. As the final step of the model, dimensional quantiles of FDC are calculated. Ceyhan River basin in southern Turkey is chosen for the case study. Forty-two streamflow gauging stations are considered; two thirds of the gauging stations are used for the model calibration, and one third for validation. The modeled FDCs are compared to the observation and assessed with a number of performance metrics. They are found similar to the observed ones with a relatively good performance; they are good in the mid and high flow parts particularly while the low flow part of FDCs might require further detailed analysis.The FDC of the hydrological basin is obtained from the observed streamflow data. However, hydrological basins are not always properly gauged [23]. Therefore, regional FDCs are developed to transfer information from gauged sites to ungauged sites through the use of morphological characteristics of the hydrological basin [24], the combination of basin characteristics with probability distribution functions [25] or the development of regression or polynomial equations based on the drainage area [26,27]. The landscape and climate characteristics are also used for regional FDCs of ungauged basins [28,29]. A particular example for the dimensionless regional FDC in watersheds with no or limited data was given by Ganora et al. [30]. The comparative study of Swain and Patra [31] on the regional FDCs in ungauged basins should finally be mentioned from the literature.Although a great experience is available in the literature on FDCs, research is still needed for ungauged basins particularly in developing countries where water resources development projects are in progress, and most of the hydrological basins are either ungauged, improperly gauged or poorly gauged. The transfer of FDC models developed for a gauged hydrological basin is not transferable to any another basin unless the basins are similar not only in terms of their hydrometeorological character but also in terms of their geomorphology [32]. With higher needs to water, smaller size river basins or subbasins within river basins, which are likely ungauged or poorly gauged, have gained importance for water resources development programs of countries under development. Therefore, studies on FDC models still emerge for ungauged river basins.This study aims at contributi...

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Frequency analysis of low flows in intermittent and non-intermittent rivers from hydrological basins in Turkey

Cited by 45 publications

References 18 publications

Identification of the Most Suitable Probability Distribution Models for Maximum, Minimum, and Mean Streamflow

Identification of the Most Suitable Probability Distribution Models for Maximum, Minimum, and Mean Streamflow

Simulated response of an intermittent stream to rainfall frequency patterns

Monthly Flow Duration Curve Model for Ungauged River Basins

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