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The wind has considerable effects on the ecosystem and evaporation as an essential parameter of the hydrological cycle. Therefore, determining historical changes in the wind will help to specify these effect levels. Although there are studies on the determination of wind speed trends by several researchers in Turkey, it is necessary to investigate the changes in the trend structure with recent data. For this purpose, the trends of monthly surface wind speed data from 1970 to 2021 belonging to 199 meteorology observation stations in Turkey are determined in the present study. The nonparametric Mann–Kendall test and Sen's slope method are used in the trend analysis accounting for serial correlation effects. The trend analysis results of wind speed data are evaluated temporally and spatially for seven geographical regions within Turkey. As a result of this study, a prominent part of stations in Turkey shows a decrease or significant decrease trend. In addition, as a result of comparisons made with previous studies, it is determined that the trend structure of the wind speed in the country has changed. In the annual and monthly wind speeds, it is observed that the number of stations has a "significant trend" decreased considerably. [ABSTRACT FROM AUTHOR]

Analyzing trends in precipitation data is crucial for understanding the effects of climate change and making informed decisions about water management and crop patterns. The objective of the presented study was to investigate precipitation trends, analyze temporal and spatial variations and identify potential change points in Turkey throughout the period from 1980 to 2019. Precipitation data were analyzed for both regional and 81 meteorological stations in Turkey on a monthly, seasonal, and annual basis. Spearman rank correlation and Mann–Kendall tests were utilized to detect possible trends and Sen's slope test to estimate the magnitude of change throughout the entire time series. The average precipitation amount of Turkey was determined 639.2 mm between the years 1980 and 2019. While Central Anatolian and Eastern Anatolian regions had below 639.2 mm, other regions were above. The range of seasonal precipitation values were found for winter 128.7–320.8 mm, 108.9–260.0 mm for spring, 43.9–109.3 mm for summer, and 79.7–238.4 mm for autumn. The analysis of the data revealed no significant increase or decrease in annual values on a regional basis, with the greatest change on a seasonal basis being observed in the winter. The 40-year trends of annual precipitation data belonging to 81 stations were decreasing in 23 provinces and increasing in 58 provinces, and 11 of them (14% of the total) were found to be statistically significant. Moreover, November was found to be a month of particular significance in terms of precipitation changes across the country, with a decrease observed in 80 out of 81 provinces. Spatial distribution analysis showed that the magnitude of variation in precipitation decreased as one moved from the southern to the northern regions of the country. [ABSTRACT FROM AUTHOR]

In this study, trend analyses of six climatic variables (mean, minimum, and maximum temperature, relative humidity, wind speed, and precipitation) for 1966-2020 are conducted for the Southeastern Anatolia Region, which is the main focus of the integrated development project in Turkey (Turkish acronym GAP). The trends for seasonal and annual periods are determined using the Mann-Kendall (MK) test, and Sen's slope method and regression analyses are used to find the trends' slopes. Moreover, Innovative Trend Analysis (ITA) is also used to find the time series changes for low, medium, and high values. As a result of the analyses, the mean, minimum, and maximum temperatures in the GAP region show increasing trends according to both methods. Significant trends are obtained at a limited number of stations for the precipitation, relative humidity, and wind speed with the MK test, while consistent decreasing trends are found at most stations with the ITA method. [ABSTRACT FROM AUTHOR]

A comprehensive evaluation of trends in annual instantaneous maximum flows (AIMF) from 153 gauge stations located in 26 river basins in Turkey is presented. Two traditional non-parametric trend tests, the Mann-Kendall (MK) and Spearman's rho (SR), are used to quantify the significance of trends, while Sen's slope method is applied to determine the magnitude of trends. The traditional tests indicate that the AIMF records of 57 stations showed statistically decreasing trends, while those of six stations showed an increasing trend. Sen's trend method, which provides more detailed assessment of the trends in different clusters (low, medium and high), was applied to the AIMF series and the results were compared with traditional tests. Sen's trend method indicated that all flow clusters at nine stations have increasing or decreasing trends, although no significant trend was detected by the MK and SR tests. [ABSTRACT FROM AUTHOR]

Knowledge of the historical changes in streamflow is essential for operating and planning water structures. Hence, the monthly mean streamflow trends of 20 streamflow gauge stations in Turkey's Mediterranean basins, which are sensitive to climate change, are examined using the Mann–Kendall test, and trend slopes are calculated using Sen's slope method. Furthermore, the innovative trend significance test (ITST) and recently proposed innovative polygon trend analysis (IPTA) method are used to analyse the historical changes in streamflow values at the stations. The trend analysis results of a total of 240-time series between 1977 and 2015 are evaluated and compared with three different trend methods. As a result of the study, the MK method determined significant trends in only 24% (3 increasing, 55 decreasing), ITST in 83% (41 increasing, 158 decreasing), and IPTA in 82% (38 increasing, 158 decreasing) of the 240-time series. The IPTA and ITST methods are more sensitive to determining significant monthly streamflow trends than the MK method. In addition, there is a more significant decrease in the streamflow values of the stations located east of the basin, and the trend slope value reaches − 26%/decade. Therefore, the results of the streamflow trend in the Mediterranean basins will benefit decision-makers in planning the efficient use of water resources in the region. [ABSTRACT FROM AUTHOR]

Temperature has a control on growth, development and yield of crops. Extreme high and low temperatures can be a limiting factor on crops. Extreme temperatures have accompanied global average temperature increase. Investigating the changes in indices derived using daily minimum and maximum temperatures may provide information about how extreme temperatures related to crop production have changed under global warming. In this sense, it is aimed in this study to investigate the climatology and monotonic temporal trends of a number of temperature-based agroclimatic indices across western Anatolia, Türkiye. The indices included number of frost days (NFD), first fall/winter frost (FFF), last winter/spring frost (LSF), frost period (FP), accumulated frost (AF), plant heat stress day (PHSD), plant heat stress accumulation (PHSA), growing season start (GSS), growing season end (GSE), growing season length (GSL) and growing degree-day (GDD). Significance of trends was assessed using Mann–Kendall test, and trend rates were quantified by Sen's slope estimator. The results firstly showed that southern low-elevation stations have the lowest frequency, intensity and duration of frost as a result of rarely occurring frost events. These stations are also characterized by the highest GDD, the earliest GSS, the latest GSE and hence the longest GSL, even with never-ending growing seasons in many years. They are also exposed to the highest heat stress in terms of frequency and intensity. On the other hand, northern high-elevation stations have completely opposite character for all indices in comparison to southern low-elevation stations. Trend analysis revealed that frequency of frost events had decreasing trends (i.e., decreased NFD), accompanied by later onset of FFF, earlier onset of LSF and hence shortened FP and decreased AF. As for growing season indices, in general, GSS occurred earlier, GSE occurred later and GSL extended. Growing degree-day and heat stress indices had substantial increasing trends, implying that, over the course of study period, the study area had more thermal accumulation and exposed to more heat stress that may hinder crop development. [ABSTRACT FROM AUTHOR]

Trend identification procedures are used to identify systematic monotonic trendlines in a given hydro-meteorological time series recording to represent time-dependent variations as increases or decreases. Different methodologies have been proposed for such descriptions, but most of them require restrictive assumptions such as normal (Gaussian) probability distribution function (PDF), serial independence, and long sample sizes. In particular, pre-whitening and over-whitening are recommended to meet the need for serial independence, but they cannot transform a serially dependent series into a completely independent one. In this paper, a new trend methodology is proposed based on the characteristics of crossings along any given straight line within the given time series, and the sought-after trend component is the one with the maximum number of crossings. This approach does not require any restrictive assumptions. Unlike previous trend algorithms, the proposed cross-empirical trend analysis (CETA) does not give a single trend, but a series of trends at different levels within the variation range of hydro-meteorological time series records. For the sake of brevity, only three levels are considered in this article, at 10%, 50%, and 90% risk levels. The comparison of the CETA approach is presented with the classical and frequently used Mann–Kendall (MK) trend determination procedure method based on Sen's slope calculation. For very small series correlation coefficients and normal PDF function cases, CETA and the classical technique give almost the same trendline within the ± 5% error band. The application of this methodology is presented for monthly and annual discharge records of the Danube River and annual precipitation records from seven geographical regions of Turkey. [ABSTRACT FROM AUTHOR]

In this study, the trend of monthly mean and annual streamflow values of 16 streamflow gauge stations in the Tigris basin, which holds 13% water potential for Turkey, is determined. The monotonic trends are calculated using non-parametric Mann−Kendall (MK) test. To remove serial correlation from time series, a modified 'pre-whitening' method is used. The trend slopes are determined by Sen's slope method. Moreover, innovative trend analysis (ITA) method is also used to determine trends of low, medium and high streamflow values. As a result of the study, trend indicators, namely, Z values of MK tests and D values of the ITA method are compared and it has been observed that the trend directions by MK and ITA are generally similar. Nevertheless, only the negative D values calculated by ITA are mostly higher than the negative Z values calculated by MK. The ITA results of the annual mean streamflow show 80% of the stations show a strong decrease in trend for high values. Most of the significant trends found by MK are obtained in a decreasing direction, and the linear slopes are mostly determined in the range of ±2% per year. According to the spatial analysis, the significant decreasing trends are generally located in the middle region of the basin. [ABSTRACT FROM AUTHOR]

Determining the change in the amount of evaporation is important for water resources management, design of water structures and preparing water action plans. In this study, trends of total monthly pan evaporation data for Gaziantep, Şanlıurfa and Mardin stations located as Southeastern Anatolia Region, which is important agricultural area of Turkey, are carried out using non-parametric Mann-Kendall (MK) and Innovative Trend Analysis (ITA) methods. The linear trend slope is determined with Sen's slope method. As a result of the study, the significant increasing trend is found with MK test in May and September at 95% confidence level and in October at 90% confidence level. The highest increase in this station according to the linear trend slope values is calculated 0.98%/year. As a result of analysis with ITA method, there is a trend occurrence in low, medium, and high values. It is concluded that ITA method can be used as an alternative method to monotonic trend analysis methods, since its ease of calculation and its ability to give results graphically. [ABSTRACT FROM AUTHOR]

The Antalya Basin is characterised by high spatiotemporal variability of precipitation. Despite the basin's importance for sustainable water use and its specific place in socio-economy of Turkey, the spatiotemporal patterns of precipitation are not thoroughly studied. This study aims to improve the understanding of spatiotemporal variability of precipitation and extreme precipitation indices (i.e. annual maximum 1-day and 5-day precipitation, maximum number of consecutive dry and wet days) in the basin for the period 1970–2017. To this end, trend detection methods—Mann-Kendall, modified Mann-Kendall, and Sen's slope estimation methods—were employed with change-point detection methods—Pettitt, Buishand, Standard Normal Homogeneity, Pruned Exact Linear Time, and Wild Binary Segmentation. Further, continuous wavelet analysis was used to analyse the multi-scale resolution features of precipitation. Our results suggested three basin-wide distinct periods with the specific spatiotemporal distribution of precipitation and extreme indices among the sub-periods. The characteristics of the variability of precipitation and extreme indices for the sub-periods were discussed. The outcomes from this study could be useful to decision makers for sustainable water management and mitigate unfavourable impacts of flood and drought threats in one of the most vulnerable and sensitive basins to the impacts of climate change of the country. [ABSTRACT FROM AUTHOR]

Despite the recent popularity of studying the effects of climate change on critical regions worldwide, there is a paucity of data documenting the results from trend analysis for these regions based on hydro‐climatic variables such as precipitation and temperature. The purpose of this study was to undertake a spatio‐temporal precipitation and temperature trend analysis for the Seyhan and Ceyhan River Basins located in the south of Turkey. The data for the seasonal and annual temperature variations (minimum, maximum and mean) and the total precipitation outputs obtained from the 14 stations in these basins are considered. The non‐parametric Mann–Kendall and the Mann–Kendall rank correlation tests are employed to determine the trend and its year of initiation. The linear slopes of the trends are calculated by using Sen's slope estimation technique and the spatial distributions for the slope of trends are presented. The results show that statistically significant upward trends exist for these basins based on the annual maximum temperature values, and the years of initiation of the trends are determined as mid‐1990 and mid‐2000. [ABSTRACT FROM AUTHOR]

Trend analyses are the necessary tools for depicting possible general increase or decrease in a given time series. There are many versions of trend identification methodologies such as the Mann-Kendall trend test, Spearman's tau, Sen's slope, regression line, and Şen's innovative trend analysis. The literature has many papers about the use, cons and pros, and comparisons of these methodologies. In this paper, a completely new approach is proposed based on the crossing properties of a time series. It is suggested that the suitable trend from the centroid of the given time series should have the maximum number of crossings (total number of up-crossings or down-crossings). This approach is applicable whether the time series has dependent or independent structure and also without any dependence on the type of the probability distribution function. The validity of this method is presented through extensive Monte Carlo simulation technique and its comparison with other existing trend identification methodologies. The application of the methodology is presented for a set of annual daily extreme rainfall time series from different parts of Turkey and they have physically independent structure. [ABSTRACT FROM AUTHOR]

ABSTRACT This study examines the spatial and temporal dynamics of wind speeds over Turkey by analysing data from 206 weather stations for a 32-year period (1975-2006). Trends in annual, seasonal, and monthly average wind speeds were determined using the Mann-Kendall trend test with the trend-free pre-whitening procedure. The strengths of trends were estimated by calculating the Sen's slope. The possible causes of wind speed changes were discussed. The analysis showed that the majority of the stations (73%) in Turkey had average wind speeds between 1.6 and 3.3 m s−1 during the 32-year period. From 1975 to 2006, 72% of stations had downward trends in annual average wind speeds. Downward trends were statistically significant at the 0.05 level for 62%. Significant upward trends were detected in only 16% of 206 stations. The rate of change in annual average wind speed data was on average −0.014 m s−1 year−1. The trends detected in monthly average wind speed data were mostly downward with an average strength between −0.007 and −0.017 m s−1 year−1. The directions and strengths of wind speed trends identified for the 1975-2006 period over Turkey are similar to the trends detected in wind speeds in many other regions over the earth. The changes in wind speeds in Turkey are most strongly related with the changes in general circulation patterns and air temperatures. The effects associated with changes in surface roughness and data quality are minor compared to other two factors. [ABSTRACT FROM AUTHOR]

In this study, it was aimed to investigate long-term trends of annual precpitation data recorded in sixteen stations operated by DMI (Turkish State Meteorological Service) and DSI (State Hydraulics Works) in Büyük Menderes Basin (Turkey) using Mann-Kendall test with TFPW (Trend-Free Prewhitening) procedure that eliminates the serial correlation for time series containing serial correlation. The slopes of trends were determinded by Sen's Slope Estimator. Homogeneity of trends among stations was tested using Van Belle and Hughes test. The results showed that total annual rainfall increased at only two stations, while decreased at other stations. However, the trend at only one station is statistically significant at 5% level. Temporal patterns of DSI-stations were found to be consistent with those of DMI-stations. Decreasing trends among the stations was found to be homogeneous. It is expected that demand on fresh water resources will increase due to decreasing rainfall as a consequence of climate change, together with domestic, industrial and agricultural water use. To cope with the expected water scarcity in the basin, reuse of treated wastewaters, especially in agriculture, may provide an important opportunity. Hence, this may alleviate the competition among water users, and fresh water resources can be allocated to domestic and industrial use. [ABSTRACT FROM AUTHOR]

The aim of this study was to investigate long-term seasonal trends and decadal change patterns of monthly mean water vapor pressure (WVP) observation series at 16 meteorological stations scattered point-wisely over the Southeastern Anatolian Project (GAP) area in Turkey, where large-scale soil and water development projects have been put into practice since the 1970s. The record length of WVP observation series of each station varied between 31- and 41-years between 1962 and 2002. The monthly mean WVP observation series of each station was rearranged on seasonal basis. Sequential Mann--Kendall trend test, Sen's slope estimator, and Spearman's rank--order correlation tests were employed for detection of likely trends, and Kruskall--Wallis test was used to detect decadal variations in WVP series of each observation station. A possible area of representation for each meteorological station was determined by using the Thiessen polygons technique in a geographical information systems media. It was found that 15 seasonal WVP series have a positive trend covering 97% of the GAP area in the summer season; although one WVP series has a negative trend direction. However, in the spring season, 33% of the area had a positive trend, and a negative trend did not appear in any stations. WVP records in the winter season showed an increasing trend over 19% of the GAP area, whereas a decreasing trend prevailed in 9% of the area. The study results led us to conclude that the substantial increase of WVP observations in summer season could be attributed to both the shift from rain-fed agriculture to irrigated agriculture being made increasingly spacious year by year and building large water reservoirs in the GAP located in a semi-arid region. The results also indirectly suggested that the historical trends in the WVP parameters might be related to global climate change phenomenon. [ABSTRACT FROM AUTHOR]