Monitoring and Analysis of Changes in the Depth and Surface Area Snow of the Mountains in Iran Using Remote Sensing Data

Safarianzengir, Vahid; Mahmoudi, Leila; Meresht, Roghayeh Maleki; Abad, Behrooz; Rajabi, Kazem; Kianian, Mohammad Kia

doi:10.1007/s12524-020-01145-0

Cited by 5 publications

(5 citation statements)

References 37 publications

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“…Previous snow cover research focused mainly on data from ground meteorological stations, whose observations were relatively limited (Yang et al, 2019). However, given the recent development of remote sensing technology, which has become highly effective for snow research, investigations of snow cover have gradually grown from the point scale to the regional and even global scales, with the time series of data having now extended to several decades (Jin et al, 2019;Li et al, 2019;Li et al, 2020;Xiao et al, 2020;Zengir et al, 2020). For instance, Jin et al (2019) extracted snow cover area (SCA) from a remote sensing dataset as an important input variable for the snowmelt runoff model, thereby compensating for the lack of observation data to a certain extent.…”

Section: Introductionmentioning

confidence: 99%

“…For instance, Jin et al (2019) extracted snow cover area (SCA) from a remote sensing dataset as an important input variable for the snowmelt runoff model, thereby compensating for the lack of observation data to a certain extent. Zengir et al (2020) considered the importance of the role that snowfall plays in supplying water resources, and monitored and analyzed the changes in snow depth (SD) and SCA and their relationships with groundwater in a mountainous area of Iran using remote sensing data; they found that the reduction in the groundwater aquifer is closely related to the decreasing levels of snowfall in the study area. Previous researches have also measured and analyzed remote sensing data to study snow phenology indicators such as SCA, snow cover days (SCDs) and SD in the Tianshan Mountains in Central Asia and in the Northern Hemisphere (Li et al, 2019;Xiao et al, 2020).…”

Section: Introductionmentioning

confidence: 99%

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Monitoring and analysis of snow cover change in an alpine mountainous area in the Tianshan Mountains, China

et al. 2022

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Estimating the snow cover change in alpine mountainous areas (in which meteorological stations are typically lacking) is crucial for managing local water resources and constitutes the first step in evaluating the contribution of snowmelt to runoff and the water cycle. In this paper, taking the Jingou River Basin on the northern slope of the Tianshan Mountains, China as an example, we combined a new moderate-resolution imaging spectroradiometer (MODIS) snow cover extent product over China spanning from 2000 to 2020 with digital elevation model (DEM) data to study the change in snow cover and the hydrological response of runoff to snow cover change in the Jingou River Basin under the background of climate change through trend analysis, sensitivity analysis and other methods. The results indicate that from 2000 to 2020, the annual average temperature and annual precipitation in the study area increased and snow cover fraction (SCF) showed obvious signs of periodicity. Furthermore, there were significant regional differences in the spatial distribution of snow cover days (SCDs), which were numerous in the south of the basin and sparse in the central of the basin. Factors affecting the change in snow cover mainly included temperature, precipitation, elevation, slope and aspect. Compared to precipitation, temperature had a greater impact on SCF. The annual variation in SCF was limited above the elevation of 4200 m, but it fluctuated greatly below the elevation of 4200 m. These results can be used to establish prediction models of snowmelt and runoff for alpine mountainous areas with limited hydrological data, which can provide a scientific basis for the management and protection of water resources in alpine mountainous areas.

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Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Monitoring and analysis of snow cover change in an alpine mountainous area in the Tianshan Mountains, China

et al. 2022

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“…For example, snow contributes more than rainfall to groundwater recharge 31 , 32 . The study conducted by Safarianzengir et al 33 highlighted a strong correlation between the decline in groundwater and a decreasing trend in snowfall in Iran (2000–2019). Recent observations also reported a decline in snowfall in different parts of Iran during the last decades 34 – 36 .…”

Section: Resultsmentioning

confidence: 99%

Decline in Iran’s groundwater recharge

Noori,

Maghrebi,

Jessen

et al. 2023

Nat Commun

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Groundwater recharge feeds aquifers supplying fresh-water to a population over 80 million in Iran—a global hotspot for groundwater depletion. Using an extended database comprising abstractions from over one million groundwater wells, springs, and qanats, from 2002 to 2017, here we show a significant decline of around −3.8 mm/yr in the nationwide groundwater recharge. This decline is primarily attributed to unsustainable water and environmental resources management, exacerbated by decadal changes in climatic conditions. However, it is important to note that the former’s contribution outweighs the latter. Our results show the average annual amount of nationwide groundwater recharge (i.e., ~40 mm/yr) is more than the reported average annual runoff in Iran (i.e., ~32 mm/yr), suggesting the surface water is the main contributor to groundwater recharge. Such a decline in groundwater recharge could further exacerbate the already dire aquifer depletion situation in Iran, with devastating consequences for the country’s natural environment and socio-economic development.

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“…Previous studies on historical snow resource patterns in Iran have primarily focused on spatiotemporal changes in snow cover area and duration estimated by remote sensing data sets (e.g., Ghasemifar et al., 2019; Keikhosravi Kiany et al., 2017; Safarianzengir et al., 2020). However, to the best of our knowledge, the present study is the primary research that applied daily snow depth measurements to investigate long‐term (1982–2019) variability and trends in snowpack dynamics across Iranian mountain ranges.…”

Section: Discussionmentioning

confidence: 99%

Long‐Term Variability and Trends in Snow Depth and Cover Days Throughout Iranian Mountain Ranges

Sadeqi,

Irannezhad,

Bahmani

et al. 2024

Water Resources Research

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In Iran, the mountain snow cover generally feeds major rivers and thereby largely provides water resources required for improving human lives and protecting nature. Hence, understanding historical variability and trends in mountainous snowpack water resources in Iran in response to global warming and climate change can play a critical role in the sustainable development of this country. Accordingly, this study investigated long‐term (1982–2018) snowpack climatology at 13 hydrometeorological measurement stations scattered throughout the Iranian mountain ranges, with a focus on Elburz, Azerbaijan, Zagros, and Khorasan mountainous regions. The non‐parametric Mann‐Kendall test was used to detect statistically significant (p < 0.05) trends, the Pettitt test to identify possible abrupt shift years, the Pearson's correlation coefficient to measure relationships among different time series, and the partial correlation to determine the most important climate factor influencing snowpack dynamics The annual snow depth (maximum snow depth) significantly declined throughout Iranian mountain ranges during 1982–2018, with an average rate of 1.0 (3.4) cm decade−1. The annual snow cover days (SCDs) also showed significant decreasing trends, ranging from 3 to 15 days decade−1 during 1982–2018, in 69% of the stations studied. Such considerable reductions in snow depth and cover days were mainly related to the compound effects of substantial increases in temperature, sunshine, and wind speed as well as decreases in precipitation and cloudiness during the SCDs across the Iranian mountain ranges. However, precipitation was the most influential climate factor controlling snow resources throughout both the Elburz and Zagros mountains in Iran.

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Monitoring and Analysis of Changes in the Depth and Surface Area Snow of the Mountains in Iran Using Remote Sensing Data

Cited by 5 publications

References 37 publications

Monitoring and analysis of snow cover change in an alpine mountainous area in the Tianshan Mountains, China

Monitoring and analysis of snow cover change in an alpine mountainous area in the Tianshan Mountains, China

Decline in Iran’s groundwater recharge

Long‐Term Variability and Trends in Snow Depth and Cover Days Throughout Iranian Mountain Ranges

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