Analysis of spatiotemporal variation in the snow cover in Western Hindukush-Himalaya region

Azizi, Abdul Haseeb; Akhtar, Fazlullah

doi:10.1080/10106049.2021.1939442

Cited by 11 publications

(4 citation statements)

References 61 publications

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“…Figure 12 shows seasonal discrepancies in CC, RMSE, BIAS, and rBIAS estimated for all SPPs (PERSIANN family products). Generally, all SPPs displayed higher variations in CC during the spring season [45][46][47][48]., as indicated in Figure 12a. The agreement between the estimates of the CCS product and reference data was comparatively poor in all seasons, excluding the winter season.…”

Section: Evaluation Of Spps At a Seasonal Scalementioning

confidence: 81%

Assessment of Multi-Satellite Precipitation Products over the Himalayan Mountains of Pakistan, South Asia

et al. 2022

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Performance assessment of satellite-based precipitation products (SPPs) is critical for their application and development. This study assessed the accuracies of four satellite-based precipitation products (PERSIANN-CDR, PERSIANN-CCS, PERSIANN-DIR, and PERSIANN) using data of in situ weather stations installed over the Himalayan Mountains of Pakistan. All SPPs were evaluated on annual, seasonal, monthly, and daily bases from 2010 to 2017, over the whole spatial domain and at point-to-pixel scale. The assessment was conducted using widely used evaluation indices (root mean square error (RMSE), correlation coefficient (CC), bias, and relative bias (rBias)) along with categorical indices (false alarm ratio (FAR), probability of detection (POD), success ratio (SR), and critical success index (CSI)). Results showed: (1) PERSIANN and PERSIANN-DIR products efficiently traced the spatio-temporal distribution of precipitation over the Himalayan Mountains. (2) On monthly scale, the estimates of all SPPs were more consistent with the reference data than on the daily scale. (3) On seasonal scale, PERSIANN and PERSIANN-DIR showed better performances than the PERSIANN-CDR and PERSIANN-CCS products. (4) All SPPs were less accurate in sensing daily light to medium intensity precipitation events. Subsequently, for future hydro-meteorological investigations in the Himalayan range, we advocate the use of monthly PERSIANN and PERSIANN-DIR products.

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Section: Evaluation Of Spps At a Seasonal Scalementioning

confidence: 81%

Assessment of Multi-Satellite Precipitation Products over the Himalayan Mountains of Pakistan, South Asia

et al. 2022

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“…Eventually, it will result in scarcity of water, landslide, drought, floods, and glacial lake outburst flood (GLOF) (Tahir et al, 2019). Snow cover research on this region usually revealed a decreasing trend of SCA; however, Tahir et al (2016), Shafiq et al (2019), and Azizi and Akhtar, 2021) reported an increasing trend of SCA due to an increasing trend of winter precipitation and decreasing trend of summer temperature. Another study also projected an increasing trend of precipitation in the HKH region during 1901-2099, while temperature indices show an inter-annual decreasing trend (Panday et al, 2015).…”

Section: Introductionmentioning

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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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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“…For example, a lack of institutional mechanisms for water sharing has plagued international relations in the Nile River (Wehling, 2021) and Kabul River Basins (Azizi and Akhtar, 2021). In the Kabul River basin, experts are still debating what kind of data should be shared and how it could be shared (Akhtar and Shah, 2020).…”

Section: Absence Of Institutional Mechanismsmentioning

confidence: 99%

Data sharing in transboundary water management

2022

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Half the world's population resides within 310 transboundary lake and river basins shared among 151 riparian nations. Approximately 60% of these basins lack cooperative frameworks to share water. The complexities of sharing water necessitate identifying approaches for managing transboundary international freshwater resources. While much has been written about the histories, theory, and mechanisms of transboundary water management, conflict, and cooperation among riparian nations, we draw attention to scholarship written about what we believe is the central tool for cooperation: data and data sharing. The 1997 United Nations' Convention on the Law of the Non-Navigational Uses of International Watercourses (UN Watercourse Convention) recognizes sharing water resources data is vital to river basin cooperation. Data sharing builds trust between riparian states, aids in mitigating conflict, and improves environmental, economic, and social outcomes. Despite calls to increase data sharing in transboundary basins to support cooperative management, few papers review the role of data sharing in transboundary water management, including how often and what types of water resources data and information are shared. We synthesize the role of data in conflict and collaboration from peer-reviewed papers on transboundary water management from the year the UN Watercourse Convention went into force, 2014 to May 2022. We outline what scholars argue are the types of water-related data to be shared, the frequency of data sharing, and the mechanisms for sharing data for facilitating cooperation in transboundary waters.

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Analysis of spatiotemporal variation in the snow cover in Western Hindukush-Himalaya region

Cited by 11 publications

References 61 publications

Assessment of Multi-Satellite Precipitation Products over the Himalayan Mountains of Pakistan, South Asia

Assessment of Multi-Satellite Precipitation Products over the Himalayan Mountains of Pakistan, South Asia

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)

Data sharing in transboundary water management

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