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Earth

Earth is an international, peer-reviewed, open access journal on earth science published bimonthly online by MDPI.

Quartile Ranking JCR - Q2 (Geosciences, Multidisciplinary | Environmental Sciences)

All Articles (421)

Categorical Prediction of the Anthropization Index in the Lake Tota Basin, Colombia, Using XGBoost, Remote Sensing and Geomorphometry Data

  • Ana María Camargo-Pérez,
  • Iván Alfonso Mayorga-Guzmán and
  • Yeison Alberto Garcés-Gómez
  • + 2 authors

This study presents a machine learning framework to automate the mapping of the Integrated Relative Anthropization Index (INRA, by its Spanish acronym). A predictive model was developed to estimate the degree of anthropization in the basin of Lake Tota, Colombia, using the XGBoost machine learning algorithm and remote sensing data. This research, part of a broader wetland monitoring project, aimed to identify the optimal spatial scale for analysis and the most influential predictor variables. Methodologically, models were tested at resolutions from 20 m to 500 m. The results indicate that a 50 m spatial scale provides the optimal balance between predictive accuracy and computational efficiency, achieving robust performance in identifying highly anthropized areas (sensitivity: 0.83, balanced accuracy: 0.91). SHAP analysis identified proximity to infrastructure and specific Sentinel-2 spectral bands as the most influential predictors in the INRA emulation model. The main result is a robust, replicable model that produces a detailed anthropization map, serving as a practical tool for monitoring human impact and supporting sustainable management strategies in threatened high-Andean ecosystems. Rather than a simple classification exercise, this approach serves to deconstruct the INRA methodology, using SHAP analysis to reveal the latent non-linear relationships between spectral variables and human impact, providing a transferable and explainable monitoring tool.

27 January 2026

Average Kappa and Accuracy for each modeling resolution.

This paper presents the development and pilot validation of an enhanced water governance assessment tool developed within the European InnWater project. Grounded in OECD Principles on Water Governance, the study combines literature review, thematic framework development, and pilot validation with stakeholders. The tool expands existing governance assessment frameworks by explicitly integrating four cross-cutting dimensions that are often insufficiently addressed: circular economy, environmental resilience, local empowerment, and procedural equity with particular attention to vulnerable groups. The assessment framework is organised across five governance domains—mega-trends and resilience; policy, institutions and regulation; financing; data, monitoring and evaluation; and engagement and accountability—and operationalised through a structured questionnaire applied in selected European pilot sites. Insights from initial pilot applications illustrate the tool’s capacity to reveal institutional coordination gaps, capacity constraints, and barriers to inclusive and adaptive governance. The paper contributes a replicable, policy-relevant governance assessment methodology designed to support reflexive learning and institutional improvement in diverse European water governance contexts.

30 January 2026

This study evaluates the spatiotemporal variations in surface water quality in An Giang province, a key upstream region of the Vietnamese Mekong Delta (VMD), under the influence of hydrological alterations and climate change impacts. Water quality data from 2010 to 2023 were collected from 10 monitoring stations along the Tien and Hau Rivers, focusing on key parameters including pH, temperature, Dissolved Oxygen (DO), Total Suspended Solids (TSS), Biological Oxygen Demand (BOD), Chemical Oxygen Demand (COD), Ammonium (N-NH4+), Nitrate (NO3), orthophosphate (P-PO43−), and Coliforms. The Mann–Kendall test and Sen’s slope estimator were employed to detect long-term trends and quantify the magnitude of changes. The findings indicated that the Hau River exhibits significant organic pollution, evidenced by elevated levels of BOD and COD, alongside diminished levels of DO. The Tien River exhibits elevated concentrations of NH4+ and total suspended solids (TSS). The MK test indicated that BOD, COD, and NH4+ levels were increasing at most locations in a statistically significant manner. This indicates that the water quality deteriorated over time. The study revealed that the majority of pollutants exhibited statistically significant increasing trends (p ≤ 0.05). The Tien River’s COD is increasing by 1.6 mg/L annually, whereas the Hau River’s COD is escalating by 1.7 mg/L per year. The biochemical oxygen demand on both rivers is increasing by 0.5 mg/L each year. The diminishing quantities of dissolved oxygen indicated a decline in water quality. Pollutant concentrations demonstrated significant positive associations with maximum temperature (r = 0.47–0.64) and hours of sunshine (r ≈ 0.50–0.64). A significant negative correlation with river discharge was observed, particularly during the dry season (r = −0.79 to −0.88), when diminished flows resulted in elevated pollution concentrations. The findings offer measurable evidence that increasing temperatures and decreasing river flows significantly affect water quality, underscoring the necessity of adapting water resource management in the Mekong Delta.

26 January 2026

Aerosol microphysical and optical properties play a crucial role in cloud microphysics, precipitation physics, and flood formation over areas characterized by complex monsoon regimes. This research presents a multi-source data integration approach to analyzing the spatio-temporal interaction between precipitation, aerosols, and flooding in the state of Kerala, incorporating an air mass trajectory analysis to examine its potential contribution to flooding. The results show that the Aerosol Optical Depth (AOD) values were high in the coastal districts (>0.8) in the La Niña year (2021) but low in the El Niño year (2015). On the precipitation side, 2018 and 2021 were both years with a high degree of anomalies, resulting in heavy rainfall that led to widespread flooding in the Thrissur district, among others. The trajectory analysis revealed that the Indian Ocean controls the precipitation during the southwest monsoon and the pre-monsoon. The post-monsoon precipitation is mainly sourced from the Arabian Peninsula and Arabian Sea, transferring marine aerosols along with desert aerosols. The overall study shows that the variability in aerosols and precipitation is more subject to change by the meteorological dynamics, as well as influenced by the regional changes in land use and land cover, causing fluxes in the land–atmosphere interactions. In conclusion, the present study highlights the possible interactive functions of atmospheric dynamics and anthropogenic land use modifications in generating a flood hazard. It provides essential information for land management policies and disaster risk reduction.

25 January 2026

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Earth - ISSN 2673-4834