Overview of terrestrial water storage changes over the Indus River Basin based on GRACE/GRACE-FO solutions

Zhu, Yanzi; Liu, Shiyin; Yi, Ying; Xie, Fuming; Grünwald, Richard; Miao, Wenfei; Wu, Kunpeng; Qi, Miaomiao; Gao, Yongpeng; Singh, Dharmaveer

doi:10.1016/j.scitotenv.2021.149366

Cited by 35 publications

(25 citation statements)

References 77 publications

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“…In addition, Dangar and Mishra (2021) highlight the impacts of long-term changes in climate in the Ganges river basin, which led to higher frequencies of droughts, warming temperature, and a decrease in monsoon rainfall. Zhu et al (2021) suggest similar reasons for negative trends in TWSA in the Indus river plains and additionally emphasize the high loss in groundwater during the pre-monsoon and monsoon season. The mismatch between trends in SWA and TWSA might be explained by the contribution of rainfall, glacier as well as snow melt, which might prevent a decrease in SWA.…”

Section: Discussionsupporting

confidence: 58%

Multi-faceted analyses of seasonal trends and drivers of land surface variables in Indo-Gangetic river basins

Uereyen¹,

Bachofer²,

Klein³

et al. 2022

Preprint

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High mountain Asia holds the largest glacier mass on Earth outside the polar regions. In combination with monsoonal rainfall, glacial meltwater provides the downstream Indo-Gangetic river basins with indispensable water resources. These rivers supply 1.2 billion people with water and their water resources are essential for many sectors including the world's largest connected irrigated cropland and domestic needs. In this context, the quantification of land surface dynamics and driving factors is of particular interest to enhance the understanding of interplays between multiple spheres. This study investigates multivariate time series including climatic, hydrological, and remote sensing-based land surface and anthropogenic variables. For the first time, we generate dense time series of multiple remote sensing-based land surface variables at biweekly intervals and employ statistical time series analyses at seasonal and annual scale. We analyze trends and controlling variables in consideration of temporal lags using causal networks between December 2002 and November 2020. The results show increasing trends in vegetation greenness being accelerated during the second half of the study period. Furthermore, a mismatch between trends in surface water area and terrestrial water storage was identified. Considering snow cover area, trends remain mostly insignificant at basin scale suggesting no change during the 18 years. At seasonal and grid scale, analyses indicate negative trends over the Upper Ganges and Brahmaputra river basins particularly during the monsoon and post-monsoon season. Furthermore, the causal networks revealed so far unexplored interactions among multivariate feature spaces at seasonal scale. For example, vegetation greenness is constrained by water availability, surface water area is influenced by river discharge, snow cover, and temperature, whereas snow cover area is largely controlled by precipitation and temperature with spatial and temporal variations. To summarize, these findings provide valuable insights with respect to the trends and interactions between various spheres in the Indo-Gangetic river basins.

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Section: Discussionsupporting

confidence: 58%

Multi-faceted analyses of seasonal trends and drivers of land surface variables in Indo-Gangetic river basins

Uereyen¹,

Bachofer²,

Klein³

et al. 2022

Preprint

View full text Add to dashboard Cite

show abstract

“…In addition, Dangar and Mishra (2021) highlighted the impacts of longterm changes in the climate in the Ganges river basin, which led to higher frequencies of droughts, warming temperatures, and a decrease in monsoon rainfall. Zhu et al (2021) suggested similar reasons for negative trends in TWSA in the Indus river plains and additionally emphasized the high loss in groundwater during the pre-monsoon and monsoon season. The mismatch between trends in SWA and TWSA could be likely explained by the contribution of rainfall, glacier as well as snow melt, which might prevent a decrease in SWA.…”

Section: Surface Water Areamentioning

confidence: 64%

Multi-faceted analyses of seasonal trends and drivers of land surface variables in Indo-Gangetic river basins

Uereyen

Bachofer

Klein

et al. 2022

Science of The Total Environment

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“…Empirical orthogonal function (EOF) analysis involves decomposing time-varying variable fields into time-invariant spatial functions and time-dependent functions. The spatio-temporal dataset is then simplified, as it is transformed into spatial modes of physical quantities and associated time projections (time series) [43]. These spatial modes are EOFs, and they can be thought of as basic functions (a set of basic vectors in a space) which correspond with the variances.…”

Section: Methodsmentioning

confidence: 99%

Increased Compound Droughts and Heatwaves in a Double Pack in Central Asia

Wang

Chen

et al. 2022

Remote Sensing

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Compound droughts and heatwaves (CDHWs) are likely to cause more severe natural disasters than a single extreme event, and they have been exacerbated by rapid global warming. Based on high-resolution grid data, this study combines the daily-scale ERA5-Land dataset and the monthly-scale SPEI dataset with multiple indicators to analyze CDHWs. We calculated and analyzed the temporal and spatial modal distribution of CDHWs in Central Asia from 1981 to 2018, and in this paper, we discuss the sequence relationship between drought events, heatwave events, and CDHWs. The results show that the number of CDHWs in the study region have increased over time and expanded in terms of area, especially in eastern and southwestern Central Asia. The tsum (total frequency of CDHWs) was 0.5 times higher than the total heatwave frequency and it increased at a rate of 0.17/yr. The maximum duration of tmax (maximum duration of CDHWs in days) was 17 days. Furthermore, the occurrence rate of tmax was 96.67%, and the AH (CDHWs’ accumulated heat) had a rate of 97.78%, which, upon examination of the spatial trend pattern, accounted for the largest increase in terms of area. We also found that the TAH (CDHWs’ average temperature anomalies, SPEI < −0.5) shows obvious seasonality, with the increases in winter and spring being significantly greater than the increases in summer and autumn. The intensity of the CDHWs was stronger than that of a single extreme event, the temperature anomaly was higher than the average of 0.4–0.8 °C, and there was a north–south spatial pattern across the study region. In eastern and northwestern Central Asia, the AH and heatwaves (SPEI < −0.5) increased by 15–30 times per year on average. During the transition from the base period to the reference period, CDHWs increased by 25%, and the number of dry days prior to the CDHWs decreased by 7.35 days. The conclusion of our study can provide a theoretical basis for coping with climate change in arid zones.

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Overview of terrestrial water storage changes over the Indus River Basin based on GRACE/GRACE-FO solutions

Cited by 35 publications

References 77 publications

Multi-faceted analyses of seasonal trends and drivers of land surface variables in Indo-Gangetic river basins

Multi-faceted analyses of seasonal trends and drivers of land surface variables in Indo-Gangetic river basins

Multi-faceted analyses of seasonal trends and drivers of land surface variables in Indo-Gangetic river basins

Increased Compound Droughts and Heatwaves in a Double Pack in Central Asia

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