Article
Geosciences, Multidisciplinary
Jianning Ren, Jennifer C. Adam, Jeffrey A. Hicke, Erin J. Hanan, Christina L. Tague, Mingliang Liu, Crystal A. Kolden, John T. Abatzoglou
Summary: The study reveals that the impact of mountain pine beetle outbreaks on water yield in watersheds is influenced by various factors, resulting in significant spatial and temporal variations. During wet years, water yield tends to increase with higher tree mortality rates, while in dry years, water yield decreases at lower to medium mortality rates but increases at high mortality rates.
HYDROLOGY AND EARTH SYSTEM SCIENCES
(2021)
Article
Forestry
Jackson P. Audley, Christopher J. Fettig, A. Steven Munson, Justin B. Runyon, Leif A. Mortenson, Brytten E. Steed, Kenneth E. Gibson, Carl L. Jorgensen, Stephen R. McKelvey, Joel D. McMillin, Jose F. Negron
Summary: The study identified factors influencing the fall rates of lodgepole pines killed by bark beetles, with slope aspect having the strongest influence. Northern aspects, increased canopy cover, and taller snag heights decreased the probability of snag fall, while southern aspects and increased height:dbh ratios increased the probability. The predicted half-life for snag fall was around 16 years since death, with a gradual decline in snag survival probability beyond that point.
FOREST ECOLOGY AND MANAGEMENT
(2021)
Article
Forestry
Zach M. Smith, Kevin D. Chase, Etsuro Takagi, Aubree M. Kees, Brian H. Aukema
Summary: The study found that using ipsenol, an aggregation pheromone of Ips grandicollis, on jack pine logs can attract more Ips grandicollis compared to logs baited with pheromones of mountain pine beetle and host volatiles. The presence of lures for mountain pine beetle inhibits colonization by Ips grandicollis, while longhorn borers are more attracted to logs baited with ipsenol. These results suggest that common bark and woodboring species like Ips grandicollis and longhorn borers may not compete with mountain pine beetles at tree-colonizing stages, posing little resistance to invasion if mountain pine beetle were to invade the Great Lakes Region.
FOREST ECOLOGY AND MANAGEMENT
(2021)
Article
Geosciences, Multidisciplinary
Yufei Liu, Yiwen Fang, Dongyue Li, Steven A. Margulis
Summary: This study examined eight global snow products in High Mountain Asia and found that there was an average underestimation of 33% in peak annual snow storage. The variability in cumulative snowfall explained the majority of the uncertainty in peak snow storage.
GEOPHYSICAL RESEARCH LETTERS
(2022)
Review
Geosciences, Multidisciplinary
W. Tyler Brandt, Kayden Haleakala, Benjamin J. Hatchett, Ming Pan
Summary: This mini review summarizes the literature on the physical processes governing mountain rain-on-snow (ROS) events. It proposes a classification scheme using the terms active and passive to describe a snowpack's contribution to terrestrial water input (TWI) during ROS. Active snowpacks contribute meltwater to TWI via the energy balance, while passive snowpacks simply convey rainwater through the snow matrix. This classification scheme helps improve communication and interpretation of past findings, and aids in forecasting future events.
FRONTIERS IN EARTH SCIENCE
(2022)
Article
Environmental Sciences
Timothy M. Lahmers, Sujay Kumar, Daniel Rosen, Aubrey Dugger, David J. Gochis, Joseph A. Santanello, Chandana Gangodagamage, Rocky Dunlap
Summary: The NASA LIS/WRF-Hydro system, combining the capabilities of the NASA Land Information System (LIS) and WRF-Hydro model, is used to analyze the Tuolumne River basin in California. Assimilation of NASA Airborne Snow Observatory (ASO) snow water equivalent (SWE) estimates was found to reduce snow and streamflow biases, and improve streamflow skill scores in wet and dry years.
WATER RESOURCES RESEARCH
(2022)
Article
Engineering, Civil
Tao Yang, Qian Li, Rafiq Hamdi, Xi Chen, Qiang Zou, Fengqi Cui, Philippe De Maeyer, Lanhai Li
Summary: This study investigated the spatiotemporal variability of rain-on-snow (ROS) events in High Mountain Asia and its influencing factors. The results showed that ROS events occurred more frequently in higher-elevation regions and experienced a significant decrease in some areas due to warming, while increasing in other areas.
JOURNAL OF HYDROLOGY
(2022)
Review
Ecology
D. C. Romualdi, S. L. Wilkinson, P. M. A. James
Summary: This meta-analysis aims to summarize available evidence regarding mountain pine beetle (MPB) and wildfire interactions, and identify environmental and methodological indicators associated with various wildfire responses. The study found that spatial scale, forest fuels, and weather are the main drivers of variation in wildfire response post-outbreak. These findings are crucial for wildfire and forest management agencies, especially in forests newly exposed to this disturbance interaction.
Article
Engineering, Civil
Daniel T. Myers, Darren L. Ficklin, Scott M. Robeson
Summary: The incorporation of a ROS model into SWAT improved winter flows and decreased summer flows in the North American Great Lakes Basin. The model outperformed the unmodified SWAT in daily streamflow and snowpack simulation, highlighting the importance of considering ROS events in hydrological models in cold climates.
JOURNAL OF HYDROLOGY
(2021)
Article
Forestry
Curtis A. Gray, Chelsea Toone, Michael J. Jenkins, Sarah E. Null, Larissa L. Yocom
Summary: Mountain pine beetle outbreaks cause significant changes in fine surface fuels and foliar fuel moisture in whitebark pine trees, leading to differences in fuel depth and moisture content among trees with different crown conditions. The hazard of fuel availability varies across the landscape following beetle attacks.
FOREST ECOLOGY AND MANAGEMENT
(2021)
Article
Forestry
Benjamin A. Jones
Summary: The mountain pine beetle destroys millions of coniferous trees annually, leading to forest air pollution and impacting human health. Research shows that MPB-induced tree mortality results in additional deaths, emergency room visits, and hospital admissions per year, with high health costs associated with PM2.5 impact.
Article
Environmental Sciences
Su Ye, John Rogan, Zhe Zhu, Todd J. Hawbaker, Sarah J. Hart, Robert A. Andrus, Arjan J. H. Meddens, Jeffrey A. Hicke, J. Ronald Eastman, Dominik Kulakowski
Summary: Subtle changes driven by shifts in land condition or biological attributes lead to minimal alterations of the terrestrial surface, and accurate monitoring of these changes is crucial for early warning. An advanced framework called 'PIDS' was introduced to detect subtle forest disturbances using Landsat data, showing improved performance compared to other methods. This study has practical implications for detecting subtle changes in land cover using event-based reference samples.
REMOTE SENSING OF ENVIRONMENT
(2021)
Article
Mechanics
Zahra Hajati, Antonia Musso, Zachary Weller, Maya Evenden, Jaime G. Wong
Summary: The Mountain Pine Beetle, a destructive pest in Western North America, has expanded its range and population due to climate change. Understanding its flight mechanics helps predict its spread. Research shows significant differences in flight performance between sexes and age groups of beetles.
Article
Ecology
David N. Soderberg, Karen E. Mock, Richard W. Hofstetter, Barbara J. Bentz
Summary: The study investigated the genetic and environmental adaptability of mountain pine beetles to climate change, finding that both populations could thrive in warmer climate conditions, with the highest reproductive success occurring in low-elevation areas, suggesting that southward migration may not be temperature limited.
ECOLOGICAL MONOGRAPHS
(2021)
Article
Agronomy
Alba Sanmiguel-Vallelado, J. Julio Camarero, Enrique Moran-Tejeda, Antonio Gazol, Michele Colangelo, Esteban Alonso-Gonzalez, Juan Ignacio Lopez-Moreno
Summary: This study in Pyrenean valley in NE Spain found that snow dynamics have a significant impact on tree growth and functioning, influencing soil temperature and moisture. It highlights the importance of early and late growing season soil temperatures on radial growth of mountain conifers, suggesting that future climate change may increase productivity in similar mountain forests.
AGRICULTURAL AND FOREST METEOROLOGY
(2021)
Article
Computer Science, Information Systems
Davit Marikyan, Savvas Papagiannidis, Eleftherios Alamanos
Summary: This study addresses the outcomes of technology use when it falls short of expectations and the coping mechanisms users may use in such circumstances. By adopting Cognitive Dissonance Theory, the study explores how negative disconfirmation of expectations can result in positive outcomes and how negative emotions impact the selection of dissonance reduction mechanisms. The study finds that post-disconfirmation dissonance leads to feelings of anger, guilt, and regret, which correlate with dissonance reduction mechanisms, ultimately affecting satisfaction and well-being.
INFORMATION SYSTEMS FRONTIERS
(2023)
Article
Forestry
Alexis Achim, Guillaume Moreau, Nicholas C. Coops, Jodi N. Axelson, Julie Barrette, Steve Bedard, Kenneth E. Byrne, John Caspersen, Adam R. Dick, Loic D'Orangeville, Guillaume Drolet, Bianca N. Eskelson, Cosmin N. Filipescu, Maude Flamand-Hubert, Tristan R. H. Goodbody, Verena C. Griess, Shannon M. Hagerman, Kevin Keys, Benoit Lafleur, Miguel Montoro Girona, Dave M. Morris, Charles A. Nock, Bradley D. Pinno, Patricia Raymond, Vincent Roy, Robert Schneider, Michel Soucy, Bruce Stewart, Jean-Daniel Sylvain, Anthony R. Taylor, Evelyne Thiffault, Nelson Thiffault, Udaya Vepakomma, Joanne C. White
Summary: Climate change is rapidly altering forest ecosystems, leading to a diversification of public expectations regarding sustainable forest resource use. Silviculturists are transitioning from empirically derived scenarios to new approaches, focusing on observe, anticipate, and adapt. Utilizing remote sensing, developing state-of-the-art models, and implementing spatially explicit guidance are key strategies to ensure adaptive silvicultural actions in rapidly changing environments.
Article
Geochemistry & Geophysics
Andrew J. Chadwick, Nicholas C. Coops, Christopher W. Bater, Lee A. Martens, Barry White
Summary: This study assessed the performance of classifying lodgepole pine and white spruce using RGB and NIR imagery. The results showed that models trained on NIR imagery slightly outperformed those trained on RGB imagery, and models trained on spectral bands outperformed those trained on spectral indices. However, the minor difference in performance between the two sets of imagery indicated that accurate classification can be achieved using conventional RGB imagery.
IEEE GEOSCIENCE AND REMOTE SENSING LETTERS
(2022)
Article
Geochemistry & Geophysics
Daniele Marinelli, Nicholas C. Coops, Douglas K. Bolton, Lorenzo Bruzzone
Summary: Monitoring forest dynamics is crucial for sustainable forest management and conservation. This study proposes an unsupervised change detection method for lidar data based on polar change vector analysis. The method effectively discriminates between different classes of lidar change.
IEEE GEOSCIENCE AND REMOTE SENSING LETTERS
(2022)
Article
Remote Sensing
Saverio Francini, Ronald E. McRoberts, Giovanni D'Amico, Nicholas C. Coops, Txomin Hermosilla, Joanne C. White, Michael A. Wulder, Marco Marchetti, Giuseppe Scarascia Mugnozza, Gherardo Chirici
Summary: Forest disturbance monitoring is crucial for understanding greenhouse gas emissions and mitigating climate change. The use of stratified estimators can help reduce errors in estimating disturbance areas. This study presents a semi-automated procedure using Google Earth Engine for mapping and estimating forest disturbance areas.
INTERNATIONAL JOURNAL OF APPLIED EARTH OBSERVATION AND GEOINFORMATION
(2022)
Article
Remote Sensing
Martin Queinnec, Nicholas C. Coops, Joanne C. White, Verena C. Griess, Naomi B. Schwartz, Grant McCartney
Summary: In this study, dominant species groups in a large boreal forest were mapped by combining area-based and individual tree metrics derived from LiDAR data with multispectral information from Sentinel-2 imagery. The study found that variables such as reflectance in the red edge region, tree crown area and volume, and cumulative distribution of LiDAR returns in the canopy were important for discriminating between species groups.
CANADIAN JOURNAL OF REMOTE SENSING
(2023)
Article
Geography, Physical
Yangqian Qi, Nicholas C. Coops, Lori D. Daniels, Christopher R. Butson
Summary: This study explored the use of drone laser scanning (DLS) and mobile laser scanning (MLS) data individually and combined to estimate tree attributes under various canopy cover levels. The research found that weighted data improved modelling efficiency by around 20% compared to fused and MLS data. Fused and weighted data achieved comparable results and outperformed DLS/MLS data in estimating tree attributes across different canopy cover levels.
ISPRS JOURNAL OF PHOTOGRAMMETRY AND REMOTE SENSING
(2022)
Article
Remote Sensing
Levi Keay, Christopher Mulverhill, Nicholas C. C. Coops, Grant McCartney
Summary: The advent of CubeSat constellations has revolutionized the ability to observe Earth systems through time. This study developed and implemented a method for the spatial and temporal detection of forest harvest operations using images from the PlanetScope constellation. Results indicate that forest harvesting can be detected with relative accuracy, providing previously unavailable levels of spatial and temporal detail for forest stakeholders.
CANADIAN JOURNAL OF REMOTE SENSING
(2023)
Article
Chemistry, Analytical
Thomas Miraglio, Nicholas C. Coops
Summary: This paper introduces a Python package called SUREHYP for processing Hyperion hyperspectral images to derive surface reflectance. Results show that SUREHYP produces results comparable to commercial software, while being completely open-source and usable globally.
Article
Remote Sensing
Alexandre Morin-Bernard, Alexis Achim, Nicholas C. Coops
Summary: Non-stand-replacing disturbances play a significant role in northern hardwood forest dynamics, but are more difficult to characterize using satellite imagery than stand-replacing events. This study proposes a hurdle approach that attributes disturbance causal agents to specific sample plots, achieving an overall accuracy of 82.9%. Disturbance-specific models were then developed to assess the severity of partial harvests and damage from ice storms, with r-squared values of 0.57 and 0.59, respectively. These models provide important information for future silvicultural planning by capturing within-stand variability in disturbance severity.
CANADIAN JOURNAL OF REMOTE SENSING
(2023)
Review
Fisheries
Spencer Dakin Kuiper, Nicholas C. C. Coops, Scott G. G. Hinch, Joanne C. C. White
Summary: Remote sensing technology has the potential to revolutionize freshwater fish habitat monitoring by providing information across large geographic areas, but the overwhelming number of platforms, sensors, and software available may hinder its widespread use. This review examines the fundamental characteristics of remote sensing technologies used for freshwater habitat characterization, reviews studies that have utilized these technologies, and identifies key habitat features, fish species, and regions that have been examined. The review also highlights the strengths and weaknesses of different remote sensing technologies, suggests future research directions, and provides important considerations for those interested in utilizing these technologies for freshwater fish habitat characterization.
FISH AND FISHERIES
(2023)
Article
Forestry
A. R. Wotherspoon, A. Achim, N. C. Coops
Summary: This study examines the future climate trends in eight ecozones in Canada that contain managed forests. The projections suggest a warming trend and an overall increase in precipitation. The study highlights the potential impacts on dominant species and wood volume for Canada's forestry industry.
CANADIAN JOURNAL OF FOREST RESEARCH
(2023)
Article
Forestry
Jose Riofrio, Joanne C. White, Piotr Tompalski, Nicholas C. Coops, Michael A. Wulder
Summary: By developing age-independent height growth models, using multi-temporal airborne laser scanning (ALS) data, a comprehensive indicator of site quality for complex and irregular stand structures is provided. This approach leverages the accurate, spatially detailed characterization of canopy heights afforded by ALS data and is independent of stand age, increasing the possible geographic extent of height growth estimates.
FOREST ECOLOGY AND MANAGEMENT
(2023)
Article
Geography, Physical
Saverio Francini, Txomin Hermosilla, Nicholas C. Coops, Michael A. Wulder, Joanne C. White, Gherardo Chirici
Summary: Remote sensing is a major source of information for monitoring forest dynamics, but accurate surface reflectance data is often difficult to obtain. Pixel-based composites are used to generate complete coverage of the area of interest from multi-temporal images, but a comprehensive methodology for assessing the quality of these composites is currently lacking. In this study, a pixel-based composite assessment methodology based on five criteria was introduced and tested on Landsat images over Europe. The results showed that the assessment approach was effective for evaluating the quality of pixel-based composites and could be applied in various applications.
ISPRS JOURNAL OF PHOTOGRAMMETRY AND REMOTE SENSING
(2023)
Article
Ecology
Margaret E. Andrew, Douglas K. Bolton, Gregory J. M. Rickbeil, Nicholas C. Coops
Summary: This study evaluates the effects of niche-based mechanisms, including environmental filtering, niche availability, and niche packing, on biodiversity patterns. The results show that the importance of these mechanisms varies with scale, position on environmental gradients, and taxonomic group.
JOURNAL OF BIOGEOGRAPHY
(2023)
Article
Engineering, Civil
Arfan Arshad, Ali Mirchi, Javier Vilcaez, Muhammad Umar Akbar, Kaveh Madani
Summary: High-resolution, continuous groundwater data is crucial for adaptive aquifer management. This study presents a predictive modeling framework that incorporates covariates and existing observations to estimate groundwater level changes. The framework outperforms other methods and provides reliable estimates for unmonitored sites. The study also examines groundwater level changes in different regions and highlights the importance of effective aquifer management.
JOURNAL OF HYDROLOGY
(2024)
Article
Engineering, Civil
Lihua Chen, Jie Deng, Wenzhe Yang, Hang Chen
Summary: A new grid-based distributed karst hydrological model (GDKHM) is developed to simulate streamflow in the flood-prone karst area of Southwest China. The results show that the GDKHM performs well in predicting floods and capturing the spatial variability of karst system.
JOURNAL OF HYDROLOGY
(2024)
Article
Engineering, Civil
Faruk Gurbuz, Avinash Mudireddy, Ricardo Mantilla, Shaoping Xiao
Summary: Machine learning algorithms have shown better performance in streamflow prediction compared to traditional hydrological models. In this study, researchers proposed a methodology to test and benchmark ML algorithms using artificial data generated by physically-based hydrological models. They found that deep learning algorithms can correctly identify the relationship between streamflow and rainfall in certain conditions, but fail to outperform traditional prediction methods in other scenarios.
JOURNAL OF HYDROLOGY
(2024)
Article
Engineering, Civil
Yadong Ji, Jianyu Fu, Bingjun Liu, Zeqin Huang, Xuejin Tan
Summary: This study distinguishes the uncertainty in drought projection into scenario uncertainty, model uncertainty, and internal variability uncertainty. The results show that the estimation of total uncertainty reaches a minimum in the mid-21st century and that model uncertainty is dominant in tropical regions.
JOURNAL OF HYDROLOGY
(2024)
Article
Engineering, Civil
Z. R. van Leeuwen, M. J. Klaar, M. W. Smith, L. E. Brown
Summary: This study quantifies the effectiveness of leaky dams in reducing flood peak magnitude using a transfer function noise modelling approach. The results show that leaky dams have a significant but highly variable impact on flood peak magnitude, and managing expectations should consider event size and type.
JOURNAL OF HYDROLOGY
(2024)
Article
Engineering, Civil
Zeda Yin, Yasaman Saadati, M. Hadi Amini, Linlong Bian, Beichao Hu
Summary: Combined sewer overflows pose significant threats to public health and the environment, and various strategies have been proposed to mitigate their adverse effects. Smart control strategies have gained traction due to their cost-effectiveness but face challenges in balancing precision and computational efficiency. To address this, we propose exploring machine learning models and the inversion of neural networks for more efficient CSO prediction and optimization.
JOURNAL OF HYDROLOGY
(2024)
Article
Engineering, Civil
Qimou Zhang, Jiacong Huang, Jing Zhang, Rui Qian, Zhen Cui, Junfeng Gao
Summary: This study developed a N-cycling model for lowland rural rivers covered by macrophytes and investigated the N imports, exports, and response to sediment dredging. The findings showed a considerable N retention ability in the study river, with significant N imports from connected rivers and surrounding polders. Sediment dredging increased particulate nitrogen resuspension and settling rates, while decreasing ammonia nitrogen release, denitrification, and macrophyte uptake rates.
JOURNAL OF HYDROLOGY
(2024)
Article
Engineering, Civil
Xue Li, Yingyin Zhou, Jian Sha, Man Zhang, Zhong-Liang Wang
Summary: High-resolution climate data is crucial for predicting regional climate and water environment changes. In this study, a two-step downscaling method was developed to enhance the spatial resolution of GCM data and improve the accuracy for small basins. The method combined medium-resolution climate data with high-resolution topographic data to capture spatial and temporal details. The downscaled climate data were then used to simulate the impacts of climate change on hydrology and water quality in a small basin. The results demonstrated the effectiveness of the downscaling method for spatially differentiated simulations.
JOURNAL OF HYDROLOGY
(2024)
Article
Engineering, Civil
Tongqing Shen, Peng Jiang, Jiahui Zhao, Xuegao Chen, Hui Lin, Bin Yang, Changhai Tan, Ying Zhang, Xinting Fu, Zhongbo Yu
Summary: This study evaluates the long-term interannual dynamics of permafrost distribution and active layer thickness on the Tibetan Plateau, and predicts future degradation trends. The results show that permafrost area has been decreasing and active layer thickness has been increasing, with an accelerated degradation observed in recent decades. This has significant implications for local water cycle processes, water ecology, and water security.
JOURNAL OF HYDROLOGY
(2024)
Article
Engineering, Civil
Chi Zhang, Xu Zhang, Qiuhong Tang, Deliang Chen, Jinchuan Huang, Shaohong Wu, Yubo Liu
Summary: Precipitation over the Tibetan Plateau is influenced by systems such as the Asian monsoons, the westerlies, and local circulations. The Indian monsoon, the westerlies, and local circulations are the main systems affecting precipitation over the entire Tibetan Plateau. The East Asian summer monsoon primarily affects the eastern Tibetan Plateau. The Indian monsoon has the greatest influence on precipitation in the southern and central grid cells, while the westerlies have the greatest influence on precipitation in the northern and western grid cells. Local circulations have the strongest influence on the central and eastern grid cells.
JOURNAL OF HYDROLOGY
(2024)
Article
Engineering, Civil
Manuel Almeida, Antonio Rodrigues, Pedro Coelho
Summary: This study aimed to improve the accuracy of Total Phosphorus export coefficient models, which are essential for water management. Four different models were applied to 27 agroforestry watersheds in the Mediterranean region. The modeling approach showed significant improvements in predicting the Total Phosphorus diffuse loads.
JOURNAL OF HYDROLOGY
(2024)
Article
Engineering, Civil
Yutao Wang, Haojie Yin, Ziyi Wang, Yi Li, Pingping Wang, Longfei Wang
Summary: This study investigated the distribution and transformation of dissolved organic nitrogen (DON) in riverbed sediments impacted by effluent discharge. The authors found that the spectral characteristics of dissolved organic matter (DOM) in surface water and sediment porewater could be used to predict DON variations in riverbed sediments. Random forest and extreme gradient boosting machine learning methods were employed to provide accurate predictions of DON content and properties at different depths. These findings have important implications for wastewater discharge management and river health.
JOURNAL OF HYDROLOGY
(2024)
Article
Engineering, Civil
Saba Mirza Alipour, Kolbjorn Engeland, Joao Leal
Summary: This study assesses the uncertainty associated with 100-year flood maps under different scenarios using Monte Carlo simulations. The findings highlight the importance of employing probabilistic approaches for accurate and secure flood maps, with the selection of probability distribution being the primary source of uncertainty in precipitation.
JOURNAL OF HYDROLOGY
(2024)
Article
Engineering, Civil
Janine A. de Wit, Marjolein H. J. van Huijgevoort, Jos C. van Dam, Ge A. P. H. van den Eertwegh, Dion van Deijl, Coen J. Ritsema, Ruud P. Bartholomeus
Summary: The study focuses on the hydrological consequences of controlled drainage with subirrigation (CD-SI) on groundwater level, soil moisture content, and soil water potential. The simulations show that CD-SI can improve hydrological conditions for crop growth, but the success depends on subtle differences in geohydrologic characteristics.
JOURNAL OF HYDROLOGY
(2024)
Article
Engineering, Civil
Constantin Seidl, Sarah Ann Wheeler, Declan Page
Summary: Water availability and quality issues will become increasingly important in the future due to climate change impacts. Managed Aquifer Recharge (MAR) is an effective water management tool, but often overlooked. This study analyzes global MAR applications and identifies the key factors for success, providing valuable insights for future design and application.
JOURNAL OF HYDROLOGY
(2024)