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Subsidence, the lowering of Earth's land surface, is a potentially destructive hazard that can be caused by a wide range of natural or anthropogenic triggers but mainly results from solid or fluid mobilization underground. Subsidence due to groundwater depletion (1) is a slow and gradual process that develops on large time scales (months to years), producing progressive loss of land elevation (centimeters to decimeters per year) typically over very large areas (tens to thousands of square kilometers) and variably affects urban and agricultural areas worldwide. Subsidence permanently reduces aquifer-system storage capacity, causes earth fissures, damages buildings and civil infrastructure, and increases flood susceptibility and risk. During the next decades, global population and economic growth will continue to increase groundwater demand and accompanying groundwater depletion (2) and, when exacerbated by droughts (3), will probably increase land subsidence occurrence and related damages or impacts. To raise awareness and inform decision-making, we evaluate potential global subsidence due to groundwater depletion, a key first step toward formulating effective land-subsidence policies that are lacking in most countries worldwide.
By Gerardo Herrera-García1,2,3, Pablo Ezquerro1,4, Roberto Tomás2,5, Marta Béjar-Pizarro1**,
Juan López-Vinielles1,6, Mauro Rossi7, Rosa M. Mateos1,3, Dora Carreón-Freyre2,8, John
Lambert2,9, Pietro Teatini2,10, Enrique Cabral-Cano2,11, Gilles Erkens2,12,13, Devin Galloway2,14, Wei-
Chia Hung2,15, Najeebullah Kakar2,16, Michelle Sneed2,17, Luigi Tosi2,18, Hanmei Wang2,19, Shujun Ye2,20
Subsidence, the lowering of Earth’s
land surface, is a potentially destruc-
tive hazard that can be caused by
a wide range of natural or anthro-
pogenic triggers but mainly results
from solid or fluid mobilization un-
derground. Subsidence due to groundwater
depletion (1) is a slow and gradual process
that develops on large time scales (months
to years), producing progressive loss of land
elevation (centimeters to decimeters per
year) typically over very large areas (tens
to thousands of square kilometers) and
variably affects urban and agricultural ar-
eas worldwide. Subsidence permanently
reduces aquifer-system storage capacity,
causes earth fissures, damages buildings and
civil infrastructure, and increases flood sus-
ceptibility and risk. During the next decades,
global population and economic growth will
continue to increase groundwater demand
and accompanying groundwater depletion
(2) and, when exacerbated by droughts (3),
will probably increase land subsidence oc-
currence and related damages or impacts. To
raise awareness and inform decision-mak-
ing, we evaluate potential global subsidence
due to groundwater depletion, a key first
step toward formulating effective land-sub-
sidence policies that are lacking in most
countries worldwide.
A large-scale systematic literature review
reveals that during the past century, land
subsidence due to groundwater depletion oc-
curred at 200 locations in 34 countries [see
supplementary materials (SM)]. However,
subsidence extent is only known for one-
third of these records, information on the
impacts is scarce, and mitigation measures
were implemented only in a few locations. In
China, widespread subsidence affects cities
developed in the main sedimentary basins.
In Indonesia, coastal subsidence in Jakarta
is so severe that government authorities are
planning to move the capital to the island of
Borneo. In Japan, subsidence affected sev-
eral cities during the 20th century, includ-
ing more than 4 m of subsidence in Tokyo,
before groundwater management practices
mitigated further subsidence. Iran currently
hosts some of the fastest-sinking cities in
the world (25 cm year--1) because of unregu-
lated groundwater pumping. In Europe, the
greatest impact of subsidence occurs in the
Netherlands, where subsidence is primarily
responsible for placing 25% of the country
below the mean sea level and increasing the
flooding risk. Subsidence in the Po River
Plain in Italy started during the second half
of the 20th century and currently threatens
30% of the Italian population, contributing
to recurrent coastal flooding during extreme
high tides in Venice. In North America, in-
tense groundwater depletion triggers sub-
sidence from California’s Central Valley,
with as much as 9 m of subsidence in the
past century, to the Atlantic and Gulf of
Mexico coastal plains in the United States,
where subsidence is increasing flooding risk.
In México, subsidence rates are among the
highest worldwide (as much as 30 cm year-1),
affecting small structurally controlled in-
termontane basins where the main urban
centers developed, causing an important but
unaccounted economic impact.
Spatial analysis of subsidence locations
identified in our global database (see SM)
reveals that subsidence has preferentially
occurred in very flat areas where unconsol-
idated sediments accumulated in alluvial
basins or coastal plains, and where urban
or agricultural areas developed in temperate
or arid climates characterized by prolonged
dry periods. Land subsidence has generally
occurred in water-stressed basins, where the
combination of groundwater withdrawal and
natural groundwater discharge outpaced
groundwater recharge, resulting in ground-
water storage losses, groundwater depletion,
and compaction of susceptible aquifer sys-
tems. In the affected basins, land subsidence
mainly occurred in highly populated areas,
with half of documented occurrences in ar-
eas susceptible to flooding. In coastal zones,
the combined effects of absolute sea-level
rise and land subsidence contribute to rela-
tive sea-level rise (4). The contribution from
land subsidence may exceed the contribu-
tion from absolute sea-level rise by a factor
of 10 or more and could be especially critical
for 21% of the geographic locations identified
in our database, where land elevation is less
than 1 m above the mean sea level.
On the basis of the spatial analysis find-
ings, a global model is proposed to combine
the main variables influencing subsidence to
identify environmental settings favoring land
subsidence and the anthropogenic factors
leading to groundwater depletion (see SM).
Statistical analyses of lithology, land-surface
slope, land cover, and Koppen-Geiger climate
classes are used to predict global subsidence
susceptibility at a spatial resolution of 1 km2.
The probability of groundwater depletion
is estimated by identifying urban and irri-
gated areas suffering water stress and where
groundwater demand is high.
The analyses do not consider subsidence
magnitude and rate, owing to the lack of
this information at a global scale. Hence,
the combination of subsidence susceptibility
and the probability of groundwater deple-
tion is used to predict a “proxy” of subsid-
ence hazard, which permits identification of
exposed areas where the probability of land
subsidence occurrence is high or very high.
Even though these results do not necessarily
translate to direct impacts or damages, they
are useful for identifying potential subsid-
ence areas where further local-scale analysis
is necessary. The comparison of our model
predictions with an independent validation
dataset reveals a 94% capability to distin-
guish between subsidence and nonsubsid-
ence areas, according to the value of the area
under the receiver operating characteristic
curve (see SM). The global exposure to po-
tential subsidence is evaluated by calculating
the number of inhabitants living in potential
subsidence areas, i.e., subsidence hazard
proxy, and the equivalent gross domestic
product (GDP). This “proxy” of exposed
assets is calculated assuming that GDP per
capita is homogeneous within each coun-
try. Finally, the evolution of potential global
subsidence and the related exposure is pre-
34 1 JANUARY 2021 • VOL 371 ISSUE 6524 SCIENCE
Mapping the global threat of land subsidence
Nineteen percent of the global population may face a high probability of subsidence
See supplementary materials for author affiliations.
1 JANUARY 2021 • VOL 371 ISSUE 6524 35SCIENCE
dicted for 2040 for a global change scenario
based on steady population growth and in-
creasing greenhouse gas emissions (Shared
Socioeconomic Pathways 2, Representative
Concentration Pathway 8.5), which accounts
for the greatest sea-level rise projections.
Our results suggest that potential sub-
sidence threatens 12 million km2 (8%) of
the global land surface with a probability
greater than 50% (MH to VH in the figure).
Potential subsidence areas are concentrated
in and near densely urban and irrigated ar-
eas with high water stress and high ground-
water demand, overlying some of the larg-
est and most depleted aquifer systems (5)
in Asia (e.g., North China Plain) and North
America (e.g., Gulf of Mexico coastal plain);
coastal and river delta areas worldwide (e.g.,
Vietnam, Egypt, or the Netherlands); and
inland sedimentary basins of México, Iran,
and the Mediterranean countries. Potential
subsidence is lower in Africa, Australia, and
South America, owing to the lower ground-
water depletion (6). In central Africa, poten-
tial subsidence only includes information on
the susceptibility, as groundwater depletion
is unknown. In this region, subsidence sus-
ceptibility (see fig. S6) could be useful to pre-
vent subsidence impacts on developing cities
that during the next decades could rely more
on the available groundwater resources.
To evaluate the exposure to potential sub-
sidence, we focus on areas where the poten-
tial subsidence probability is high or very
high (see the figure). The cumulative po-
tential subsidence area amounts to 2.2
million km2, or 1.6% of the land; includes
1.2 billion inhabitants, or 19% of the global
population; and has an exposed GDP of
US$ 8.19 trillion, or 12% of the global GDP.
High-income countries account for 62%
of the global exposed GDP but only 11%
of the global exposed population, whereas
low-income countries account for 54% of
the global exposed population and 12% of
the global exposed GDP. It is expected that
the capability of low-income countries to
implement the political, regulatory, and
socioeconomic measures necessary to pre-
vent and mitigate subsidence impact will
be less than that for high-income countries.
Potential global subsidence
The color scale indicates the probability intervals classied from very low (VL) to moderately low (ML) to moderately high (MH) to very high (VH), for every 30-arcsec
resolution pixel (1 km by 1 km at the Equator). The white hatched polygons indicate countries where groundwater data is unavailable, and the potential subsidence only
includes information on the susceptibility. For details on data and methods, and for maps of other regions, see supplementary materials.
120ºW 60ºW 120ºE60ºE
45ºN40ºN 35ºN
110ºE 120ºE 130ºE
30ºN 40ºN 35ºN
East Asia
North America
Potential global subsidence
The color scale indicates the probability intervals classied from very low (VL) to moderately low (ML) to moderately high (MH) to very high (VH), for every 30-arcsec
resolution pixel (1 km by 1 km at the Equator). The white hatched polygons indicate countries where groundwater data is unavailable, and the potential subsidence only
includes information on the susceptibility. For details on data and methods, and for maps of other regions, see supplementary materials.
120ºW 60ºW 120ºE60ºE
45ºN40ºN 35ºN
110ºE 120ºE 130ºE
30ºN 40ºN 35ºN
East Asia
North America
Potential global subsidence
The color scale indicates the probability intervals classified from very low (VL) to very high (VH), for every 30-arcsec resolution pixel (1 km by 1 km
at the Equator). The white hatched polygons indicate countries where groundwater data is unavailable, and the potential subsidence only includes information
on the susceptibility. See maps of other regions in supplementary materials.
36 1 JANUARY 2021 • VOL 371 ISSUE 6524 SCIENCE
Potential subsidence threatens 484 million
inhabitants living in flood-prone areas, 75%
of whom live in fluvial areas and 25% of
whom live near the coast. This number of
threatened inhabitants corresponds to 50%
of the global population exposed to flooding
hazards according to previous estimates (7),
demonstrating the importance of consider-
ing potential subsidence in global flooding
risk analyses.
Most of the global population exposed
to potential subsidence live in Asia (86%),
which is about 10 times the combined ex-
posed population of North
America and Europe (9%).
The results indicate that 97%
of the exposed global pop-
ulation is concentrated in
30 countries (see SM). India
and China share the top two
rankings of potential subsid-
ence in terms of spatial ex-
tent and exposed population.
Egypt and the Netherlands
have the largest populations
living in potential subsid-
ence areas that are below
the mean sea level. The greatest population
densities in potential subsidence areas oc-
cur in Egypt and Indonesia, whereas the
relative exposure per country, measured as
the exposed population normalized by the
total population, is greater than 30% for
Egypt, Bangladesh, Netherlands, and Italy.
The United States ranks first in terms of
GDP exposed to potential subsidence, ow-
ing to its high GDP per capita.
Combination of the aforementioned
metrics permits derivation of a potential
subsidence index ranking (see SM). Seven
of the first ten ranked countries have the
greatest subsidence impact, accounting for
the greatest amount of reported damages
(Netherlands, China, USA, Japan, Indonesia,
México and Italy).
During this century, climate change will
cause serious impacts on the world’s wa-
ter resources through sea-level rise, more
frequent and severe floods and droughts,
changes in the mean value and mode of pre-
cipitation (rain versus snow), and increased
evapotranspiration. Prolonged droughts
will decrease groundwater recharge and in-
crease groundwater depletion, intensifying
subsidence. The global potential subsidence
is predicted for 2040 using the same sub-
sidence metrics and available global pro-
jections of water stress, water demand var-
iations, climate, and population (see SM).
Although predicted potential subsidence ar-
eas increase only by 7% globally, the threat-
ened population is predicted to rise by 30%,
affecting 1.6 billion inhabitants, 635 million
of whom will be living in flood-prone ar-
eas. These changes will not be homogene-
ous. Between 2010 and 2040, the predicted
population exposed to potential subsidence
increases more than 80% in the Philippines,
Iraq, Indonesia, México, Israel, Netherlands,
Algeria, and Bangladesh. The increase will
be moderate, less than 30%, for China, the
United States, Italy, and Iran. Potential sub-
sidence is forecasted to decrease in Japan
and Germany, owing to effective ground-
water management policies and population
declines. Finally, potential subsidence is pre-
dicted to emerge in high-latitude northern
countries like Canada and to
increase in extent in Russia
or Hungary, where climate
change will favor longer dry
Further advancements in
the global evaluation of sub-
sidence can be made when a
global historical database on
subsidence rate, magnitude,
and extent has been com-
piled, which could be largely
sourced from continental
monitoring of surface dis-
placements using satellite radar imagery (8).
Widespread continuous monitoring of sub-
sidence will permit better evaluation of the
potential impact of land subsidence, espe-
cially in countries like Indonesia, México, and
Iran, where local studies revealed the highest
subsidence rates worldwide, but the national
dimension of subsidence is still unknown.
Further research also is necessary to evalu-
ate the cost of damage caused by current and
historical subsidence worldwide. The combi-
nation of damage information with hazard
estimates will permit improved assessments
of potential loss and design of cost-effective
countermeasures. Presently, annual subsid-
ence costs are only published for China (US$
1.5 billion) and the Netherlands (US$ 4.8
billion) (9). The greater subsidence costs in
the Netherlands owe to the exposed popula-
tion below the mean sea level and the large
investments made to prevent flooding. Our
model, which does not yet consider mitiga-
tion measures, likely overestimates potential
subsidence exposure in the Netherlands and
Japan, where groundwater management has
effectively controlled subsidence over the
past decades (10).
Our results identify 1596 major cities, or
about 22% of the world’s 7343 major cities
that are in potential subsidence areas, with
57% of these cities also located in flood-
prone areas. Moreover, subsidence threatens
15 of the 20 major coastal cities ranked with
the highest flood risk worldwide (11), where
potential subsidence can help delimit areas
in which flooding risk could be increased
and mitigation measures are necessary.
Overall, potential global subsidence re-
sults can be useful to better define the spa-
tial extent of poorly documented subsidence
occurrences, discover unknown subsiding
areas, prevent potential subsidence impacts
wherever groundwater depletion occurs,
and better identify areas where subsidence
could increase the flooding risk. In any
of these scenarios, an effective land-sub-
sidence policy should include systematic
monitoring and modeling of exposed ar-
eas, evaluation of potential damages, and
cost-benefit analyses permitting implemen-
tation of adequate mitigation or adaptation
measures. These measures should consider
groundwater regulation and strategic long-
term measures, such as the development
of alternative water supplies and the pro-
tection and (or) enhancement of natural or
artificial recharge of aquifers.
Considering that the potential subsidence
may affect 635 million inhabitants living in
flood-prone areas in 2040, it is of prime im-
portance that potential subsidence is quanti-
fied and systematically included in flood risk
analyses and related mitigation strategies.
1. D. L. Galloway, T. J. Burbey, Hydrogeol. J. 19, 1459 (2011).
2. J. S. Famiglietti, Nat. Clim. Chang. 4, 945 (2014).
3. K. E. Trenberth, Clim. Res. 47, 123 (2011).
4. J. P. M. Syvitski et al., Nat. Geosci. 2, 681 (2009).
5. P. Döll, H. Müller Schmied, C. Schuh, F. T. Portmann, A.
Eicker, Water Resour. Res. 50, 5698 (2014).
6. R. G. Taylor et al., Nat. Clim. Chang. 3, 322 (2013).
7. B. J ongm an, P. J. Ward, J. C. J. H. A erts, Glob. Environ.
Change 22, 823 (2012).
8. R. Lanari et al., Remote Sens. 12, 2961 (2020).
9. T. H. M. Bucx, C. J. M. Van Ruiten, G. Erkens, G. De Lange
in, Proceedings of the International Association of
Hydrological Sciences 372, 485 (2015).
10. K. A. B. Jago-on et al., Sci. Total Environ. 407, 3089
11. S. Hallegatte, C. Green, R. J. Nicholls, J. Corfee-Morlot,
Nat. Clim. Chang. 3, 802 (2013).
12. G. Herrera, P. Ezquerro, Global Subsidence Maps, fig-
share (2020); 10.6084/m9.figshare.13312070.
Four anonymous peer reviewers and S. E. Ingebritsen (U.S.
Geological Survey) helped to improve the manuscript.
Funding for this study was provided partly by the Spanish
Research Agency (AQUARISK, PRX19/00065, TEC2017-
85244-C2-1-P projects) and PRIMA RESERVOIR project, and
by all the institutions represented in the Land Subsidence
International Initiative from UNESCO. G.H-G., P.E., R.T., M.B.-P,
and J.L.-V. designed the study, performed the analysis, and
wrote the initial manuscript with input from all other authors.
R.M.M., E.C.-C., and M.R. advised on the susceptibility
analysis. R.M.M., J.L., P.T., and G.E. advised on hazard analysis.
D.C.-F., J.L., P.T., E.C.C., G.E., D.G., W.C.H., N.K., M.S., L.T., H.W.,
and S.Y. advised on global exposure analysis. R.T., M.B.P.,
R.M.M., J.L., P.T., W.-C.H., N.K., L.T., H.W., and S.Y. contributed
essential data for the analysis. All the authors edited and
revised the manuscript through the different reviews. Any use
of trade, firm, or product names is for descriptive purposes
only and does not imply endorsement by the U.S. government.
The authors declare no competing interests. All data included
in this study are available at figshare (12).
threatens 15
of the 20 major
coastal cities
ranked with
the highest flood
risk worldwide.
... 2021a;Song et al. 2023). Globally, there are 1596 major cities situated within regions of potential land subsidence, with a more pronounced occurrence in Asian cities (Herrera-García et al. 2021). For instance, Jakarta, the capital of densely populated Indonesia, experienced land sinking nearly 15 times faster than the global average rate of sea level rise between 2015 and 2020 (Bott et al. 2021). ...
... 2021b;Miao et al. 2023). The influences triggering urban land subsidence encompass the natural gravitational forces acting upon surface soils, dynamic crustal movements, human-induced activities encompassing groundwater extraction, petroleum drilling, natural gas exploitation, and the imposition of structural loads (Herrera-García et al. 2021;Bagheri-Gavkosh et al. 2021). Moreover, the global rise in temperatures has contributed to the peril by inducing an elevation in sea levels, thereby accentuating the susceptibility of urban lands to subsidence (Erban et al. 2014;Tay et al. 2022). ...
Full-text available
Land subsidence in urban settlements is globally becoming prevalent and severe due to sea level rise and accelerated construction. However, few studies have analyzed the susceptibility of land subsidence in urban settlements and the subsidence rate thresholds that have a great impact on the reliability of the land subsidence susceptibility map (LSSM). This work aims to provide a novel LSSM framework for decision makers to conduct risk control in regional urban settlements. Herein, the COSMO-SkyMed Synthetic Aperture Radar (SAR) data from July 2016 to June 2021 was acquired for remote sensing interpretation in Wuhan, China. Persistent Scatterer Interferometric Synthetic Aperture Radar (PS-InSAR) technology, combined with geostatistical analysis, was employed to map regional land subsidence rates. A total of 12 impact factors, identified through Pearson correlation coefficient (PCC) and multicollinearity tests, were selected as input features for the machine learning model. The performance of the model was assessed using Receiver Operating Characteristic (ROC) curves, and the segmentation of PS points for land subsidence rate was discussed. Furthermore, the correspondence between the measured ground-level observations and the predicted LSSM was compared. The results demonstrate that the random forest (RF) model outperforms other models in the test set, achieving an Area Under the Curve (AUC) of 0.940. The optimal threshold of-10mm/year is proposed for segmenting PS points, which exhibits the strongest reliability in the distribution characteristics of the susceptibility index (SI). Combined with a high-performance hybrid model, this work is expected to provide a promising reference for land subsidence susceptibility prediction in similar urban settlements worldwide.
... Human activity impacts mainly include the development of underground fluid resource extraction (groundwater, oil, natural gas, etc.) [8,9], solid mineral exploitation [10], and pore soil compaction and consolidation settlement induced by engineering construction in soft soil areas [11]. Recently, many cities around the world have been affected by land subsidence disasters [12][13][14][15][16][17][18][19][20]. For example, the annual land subsidence in Mexico City is about 10 to 40 cm, causing buildings to tilt and crack [9], and the ground subsidence in Tokyo has adverse effects on the construction of underground engineering projects [16]. ...
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As one of the most developed coastal cities, Shanghai experiences long-term ground surface settlement disasters during urban expansion periods, which has adverse effects on economic development. To date, many studies regarding Shanghai’s ground surface sedimentation have been conducted with microwave remote sensing technology. However, the systematic and timely analysis of the time series deformation results and risk evaluation is still absent. Therefore, we focused on the following aspects in this study: Firstly, revealing in detail the time series deformation characteristics during 2016–2022 with Sentinel-1A images and verifying the deformation results with different InSAR technologies and SAR data. Secondly, fully discussing the reasons for ground sedimentation from the aspects of subway construction, land use type, monthly rainfall, and human activities, and studying the correlation between surface deformation and rainfall with the singular spectrum analysis (SSA) method. Finally, conducting a risk evaluation and risk level division using the entropy method, combining the long time series deformation results and geoinformation data. Meanwhile, the following conclusions were reached: 1. There are six typical deformation areas, distributed in the Baoshan District, Minhang District, and Jinshan District of Pudong New District from 2016 to 2022. The maximum annual rate is −32.3 mm/a, and the maximum cumulative sedimentation reaches −188.6 mm. 2. Ground sedimentation is mainly due to engineering construction during city development and verifies the weak correlation between surface deformation and rainfall. 3. We obtained different levels of geological hazard risk areas, and Huangpu, Yangpu, Hongkou District, the northwest area of Pudong New Area, and the vicinity of Dishui Lake belong to higher-risk areas. The above time series deformation research results and systematic analysis of induced factors, and the higher-risk-area division, will provide valuable insights for urban risk management.
... Subsidence is a pressing societal issue that has affected many regions globally (Herrera-García et al., 2021). The mechanisms driving land subsidence have been well-documented (i.e., Galloway & Burbey, 2011;Riley, 1998), but mapping and understanding local and regional drivers of subsidence remains a challenge due to the long-term nature of subsidence, and the lack of long-term subsidence and head monitoring. ...
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The San Joaquin Valley, California has experienced dramatic subsidence over the past 100 years, but the regions with the most subsidence have shifted dramatically over this time period, from west (Kettleman City/Los Banos) to south (Tulare/Pixley/Corcoran). To date, no study has done an in‐depth analysis of the mechanisms driving this shift in subsidence. We analyze head records, utilizing a novel approach that assimilates change in head data from multiple overlapping time periods, to produce an 80‐year record of change in head over both the historical and modern regions of greatest subsidence. We then calibrate a deformation model to fit both historical (measured with leveling surveys) and modern (measured with Interferometric Synthetic Aperture Radar, or InSAR) data sets. We find that the stress history of the Kettleman City/Los Banos region with historically high subsidence plays a large role in reducing modern subsidence in that region, while declining heads in both regions are likely to result in major subsidence over the next several decades. This study highlights the need for active groundwater management to mitigate ongoing and future subsidence. One key data set needed in this effort is accurate long‐term head histories to reconstruct the stress history of aquifers for accurate deformation modeling.
... Consequently, modern societies have been forced to face numerous challenges related to ground deformation caused by the over-exploitation of groundwater (Galloway and Burbey, 2011). Land subsidence due to groundwater withdrawal is one of the most extensive types of geological phenomenon induced by human activity in the 20th century, affecting many major cities and regions in the world (Herrera-García et al., 2021). This widespread phenomenon is well-known and studied in China (Bian et al., 2014;Chen et al., 2021;Jiang et al., 2021;Shi et al., 2008;Zhou et al., 2017), central Mexico (Chaussard et al., 2014b;Cigna et al., 2021;Yalvac, 2020); Italy (Bonì et al., 2017;Poluzzi et al., 2019;Teatini et al., 2005;Tosi et al., 2009), and Mediterranean regions in Spain (Béjar-Pizarro et al., 2016;Bonì et al., 2015Bonì et al., , 2016Herrera et al., 2010;Tessitore et al., 2016). ...
Ground subsidence is a pervasive feature of landscapes. There are many processes that cause it: changing groundwater conditions, solutional collapse of salt and gypsum, coal and salt mining, the abstraction of hydrocarbons, geothermal fluid abstraction, shrinkage of organic soils and peats, and hydrocompaction. Subsidence can be associated with enhanced seismic activity and the formation of ground fissures.
Uneven settlement caused by excessive exploitation of groundwater will seriously affect the smooth operation of high-speed railways. This study takes the Jinwei high-speed railway as an example to explore the development characteristics and distribution of groundwater and land subsidence along the railway under the influence of groundwater exploitation. Based on the comprehensive analysis of hydrogeological conditions and soil characteristics, a three-dimensional coupling model of groundwater seepage and land subsidence was established. The groundwater flow field and land subsidence along the railway under different mining schemes were quantified, and the prevention and control scheme to ensure the smooth operation of the high-speed railway was determined. The results show that the coupling model verified by groundwater and subsidence monitoring data can better simulate the development process of land subsidence. The subsidence center along the railway line is located between DK315 ∼ DK327, with a predicted maximum subsidence rate of 16.36 mm/a. The second most serious area is located between DK295 ∼ DK309, with a maximum subsidence rate of 12.21 mm/a. The maximum ban on mining along the railway is extended to 350 m at the section DK295 ∼ DK309, and to 450 m at the section DK315 ∼ DK325, which can minimize the impact of land subsidence on the high-speed railway.
The intensity of global groundwater use rose from 124 m ³ per capita in 1950 to 152 m ³ in 2021, for a 22.6 % rise in the annual per capita use. This rise in global per capita water use reflects rising consumption patterns. The global use of groundwater, which provides between 21% and 30% of the total freshwater annual consumption, will continue to expand due to the sustained population growth projected through most of the 21 st century and to the important role that groundwater plays in the water‐food‐energy nexus. The rise in groundwater use, on the other hand, has inflicted adverse impacts in many aquifers, such as land subsidence, seawater intrusion, stream depletion and deterioration of groundwater‐dependent ecosystems, groundwater‐quality degradation, and aridification. This paper projects global groundwater use between 2025 and 2050. The projected global annual groundwater withdrawal in 2050 is 1,535 km ³ (1 km ³ =10 ⁹ m ³ = 810,713 acre feet). The projected global groundwater depletion, i.e., the excess of withdrawal over recharge, in 2050 equals 887 km ³ , which is about 61% larger than in 2021. This projection signals probable exacerbation of adverse groundwater‐withdrawal impacts, which are worsened by climatic trends and the environmental requirement of groundwater flow unless concerted national and international efforts achieve groundwater sustainability. This article is protected by copyright. All rights reserved.
Land subsidence risk assessment basically based on current information found that the analyzed subsidence districts are over the top and medium hazards of tormented by subsidence resulted in damages like diminish in runoff and wastewater seepage capacity, disturbance to water transportation structures undermine artificial infrastructure balance. Also, land subsidence may also be caused by oil and gas exploration. Russia is a major oil and gas producer in the globe. The Romashkino field is an oil and gas field located in Tatarstan, Russia. In 1948, the largest oil field in the Volga-Ural Basin was found there. In this study, we focus, application of INSAR analysis for surface deformation by oil and gas extraction and injection cycle with 14 SLC SAR Images of the descending pass from sentinel-1 satellite in C band between 2017 and 2020. The Permanent Scatterers (PS-InSAR) Technique was utilized to study displacement deformation utilizing the SARPROZ software. PSI was applied using interferograms with a super master scene. This approach processes only the coherent pixels with stable phase or amplitude. Due the high-density vegetation cover and long winter time with snow cover, decreased the number of resulting points. Results of the displacement re-sampled price of local land deformation between 2017 and 2020 projected. The displacement rates surrounding the Romashkino oilfield in this study range from 3 mm/yr to -9 mm/yr, according to PS-InSAR measurements. Additionally, we suggest an acceptable cutoff to choose the PSs for the case study when ASI is > 0.70 (DA 0.25).
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We present in this work an advanced processing pipeline for continental scale differential synthetic aperture radar (DInSAR) deformation time series generation, which is based on the parallel small baseline subset (P-SBAS) approach and on the joint exploitation of Sentinel-1 (S-1) interferometric wide swath (IWS) SAR data, continuous global navigation satellite system (GNSS) position time-series, and cloud computing (CC) resources. We first briefly describe the basic rationale of the adopted P-SBAS processing approach, tailored to deal with S-1 IWS SAR data and to be implemented in a CC environment, highlighting the innovative solutions that have been introduced in the processing chain we present. They mainly consist in a series of procedures that properly exploit the available GNSS time series with the aim of identifying and filtering out possible residual atmospheric artifacts that may affect the DInSAR measurements. Moreover, significant efforts have been carried out to improve the P-SBAS processing pipeline automation and robustness, which represent crucial issues for interferometric continental scale analysis. Then, a massive experimental analysis is presented. In this case, we exploit: (i) the whole archive of S-1 IWS SAR images acquired over a large portion of Europe, from descending orbits, (ii) the continuous GNSS position time series provided by the Nevada Geodetic Laboratory at the University of Nevada, Reno, USA (UNR-NGL) available for the investigated area, and (iii) the ONDA platform, one of the Copernicus Data and Information Access Services (DIAS). The achieved results demonstrate the capability of the proposed solution to successfully retrieve the DInSAR time series relevant to such a huge area, opening new scenarios for the analysis and interpretation of these ground deformation measurements.
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The mechanism of land subsidence and soil deformation deals with the dissipation of excess pore water pressure and the compaction of soil skeleton under the effect of natural or man-made factors, which can lead to serious disasters in the process of urbanization. The negative effects of land subsidence include structural and fundamental damages to underground and aboveground infrastructures such as pipelines and buildings, changes in land surface morphology, and creation of earth fissures. Arid and semi-arid countries like Iran are highly prone to land subsidence phenomenon. In these regions, precipitation rate and natural recharges are relatively lower than those of the global average showing the importance of ground waters for agricultural and industrial activities. Land subsidence has already occurred in more than 300 plains in Iran. Semnan Plain is one of the most important areas facing this phenomenon. The purpose of this research was to assess land subsidence susceptibility using random forest machine learning theory. At first, prioritization of conditioning factors was done using random forest method. Results showed that distance from fault, elevation, slope angle, land use, and water table have the greatest impacts on subsidence occurrence. Then land subsidence susceptibility map was prepared in GIS and R environment. The receiver operating characteristic curve was applied to assess the accuracy of random forest algorithm. The area under the curve by value of 0.77 showed that random forest is an acceptable model for land subsidence susceptibility mapping in the study area. The research results can provide a basis for the protection of environment and also promote the sustainable development of economy and society.
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The modern era of scientific global-mean sea level rise (SLR) projections began in the early 1980s. In subsequent decades, understanding of driving processes has improved, and new methodologies have been developed. Nonetheless, despite more than 70 studies, future SLR remains deeply uncertain. To facilitate understanding of the historical development of SLR projections and contextualize current projections, we have compiled a comprehensive database of 21st century global SLR projections. Although central estimates of 21st century global-mean SLR have been relatively consistent, the range of projected SLR has varied greatly over time. Among studies providing multiple estimates, the range of upper projections shrank from 1.3–1.8 m during the 1980s to 0.6–0.9 m in 2007, before expanding again to 0.5–2.5 m since 2013. Upper projections of SLR from individual studies are generally higher than upper projections from the Intergovernmental Panel on Climate Change, potentially due to differing percentile bounds or a predisposition of consensus-based approaches toward relatively conservative outcomes.
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Global warming is expected to drive increasing extreme sea levels (ESLs) and flood risk along the world’s coastlines. In this work we present probabilistic projections of ESLs for the present century taking into consideration changes in mean sea level, tides, wind-waves, and storm surges. Between the year 2000 and 2100 we project a very likely increase of the global average 100-year ESL of 34–76 cm under a moderate-emission-mitigation-policy scenario and of 58–172 cm under a business as usual scenario. Rising ESLs are mostly driven by thermal expansion, followed by contributions from ice mass-loss from glaciers, and ice-sheets in Greenland and Antarctica. Under these scenarios ESL rise would render a large part of the tropics exposed annually to the present-day 100-year event from 2050. By the end of this century this applies to most coastlines around the world, implying unprecedented floodrisk levels unless timely adaptation measures are taken
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In this paper, we do a critical review of statistical methods for landslide susceptibility modelling and associated terrain zonations. Landslide susceptibility is the likelihood of a landslide occurring in an area depending on local terrain conditions, estimating “where” landslides are likely to occur. Since the first attempts to assess landslide susceptibility in the mid-1970s, hundreds of papers have been published using a variety of approaches and methods in different geological and climatic settings. Here, we critically review the statistically-based landslide susceptibility assessment literature by systematically searching for and then compiling an extensive database of 565 peer-review articles from 1983 to 2016. For each article in the literature database, we noted 31 categories/sub-categories of information including study region/extent, landslide type/number, inventory type and period covered, statistical model used, including variable types, model fit/prediction performance evaluation method, and strategy used to assess the model uncertainty. We present graphical visualisations and discussions of commonalities and differences found as a function of region and time, revealing a significant heterogeneity of thematic data types and scales, modelling approaches, and model evaluation criteria. We found that the range of thematic data types used for susceptibility assessment has not changed significantly with time, and that for a number of studies the geomorphological significance of the thematic data used is poorly justified. We also found that the most common statistical methods for landslide susceptibility modelling include logistic regression, neural network analysis, data-overlay, index-based and weight of evidence analyses, with an increasing preference towards machine learning methods in the recent years. Although an increasing number of studies in recent years have assessed the model performance, in terms of model fit and prediction performance, only a handful of studies have evaluated the model uncertainty. Adopting a Susceptibility Quality Level index, we found that the quality of published models has improved over the years, but top-quality assessments remain rare. We identified a clear geographical bias in susceptibility study locations, with many studies in China, India, Italy and Turkey, and only a few in Africa, South America and Oceania. Based on previous literature reviews, the analysis of the information collected in the literature database, and our own experience on the subject, we provide recommendations for the preparation, evaluation, and use of landslide susceptibility models and associated terrain zonations.
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Although the European Alps are one of the most investigated regions worldwide, maps depicting climate change by means of climate classification are still not-existent. To contribute to this topic, a time series of very high resolution (30 arc-seconds) maps of the well-known Köppen-Geiger climate classification is presented. The maps cover the greater Alpine region located within the geographical domain of 4 to 19 degrees longitude and 43 to 49 degrees latitude. Gridded monthly data were selected to compile climate maps within this region. Observations for the period 1800–2010 were taken from the historical instrumental climatological surface time series of the greater Alpine region, HISTALP. Projected climate data for the period 2011–2100 were taken, as an example, from the Rossby Centre regional atmospheric model RCA4. Temperature fields were spatially disaggregated by applying the observed seasonal cycle of the environmental lapse rate. The main results of this study are, therefore, 366 observed and predicted (two scenarios) very high resolution Köppen-Geiger climate maps of the greater Alpine region covering the period 1800–2100. Digital data, as well as animated maps, showing the shift of the climate zones are provided on the following website Furthermore, the relationship between the Köppen-Geiger climate classification and the altitudinal belts of the Alps is demonstrated by calculating the boundaries of the climate zones, i.e. the deciduous forest line, the mixed forest line, the forest and tree line (timber line) and the snow line. The mean altitude of the potential timber line in the greater Alpine region, for example, was calculated to be 1730 m by the end of the 19th century, 1880 m by the end of the 20th century and to lie between 2120 and 2820 m by the end of the 21st century. The latter altitudes were projected for the greenhouse gas scenarios RCP 2.6 (best case) and RCP 8.5 (worst case). The altitude of the timber line (and the other boundaries of the altitudinal belts) is generally higher in the Western Alps, showing a clear west-east slope.
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Nowadays, the development of high-resolution flood hazard models have become feasible at continental and global scale, and their application in developing countries and data-scarce regions can be extremely helpful to increase preparedness of population and reduce catastrophic impacts.The present work describes the development of a novel procedure for global flood hazard mapping, based on the most recent advances in large scale flood modelling. We derive a long-term dataset of daily river discharges from the hydrological simulations of the Global Flood Awareness System (GloFAS). Streamflow data is downscaled on a high resolution river network and processed to provide the input for local flood inundation simulations, performed with a two-dimensional hydrodynamic model. All flood-prone areas identified along the river network are then merged to create continental flood hazard maps for different return periods at 30'' resolution. We evaluate the performance of our methodology in several river basins across the globe by comparing simulated flood maps with both official hazard maps and a mosaic of flooded areas detected from satellite images. The evaluation procedure also includes comparisons with the results of other large scale flood models. We further investigate the sensitivity of the flood modelling framework to several parameters and modelling approaches and identify strengths, limitations and possible improvements of the methodology.
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Coastal plains are amongst the most densely populated areas in the world. Many coastal peatlands are drained to create arable land. This is not without consequences; physical compaction of peat and its degradation by oxidation lead to subsidence, and oxidation also leads to emissions of carbon dioxide (CO2). This study complements existing studies by quantifying total land subsidence and associated CO2 respiration over the past millennium in the Dutch coastal peatlands, to gain insight into the consequences of cultivating coastal peatlands over longer timescales. Results show that the peat volume loss was 19.8 km3, which lowered the Dutch coastal plain by 1.9 m on average, bringing most of it below sea level. At least 66%of the volume reduction is the result of drainage, and 34 % was caused by the excavation and subsequent combustion of peat. The associated CO2 respiration is equivalent to a global atmospheric CO2 concentration increase of ~0.39 ppmv. Cultivation of coastal peatlands can turn a carbon sink into a carbon source. If the path taken by the Dutch would be followed worldwide, there will be double trouble: globally significant carbon emissions and increased flood risk in a globally important human habitat. The effects would be larger than the historic ones because most of the cumulative Dutch subsidence and peat loss was accomplished with much less efficient techniques than those available now.
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In many delta cities land subsidence exceeds absolute sea level rise up to a factor of ten by excessive groundwater extraction related to rapid urbanization and population growth. Without change, parts of Jakarta, Ho Chi Minh City, Bangkok and numerous other delta (and coastal) cities will sink below sea level. Increased flooding and also other widespread impacts of land subsidence result already in damage of billions of dollars per year. In order to gain insight in the complex, multi-sectoral aspects of subsidence, to raise awareness and to support decision making on appropriate adaptation strategies and measures, an Integrated Assessment Framework (IAF) for subsidence is introduced, illustrated by several (delta) case studies. Based on that a list of 10 generic key issues and possible solutions is presented in order to further develop and support a (generic) approach how to deal with subsidence in current and future subsidence-prone areas. For exchange of experiences and knowledge development.on subsidence in deltas the Delta Alliance, a knowledge network of deltas worldwide, can be supportive.