Urban growth and land subsidence: Multi-decadal investigation using human settlement data and satellite InSAR in Morelia, Mexico

Applying hesitant q-rung orthopair fuzzy sets to evaluate uncertainty in subsidence causes factors

Land subsidence is a widespread problem impacting communities worldwide. Understanding the causes and factors of land subsidence is crucial for identifying and prioritizing effective mitigation measures. One of the main reasons for prioritizing land subsidence causes is the potential impact on infrastructure and the environment. The main objective of this paper is to emphasize the importance of prioritizing the causes of land subsidence. By understanding and prioritizing the factors contributing to land subsidence based on their impact and urgency, the aim is to develop targeted strategies for mitigation, inform policy decisions, and prevent further exacerbation of this problems. The study comprises three phases, where experts in the field provide their opinions and propose a robust hybrid framework. This framework integrates the Failure Mode and Effect Analysis (FMEA) and Step-wise Weight Assessment Ratio Analysis (SWARA) with Hesitant q-rung orthopair fuzzy set (Hq-ROFS). The performance of the proposed technique was then compared with two other decision-making techniques for evaluating and ranking land subsidence causes. According to the results, extraction of groundwater, excessive irrigation using groundwater, and oxidation and drainage of organic soils were identified as primary drivers of subsidence.

Machine learning-based techniques for land subsidence simulation in an urban area

Understanding and mitigating land subsidence (LS) is critical for sustainable urban planning and infrastructure management. We introduce a comprehensive analysis of LS forecasting utilizing two advanced machine learning models: the eXtreme Gradient Boosting Regressor (XGBR) and Long Short-Term Memory (LSTM). Our findings highlight groundwater level (GWL) and building concentration (BC) as pivotal factors influencing LS. Through the use of Taylor diagram, we demonstrate a strong correlation between both XGBR and LSTM models and the subsidence data, affirming their predictive accuracy. Notably, we applied delta-rate (Δr) calculus to simulate a scenario with an 80% reduction in GWL and BC impact, revealing a potential substantial decrease in LS by 2040. This projection emphasizes the effectiveness of strategic urban and environmental policy interventions. The model performances, indicated by coefficients of determination R2 (0.90 for XGBR, 0.84 for LSTM), root-mean-squared error RMSE (0.37 for XGBR, 0.50 for LSTM), and mean-absolute-error MAE (0.34 for XGBR, 0.67 for LSTM), confirm their reliability. This research sets a precedent for incorporating dynamic environmental factors and adapting to real-time data in future studies. Our approach facilitates proactive LS management through data-driven strategies, offering valuable insights for policymakers and laying the foundation for sustainable urban development and resource management practices.

Land subsidence prediction in Zhengzhou's main urban area using the GTWR and LSTM models combined with the Attention Mechanism

In recent years, due to urbanization and human activities, groundwater overexploitation has become increasingly severe, resulting in some degrees of land subsidence and, consequently, causing a series of geological disasters and other environmental issues. Therefore, large-scale and high-precision land subsidence prediction is of great importance for the prevention and control of geological disasters. However, the existing prediction models and methods ignore the effects of the spatiotemporal non-stationary relationships between the influencing factors and the accumulated land subsidence, causing the poor accuracy of the predicted land subsidence results. In this context, a Geographically and Temporally Weighted Regression combined with the Long Short-Term Memory (LSTM)-multivariable and Attention Mechanism (AM) (GTWR-LSTMm-AM) was proposed to more accurately predict the deformation of time series land subsidence in this study. The small baseline subset-interferometric synthetic aperture radar (SBAS-InSAR) was used to reveal the temporal deformation information of Zhengzhou's main urban area, then the GTWR model was used to assess the spatiotemporal non-stationarity relationships between the accumulated land subsidence and its influencing factors monthly groundwater stability level, monthly precipitation and Normalized Difference Vegetation Index (NDVI) data, and to determine the corresponding weight matrix. In addition, we introduced an LSTM model with AM to extract key information from the time-series land subsidence data and adjusted the dynamic weights of the three selected influencing factors to predict the land subsidence in Zhengzhou's main urban area. The prediction accuracy R2 of the GTWR-LSTMm-AM model reaches 0.972, which is higher than 0.929 of the LSTMm model. The prediction accuracy RMSE is less than 3 mm and reaches 2.403 mm. In addition, we determined the importance of the impact factor on the subsidence results by randomly interrupting the impact factor time series, disclosuring that the monthly groundwater level contributed the most to the land subsidence in Zhengzhou's main urban area.

The alarming state of Central Chile's groundwater resources: A paradigmatic case of a lasting overexploitation

Ensuring water supply under climate change scenarios is a global concern, and groundwater resources play a crucial role. Aquifer depletion is a worldwide trend, and Chile is no exception. Through a statistical approach with strong hydrogeological criteria, the groundwater overexploitation phenomenon is studied in Central Chile, the most populated region in this mountainous country. With this purpose, we assess the evolution of groundwater levels and pumping between 1970 and 2020 by analysing 26,065 groundwater rights and 222 observation wells. Withdrawals increased from 498 hm3 in 1970 to 8883 hm3 in 2020. We recognised two general trends in groundwater levels: a quasi-steady state hydrodynamic regime pre-1988 and sustained decline post-1988, exacerbated since 2010 with the start of the Megadrought. Although groundwater recharge is expected to decrease during this severe drought, the declining trend strongly correlates with pumping but not with precipitation changes. Climate forcing is usually invoked to warrant the dramatic depletion of groundwater resources, but we demonstrated that all analysed aquifers have been overexploited since much earlier than 2010. Finally, the Chilean aquifers' overexploitation is a clear example of the consequences of prioritising the water offer over the water demand regulation, which hinders the United Nations' sustainable development goals accomplishment.

Living on the edge: urban fireflies (Coleoptera, Lampyridae) in Morelia, Michoacán, Mexico

Fireflies (Coleoptera, Lampyridae) are a globally threatened group of insects due to habitat loss and fragmentation, light pollution, climate change and pesticides. However, against all odds, some firefly populations persist in urbanized environments where all four of these factors are present simultaneously. In this work, we compiled several data sources to document the diversity of fireflies in the urbanized area of Morelia, characterize their current habitats, and determine the main stressors affecting these bioluminescent insects. We found seven genera and 26 species of fireflies (19 nocturnal, seven diurnal) associated with 32 urban, peri-urban and extra-urban areas; at least, 14 are new records for Michoacán, and the list for the state now includes nine genera and 41 species. Five additional sites were documented as extinction sites. We compared the characteristics of these five sites with those of the sites with extant populations. We found that in Morelia, fireflies are mainly associated with areas that have high to moderate proportions of vegetation cover, are near water bodies, have very gentle to moderate slopes, and are exposed to low levels of light pollution. In contrast, the extinction sites showed high proportions of artificial surfaces and high levels of light pollution. Because some fireflies are considered bioindicators of ecosystem integrity as they are associated to specific habitats, are highly diverse and due to their sensitivity to environmental changes, we consider that sites from Morelia's urban core and extinction sites show the highest levels of environmental degradation, threatening most fireflies and other insects living in the urban core with local extinction. At the same time, our results also suggest that implementing conservation strategies and sustainable planning for the urban development of Morelia in the short term could allow fireflies and other vital elements of the city's insect communities to persist for future generations. Restoration and conservation of green areas and nighttime environments are essential for biodiversity and human health, especially in intra-urban zones.

Integrated analysis of Hashtgerd plain deformation, using Sentinel-1 SAR, geological and hydrological data

Due to its proximity to Tehran, the Hashtgerd catchment in Iran is an important region that has experienced alarming subsidence rates in recent years. This study estimated the ground surface deformation in the Hashtgerd plain between 2015 and 2020 using Sentinel-1 SAR data and InSAR technique. The average LOS displacement of the ascending and descending tracks was - 23 cm/year and - 22 cm/year, respectively. The central area of the plain experienced the greatest vertical subsidence, with a more than - 100 cm cumulative displacement. The Karaj-Qazvin railway and highway that pass through this area have been damaged by subsidence, according to an analysis of profiles drawn along the transportation lines. The southern sections of Hashtgerd city have experienced a total displacement of - 30 cm/year over the course of about 6 years. The relationship between changes in groundwater level and subsidence rate in this region was examined using piezometer and precipitation data. Geoelectric sections and piezometric well logs were also utilized to investigate the geological characteristics of the Hashtgerd aquifer. According to the findings, the leading causes of subsidence were uncontrolled groundwater abstraction. This research highlights the need to comprehend the spatial distribution of confined aquifers and their effect on subsidence, which can aid in the development of a suitable management strategy to restore these aquifers.

Analysing Effects on Ground Water Levels Due to Conversion of Rural to Urban Landscapes

Greater NOIDA evolved from 1991 with 101 villages to 2020 with 293 villages. This is an ideal case of rural to urban transformation in the immediate past. This transformation led to a decrease in recharging natural surfaces and an increase in impermeable surfaces. Along with the reduction in recharge areas, an increase in population has necessitated more and more extraction of groundwater resulting in an imbalance of water extraction and recharge. The result is depletion of groundwater levels in this area. The area is part of the wide Indo-Gangetic alluvium with sand, silt and clay layers resting on quartzite’s of Delhi Super Group. Geomorphological map prepared using digital elevation models of the area shows older and younger alluvial plains and active flood plains of the river Hindan. Time series analysis of key land use land cover classes shows that recharge areas were reduced from 77 % to 30 % from 2005 to 2019 and impervious surfaces have increased from 19 % to 65 % for the same period. Aquifers of the area are both phreatic and semi-confined. The aquifer parameters estimated through step drawdown test and long duration aquifer performance test indicates that the average coefficient of transmissivity of the area is 1752 m2/day and the average coefficient of storage is 4.84 x 10-4. Discharge of the wells shows a yield of 8 to 16 lps for a drawdown of 3 to 6 m. An attempt has been made to know the behaviour of groundwater levels during the same period as that of land use land cover. The results indicate a 74 % depletion in groundwater levels with an average annual depletion of 21 %. An interrelationship between urban growth and groundwater levels has been established in this study. This analysis indicates that as agriculture declined water levels also depleted and have a positive correlation of 0.852. On the contrary, as the built-up increased water level has depleted hence have a negative relationship with a correlation coefficient of -0.851. To make it a sustainable resource, these overexploited aquifers need careful participatory management by communities, Scientists, and policymakers.

Monitoring and Predicting the Subsidence of Dalian Jinzhou Bay International Airport, China by Integrating InSAR Observation and Terzaghi Consolidation Theory

Dalian Jinzhou Bay International Airport (DJBIA) is an offshore artificial island airport, where the reclaimed land is prone to uneven land subsidence due to filling consolidation and construction. Monitoring and predicting the subsidence are essential to assist the subsequent subsidence control and ensure the operational safety of DJBIA. However, the accurate monitoring and prediction of reclaimed subsidence for such a wide area under construction are hard and challenging. This paper utilized the Small Baseline Subset Synthetic Aperture Radar (SBAS-InSAR) technology based on Sentinel-1 images from 2017 to 2021 to obtain the subsidence over the land reclamation area of the DJBIA, in which the results from ascending and descending orbit data were compared to verify the reliability of the results. The SBAS-InSAR results reveal that uneven subsidence is continuously occurring, especially on the runway, terminal, and building area of the airport, with the maximum subsidence rate exceeding 100 mm/year. It was found that there is a strong correlation between the subsidence rate and backfilling time. This study provides important information on the reclaimed subsidence for DJBIA and demonstrates a novel method for reclaimed subsidence monitoring and prediction by integrating the advanced InSAR technology and Terzaghi Consolidation Theory modeling. Moreover, based on the Terzaghi consolidation theory and the corresponding geological parameters of the airport, predicted subsidence curves in this area are derived. The comparison between predicted curves and the actual subsidence revealed by InSAR in 2017–2021 is highly consistent, with a similar trend and falling in a range of ±25 mm/year, which verifies that the subsidence in this area conforms to Terzaghi Consolidation Theory. Therefore, it can be predicted that in the future, the subsidence rate of the new reclamation area in this region will reach about 80 mm/year ± 25 mm/year, and the subsidence rate will gradually slow down with the accumulation of reclamation time. The subsidence rate will slow down to about 30 mm/year ± 25 mm/year after 10 years.