Uncovering the impacts of depleting aquifers: A remote sensing analysis of land subsidence in Iran.

Intensive groundwater pumping, previously unrecognized in its full extent, is blamed for aquifer degradation and widespread land subsidence in Iran. We use a 100-meter resolution satellite survey from 2014 to 2020 to assess the recent implications of groundwater usage across the country. Results indicate that approximately 56,000 km2 (3.5%) of the country's area is subject to land subsidence, primarily linked to irrigation; 3000 km2 of this area experiences subsidence rates greater than 10 cm/year. The central plateau catchment hosts two-thirds of the country's depleting aquifers, with locations sinking at rates higher than 35 cm/year. The results suggest an annual groundwater depletion of 1.7 billion cubic meters (BCM) from confined and semiconfined aquifers, with the long-term inelastic compaction for most aquifers being approximately one order of magnitude larger than their seasonal elastic response. This underscores the permanent loss of aquifers that jeopardizes the sustainability of water resources across Iran.

Tracking hidden crisis in India's capital from space: implications of unsustainable groundwater use.

National Capital Region (NCR, Delhi) in India is one of the fastest-growing metropolitan cities which is facing a severe water crisis due to increasing water demand. The over-extraction of groundwater, particularly from its unconsolidated alluvial deposits makes the region prone to subsidence. In this study, we investigated the effects of plummeting groundwater levels on land surface elevations in Delhi NCR using Sentinel-1 datasets acquired during the years 2014-2020. Our analysis reveals two distinct subsidence features in the study area with rates exceeding 11 cm/year in Kapashera-an urban village near IGI airport Delhi, and 3 cm/year in Faridabad throughout the study period. The subsidence in these two areas are accelerating and follows the depleting groundwater trend. The third region, Dwarka shows a shift from subsidence to uplift during the years which can be attributed to the strict government policies to regulate groundwater use and incentivizing rainwater harvesting. Further analysis using a classified risk map based on hazard risk and vulnerability approach highlights an approximate area of 100 square kilometers to be subjected to the highest risk level of ground movement, demanding urgent attention. The findings of this study are highly relevant for government agencies to formulate new policies against the over-exploitation of groundwater and to facilitate a sustainable and resilient groundwater management system in Delhi NCR.

A decade-long silent ground subsidence hazard culminating in a metropolitan disaster in Maceió, Brazil.

Ground subsidence caused by natural or anthropogenic processes affects major urban areas worldwide. Sinkhole formation and infrastructure fractures have intensified in the federal capital of Maceió (Alagoas, Brazil) since early 2018, forcing authorities to relocate affected residents and place buildings under demolition. In this study, we present a 16-year history (2004-2020) of surface displacement, which shows precursory deformations in 2004-2005, reaching a maximum cumulative subsidence of approximately 200 cm near the Mundaú Lagoon coast in November 2020. By integrating the displacement observations with numerical source modelling, we suggest that extensive subsidence can be primarily associated with the removal of localized, deep-seated material at the location and depth where salt is mined. We discuss the accelerating subsidence rates, influence of severe precipitation events on the aforementioned geological instability, and related hazards. This study suggests that feedback destabilization mechanisms may arise in evaporite systems due to anthropogenic activities, fostering enhanced and complex superficial ground deformation.

Complex hazard cascade culminating in the Anak Krakatau sector collapse.

Flank instability and sector collapses, which pose major threats, are common on volcanic islands. On 22 Dec 2018, a sector collapse event occurred at Anak Krakatau volcano in the Sunda Strait, triggering a deadly tsunami. Here we use multiparametric ground-based and space-borne data to show that prior to its collapse, the volcano exhibited an elevated state of activity, including precursory thermal anomalies, an increase in the island's surface area, and a gradual seaward motion of its southwestern flank on a dipping décollement. Two minutes after a small earthquake, seismic signals characterize the collapse of the volcano's flank at 13:55 UTC. This sector collapse decapitated the cone-shaped edifice and triggered a tsunami that caused 430 fatalities. We discuss the nature of the precursor processes underpinning the collapse that culminated in a complex hazard cascade with important implications for the early detection of potential flank instability at other volcanoes.

The rise, collapse, and compaction of Mt. Mantap from the 3 September 2017 North Korean nuclear test.

Surveillance of clandestine nuclear tests relies on a global seismic network, but the potential of spaceborne monitoring has been underexploited. We used satellite radar imagery to determine the complete surface displacement field of up to 3.5 meters of divergent horizontal motion with 0.5 meters of subsidence associated with North Korea's largest underground nuclear test. Combining insight from geodetic and seismological remote sensing, we found that the aftermath of the initial explosive deformation involved subsidence associated with subsurface collapse and aseismic compaction of the damaged rocks of the test site. The explosive yield from the nuclear detonation with best-fitting source parameters for 450-meter depth was 191 kilotonnes of TNT equivalent. Our results demonstrate the capability of spaceborne remote sensing to help characterize large underground nuclear tests.

Bathymetric survey of water reservoirs in north-eastern Brazil based on TanDEM-X satellite data.

Water scarcity in the dry season is a vital problem in dryland regions such as northeastern Brazil. Water supplies in these areas often come from numerous reservoirs of various sizes. However, inventory data for these reservoirs is often limited due to the expense and time required for their acquisition via field surveys, particularly in remote areas. Remote sensing techniques provide a valuable alternative to conventional reservoir bathymetric surveys for water resource management. In this study single pass TanDEM-X data acquired in bistatic mode were used to generate digital elevation models (DEMs) in the Madalena catchment, northeastern Brazil. Validation with differential global positioning system (DGPS) data from field measurements indicated an absolute elevation accuracy of approximately 1m for the TanDEM-X derived DEMs (TDX DEMs). The DEMs derived from TanDEM-X data acquired at low water levels show significant advantages over bathymetric maps derived from field survey, particularly with regard to coverage, evenly distributed measurements and replication of reservoir shape. Furthermore, by mapping the dry reservoir bottoms with TanDEM-X data, TDX DEMs are free of emergent and submerged macrophytes, independent of water depth (e.g. >10m), water quality and even weather conditions. Thus, the method is superior to other existing bathymetric mapping approaches, particularly for inland water bodies. The proposed approach relies on (nearly) dry reservoir conditions at times of image acquisition and is thus restricted to areas that show considerable water levels variations. However, comparisons between TDX DEM and the bathymetric map derived from field surveys show that the amount of water retained during the dry phase has only marginal impact on the total water volume derivation from TDX DEM. Overall, DEMs generated from bistatic TanDEM-X data acquired in low water periods constitute a useful and efficient data source for deriving reservoir bathymetry and show great potential in large scale application.

A study on rational function model generation for TerraSAR-X imagery.

The Rational Function Model (RFM) has been widely used as an alternative to rigorous sensor models of high-resolution optical imagery in photogrammetry and remote sensing geometric processing. However, not much work has been done to evaluate the applicability of the RF model for Synthetic Aperture Radar (SAR) image processing. This paper investigates how to generate a Rational Polynomial Coefficient (RPC) for high-resolution TerraSAR-X imagery using an independent approach. The experimental results demonstrate that the RFM obtained using the independent approach fits the Range-Doppler physical sensor model with an accuracy of greater than 10-3 pixel. Because independent RPCs indicate absolute errors in geolocation, two methods can be used to improve the geometric accuracy of the RFM. In the first method, Ground Control Points (GCPs) are used to update SAR sensor orientation parameters, and the RPCs are calculated using the updated parameters. Our experiment demonstrates that by using three control points in the corners of the image, an accuracy of 0.69 pixels in range and 0.88 pixels in the azimuth direction is achieved. For the second method, we tested the use of an affine model for refining RPCs. In this case, by applying four GCPs in the corners of the image, the accuracy reached 0.75 pixels in range and 0.82 pixels in the azimuth direction.