Changeability evaluation of hydro-climate variables in Western Caspian Sea region, Iran

Kazemzadeh, Majid; Malekian, Arash

doi:10.1007/s12665-018-7305-x

Cited by 14 publications

(12 citation statements)

References 29 publications

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“…The Pettit test is a nonparametric statistical test that is widely used to identify monotonic jump points in a hydro-climatic data time series [17,[45][46][47]. The null hypothesis (H 0 ) is that there is no abrupt change in the given time series.…”

Section: Pettit Testmentioning

confidence: 99%

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Uncovering the Depletion Patterns of Inland Water Bodies via Remote Sensing, Data Mining, and Statistical Analysis

Zolghadr‐Asli

Jahromi

Wan

et al. 2023

Water

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Addressing the issue of shrinking saline lakes around the globe has turned into one of the most pressing issues for sustainable water resource management. While it has been established that natural climate variability, human interference, climate change, or a combination of these factors can lead to the depletion of saline lakes, it is crucial to investigate each case and diagnose the potential causes of this devastating phenomenon. On that note, this study aims to promote a comprehensive analytical framework that can reveal any significant depletion patterns in lakes while analyzing the potential reasons behind these observed changes. The methodology used in this study is based on statistical analysis, data mining techniques, and remote sensing-based datasets. To achieve the objective of this study, Maharlou Lake has been selected to demonstrate the application of the proposed framework. The results revealed two types of depletion patterns in the lake’s surface area: a sharp breaking point in 2007/2008 and a gradual negative trend, which was more pronounced in dry seasons and less prominent in wet seasons. Furthermore, the analysis of hydro-climatic variables has indicated the presence of abrupt and gradual changes in these variables’ time series, which could be interpreted as a signal that climate change and anthropogenic drought are changing the basin’s status quo. Lastly, analyzing the statistically significant correlation between hydro-climatic variables and the lake’s surface area showed the potential connection between the observed changing patterns. The results obtained from data mining models suggest that Maharlou Lake has undergone a morphological transformation and is currently adopting these new conditions. If preventive measures are not taken to revive Maharlou Lake, the tipping point might have been reached, and reviving the lake could be improbable, if not impossible.

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Section: Pettit Testmentioning

confidence: 99%

“…Sen's slope estimator is a nonparametric procedure that can be used to estimate the slope of the linear trend (i.e., the linear rate of change per unit of time). Sen's slope estimator has been verified for its applicability to hydro-climatic time series data [45,51,52]. Moreover, the rate of change can be computed [30,45]:…”

Section: Sen's Slope Estimatormentioning

confidence: 99%

Uncovering the Depletion Patterns of Inland Water Bodies via Remote Sensing, Data Mining, and Statistical Analysis

Zolghadr‐Asli

Jahromi

Wan

et al. 2023

Water

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“…Several studies on temperature trend analysis for Iran have been conducted (Ghasemi and Khalili, 2006;Tabari and Talaee, 2011;Saboohi et al, 2012;Kousari et al, 2013;Ghasemi, 2015;Balling et al, 2016;Soltani et al, 2016;Kazemzadeh and Malekian, 2018;Pour et al, 2019;Doulabian et al, 2021). Most of these studies are concerned with detecting or estimating linear trends (negative or positive) using ordinary least-squares (OLS) linear regression models.…”

Section: Introductionmentioning

confidence: 99%

Forty Years of Air Temperature Change over Iran Reveals Linear and Nonlinear Warming

et al. 2022

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Spatiotemporal analysis of long-term changes in air temperature is of prime importance for climate change research and the development of effective mitigation and adaptation strategies. Although there are considerable studies on air temperature change across the globe, most of them have been on linear trends and time series analysis of nonlinear trends have not received enough attention. Here, spatiotemporal patterns of monthly and annual mean (Tmean), maximum (Tmax), and minimum (Tmin) air temperature at 47 synoptic stations across climate zones in Iran for a 40-yr period (1978–2017) are analyzed. A polynomial fitting scheme (Polytrend) is used to both monthly and annual air temperature data to detect trends and classify them into linear and nonlinear (quadratic and cubic) categories. The significant (non-significant) trends in Tmean, Tmax, and Tmin across all climate zones are 41.1% (58.9%), 34.1% (65.9%), and 46% (54%), respectively. The highest magnitude of increasing trends is observed in the annual Tmin (0.47°C decade−1) and the lowest magnitude is for the annual Tmax (0.4°C decade−1). Across the country, increasing trends $$(\bar x = 37.2\% )$$ ( x ¯ = 37.2 % ) have higher spatial coverage than the decreasing trends $$(\bar x = 3.2\% )$$ ( x ¯ = 3.2 % ) . Warming trends in Tmean (65.3%) and Tmin (73.1%) are mainly observed in humid climate zone while warming trends in Tmax are in semi-arid (43.9%) and arid (34.1%) climates. Linear change with a positive trend is predominant in all Tmean (56.7%), Tmax (67.8%), and Tmin (71.2%) and for both monthly and annual data. Further, the linear trends have the highest warming rate in annual Tmin (0.83°C decade−1) and Tmean (0.46°C decade−1) whereas the nonlinear trends have the highest warming rate in annual Tmax (0.52°C decade−1). The linear trend type is predominant across the country especially in humid climate zones whereas the nonlinear trends (quadratic and cubic) are mainly observed in the arid climate zones. This study highlights nonlinear changes and spatiotemporal trends in air temperature in Iran and contributes to a growing body of climate change literature that is necessary for the development of effective mitigation and adaptation strategies in the Middle East.

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“…Hajani and Rahman (2018) investigated the characteristics of precipitation in Australia from 1945 to 2014, a 70 year-length. Kazemzadeh and Malekian (2018) covered hydroclimatic changes in Iran for 30 years, from 1981 to 2010. Moreover, recent studies in Canada (TAN et al, 2017), Germany (BORMANN; PINTER, 2017), India (PIYOOSH; GHOSH, 2017) and United States (TEEGAVARAPU; NAYAK, 2017) can also be listed.…”

Section: Introductionmentioning

confidence: 99%

Changes in precipitation rates over the last 70 years in Eastern Paraná State, Brazil

Juliani

Okawa

Mine

2021

CeN

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Temporal hydrometeorological series may present variations over time. The awareness of these characteristics is important to improve the monitoring of changes that these series may suffer along time. In this regard, the present paper aims to identify the existence of precipitation trends for the east portion of Paraná state, in Brazil, and also investigate the changes in the observed rates over the last 70 years. The statistical tests of Mann-Kendall and Pettitt, and also the Theil-Sen estimator, are applied for series of precipitation from 13 pluviometric stations of eastern Paraná state, Brazil, with 70 years of data records. By the results it was identified long-term linear positive trend for 11 of the precipitation series and also detected medium-term patterns in precipitation over 10 stations, characterizing the Joseph effect. These series have presented a behavior with higher rates in the most recent years in comparison from the first years of the historical data, sectioning the complete series into two shorter stationary periods, and presenting an abrupt change point.

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Changeability evaluation of hydro-climate variables in Western Caspian Sea region, Iran

Cited by 14 publications

References 29 publications

Uncovering the Depletion Patterns of Inland Water Bodies via Remote Sensing, Data Mining, and Statistical Analysis

Uncovering the Depletion Patterns of Inland Water Bodies via Remote Sensing, Data Mining, and Statistical Analysis

Forty Years of Air Temperature Change over Iran Reveals Linear and Nonlinear Warming

Changes in precipitation rates over the last 70 years in Eastern Paraná State, Brazil

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