Coupling land use evolution and subsidence in the Po Delta, Italy: Revising the past occurrence and prospecting the future management challenges

Can river flow prevent land subsidence in urban areas?

Land subsidence, a silent death, occurs due to various factors like significant reduction in groundwater (GW) levels. It is a widespread phenomenon with irreparable consequences on buildings, infrastructures, and, in severe cases, groundwater aquifers. This study aims to assess the impact of river flow on the acceleration and control of land subsidence in an arid and semi-arid region. To achieve this goal, we analyze the interconnection between GW and SW and investigate the role of the Zayandeh-Rud River's drying up on land subsidence in the Isfahan-Borkhar aquifer in Iran's central plateau. To facilitate this assessment, we utilize the Interferometric Synthetic Aperture Radar (InSAR) technique to estimate the vertical deformation velocity of the aquifer (average land subsidence rate). The results show that the Isfahan-Borkhar aquifer has experienced a significant annual decline of more than 25 m, with an alarming rate exceeding 0.8 m/year. Our analysis of 31 piezometric wells (P-Wells) from 2000 to 2022 reveals a downward monotonic (in 16 P-Wells) and nonmonotonic (in 12 P-Wells) trend in groundwater table changes. Moreover, the GW table in the P-Wells near the river depends entirely on river flow. Furthermore, our findings indicate that river regulation exerts a dominant role in the control of land subsidence. Consequently, when water flows in the Zayandeh-Rud River, the rate of land subsidence declines significantly, particularly in urban regions. Therefore, maintaining a constant flow of water in the river can prevent or reduce ongoing land subsidence in Isfahan.

Soil organic carbon data comparison after 85 years and new 13 C/12 C compositions: The case study of the Ferrara province (Northeastern Italy)

The main causes of soil organic matter (SOM) loss are land use (e.g., conventional agriculture) and land-use change (e.g., conversion of wetlands into croplands). Before World War II and until 1960s, the Ferrara province in the Emilia-Romagna region (Northeast Italy) enlarged its agricultural production area through drainage of wetlands. After that, the newly drained area was put into intensive agricultural production with practices that proved to be unsustainable, and whose negative effects (depletion of soil organic carbon [SOC] and emissions of greenhouse gases [GHGs], e.g., CO2 ) have never been quantified. In this work, we estimated the changes in SOC 85 years after the drainage of the palustrine environment, by comparing 1937 SOC measurements with those made in 2022. Comparison of SOC maps from 1937 and 2022 indicates that most of the area suffered a significant SOC loss (∆OC85 years from 0.05 to 18.57 wt%), except for northern areas in which the peat nature of the soil has been preserved. We also measured the 13 C/12 C on the 2022 soil samples and generated a present-day map of the SOC isotopic ratios, which could be used in future as a benchmark to evaluate changes in soil carbon stocks and fluxes.

Global land subsidence mapping reveals widespread loss of aquifer storage capacity

Groundwater overdraft gives rise to multiple adverse impacts including land subsidence and permanent groundwater storage loss. Existing methods are unable to characterize groundwater storage loss at the global scale with sufficient resolution to be relevant for local studies. Here we explore the interrelation between groundwater stress, aquifer depletion, and land subsidence using remote sensing and model-based datasets with a machine learning approach. The developed model predicts global land subsidence magnitude at high spatial resolution (~2 km), provides a first-order estimate of aquifer storage loss due to consolidation of ~17 km3/year globally, and quantifies key drivers of subsidence. Roughly 73% of the mapped subsidence occurs over cropland and urban areas, highlighting the need for sustainable groundwater management practices over these areas. The results of this study aid in assessing the spatial extents of subsidence in known subsiding areas, and in locating unknown groundwater stressed regions.

Analysis of the characteristics and causations of surface deformation based on TS-InSAR: a case study of Jimo district, China

Due to the rapid economic development and urban construction and the high exploitation rate of groundwater and geothermal resource, Jimo district existed a potential threat of surface deformation. To clarify the characteristics and causations of surface deformation, this study firstly used SBAS-InSAR (Small Baseline Subset-Interferometric Synthetic Aperture Radar) technology to analyze the surface defor-mation distribution in the whole research area. Then, three areas with different surface cover conditions were selected to analyze the causations of surface deformation. Lastly, taking central urban area as the key research area, surface deformation causations were analyzed in detail based on PS-InSAR (Persistent Scatter-Interferometric Synthetic Aperture Radar) technology. The study found that, in coastal mollisol area, farmland area, and hot spring area, the maximum subsidence velocity reached up to 46.8 mm/a, 24 mm/a, and 19.1 mm/a, respectively. The factors, including surface loading, precipitation, and the groundwater level, were the causations of surface deformation in different research areas. The trend of the surface deformation curve was consistent with that of the groundwater level curve in the central urban area, but the response time of surface deformation lagged behind the change of groundwater level by approximately 4 months.

Spatiotemporal heterogeneity of land subsidence in Beijing

Land subsidence induced by groundwater level decline has spatiotemporal variations. Taking the Interferometric Synthetic Aperture Radar (InSAR) results and the groundwater subsidence data acquired by the monitoring stations as the source material, this paper aims to reveal the spatiotemporal heterogeneity of groundwater-land subsidence in Beijing plain by using the Wind Rose Map (WRM) method and the Change Point Analysis (CPA) method. The WRM results show that the amount and variation in subsidence differs in different directions. This method detected the formation of new subsidence centers and the slowdown of land subsidence in 2008. The CPA results show that obvious changes are detected in subsidence development at the Wangsiying (WSY), Tianzhu (TZ) and Wangjing (WJ) stations. However, there is a relatively stable trend of groundwater decline and land subsidence at the Tianzhu (TZ) station. The stages of land subsidence development show a significant response to groundwater. Moreover, changes in land subsidence also show delayed response behind the changes in groundwater level. The time-lag could be affected by the variation in amplitude of the groundwater level.

Analysis of the Periodic Component of Vertical Land Motion in the Po Delta (Northern Italy) by GNSS and Hydrological Data

Nowadays, several methodologies, implemented for satellite or terrestrial surveys, reveal that daily and weekly site-positioning time series can exhibit linear trends plus seasonal oscillations. Such periodic components affect the evaluation of subsidence rates and, thus, they must be recognized and properly modelled. In this work, the periodic component of vertical land motion in Po Delta (Northern Italy) is estimated by a multi-component and multi-source procedure recently proposed by some of the authors for studying land subsidence in delta areas. First, land vertical motion data, acquired in the central part of the Po Delta over a six-year time interval, were compared with hydro-meteorological and climate datasets collected from nineteen stations distributed over the entire Delta. Then, four physically based models of the test site were implemented to verify the water pressure- and water mass-dependent processes inferred from the analytical phase. Modelling results show that the annual ground oscillation is better explained by soil moisture change, although river water mass variation gives a relevant contribution to land deformation, especially in the wet periods. Finally, to account for intra-annual processes, the joint contributions of all the inferred sources were treated as a nonlinear problem and solved applying the generalized reduced gradient method. The obtained combination is well supported by statistical parameters and provides the best agreement with the geodetic observations.

Three-Dimensional Surface Deformation Characteristics Based on Time Series InSAR and GPS Technologies in Beijing, China

Excessive exploitation of the groundwater has resulted in obvious three-dimensional (3D) deformation features on the surface of the Beijing Plain. This paper, by combining Interferometric Synthetic Aperture Radar (InSAR) and Global Positioning System (GPS) technologies, has obtained time-series information of the 3D surface deformation in the Beijing Plain, analyzing its spatial distribution characteristics. On this basis, the relationship between different controlling factors with the 3D deformation of the surface has been analyzed as well. The following results are obtained: (1) From 2013 to 2018, the land subsidence, which generally showed the trend of slowing down, was mainly concentrated in the eastern, northern, and southern regions of Beijing Plain, with multiple subsidence centers. (2) Under the International Terrestrial Reference Frame 2005 (ITRF2005), the horizontal direction of all GPS points in the plain is basically the same, with the dominant movement direction being NE112.5°~NE113.8°. Under the Eurasian reference frame, the horizontal movement rate of GPS points significantly decreases. The movement rate and direction of each point are not characteristic of overall trend activity. (3) The distribution and extent of the 3D surface deformation in the Beijing Plain are controlled by the basement structure. Part of the subsided area corresponds to a Quaternary depression formed at the junction of active faults disrupting the area. Similarly, the distribution of horizontal deformation in the E-W and N-S directions of the plain is controlled by the regional basement structure comprising major faults bounding horizontal deformation. (4) Groundwater exploitation is the main cause of the 3D surface deformation in the Beijing Plain. The groundwater funnels of the second and third confined aquifer are in suitable agreement with the land subsidence. The horizontal movement in the Beijing Plain is either directed toward the center of the groundwater or the land subsidence funnel, and the deformation is directed from areas with higher to areas with lower groundwater levels.

An investigation into time-variant subsidence potentials using inclusive multiple modelling strategies

Groundwater over-abstraction due to the absence of an effective management plan is often one of the main reasons for land subsidence in aquifer areas. This paper investigates this environmental problem at Salmas plain, Iran, by using the ALPRIFT framework, an acronym of a set of seven general-purpose data layers, introduced recently by the authors. It is capable of mapping Subsidence Vulnerability Indices (SVI) and the paper investigates an innovation to transform it into Time-variant SVI (TSVI) mapping capabilities through a three module strategy: Module 1: maps SVI; Module 2: develops a predictive model for Groundwater Levels (GWL); Module 3: combines both modules to produces TSVI maps. Modules 1 and 2 employ Inclusive Multiple Modelling (IMM) practices, which promote learning from multiple models, as opposed to their ranking and selecting a 'superior' one. IMM is implemented through the same single modelling strategy for both Modules 1 and 2 at two levels: at Level 1, multiple models are constructed by three Fuzzy Logic (FL) models: Sugeno FL (SFL), Mamdani FL (MFL) and Larsen FL (LFL). (ii) At Level 2, FL models at Level 1 are reused by Support Vector Machine (SVM) as the combiner model. The results show that (i) the models at Level 1 are fit-for-purpose; (ii) the models at Level 2 are defensible owing to IMM strategies focussed on enhancing their accuracy and investigating their residuals; and (iii) according to TSVI maps, the north of the plain is vulnerable to hotspot areas and is exposed to subsidence risks due to unplanned over-abstraction of groundwater from the aquifer at Salmas plain.

Multi-Decadal Deltaic Land-Surface Changes: Gauging the Vulnerability of a Selection of Mediterranean and Black Sea River Deltas

Areal changes over delta surfaces determined by land and water ratios are a promising tool for identifying spatial and temporal changes in deltas that may reveal subsidence and shoreline erosion. Such changes can also provide the basis for more detailed studies on variations in land-cover and vegetation. Changes in land and water areas over a 35-year period (1984–2019) were determined for a selection of ten river deltas in the Mediterranean (Nile, Rhône, Po, Ebro, Moulouya, Ceyhan-Seyhan, Medjerdja, Ombrone, Arno) and the Black Sea (Danube), with a particular focus on aspects of subsidence and shoreline erosion. With the exception of the Ombrone, Arno, and Moulouya, and to lesser extent the Medjerdja, where notable changes dominate in the coastal zone and are tantamount to net erosion, the spatial pattern is largely dominated by delta-plain changes characterized by increasing areas of water. The pattern reflects a mix of shoreline erosion, land-use and land-cover changes, such as the ecological restoration of wetlands, but also increasing subsidence in these deltas, all of which have been exposed to a declining fluvial sediment supply due to human influence. The use of data on land-water ratios needs to be complemented by more detailed studies devoted to each delta in order to clearly disentangle changes related to land-use, vegetation, and subsidence. It is also important to determine how wetlands are interpreted in such ratios, as these important ecological elements are sensitive to ratio variations. It would also be interesting in future studies to examine how these variations play out over time, notably in deltas where changes have been significant over the period 1984–2019.

Characterizing the Topographic Changes and Land Subsidence Associated with the Mountain Excavation and City Construction on the Chinese Loess Plateau

A mega project, Mountain Excavation and City Construction (MECC), was launched in the hilly and gully region of the Chinese Loess Plateau in 2012, in order to address the shortage of available land and create new flat land for urban construction. However, large-scale land creation and urban expansion significantly alters the local geological environment, leading to severe ground deformation. This study investigated the topographic changes, ground deformation, and their interactions due to the MECC project in the Yan’an New District (YND). First, new surface elevations were generated using ZiYuan-3 (ZY-3) stereo images acquired after the construction in order to map the local topographic changes and the fill thickness associated with the MECC project. Then, the interferometric synthetic aperture radar (InSAR) time series and 32 Sentinel-1A images were used to assess the spatial patterns of the ground deformation in the YND during the postconstruction period (2017–2018). By combining the InSAR-derived results and topographic change features, the relationship between the ground deformation and large-scale land creation was further analyzed. The results indicated that the MECC project in the YND has created over 22 km2 of flat land, including 10.8 km2 of filled area, with a maximum fill thickness of ~110 m. Significant uneven ground deformation was detected in the land-creation area, with a maximum subsidence rate of approximately 121 mm/year, which was consistent with the field survey. The strong correlation between the observed subsidence patterns and the land creation project suggested that this recorded uneven subsidence was primarily related to the spatial distribution of the filling works, along with the changes in the thickness and geotechnical properties of the filled loess; moreover, rapid urbanization, such as road construction, can accelerate the subsidence process. These findings can guide improvements in urban planning and the mitigation of geohazards in regions experiencing large-scale land construction.

Monitoring of Land Subsidence in the Po River Delta (Northern Italy) Using Geodetic Networks

The Po River Delta (PRD, Northern Italy) has been historically affected by land subsidence due to natural processes and human activities, with strong impacts on the stability of the natural ecosystems and significant socio-economic consequences. This paper is aimed to highlight the spatial and temporal evolution of the land subsidence in the PRD area analyzing the geodetic observations acquired in the last decade. The analysis performed using a moving window approach on Continuous Global Navigation Satellite System (CGNSS) time-series indicates that the velocities, in the order of 6 mm/year, are not affected by significant changes in the analyzed period. Furthermore, the use of non-permanent sites belonging to a new GNSS network (measured in 2016 and 2018) integrated with InSAR data (from 2014 to 2017) allowed us to improve the spatial coverage of data points in the PRD area. The results suggest that the land subsidence velocities in the easternmost part of the area of interest are characterized by values greater than the ones located in the western sectors. In particular, the sites located on the sandy beach ridge in the western sector of the study area are characterized by values greater than −5 mm/year, while rates of about −10 mm/year or lower have been observed at the eastern sites located in the Po river mouths. The morphological analysis indicates that the land subsidence observed in the PRD area is mainly due to the compaction of the shallow layers characterized by organic-rich clay and fresh-water peat.

Deriving Natural Background Levels of Arsenic at the Meso-Scale Using Site-Specific Datasets: An Unorthodox Method

Arsenic is found in groundwater above regulatory limits in many countries and its origin is often from natural sources, making the definition of Natural Background Levels (NBLs) crucial. NBL is commonly assessed based on either dedicated small-scale monitoring campaigns or large-scale national/regional groundwater monitoring networks that may not grab local-scale heterogeneities. An alternative method is represented by site-specific monitoring networks in contaminated/polluted sites under remediation. As a main drawback, groundwater quality at these sites is affected by human activities. This paper explores the potential for groundwater data from an assemblage of site-specific datasets of contaminated/polluted sites to define NBLs of arsenic (As) at the meso-scale (order of 1000 km2). Common procedures for the assessment of human influence cannot be applied to this type of dataset due to limited data homogeneity. Thus, an “unorthodox” method is applied involving the definition of a consistent working dataset followed by a statistical identification and critical analysis of the outliers. The study was conducted in a highly anthropized area (Ferrara, N Italy), where As concentrations often exceed national threshold limits in a shallow aquifer. The results show that site-specific datasets, if properly pre-treated, are an effective alternative for the derivation of NBLs when regional monitoring networks fail to catch local-scale variability.

Assessing Po River Deltaic Vulnerability Using Earth Observation and a Bayesian Belief Network Model

Deltaic systems are broadly recognized as vulnerable hot spots at the interface between land and sea and are highly exposed to harmful natural and manmade threats. The vulnerability to these threats and the interactions of the biological, physical, and anthropogenic processes in low-lying coastal plains, such as river deltas, requires a better understanding in terms of vulnerable systems and to support sustainable management and spatial planning actions in the context of climate change. This study analyses the potential of Bayesian belief network (BBN) models to represent conditional dependencies in vulnerability assessment for future sea level rise (SLR) scenarios considering ecological, morphological and social factors using Earth observation (EO) time series dataset. The BBN model, applied in the Po Delta region in the northern Adriatic coast of Italy, defines relationships between twelve selected variables classified as driver factors (DF), land cover factors (LCF), and land use factors (LUF) chosen as critical for the definition of vulnerability hot spots, future coastal adaptation, and spatial planning actions to be taken. The key results identify the spatial distribution of the vulnerability along the costal delta and highlight where the probability of vulnerable areas is expected to increase in terms of SLR pressure, which occurs especially in the central and southern delta portion.

Analysis of the influence of groundwater on land subsidence in Beijing based on the geographical weighted regression (GWR) model

A global geological phenomenon caused by natural or human activities is described as land subsidence. Groundwater extraction plays a significant part in causing land subsidence. Due to economic development, urban expansion, and rapid population expansion, the unscientific exploitation of groundwater in Beijing has been accelerated, which makes it the region with the fastest land subsidence rate in China. To study the spatial heterogeneity of land subsidence caused by groundwater aquifers level changes, the monitoring results of land subsidence in 2003-2010 years were analyzed by using PS-InSAR, based on ENVISAT ASAR in Beijing plain area. The maximum value of accumulated land subsidence in the study area is 707 mm, and in this study area multiple subsidence center areas have been formed. A GWR model based on a regular grid has been established by exploring the effects of unconfined aquifer (UA), first confined aquifer (FCA), second confined aquifer (SCA), third confined aquifer (TCA) on land subsidence and their spatial non-stationarity. The change of subsidence in all subsidence areas is positively related to the change of SCA water level. Except the fact that the main control factors of Liyuan and Songzhuang are the change of UA layer, the change of SCA is the main control factor of land subsidence in most subsidence areas. Though the contribution rate of SCA to land subsidence is the highest, the contribution rate of TCA has been increasing. It is predicted that the impact on land subsidence will increase year by year. The results of this will not only help to understand the spatial impact patterns of aquifers on land subsidence zones, but also to formulate optimal groundwater regulation and recharge policies. There is a scarcity of the consideration of the compressible layer in the study and it will become more comprehensive if further datasets are obtained.

Land subsidence and its relation with groundwater aquifers in Beijing Plain of China

Beijing is a major metropolis with significant land subsidence because of long-term overexploitation of groundwater. While the South-to-North Water Diversion Project (SWDP) has provided new water sources Beijing; it has changed the pattern of land subsidence evolution in Beijing since 2015. Here we address how land subsidence evolution before and after SWDP, and we quantify also the impact of groundwater level changes in different aquifers on land subsidence at spatial scale. Subsidence evolution before and after SWDP were compared by adopting Persistent Scatterer Inteferomotry (PSI) with Radarsat-2 and Sentinel-1 data. Spatial correlation between Interferometric Synthetic Aperture Radar (InSAR) derived subsidence and groundwater levels in four aquifers was investigated using the Random Forest (RF) machine learning algorithm and Geographical Detectors (GD) technique. Extensometer deformation data and corresponding variation in groundwater level observations at three monitoring stations were used for validations. The study reveals that: firstly, both InSAR-derived subsidence area and maximum annual deformation rate decreased from 79.2% and 141 mm/yr before SWDP, to 60.1% and 135 mm/yr after SWDP. A reduction of time series deformation at four subsidence centers started about two years after the commence of SWDP in 2015. Secondly, the variation of groundwater level in the second confined aquifer has the strongest spatial correlation with subsidence in all the aquifers, but its impact on this aquifer has decreased after SWDP. These findings have an important scientific significance for the rational allocation of water resources and management strategy for mitigating hazards associated with subsidence against the background of SWDP.

Multi-Component and Multi-Source Approach for Studying Land Subsidence in Deltas

The coupled effects of climate change and land sinking make deltas and coastal areas prone to inundation and flooding, meaning that reliable estimation of land subsidence is becoming crucial. Commonly, land subsidence is monitored by accurate continuous and discrete measurements collected by terrestrial and space geodetic techniques, such as Global Navigation Satellite System (GNSS), Interferometry Synthetic Aperture Radar (InSAR), and high precision leveling. In particular, GNSS, which includes the Global Positioning System (GPS), provides geospatial positioning with global coverage, then used for deriving local displacements through time. These site-positioning time series usually exhibit a linear trend plus seasonal oscillations of annual and semi-annual periods. Although the periodic components observed in the geodetic signal affect the velocity estimate, studies dealing with the prediction and prevention of risks associated with subsidence focus mainly on the permanent component. Periodic components are simply removed from the original dataset by statistical analyses not based on the underlying physical mechanisms. Here, we propose a systematic approach for detecting the physical mechanisms that better explain the permanent and periodic components of subsidence observed in the geodetic time series. It consists of three steps involving a component recognition phase, based on statistical and spectral analyses of geodetic time series, a source selection phase, based on their comparison with data of different nature (e.g., geological, hydro-meteorological, hydrogeological records), and a source validation step, where the selected sources are validated through physically-based models. The application of the proposed procedure to the Codigoro area (Po River Delta, Northern Italy), historically affected by land subsidence, allowed for an accurate estimation of the subsidence rate over the period 2009–2017. Significant differences turn out in the retrieved subsidence velocities by using or not periodic trends obtained by physically based models.