5 Feb 2026

GeoClimate Intelligence Platform: A Web-Based Framework for Environmental Data Analysis

Abstract: Environmental science education faces a critical barrier: programming requirements prevent students, novice researchers, and domain experts from accessing planetary-scale datasets. This study presents the GeoClimate Intelligence Platform, a web-based framework powered by Google Earth Engine (GEE) that eliminates programming barriers while maintaining research-grade analytical capabilities. The platform comprises five integrated modules: GeoData Explorer for climate dataset access, Climate Analytics implementing 20+ ETCCDI-compliant climate indices, Hydrology Analyzer for precipitation analysis and return periods, Product Selector for dataset validation, and Data Visualizer for interactive analysis. This modular design supports integrated workflows while maintaining analytical independence across specialized functions. Development was motivated by workshops where students found programming barriers insurmountable despite strong motivation. Educational validation through university coursework demonstrated effectiveness. Performance evaluation shows robust scalability from educational to research-scale applications. The platform requires only a GEE account and operates through web browsers, eliminating software installation. This accessibility transformation enables broader participation in data-driven environmental problem-solving with scientific rigor, democratizing sophisticated environmental analysis for educational and research communities.

5 Feb 2026

Upscaling Nature-Based Solutions for Reducing Risk from Natural Hazards: From Process to Practice

Abstract: Nature-based solutions (NbS) offer an innovative approach to reducing risks from natural hazards, aligning ecological processes with engineering objectives. However, successfully scaling NbS from site-specific interventions to systems-level applications remains a challenge. This paper examines an Engineering With Nature® (EWN®) case study to explore how NbS can be integrated into broader, systems-based engineering practices, demonstrating the transition from conceptual design to wide-scale, regional implementation. One such case study is Deer Island, located off the coast of Mississippi, USA, where EWN approaches stabilized shorelines and restored critical habitats. The project utilized natural sediment transport processes to rebuild marsh and dune systems, enhancing the island’s resilience to storm surges and erosion. Through careful integration of natural and engineered systems, Deer Island serves as a model for how NbS can mitigate risks at both local and regional scales, increasing the ability to recover from a natural disaster and overall ecological health. In particular, the case study highlights the benefit of designing for multiple integrated ecosystem components to deliver a diverse array of ecological functions, goods, and services. The paper further underscores the importance of interdisciplinary collaboration, highlighting the role of landscape architects in creating multifunctional designs that incorporate natural features and processes. These designs enhance ecosystem services while addressing societal needs, providing a blueprint for how when combined landscape architecture, science, and engineering can synergize in NbS projects. By synthesizing lessons from the EWN and emphasizing the need for cross-sector collaboration, this paper outlines pathways to scale NbS from localized efforts to comprehensive strategies that reduce coastal storm risk.

5 Feb 2026

Evaluating Snow Pavement Strength in Remote Cold Environments via California Bearing Ratio (CBR) and Russian Snow Penetrometer (RSP) Combined Testing

Abstract: Accurate assessment of compacted snow strength is critical for ensuring the safety and performance of snow runways in cold environments. The Russian Snow Penetrometer (RSP) is widely used in snow science and engineering due to its simplicity, portability, and capability for rapid field measurements under extreme conditions. Conversely, the California Bearing Ratio (CBR) test remains the benchmark for evaluating the load-bearing capacity of conventional granular materials but is seldom applied to snow because of logistical constraints and the material’s complex mechanical behavior. The relationship between these two pavement evaluation tools remains poorly defined. This work investigates how RSP strength indices relate to CBR measurements to determine whether the RSP can serve as a practical proxy for snow pavement load-bearing capacity. Side-by-side field measurements of snow pavement strength were collected over a 30 h period at two test section locations. Both methods captured temporal strength increases and spatial variability, with consistently higher values at the second site attributed to extended sintering. A moderate linear correlation (R2 = 0.44) between RSP and CBR results supports a quantifiable relationship between the two methods. These findings begin to bridge the gap between conventional pavement testing and snow-specific strength evaluation, demonstrating the potential of the RSP for rapid assessment of snow runways. Continued data collection and analysis will refine this relationship and strengthen its applicability for operational use.

5 Feb 2026

Compressed Snow Blocks: Evaluating the Feasibility of Adapting Earth Block Technology for Cold Regions

Abstract: Snow construction plays a crucial role in military operations in cold regions, providing tactical fortifications, thermal insulation, and emergency infrastructure in environments where conventional building materials are scarce or require extensive infrastructure for support. Current snow construction methods, including manual piling and compaction, are labor-intensive and inconsistent, limiting their use in large-scale or time-sensitive operations. This study explores the feasibility of adapting a compressed earth block (CEB) machine to produce compressed snow blocks (CSBs) as modular, uniform building units for cold-region applications. Using an AECT Impact 2001A hydraulic press, naturally occurring snow was processed with a snowblower and compacted at maximum operating pressure (i.e., 20,684 kPa) to evaluate block formation, dimensional consistency, and density. The machine successfully produced relatively consistent CSBs, but the initial 3–4 blocks following block height adjustment were generally unsuccessful (e.g., incorrect block height or collapsed/broke) while the machine reached its steady state cyclic condition. These blocks were discarded and excluded from the dataset. The successful CSBs had mean block heights of 7.76 ± 0.56 cm and densities comparable to ice (i.e., 0.83 g/cm ³). Variations in block height and mass may be attributed to manual snow loading and minor material impurities. While the dataset is limited, the results warrant further investigation into this technology, particularly regarding CSB strength (i.e., hardness and compressive strength) and performance under variable snow and environmental conditions. Mechanized snow compaction using existing CEB technology is technically feasible and capable of producing uniform, structurally stable CSBs but requires further investigation and modifications to reach its full potential. With design improvements such as automated snow feeding, cold-resistant components, and system winterization, this approach could enable scalable CSB production for rapid, on-site construction of snow-based structures in Arctic environments, supporting the military and civilian needs.

3 Feb 2026

Sensitivity and Impact of Atmospheric Forcings on Hurricane Wind Wave Modeling in the Gulf of Mexico Using Nested WAVEWATCH III

Abstract: Precise estimation of hurricane wind-induced waves is critical to enhance the accuracy of predicting coastal flooding events in real-time besides helping in the design of sustainable coastal/offshore structures. In this study, we aim to investigate the importance of atmospheric forcings and their impact on wind wave modeling for extreme hurricane conditions in the Gulf of Mexico (GOM) basin. Hurricanes Michael (2018) and Ida (2021) were chosen to be modeled as they were among the two most severe storm events that attained category 5 and category 4 status, respectively, during landfall in the GOM basin. A multi-grid nested modeling approach was implemented in WAVEWATCH III with three different wind forcings: ECMWF’s ERA5, NOAA’s High-Resolution Rapid Refresh (HRRR: v3 and v4) and ECMWF’s Operational High-Resolution Forecast Model (ECMWF) to model both hurricanes. The results generated through model simulations of various cases were compared with the field observations obtained at NDBC stations. One of the findings suggests that the ERA5 based wind model substantially underestimates the peak winds of both the hurricanes by 50–60 %, thereby resulting in significant underestimation of the wave heights by 40 %. Although the ECMWF model could not capture the maximum winds generated by Michael and Ida, it still gave better results than the ERA5 and HRRR (v3). The updated version (v4) of HRRR performed better than both ERA5 and ECMWF wind models in predicting the peak wind speeds and wind field distribution of Hurricane Ida in all the quadrants.

3 Feb 2026

Public Risk Perceptions of Advanced Water Purification in an Arid Urban Region of the U.S. Southwest: A Mixed Methods Study

Abstract: As water utilities implement potable reuse technology, there is a need to understand how to increase public acceptance and trust in public water supplies. The study objective was to use surveys and interviews in a large metropolitan area in Arizona to characterize tap water and advanced purified water acceptability, and factors contributing to (un)acceptability. Participants were recruited through a water utility email listserv for participation in an online REDCap survey and/or 1-hr Zoom interview. Surveys and interviews inquired about perceptions of tap water safety, familiarity with water reuse terms, acceptability of direct potable reuse (called “advanced water purification” in our study for consistency with state messaging), and rationales related to acceptance. Four hundred seventy-nine individuals participated in the survey, and twenty-two individuals participated in the interviews, with roughly comparable demographics for our city of interest but with slightly higher levels of household income and education. Only 36 % of survey respondents use their tap water for drinking water supplies, but (42 %) would be open to drinking advanced purified water. Semi-structured interviews were conducted in 2024 on risk-based thinking to evaluate how advanced purified water may compare to current drinking water safety and analyzed with inductive thematic analysis. Survey and interview participants wanted more reassurances (e.g., third party testing and opportunities for hands-on testing). Water utilities should prioritize transparent communication strategies, including sharing detailed third-party testing data and direct community engagement initiatives, to enhance public acceptance. Utilities can build trust through clear comparisons between advanced purified water and current tap water quality.

3 Feb 2026

A Systematic Review of Literature Utilizing Residential Smart Meter Data

Abstract: The global transition from traditional to advanced metering infrastructure (AMI) has led to an exponential increase in residential electricity consumption data collected through smart meters. Research themes and methodologies developed to analyze these data are driven largely by characteristics of smart meter datasets, such as the temporal resolution of data, the spatial and temporal extent of the dataset, and number of households included. However, these trends in the smart meter literature have not been comprehensively reviewed. Here, we present a systematic review of 268 studies analyzing smart meter data, published up to May 1, 2024, using the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) framework. Our findings reveal that cur-rent research is heavily reliant on a few open datasets, predominantly from high-income countries (e.g., the Customer Behavior Trials in Ireland and Low Carbon London in the UK), with approximately 90 % of studies utilizing data from developed countries. Although existing research highlights the potential of smart meter data to support a more sustainable and reliable electricity grid, especially in the face of rising demand and climate change, limited access to diverse data sources has constrained the inclusion of different geographic, climatic, and cultural contexts. Broader access to smart meter datasets is essential to expand research scope and generate insights applicable across different geographic and socio-economic settings; however, wider access also needs to be accompanied by well-designed privacy protections.

30 Jan 2026

Estimating Component Probability of Failure at USACE Civil Works Facilities for Asset Management

Abstract: Infrastructure components are the building blocks of US Army Corps of Engineers (USACE) facilities such as navigation locks and dams. Estimates of component probability of failure are needed to support risk-informed decisions about managing and maintaining these systems and their components. At Inland Navigation (INAV) facilities, the models and methods currently in use are based on an expert elicitation. There is a need for more objective estimates of component probability of failure derived from data using statistical models and methods. This report demonstrates these models and methods and describes what kinds of data would be needed to put them into practice. The major impediment to putting these models and methods into practice is a lack of data on the age, performance, and other characteristics of in-service components. It will take time to develop these data. In the meantime, this report describes how these statistical methods and models can be adapted for use with operational condition assessment (OCA) ratings, which USACE maintains in an existing database at the enterprise scale. Finally, this report describes an analytical approach to criticality assessment, which is a systematic process for identifying which components, if failed, would lead to significant operational disruptions.

30 Jan 2026

Linear Propagation of Tsunami and Acoustic–Gravity Waves on a Sphere: Geometrical Focusing and Defocusing

Abstract: This study investigates the propagation of tsunami and acoustic–gravity waves at oceanic scales, accounting for the Earth’s curvature within a linear, potential flow framework. While local, near-field analyses often neglect Earth’s curvature and employ Cartesian or cylindrical coordinate systems, this work utilises spherical coordinates to examine wave behaviour over large distances. The analysis reveals that wave amplitudes experience a defocusing effect as they travel from the source (e.g., the Pole) toward the equator, followed by a focusing effect as they approach the antipodal point beyond the equator. A qualitative comparison is made with the 2022 Hunga Tonga–Hunga Ha’apai volcanic eruption in the South Pacific. The study models surface-gravity (tsunami) waves propagating through a compressible water layer, as well as atmospheric acoustic–gravity waves propagating through the air. The entire analysis is carried out within the framework of linear theory.

30 Jan 2026

Well-Defined Glycopolymer Chitosan Mimics for Design of Chitosan Nanocomposites

Abstract: Chitosan, a naturally derived polysaccharide with intriguing antimicrobial and polycationic properties, is highly desirable as a biosourced and biodegradable material for biomedical, food packaging, and personal care applications. Its inherent high levels of variability in molecular weight, dispersity, and degree of deacetylation, however, make the establishment of structure− property−processing relationships difficult and limit materials development. In this study, a novel methacrylate-based glycomonomer with saccharide structure similar to that of chitosan was synthesized and copolymerized with methyl methacrylate via reversible addition−fragmentation chain-transfer (RAFT) polymerization to create a series of well-defined chitosan mimics with controlled molecular weights and low dispersity (<1.1). Evaluation of mammalian cytotoxicity and antibacterial activity against Escherichia coli and Staphylococcus aureus revealed performance similar to that of chitosan. The copolymers were used as models to evaluate difficult-to-probe interactions between chitosan and graphene oxide (GO) and elucidate mechanisms of mechanical property improvements observed in chitosan/GO nanocomposite films.