Topographic and climatic influence on seasonal snow cover: Implications for the hydrology of ungauged Himalayan basins, India

Misra, Anshuman; Kumar, Amit; Bhambri, Rakesh; Haritashya, U. K.; Verma, Akshaya; Dobhal, D. P.; Gupta, Anil K.; Gupta, Gaurav; Upadhyay, Rajeev

doi:10.1016/j.jhydrol.2020.124716

Cited by 38 publications

(12 citation statements)

References 70 publications

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“…In this zone, the below-freezing temperature remains until April, and the snow melt period becomes shorter. Therefore, zone 4 has weaker snow cover variations (S = 0.03%/ year, tau's = 0.97) (Figure 6A) (Tahir et al, 2015;Misra et al, 2020). Zone 4 of the elevation class covered 27.4% of SCA (Figure 5A).…”

Section: Topographic Parameter and Snow Cover Areamentioning

confidence: 99%

“…Particularly, in this study, we observed that zone 2 and zone 3 have an increasing trend of temperature and decreasing trend of rainfall, which is the reason for decreasing trend of SCA (Supplementary Table S4). Annual SCA at mid-altitude zones decreases but insignificantly which is closely related to the elevation-dependent temperature change as compared to precipitation (Misra et al, 2020;Shen et al, 2021) (Supplementary Table S4).…”

Section: Topographic Parameter and Snow Cover Areamentioning

confidence: 99%

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Trend of snow cover under the influence of climate change using Google Earth Engine platform: A case study of Astore (Western Himalayas) and Shigar (Karakoram region)

Moazzam

Rahman²,

Lee³

et al. 2022

Front. Environ. Sci.

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Freshwater resources present in the Upper Indus Basin (UIB) supply water to Pakistan’s irrigation. Half of the annual water discharge in the UIB is contributed from the glacier and snow-fed basins in the Hindu Kush, Karakoram, and Himalaya (HKH) region, and it is currently under the threat of climate change. Therefore, it is very necessary to study and monitor the spatiotemporal changes in the snow cover area (SCA) and its response to climate variables to efficiently manage water reservoirs. Thus, keeping this problem in mind, we conducted this study using the Google Earth Engine Application Programming Interface (GEE API) for Astore and Shigar. We used mean annual Landsat data between 1991 and 2021 to derive the SCA using the normalized difference snow index (NDSI). ASTER GDEM data was used to extract the elevation and analyze the distribution of SCA on different elevation zones. Eventually, we used the climate research unit (CRU) data (rainfall and temperature) to analyze them with SCA. The results revealed that SCA in Astore and Shigar has an increasing trend with a rate of 11.16 km2/year and 4.27 km2/year, respectively. Mean annual precipitation and temperature also confirmed the increasing trend of SCA because mean annual precipitation is increasing and temperature is decreasing in both regions. SCA and elevation analysis revealed that SCA is decreasing on foothills while increasing at the valley top. This is because temperature is increasing and precipitation is decreasing from zone 1 to zone 3 and vice versa for zone 4. It is found that Astore and Shigar in UIB have an increasing trend of SCA and are not affected by global warming. Therefore, it is necessary to conduct studies on large scale to efficiently evaluate the impact of climate change on SCA.

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Section: Topographic Parameter and Snow Cover Areamentioning

confidence: 99%

Section: Topographic Parameter and Snow Cover Areamentioning

confidence: 99%

Trend of snow cover under the influence of climate change using Google Earth Engine platform: A case study of Astore (Western Himalayas) and Shigar (Karakoram region)

Moazzam

Rahman²,

Lee³

et al. 2022

Front. Environ. Sci.

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“…According to previous studies (Xu et al ., 2017; Wang et al ., 2018; Misra et al ., 2020; You et al ., 2020), T s and P s are dominating driving factors of snow anomalies in spring. To explore the response of SSD to climate change in a given month (m) in spring, the month‐averaged daily snow depth ( S m ), surface air temperature ( T m ), and precipitation ( P m ) were analysed.…”

Section: Methodsmentioning

confidence: 99%

“…As inferred by previous studies (Xu et al ., 2017; Misra et al ., 2020; You et al ., 2020), T s and P s are controlled by different climate mechanisms and vary according to elevation and season across the TP. Therefore, the relationship between SSD and climate variables is complicated by the changes in P s regimes being coupled with T s variations under a varied range of topographical conditions.…”

Section: Observed Climate Change and Spring Snow Depth Decline Across...mentioning

confidence: 99%

Spring snow depth changes and feedback to surface air temperature across the Tibetan plateau from 1961 to 2013

Chen

Yang

2021

Intl Journal of Climatology

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Spring snow depth (SSD) in the Tibetan Plateau (TP) plays an essential role in snow water estimation, vegetation growth, and climate projections for Southwest China and the surrounding Asian countries. Previous studies have reported a decline in SSD that is associated with increasing surface air temperature (Ts) across the TP over the past decades. However, only a few studies have explored the potential feedback of SSD to Ts, which has hindered the elucidation of the vulnerability of snow cover in the TP against the backdrop of rapid climate change. Based on data from 69 meteorological stations in the central and eastern parts of the TP, this study analyses changes in SSD and its feedback to Ts from 1961 to 2013. Overall, a slightly negative trend in SSD was observed from 1961 to 2013, during which two contrasting trends were detected using a piecewise regression approach: an initial increase from 1961 to 1981 (0.12 cm decades−1, p < .01) followed by a decrease from 1982 to 2013 (−0.36 cm decades−1, p < .01). Sensitivity analysis revealed that the SSD decline was systematically correlated with a positive Ts anomaly, with sensitivities of −0.050 cm °C−1 (p < .01) and −0.069 cm °C−1 (p < .01) for 1961–2013 and 1982–2013, respectively. However, following the accelerated SSD decline during 1982–2013, its potential feedback to Ts was attenuated, with averaged feedback values from −1.328°C cm−1 during 1961–2013 to −0.936°C cm−1 during 1982–2013 in latitudes below 3,500 m, distributed in the Qaidam and Yellow River basins, and the upper reaches of the Yangtze River basin. The decrease in feedback from SSD to Ts may lead to changes in the mechanism controlling Ts dynamics across the TP, which should be considered in climate change projections in future studies.

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“…The elevation defined as height elevated above a reference point, which usually means sea level. The elevation is an important parameter that provides an essential role in managing water resources [21][22][23][24]. For example, in groundwater recharge, the regions with lower elevation are considered a good recharge zone and the areas with higher elevation considered a less potential recharge zone [25].…”

Section: Elevationmentioning

confidence: 99%

Role of Integrated Approaches in Water Resources Management: Antofagasta Region, Chile

et al. 2021

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Water is essential for the survival of all living beings and plays a significant role in the growth of any country′s economy. At present, water depletion and pollution are a serious challenge due to anthropogenic, geogenic and climate change activities worldwide, including in Chile. The Antofagasta region is located in northern Chile and is the heart of its mining industry, playing a significant role in the country′s economy. The Antofagasta region′s main challenge is water shortage and contamination. Due to it, the region′s local population is facing major difficulties in obtaining the necessary water for domestic, industrial, irrigation, and other uses. Therefore, a water resources management plan is essential for the region to maintain a sustainable environment. Considering the above points, significant parameters, such as slope, aspect, elevation, hillshade, drainage, drainage density and river basin—maps of the Antofagasta region prepared using the digital elevation model (DEM) data in geographic information system (GIS) environment. Besides, a pollution risk level assessment of the study area′s cities/villages done using GIS application. The important created maps and the identification of pollution risk of cities/villages of the present study could provide significant information to policymakers and help them make a suitable water management plan for the area.

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Topographic and climatic influence on seasonal snow cover: Implications for the hydrology of ungauged Himalayan basins, India

Cited by 38 publications

References 70 publications

Trend of snow cover under the influence of climate change using Google Earth Engine platform: A case study of Astore (Western Himalayas) and Shigar (Karakoram region)

Trend of snow cover under the influence of climate change using Google Earth Engine platform: A case study of Astore (Western Himalayas) and Shigar (Karakoram region)

Spring snow depth changes and feedback to surface air temperature across the Tibetan plateau from 1961 to 2013

Role of Integrated Approaches in Water Resources Management: Antofagasta Region, Chile

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