Vermont State Colleges

Non-stationarity has long been recognized as a fundamental challenge in hydrological modelling, as climate change and human activities continuously alter catchment properties and the boundary conditions under which hydrological systems operate. However, translating this long-standing recognition into systematic model evaluation remains challenging, as suitable large-sample hydrological datasets that explicitly represent temporal change are still scarce. Most existing datasets adopt a static design, with time-invariant catchment attributes and hydro-meteorological time series limited to retrospective observations, which constrains the systematic testing of hypotheses and models targeting non-stationary hydrological behaviour. Here, we introduce Changing-CAMELS, a pan-European, CAMELS-style dataset explicitly designed to support non-stationary hydrological modelling. Building on the strengths of existing datasets such as CAMELS, Caravan, and EStreams, the developed dataset moves beyond static representations by incorporating time-varying catchment attributes and future climate forcing on a European scale.In particular, dynamic land-use and land-cover changes are derived from the European LUCAS dataset, providing annual updates to vegetation and land-cover fractions. Simultaneously, the inclusion of both raw and bias-corrected daily-resolution regional and global climate model datasets extends hydro-meteorological forcing beyond the historical period. This integration enables consistent analyses of evolving land cover, shifting climate regimes, and their combined impacts on hydrological responses. Changing-CAMELS covers 4,575 catchments across Europe and harmonizes observations and attributes across national boundaries. By providing both retrospective and prospective information within a unified framework, the dataset allows researchers to systematically evaluate competing hypotheses, compare stationary and non-stationary model formulations, and assess the robustness and uncertainty of hydrological models under climate and land-use change.

Abstract Climate change and land use/land cover (LULC) changes influence streamflow by altering precipitation patterns, evaporation, and hydrological processes. Disentangling their combined effects is critical for effective water management under increasing climatic and environmental pressures. This meta‐analysis integrates quantitative and qualitative approaches to assess the impacts of precipitation, temperature, and LULC changes on streamflow using published data sets, multiple linear regression, and Random Forest models. Precipitation emerges as the dominant driver, showing significant variability and a direct linear correlation with streamflow. Temperature impacts are inconsistent, while LULC changes demonstrate nuanced effects. Conversions to agriculture generally increase streamflow, whereas transitions to forests reduce it. Multiple linear regression revealed that precipitation alone explains nearly half of the variance in streamflow, with LULC changes contributing an additional but smaller percentage. In contrast, temperature changes have minimal influence. Variability in LULC conversions correlates with residuals, underscoring diverse impacts across land use types. The Random Forest model, which allows the consideration of non‐linear dependencies, achieved R 2 values of 0.7, confirming precipitation as the most critical predictor, followed by temperature and LULC changes. Including catchment area and climate zone added no significant improvement. These findings highlight the combined importance of precipitation, temperature and LULC changes in shaping streamflow dynamics. While comprehensive, the meta‐analysis may overlook local factors such as micro‐climate variations or land management practices. The variability in model predictive power underscores the challenge of modeling nonlinear relationships between climate, LULC changes, and streamflow. The results offer critical insights for sustainable water resource management and predictive hydrological modeling.

Abstract The study explores the effectiveness of ChatGPT in fostering intercultural pragmatic competence, focusing on Japanese learners of English. Using Kecskes’ sociocognitive framework, the research examines ChatGPT’s role in conversations involving meaning negotiation and repair mechanisms. The study analyzed over 10,000 responses generated by ChatGPT during interactions with 45 students from different nationalities, ranging from upper-beginner to upper-intermediate proficiency levels, in simulated social situations. A comprehensive examination of AI and participant responses and feedback yields a sophisticated understanding of the AI strengths and flaws, along with intercultural communication repair strategies for meaning negotiation. Specifically, findings reveal that while ChatGPT effectively models certain cooperative aspects of communication, it struggles with maintaining relevance and lacks human-like repair strategies. Students often initiate self-repair instead of other-repair, indicating limited interactive feedback from ChatGPT. Furthermore, excessive information. On the positive side, ChatGPT encourages confidence in students through predictions and co-constructed phrases, although its performance is repetitive and lacks deep contextual understanding. The study recommends cautious use of ChatGPT in pragmatic learning and highlights the need for more advanced frameworks to enhance AI’s role in intercultural communication education.

Background: Autistic adults commonly experience shutdowns, which are distressing events widely discussed within Autistic communities. Yet, few studies to date have explored firsthand accounts of shutdown experiences. In this study, we aimed to identify figurative language that Autistic adults use to describe shutdowns, thereby broadening the understanding of and providing language for this complex phenomenon. Methods: We used a participatory research approach to conduct a secondary analysis of qualitative data from two prior studies on shutdowns in Autistic adults. Primary studies used asynchronous interviews and a survey, with a total sample size of 86 participants. We analyzed a corpus of 87 typed pages using the Pragglejaz Group’s metaphor identification procedure to identify figurative language that Autistic adults used to describe shutdowns. Results: Autistic adults in this sample used six metaphors to explain shutdowns, including the following: being frozen, a computer crash, going inside myself, when I can’t keep up, survival mode, and playing a role. Discussion: These metaphors help to externalize the internal experience of shutdowns. Participants described shutdowns as a state of being stuck, often involving physical and/or vocal immobilization. They frequently described shutdowns as a response to perceived threats, connecting them to a sense of survival and self-protection. Metaphors provide a rich context for understanding and talking about shutdowns. Findings also highlight how Autistic adults organically construct metaphors to articulate their experiences. Future studies could use metaphor analysis to explore other affective experiences of Autistic individuals.

In order to develop technologies to use lunar ice as a resource, it is important to be able to produce representative analogs, or simulants, of icy lunar regolith. Unfortunately, previous work in this area has not been relevant to the lunar environment due to the practice of mixing liquid water with a regolith simulant before freezing. The lunar near subsurface cannot support liquid water due to very low temperatures and pressures, so water ice modification processes are limited to sublimation deposition. In this work, we investigate the microstructure of various icy lunar regolith simulants via micro-CT scans, including pressure sintered (PSS), thermally sintered (TSS), wet mixed, and unsintered. We show that the PSS and TSS samples are microstructurally most similar to each other and exhibit stark differences to the wet mix samples. We found that the presence of liquid water in the sample preparation process drastically altered the microstructure of the samples and identified key features differentiating the lunar-relevant sintering processes from the wet-mixed samples, including differences in total porosity, pore size, ice particle size, and degree of ice-regolith interconnection. These microstructural dissimilarities are caused in large part by the wetting and lubricating behaviors of liquid water. We conclude that because liquid water cannot exist in the lunar near subsurface and has been shown to behave fundamentally differently from sintered samples at the microstructural level, dry-mixed and sintered analogs should be used for lunar technology development, rather than wet-mixed analogs.

Abstract Winter/spring runoff has changed in streams worldwide due to climate change, particularly in temperate areas where winter/spring streamflow depends on snowmelt. Such changes potentially affect receiving waters through altered nutrient loading and mixing patterns. The Laurentian Great Lakes are an important freshwater resource and have experienced a myriad of impacts due to climate change. We analyzed 70 years of stream gauge data in the Great Lakes Basin to test for changes in timing, duration, and amount of winter/spring runoff during the period 1950–2019. We found strong evidence for earlier runoff in each of the Great Lakes except Lake Erie, protracted winter/spring runoff throughout the Great Lakes Basin, and a higher runoff depth during the winter‐spring period over time for all watersheds except Lake Superior. Lake Ontario had the greatest change in the date by which 50% of the Jan–May runoff had been discharged (6 days earlier from 1950 to 2019). For winter/spring runoff duration, the most extreme change was observed in Lake Erie (increase of 19 days), and for runoff depth, the greatest change was in the Lake Huron Basin (increase of 3.3 cm). Results were similar for natural and impacted streams. Our results demonstrate dramatic changes in runoff patterns over the last seven decades in the Great Lakes Basin concomitant with previously published changes in precipitation and snowpack. Shifts toward earlier, more protracted, and more voluminous runoff likely change nutrient loading and mixing patterns that influence primary producers, particularly in the nearshore areas of the Great Lakes.

Currently, the concept of plant capture efficiency is not quantitatively considered in the evaluation of off-target drift for the purposes of pesticide risk assessment in the United States. For on-target pesticide applications, canopy capture efficiency is managed by optimizing formulations or tank-mixing with adjuvants to maximize retention of spray droplets. These efforts take into consideration the fact that plant species have diverse morphology and surface characteristics, and as such will retain varying levels of applied pesticides. This work aims to combine plant surface wettability potential, spray droplet characteristics, and plant morphology into describing the plant capture efficiency of drifted spray droplets. In this study, we used wind tunnel experiments and individual plants grown to 10-20cm to show that at two downwind distances and with two distinct nozzles capture efficiency for sunflower (Helianthus annuus L.), lettuce (Lactuca sativa L.), and tomato (Solanum lycopersicum L.) is consistently higher than rice (Oryza sativa L.), peas (Pisum sativum L). and onions (Allium cepa L.), with carrots (Daucus carota L.) showing high variability and falling between the two groups. We also present a novel method for three-dimensional modeling of plants from photogrammetric scanning and use the results in the first known computational fluid dynamics simulations of drift capture efficiency on plants. The mean simulated drift capture efficiency rates were within the same order of magnitude of the mean observed rates of sunflower and lettuce, and differed by one to two orders for rice and onion. We identify simulating the effects of surface roughness on droplet behavior, and the effects of wind flow on plant movement as potential model improvements requiring further species-specific data collection.

Accurate characterization of contaminant mass in zones of low hydraulic conductivity (low k) is essential for site management because this difficult-to-treat mass can be a long-term secondary source. This study developed a protocol for the membrane interface probe (MIP) as a low-cost, rapid data-acquisition tool for qualitatively evaluating the location and relative distribution of mass in low-k zones. MIP operating parameters were varied systematically at high and low concentration locations at a contaminated site to evaluate the impact of the parameters on data quality relative to a detailed adjacent profile of soil concentrations. Evaluation of the relative location of maximum concentrations and the shape of the MIP vs. soil profiles led to a standard operating procedure (SOP) for the MIP to delineate contamination in low-k zones. This includes recommendations for: (1) preferred detector (ECD for low concentration zones, PID or ECD for higher concentration zones); (2) combining downlogged and uplogged data to reduce carryover; and (3) higher carrier gas flow rate in high concentration zones. Linear regression indicated scatter in all MIP-to-soil comparisons, including R(2) values using the SOP of 0.32 in the low concentration boring and 0.49 in the high concentration boring. In contrast, a control dataset with soil-to-soil correlations from borings 1-m apart exhibited an R(2) of ≥ 0.88, highlighting the uncertainty in predicting soil concentrations using MIP data. This study demonstrates that the MIP provides lower-precision contaminant distribution and heterogeneity data compared to more intensive high-resolution characterization methods. This is consistent with its use as a complementary screening tool.

As faculty collective bargaining reaches the half-century mark, the authors take a critical look at what has or has not worked at the bargaining table; how the early expectations of what faculty bargaining would bring to the academy have or have not been realized; and what the future holds, both in terms of process and the substantive issues that will be brought to the table. Dr. Julius has been a faculty member, administrator and employer representative in negotiations at many institutions; Mr. DiGiovanni has served a labor counsel and has negotiated with faculty unions at numerous institutions since the late 1970s. Both share their retrospective on what is new today and what has not changed over that time.