Large-scale climate variability controls on climate, vegetation coverage, lake and groundwater storage in the Lake Urmia watershed using SSA and wavelet analysis

Rezaei, Abolfazl; Gurdak, Jason J.

doi:10.1016/j.scitotenv.2020.138273

Cited by 75 publications

(41 citation statements)

References 61 publications

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“…It is likely apparent that the results from each index well correspond to its dominant power spectrums highlighted in Fig. 3 with those results obtained by Rezaei and Gurdak (2020) for the aquifers in the Lake Urmia watershed.…”

Section: Wavelet Coherence (Wtc)supporting

confidence: 76%

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Large-scale Climate Variability Footprint in Water Levels of Alluvial Aquifers Across Iran

Rezaei

2021

Preprint

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The ability to predict future variability of groundwater resources in time and space is of critical importance in society’s adaptation to climate variability and change. Periodic control of large scale ocean-atmospheric circulations on groundwater levels proposes a potentially effective source of longer term forecasting capability. In this study, as a first national-scale assessment, we use the continues wavelet transform, global power spectrum, and wavelet coherence analyses to quantify the controls of the Atlantic Multidecadal Oscillation (AMO), Pacific Decadal Oscillation (PDO), North Atlantic Oscillation (NAO), and El Niño Southern Oscillation (ENSO) over the representative groundwater levels of the 24 principal aquifers, scattered across different 14 climate zones of Iran. The results demonstrate that aquifer storage variations are partially controlled by annual to interdecadal climate variability and are not solely a function of pumping variations. Moreover, teleconnections are observed to be both frequency and time specific. The significant coherence patterns between the climate indices and groundwater levels are observed at five frequency bands of the annual (~1-yr), interannual (2-4- and 4-6-yr), decadal (8-12-yr), and interdecadal (14-18yr), consistent with the dominant modes of climate indices. AMO’s strong footprint is observed at interdecadal and annual modes of groundwater levels while PDO’s highest imprint is seen in interannual, decadal, and interdecadal modes. The highest controlling influence of ENSO is observed across the decadal and interannual modes whereas the NAO’s footprint is marked at annual and interdecadal frequency bands. Further, it is observed that the groundwater variability being higher modulated by a combination of large-scale atmospheric circulations rather than each individual index. The decadal and interdecadal oscillation modes constitute the dominant modes in Iranian aquifers. Findings also mark the unsaturated zone contribution in damping and lagging of the climate variability modes, particularly for the higher frequency indices of ENSO and NAO where the groundwater variability is observed to be more correlated with lower frequent climate circulations such as PDO and AMO, rather than ENSO and NAO. Finally, it is found that the data length can significantly affect the teleconnections if the time series are not contemporaneous and only one value of coherence/correlation is computed for each particular series instead of separate computations for different frequency bands and different time spans.

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Section: Wavelet Coherence (Wtc)supporting

confidence: 76%

“…Here, we use the monthly time series from AMO, PDO, NAO, and Southern Oscillation Index (SOI) indices (Fig. S2) along with monthly representative groundwater levels from 24 aquifers listed in (Hanson et al, 2004;Rezaei and Gurdak, 2020).…”

Section: Methodsmentioning

confidence: 99%

Large-scale Climate Variability Footprint in Water Levels of Alluvial Aquifers Across Iran

Rezaei

2021

Preprint

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“…The wavelet analysis method has the characteristics of multi-resolution analysis in the time-frequency domain. Both can characterize multi-scale detailed analysis on the signal to obtain the change of each frequency with time and the relationship between different frequencies, so it is widely used in analyzing hydrological time series [36][37][38].…”

Section: Wavelet Analysismentioning

confidence: 99%

Quantitative Detection and Attribution of Groundwater Level Variations in the Amu Darya Delta

Pan

Wang

et al. 2020

Water

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In the past few decades, the shrinkage of the Aral Sea is one of the biggest ecological catastrophes caused by human activity. To quantify the joint impact of both human activities and climate change on groundwater, the spatiotemporal groundwater dynamic characteristics in the Amu Darya Delta of the Aral Sea from 1999 to 2017 were analyzed, using the groundwater level, climate conditions, remote sensing data, and irrigation information. Statistics analysis was adopted to analyze the trend of groundwater variation, including intensity, periodicity, spatial structure, while the Pearson correlation analysis and principal component analysis (PCA) were used to quantify the impact of climate change and human activities on the variabilities of the groundwater level. Results reveal that the local groundwater dynamic has varied considerably. From 1999 to 2002, the groundwater level dropped from −189 cm to −350 cm. Until 2017, the groundwater level rose back to −211 cm with fluctuation. Seasonally, the fluctuation period of groundwater level and irrigation water was similar, both were about 18 months. Spatially, the groundwater level kept stable within the irrigation area and bare land but fluctuated drastically around the irrigation area. The Pearson correlation analysis reveals that the dynamic of the groundwater level is closely related to irrigation activity within the irrigation area (Nukus: −0.583), while for the place adjacent to the Aral Sea, the groundwater level is closely related to the Large Aral Sea water level (Muynak: 0.355). The results of PCA showed that the cumulative contribution rate of the first three components exceeds 85%. The study reveals that human activities have a great impact on groundwater, effective management, and the development of water resources in arid areas is an essential prerequisite for ecological protection.

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“…In the Azarshar and Ajabshir planes the average annual temperatures are 13°C and 12°C and the average annual precipitations are 221.2 and 300 mm, respectively (Docheshmeh Gorgij & Asghari Moghaddam 2017;Gorgij et al 2017;Moghaddam et al 2018). The mean water table depths of the aquifers are in the range of 0.7-29.8 m in the Azarshar plane and 0.5-37.7 m in the Ajabshir plane (Rezaei & Gurdak 2020). In recent years, the groundwater aquifers in the study area have been faced with over-extraction due to overpopulation, industrialization, and overuse of fertilizers.…”

Section: Characteristics Of the Study Areamentioning

confidence: 99%

Spatial and temporal assessment of groundwater quality and hydrogeochemical processes in Urmia Lake Basin, Iran

et al. 2021

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The evaluation of groundwater quality and geochemistry have an important role in the management of water resources in arid and semi-arid regions. In the present study, the spatio-temporal assessment of groundwater quality and hydrogeochemical processes, as well as, statistical analyses in the Azarshahr and Ajabshir planes located in the Urmia Lake basin were investigated. The results revealed that within six years (from 2014 to 2019), the value of total hardness was higher than the permissible level and the quality of groundwater for drinking was very hard and fresh in both planes. In 2019, 84 and 67% of the samples fell within the range of good to poor groundwater quality in the Azarshahr and Ajabshir planes, respectively. The temporal assessment with the help of water quality index values for both planes revealed a good groundwater quality for the Azarshahr plane and a good to poor groundwater quality for the Ajabshir plane. However, deterioration of water quality was observed in both planes from 2014 to 2019. The level of water quality for irrigation was better in the Azarshahr plane than in the Ajabshir plane, due to the presence of fewer salty sites. In addition, Ca–Mg–HCO3 and rock dominance were identified as hydrochemical facies and controlling factor in the groundwater of both planes, respectively. Multivariate statistical analyses indicated both natural and anthropogenic sources (such as weathering, fertilizers, and wastewater) for hydrochemical parameters. It was suggested to develop a comprehensive regulation to control the entry of pollutants into the groundwater of the study area.

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Large-scale climate variability controls on climate, vegetation coverage, lake and groundwater storage in the Lake Urmia watershed using SSA and wavelet analysis

Cited by 75 publications

References 61 publications

Large-scale Climate Variability Footprint in Water Levels of Alluvial Aquifers Across Iran

Large-scale Climate Variability Footprint in Water Levels of Alluvial Aquifers Across Iran

Quantitative Detection and Attribution of Groundwater Level Variations in the Amu Darya Delta

Spatial and temporal assessment of groundwater quality and hydrogeochemical processes in Urmia Lake Basin, Iran

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