Explore the vast range of titles available.

Land subsidence occurrence in the Tasuj plane is becoming more frequent and hazardous in the near future due to the water crisis. To mitigate damage caused by land subsidence events, it is necessary to determine the susceptible or prone areas. This study focuses on producing and comparing land subsidence susceptibility map (LSSM) using boosted regression tree (BRT), random forest (RF), and classification and regression tree (CART) approaches with twelve influencing variables, namely altitude, slope angle, aspect, groundwater level, groundwater level change, land cover, lithology, distance to fault, distance to stream, stream power index, topographic wetness index, and plan curvature. Moreover, by implementing the Relief-F feature selection method, the most important variables in LSSM procedure were identified. The performance of the adopted methods was assessed using the area under the receiver operating characteristics curve (AUROC) and statistical evaluation indexes. The results showed that all the employed methods performed well; in particular, the BRT model (AUROC = 0.819) yielded higher prediction accuracy than RF (AUROC = 0.798) and CART (AUROC = 0.764). Findings of this study can assist in characterizing and mitigating the related hazard of land subsidence events.

Understanding the influence of land use/land cover (LULC) on water quality is pertinent to sustainable water management. This study aimed at assessing the spatio-seasonal variation of water quality in relation to land use types in Lake Muhazi, Rwanda. The National Sanitation Foundation Water Quality Index (NSF-WQI) was used to evaluate the anthropogenically-induced water quality changes. In addition to Principal Components Analysis (PCA), a Cluster Analysis (CA) was applied on 12-clustered sampling sites and the obtained NSF-WQI. Lastly, the Partial Least Squares Path Modelling (PLS-PM) was used to estimate the nexus between LULC, water quality parameters, and the obtained NSF-WQI. The results revealed a poor water quality status at the Mugorore and Butimba sites in the rainy season, then at Mugorore and Bwimiyange sites in the dry season. Furthermore, PCA displayed a sample dispersion based on seasonality while NSF-WQI’s CA hierarchy grouped the samples corresponding to LULC types. Finally, the PLS-PM returned a strong positive correlation (+ 0.831) between LULCs and water quality parameters in the rainy season but a negative correlation coefficient (− 0.542) in the dry season, with great influences of cropland on the water quality parameters. Overall, this study concludes that the lake is seasonally influenced by anthropogenic activities, suggesting sustainable land-use management decisions, such as the establishment and safeguarding protection belts in the lake vicinity.

Micro- and small-scale enterprises (MSEs) have emerged as one of the most important tools for addressing economic and social issues and achieving development goals. In both developed and developing economies, MSEs have been acknowledged as critical components of national development. This study aimed to assess the contributions of MSEs toward sustainable community livelihood in Emba Alaje, Wereda, Ethiopia. The results revealed that MSEs contributed to economic growth, employment formation, and income generation for the local community. In addition, the study indicated that the MSEs were significantly affected by different determinant factors such as infrastructures, raw material, working premises, and human capital. The study clearly showed that there was a gender gap over participation in different MSE sectors. In addition, many sectors which can employ more people are still managed by men. This shows that the bodies involved, such as the MSE Development Offices, Bureau of Cooperatives, and Bureau of Works and Social Affairs, should join their hands and allow women to enter traditionally male-dominated sectors such as construction, manufacturing, and urban farming. Above all, greater efforts should be made to consider both female- and male-owned businesses.

Climate change is a serious concern for the agricultural sector given that this sector is highly dependent on climate conditions. Moreover, farmersʼ adaptation process under changing climate can be explained by the psychological factors and the incorporation of socio-environmental background. Therefore, the current study aimed at socio-cognitive perceptions and extended protection motivation theory (PMT) as the basis. This paper estimated the influence of cognitive factors on individualsʼ views and decisions regarding climate change adaptation. Data from this study came from a survey with 245 rural farmers in temperate mount areas of Fars province, Iran. Structural equation modeling (SEM) was used to estimate the different factors. Results showed that three core elements of the theory, namely, risk evaluation, adaptation evaluation, and maladaptation, were the statistically significant factors that could directly explain farmersʼ adaptation decisions to adopt appropriate coping strategies under changing climate. Findings also suggested that another structural factor, adaptation incentives, had a statistically significant influence on adaptation decision-making among farmers. The study proposed valuable insights on social discourse to promote adaptation. Findings strongly offered that social discourse should focus more strongly on confirming the truth and timeliness of information that individuals gained. Eventually, further investigations are necessary to conduct the measurement model in other cultures and geographical areas and see how socio-environmental components can influence risk evaluation and adaptation evaluation.

Hydrogen storage is an environmentally friendly technology and an enabler for technological advancements in applications such as transportation. However, the appropriate location of hydrogen refueling stations is crucial in increasing the adoption of hydrogen fuel. Therefore, the aim of this study is to investigate the influence of key variables (such as policy requirements, construction and maintenance costs, social demand, and environmental variables) on the location of hydrogen refueling stations on a global scale. For this purpose, this study examined the findings of 26 primary articles published between 2000 and 2025, using the weighted meta-analysis method. The results of this study showed that environmental variables (such as road access and weather conditions), compared to construction and maintenance costs, had a higher impact of around 76% on the better siting of liquid hydrogen stations. In addition, the meta-regression results showed that environmental variables can affect achieving a better location of compressed hydrogen stations by 23% and a better location of liquid hydrogen stations by 20%. The findings indicate an 18% reduction in the impact of variables affecting the location of compressed hydrogen stations in studies after 2020, as well as a spatial focus of most studies on Europe with a share of about 2%. This study demonstrates how zoning laws, infrastructural corridors, and environmental restrictions determine the best site for hydrogen refueling stations, which compete with other land uses (urban and suburban). Therefore, the emphasis on land science research is evident through choices about energy infrastructure siting, spatial growth patterns, and land use sustainability.

In the global COVID-19 epidemic, humans are faced with a new challenge. The concept of quarantine as a preventive measure has changed human activities in all aspects of life. This challenge has led to changes in the environment as well. The air quality index is one of the immediate concrete parameters. In this study, the actual potential of quarantine effects on the air quality index and related variables in Tehran, the capital of Iran, is assessed, where, first, the data on the pollutant reference concentration for all measuring stations in Tehran, from February 19 to April 19, from 2017 to 2020, are monitored and evaluated. This study investigated the hourly concentrations of six particulate matters (PM), including PM2.5, PM10, and air contaminants such as nitrogen dioxide (NO 2 ), sulfur dioxide (SO2), ozone (O3), and carbon monoxide (CO). Changes in pollution rate during the study period can be due to reduced urban traffic, small industrial activities, and dust mites of urban and industrial origins. Although pollution has declined in most regions during the COVID-19 quarantine period, the PM2.5 rate has not decreased significantly, which might be of natural origins such as dust. Next, the air quality index for the stations is calculated, and then, the interpolation is made by evaluating the root mean square (RMS) of different models. The local and global Moran index indicates that the changes and the air quality index in the study area are clustered and have a high spatial autocorrelation. The results indicate that although the bad air quality is reduced due to quarantine, major changes are needed in urban management to provide favorable conditions. Contaminants can play a role in transmitting COVID-19 as a carrier of the virus. It is suggested that due to the rise in COVID-19 and temperature in Iran, in future studies, the effect of increased temperature on COVID-19 can be assessed.

Wireless sensor networks (WSNs) are considered part of an environmentally friendly technology leading to more timely and cost-effective production and management of farms. Despite the potential of WSNs to agricultural development in the global South, outreach is still very limited, also in Iran. Therefore, in order to facilitate the adoption of WSNs, it is necessary to identify the factors influencing and challenging the adoption of this technology. This exploratory study uses a qualitative approach to identify the main barriers WSN outreach is facing. In the results, we distinguish facts that we define as issues or barriers that were identified by others from fears that are not supported by evidence so far, at the level of the farmers, the government actors as well as the technology itself. Facts include communication barriers such as internet access, farmers’ knowledge levels and rigidity to change as well as the government’s top-down organisation of the extension programme and support levels. Fears are mainly expressed on the technology itself and relate to costs, a lack of access, the complexity of use and reliability of the data. We provide a nuanced view of how fears need to be acknowledged and facts are to be tackled.

Rangelands play a vital role in supporting livelihoods, biodiversity, and ecological balance across arid and semi-arid regions. However, these fragile ecosystems are increasingly threatened by overexploitation, land degradation, and unsustainable management practices. Understanding the human and behavioral dimensions of rangeland conservation has therefore become an urgent priority. Many of the world’s rangelands, including those in Iran, have recently been exposed to destruction and serious damage. Collaboration among various stakeholders (especially pastoralists) in sustainable land use and management is considered a key factor in reducing this degradation. Guided by the Theory of Planned Behavior (TPB), this study tries to identify and analyze the behavioral nudges for the sustainable land use and management in Iran. This research employed a cross-sectional survey design involving 248 pastoralists in Fars Province, southern Iran, selected through simple random sampling. An extended version of the TPB was applied, incorporating two additional constructs—awareness of consequences and moral norms—to enhance its explanatory power in predicting sustainable land use intentions. Behavioral nudges, such as increased awareness of consequences, strengthening moral norms, perceived behavioral control, and attitudes, can lead pastoralists to sustainable land use and management, thereby helping to conserve rangelands. To operationalize the research, a cross-sectional survey of 248 pastoralists with livestock grazing certificates, who were selected using simple random sampling, was used. The results of the research showed that the constructs of attitude towards sustainable land use and management had a positive and significant effect on the intention towards sustainable land use and management (Beta = 0.292; T = 4.239; Sig = 0.001). The direct effects of two variables, awareness of consequences of rangelands’ destruction (Beta = 0. 335; T = 3.333; Sig = 0.001) and moral norms of sustainable land use and management (Beta = 0. 323; T = 2.791; Sig = 0.005), were positive and significant on Intention. In addition, the results of this study showed that moral norms not only act as a constructive factor in the intention of the pastoralists towards sustainable land use and management, but also can play a mediating role for some other variables such as awareness of consequences of rangeland destruction. The results of SEM analysis showed that the extended TPB can explain 75% of the variance of pastoralists’ behavioral intention, which shows the high explanatory power of the model. These findings provide practical insights for policymakers and land managers by emphasizing the need to design interventions that enhance moral and environmental awareness, promote participatory management, and align behavioral policies with local cultural norms. However, as this study is based on a cross-sectional design, causal inferences should be made cautiously, and future longitudinal research is recommended to validate these relationships over time.

The Persian Qanats, ancient underground aqueduct systems that have provided irrigation water to arid regions in Iran for over 3000 years, are recognized as a vital element of the country’s cultural heritage. Eleven of these impressive structures have been included on the UNESCO World Heritage List, underlining their cultural, social, political, and physical significance. As these underground heritage sites offer a unique opportunity for fostering territorial collaboration and social capital between tourists and the local community, it is important to develop a comprehensive model to influence the behavior of tourists, officials, and natives in their treatment of these invaluable sites. This study aimed to design a sustainable behavior model for underground heritage tourism management in Persian Qanats that have been listed as UNESCO World Heritage properties. The research employed a theme analysis approach, utilizing a statistical sample of 22 base managers and Qanat tourism experts. The study used content and thematic analysis to develop a research model that guarantees the sustainable protection of these valuable underground heritage sites by shaping the behavior of tourists, officials, and natives. The proposed model serves as a guideline for effective behavior management, leading to the preservation of these significant underground heritage sites for future generations. In conclusion, this study provides valuable insights into the sustainable management of Persian Qanats and the promotion of a strong sense of territorial collaboration and social capital between tourists and the local community.

In arid-zone water resource management and water-security assessment, changes in water-body volume are key indicators of water availability and regulation performance. However, arid-zone lakes often lack sufficient bathymetric information to constrain geometry under low lake-level conditions. Shrinkage-driven hydrological disconnection can destabilize extrapolation of water level–storage relationships. This increases uncertainty in quantifying long-term storage changes. Here, we develop a multi-digital elevation model (DEM) hypsometry framework to reconstruct near-monthly lake storage for 1993–2024, recovering storage during low-level periods without bathymetric surveys. Reconstructed changes agree with independent satellite altimetry (r = 0.93 for level and 0.90 for storage), outperforming above-water-only (r ≈ 0.637 for water level) and conventional model-selection base-lines (r ≈ 0.753 for water level). The framework was quantified across three scenarios: expanding lakes, lake systems and reservoirs, and terminally shrinking lakes. For the persistently shrinking Big Aral Sea, under the whole-lake modeling assumption, the Copernicus-based reconstruction provides a cumulative storage change of −214.3 km3, closest to the satellite altimetry estimate of −210.68 km3 among the tested DEMs. In contrast, other DEMs overestimate the 1993–2024 cumulative loss by 66.15–141.01 km3. Sub-lake modeling further adjusts the Shuttle Radar Topography Mission (SRTM)-based cumulative change to −248.38 km3, substantially reducing structural bias caused by lake disconnection. This study provides a transferable technical framework for lake storage reconstruction in arid regions under degraded low lake-level conditions and hydrological disconnection.