Detection of Land Subsidence using Sentinel-1 interferometer and its relationship with Sea-Level-Rise, Groundwater, and Inundation: A case study along Mumbai Coastal city

doi:10.21203/rs.3.rs-1392714/v1

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Detection of Land Subsidence using Sentinel-1 interferometer and its relationship with Sea-Level-Rise, Groundwater, and Inundation: A case study along Mumbai Coastal city

https://doi.org/10.21203/rs.3.rs-1392714/v1

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Mumbai, an amalgamation of seven Islands with distinct landforms, is being reclaimed for urban sprawl. It is India's financial capital, with a vast population and a large port for trade, owing to a high demand for working class. As one of the most densely inhabited cities in the world, it faces a significant seasonal water scarcity crisis, resulting in groundwater exploitation for domestic and industrial purposes. The two key consequences are land subsidence and the influence of sea levels on coastal communities. The current study looked at the rate of land subsidence and tried to figure out how groundwater exploitation affected it. The Sentinel-1 SAR imagery was gathered for this purpose, and during the months of October 2014 to May 2019. The findings show that land sinking is irregular and has no consistent pattern. However, the spatial pattern of land subsidence was more closely related to urban area than with other types of terrain. Between 2015 and 2019, the largest yearly subsidence rate observed with the Sentinel data was − 93 mm/yr where the mean is -28.8 mm/yr. Groundwater data from well observations showed a falling tendency over the same time period as well as over a longer time period. In addition, a study is being conducted to better understand sea level rise scenarios and their influence on coastal inundation in low-lying locations. According to the observed sea level scenarios, the upper regional sea level will rise 0.7 m, 0.9 m, and 1.06 m by 2055, 2085, and 2095, respectively. Whereas for RCP recent emission scenarios the highest SLR observed at 1.2 m. Furthermore, with an increase in 1 m SLR, nearly 1700 sq km of low-lying areas, or nearly 38 percent of total land, could be swamped by 2095 during a regular monsoon. Regrettably, if urban infrastructure continues to expand, current conditions will be undermined. Therefore, it is high time to address the land subsidence and its consequences for the solutions.

Land subsidence

sea-level-rise

ground water

coastal inundation.

Since last few decades, sea-level-rise (SLR) due to climate-change has been a major challenge throughout the world. Coastal plains, deltas, estuaries and coastal ecosystems are vulnerable to regional land subsidence phenomenon as it plays a vital role in lowering of surface elevation that contributes to relative sea level rise and its impact (Tosi et al. 2018). Climate change has been the major driver for sea level rise leading to coastal land loss, however, the emphasis in most parts of the world is put upon hazards and post hazard impacts associated with it, whereas land subsidence is not considered as a prominent factor currently. Primarily, erosion/accretion, flood, coastal ecosystem sensitivity, cyclone and storm surge catastrophes are considered as the major indices for coastal vulnerability assessments. During the last three decades salt-water-intrusion (SWI) into coastal aquifers and coastal land-subsidence (LS) were acknowledged to this list. Understanding the subsidence-induced changes in these landscapes can be a breakthrough in sustainable land use, flood mitigation and restoration plans, further reducing the socio-economical risks along the coasts (Syvitski et al. 2009; Tosi et al. 2018).

Further, owing to increase in the population with respect to economic, industrial, and social developmental activities, these coastal cities are subjected to anthropogenic hazards. Wang et al. 2012, pointed out that, the majority of the coastal population resides in 17 of the world’s largest cities and Mumbai is one of those major cities. Coastal cities always remain under active development primarily due to human activities. The causes of subsidence in cities are very diverse as the forms of failure, and include dewatering of organic soils, dissolution in limestone aquifers, first time wetting of moisture-deficient low-density soils, natural compaction, liquefaction, crustal deformation, subterranean mining, and withdrawal of fluids (groundwater, petroleum, geothermal) (Malik et al. 2019). The Intergovernmental Panel on Climate Change (IPCC) technical report (Field et al., 2014) suggested that, due to loads of buildings, dredging, sediment variations in terms of erosion/accretion causes sediment compaction and may contribute to regional Relative-Sea-Level-Rise (RSLR).

These are also heterogeneous areas with a wide variety of habitats that can accommodate major changes in local species in response to regional and global influences. However, rapid urbanisation and economic development increase the risk factor for coastal habitat. As per the Intergovernmental Panel on Climate Change (IPCC 1995; IPCC 2007, IPCC 2018) reports consistently stressing the fact that ongoing global climate change will cause the sea level to rise in coastal areas, whereas the land subsidence and storm surges will result in the permanent flooding of low-lying areas, inland extension of episodic flooding, increased beach erosion, and saline intrusion (Hallegatte et al., 2011; McLean and Tsyban, 2001). Over the last two decades, detection and mapping of land deformation with the satellite-based sensors have been increasingly in use. The fact that satellites provide advances in spatial, temporal coverage and support continuous monitoring of the region, they are highly recommended. Synthetic Aperture Radar (SAR) sensors with reduced atmospheric disturbances and increased computational capabilities have become most sought out data type for such studies (Raspini et al. 2018). DInSAR technique specifically made the land deformation studies progress for a long period of time and covered wide regions. Teatini et al., 2012 showed a maximum of 5 mm/yr subsidence along the lagoon margins of Venice using the ERS-1/2 and ENVISAT SAR imagery. Qu et al. 2014 studied the Xi'an province in China using Envisat ASAR, ALOS PALSAR, TerraSAR-X satellite data, and found that surface deformation is happening at a rate of ~ 50 mm/yr along the region. Bonì et al., 2015 used DInSAR technique to study the land subsidence along southeast Spain and demonstrated that the subsidence along the region is due to groundwater over exploitation for a prolonged period. Hu et al., 2016 used ENVISAT ASAR data along the Los Angeles, USA and showed the land subsidence in the range of − 2.6 to − 4.8 cm/yr on East side.

Groundwater exploitation results into varied hazardous environmental concerns. For example, loss of ecosystem, land subsidence, infrastructure damage and climate change imbalance (Whiteman et al. 2010; Ahmad et al. 2019). Groundwater extraction induced land-subsidence is becoming major concern across the globe (Teatini et al. 2011; Wang et al. 2012; Erban et al. 2014; Ingebritsen and Galloway 2014; Qu et al. 2015; Hu et al. 2016). During the years, there have been several techniques used to measure Land subsidence, such as, GPS, LiDAR, Interferometric Synthetic Aperture Radar (InSAR) and general surveying (Phien-wej et al. 2006; Ganguli 2011; Sahu and Sikdar 2011; Bouchahma and Yan 2012; Qu et al. 2014, 2015; Thoang and Giao 2015). These studies that particularly used borehole and water well data revealed a distinct relation between falling groundwater levels and subsidence. Traditional methods such as borewell observations were employed by many to study the land subsidence due to groundwater exploitation (Example: Hung et al., 2012; Phien-wej et al., 2006; Sahu and Sikdar, 2011). Church, et al., 2013 showed that land subsidence rates in fact are greatly exceeding regional SLR (global mean as of 2013: 0.32 cm/yr). Famous coastal examples include Venice, Tokyo and Bangkok, portions of which have subsided in response to groundwater extraction while Jakarta being the major one of all. These conventional studies are limited to small spatial coverage. However, the validation or correlations combined with the available satellite data can give the information for a larger area extent.

Submergence of coastal regions should not be necessarily due to SLR only. The major factor driving this is anthropogenic interventions like over-pumping of groundwater, extraction of oil/gas, overloaded built infrastructure with it’s over population and soil loss (Example: Carbognin et al., 2004; Castellazzi et al., 2016; Yuill et al., 2009). The primary challenges due to LS are shoreline retreat, coastal inundation, relative sea level rise and even increase in storm surge affects along the coastal region.

Most of the coastal cities in the world are densely populated due to their opportunities, ease of trading and resources. Especially India with high populace and its need have preceded to expanding utilization of the natural resources and is becoming vulnerable to sea level rise as well as land subsidence. While, sea level rise vulnerability is a global phenomenon owing to the climate change, land subsidence is due to sediment compaction resulting from over exploitation of natural resources like oil, gas and water from ground. In India, the unawareness of impacts due to over exploitation is the major reason. Since decades unrestrained groundwater extraction for domestic, agricultural, and industrial use resulted in depletion of groundwater, consequently leading to sediment compaction. In Mumbai city, the sinking is further stressed due to higher population, poor urban planning, intense traffic, and perennial growth of concrete buildings. The focal point of India’s largest economy has seen rapid development over the years pushing the land further down. However, the most concerning aspect is sinking due to vertical deformation of land which is exacerbating the effect of sea level rise. Here we present an assessment of land subsidence along the Mumbai coastal region and its surroundings to assess the future risk in terms of land subsidence, sea-level-rise and population.

This study is the first attempt to estimate rates of land subsidence due to groundwater exploitation along Mumbai coast as well as to study the future scenarios. The outcome will be useful for the policy makers and stack holders to take necessary actions and reduce risk.

Mumbai, the highly urbanised largest tropical coastal city and epicentre of technology development, economy, and infrastructure growth, located at 18°58'N latitude and 72°50'E longitude along west coast of India (shown in Fig. 1). Under the Köppen climate classification system Mumbai is further classified as a tropical wet and dry (Aw) climate. Mumbai is known as the largest commercial and financial capital for India and has the biggest port along West coast of India. According to United Nations, Department of Economic and Social Affair (UNDESA 2016) report, the city with population 16.4 million in 2001 has seen a growth of 21.3 million in 2016 and projected to increase up to 27.79 million by 2030. In Mumbai, seasonal water scarcity is the major problem that is being dealt with every year followed by inundation due to rainfall. Mumbai receives water from four major river basins, six lakes and groundwater for domestic and industrial use (Safe water network report, Chauhan and Sewak, 2016). However, demand is always exceeding supply particularly along industrial locations, multi-storeyed buildings, and low developed regions. This in turn is risking the socio-ecosystem leading to groundwater exploitation at sensitive locations along the coast. Population growth on the other hand is leading to land reclamation from wetlands, forests, and other eco-sensitive regions to transform them into built-up areas. Together, all these forces lead to land subsidence and increase the risk rate to many factors including inundation along the coast.

The present study uses different types of data for the evaluation (Table 1). The idea is to use freely available SAR data from Sentinel to analyse the land subsidence locations. Both borehole and well data from Central Ground Water Board (CGWB) are used for the study and validation purpose. The Sentinel satellite characteristics and details of master and slave images considered were summarized in Table 2 and Fig. 2.

Table 1

Land subsidence monitoring data types
Method	Type of data	Spatial coverage	Temporal detail	Data
Borehole observation data	Aquifer-system thickness at one location, continuous record (Point data)	Low	High	Bore well and Dug well
Tidal	Sea elevation at one location, continuous record (Point data)	Low	High	Tide gauge data
Altimetry	Sea surface height	High	Moderate
Remote sensing (InSAR)	Land elevations over a wide area, at multiple times (Spatial data)	High	Low	Sentinel 1A

Table 2

Properties of Sentinel-1 Interferometric Wide (IW) Single Look Complex (SLC)
Spatial Resolution	5 m (ground range) x 20 m (azimuth)
Pixel Spacing	2.3 m (slant range) x 14.1 m (azimuth)
Incidence Angle	29°–46°
Polarisations	HH + HV, VH + VV, HH, VV
Total Swath Width	250 km

Developed by European Space Agency (ESA), Sentinel-1 is a space mission in Copernicas program framework. Sentinel-1A was launched in 2014 with four different modes of SAR image captures. The vertical displacement assessment needs to have phase and coherence which is captured in one of the SAR images known as Interferometric Wide (IW) mode, besides this is the only swath mode over the land. The IW with a swath 250 km creates three sub-swaths with separate Single Look Complex (SLC) images called burst at a 5m x 20m resolution (Source: https://sentinel.esa.int/web/sentinel/user-guides/sentinel-1-sar).

4.1 Land Subsidence from InSAR: For the present study, to evaluate the land subsidence along Mumbai, we used collection of Sentinel-1 satellite data from October 2014 to May 2019. As mentioned in the above data section, we used 20 Sentinel-1A IW SLC images and are acquired from 10th June 2014 to 2nd October 2019. By using two SAR images and applying D-InSAR technique, surface displacement is measured. DInSAR uses interferometric technique to measure the phase difference of two images at different acquisition times. This phase difference between two interferometry (δϕ_int) SAR images can be expressed as follows (Bhattarai et al. 2017):

$${\delta ɸ}_{int}={\delta \varphi }_{flat}+ {\delta \varphi }_{topo}+ {\delta \varphi }_{disp}+ {\delta \varphi }_{noise}+ {\delta \varphi }_{atm}$$

where, δϕ_flat is the ideal flat earth assumption,

δϕ_topo is the topographic height information,

δϕ_disp is the phase difference from ground displacement along the slant range,

δϕ_noise is the noise from the radar,

and δϕ_atm is the atmospheric effect (Bayuaji et al. 2010; Bhattarai et al. 2017).

Sentinel Application Platform (SNAP) tool is used to process the data and the flowchart for the same is shown in Fig. 3. Each Sentinel SLC image consists of three IW SLC images with three sub-swaths each (IW1, IW2, IW3). Again, each sub-swath consists of nine images called as bursts. To process the image, these IW swath images are split into individual images, de-burst to demarcate and then merged to get a seamless image. The next step, co-registration is a crucial one to align the slave images with selected master images. This ensures that ground target in both master and slave images contribute to the same range and azimuth pixels. The interferogram thus generated will have errors due to topographic variation, spatial and temporal decorrelation, atmospheric variation, and signal-to-noise during data acquisition. Therefore, Shuttle Radar Topography Mission (SRTM) data derived DEM was used to for the topographic phase removal. Whereas, Goldstien-filtering techniques (Goldstein and Werner 1998) is used to remove the phase-to-noise in the radar signal of the interferogram. The obtained image is then unwrapped to get the final land-subsidence image.

4.2. GPS measurements for validation:

The Global Positioning System (GPS) measurements at sites located along the complex tectonic boundaries has been in use for geo-scientific studies like deformation estimates. A continuous GPS monitoring stations in IITB (Indian Institute of Technology Bombay) is used in this study to monitor land-surface deformation for the year 2018 to validate the INSAR process outcome. The station is installed at the ground level to provide regular and frequent observations for civil surveying. Monitoring signals and observation data were transmitted to a remote server through the Internet.

The epoch interval was 30 seconds, with a 15-degree elevation cut-off, similar with standard GPS survey techniques. The GAMIT/GLOBK application was used to calculate GPS station movement in relation to a few IGS stations. GAMIT/GLOBK (http://geoweb.mit.edu/gg/) is a comprehensive suite of programmes developed by MIT, Scripps Institution of Oceanography, and Harvard University for analysing GPS measurements, primarily to examine crustal deformation. Nine IGS stations (BAKO, COCO, DGAR, HYD, IISC, KARR, LCK3, LHAZ, POL2) that operate in the neighbouring areas/standard stations were included in the processing to serve as connections with the International Terrestrial Reference Frame ITRF96 (Boucher, Claude ; Altamimi, Zuheir ; Patrick 1999). For antenna phase corrections, we used IGS final orbits, IERS Earth rotation parameters, and IGS tables.

4.3. Groundwater:

The Central Ground Water Board (CGWB) collects the groundwater data from both Dug well as well as Bore well. Since the data collected is for the groundwater levels and its chemical analysis, the Land subsidence rates has to be evaluated indirectly from groundwater depth variations (Riley, 1969). However, the lack of availability of continuous data on hydrogeological parameters like aquifer layer thickness and specific storage on a regular basis has limited the current study to correlate the land subsidence with the groundwater depletion throughout the years.

According to CGWB report, Mumbai region groundwater is not to be used for domestic usage, therefore it is supplied only for the industrial purpose. However, to meet the demand every year more bore-wells are being dug (Safe water network report, 2016, Chauhan and Sewak, 2016). Managed by the Brihanmumbai Municipal Corporation (BMC) and Government of Maharashtra (GoM), there is a large restriction to withdraw the groundwater for industrial purpose as well to mitigate the saline water intrusion along the coast. The CGWB reports the Mumbai aquifer system as semi-confined and confined conditions, while few deeper aquifers are in leaky confined condition as well. The major issue concerning the groundwater in Mumbai is due to sewage water pollution into the creeks and industrial effluents (Naik et al. 2007).

4.4. Sea-level-Rise:

Unnikrishnan and Shankar, 2007 showed variabilities of SLR along different coastal regions, for example: Mumbai net SLR (during 1878–1993) is 1.20 mm/yr, Kochi (during 1939–2003) is 1.75 mm/yr, Visakhapatnam (during 1937–2000) is 1.09 mm/yr, whereas Diamond Harbour (during 1948–2004) is 5.74 mm/yr. However, the reason for these variations is tide gauge systems that cannot distinguish between rising sea level and land subsidence. Consequently, RSLR is combined elevation of actual SLR with regional LS (Eggleston and Pope 2013). Subsidence significantly complicates regulation of accurate levelling and misrepresents the future sea-level rise prediction (Davis, 1987).

Sea level rise along the Mumbai coast has shown increasing trend by both tide-gauge data, as well as Altimetry data (Unnikrishnan et al. 2015). As per the PSMSL data, the monthly mean SLR has been observed as shown in Fig. 4.

Sea-level-Rise Scenarios: Nicholls et al. (2011) provided the guidelines to derive RSLR scenarios linking with IPCC SRES scenarios: B1, B2, A1B, A1T, A2 and A1F1 (Church et al. 2013, IPCC report). In this approach, RSLR projections for a specific location accounts contribution of different factors at the global, regional and local scales.

These components are then integrated using following equation:

$$\varDelta RSL={\varDelta SL}_{G}+ {\varDelta SL}_{RM}+ {\varDelta SL}_{RF}+ {\varDelta SL}_{VLM}$$

where :

ΔRSL is the change in relative sea level

ΔSL_G is the change in global mean sea level

ΔSL_RM is the regional variation in sea level from the global mean due to meteo-oceanographic factors

ΔSL_RG is the regional variation in sea level due to changes in the earth’s gravitational field

ΔSL_VLM is the change in sea level due to vertical land movement

The scenarios are characterised with different assumptions. A1 is the region with rapid economic growth with extensive social and cultural interactions, higher population and new technologies. A2 scenario represents an independently operating state/regions with increasing population, high emissions and self-reliant. B1 represents rapid economic growth but with rapid changes in service and information economy, population growth rate rising and then declining as in A1, an emphasis on global solutions to economic, social and environmental stability. B2 scenarios are characterised by increasing population but at slower rate, intermediate levels of economic development, social and environmental stability, and less rapid technologies than the above scenarios. F1 is the fossil intensive region

The current study carried out the scenarios B1 and A1F1 as the Mumbai city comes predominantly under these two categories by using the methodology provided by Nicholls et al. 2011.

5.1 Land subsidence from InSAR: The land subsidence occurrence was monitored for a period of 61 months with twenty interferograms along Mumbai city. Normalised histograms are shown in Fig. 5 for six selected interferograms. The x-axis in the figure shows subsidence measured from the reference image whereas the y-axis shows the frequency of subsidence. The histograms in the figure are depicting the bimodal pattern, which implies subsidence rate is uneven throughout the period. Furthermore, the subsidence values for individual histogram has extended up to a maximum of -134 mm/yr, however, whereas the vertical uplift up to 75 mm/yr is also observed. However, the histogram shows, the number of pixels with maximum values are very low. The range can be considered from − 93mm/yr to 55mm/yr, with reasonable number of pixels. Further,, a reference value with a threshold must be taken for steady results in future.

Considering land subsidence resulting due to groundwater withdrawal and urbanisation with higher population, the current vertical displacement may be combined effect of all these parameters. The spatial distribution of land subsidence for Mumbai is shown in Fig. 6. The maps show higher rates of subsidence at few locations including Byculla dockyard area, Colaba, Churchgate, Kalba Devi, Karla, Andheri East, Mulund, Nahur East, Sonapur, part of Janata nagar, part of Worli area, Dadar, Wadala, Anushakti Nagar and Govandi slums. Overall, the vertical displacement rate for the study region varies between − 93 mm/yr to 55 mm/yr with an average land subsidence value of -28.8 mm/yr.

5.2 Groundwater: Land subsidence is primarily related to the groundwater levels below ground and its over exploitation. The seasonal water level below ground level from well data were observed for a long period to understand the groundwater variations. A groundwater declining trend has been observed for the period 1996 to 2018 as shown in Fig. 8. These well locations at Churchgate, Colaba and Mahim are showing subsiding land. Furthermore, the higher stress is observed along the regions where the construction and industries were located Fig. 7(a). This was observed using Land Use Land Cover (LULC) mapping with Landsat and identifying the urban locations from Google Earth imagery Fig. 7(b).

5.3 GPS measurements: Because this study used GPS data to observe land subsidence, only 8 other GPS stations were considered for quantification to reduce the processing time. Figure 8 depicts the GPS vertical component, for the Mumbai station (IITB station). According to Fig. 7, IITB station shows vertical uplift. IITB station baseline uncertainty is acceptable as the horizontal components do not exceed 5 mm level (shown in Fig. 8). The time-series plot in the figure shows north offset rates of ~ 33.94 mm/yr and East offset rates of ~ 34.09 mm/yr. This means that the station movement is to the North East side.

The angular velocities and deformations along the Indian plates were studied by Jade et al. 2017 using data from the IITB station. According to their findings, the GPS velocities for North and East were 34.05 mm/yr and 39.14 mm/yr, respectively. This slight discrepancy for higher adjustments in comparison to Table 3 (results) may be due to missing and shorter duration data in the current study. The velocities may be comprehended with time-series data spanning multiple years.

Table 3

GPS-derived vertical velocity rates for IITB, Mumbai station
Station	IITB
Longitude (deg.)	72.91626
Latitude (deg)	19.13256
East velocity (Ve mm/year)	33.27
North Velocity (Vn mm/year)	33.77
Up offset velocity (Vh mm/year)	15.69
σVe (±)	0.63
σVn (±)	0.78
σVh (±)	0.56

Furthermore, the spatial distribution maps (from Sentinel data) of land subsidence (/uplift) in Fig. 6 reveal that the IITB GPS station location does not show any subsidence for the year 2018, which is consistent with the positive velocities derived from the GLOBK data.

The study for the subsiding regions cannot be correlated here due to lack of GPS stations at those specific zones. However, the vertical deformation analysed from sentinel data ranged between − 30.66 mm/yr to + 48.79 mm/yr in 2018; while the range for IITB GPS region in that year is + 10 to + 20 mm/yr. Therefore, the current GPS observations may validate that the InSAR spatial distribution maps are reliable, relying on GPS data that revealed land deformation of + 13.78 mm/yr.

Multiple years of continuous data could have enhanced the GPS estimates in this investigation. Furthermore, because the site along the coast is a dynamic zone, use of the ocean tidal loading parameter for the location could improve the results.

5.4 Sea-level-rise (SLR) and Future Scenarios SLR: Land subsidence acts as positive feedback to sea-level-rise exacerbating the flooding conditions at any given location. At a global scale SLR acceleration of 3 mm/yr are reported (Nerem, et al., 2018). However, at a regional level, SLR may vary due to land subsidence, sedimentation, elevation, and anthropogenic intervention into coastal ecosystem. The land subsidence associated with SLR has a major impact on coastal flooding and saltwater ingress into groundwater thus increasing the coastal vulnerability. Therefore, when one prepares a policy for a developed coastal city, land subsidence should be considered as one of the parameters with respect to SLR. For the current to comprehend climate change and sea level rise, the recent IPCC working group report (Oppenheimer et al. 2019) on sea level rise scenarios, which are known as Representative Concentration (RCP) Scenarios are employed. As per the IPCC reports, these RCPs range from very high (RCP8.5) to very low (RCP2.6) concentrations. As illustrated in Fig. 10, the mean SLR for 2021 for these new scenarios might rise by 0.9m (for RCP2.6) to 1.2m (for RCP8.0), which are higher than the previous reported IPCC scenarios.

5.5 Inundation Scenarios: Considering the SLR scenarios (Church et al. 2013, IPCC report) according to RCP4.5 the inundation extent is foreseen for the years 2150 (0.5m rise in sea-level) and 2100 (1m rise in sea-level). These scenarios are preferred as they are normal reductions in global warming and emission. The limitation for these projections is, they do not consider the effects of storm-surge and rainfall periods which are very important while studying the flooding across coastal regions. These inundation maps are prepared using SRTM DEM superposed with SLR and local land-subsidence. Figure 11 shows the inundation vulnerability extent for the study area due to SLR and combined land-subsidence. The total area (sq. km) vulnerable due to SLR scenarios are provided in Table (4), Fig. 12.

Table 4

Inundation area (sq km) due to SLR scenarios
Flood prone region	Area (sq km)
Mumbai total area	4355
For current SLR and elevation	1500.128823
For a 0.5 m rise in sea-level	1583.2153
For 1 m rise in sea-level	1689.410786

5.6 Population: Groundwater extraction increases with increase in population and rapid urbanisation, which further leads to severe land subsidence. The regions with industrialisation demand additional water supply thus leading to further groundwater exploitation. Therefore, one can say that population growth and urbanisation act as major driving force for the land subsidence. Whereas, when it comes to risk rate, higher the population, larger the coastal risk/hazard would be. United Nations-World Population Prospects (https://population.un.org/wpp/Graphs/), provides the population growth rate during the period 1950 to 2020 and its future projections for next 15 years as shown in Fig. 13. This data has been collected from macrotrends(http://www.macrotrends.net/) webpage. Here, though the growth rate has demonstrated a dynamic trend, the figure depicts population increasing consistently.

Further, groundwater extraction increases in tandem with population growth and fast urbanisation, resulting in significant land subsidence. As a result of the increased demand for water in industrialised areas, more groundwater is being exploited. Therefore, population increase and urbanisation may well be considered as key driving forces behind land subsidence. When it comes to risk rate, larger the population, greater the coastal risk/hazard. Figure 13 shows the population growth rate from 1950 to 2020, as well as forecasts for the next 15 years. Whenever there is an absolute rise in population near the coasts, land subsidence occurs. For the present study social parameters were not collected extensively to create a social vulnerability map for each individual block. However, the demographic database indicates that the study region's social vulnerability is exceptionally high as a result of land subsidence and the SLR impact on population and growth.

The current research is being conducted along Mumbai coast, India, to measure the rate of land subsidence using the InSAR technique. Sentinel-1 SLC imagery were obtained for this purpose, and the DInSAR approach has been used to the images over a 61-month period. The spatial distribution pattern revealed uneven subsidence at several places, with a maximum subsidence of -93 mm/yr and an average annual subsidence of -28.8 mm/yr. These InSAR land subsidence estimates are the first of its kind for Mumbai region, and therefore, there is no literature available to corroborate. Furthermore, groundwater levels have been monitored for a long time and have shown a declining trend. Due to a prolonged decline of groundwater in the area that plays a crucial role in land subsidence along the coast, a considerable relationship between land subsidence and groundwater decline can be established over the regions. With this declining groundwater, high-rise buildings, and metro development projects, the study area is becoming increasingly vulnerable to subsidence, leading to increased inundation and vulnerability.

SLR scenarios with regional land-subsidence were examined, and it has been found that by 2095, the SLR might rise by 1.06m/1.2m in rapid economic growth /high emission scenarios. These scenarios are then incorporated into the Mumbai elevations to determine the extent of inundation, with the findings indicating that almost 38% of land will be inundated by 2095 during a normal rainfall. This is a severe issue that has to be addressed immediately.

However, with the declining groundwater levels Due to a prolonged decline of groundwater in the area and its influence on land subsidence is a well-known concept already. Therefore, a considerable relationship between land subsidence and groundwater decline can be established over the regions.

Coastal subsidence has put many countries in a precarious position. Mumbai, with its rapidly increasing economy, diverse ecosystem, large special economic zone, and urban growth, has to be closely monitored in order to mitigate and adapt to coastal vulnerability. For investigating subsidence rates over longer spatial distances, InSAR techniques are useful resources.

The study's limitations include a lack of comprehensive direct archival databases and validation literature on land subsidence for the studied region. Rising sea levels and its affects can also reduce the asset value of property owners, industries and corporate credit. Furthermore, there are still greater challenges in financing, markets, insurance regulations, technology and decision-making ignorance; and incorporating the climate-risks into regulatory frameworks are utmost challenging for economists as well for coastal cities like Mumbai. In order to combine science with socioeconomic repercussions, the city future planning must integrate ecosystem conservation, flood mitigation, and infrastructure development, as well as consistent subsidence measurements and modelling across the city. Therefore, there is an urgent need of improving the technological requirements for such studies, like installation of GPS monitoring stations and collecting continuous hydro-geological parameter measurements can improve the current study and enable policymakers and stakeholders in making better decisions.

We acknowledge the ESA Copernicus data hub for the provision of Sentinel–1 and Sentinel–2 data, we also extend our gratitude to Prof. Milind A. Sohoni, Indian Institute of Technology Bombay for providing the groundwater table in and around Mumbai. I would like to thank Siva Sai Kumar, CMMACS for the guidance to run the GAMIT. Finally, to the Indian Institute of Technology Bombay for providing the necessary facilities and research fellowship to carry out this work.

Both the authors contributed to the study conception. The project was designed by the first author. Material preparation, data collection and analysis were performed by Dr N N V Sudha Rani and Prof. Manasa Ranjan Behera. The first draft of the manuscript was written by Dr N.N.V Sudha Rani and all authors commented on previous versions of the manuscript. All authors read and approved the final manuscript.

Ethics declaration: This article has no conflict of interests to the best of my knowledge, as well as no financial or non-financial interests to disclose. Further, this manuscript has not been previously published and is not under consideration in the same or substantially similar form in any other peer-reviewed media.

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Detection of Land Subsidence using Sentinel-1 interferometer and its relationship with Sea-Level-Rise, Groundwater, and Inundation: A case study along Mumbai Coastal city

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Abstract

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1. Introduction

2. Study Area

3. Data

4. Methodology

4.2. GPS measurements for validation:

4.3. Groundwater:

4.4. Sea-level-Rise:

5. Results And Analysis

6. Conclusion

Declarations

References

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