Investigation of innovative trend approaches (ITA with significance test and IPTA) comparing to the classical trend method of monthly and annual hydrometeorological variables: a case study of Ankara region, Turkey

Eşit, Musa

doi:10.2166/wcc.2022.356

Cited by 27 publications

(13 citation statements)

References 51 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Moreover, the ITA method complies perfectly with the other applied methods but with higher percentages than the others. This discrepancy can be explained by the ability of this method to unmask hidden increasing (decreasing) trends in the time series in Turkey (Esit, 2022; Güçlü, 2020), in Southern Italy (Caloiero, 2019) and in China (Dong et al, 2020; Li et al, 2018).…”

Section: Resultsmentioning

confidence: 99%

Spatio‐temporal analysis of trends in annual maximum rainfall in the North‐West of Algeria: Comparative analysis of recent and old non‐parametric methods

Benzater,

Elouissi,

Fellah

et al. 2023

Water & Environment J

View full text Add to dashboard Cite

This article examines the spatial variability of extreme precipitation trends in northwestern Algeria (Macta) and compares the results obtained from the four recent and old non‐parametric methods. A dataset of annual maximum precipitation consisting of 41 observation years (1970–2010) and 41 rain gauges was used. The results of the four old and new methods used to detect trends, Mann–Kendall (MK), Bravais–Pearson (BP), Spearman (SR) and innovative trend analysis (ITA), show good agreement. They revealed that a decrease in the trend of annual maximum precipitation was detected during the first period (1970–1992) with −44% (MK), −61% (BP), −68% (SR) and −76% (ITA). On the other hand, in the second period (1993–2010), a total shift occurred in which a significant increase in annual maximum precipitation trends was observed with +63% (BP), +34% (MK and SR) and +93% (ITA). These results show the ability of ITA to detect partial trends that the other three tests do not allow. Our results allow decision‐makers to properly design adaptation strategies in the face of the intensification of these extreme events.

show abstract

Section: Resultsmentioning

confidence: 99%

Spatio‐temporal analysis of trends in annual maximum rainfall in the North‐West of Algeria: Comparative analysis of recent and old non‐parametric methods

Benzater,

Elouissi,

Fellah

et al. 2023

Water & Environment J

View full text Add to dashboard Cite

show abstract

“…The examination of trends in meteorological variables is a vital topic of research before the projection of future climate variables since climate change continues to have an impact on many facets of life (Birpnar et al, 2023;Sen et al, 2019;Esit, 2023). The identification of climate change impact in a specific area often relies on the analysis of key meteorological variables such as precipitation and air temperature (Dong et al, 2020).…”

Section: Trend Analysismentioning

confidence: 99%

“…Moreover, this method is capable of uncovering monthly and seasonal variations that may not be detected by the traditional annual hydrometeorological analysis (Sen et al, 2019). Several studies currently apply the IPTA technique and suggest its capacity for exploring the hidden trends that occur during the holistic annual trend detection approach (Akcay et al, 2022;Esit, 2023;Sen et al, 2019). Akcay et al (2022) applied both IPTA and Man Kendall (MK) for trend analysis of winds and waves and indicated that the IPTA method is more sensitive and detects more trends than the MK method.…”

Section: Innovative Polygon Trend Analysis (Ipta)mentioning

confidence: 99%

“…In the Shandong plain regions, the highest significant increasing trend is identified at the Dingtao station in January (39.3%), whereas the maximum significant decreasing trend is recorded at the Heze station in December (180.4%). Several studies currently apply the IPTA technique and suggest its capacity for exploring the hidden trends that occur during the holistic annual trend detection approach (Akcay et al, 2022;Esit, 2023;Sen et al, 2019). Akcay et al (2022) applied both IPTA and Man Kendall (MK) for trend analysis of winds and waves and indicated that the IPTA method is more sensitive and detects more trends than the MK method, which aligns with these study results.…”

Section: Ipta Testmentioning

confidence: 99%

See 1 more Smart Citation

Trend Analysis and Projection of Climate Variables Using the LARS-WG Model in Coastal Areas of China

Disasa,

Yan,

Wang

et al. 2024

Preprint

View full text Add to dashboard Cite

The rising air temperature and shifting precipitation patterns threaten crop production and water distribution worldwide. The coastal region of China, specifically the Huaibei and Shandong Plains, is recognized as one of the most vulnerable areas among those impacted due to the complex interplay of land, sea, and atmospheric dynamics. The study utilized traditional trend analysis methods (Mann-Kendall and Sen's Slope) along with an innovative polygon trend analysis (IPTA) to predict the baseline arithmetic mean and standard deviation of the monthly precipitation trend. Moreover, the latest version of the Long Ashton Research Station Weather Generator (LARS-WG 7) model was used to predict average mean monthly precipitation and maximum and minimum temperatures for two future times: midterm 2050 (2041–2060) and long-term 2080 (2071–2090). The performance of each GCM incorporated in LARS-WG was evaluated independently and compared to a multi-model ensemble. All of the meteorological stations that were analyzed using the MK method (except for Suzhou, Dangshan, and Mengcheng) showed a significant decreasing trend in the arithmetic mean of monthly precipitation in March. However, for the majority of the remaining months, the study indicated a non-significant decreasing trend. In contrast, the IPTA method demonstrated a significant decreasing trend in most months, highlighting its superior ability to detect hidden trends compared to the MK method. The projections showed that mean annual precipitation is likely to increase at all meteorological stations in the Huaibei Plains and Shandong Plains during two periods: 2050 (2041–2060) and 2080 (2071–2090). A maximum increase in average mean annual precipitation is projected at the highest emission scenario (ssp585) as compared to the medium (ssp245) and low emission (ssp126) scenarios, and at the long-term period 2080 (2071-2090) as compared to the mid-term period 2050 (2041-2060). The mean annual precipitation in the Shandong Plain is projected to increase by 10.4%, 14.5%, and 14.8% under the ssp126, ssp245, and ssp585 scenarios, respectively. Similarly, in the Huaibei Plain, the projected increases are 10.9%, 13.6%, and 15.1% under the ssp126, ssp245, and ssp585 scenarios, respectively. The anticipated increase in mean precipitation per decade is expected to be 2.0% (= 1.96 mm/decade) in the Huaibei Plain and 1.31% (= 0.63 mm/decade) in the Shandong Plain. Both maximum and minimum temperatures are projected to increase persistently across all meteorological stations during two time periods: 2050 (2041–2060) and 2080 (2071–2090) under three different SSPs (ssp126, ssp245, and ssp585). The long-term period 2080 (2071–2090) is projected to experience the highest increase in both maximum and minimum temperatures, surpassing the increases observed in the midterm period 2050 (2041–2060). Among the different SSPs, the greatest increase in both maximum and minimum temperature was projected under the highest forcing emission scenario, SSP 585. With a persistent increase in air temperature and precipitation patterns fluctuating under a future climate scenario in the coastal area of China, climate change can influence all aspects of life, especially water resource distribution and agricultural water management. This study provides valuable insight for water resources planners and agricultural experts in the coastal region of China, as this area is a very vulnerable area to climate change and is also the main staple food-producing area in China.

show abstract

“…In this method, as the existing data can be divided into any number of clusters, unlike rank‐based statistical tests, a monotonous trend is not the only type that can be detected. This feature allows the method to offer a more flexible approach, and therefore, it has been used in various studies and compared with classical approaches (Dabanlı et al, 2016; Esit, 2023; Gumus et al, 2023; Phuong et al, 2020; Touhedi et al, 2023). Güçlü (2020) suggested the improved visualization of the ITA (IV‐ITA) approach to determine trend conditions.…”

Section: Introductionmentioning

confidence: 99%

Spatiotemporal variability and trends of droughts in the Mediterranean coastal region of Türkiye

Kesgin,

Yaldız,

Güçlü

2024

Intl Journal of Climatology

View full text Add to dashboard Cite

Drought, defined as the period when water availability considerably remains below normal levels for a certain time period, has devastating social, economic and environmental impacts. It is significant to closely monitor the temporal and spatial variability of drought in order to implement policies to mitigate the drought risk and ensure the sustainable management of water resources. In this study, three different drought indices, standard precipitation index (SPI), standardized precipitation‐evapotranspiration index (SPEI) and reconnaissance drought index (RDI), are calculated for 3‐, 6‐ and 12‐month time scales from the precipitation and temperature data measured in 11 meteorological observation stations within the Mediterranean coastal region of Türkiye during 1972–2020. Initially, two absolute homogeneity tests were applied, namely the standard normal homogeneity test (SNHT) and the Pettitt test, to detect abrupt changes in drought index time series. Then, trend analysis was carried out with the innovative trend analysis (ITA) and improved visualization of ITA (IV‐ITA) methods to determine the temporal variation of the drought in the region. A graphical representation is developed for the drought classifications based on IV‐ITA. As a result of the SNHT and Pettitt test, significant change points were found at a 5% significance level in 91.92% and 85.86% of all indices, respectively. In both tests, breaks were detected at similar times (between 1972 and 1974) at Marmaris station, while at Alanya station, changes were found between 1972 and 1973 for the SNHT and in 2008 for the Pettitt test. The trend differences between extreme conditions (extremely dry and wet) decreased with an increase in time scale, distinctively. The ITA trends were almost identical for 3‐month time scales, and they started to differ with time scale increases. Particularly, the presence of negative differences in data points contributes to the augmentation of drought periods, despite a few instances of extreme cases and minor fluctuations that can also be observed in IV‐ITA. The findings obtained from the study are expected to provide valuable information about the recent shifts in drought in the Mediterranean basin.

show abstract

Investigation of innovative trend approaches (ITA with significance test and IPTA) comparing to the classical trend method of monthly and annual hydrometeorological variables: a case study of Ankara region, Turkey

Cited by 27 publications

References 51 publications

Spatio‐temporal analysis of trends in annual maximum rainfall in the North‐West of Algeria: Comparative analysis of recent and old non‐parametric methods

Spatio‐temporal analysis of trends in annual maximum rainfall in the North‐West of Algeria: Comparative analysis of recent and old non‐parametric methods

Trend Analysis and Projection of Climate Variables Using the LARS-WG Model in Coastal Areas of China

Spatiotemporal variability and trends of droughts in the Mediterranean coastal region of Türkiye

Contact Info

Product

Resources

About