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The Short-Term and Seasonal Trend Detection of Sediment Discharges in Turkish Rivers

Burgan Halil Ibrahim

Rocznik Ochrona Środowiska

2022

Tom 24

214--230

Hydrometeorological variables are tested by trend methods to detect trends in river basins. Mann-Kendall and Spearman’s rho tests are widely used as traditional trend methods. Besides, some new trend tests are applied to hydrometeorological variables, such as Innovative Trend Analysis (ITA). Sediment discharge observations are more complicated than other hydrometeorological variables. In general, sediment data are observed on a monthly time scale. Therefore, there are minimal studies on sediment data, especially in Turkey. In this study, Innovative Trend Analysis (ITA), Mann-Kendall, Correlated Mann-Kendall and Seasonal Mann-Kendall trend analyses are applied to sediment discharges in Turkish river basins. According to Mann-Kendall, Correlated Mann-Kendall and Seasonal Mann-Kendall results, positive trends have detected only 8, 2 and 20 gauging stations, respectively. Then, 30 positive and 15 negative trends were detected by ITA methodology. The trend slopes calculated from ITA methodology are categorised because some positive and negative trends are weak. The applied trend methods are evaluated together, considering the climate properties of hydrological regions in Turkey. Increasing trends in sediment data are detected from the rivers in the Mediterranean region of Turkey. The results of the study would help to manage water resources as well as sustainable development in the Turkish river basins.

Visual and statistical inference of hourly and sub hourly extreme rainfall trends Central Anatolia, Turkey case

Oruc Sertac

Acta Geophysica

2021

Vol. 69, no. 1

199--216

The analysis of long-term rainfall data in a changing climate is important because it has many sectoral applications such as agriculture, infrastructure, and water resources management. Statistical analyses of the annual maximum rainfall data were performed using the Mann–Kendall (MK) trend test to evaluate the annual maximum trend characteristics of the rainfall time series, the innovative trend analysis (ITA) method to detect categorial trends, and the ITA indicator to digitize the ITA results. Storm durations of 5, 10, 15, 30 min and 1, 3, 6, 24 h annual maximum rainfall series at 13 central stations in Central Anatolia, Turkey were used. According to the MK test results, there were no signifcant upward or downward monotonic trend at four stations, whereas the remaining nine stations showed a signifcant upward or downward monotonic trend. Signifcant negative and positive trends were identifed for the sub-hourly and hourly rainfall, whereas signifcant positive trends were detected for hourly storm durations. Signifcant trend results were mostly consistent with the general ITA results. The sub hourly storm duration data were more consistent in terms of signifcant trends. Conversely, when evaluated according to low, medium, and high data values in the rainfall series (categories), the high data values showed diferent trends. Although no trend was detected with the MK test, the ITA results showed an upward or downward trend for 25 rainfall series. 29 of 30 signifcant MK test results were consistent with the ITA indicator results, compared with 24 of 30 results of the visually inspected ITA results.