Yavuz Selim Güçlü

Trend Assessment by the Innovative-Şen Method

Hydro-meteorological time series may include trend components mostly due to climate change since about three to four decades. Trend detection and identification in a better and refined manner are among the major current research topics in water resources domain. Even though different methodologies can be found for trend detection in literature, two well-known procedures are the Mann-Kendall (MK) trend test and recently innovative-Şen trend method, which provides different aspects of the trend. The theoretical basis and application of these two methods are completely different. The MK test gives a holistic monotonic trend without any categorization of the time series into a set of clusters, but the innovative-Şen method is based on cluster and provides categorical trend behavior in a given time series. The main purpose of this paper is to provide important differences between these two approaches and their possible similarities. The applications of the two approaches are given for hydro-meteorological records including relative humidity, temperature, precipitation and runoff from Ergene drainage basin in the north-western part of Turkey. It is observed that although MK trend test does not show significant trend almost in all the cases, the innovative-Şen approach yields trend categorizations as “very low”, “low”, “medium” “high” and “very high”, which should be taken into consideration in future flood (“very high”) and drought (“very low”) studies.

Climate change and frequency–intensity–duration (FID) curves for Florya station, Istanbul

In recent decades, according to Intergovernmental Panel on Climate Change reports, the impact of climate change on hydro-meteorological events has increased substantially. This point is obvious in many rainfall–runoff time series as a negative or positive trend. In this paper, first of all such trend possibilities are searched graphically according to Şen’s 1:1 (45°) straight-line method, which has been proposed instead of the classical methods including Mann– Kendall, Spearman’s rho and linear regression approaches. Additionally, these trends are quantified by using frequency–intensity–duration (FID) curves, instead of intensity–duration–frequency (IDF) curves obtained from a set of single storm rainfall records. The FID curves provide practical, easy and clear representation of rainfall intensity variation through fitted exponential curves with coefficient of determination that is almost equal to 1 (R ≈ 1). FID curves are drawn on semilogarithmic paper with rainfall intensity estimations from the convenient Gamma probability distribution functions (PDFs) or cumulative distribution functions (CDFs). In this study 46-year rainfall records are used from Florya station, which is located in Istanbul, Turkey. The comparisons generally indicated that a negative trend is valid at this station, and accordingly, representative FID curves are obtained on ordinary and semilogarithmic papers for this station.

Short- and Long-Term Solar Radiation Estimation Method

In this study, Angstrom equation solar radiation estimation values corresponding to the sunshine durations are achieved by a linear equation, which is an improvement over the classical model. The results turn out to be better than the classical Angstrom equation. In the suggested equation, 1–10 days’ solar irradiation values are assumed to affect the present-day values as short-term estimates. The proposed model for summer months (June–July–August) has provided estimations that are in close agreement with observations. Both long- and short-term estimations have been obtained rather successfully. In the proposed methodology there are two extra factors, as dependence coefficients. Finally, the classical Angstrom equation remains as a special case of the model.

Alternative Trend Analysis: Half Time Series Methodology

This paper attempts to determine and visualize the trends by considering the value via Şen’s innovative trend analysis methodology, which has been suggested instead of the well-known approaches called Mann-Kendall (MK), Spearman’s rho (SR), Sen’s slope, and linear regression methodologies. Another attempt is to show that an additional trend approach by using half time series methodology (HTSM) including MK’s Z value, and to compare it with the innovative method. Although, Şen’s method is practical, easy and clear representation of data variation, but some information is not evident on time series. This study comprises 66-year rain gage records in Adana, İzmir, and Rize stations located in different regions of Turkey. The comparison results indicated different trend conditions for these stations. Based on this information, representative figures are obtained according to Şen’s and HTSM for the precipitation records. According to Şen’s method, Adana and Rize stations’ measurements have no trend component but İzmir data have monotonically increasing trend. HTSM results reveal some additional information on Şen’s half time series approach. Adana station time series halves include opposite trends (increasing-decreasing) detected by HTSM in spite of no trend. Different extreme cases are encountered in İzmir and Rize stations through HTSM. As a result, if the proposed method is combined with Şen’s method, better trend analysis results can be obtained for detailed interpretations.

Improving of the Angström-Prescott Model Using Harmonic Analysis

The solar energy as one of the most important energy sources is investigated for effective use in a variety of areas. Especially, with the tendency of depletion of fossil fuel consumption as well as their greenhouse gas emissions leading to atmospheric pollution and, hence, global warming and climate change, the value of renewable energy sources and solar energy is increasing rapidly. In the solar energy prediction, the relationship between solar irradiation and sunshine duration plays the most dominant role. The aim of this study is to apply harmonic analysis, coupled with the classical Angstrom-Prescott equation, to solar irradiation and sunshine duration data for the extraction of its relevant relationship. Firstly, it helps to eliminate the periodicity from the measurement record and then the application of the Angstrom-Prescott model is applied, which is then tested and compared with the classical Angstrom-Prescott model based on the regression approach. The applications are achieved by use of measurements at the major city in the south-eastern Anatolian part of Turkey, namely, Diyarbakir. The improved model provides more successful and reliable outputs than the classical approach.