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<p>Land Subsidence (LS) is one of the critical environmental hazards reported in many countries worldwide with prominent examples from Mexico City (Mexico), Houston (US), Beijing (China), and Jakarta (Indonesia). It is the gradual compaction of the aquifer usually caused by groundwater exploitation in regions with abundant silt and clay sediments susceptible to compression. In this study, the spatio-temporal subsidence analysis of five districts (Quetta, Gulistan, Pishin, Mastung, and Kalat) in Balochistan, Pakistan was done using multi-sensor Small Baseline Subset (SBAS) Interferometric Synthetic Aperture Radar (InSAR) employing datasets from Envisat ASAR, Sentinel-1 and Global Navigation Satellite System (GNSS). This study represents the first comprehensive long-term analysis of LS in Pakistan, covering a 2-decade period (2003–2023) and encompassing multiple districts. For Sentinel-1, 193, 195, and 182 acquisitions on the Ascending track and 183 scenes in the Descending track were utilized to analyse LS from December 2015 to December 2022. For Envisat, 38 acquisitions in the descending track were processed to study LS from April 2003 to January 2010. These two SAR datasets were fused using GNSS data (2008–2023). A two-decade (2003–2023) LS analysis was conducted in Quetta, whereas a seven-year (2015–2022) analysis was performed in the other 4 districts. In the Quetta region, the maximum LS rate from 2003 to 2010 was − 11.4&#xa0;cm/y which accelerated to −12&#xa0;cm/y during 2010–2016 and then further increased to − 16&#xa0;cm/y after 2016. This is likely caused by the decline in groundwater level (GWL) and the presence of clay-rich sediments susceptible to compaction. The maximum accumulative subsidence recorded in Quetta from 2003 to 2023 was − 273&#xa0;cm. In Gulistan, Pishin, Mastung, and Kalat, the maximum subsidence rates were − 13&#xa0;cm/y, − 9.6&#xa0;cm/y, − 14.1&#xa0;cm/y, and − 7.1&#xa0;cm/y while the maximum accumulative LS from 2015 to 2022 in these districts was − 90&#xa0;cm, − 74&#xa0;cm, − 99.4&#xa0;cm, and − 49.7&#xa0;cm. Furthermore, the LS compared with the GWL decline in Quetta showed a correlation coefficient of 0.95 which illustrates that the GWL decline may be the primary reason for LS. A comparison of the ascending and descending tracks on two different frames showed standard deviations of 2.5&#xa0;cm and 1.22&#xa0;cm, indicating negligible horizontal deformation. The land use analysis revealed that LS is influenced by urbanisation in Quetta and agricultural activities in Gulistan, Pishin, Mastung, and Kalat regions. The geological analysis indicated that the LS mainly occurs in recent deposits rich in silt and clay. This correlation reveals the significance of sediment composition in understanding LS issues in the region. Large-scale fissures caused by uneven LS pose a threat to the infrastructure and aquifer contamination.</p>

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Spatio-temporal analysis of subsiding districts in Balochistan, Pakistan using Multi-Sensor SBAS InSAR and GNSS

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  • 发表日期：

    2025年3月19日

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  • Najeebullah Kakar,
  • Chaoying Zhao,
  • Guangrong Li,
  • Zhijie Zhang,
  • Bright Adoko

摘要

Land Subsidence (LS) is one of the critical environmental hazards reported in many countries worldwide with prominent examples from Mexico City (Mexico), Houston (US), Beijing (China), and Jakarta (Indonesia). It is the gradual compaction of the aquifer usually caused by groundwater exploitation in regions with abundant silt and clay sediments susceptible to compression. In this study, the spatio-temporal subsidence analysis of five districts (Quetta, Gulistan, Pishin, Mastung, and Kalat) in Balochistan, Pakistan was done using multi-sensor Small Baseline Subset (SBAS) Interferometric Synthetic Aperture Radar (InSAR) employing datasets from Envisat ASAR, Sentinel-1 and Global Navigation Satellite System (GNSS). This study represents the first comprehensive long-term analysis of LS in Pakistan, covering a 2-decade period (2003–2023) and encompassing multiple districts. For Sentinel-1, 193, 195, and 182 acquisitions on the Ascending track and 183 scenes in the Descending track were utilized to analyse LS from December 2015 to December 2022. For Envisat, 38 acquisitions in the descending track were processed to study LS from April 2003 to January 2010. These two SAR datasets were fused using GNSS data (2008–2023). A two-decade (2003–2023) LS analysis was conducted in Quetta, whereas a seven-year (2015–2022) analysis was performed in the other 4 districts. In the Quetta region, the maximum LS rate from 2003 to 2010 was − 11.4 cm/y which accelerated to −12 cm/y during 2010–2016 and then further increased to − 16 cm/y after 2016. This is likely caused by the decline in groundwater level (GWL) and the presence of clay-rich sediments susceptible to compaction. The maximum accumulative subsidence recorded in Quetta from 2003 to 2023 was − 273 cm. In Gulistan, Pishin, Mastung, and Kalat, the maximum subsidence rates were − 13 cm/y, − 9.6 cm/y, − 14.1 cm/y, and − 7.1 cm/y while the maximum accumulative LS from 2015 to 2022 in these districts was − 90 cm, − 74 cm, − 99.4 cm, and − 49.7 cm. Furthermore, the LS compared with the GWL decline in Quetta showed a correlation coefficient of 0.95 which illustrates that the GWL decline may be the primary reason for LS. A comparison of the ascending and descending tracks on two different frames showed standard deviations of 2.5 cm and 1.22 cm, indicating negligible horizontal deformation. The land use analysis revealed that LS is influenced by urbanisation in Quetta and agricultural activities in Gulistan, Pishin, Mastung, and Kalat regions. The geological analysis indicated that the LS mainly occurs in recent deposits rich in silt and clay. This correlation reveals the significance of sediment composition in understanding LS issues in the region. Large-scale fissures caused by uneven LS pose a threat to the infrastructure and aquifer contamination.