Abdullah Gokhan Yilmaz

Accuracy of HEC-HMS and LBRM Models in Simulating Snow Runoffs in Upper Euphrates Basin

Forecasting streamflow is extremely significant in hydrological studies to optimize the operation of water resources systems. Upper Euphrates Basin, which is located in eastern Turkey, is a snow-dominated basin and its runoff is largely affected by snowmelt. Snowmelt is an important water resource to many aspects of hydrology, including water supply, flood control, and erosion. Selection of a suitable tool was necessary to assess potential impacts of climate change on the hydrological cycle of this region. Hydrologic models are useful tools for the prediction of runoffs and interactions among hydrological variables within the hydrologic cycle. Because of limited data availability, lumped conceptual hydrological models are often used instead of distributed hydrological models. To assess the accuracy of lumped conceptual hydrological models, this paper presents simulation results of snowmelt runoffs of Upper Euphrates Basin by using two models that use the temperature index approach to calculate snowmelt pr...

Development of river water quality indices—a review

The use of water quality indices (WQIs) as a tool to evaluate the status of water quality in rivers has been introduced since the 1960s. The WQI transforms selected water quality parameters into a dimensionless number so that changes in river water quality at any particular location and time could be presented in a simple and easily understandable manner. Although many WQIs have been developed, there is no worldwide accepted method for implementing the steps used for developing a WQI. Thus, there is a continuing interest to develop accurate WQIs that suit a local or regional area. This paper aimed to provide significant contribution to the development of future river WQIs through a review of 30 existing WQIs based on the four steps needed to develop a WQI. These steps are the selection of parameters, the generation of sub-indices, the generation of parameter weights and the aggregation process to compute the final index value. From the 30 reviewed WQIs, 7 were identified as most important based on their wider use and they were discussed in detail. It was observed that a major factor that influences wider use of a WQI is the support provided by the government and authorities to implement a WQI as the main tool to evaluate the status of rivers. Since there is a lot of subjectivity and uncertainty involved in the steps for developing and applying a WQI, it is recommended that the opinion of local water quality experts is taken, especially in the first three steps (through techniques like Delphi method). It was also observed that uncertainty and sensitivity analysis was rarely undertaken to reduce uncertainty, and hence such an analysis is recommended for future studies.

Runoff Estimation by Machine Learning Methods and Application to the Euphrates Basin in Turkey

AbstractMachine learning (ML) techniques have been popular data-driven approaches for hydrological studies during the last few decades owing to their capability to identify complex nonlinear relationships between input and output data without the requirement for physical understanding of the system. This paper aims to predict river flows using various ML methods [feed forward neural network (FFNN), adaptive neuro fuzzy inference system (ANFIS), and genetic programming (GP)] and also a non-ML method (multiple linear regression) in the Euphrates Basin in Turkey. Infilling the missing data in the runoff record of the selected stations in Euphrates Basin is also an objective of this study. The ML methods were applied to the three main sub-basins of the Euphrates Basin, namely the Upper, Middle, and Lower Euphrates Basins. ANFIS and FFNN methods were the most successful ML methods for runoff estimation in the Upper and Lower Euphrates Basins, whereas GP and ANFIS models were the best ones in the Middle Euphrat...

Genetic Programming-Based Ordinary Kriging for Spatial Interpolation of Rainfall

AbstractRainfall data provide an essential input for most hydrologic analyses and designs for effective management of water resource systems. However, in practice, missing values often occur in rainfall data that can ultimately influence the results of hydrologic analysis and design. Conventionally, stochastic interpolation methods such as kriging are the most frequently used approach to estimate the missing rainfall values where the variogram model that represents spatial correlations among data points plays a vital role and significantly impacts the performance of the methods. In the past, the standard variogram models in ordinary kriging were replaced with the universal function approximator-based variogram models, such as artificial neural networks (ANN). In the current study, applicability of genetic programming (GP) to derive the variogram model and use of this GP-derived variogram model within ordinary kriging for spatial interpolation was investigated. Developed genetic programming-based ordinary ...

The effects of climate change on historical and future extreme rainfall in Antalya, Turkey

Abstract There is increasing concern that flood risk will be exacerbated in Antalya, Turkey as a result of global-warming-induced, more frequent and intensive, heavy rainfalls. In this paper, first, trends in extreme rainfall indices in the Antalya region were analysed using daily rainfall data. All stations in the study area showed statistically significant increasing trends for at least one extreme rainfall index. Extreme rainfall datasets for current (1970–1989) and future periods (2080–2099) were then constructed for frequency analysis using the peaks-over-threshold method. Frequency analysis of extreme rainfall data was performed using generalized Pareto distribution for current and future periods in order to estimate rainfall intensities for various return periods. Rainfall intensities for the future period were found to increase by up to 23% more than the current period. This study contributed to better understanding of climate change effects on extreme rainfalls in Antalya, Turkey.

Cokriging for enhanced spatial interpolation of rainfall in two Australian catchments

Rainfall data in continuous space provide an essential input for most hydrological and water resources planning studies. Spatial distribution of rainfall is usually estimated using ground-based point rainfall data from sparsely positioned rain-gauge stations in a rain-gauge network. Kriging has become a widely used interpolation method to estimate the spatial distribution of climate variables including rainfall. The objective of this study is to evaluate three geostatistical (ordinary kriging (OK), ordinary cokriging (OCK), kriging with an external drift (KED)) and two deterministic (inverse distance weighting, radial basis function) interpolation methods for enhanced spatial interpolation of monthly rainfall in the Middle Yarra River catchment and the Ovens River catchment in Victoria, Australia. Historical rainfall records from existing rain-gauge stations of the catchments during 1980-2012 period are used for the analysis. A digital elevation model of each catchment is used as the supplementary information in addition to rainfall for the OCK and KED methods. The prediction performance of the adopted interpolation methods is assessed through cross-validation. Results indicate that the geostatistical methods outperform the deterministic methods for spatial interpolation of rainfall. Results also indicate that among the geostatistical methods, the OCK method is found to be the best interpolator for estimating spatial rainfall distribution in both the catchments with the lowest prediction error between the observed and estimated monthly rainfall. Thus, this study demonstrates that the use of elevation as an auxiliary variable in addition to rainfall data in the geostatistical framework can significantly enhance the estimation of rainfall over a catchment.

Climate change and water resources in Turkey: a review

There is a close link between climate change and water resources owing to the strong relationship between climate and hydrology. Effects of climate change on water availability have potential to impact water supply for domestic, agricultural, industrial, environmental, and hydro-electricity generation purposes in Turkey. Thereby, it is necessary to develop hydro-meteorological impact studies in Turkey to have better understanding of how climate change may affect the regions, in order to enable policy makers to produce efficient adaptation policies. The first step of a hydro-meteorological impact study is to make a comprehensive review of the literature to identify where and how to contribute. This paper aims to provide an extensive review of the literature on climate change effects on hydrometeorology and water resources in Turkey and it proposes to put a light on the future climate change studies in Turkey.

Climate change fingerprints in lower Euphrates basin: climate and flow data trend analysis

It is expected that climate change will affect the global weather, snow coverage and ice melting, sea level rise, hydrological cycle, agriculture and forests, ecosystems and health. One of the most affected areas of climate change is hydrology and water resources. In addition to adverse impact of climate change, increasing uncontrolled abstractions from the upper basins is likely to worsen the situation in the lower basins. Euphrates River, the longest in Western Asia, originates from the Armenian highlands and flows through Turkey, Syria and Iraq. The lower Euphrates River basin is predominantly in Iraq and likely to be affected by climate change. Owing to constant rise of water demands, to achieve a sustainable water management policy it is necessary to assess the impacts of climate change in the region. To assess trends of precipitation, temperature and streamflow to determine whether climate change impacts have already started in the lower Euphrates basin, two popular non-parametric trend analysis methods, Mann-Kendall and Spearmans rho tests, were applied in this study. Based on the time series data, a significant rising trend in temperature and a significant decreasing trend in streamflow were observed, which would be an important perception for policy making pertaining to water resources management in the lower Euphrates basin.