earth_science papers | Gist.Science

Spatially concentrated heat emissions from data centers lead to localized urban warming and heat exposure

This study integrates facility-level data with urban climate modeling to reveal that concentrated heat emissions from data centers in California create localized warming hotspots, significantly increasing land surface and air temperatures, particularly at night and in densely populated areas like Los Angeles, thereby highlighting the need for informed urban planning and facility siting.

Jiachen Zhang, Hao Hu, Arman Shehabi, Cenlin He, Kelly Sanders2026-07-08

📄 earth_science

Contribution of matrix hydraulic conductivity to groundwater flow in highly fractured high-porosity rock with low swelling properties and minimal fracture infill

Through in situ hydraulic testing and stochastic inverse analysis at the Horonobe Underground Research Laboratory, this study demonstrates that in highly fractured, high-porosity mudstones with low swelling properties, both high matrix hydraulic conductivity and fractures significantly contribute to groundwater flow regardless of fracture density.

YUSUKE OZAKI2026-07-08

📄 earth_science

Explainable Machine Learning for Bio-regional Drought Prediction in South Australia

This study presents an explainable machine learning framework using XGBoost and Temporal Attention LSTM models to forecast drought severity across six South Australian IBRA subregions with high accuracy, revealing that lagged SPI-12 and rainfall anomalies are dominant predictors and mapping the six-year propagation of the Millennium Drought from the Murray Scroll Belt to the Eyre Mallee.

Fizza Anwar, Arnick Abdollahi, Andres Sutton2026-07-08

📄 earth_science

Compound climate extremes reshape staple-crop phenology and cropping-system turnaround windows across China

This study demonstrates that concurrent heat and water deficits, rather than single hazards alone, independently reshape the phenology of China's staple crops and disrupt cropping-system turnaround windows, particularly in southern regions and after 2010, highlighting a critical pathway for climate adaptation policy.

Gangyi Wang, Baoyang Han, Yonghui Fang2026-07-08

📄 earth_science

Seasonal rainfall predictability governed by interacting oceanic and terrestrial memory reservoirs

This study reveals that seasonal rainfall predictability, particularly in the South Asian monsoon, is governed not solely by remote oceanic forcing like ENSO but significantly by the persistence and spatial organization of terrestrial memory reservoirs, where soil moisture acts as a primary driver that often mediates oceanic influences and enhances forecast skill when initialized.

Swadhin Behera, Mukunda Dev Behera2026-07-08

📄 earth_science

Climate Adaptation Strategies For Kullu

This paper proposes a risk-responsive spatial planning framework for the Kullu Valley that integrates downscaled climate projections and hydrodynamic simulations to address the critical exposure of over 8,400 structures to future flood hazards caused by rapid urbanization and climate change, recommending specific adaptation measures such as a re-zoned river corridor buffer and nature-based slope stabilization.

Saurabh2026-07-08

📄 earth_science

Woody plant assemblages in restoration sites and remnants of Seasonal Atlantic Forest in Southern Brazil

This study compares woody plant assemblages in Seasonal Atlantic Forest remnants and 22–25-year-old restoration sites in southern Brazil, finding that while restoration sites show high floristic similarity driven by planted species, they remain distinct from remnants, highlighting the need to account for historical disturbance in reference selection and acknowledging that full ecological convergence is a long-term process.

Jéssica Oliveira Araújo, Géssi Souza Gonzaga, Juliana Deganello Vieira, Alba Lúcia Cavalheiro, José Marcelo Domingues To (…)2026-07-08

📄 earth_science

Machine learning and deep learning for ground data deformation analytics: a comprehensive critical review

This comprehensive critical review synthesizes 312 high-quality studies on machine learning and deep learning for ground deformation analytics, utilizing a novel tripartite framework and bibliometric analysis to identify research gaps in uncertainty quantification and advocate for physics-informed, interpretable models to enhance geohazard mitigation.

Francis Quayson, Ishmael Yaw Dadson2026-07-08

📄 earth_science

Blue Water Footprint of Hydropower Generation under Arid and Semi-Arid Climatic Conditions

This study quantifies the blue water footprint of 25 Iranian hydropower plants from 2004 to 2021, revealing that evaporation losses in arid and semi-arid regions are significantly high and highly variable, thereby underscoring the urgent need for improved reservoir management and climate-integrated strategies to ensure sustainable energy-water interactions.

Seyed Mohsen Mousavi, Forouzan Farrokhian2026-07-08

📄 earth_science

Building blocks for 3D fuelbeds: object-centered scanning and meshing protocol

This paper introduces an object-centered scanning and meshing protocol using industrial-grade laser scanners to generate high-precision 3D digital twins of individual wildland fuel particles, establishing a foundational framework for improving fire behavior, emissions, and ecological modeling through detailed structural characterization.

Iris Mire, Jessie Thoreson, Susan Prichard, Michael Gallagher, Matthew Patterson, Nicholas Skowronski2026-07-08

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