Analysis of terrestrial water storage changes in the Shaan-Gan-Ning Region using GPS and GRACE/GFO

Li, Xianpao; Zhong, Bo; Li, Jiancheng; Liu, Renli

doi:10.1016/j.geog.2021.11.001

Cited by 16 publications

(11 citation statements)

References 37 publications

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“…Liu et al (2022) inverted the GNSS vertical displacement time series for TWS changes based on the independent component analysis (ICA) method in the Sichuan-Yunnan region of China, and the ICA-based GNSS vertical displacements could infer more reliable TWS changes. Li et al (2022) introduced an improved regularization Laplacian matrix to improve the reliability of GNSS-derived TWS changes in the Shaan-Gan-Ning Region of China. Additionally, White et al (2022) systematically introduced the research advances of the applications and implications for GNSS observations in retrieving TWS changes.…”

Section: 1029/2022ea002608mentioning

confidence: 99%

“…2 of 18 such as the United States (Argus et al, 2017;Borsa et al, 2014;Enzminger et al, 2018;Fu et al, 2015;Jin & Zhang, 2016;Shen et al, 2020), China (Fok & Liu, 2019;Hsu et al, 2020;Jiang, Hsu, Yuan, & Huang, 2021;Lai et al, 2020;Li et al, 2022;Shen et al, 2021;Zhang et al, 2016;Zhong et al, 2020) and South America (Ferreira et al, 2019). For example, Borsa et al (2014) used the GNSS-derived TWS changes to reveal the ongoing drought in the western United States, and the results showed that GNSS-derived TWS changes presented good consistency with precipitation and streamflow.…”

Section: 1029/2022ea002608mentioning

confidence: 99%

“…Li et al. (2022) introduced an improved regularization Laplacian matrix to improve the reliability of GNSS‐derived TWS changes in the Shaan–Gan–Ning Region of China. Additionally, White et al.…”

Section: Introductionmentioning

confidence: 99%

“…(2014) first inverted the GNSS vertical displacements for regional TWS changes using the Green's function method in California, and the spatial resolution of GNSS‐derived TWS changes could reach ∼50 km. Subsequently, the Green's function method has been widely used to invert GNSS observations for regional TWS changes in different regions, such as the United States (Argus et al., 2017; Borsa et al., 2014; Enzminger et al., 2018; Fu et al., 2015; Jin & Zhang, 2016; Shen et al., 2020), China (Fok & Liu, 2019; Hsu et al., 2020; Jiang, Hsu, Yuan, & Huang, 2021; Lai et al., 2020; Li et al., 2022; B. Liu et al., 2022; Shen et al., 2021; Zhang et al., 2016; Zhong et al., 2020) and South America (Ferreira et al., 2019). For example, Borsa et al.…”

Section: Introductionmentioning

confidence: 99%

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Inversion of GNSS Vertical Displacements for Terrestrial Water Storage Changes Using Slepian Basis Functions

Zhong

et al. 2023

Earth and Space Science

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The surface displacements measured by the Global Navigation Satellite System (GNSS) provide a unique insight for studying terrestrial water storage (TWS) changes. In this study, we recovered the TWS changes from GNSS vertical displacements in Southwest China (SWC) using Slepian basis function (SBF) from January 2011 to December 2020. The performance of the TWS changes estimated by SBF was validated against the Gravity Recovery and Climate Experiment (GRACE)/GRACE Follow‐On (GFO) and the GNSS‐inverted TWS changes estimated by Green's function method. The results showed that the spatial patterns, seasonal, and linear trends of the TWS changes derived from GNSS using SBF agreed with the GRACE/GFO estimates. However, there are still evident differences in the local scope, and the GNSS‐derived TWS changes presented stronger amplitudes and more details in the spatio‐temporal domains than the GRACE/GFO estimates in SWC. The unconstrained GNSS inversion results using SBF also presented stronger signal amplitudes than those estimates with Green's function, and the TWS changes estimated by SBF were more reliable than Green's function method for regions with sparsely distributed GNSS stations in SWC. Additionally, the average distance between the GNSS stations can be considered as a reasonable filtering radius of SBF, and the SBF‐estimated TWS changes with different Gaussian filtering radii had comparable signal amplitudes and spatial patterns with the estimates of Green's function and GRACE/GFO.

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Section: 1029/2022ea002608mentioning

confidence: 99%

Section: 1029/2022ea002608mentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Inversion of GNSS Vertical Displacements for Terrestrial Water Storage Changes Using Slepian Basis Functions

Zhong

et al. 2023

Earth and Space Science

Self Cite

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“…Namun, walaupun telah ditanam dengan pola dan jarak yang ditentukan, sering kali produksi yang dihasilkan tanaman kelapa sawit per hektare tidak dapat mencapai potensi produksinya (Kumar et al, 2022;Li et al, 2022;Liang et al, 2021). Tidak tercapainya potensi produksi tersebut salah satunya dapat disebabkan karena tanaman yang ada dalam suatu luasan tidak seluruhnya merupakan pokok yang produktif, tetapi ada kemungkinan pokok tersebut adalah pokok abnormal, mati bahkan kosong (tidak terdapat tanaman) (Lv et al, 2022;Memarian et al, 2022;Muhammad et al, 2021).…”

Section: Pendahuluanunclassified

Metode Sensus Pokok Tanaman Kelapa Sawit Menggunakan Software Map Source Dan Autodesk Map

Stefano¹,

Endayani²,

Fathiah³

2023

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Mendapatkan data tanaman yang akurat sesuai dengan kondisi real di lapangan perlu dilakukan kegiatan sensus pokok secara teliti. Pada umumnya hasil kegiatan sensus pokok dituang ke dalam form blangko sensus (staple card). Data yang dihasilkan sering kali tidak akurat. Sebagai upaya untuk menghasilkan data sensus pokok yang lebih akurat, digunakanlah GPS (Global Positioning System) sebagai alat sensus. Kajian ini dilakukan untuk menentukan metode sensus pokok yang efektif dan efisien antara menggunakan staple card dan menggunakan GPS. Metode yang digunakan dalam pelaksanaan kajian ini, yaitu dengan melakukan pengamatan dan observasi di lapangan mengenai kedua metode sensus pokok yang dikaji. Parameter yang diamati yaitu biaya, waktu dan tenaga yang dibutuhkan, serta akurasi data yang dihasilkan masing–masing metode. Hasil kajian menunjukkan bahwa sensus pokok menggunakan GPS akan lebih efisien dan efektif, serta dapat menghasilkan profit yang lebih besar bagi perusahaan yaitu Rp.204.674/ha/tahun.

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Understanding satellite‐derived groundwater dynamics and its association with hydrological processes over India during excess and deficit monsoon years

Shaikh,

Parekh,

Gnanaseelan

2024

Hydrological Processes

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The Gravity Recovery and Climate Experiment (GRACE) satellite provides valuable data to monitor groundwater variation. This study investigates groundwater dynamics in India during deficit and excess monsoon years. It finds possible interactions by exploring how groundwater levels respond to meteorological and hydrological conditions. Groundwater anomalies (GWA) are estimated using Terrestrial Water Storage Anomalies (TWSA) from GRACE and hydrological parameters from the Global Land Data Assimilation System (GLDAS). The statistical analysis reveals that the standard deviation is higher for hydrological parameters in summer (June to September), whereas it is higher in fall (October to November) for GWA in many parts of India. The modulation in hydrological parameters subsequently impacts GWA during the following seasons. The study reports increased groundwater across many parts of India during fall. However, groundwater decline is closely linked to unsaturated soil moisture from fall to winter (December to February). Groundwater storage is at its lowest levels during the following spring (March to May) over India. Four deficit and three excess summer monsoons occurred from 2002 to 2022. Composite analysis of GWA reveals that there is replenishment (depletion) of groundwater during the following fall and winter in excess (deficit). The analysis based on extreme deficit monsoon years (2002, 2009) and excess monsoon year (2019) reveals that during the deficit years, groundwater recharge is less, and excess monsoon year it is more; and is vice versa for GWA. The study reports decline in GWA during the summer 2019, which is attributed to the hydrological conditions of the preceding year and modulation of the hydrological processes. As climate variability and water scarcity become increasingly pressing issues, understanding the relationships between hydrological factors and groundwater dynamics is essential for ensuring sustainable water use and resilience to extremely varying climate conditions.

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Analysis of terrestrial water storage changes in the Shaan-Gan-Ning Region using GPS and GRACE/GFO

Cited by 16 publications

References 37 publications

Inversion of GNSS Vertical Displacements for Terrestrial Water Storage Changes Using Slepian Basis Functions

Inversion of GNSS Vertical Displacements for Terrestrial Water Storage Changes Using Slepian Basis Functions

Metode Sensus Pokok Tanaman Kelapa Sawit Menggunakan Software Map Source Dan Autodesk Map

Understanding satellite‐derived groundwater dynamics and its association with hydrological processes over India during excess and deficit monsoon years

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