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利用遙測資料及水文模型評估印度河上游盆地之冰凍圈動力學

為了解決CC BY-ND的問題，作者胡督塔 這樣論述：

A major progress has been made for the assessment of cryosphere dynamics globally, however regional and basin scale response that differs from global response of cryosphere remain poorly understood. In this study, we present a comprehensive analysis of cryosphere dynamics in Upper Indus Basin (UIB)

by using Spaceborn remote sensing satellites data along with hydrological model. The Indus River, which flows through China, India, and Pakistan, is mainly fed by melting snow and glaciers that are spread across the Hindukush, Karakoram and Himalaya (HKH) Mountains. The downstream population of the

Indus Plain heavily relies on this water resource for drinking, irrigation, and hydropower generation. Therefore, its cryosphere dynamics and river runoff variability must be properly monitored. Gilgit Basin, the northwestern part of the Upper Indus Basin, is selected for studying cryosphere dynami

cs and its implications on river runoff. In this study, 8−day snow products (MOD10A2) of moderate resolution imaging Spectroradiometer, from 2001 to 2015 are selected to access the snow−covered area in the catchment. A non−parametric Mann–Kendall test and Sen’s slope are calculated to assess whether

a significant trend exists in the Snow cover area (SCA) (%) time series data. Then, data from ground observatories for 1995–2013 are analyzed to demonstrate annual and seasonal signals in air temperature and precipitation. Results indicate that the annual and seasonal mean of SCA show a non−signifi

cant decreasing trend, but the autumn season shows a statistically significant decreasing SCA with a slope of−198.36 km2/year. The annual SCA shows a decreasing trend with the slope of−0.04 km2/year, however a sharp decline trend observed from 2010–2015. Seasonal analysis of SCA indicates that sprin

g season has the greatest SCA compared to winter season with 59.15% SCA for winter, spring (65.33 %), summer (30.43%), and autumn (50.76%). The annual mean temperature and precipitation show an increasing trend with highest values of slope 0.05 °C/year and 14.98 mm/year, respectively. Furthermore, P

earson correlation coefficients are calculated for the hydro−meteorological data to demonstrate any possible relationship. The SCA is affirmed to have a highly negative correlation with mean temperature and runoff. Meanwhile, SCA has a very weak relation with precipitation data. The Pearson correlat

ion coefficient between SCA and runoff is −0.82, which confirms that the Gilgit River runoff largely depends on the melting of snow cover rather than direct precipitation. The study indicates that the SCA slightly decreased for the study period, which depicts a possible impact of global warming on t

his mountainous region.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 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 0.691and 0.649, respectively, indicating that the TWS signal is mainly reliant on snow water in the study region. The analysis of seasonal TWS indicates that TWS is high in spring and summer season while it is low in winter and autumn. In addition,

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. Furthermore, we take advantage of the potential of satellite altimetry in measuring lake water level variations in Attabad Lake,

and our result indicates that Crysot−2 SARin mode altimetry data can be used in estimating small water bodies accurately in the high mountainous region of the UIB. Our study indicates that the water level in the lake is decreasing. However, a sharp decrease in lake level was observed from 2011 to 20

14, that is, −29.65 m possibly due to opening of spillway to reduced lake water level. 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. The assessment of cryosphere dynam

ics in UIB probably has an importance for better management of water resource and forecasting of natural hazards.