Impacts of aspect on snow characteristics using remote sensing from 2000 to 2020 in Ajichai-Iran

Goodarzi, Mohammad Reza; Sabaghzadeh, Maryam; Mokhtari, Mohammad Hossein

doi:10.1016/j.coldregions.2022.103682

Cited by 12 publications

(3 citation statements)

References 36 publications

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“…In areas where investigating features is difficult or where data collection stations are absent, satellite imagery can be of significant assistance (Goodarzi et al 2022b). The Sentinel-2/MSI satellite imagery was used for obtaining the second part of the data in this study.…”

Section: Satellite Imagesmentioning

confidence: 99%

Assessing the impact of COVID-19 lockdowns on water quality in Anzali Wetland, Iran, using remote sensing data

Goodarzi,

Niknam,

Sabaghzadeh

et al. 2024

Water Practice &Amp; Technology

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This study investigates temporal variations of two water quality indices, namely, turbidity and chlorophyll-a (Chl-a), from 2016 to 2021 in the Anzali Wetland. For this purpose, ground-based measurements were collected at four stations from 2016 to 2019, while Sentinel-2/MSI images were utilized to predict Chl-a and turbidity from 2016 to 2021. To validate the forecasted results, remote sensing data for Chl-a and turbidity were compared to measurements. After the validation step, Chl-a and turbidity were predicted using remotely sensed data for the first and fourth peaks of the COVID-19 pandemic, which coincide with the COVID-19 lockdowns in 2020 and 2021 in Iran, respectively. The results indicate 26 and 16% decrease in Chl-a and turbidity, respectively, in the COVID-19 lockdown imposed in 2020, while it yielded to 1% decrease in turbidity and 21% increase in the Chl-a concentration in the COVID-19 lockdown applied in 2021, compared to the corresponding mean values measured from 2016 to 2019. In conclusion, the lockdown imposed in 2020, which turned out to be a much more restricted quarantine than the one applied in 2021, was found to be one of the primary reasons behind improving water quality indices of Anzali Wetland in March and April of 2020.

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Section: Satellite Imagesmentioning

confidence: 99%

Assessing the impact of COVID-19 lockdowns on water quality in Anzali Wetland, Iran, using remote sensing data

Goodarzi,

Niknam,

Sabaghzadeh

et al. 2024

Water Practice &Amp; Technology

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“…On the other hand, with the expansion of urbanization and the increase of greenhouse gas emissions, according to the studies conducted and the reports published in this field, it is expected that the world will gradually face climate change, which is known as the climate change phenomenon (Piao et al, 2010; Zahabiyoun et al, 2013). A phenomenon that will affect temperature and precipitation in the future (Bal et al, 2016; Goodarzi, Pooladi, & Niazkar, 2022; Goodarzi, Sabaghzadeh, & Mokhtari, 2022). Snow is closely related to temperature, and an increase in temperature causes a decrease in snowfall or a faster melting of snow (Goodarzi, Pooladi, & Niazkar, 2022; Goodarzi, Sabaghzadeh, & Mokhtari, 2022).…”

Section: Introductionmentioning

confidence: 99%

“…A phenomenon that will affect temperature and precipitation in the future (Bal et al, 2016; Goodarzi, Pooladi, & Niazkar, 2022; Goodarzi, Sabaghzadeh, & Mokhtari, 2022). Snow is closely related to temperature, and an increase in temperature causes a decrease in snowfall or a faster melting of snow (Goodarzi, Pooladi, & Niazkar, 2022; Goodarzi, Sabaghzadeh, & Mokhtari, 2022). Even an increase in precipitation will affect the quicker melting of snow in the region, which can cause floods in the area (Sui & Koehler, 2001).…”

Section: Introductionmentioning

confidence: 99%

Climate change impacts on snow cover area and snowmelt runoff in the Ajichai Basin‐Iran

Goodarzi

Sabaghzadeh

Fatehifar

et al. 2023

Intl Journal of Climatology

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During snowmelt in mountainous areas, runoff can play an important role in providing water to the region. This study examined the effect of climate change on runoff in Ajichai, Iran, since it affects air warming and faster melting of snow and ice. Using the sixth report provided by IPCC, the future temperature and precipitation in the years 2015–2100 were predicted using two scenarios, SSP1‐2.6 and SSP5‐8.5. According to the results, the average annual minimum and maximum temperatures would increase by 1° during this period, but precipitation would decrease by about 3%. Based on the Snow Runoff Model (SRM) model and the snow cover area (SCA) obtained from Google Earth Engine and MODIS daily images from 2013 to 2018, runoff caused by snow melting was simulated. Based on the Pearson correlation coefficient between snow cover and temperature and precipitation, the SCA was estimated in three decades: 2031–2040, 2061–2070, and 2091–2100. With reasonable accuracy, the SRM was able to simulate runoff. In the SSP1 scenario, the SCA in spring and winter will remain the same throughout all three decades, but in the SSP5 scenario, it will decrease by about 17%. In the future, the runoff will decrease by up to 6% in the winter and increase in the spring.

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Impact of Climate Change on Regional Water Availability and Demand for Agricultural Production: Application of Water Footprint Concept

Sreeshna,

Athira,

Soundharajan

2024

Water Resour Manage

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Impacts of aspect on snow characteristics using remote sensing from 2000 to 2020 in Ajichai-Iran

Cited by 12 publications

References 36 publications

Assessing the impact of COVID-19 lockdowns on water quality in Anzali Wetland, Iran, using remote sensing data

Assessing the impact of COVID-19 lockdowns on water quality in Anzali Wetland, Iran, using remote sensing data

Climate change impacts on snow cover area and snowmelt runoff in the Ajichai Basin‐Iran

Impact of Climate Change on Regional Water Availability and Demand for Agricultural Production: Application of Water Footprint Concept

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