Spaceborne Satellite for Snow Cover and Hydrological Characteristic of the Gilgit River Basin, Hindukush–Karakoram Mountains, Pakistan

Hussain, Dostdar; Kuo, Chung Yen; Hameed, Abdul; Tseng, Kuo Hsin; Jan, Bulbul; Abbas, Nasir; Kao, Huan Chin; Lan, Wen Hau; Imani, Moslem

doi:10.3390/s19030531

Cited by 26 publications

(24 citation statements)

References 27 publications

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“…Such an increase in biomass was highly taxa-specific, favoring some species upon others, and thereby modifying community composition. This taxa-specific pattern of plant community responses to warming has been stressed in other studies performed in challenging environmental conditions such as the Arctic [11,35,61–63]. Flower production response to warming was positive in 41% of plants but had no effects on the other taxa.…”

Section: Discussionsupporting

confidence: 54%

“…The maximum temperature recorded in May goes up to 25°C in the warm year [32] while in winter it drops down below 0°C from October (3590m) [15,33,34]. Annual precipitation ranges from 200 to 900 mm per year [31,35]. Being alpine KNP harbors the following vegetation altitudinal zones: 1) The sub nival zone (> 4500 m) is made of snow and bare desert, covering about 30% of the park’s area.…”

Section: Methodsmentioning

confidence: 99%

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The Response of Culturally Important Plants to Experimental Warming and Grazing in Pakistan Himalayas

Karimi

Nawaz

Naseem

et al. 2020

Preprint

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The response of wild plants towards climate warming is taxa specific, but overgrazing could also be a determining factor for the alpine ecosystems. Overgrazing and climate warming are important drivers of alpine grassland degradation worldwide. Local indigenous peoples will be the first impacted by such degradation due to impacts on animal production and the availability of local medicinal plants. Studies on plant responses to overgrazing and climate change are rarely performed to assess threats to these biological and cultural systems. Long-term observations or manipulative experiments are promising, but rarely use strategies to evaluate the sensitivity and vulnerability of such ecosystems to climatic change. We studied the combined effects of overgrazing and increased temperatures on culturally important medicinal plants of Khunjerab National Park, Pakistan. Three experimental treatments were used (control, warming through an open-top chamber, and exclusion of grazing animals vs. the control). These experimental plots were installed at different elevations (3352-4969 m) and were monitored routinely. Grazing reduced vegetation cover & biomass by 2.3% and 6.26%, respectively, but that was not significant due to the high variability among study plots. However, warming significantly increased the overall percentage cover and biomass of all target plant species, ranging from 1±0.6% in Bistorta officinalis to 18.7 ± 4.9% in Poa alpina. Thus, warming may increase the availability of therapeutic plants for indigenous people while overgrazing would have deteriorating effects locally. This research illustrates that vegetation sensitivity to warming and overgrazing is likely to affect man– environment relationships, and traditional knowledge on a regional scale.

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Section: Discussionsupporting

confidence: 54%

Section: Methodsmentioning

confidence: 99%

The Response of Culturally Important Plants to Experimental Warming and Grazing in Pakistan Himalayas

Karimi

Nawaz

Naseem

et al. 2020

Preprint

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“…This finding could be explained by enhanced melting from the observed warming during winter [53,54]. The Khunjerab climate station in Hunza, which is located at 4710 m a.s.l., also shows an increasing trend in both annual and seasonal temperatures [21,55]. On the other hand, earlier studies have shown an increasing trend in the SCA [18,24,33].…”

Section: Discussionmentioning

confidence: 63%

“…The snow cover area was estimated using original and improved MODIS snow products. The original products were also used with the <20% clouds threshold (as commonly used by previous studies [18,21]) for comparison with the improved product. In the products with 20% cloud thresholds, the original Aqua and Terra images with a percentage cloud cover more than 20% were discarded for the comparative assessment among five different products.…”

Section: Snow Cover Area Calculationmentioning

confidence: 99%

Contemporary Snow Changes in the Karakoram Region Attributed to Improved MODIS Data between 2003 and 2018

Thapa

Sher

2020

Water

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Snowmelt significantly contributes to meltwater in most parts of High Mountain Asia. The Karakoram region is one of these densely glacierized and snow-covered regions. Several studies have reported that glaciers in the Karakoram region remained stable or experience slight mass loss. This trend has called for further investigation to understand changes in other components of the cryosphere. This study estimates the comparative snow cover area (SCA) and snowline altitude (SLA) changes between 2003 and 2018 in the Karakoram region and its subbasins, including Hunza, Shigar, and Shyok. We used three different 8-day composite snow products of the Moderate Resolution Imaging Spectroradiometer (MODIS) in this study including (1) Original Aqua (MYD10A2), (2) Original Terra (MOD10A2), and (3) Improved Terra-Aqua (MOYDGL06*) snow products from 2003 to 2018. We used Mann–Kendall and Sen Slope methods to assess trends in the SCA and SLA. Our results show that the original snow products are significantly biased when investigating seasonal and annual trends. However, discarding a cloud cover of >20% in the original products improves the results and makes them more comparable to our improved snow product. The original products (without cloud removal) overestimate the SCA during summer and underestimate the SCA during winter and year-round throughout the Karakoram region. The bias in the mean annual SCA between improved and Aqua and Terra cloud threshold products for the Karakoram region is found to be −1.67% and 1.1%, respectively. The improved (MOYDGL06*) product reveals a statistically insignificant decreasing trend of the SCA on the annual scale between 2003 and 2018 in the Karakoram region and all three subbasins. The annual trends decreased at −0.13%, −0.1%, −0.08%, and −0.05% in the Karakoram, Hunza, Shigar, and Shyok, respectively. The monthly trends were slightly positive overall in December. The annual maximum SLA shows a statistically significant upward trend of 13 m above sea level (m a.s.l.) per year for the entire Karakoram region. This finding suggests a significant uncertainty in water resource planning based on the original snow data, and this study recommends the use of the improved snow product for a better understanding.

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“…However, a major area in the UIB is covered with snow and glaciers wherein melting water is used for irrigation, domestic use, and hydropower generation [7]. According to the study of Hussain et al [71], the snow cover showed a decreasing trend in the Gilgit river basin, whereas that of Tahir et al [72] reported a slightly increasing trend in the Hunza river basin.…”

Section: E Ground Water Storage(gws) Anomalies From Gracementioning

confidence: 99%

Spatial and Temporal Variations of Terrestrial Water Storage in Upper Indus Basin Using GRACE and Altimetry Data

et al. 2020

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Gravity Recovery and Climate Experiment (GRACE) and satellite altimetry are suitable for the precise measurement of terrestrial water storage (TWS) and lake water level variations from space. In this study, two GRACE solutions, namely, spherical harmonics (SH) and mascon (MSC), are utilized with the Global Land Data Assimilation System (GLDAS) model to estimate the spatial and temporal variations of TWS in the Upper Indus Basin (UIB) for the study period of January 2003 to December 2016. The TWS estimated by SH, MSC, and the GLDAS model are consistent and generally show negative trends of −4.47 ± 0.38 mm/year, −4.81 ± 0.49 mm/year, and −3.77 ± 0.46 mm/year, respectively. Moreover, we use the GLDAS model data to understand the roles of variations in land surface state variables (snow water equivalent (SWE), soil moisture, and canopy water storage) in enhancing or dissipating the TWS in the region. Results indicate that SWE, which has a significant contribution to GRACE TWS variability, is an important parameter. Spearman's rank correlations are calculated to demonstrate the relationship of the GLDAS land surface state variables and the GRACE signals. A highly positive correlation between SWE with TWS is estimated by SH and MSC as 0.691 and 0.649, respectively, indicating that the TWS signal is mainly reliant on snow water in the study region. The ground water storages estimated by SH and MSC solutions are nearly stable with slight increasing trends of 0.63 ± 0.48 mm/year and 0.29 ± 0.51 mm/year, respectively. We also take advantage of the potential of satellite altimetry in measuring lake water level variations, and our result indicates that Cryosat-2 SARin mode altimetry data can be used in estimating small water bodies accurately in the high mountainous region of the UIB. Moreover, the climate indices data of El-Niño Southern Oscillation and Pacific Decadal Oscillation are analyzed to determine the influence of pacific climatic variability on TWS. INDEX TERMS Cryosat-2, GLDAS model, GRACE Satellite, terrestrial water storage, upper indus basin. I. INTRODUCTION Terrestrial water storage (TWS) refers to all forms of water stored on and beneath the surface of the Earth. It consists of surface water bodies (e.g., reservoirs, lakes, and rivers), snow water equivalent (SWE), glaciers, soil moisture (SM), canopy water storage (CWS), and groundwater [1], [2]. TWS is a substantial component of the hydrological cycle [3], which The associate editor coordinating the review of this manuscript and approving it for publication was Xian Sun. has a significant impact on the environment, society, ecology, and economy [4], [5]. Snow and glaciers are essential factors of TWS in mountainous regions [6] and are affected by climate change [7]. Studies have reported that the increment in the melting of snow and glaciers has decreased the TWS in highlands [8] but increased in surrounding basin areas [9]. The changes in TWS may associated with anthropogenic activities and climate variability, which plays a major role in global and regio...

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Spaceborne Satellite for Snow Cover and Hydrological Characteristic of the Gilgit River Basin, Hindukush–Karakoram Mountains, Pakistan

Cited by 26 publications

References 27 publications

The Response of Culturally Important Plants to Experimental Warming and Grazing in Pakistan Himalayas

The Response of Culturally Important Plants to Experimental Warming and Grazing in Pakistan Himalayas

Contemporary Snow Changes in the Karakoram Region Attributed to Improved MODIS Data between 2003 and 2018

Spatial and Temporal Variations of Terrestrial Water Storage in Upper Indus Basin Using GRACE and Altimetry Data

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