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A special issue of Sustainability (ISSN 2071-1050). This special issue belongs to the section "Sustainability in Geographic Science".

Deadline for manuscript submissions: 30 September 2026 | Viewed by 16117

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Editors

Prof. Dr. Francisco Javier Torrijo

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Guest Editor

Architecture, Heritage and Management for Sustainable Development Research Centre (PEGASO), Department of Geological and Geotechnical Engineering, Universitat Politècnica de València, Valencia, Spain
Interests: natural hazards; landslides; sustainable geology applications; tunnel design optimization and numerical modelling of geotechnical structures

Prof. Dr. Olegario Alonso-Pandavenes

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Guest Editor

Geology and Mining Engineering Faculty (FIGEMPA), Central University of Ecuador, Quito, Ecuador
Interests: applied geophysics; landslides; sustainable geology applications; drilling processes; hydrogeology; seismic microzonation and site effects

Dr. Julio Garzón-Roca

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Guest Editor

Department of Geodynamics (GEODESPAL), Faculty of Geology, Complutense University of Madrid, Madrid, Spain
Interests: sustainable characterization of geomaterials; landslides induced by extreme events; application of artificial intelligence tools to environmental and geological engineering

Special Issue Information

Dear Colleagues,

Geological engineering and the sustainable environment converge at a crucial point where technical innovation combines with environmental and social responsibility. Geological engineering focuses on understanding and using geological resources efficiently and safely, while sustainable engineering focuses on developing solutions that meet the needs of the present without compromising the ability of future generations to meet theirs. In this sense, the integration of both disciplines is essential to address contemporary challenges such as climate change mitigation, water resource management, and resilient infrastructure planning.

Geological engineers play a key role in the assessment of geological hazards, such as landslides, earthquakes, and tsunamis, thus contributing to the safety of multiple communities. They also work to identify and develop renewable energy sources, such as geothermal and hydropower, promoting the transition to a more sustainable future. By integrating environmental conservation practices and clean technologies into their projects, geological engineers can minimize the environmental impact of human activities and contribute to the preservation of natural ecosystems.

In short, collaboration between engineering geology and sustainable engineering is essential to address today's global challenges and build a safer and more equitable future for generations to come.

We look forward to receiving your contributions.

Prof. Dr. Francisco Javier Torrijo
Prof. Dr. Olegario Alonso-Pandavenes
Dr. Julio Garzón-Roca
Guest Editors

Manuscript Submission Information

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Keywords

sustainable engineering
geological engineering
resilience
geomaterials
climate change
applied AI
environmental impact
natural hazards

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Published Papers (10 papers)

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Research

21 pages, 4240 KB

Open AccessArticle

Research on Geological Environmental Carrying Capacity Evaluation Based on the FAHP-CRITIC Weighting Method: A Case Study of the Northern New District of Liaoyuan City

by Kui Chen, Yichen Zhang, Jiquan Zhang, Zhou Wen, Menghao Li and Chaoguang Qi

Sustainability 2026, 18(17), 8687; https://doi.org/10.3390/su18178687 - 25 Aug 2026

Abstract

This study focuses on the Northern New District of Liaoyuan City, Jilin Province, and develops an indicator-based relative spatial assessment framework for geological environmental carrying capacity. Fourteen indicators were selected from the geological, ecological, and socio-economic dimensions to characterize spatial differences in regional geological environmental conditions. The weights of the indicators were determined by integrating subjective and objective methods, where the Fuzzy Analytic Hierarchy Process (FAHP) and the CRITIC method were applied respectively, and the final composite weights were obtained through a game theory-based combination weighting approach. Based on the weighted results, ArcGIS was used to perform spatial analysis, and the geological environmental carrying capacity was classified into four levels: excellent, good, moderate, and poor. The results indicate significant spatial heterogeneity in geological environmental carrying capacity. Moderate-capacity areas dominate the study area, with poor-capacity areas mainly distributed in the central and southeastern regions. The proposed framework provides spatial information for identifying areas with different geological environmental conditions and supports differentiated environmental management and planning in mining areas. Full article

(This article belongs to the Special Issue Geological Engineering and Sustainable Environment)

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34 pages, 2535 KB

Open AccessArticle

Interpretable Machine Learning for Monthly Mean Air Temperature Modeling Under Correlated Meteorological Predictors: A Single-Station Case Study in Zonguldak, Türkiye

by Rukiye Uzun Arslan, İrem Şenyer Yapici and Berna Aksoy

Sustainability 2026, 18(16), 8458; https://doi.org/10.3390/su18168458 - 18 Aug 2026

Viewed by 154

Abstract

Reliable modelling of monthly air temperature is relevant to station-scale climate assessment and the evaluation of meteorological data-driven models. However, station-scale monthly meteorological datasets often contain correlated and partially redundant predictors because thermal, moisture, precipitation, wind, and seasonal variables are jointly controlled by atmospheric and seasonal forcing. This study conducts an integrated comparative analysis of established regression and machine learning models for monthly mean air temperature modelling in Zonguldak, a humid coastal province in the Western Black Sea Region of Türkiye. Monthly meteorological observations from 2000 to 2022 were used to evaluate eight primary regression and machine-learning models: Partial Least Squares regression, Ridge, Lasso, ElasticNet, Support Vector Regression, Random Forest, Gradient Boosting, and Extreme Gradient Boosting. Ordinary Least Squares (OLS) and Huber regression were additionally included as reference models. The analysis retained the original meteorological predictors and jointly evaluated predictive accuracy, model stability, ablation sensitivity, and model-specific predictor relevance. Reduced-predictor and seasonality-only scenarios were examined to distinguish direct thermal reconstruction from broader climatological predictability. Model performance was assessed using repeated nested cross-validation, bootstrap summaries of performance variability, supplementary rolling-origin validation, and Wilcoxon signed-rank tests with Holm correction. Although the full-predictor models achieved high predictive accuracy, this performance largely reflected the direct thermal information contained in minimum and maximum air temperature. When these thermal predictors were excluded, MAE increased to approximately 1.13–1.22 °C and

R^{2}

decreased to approximately 0.93–0.94. The seasonality-only scenario yielded MAE values of approximately 1.27–1.34 °C and R² values of approximately 0.92, indicating that the annual cycle accounted for a substantial proportion of monthly temperature predictability. The additional non-thermal meteorological predictors provided only limited improvement beyond the strong seasonal baseline. Overall, model performance depended on the predictor information available, and no single model family showed a consistent advantage across the evaluated scenarios. These findings highlight the importance of considering predictive accuracy together with model stability and predictor dependence in data-limited station-scale temperature modelling. Full article

(This article belongs to the Special Issue Geological Engineering and Sustainable Environment)

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25 pages, 27810 KB

Open AccessArticle

Predicting Dynamic Landslide Susceptibility Under Changing Land-Use Scenarios with Generalized Additive Model

by Hong Xie, Hongwei Deng, Peng Wang and Mengfei Lei

Sustainability 2026, 18(16), 8371; https://doi.org/10.3390/su18168371 - 15 Aug 2026

Viewed by 403

Abstract

Conventional landslide susceptibility assessment (LSA) generally relies on static land-use/land-cover (LULC) data, limiting its ability to capture the influence of future land-use evolution on landslide susceptibility. To address this limitation, this study proposes a dynamic LSA framework by integrating the Patch-generating Land Use Simulation (PLUS) model with a slope unit-based Generalized Additive Model (GAM). Using Wushan County in the Three Gorges Reservoir Area (TGRA), China, as a case study, historical LULC data were first analyzed, and future LULC scenarios for 2026 and 2030 were simulated using the PLUS model. Landslide susceptibility under different LULC scenarios was then evaluated using the interpretable GAM, while the statistical association between LULC categories and the spatial distribution of LSI was quantified using the GeoDetector model. The results show that the PLUS model accurately reproduced LULC evolution with a Kappa coefficient of 0.963. The GAM exhibited robust predictive performance, with 100 repeated spatial cross-validations (SCVs) yielding a mean AUC value exceeding 0.75. Although dynamic LULC had only a limited influence on the overall spatial pattern of landslide susceptibility, the proportion of very high-susceptibility areas gradually increased from 4.54% in 2022 to 4.62% in 2030. The interpretable model further revealed distinct nonlinear responses of environmental variables and demonstrated that different LULC categories contributed differently to the spatial distribution of landslide susceptibility. The proposed framework provides a practical approach for incorporating future land-use dynamics into landslide susceptibility assessment and offers valuable support for long-term landslide risk management and sustainable land-use planning. Full article

(This article belongs to the Special Issue Geological Engineering and Sustainable Environment)

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22 pages, 4568 KB

Open AccessArticle

An Integrated Entropy-Weight and Attribute Interval Recognition Approach for Sustainable Water-Inrush Risk Assessment in Karst Tunnels

by Lei Zhu, Ruofan Yu, Haifeng Li, Lizhao Liu, Zelin Zhou and Xin Liao

Sustainability 2026, 18(14), 7097; https://doi.org/10.3390/su18147097 - 11 Jul 2026

Viewed by 402

Abstract

Water inrush disasters in karst tunnels pose a significant threat to construction safety, project timelines, and the long-term sustainability of infrastructure. Effective risk assessment is crucial for mitigating these hazards and ensuring the resilient development of underground transportation networks. This study proposes a quantitative risk assessment model that integrates the entropy weight method with attribute interval recognition theory to address the uncertainties inherent in complex geological environments. First, a hierarchical evaluation index system is established based on four primary controlling factors: stratigraphy, geological structure, topography, and hydrogeology. Subsequently, the entropy weight method is employed to objectively determine the weight of each index, thereby minimizing human bias. The attribute interval recognition model is applied to calculate the comprehensive attribute measure for each tunnel segment, effectively managing the fuzziness of risk classification boundaries. The risk grade is ultimately determined using the confidence criterion. The proposed model is applied to the Qigan Mountain karst tunnel in Chongqing, China, which is divided into 56 segments for detailed analysis. Results show 41.32% (4088 m) high-risk, 40.14% (3971 m) medium-risk and 18.55% (1835 m) low-risk sections, which are highly consistent with the theoretical water inflow calculation results. The model realizes accurate and quantitative water inrush risk assessment, providing a scientific basis for disaster prevention and control in karst tunnel construction, and further promoting the sustainability and safety of underground engineering in karst areas. Full article

(This article belongs to the Special Issue Geological Engineering and Sustainable Environment)

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20 pages, 3618 KB

Open AccessArticle

Geomechanical Characterization of Unwelded Volcanic Bimrock Materials for Sustainable Slopes: Application to Road Instability Problems in the Western Cordillera of Ecuador

by Marlon Ponce-Zambrano, Julio Garzón-Roca, Francisco J. Torrijo and Olegario Alonso-Pandavenes

Sustainability 2025, 17(15), 7080; https://doi.org/10.3390/su17157080 - 5 Aug 2025

Viewed by 1355

Abstract

This paper presents a geomechanical characterization for unwelded volcanic bimrock materials. Bimrocks are geological materials consisting of blocks of rock of different sizes embedded in a finer matrix. Many volcanic deposits and outcrops can be classified as bimrocks, and some of them correspond to unwelded bimrocks, i.e., with the absence of strong bonds between blocks of rock and matrix. The geomechanical characterization proposed is oriented towards bimrocks slopes, their stability and landslide hazard occurrence. It consists of five steps which includes the material description, the volcanic deposit classification, the definition of block size range, the computation of the volumetric block percentage, the geotechnical characterization of the blocks of rock, and the geological and geotechnical analysis of the matrix that surrounds the blocks. The geomechanical characterization proposed is applied to four slopes at the Western Cordillera of Ecuador, where slopes instabilities are common. Results show that the geomechanical characterization sets a reliable framework for geotechnically describing bimrocks materials, explaining the actual stability state of the slopes. It also enables taking appropriate and optimum decisions in the design and management of volcanic slopes, thus contributing to a sustainable approach of landslide mitigation. Full article

(This article belongs to the Special Issue Geological Engineering and Sustainable Environment)

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24 pages, 4411 KB

Open AccessArticle

Characterization of Historical Tailings Dam Materials for Li-Sn Recovery and Potential Use in Silicate Products—A Case Study of the Bielatal Tailings Dam, Eastern Erzgebirge, Saxony, Germany

by Kofi Moro, Nils Hoth, Marco Roscher, Fabian Kaulfuss, Johanes Maria Vianney and Carsten Drebenstedt

Sustainability 2025, 17(10), 4469; https://doi.org/10.3390/su17104469 - 14 May 2025

Cited by 4 | Viewed by 2413

Abstract

The characterization of historical tailings bodies is crucial for optimizing environmental management and resource recovery efforts. This study investigated the Bielatal tailings dam (Altenberg, Germany), examining its internal structure, material distribution influenced by historical flushing technology, and the spatial distribution of valuable elements. To evaluate the tailings resource potential, drill core sampling was conducted at multiple points at a depth of 7 m. Subsequent analyses included geochemical characterization using sodium peroxide fusion, lithium borate fusion, X-ray fluorescence (XRF), and a scanning electron microscope with energy dispersive X-ray spectroscopy (SEM-EDX). Particle size distribution analysis via a laser particle size analyzer and wet sieving was conducted alongside milieu parameter (pH, Eh, EC) analysis. A theoretical assessment of the tailings’ potential for geopolymer applications was conducted by comparing them with other tailings used in geopolymer research and relevant European standards. The results indicated average concentrations of lithium (Li) of 0.1 wt%, primarily hosted in Li-mica phases, and concentrations of tin (Sn) of 0.12 wt%, predominantly occurring in cassiterite. Particle size analysis revealed that the tailings material is generally fine-grained, comprising approximately 60% silt, 32% fine sand, and 8% clay. These textural characteristics influenced the spatial distribution of elements, with Li and Sn enriched in fine-grained fractions predominantly concentrated in the dam’s central and western sections, while coarser material accumulated near injection points. Historical advancements in mineral processing, particularly flotation, had significantly influenced Sn distribution, with deeper layers showing higher Sn enrichment, except for the final operational years, which also exhibited elevated Sn concentrations. Due to the limitations of X-ray fluorescence (XRF) in detecting Li, a strong correlation between rubidium (Rb) and Li was established, allowing Li quantification via Rb measurements across varying particle sizes, redox conditions, and geological settings. This demonstrated that Rb can serve as a reliable proxy for Li quantification in diverse contexts. Geochemical and mineralogical analyses revealed a composition dominated by quartz, mica, topaz, and alkali feldspars. The weakly acidic to neutral conditions (pH 5.9–7.7) and reducing redox potential (Eh, 570 to 45 mV) of the tailings material indicated a minimal risk of acid mine drainage. Preliminary investigations into using Altenberg tailings as geopolymer materials suggested that their silicon-rich composition could serve as a substitute for coal fly ash in construction; however, pre-treatment would be needed to enhance reactivity. This study underscores the dual potential of tailings for element recovery and sustainable construction, emphasizing the importance of understanding historical processing techniques for informed resource utilization. Full article

(This article belongs to the Special Issue Geological Engineering and Sustainable Environment)

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19 pages, 5008 KB

Open AccessArticle

The Application and Development of Innovative Models in the Sustainable Management of Natural Gully Consolidation and Highland Protection Projects

by Aidi Huo, Peizhe Li, Yilu Zhao, Mohamed EL-Sayed Abuarab, Salah Elsayed and Jinchun Zhang

Sustainability 2025, 17(10), 4329; https://doi.org/10.3390/su17104329 - 10 May 2025

Cited by 2 | Viewed by 1315

Abstract

The Loess Plateau is threatened by severe gully erosion and tableland retreat, primarily driven by uncontrolled surface runoff. Numerical simulations of Gully Consolidation and Highland Protection (GCHP) demonstrate that individual measures such as check dams, terraces, and gully head backfilling can reduce sediment by 31–35% in the short term, but their effectiveness declines after approximately 10 years. This study classifies GCHP models into four types, progressively integrating drainage, filling, slope protection, and ecological measures. Simulation results confirm that the most comprehensive model—coupling all four types—offers the highest and most sustainable effectiveness in both erosion control and ecological restoration. To address long-term challenges, the study proposes a Sustainable Natural GCHP Management Method, combining cascade interception, guided drainage, and ecological retention, thereby enhancing project resilience and supporting China’s Yellow River Basin ecological protection strategy. Full article

(This article belongs to the Special Issue Geological Engineering and Sustainable Environment)

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20 pages, 6325 KB

Open AccessArticle

Sustainable Management of Landslides in Ecuador: Leveraging Geophysical Surveys for Effective Risk Reduction

by Olegario Alonso-Pandavenes, Francisco Javier Torrijo Echarri and Julio Garzón-Roca

Sustainability 2024, 16(24), 10797; https://doi.org/10.3390/su162410797 - 10 Dec 2024

Cited by 7 | Viewed by 3915

Abstract

The present work explores the use of geophysical surveys as valuable tools for the study and sustainable management of landslides, with a particular focus on Ecuador. As an Andean country, Ecuador’s geomorphology and geology are dominated by volcano-sedimentary materials and processes, which confers a high susceptibility to landslides. In the last few years, a number of landslide events (such as those at La Josefina, Alausí, and Chunchi) have given rise to disasters with significant material damage and loss of life. Climatic events, affected by climate change, earthquakes, and human activity, are the main landslide triggers. Geophysical surveys, like seismic refraction, electrical resistivity tomography (ERT), and ground-penetrating radar (GPR), are easy and low-cost techniques that provide valuable and critical subsurface data. They can help define the failure surface, delimit the mobilized materials, describe the internal structure, and identify the hydrological and geotechnical parameters that complement any direct survey (like boreholes and laboratory tests). As a result, they can be used in assessing landslide susceptibility and integrated into early warning systems, mapping, and zoning. Some case examples of large landslide events in Ecuador (historical and recent) are analyzed, showing how geophysical surveys can be a valuable tool to monitor landslides, mitigate their effects, and/or develop solutions. Combined or isolated geophysical techniques foster sustainable management, improve hazard characterization, help protect the most vulnerable regions, promote community awareness for greater safety and resilience against landslides, and support governmental actions and policies. Full article

(This article belongs to the Special Issue Geological Engineering and Sustainable Environment)

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16 pages, 2296 KB

Open AccessArticle

Hazard Study of Sludge from Mining Wastewater Treatment Systems (Tailings), Accumulation of Contaminants and Potential Utilization Proposals

by Paúl N. Malacatus, Paulina E. Manobanda and Inmaculada Romero

Sustainability 2024, 16(23), 10569; https://doi.org/10.3390/su162310569 - 2 Dec 2024

Cited by 2 | Viewed by 2869

Abstract

The increase in gold mining activities has led to a substantial rise in tailings generation, which carry distinct physicochemical and microbiological properties. This study aimed to evaluate the hazardous characteristics of mining tailings using the CRETIB (corrosivity, reactivity, explosiveness, toxicity, ignitability, biological-infectious) methodology. The research analyzed concentrations of heavy metals including arsenic, cadmium, copper, chromium, lead, mercury, nickel, and zinc, alongside parameters such as pH, cyanide, hydrogen sulfide, and coliform bacteria. Tailings samples were collected from a mine in Ponce Enriquez, Ecuador, at the surface and at a depth of 2 m across three monitoring campaigns. The results indicate that the tailings do not exhibit hazardous characteristics according to CRETIB criteria. While arsenic, chromium, copper, nickel, zinc, and mercury concentrations showed significant differences between the surface and 2 m depth, accumulating at the bottom of the tailings dam by 30–72%, parameters such as pH, cyanide, and hydrogen sulfide were higher at the surface, likely due to volatilization and precipitation effects. Lead did not show significant differences, but also tended to accumulate at depth. These findings suggest that the tailings could be safely utilized in the production of construction materials such as bricks, geopolymer concrete, and fiber cement, promoting circular economy practices and sustainable development in mining. Full article

(This article belongs to the Special Issue Geological Engineering and Sustainable Environment)

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14 pages, 2634 KB

Open AccessArticle

Evaluation of Geoenvironment Carrying Capacity in Mineral Resource-Based Cities from the Perspective of Sustainable Development

by Jiawei Liu, Gao Liu, Zhengqi Ma, Fengchuan Chen, Yaodong Wu, Chongji Ge and Xu Wang

Sustainability 2024, 16(18), 7934; https://doi.org/10.3390/su16187934 - 11 Sep 2024

Cited by 1 | Viewed by 1956

Abstract

The exploitation of natural resources and the degradation of the geological environment pose dual challenges for mineral resource-based cities amidst rapid economic development and urbanization. Evaluating geoenvironmental carrying capacity is essential in measuring the harmony between human activities and the geological environment. Unfortunately, current evaluation methods do not adequately capture the intricate interplay of multiple factors, hindering a comprehensive understanding of this concept in mineral resource cities. To address this gap, this study integrates the DPSR model into the assessment of geoenvironmental carrying capacity, aligning with the characteristics and sustainable development objectives of these cities. By employing catastrophe theory, entropy method, and analytic hierarchy process, a robust evaluation index system specific to mineral resource cities is established. Using Fushun City in Liaoning Province, China, as a case study, the analysis reveals consistently high comprehensive evaluation values over the past five years, reflecting the city’s actual environmental status. The research highlights enhancing the response layer as a key strategy to boost regional geoenvironmental carrying capacity. These results offer valuable insights for the planning of mineral resource cities, fostering regional sustainable development, and promoting geological environmental protection. Full article

(This article belongs to the Special Issue Geological Engineering and Sustainable Environment)

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