GM6.5

EDI
Coastal subsidence: natural and anthropogenic drivers

Low-lying coastal areas can be an early casualty to sea-level rise, especially where enhanced by land subsidence. An ever increasing number of studies indicates that land subsidence due to natural and anthropogenic causes has induced damage to wetland ecosystems in many countries worldwide, and has increased flooding hazard and risk. Coastal subsidence causes include excessive groundwater extraction from aquifers, peat oxidation due to surface water drainage through land reclamation, urbanization and agricultural use, as well as sediment starvation due to construction of dams and artificial levees. Contrary to the global processes behind sea-level rise, natural and anthropogenic coastal subsidence is primarily a local phenomenon, and its causes and severity may vary substantially from place to place.
The combination of geological and historical measurements with remote sensing data is required to understand all drivers of coastal vertical land motion and the contributions to past, present, and future subsidence.
Understanding coastal subsidence requires multidisciplinary expertise, models, and remote and in-situ observations from geology, geodesy, natural hazards, oceanography, hydrogeology, and geomechanics. In this session, we aim to bring together all the involved disciplines. We invite contributions on all aspects of coastal subsidence research and applications, including recent advances on: i) measurement through ground-based, aerial and satellite remote sensing techniques, ii) numerical models and future projections, iii) their applicability to distinguish between the different drivers contributing to land subsidence, and iv) quantification of coastal hazards associated with relative sea-level rise. In particular, efforts towards characterizing human intervention on coastal vertical land motion are welcomed.

Co-organized by G3/NH1
Convener: Francesca Cigna | Co-conveners: Makan A. KaregarECSECS, Simon Engelhart, Thomas FrederikseECSECS
Presentations
| Thu, 26 May, 08:30–10:00 (CEST)
 
Room G2

Presentations: Thu, 26 May | Room G2

Chairpersons: Francesca Cigna, Makan A. Karegar, Ufuk Tarı
08:30–08:32
08:32–08:42
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EGU22-1300
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ECS
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solicited
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Highlight
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Virtual presentation
Megan M. Miller and Manoochehr Shirzaei

In August 2017, Hurricane Harvey brought record rainfall, elevated storm tide, flooding and socioeconomic devastation to southeastern Texas. Using the radar backscattering difference between Sentinel-1A/B satellite acquisitions, a snapshot of standing water at the time of the satellite acquisition is provided and compared with designated flood hazard zones.

Next, Vertical land motion (VLM) is found by combining GNSS with multitemporal interferometric processing of SAR datasets acquired by ALOS and Sentinel-1A/B satellites. Land subsidence is observed up to 49 mm/yr during the ALOS acquisition period (Jul-2007–Jan-2011) and 34 mm/yr for the Sentinel-1A/B (Dec-2015 to Aug-2017) acquisition periods. Of the flooded area, 85% subsided at a rate > 5 mm/yr supported by the Chi-square test of independence.

Hurricane Harvey and other recent storms highlight potential vulnerabilities of flood resilience plans in coastal Texas that will degrade with climate change and rising seas. Combining VLM with sea-level rise (SLR) projections and storm surge scenarios for the years 2030, 2050, and 2100, we quantify the extent of flooding hazards for the Houston and Galveston areas. VLM is resampled and projected on LIDAR high-resolution topographic grids, then multiple inundation and flooding scenarios are modeled. By the year 2100, over 76 km2 are projected to subside below sea level from VLM. Holding other variables constant, subsidence increases the area of inundation over SLR alone by up to 39%. Under the worst-case composite scenario of an 8-m storm surge, subsidence, and the SLR RCP8.5, the total affected area is 1,156 km2. These composite scenarios produce model maps which can improve flood resiliency plans.

How to cite: Miller, M. M. and Shirzaei, M.: Land subsidence correlated with flooding during Hurricane Harvey and the assessment of future flood hazards for Houston & Galveston Texas, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-1300, https://doi.org/10.5194/egusphere-egu22-1300, 2022.

08:42–08:47
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EGU22-3199
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Highlight
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Virtual presentation
Shimon Wdowinski and Simone Fiaschi

We revisit our study of localized land subsidence in Miami Beach, which relied on SAR data from the 1990s (Fiaschi and Wdowinski, 2020) to detect changes in subsidence patterns and velocities. Our original study used ERS-1/2 data acquired during 1993-1999 and revealed that subsidence occurs in localized patches (< 0.02 km2) with a magnitude of up to 3 mm/yr. Most of the subsidence occurred in the western side of the city in urban areas built on reclaimed wetlands. We also detected one location of localized subsidence in the eastern part of the city, which centered at a 12-story condominium building. This building, Champlain's South Tower (CTS), collapsed on June 24th, 2021 resulting in the tragic death of 98 residents. The study revealed that the CTS slowly settled during the 6-years observation period (1993-1999), which may induce structural damage to the building, 20-30 years before the building’s collapse.

Following the tragic collapse of the CTS, societally important questions were raised by investigating teams, the media, and the public. In the current study we address some of these important questions:

  • Did the detected subsidence of the CTS in the 1990s have a differential component?
  • Did the CTS building continue subsiding after 1999?
  • Did other subsiding areas in Miami Beach continue to subside after 1999?
  • Did other areas in Miami Beach start subsiding after 1999? 
  • What is the significance of these findings?

The answer to the first question is based on a new post-processing of the ERS-1/2 solution, which revealed a small (0.5 mm/yr) differential component of the CTS building during 1993-1999. The answers to the next three questions were obtained from the analysis of Sentinel-1 data acquired during 2016-2021, which revealed a somewhat different subsidence field compared to the ERS-1/2 results. Finally, we used soil consolidation theory to explain the significance of the ERS-1/2 and Sentinel-1 results in terms of primary and secondary soil consolidation processes.

How to cite: Wdowinski, S. and Fiaschi, S.: Localized coastal subsidence in Miami Beach and Surfside, Florida, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-3199, https://doi.org/10.5194/egusphere-egu22-3199, 2022.

08:47–08:52
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EGU22-9302
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ECS
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Virtual presentation
Makan Karegar

The solid Earth aspects of relative sea-level change can dominate in low-lying coastal areas with potentially vulnerable to accelerating rates of sea-level rise. Global Navigation Satellite System (GNSS) as companion tools to tide gauges allow long-term assessment of solid Earth deformation, thus essential for disclosing climate-forced mechanisms contributing to sea-level rise (SLR). So far, it has not been possible to measure shallow displacements that occur above the base of GNSS monument because conventional positioning determines the vertical component of position changes resulting from displacements occurring beneath the foundation. We use an emerging technique, GNSS interferometric reflectometry (GNSS-IR), to estimate the rate of this process in two coastal regions with thick Holocene deposits, the Mississippi Delta and the eastern margin of the North Sea. We show that the rate of land motion from shallow compaction is comparable to or larger than the rate of SLR. Since many of the world's great coastal cities are built on river deltas with comparable Holocene sections, our results suggest that estimates of flood risk and land loss have been underestimated. We demonstrate environmental impact of parking lots and streets surrounding several monitoring sites on GNSS measurements. Such kinematic environments will perturb the amplitude of reflected signals to GNSS sensors and leave time-variable imprints on GNSS observations. Thus, obtaining desirable reflections for shallow subsidence monitoring could be challenging.

How to cite: Karegar, M.: on GNSS-IR technique for measuring shallow sediment compaction, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-9302, https://doi.org/10.5194/egusphere-egu22-9302, 2022.

08:52–08:57
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EGU22-1080
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ECS
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On-site presentation
Manon Verberne, Kay Koster, Aris Lourens, Joana Esteves Martins, Jan Gunnink, Thibault Candela, and Peter Fokker

Reclaimed coastal plains often experience significant subsidence as a result of phreatic water level lowering, which induces oxidation of organic material, shrinkage of clay, and sediment compaction. A primary example in the center of the Netherlands, is the ‘South Flevopolder’ which was reclaimed in 1968 and transformed into an area for residential, industrial and agricultural use. The area subsided over 1.5 m since its reclamation and its surface is still lowering.

The city of Almere, with roughly 200.000 inhabitants and a surface area of c. 250 km2, is situated in the South Flevopolder. Most buildings in the city are founded in deeper Pleistocene sand, whilst objects such as parking lots, sport fields and playgrounds are often unfounded and are directly situated on the younger Holocene coastal deposits. Currently, the unfounded objects show subsidence rates as high as 5 mm per year for which the different subsidence rates  may be related to subsurface heterogeneities. The upper layers in the area are dominated by clay and sand, up to a few meters in thickness, which overly peat and highly organic layers. The lowering of the phreatic surface results in an erratic pattern of subsidence over the area.

We present a workflow to disentangle and parameterize the different contributions of shallow subsidence from Interferometric synthetic-aperture radar (InSAR) measurements. InSAR measurements from founded and unfounded scatterers are separated with a dimensionality reduction technique, t-Distributed Stochastic Neighbor Embedding (t-SNE), followed by an automatic detection of clusters with Hierarchical Density-Based Spatial Clustering of Applications with Noise (HDBSCAN). We have limited ourselves to structures with a construction date of >10 years with respect to the first InSAR measurement date to reduce the effect of construction-related consolidation and isolate the effect of shallow subsidence related to reclamation and phreatic surface level changes. The filtered dataset represents the surface response of unfounded structures in the urbanized reclaimed coastal area.

The subsidence processes are disentangled and parameterized with an Ensemble Smoother with Multiple Data Assimilation (ES-MDA). Additional input data for this method is provided by a phreatic groundwater level model and a voxelized lithological model from the surface towards the top of the Pleistocene sand layers.

We show that the automated data selection method prevents bias by selecting unfounded objects and the proposed workflow can be of aid when studying shallow subsidence in urbanized areas, where most objects are founded below the level at which shallow subsidence takes place. The results of this study quantify the rate of the different subsidence processes on a spatiotemporal scale and thus provide insights for tailored decision making to mitigate subsidence.

How to cite: Verberne, M., Koster, K., Lourens, A., Esteves Martins, J., Gunnink, J., Candela, T., and Fokker, P.: ­­­­Disentangling shallow sources of subsidence in an urbanized reclaimed coastal plain, Almere, South Flevopolder the Netherlands, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-1080, https://doi.org/10.5194/egusphere-egu22-1080, 2022.

08:57–09:02
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EGU22-3943
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Virtual presentation
Madelon Molhoek, Kay Koster, Merijn de Bakker, Thibault Candela, Joana Esteves Martins, and Peter Fokker

Hydrocarbon reservoirs can be situated below low-lying coastal plains. Extraction from these reservoirs are known to cause substantial amounts of subsidence. Yet, the relative contribution of hydrocarbon extraction to total subsidence is often ignored in many coastal areas around the world. The primary reason for such negligence is because hydrocarbon extraction data are often confidential and therefore difficult to access for scientific research purposes. Incorporating the effects of hydrocarbon extraction in coastal subsidence research is however critical, as reservoirs can be depleted for decades in a row, causing decimeters of subsidence. Furthermore, gas is recently labeled by the European Union as a ‘green energy,’ motivating countries to increase production from low-lying coastal areas. Therefore, taking coastal subsidence by hydrocarbon extraction into account with datasets that are commonly private is essential for understanding regional subsidence processes, and eventually to design mitigation or adaptation strategies. 

In this study, we present the outline of a workflow being developed to deploy hydrocarbon extraction data for subsidence modelling while acknowledging data privacy constraints. The targeted area is the urbanized coastal plain of Friesland (The Netherlands), which is subsiding by compaction of ca. 2-3 km deep gas reservoirs, as well as by surficial processes such as peat oxidation and clay shrinkage. 

The core of the method is a Federated Learning framework for Neural Networks on vertically partitioned data including cryptographic techniques. Federated Learning implies that a central model can be trained on data which is only stored locally. Therefore, the data does not leave the premises of the data-owner (in this case the hydrocarbon operator), to protect confidential information. Such a model trains at each dataset and only model-updates are sent back and aggregated to the central server. The trained model and its output are shared between the parties involved.  

Our workflow comprises a secure learning set-up for gas reservoir pressure depletion. The workflow uses the library FATE (FAir, Transparent and Explainable decision making), which combines secure inner sect (a Multi-Party Computation) techniques with a bottom and top split Neural Network, combining the outputs of the bottom models with an interactive layer. The technique of Neural Network was selected for flexibility in algorithms used, such as future intertwining of the workflow with physical models (e.g., transfer learning and physics informed neural networks). Current work focuses on extracting relevant information on feature importance causing subsidence from the Federate Learning framework without compromising confidentiality. 

Preliminary results show that a Federated trained model does not significantly increase the prediction error compared to a centrally trained model, suggesting that the developed approach can be a critical step forward in convincing hydrocarbon operators to provide their data in a confidential way. In this way, subsidence by hydrocarbon extraction can be integrated into overall coastal subsidence studies. 

How to cite: Molhoek, M., Koster, K., de Bakker, M., Candela, T., Esteves Martins, J., and Fokker, P.: A Federated Learning approach to use confidential hydrocarbon extraction data for investigating coastal subsidence , EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-3943, https://doi.org/10.5194/egusphere-egu22-3943, 2022.

09:02–09:07
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EGU22-2549
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ECS
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Virtual presentation
Vitalijus Kondrat, Ilona Sakurova, Egle Baltranaite, and Loreta Kelpsaite-Rimkiene

Port of Klaipeda is situated in a complex hydrological system, between the Curonian Lagoon and the Baltic Sea, at the Klaipeda strait in the South-Eastern part of the Baltic Sea. It has almost 300 m of jetties separating the Curonian Spit and the mainland coast, interrupting the main path of sediment transport through all South-Eastern coast of the Baltic Sea. Due to the Port of Klaipeda reconstruction in 2002 and the beach nourishment project, which was started in 2014, the shoreline position change tendency was observed. Shoreline position measurements of various periods can be used to derive quantitative estimates of coastal processes direction and intensity. This data can be used to further our understanding of the scale and timing of shoreline changes in a geological and socio-economic context. This study analyzes long and short-term shoreline position changes before and after the Port of Klaipeda reconstruction in 2002. Positions of historical shorelines from various sources were used, and the rates (EPR, NSM, and SCE) of shoreline changes have been assessed using the Digital Shoreline Analysis System (DSAS). An extension of ArcGIS. K-means clustering was applied for shoreline classification into different coastal dynamic stretches. Coastal development has changed in the long-term (1984–2019) perspective: the eroded coast length increased from 1.5 to 4.2 km in the last decades. Coastal accumulation processes have been restored by the Port of Klaipeda executing the coastal zone nourishment project in 2014.

How to cite: Kondrat, V., Sakurova, I., Baltranaite, E., and Kelpsaite-Rimkiene, L.: Natural and anthropogenic factors shaping the shoreline of Klaipeda, Lithuania, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-2549, https://doi.org/10.5194/egusphere-egu22-2549, 2022.

09:07–09:12
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EGU22-5138
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Virtual presentation
Marco Anzidei, Michele Crosetto, Josè Navarro, Cristiano Tolomei, Petros Patias, Charalampos Georgiadis, Antonio Vecchio, Fawzi Doumaz, Lucia Trivigno, Antonio Falciano, Michele Greco, Enrico Serpelloni, Silvia Torresan, Qui Gao, Anna Barra, Claudia Ferrari, Chiara Tenderini, Xenia Loizidou, and Demetra Orthodoxou

Here we show and discuss the results arising from the SAVEMEDCOASTS-2 Project (Sea Level Rise Scenarios along the Mediterranean Coasts - 2, funded by the European Commission ECHO) for the Venice lagoon (northern Italy). We used geodetic data from global navigation satellite system (GNSS), synthetic aperture radar interferometric measurements (InSAR) from Copernicus Sentinel-1A (S1A) and Sentinel-1B (S1B) sensors and sea-level data from a set of tidal stations, to show subsidence rates and SLR in this area. The lagoon is well known for centuries to be prone to accelerated SLR due to natural and anthropogenic land subsidence that is causing increasing events of flooding and storm surges exacerbated by climate change. We focused on selected zones of the lagoon, characterized by particular heritage, coastal infrastructures and natural areas where the expected RSLR by 2100 is a potential cause of significant land flooding and morphological changes of the land. Results of the multi-temporal flooding scenarios until 2100 are based on the spatially variable rates of vertical land movements (VLM), the topographic features of the area provided by airborne Light Detection And Ranging (LiDAR) data and the Intergovernmental Panel on Climate Change (IPCC AR-5) projections of SLR in the Representative Concentration Pathways RCP2.6 and RCP8.5 emission scenarios. Our results show a diffuse land subsidence locally exceeding 9±2 mm/yr1. A variable RSLR between 0.62±0.12 m and 1.26±0.12 m is expected for 2100 AD in the RCP8.5 scenario. For this reference epoch, most of the investigated areas will be vulnerable to inundation in the next 80 years. A relevant concern is the protection of the historical city of Venice although the MOSE system has recently come into operation to prevent the effects of high tides in the lagoon. The hazard implications for the population living along the shore should push land planners and decision-makers to take into account long-term SLR scenarios in the definition and prioritization of adaptive pathways for a climate-resilient management of the Venice lagoon.

How to cite: Anzidei, M., Crosetto, M., Navarro, J., Tolomei, C., Patias, P., Georgiadis, C., Vecchio, A., Doumaz, F., Trivigno, L., Falciano, A., Greco, M., Serpelloni, E., Torresan, S., Gao, Q., Barra, A., Ferrari, C., Tenderini, C., Loizidou, X., and Orthodoxou, D.: Relative sea-level rise scenarios for 2100 in the Venice lagoon by integrated geodetic data, high-resolution topography and climate projections. New insights from the SAVEMEDCOASTS-2 Project., EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-5138, https://doi.org/10.5194/egusphere-egu22-5138, 2022.

09:12–09:17
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EGU22-1464
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Virtual presentation
Francesca Cigna and Deodato Tapete

The Capo Colonna promontory in southern Italy has long been affected by ground instability involving not only coastal erosion and loss of land, but also a noticeable subsidence process, both posing risk to houses and roads built onto the promontory, alongside its archeological site including Hera Lacinia’s sanctuary. Tectonic-induced submergence of some formerly exposed structures and sites and landward retreat up to 200 m were recorded over the centuries along the coastlines of this region. Anthropogenic activities associated with hydrocarbon exploitation add onto Capo Colonna’s ground deformation drivers, with an influence zone that appears to be mostly limited to the shallow-marine terrace that defines the promontory. Subsidence at the site has been monitored since 2005 with geodetic and geophysical methods by the national hydrocarbons authority and the archaeological superintendence. More recent investigations included satellite Interferometric Synthetic Aperture Radar (InSAR) techniques, that revealed −1 to −2 cm/year subsidence rates in 1992−2014 [1-2]. Artificial corner reflectors were also installed to enhance the backscattering properties of the archaeological site and the coastline, trying to ease identification of persistent and coherent scatterers suitable to act as InSAR monitoring targets [2]. This work extends the temporal coverage of past InSAR surveys using two 6 year-long big data stacks of ~300 Sentinel-1 IW scenes each [3], allowing the estimation of subsidence rates and patterns to date, with an unprecedented weekly temporal sampling. The Parallel Small BAseline Subset (P-SBAS) method integrated in ESA’s Geohazards Exploitation Platform (GEP) is used to run the advanced image processing workflow using a cloud environment. Present-day vertical rates are found in the order of −0.7 to −1.5 cm/year, with peaks of −2.3 cm/year. Two clear bands of east-west deformation are identified, with rates reaching ±1 cm/year and pointing towards the maximum subsidence center, i.e. west of a gas production well. While Sentinel-1 data corroborate the spatial association between land subsidence and gas extraction infrastructure (that was already observed in previous studies), the new results suggest an acceleration of the subsidence process with respect to its long-term trend. Some previously unknown short-term trend variations that overlapped onto the main subsidence process over the last few years are also highlighted, owing to the temporal granularity of the Sentinel-1 acquisitions. These outcomes contribute to advance the understanding of a local phenomenon studied for years, and prove the benefits that technical improvements in satellite observations can bring to refine coastal subsidence rates and distinguish driving factors.

 

[1] Tapete D., Cigna F. 2012. Site-specific analysis of deformation patterns on archaeological heritage by satellite radar interferometry. MRS Online Proceedings Library, 1374, 283-295. https://doi.org/10.1557/opl.2012.1397

[2] Cigna F. et al. 2016. 25 years of satellite InSAR monitoring of ground instability and coastal geohazards in the archaeological site of Capo Colonna, Italy. In: SAR Image Analysis, Modeling, and Techniques XVI, SPIE, Vol. 10003, id. 100030Q. https://doi.org/10.1117/12.2242095

[3] Cigna F., Tapete D. 2021. Sentinel-1 big data processing with P-SBAS InSAR in the Geohazards Exploitation Platform: an experiment on coastal land subsidence and landslides in Italy. Remote Sensing, 13, 885. https://doi.org/10.3390/rs13050885

How to cite: Cigna, F. and Tapete, D.: InSAR-derived present-day rates and drivers of coastal land subsidence at Capo Colonna, Italy, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-1464, https://doi.org/10.5194/egusphere-egu22-1464, 2022.

09:17–09:22
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EGU22-5794
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ECS
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On-site presentation
Orkan Özcan, Ufuk Tarı, Gürsel Sunal, and Cenk Yaltırak

Coastal landscapes are dynamic sites, with their evolution strongly linked with sea level variations and tectonic activity produced intense faulting at different temporal and spatial scales. Geomorphological features in the coastal area, such as beachrock formations, can function as indicators of the coastal landscape evolution through time. However, mapping beachrocks on coastal areas is fundamental to study beach evolution and the vulnerability of low-lying coasts to erosion and waves. Also, high resolution coastal maps are going to be obtained by using air photogrammetry (Unmanned Aerial Vehicle-UAV) to construct the changing dynamics of the coastal geomorphology of the region in recent years. Moreover, the existence of beachrocks and monitoring them in far-field sites provide a good potential indicator of former sea level position. Such a case is the northern coast of the Sea of Marmara (Tekirdag-Altinova coastal area), hosting submerged beachrocks bordering low-lying coasts. However, our knowledge of the submerged beachrocks in the Sea of Marmara coasts is limited and scarce.

 

The Tekirdag-Altinova coastal area lies in the western Marmara Region, being part of the Sea of Marmara. The western coasts of the Marmara Region include a number of natural features inherited from their coastal evolution. Typically, the western coasts of the Marmara Region are composed of a sandy beach, bordered by a low lying beachrock, a coastal lagoon and an alluvial plain. Furthermore, in this region relative sea level (RSL) changes during late Quaternary and its vicinity are generally not homogeneous as a result of the tectonic activity controlled by the North Anatolian Fault Zone (NAFZ) that played a crucial role in the coastal evolution at different periods of the region.

 

The aim of the study is to define spatial extent of the beachrocks, and to collect high-resolution aerial photos of the coastline in the study area. For this purpose, we performed coupled detailed aerial surveys with UAV, analysis of aerial photogrammetry and morphometric analysis to study beachrock outcrops found down to 2 m below the present sea level with a ~5 km coastal extend. In particular, it was used to generate a dense point cloud and successively a high resolution Digital Surface Model (DSM) of submerged beachrocks. Hereby, Structure from Motion (SfM) photogrammetry technique was exploited to a low-cost and effective UAV derived imagery to achieve monitoring submerged beachrocks. Then, we further carried out one or more underwater transects to measure width and depth of the beachrock slabs and sampled seaward and landward parts of each beachrock slab. As a result of our analysis, we aim to better elucidate monitoring the submerged beachrocks in the nearshore of the Tekirdag-Altinova coastal area and provide new insight to the RSL evolution.

How to cite: Özcan, O., Tarı, U., Sunal, G., and Yaltırak, C.: Monitoring beachrock and low-altitude aerial photogrammetry-UAV in the northern coast of the Sea of Marmara, Turkey: A tool for coastal evolution and relative sea level change, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-5794, https://doi.org/10.5194/egusphere-egu22-5794, 2022.

09:22–09:27
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EGU22-10589
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Virtual presentation
Joel Johnson, Kristy Tiampo, Eduard Heijkoop, Michael Willis, and Steven Nerem

Over 10 percent of the worlds’ population lives less than 10 meters above sea level(McGranahan et al,. 2007), at risk for rising seas and sinking coasts. In addition, coastal inhabitants preferentially live in locations that are subsiding (Nicholls et al,. 2021), representing a flooding threat to people and infrastructure in coastal cities. Findings from the Intergovernmental Panel on Climate Change(IPPC) outline the risks and impacts of sea level rise on flooding and identify a knowledge gap regarding the combined effects with coastal subsidence. When drivers of subsidence combine, they can generate sinking rates of 6-100mm/yr, an order of magnitude larger than the 3-10mm/yr for sea level rise (Erkens et al., 2015). 

Access to C-band Synthetic Aperture Radar (SAR) data through the European Space Agency (ESA) Sentinel-1A/B satellites and the upcoming NASA-ISRO SAR (NISAR)  mission provides increased opportunities for differential interferometric synthetic aperture radar (DInSAR) monitoring. Here we provide results from a dockerized supercomputer workflow that rapidly generates DInSAR pairs from Sentinel-1 imagery using the JPL/Caltech/Stanford InSAR Scientific Computing Environment (ISCE)  processing software (Rosen et al., 2012) at ~10 meter resolution. Results from this workflow are used to create a time series of subsidence for Lagos, Nigeria, where rapid urban growth has led to accelerated subsidence throughout the city.

How to cite: Johnson, J., Tiampo, K., Heijkoop, E., Willis, M., and Nerem, S.: Mapping subsidence in Lagos, Nigeria with Sentinel-1A/B Satellite Radar, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-10589, https://doi.org/10.5194/egusphere-egu22-10589, 2022.

09:27–09:32
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EGU22-8682
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Virtual presentation
Jagat Dwipendra Ray, Walyeldeen Godah, Balaji Devaraju, and M Sithartha Muthu Vijayan

The GNSS (Global Navigation Satellite Systems) position time series contains various geophysical signals which can be grouped into tectonic and non-tectonic signals. The tectonic signals include the signals of crustal deformation, volcanic deformation, transient signals of the earthquake and even landslide. On the other hand, the non-tectonic signal contains contributions of various surface mass loadings induced by temporal mass variations within the Earth’s system. The effects of the tidal components of these temporal mass variations are generally get removed during routine GNSS data processing. However, the effects of non-tidal mass loading are typically removed in the post GNSS data processing stage. Therefore, a raw GNSS position time series provides an opportunity to study the sensitivity of a GNSS station towards various non-tidal mass loadings. The understanding of the effect of non-tidal mass loadings in coastal GNSS stations is very important as these coastal GNSS stations are generally used to constrain vertical land motions of Tide gauge stations.

The objective of this study is to investigate the effects of various non-tidal mass loadings, such as non-tidal ocean loading, non-tidal atmospheric loading, hydrological loading and sea level loading, in a few coastal GNSS permanent stations. The vertical GNSS position time series of these stations are obtained from the Nevada Geodetic Laboratory (NGL) and analysed using the seasonal decomposition method. The seasonal components of the GNSS position time series resulting from this analysis are assessed through surface deformations due to various surface mass loading effects provided by the German Research Centre for Geosciences (GFZ). Furthermore, the resulted seasonal components of the GNSS position time series are also compared with the corresponding ones obtained from Gravity Recovery and Climate Experiment/GRACE Follow-On (GRACE/GRACE-FO) satellite missions data. The results of these assessments and comparisons are analysed and discussed from the perspective of surface deformations induced by non-tidal mass loadings at coastal GNSS stations.

How to cite: Ray, J. D., Godah, W., Devaraju, B., and Vijayan, M. S. M.: Investigating the sources of surface mass loading signals in coastal GNSS permanent stations , EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-8682, https://doi.org/10.5194/egusphere-egu22-8682, 2022.

09:32–09:37
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EGU22-1721
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Virtual presentation
Hasanuddin Z. Abidin, Heri Andreas, Irwan Gumilar, Teguh P. Sidiq, Dhota Pradipta, and Bambang D. Yuwono

Land subsidence has been observed in several locations along Indonesia's northern coast of Java, most notably in Jakarta, Indramayu, Semarang, Demak, and Pekalongan. It could be caused by a combination of natural and anthropogenic processes, such as excessive groundwater extraction, natural consolidation of alluvium soil, building and construction load, and tectonic activity. Observations using various geodetic methods, including Leveling, GPS, and InSAR, show that typical subsidence rates of 3-10 cm/year have occurred and continue to occur at these locations. The rates vary both spatially and temporally. Coastal subsidence causes coastal inundation, flooding, and infrastructure sinking and cracking, resulting in significant infrastructure, economic, environmental, and social losses. Coastal flooding and inundation are typically exacerbated by high tides, high waves, and heavy rain. Given the significant impact of land subsidence in the coastal area on community life activities and regional development, sustainable disaster risk reduction management must be used to prevent and mitigate land subsidence. Furthermore, because this phenomenon persists, both the government and the community must continue to adapt to its consequences. This paper describes the observations and effects of land subsidence on Java's north coast, specifically in Jakarta and Semarang. Initiatives and programs to aid in prevention, mitigation, and adaptation will be proposed and discussed.

How to cite: Abidin, H. Z., Andreas, H., Gumilar, I., Sidiq, T. P., Pradipta, D., and Yuwono, B. D.: On the Disaster Risk Reduction of Land Subsidence in Indonesia's Northern Coastal Areas of Java, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-1721, https://doi.org/10.5194/egusphere-egu22-1721, 2022.

09:37–09:42
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EGU22-6617
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Highlight
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Virtual presentation
Robert Nicholls and Jiayi Fang

Land subsidence is impacting large populations in coastal Asia via relative sea-level rise. This paper quantitatively assesses the risks and possible response strategies for China from 2020 to 2050, focusing on observed changes in urban and delta areas where subsidence is largest. Using observed subsidence rates as scenarios, flood impacts are assessed with the Dynamic and Interactive Vulnerability Assessment (DIVA) model framework. Land area, population and assets exposed to the 100-year coastal flood event by 2050 are approximately 20%-39%, 17%-37% and 18%-39% higher than assuming climate change only scenarios. Realistic subsidence control measures can reduce this growth in exposure, leading to 7% more exposed land, 6% more population and 7% more assets than due to climate change alone. This emphasizes that subsidence control, combined with upgraded coastal protection, is a plausible and desirable adaptation response for coastal China.

Our results emphasise that subsidence is degrading China’s coastal environment quality and well-being. Subsidence is nationally significant as people preferentially live in the subsiding areas. Compared with natural subsidence occurring and accumulating over centuries and longer, human-induced subsidence is more local and is usually much more rapid. The effects of human-induced subsidence are visible over relatively shorter timescales (i.e., decades). It reduces the effective protection levels of dikes and amplifies the consequences of failure of flood protection infrastructure. For example, subsidence in Shanghai, has required the flood defence walls to be raised four times since 1959, amounting to more than a three metre raise, requiring large expenditure and also enhancing residual risk.

Subsidence can also lead to saline intrusion and water logging thus affecting water quality, ecosystem service and agriculture. In urban areas, subsidence is greater than in rural environments, due to greater groundwater withdrawal and lowering of water tables enhancing consolidation in geologically young sediments. Significant land subsidence and deformation is also observed in new coastal reclamations such as Hong Kong, Shenzhen, Shanghai, Tianjin, where critical infrastructure is often located, such as airports. New reclamations should expect subsidence and design for it.

In conclusion, this research shows it is essential to understand and address subsidence and resulting relative sea-level rise across coastal China. Traditionally, subsidence is considered a local problem. This study demonstrates subsidence has national implications and there is a need for a national policy response: a combination of subsidence control and adaptation (e.g. higher dikes). More detailed national and regional assessments of flooding and subsidence are recommended include the costs and benefits of management in the context of climate-induced sea-level rise. The issues raised in this paper have global significance, particularly in south, south-east and east Asia. Similar assessments across these Asian nations and more systematic collection of subsidence data would facilitate improved responses to this issue.

How to cite: Nicholls, R. and Fang, J.: Implications of subsidence for coastal flood risk and adaptation in China, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-6617, https://doi.org/10.5194/egusphere-egu22-6617, 2022.

09:42–09:47
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EGU22-2133
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ECS
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Virtual presentation
Sihui Li, Jie Dong, Lu Zhang, and Mingsheng Liao

The global mean sea level rise (SLR) is accelerating and has reached 3.2 mm/yr over the last decades. Combining with local ground subsidence, relative sea level rise (RSLR) rate will be dozens of times the global mean sea level rise in some areas with serious subsidence. The RSLR will lead to an increase in the frequency of floods and storm surges, salinization of surface and ground waters, coastal erosion, and degradation of coastal habitats, which will have a serious impact on coastal cities and low-lying areas.

In this study, we combine satellite altimetry data with time series interferometric synthetic aperture radar (InSAR) to capture the distribution of RSLR rates along China's coastline. The Sentinel-1 SAR data from nine ascending tracks covering China’s coastal areas from 2016 to 2020 are used for SBAS analysis to obtain ground subsidence within the 100 km buffer zone of China’s coastline. The line of sight (LOS) deformation is projected to the vertical direction based on the incidence angle. Then 33 GNSS stations from Crustal Movement Observation Network of China whose three-dimensional velocities are known within the inertial terrestrial reference frame (ITRF) are used to calibrate and validate the obtained InSAR ground deformation rates. We use satellite altimetry products from Copernicus Marine Environment Monitoring Service (CMEMS) to calculate the sea level change, and four tide gauges from the national marine data center are used for validation purposes. The ground deformation rates are combined with SLR rates to calculate RSLR rates.

The results show that significant ground subsidence has occurred in some coastal areas of China, including Dalian and Jinzhou in Liaoning Province, Lianyungang, Huai 'an and Yancheng in Jiangsu Province, Ningbo, Zhoushan and Wenzhou in Zhejiang Province, Guangzhou, Shenzhen and Zhuhai in Guangdong Province and so on. The subsidence in Tianjin, Tangshan, and Dongying are the most serious, with the maximum subsidence rate exceeding 200 mm/yr. Overexploitation of underground liquid resources such as water and oil is the main cause of ground subsidence in China's coastal areas. While in Shanghai, the ground subsidence has been effectively controlled with the decrease of groundwater exploitation and artificial recharge of aquifer systems.

The SLR rates in China's coastal areas are slightly higher than the global average, but the maximum is less than 6 mm/yr, which makes ground subsidence dominant in the analysis of RSLR and the distribution of RSLR is consistent with that of ground subsidence. Based on the profile analysis of RSLR along the coast, there are many places that have high RSLR rates due to ground subsidence, such as Tangshan, Tianjin, Dongying, Weifang, Lianyungang, Yancheng, Ningbo, Wenzhou, Zhuhai and so on, among which the RSLR rate in Dongying is close to 200 mm/yr. Understanding the distribution of RSLR can provide decision-making suggestions for the government’s urban planning of coastal cities.

How to cite: Li, S., Dong, J., Zhang, L., and Liao, M.: Ground subsidence and relative sea level rise in coastal areas of China, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-2133, https://doi.org/10.5194/egusphere-egu22-2133, 2022.

09:47–09:52
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EGU22-11861
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Virtual presentation
Tsung Ying Tsai and Kuo Hsin Tseng

        With the unique geological setting, Taiwan Strait was formed by shallow bathymetry and gentle topography composed of sandy substrate types. The depth of this area seldom exceeds 100 m, and it could be shallower than 20 m in the Taiwan Shoal area. Therefore, in recent years, there have been frequent cases of illegal sand dredgers around the central of Taiwan Strait. Apart from destroying marine ecology, the greatest problem of illegal sand pumping is the consequential retreat of the neighboring coastline.

        To address this problem, the objective of this research aims to take advantage of Synthetic Aperture Radar (SAR) technology in satellite remote sensing, and to monitor the spatiotemporal hotspots of unidentified vessels. SAR instruments have the advantages of superior penetration, high resolution, and independent from sunlight, making it a great tool for ocean object detection. This research uses Sentinel-1 SAR imagery as data source. We take Taiwan strait as study area and focused on Taiwan Shoal and the offshore of Matsu islands, which are the regions with higher number of cases of illegal sand dredging in recent years. The workflow is composed of four steps: image preprocessing, land masking, prescreening, and ship discrimination. Our preliminary results show that the developed algorithm can automatically detect targets over a specific size (>30 m), with an accuracy of >80% compared with the manually identified results. The hotspot of sand dredgers is changing in locations in the last three years, with the peak number occurred in 2019. It is concluded that Sentinel-1 SAR image has the ability to serve as a tool for ship detection.

How to cite: Tsai, T. Y. and Tseng, K. H.: Using Synthetic Aperture Radar Images to Monitor Sand Dredgers in Taiwan Strait, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-11861, https://doi.org/10.5194/egusphere-egu22-11861, 2022.

09:52–10:00