Exploring the effects of climatic variables on monthly precipitation variation using a continuous wavelet-based multiscale entropy approach

Roushangar, Kiyoumars; Alizadeh, Farhad; Adamowski, Jan

doi:10.1016/j.envres.2018.04.017

Cited by 44 publications

(16 citation statements)

References 52 publications

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“…The results of the local Moran's index and hotspot analysis revealed that the precipitation along the Caspian Sea's coast, western and southwestern parts of Iran had a positive spatial auto-correlation, while the precipitation variation in central Iran and along the southern coastline of the country showed a negative spatial autocorrelation (Ghalhari et al 2016). Exploring the effects of teleconnection climatic indices on monthly precipitation in Iran revealed that all climatic features except NAO index influenced precipitation in Iran during 1960-2010 (Roushangar et al 2018).…”

Section: Current Climate Change and Warming Facts In Iranmentioning

confidence: 99%

“…Spatial and temporal trend of precipitation has been widely studied in Iran by several researchers. The literature review revealed that two high mountain ranges of Zagros and Alborz in west and north, respectively, strikingly affect the temporal and spatial patterns of rainfall and temperature (Dinpashoh et al 2004;Modarres and Sarhadi 2009;Tabari and Talaee 2011;Raziei et al 2012;Soltani et al 2012;Somee et al 2012;Dinpashoh et al 2014;Darand and Mansouri Daneshvar 2014;Darand et al 2015;Zarenistanak et al 2015;Ghalhari et al 2016;Roushangar et al 2018).…”

Section: Current Climate Change and Warming Facts In Iranmentioning

confidence: 99%

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An overview of climate change in Iran: facts and statistics

Daneshvar¹,

2019

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Background: The climate change fact is intensive among the Middle East countries and especially Iran. Among the Middle East countries, Iran will experience an increase of 2.6 °C in mean temperatures and a 35% decline in precipitation in the next decades. In vice versa, Iran by total greenhouse gas (GHG) emissions nearly to 616,741 million tons of CO 2 is the first responsible country to climate change in the Middle East, and seventh in the world. The high-level contribution of Iran to emissions of GHG depends on a significant production of oil, gas, and rapid urbanization. The present study aimed to reveal an overview of climate change facts and statistics in Iran. Results:In this manuscript, the evidential facts on climate change were investigated in global, regional, and national scales. For this purpose, the main increasing annual temperature and GHG emissions were considered. Besides, the variations of meteorological characteristics such as surface temperature, total precipitation, and upward longwave radiation (ULR) were reviewed in Iran indicating an anomalous decrease in precipitation events and anomalous increase in ULR and temperature characteristics confirming the global warming/climate change effects. Afterward, the legislative agreements on climate change concerning international adoptions and conventions were reviewed from Rio 1992 to NY 2016. Conclusions:The results showed that further research and development should be considered the novel methods to explore renewable energy applications and to mitigate GHG emissions in order to overcome the increased risk of climate change effects. Technological affairs and international participants should support this target. which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. ReferencesAbolverdi J, Ferdosifar G, Khalili D, Haghighi AK, Haghighi MA (2014) Recent trends in regional air temperature and precipitation and links to global climate change in the Maharlo watershed, Southwestern Iran. Meteorol

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Section: Current Climate Change and Warming Facts In Iranmentioning

confidence: 99%

Section: Current Climate Change and Warming Facts In Iranmentioning

confidence: 99%

An overview of climate change in Iran: facts and statistics

Daneshvar¹,

2019

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“…Understanding precipitation on a regional basis is an important component of wetlands planning and management (Roushangar et al 2018). The average monthly precipitation in BG is 125.0 mm (Fig.…”

Section: Study Areamentioning

confidence: 99%

Integration of multi-sensor analysis and decision tree for evaluation of dual and quad-Pol SAR in L- and C-bands applied for marsh delineation

Simioni

Guasselli

Nascimento

et al. 2019

Environ Dev Sustain

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Marsh is a wetland type characterized by hydromorphic soils, herbaceous vegetation, aquatic and emergent vegetation; usually, the apparent water surface does not exceed 25% of the area. Multi-polarized active remote sensors with different frequencies have characteristics that make them ideal for mapping and delineating marsh areas since they provide information on canopy roughness, vegetation moisture and amount of biomass. Therefore, the main objective of this study is to develop a method based on multi-frequency radar satellites images to delineate marsh areas using decision tree classification. In order to reach this objective, we sought to answer the following questions: (1) Are L-band SAR images more efficient for marshes delineation than C-band SAR images? (2) Is multi-sensor (L and C-band) integration more accurate for marsh areas delineation than a single sensor? and (3) What are the most efficient channels for marshes delineation? Our findings showed that L-band images present greater proportion correct (PC) for marshes delineation compared to C-band images. However, the greatest PC was found using integration of Alos Palsar 1 and Sentinel 1 satellites images, reaching more than 72% of correctness. Regarding the polarization importance to Alos Palsar 1 image, HVVH presented the highest importance, with 29%, followed by VH and HV polarizations, both with 28%. For Sentinel 1 image, the most important polarization was VH, with 22%, followed by VV + VH that presented 20%. HVVH polarization was the most important in Alos and Sentinel images integration, with 35%, followed by Alos Palsar HV and VH, with 34 and 33%, respectively. Thus, we concluded that the method based on SAR multi-frequency data integration used in this study can be easily applied by other researchers interested in marsh delineation since the radar images used are freely available and can be processed and manipulated in free GIS software.

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“…During the past decades, it was observed that different AI-based models have been applied for time series analysis of rainfall data [19]. Authors in [20] used Continuous Wavelet Transform (CWT) and the multiscale entropy concept for the time series analysis of monthly rainfall data. As similar patterns are involved in the rainfall data series and due to the high potential of WT in multi-scale analysis of signals, the concept of wavelet analysis in the hydro-meteorological field can be used for better data pre-processing [21].…”

Section: Introductionmentioning

confidence: 99%

Spatiotemporal Rainfall Dynamics in Kosi Basin Using Wavelet Analysis

Towheed

Roshni

2021

Eng. Technol. Appl. Sci. Res.

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Spatial and temporal analysis of rainfall data were carried out along with wavelet analysis for seven rain gauge sites of Kosi basin, India during the time period from 1985 to 2017. Wavelet spectrum analysis and wavelet coherence analysis were performed to fully characterize the time-frequency rainfall variability of the rain gauge data in these areas. For all the selected gauge stations during the study period, the peak value of the wavelet power spectrum was identified for the 8-16 month band. The results of wavelet spectrum analysis reveal a good correlation of rainfall data in the rain gauge sites lying in the southwest of the Kosi basin. The spectrum analysis also differentiates the wet and dry periods and it was observed that in the majority of the selected sites, a dry period occurred from the year 2005 onwards. This was again confirmed with breakpoint analysis. The wavelet coherence analysis explicit is a good correlation between the rain gauges in the study area. Overall, the variability of the rainfall parameters was more vivid with the wavelet analysis and this can be extended to other climatological parameters.

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Exploring the effects of climatic variables on monthly precipitation variation using a continuous wavelet-based multiscale entropy approach

Cited by 44 publications

References 52 publications

An overview of climate change in Iran: facts and statistics

An overview of climate change in Iran: facts and statistics

Integration of multi-sensor analysis and decision tree for evaluation of dual and quad-Pol SAR in L- and C-bands applied for marsh delineation

Spatiotemporal Rainfall Dynamics in Kosi Basin Using Wavelet Analysis

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