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Articles 661 - 690 of 6788
Full-Text Articles in Environmental Indicators and Impact Assessment
Assessment Of Estuarine Respiration And Benthic Nutrient Fluxes In Mississippi Sound, Nur Pasha Sufian
Assessment Of Estuarine Respiration And Benthic Nutrient Fluxes In Mississippi Sound, Nur Pasha Sufian
Master's Theses
This study quantified seasonal and spatial variability of both water column and benthic respiration rates as well as benthic nutrient fluxes along the Mississippi Sound. Respiration was measured in recirculating incubation chambers using Firesting optical DO sensors (PyroScience GmbH), and changes in nutrient concentrations were assessed. Mean water column respiration rates ranged from 0.35 and 2.76 µM O₂ hr⁻¹, with the lowest rates in the winter and the highest in the summer while detectable nutrient concentrations (ammonium, (NH₄⁺), and soluble reactive phosphate (PO₄³⁻)) showed only slight decreases (< 1 µM) over all seasons. Sediment incubation chambers consistently had much greater oxygen declines than the water incubations and showed seasonal trends with the highest mean respiration rates measured in the summer and the lowest mean in the winter, with a range from 107.4 to 1514.9 µmol O₂ m⁻² hr⁻¹ (2.6 to 36.3 mmol O₂ m⁻² d⁻¹). Sediment incubations consistently showed increases in NH₄⁺ concentrations in the overlying water, resulting in calculated NH₄⁺ benthic flux rates of 0.73 to 379.01 µM N m⁻² hr⁻¹ with the lowest rates in the winter and highest rates in the summer. Although PO₄³⁻ concentrations were often below detection in cooler seasons, PO₄³⁻ flux also peaked during the summer (< 28.8 µmol P m⁻² hr⁻¹). In this study, temperature was a key regulator for estuarine respiration and benthic nutrient flux rates, and these rates were positively correlated with porewater nutrient concentrations and sedimentary organic matter. These findings illustrate that benthic respiration can contribute to water column hypoxia and that sediments serve as a source of nutrients to the water column. Overall, these findings provide us with valuable insight about the seasonal coupling of oxygen demand and nutrient flux in the Mississippi Sound and provide valuable baseline data for future biogeochemical modelling of hypoxia, eutrophication, and productivity.
Multi-Crop Systems And Crop-Switching Strategies To Enhance Water Use Efficiency And Climate Resilience In Arid Agricultural Regions, Shahryar Fazli, Wenzhao Li, Surendra Maharjan, Hesham El-Askary
Multi-Crop Systems And Crop-Switching Strategies To Enhance Water Use Efficiency And Climate Resilience In Arid Agricultural Regions, Shahryar Fazli, Wenzhao Li, Surendra Maharjan, Hesham El-Askary
Mathematics, Physics, and Computer Science Faculty Articles and Research
Agriculture in the Lower Colorado River (LCR) region faces mounting challenges from climate change, arid conditions, and water scarcity. This study evaluates water use efficiency (WUEc) and crop-switching strategies under SSP2-4.5 and SSP5-8.5 scenarios for 2025–2049, 2050–2074, and 2075–2099. Using historical data, climatic drivers such as temperature and precipitation were analyzed for their influence on key crops, including durum wheat, winter wheat, and corn. Results show SSP2-4.5 supports water use reductions up to 16%, stable profits (80–90%), and modest calorie increases (up to 15%), while SSP5-8.5 poses severe challenges, with water use reductions of 2–5%, profits dropping to around 20%, …
Wildfires Classification In Canadian Boreal Forest: A Comparative Study Of Logistic Regression And Xgboost Models, Brandon Tran, Elijah James Duran, Mike Luu, Hesham Morgan, Surendra Maharjan, Wenzhao Li, Hesham El-Askary
Wildfires Classification In Canadian Boreal Forest: A Comparative Study Of Logistic Regression And Xgboost Models, Brandon Tran, Elijah James Duran, Mike Luu, Hesham Morgan, Surendra Maharjan, Wenzhao Li, Hesham El-Askary
Mathematics, Physics, and Computer Science Faculty Articles and Research
In recent years, Canada has faced a growing number of wildfires. These events have devastated ecosystems, displaced communities, and posed severe health risks. To minimize the damage caused by such disasters, this study aims to develop an early warning system that predicts wildfire occurrences. Two machine learning models for binary classification of wildfire occurrence in Canadian wild forests, Logistic regression and XGBoost, will be compared and evaluated. The models are used to predict the likelihood of wildfire events based on various environmental and climatic factors. The models are evaluated using a 70-30 split validation approach and their performance is assessed …
Decoding Teleconnection Impacts On Hydrological Switches In The Conus Using Wavelet Analysis, Surendra Maharjan, Wenzhao Li, Shahryar Fazli, Hesham Morgan, Hesham El-Askary
Decoding Teleconnection Impacts On Hydrological Switches In The Conus Using Wavelet Analysis, Surendra Maharjan, Wenzhao Li, Shahryar Fazli, Hesham Morgan, Hesham El-Askary
Mathematics, Physics, and Computer Science Faculty Articles and Research
Hydrometeorological teleconnections are key drivers of hydrological processes, representing the influence of large-scale atmospheric circulation patterns on regional climates. Understanding these teleconnections provides crucial insights into the mechanisms underlying hydrometeorological phenomena, particularly hydrological switches—rapid transitions between extreme events such as droughts and floods. These switches have become increasingly prevalent across the contiguous United States (CONUS), fueled by climate variability and evolving atmospheric patterns. This study utilizes cross-wavelet transform analysis to examine the spatial and temporal dynamics of hydrological switches and their correlations with major teleconnection indices, including NAO, ONI, WP, PDO, PNA, and QBO. The findings indicate significant coherence between …
Insights From Swot Data On Transboundary Upstream-Downstream Impacts In The Nile Basin, Hesham Morgan, Wenzhao Li, Ali Elgendy, Surendra Maharjan, Rejoice Thomas, Hesham El-Askary
Insights From Swot Data On Transboundary Upstream-Downstream Impacts In The Nile Basin, Hesham Morgan, Wenzhao Li, Ali Elgendy, Surendra Maharjan, Rejoice Thomas, Hesham El-Askary
Mathematics, Physics, and Computer Science Faculty Articles and Research
This study utilizes high-resolution data from NASA's Surface Water and Ocean Topography (SWOT) mission to investigate water dynamics and upstream-downstream impacts across key reservoirs in the Nile Basin. Focusing on the Grand Ethiopian Renaissance Dam (GERD), Rosaries Dam, Merowe Dam, and the Aswan High Dam, the analysis spans 15 months (August 2023 to October 2024). By systematically selecting 30 points across each reservoir, monthly boxplots of surface water elevation were generated, revealing significant temporal and spatial variability. The results show that GERD’s filling phase led to a steady increase in water levels (peaking at ~615 meters from June to October …
Assessing Meteorological Impacts On Hydrological Switches In The Conus, Surendra Maharjan, Wenzhao Li, Sujan Shrestha, Hesham El-Askary
Assessing Meteorological Impacts On Hydrological Switches In The Conus, Surendra Maharjan, Wenzhao Li, Sujan Shrestha, Hesham El-Askary
Mathematics, Physics, and Computer Science Faculty Articles and Research
Hydrological switches, defined as rapid transitions between extreme meteorological events such as droughts and floods, are becoming increasingly frequent across the contiguous United States (CONUS) due to climate variability. This study analyzes the spatial and temporal patterns of these hydrological switches and their correlation with large-scale meteorological indices, such as the Standardized Precipitation Index (SPI) and Standardized Precipitation Evapotranspiration Index (SPEI). Streamflow data from the US Geological Survey (USGS) is analyzed to investigate the impact of meteorological drivers on hydrological variability. Results indicate that regions dependent on snowmelt exhibit delayed hydrological responses to climatic conditions, while areas in the Eastern …
Highly Contaminated Sediments From The Gowanus Canal (New York) Superfund Site: An Environmental Forensic Approach, Michael A. Kruge, Kevin K. Olsen, Eric A Stern, Maria Mastalerz, Albert Permanyer
Highly Contaminated Sediments From The Gowanus Canal (New York) Superfund Site: An Environmental Forensic Approach, Michael A. Kruge, Kevin K. Olsen, Eric A Stern, Maria Mastalerz, Albert Permanyer
Department of Earth and Environmental Studies Faculty Scholarship and Creative Works
The 2.5 km long Gowanus Canal (Brooklyn, NY, USA) is a severely contaminated urban waterway dating from the mid-19th century, listed as a US Environmental Protection Agency (USEPA) Superfund site since 2010. Applying an environmental forensics approach to the extensive USEPA data set, we detect systematic variations in parent PAH ring number distributions in the canal sediments, as well as an extraordinary enrichment in organic carbon. We subjected a supplemental sample set to a more detailed analysis by quantitative pyrolysis-GC-MS, Rock-Eval pyrolysis, and organic petrology. With these sensitive methods, we can confirm the alkyl-PAH fingerprint of coal tar (a legacy …
Re: Comment Letter For Clark Tailings Consolidated Waste Management Area (Ctcwma) Site Investigation Quality Assurance Project Plan Revision 01 (Dated June 6, 2025), Emma Rott
Silver Bow Creek/Butte Area Superfund Site
No abstract provided.
Revised Draft Final Uniform Federal Policyquality Assurance Project Plan, Hydrogeologic, Inc.
Revised Draft Final Uniform Federal Policyquality Assurance Project Plan, Hydrogeologic, Inc.
Silver Bow Creek/Butte Area Superfund Site
No abstract provided.
Adaptive Crop Switching For Irrigated Agriculture In Response To Climate Change In The Western U.S., Shahryar Fazli, Wenzhao Li, Surendra Maharjan, Rejoice Thomas, Aqil Tariq, Hesham El-Askary
Adaptive Crop Switching For Irrigated Agriculture In Response To Climate Change In The Western U.S., Shahryar Fazli, Wenzhao Li, Surendra Maharjan, Rejoice Thomas, Aqil Tariq, Hesham El-Askary
Mathematics, Physics, and Computer Science Faculty Articles and Research
Adaptive irrigation strategies are crucial for balancing water use, economic viability, and food security in the arid Western United States. However, as a key indicator vital in regulating agricultural productivity and crop irrigation, water use efficiency (WUEc) is becoming increasingly complex to estimate due to climate change. This study explores the critical role of key meteorological drivers, such as maximum temperature (tmax) and vapor pressure deficit (vpd), and their impacts on crop-specific WUEc. Future impacts are also assessed through integrating machine learning models with climate projections from the CMIP6 framework under SSP2–4.5 and SSP5–8.5 scenarios to forecast WUEc trends from …
Re: Butte Mine Flooding Operable Unit Berkeley Pit And Discharge Pilot Project – June 2025 Monthly Discharge Monitoring Report, Mark Thompson, Dave Griffis
Re: Butte Mine Flooding Operable Unit Berkeley Pit And Discharge Pilot Project – June 2025 Monthly Discharge Monitoring Report, Mark Thompson, Dave Griffis
Silver Bow Creek/Butte Area Superfund Site
No abstract provided.
High Spatial Resolution Crop Type And Land Use Land Cover Classification Without Labels: A Framework Using Multi-Temporal Planetscope Images And Variational Bayesian Gaussian Mixture Model, Minh Tri Le
Mathematics, Physics, and Computer Science Faculty Articles and Research
Previous studies often combined high spatial resolution data (e.g., PlanetScope) with wider spectral range data (e.g., Sentinel-2) and relied on supervised classification methods to produce land use and land cover (LULC) maps. This study proposed a new unsupervised framework to generate crop type and LULC maps at high spatial resolution (< 5 m) using available PlanetScope data solely without requiring ground truths. We used PlanetScope surface reflectance images and their derived spectral indices during growing seasons to create multi-temporal input features, which were fed into an unsupervised Variational Bayesian Gaussian Mixture Model (VBGMM). The VBGMM, unlike the traditional unsupervised classification methods, (1) first estimated optimal parameters that are most suitable based on the input features and then (2) assigned pixels to the cluster with maximum posteriori probability of a mixture of several Gaussian distributions. The crop type and LULC maps were then generated by labeling the derived clusters using the best possible assignment method, referring to the existing crop type or LULC products. We evaluated the produced PlanetScope-based crop type and LULC maps using true labels, corresponding reference maps, and other unsupervised classification methods. The results demonstrated the robustness and effectiveness of the proposed framework in mapping crop types and LULC at 3–5 m pixels across various ecosystems, climate zones, and human-managed landscapes. The spatial patterns of PlanetScope-based maps were (1) highly comparable with all the reference datasets at 10–30 m spatial resolution and (2) better than the traditional GMM and K-means clustering methods. The VBGMM produced classification maps with high confidence, yielding class probabilities above 0.9 for over 90 % of all study areas. The area percentage for all crop type and LULC classes agreed well with their reference maps, with R2 of 0.95 and RMSE of 1.04 %. The confusion matrices using true labels indicated that PlanetScope-based maps achieved a higher overall accuracy of 84 % than the supervised referenced maps of 81 %. Besides, the entropy comparison showed that our framework-based maps were better at capturing fine-scale features such as developed areas within cities that commonly mix with open space and vegetation, deforestation and cropland conversion in South America, smallholder croplands in Africa and Asia, and generating homogeneous crop fields in North America. This study further highlighted the potential for future research to implement our proposed framework to generate timely and extensive annotated datasets, which can be used for operationally training machine learning models to map crop types and LULC, track deforestation, detect wildfires, and delineate flooded areas at larger scales using medium/coarse Earth observations.
Re: Approval Letter For The Butte Priority Soils Operable Unit (Bpsou) Insufficiently Reclaimed Sites Sampling: Bres No. 84 Site Evaluation Summary Report (Dated April 11, 2025), Molly Roby
Silver Bow Creek/Butte Area Superfund Site
No abstract provided.
Re: Comment Letter For The Butte Priority Soils Operable Unit (Bpsou) Draft Final 2022 Unreclaimed Sites Sampling: Ur-06 Site Evaluation Summary Report (Dated April 1, 2025), Molly Roby
Silver Bow Creek/Butte Area Superfund Site
No abstract provided.
Re: Comment Letter For The Butte Priority Soils Operable Unit (Bpsou) Unreclaimed Sites Ur-22 Site Evaluation Summary Report (Dated April 2, 2025), Molly Roby
Silver Bow Creek/Butte Area Superfund Site
No abstract provided.
Re: Comment Letter For The Butte Priority Soils Operable Unit (Bpsou) Draft Final 2025 Residential Metals Abatement Program (Rmap) Valley Sand & Gravel (Builders Firstsource) Borrow Submittal #1 (Dated June 27, 2025), Molly Roby
Silver Bow Creek/Butte Area Superfund Site
No abstract provided.
Re: Comment Letter For The Butte Priority Soils Operable Unit (Bpsou) Draft Final 2022 Unreclaimed Sites Sampling: Ur-12 Site Evaluation Summary Report (Dated April 8, 2025), Molly Roby
Silver Bow Creek/Butte Area Superfund Site
No abstract provided.
Re: Comment Letter For Bpsou Uncontrolled Surface Flow Areas Drainage C 30% Design Rawp (Dated June 23, 2025), Molly Roby
Silver Bow Creek/Butte Area Superfund Site
No abstract provided.
Re: Comment Letter For The Draft Final Butte Priority Soils Operable Unit (Bpsou) 2022 Unreclaimed Sites Sampling: Ur-20 Site Evaluation Summary Report (Dated March 19, 2025), Molly Roby
Silver Bow Creek/Butte Area Superfund Site
No abstract provided.
Re: June 2025 Berkeley Pit Migratory Waterfowl Protection Monthly Report, Mark Thompson, Loren Burmeister
Re: June 2025 Berkeley Pit Migratory Waterfowl Protection Monthly Report, Mark Thompson, Loren Burmeister
Silver Bow Creek/Butte Area Superfund Site
No abstract provided.
Re: Butte Priority Soils Operable Unit (Bpsou) Superfund Operation And Maintenance (O&M) Request For Maintenance – Kelley Stormwater Channels (Dated April 22, 2025), Josh Bryson
Silver Bow Creek/Butte Area Superfund Site
No abstract provided.
Re: Comments On The Repository, Haul Route, And Pipeline Geotechnical Pre-Design Investigation Summary Report (Dated May 13, 2025), Emma Rott
Silver Bow Creek/Butte Area Superfund Site
No abstract provided.
Re: Comment Letter For Butte Priority Soils Operable Unit (Bpsou) Draft 2024 Groundwater Monitoring Data Summary Report (Dated May 30, 2025), Emma Rott
Silver Bow Creek/Butte Area Superfund Site
No abstract provided.
Re: Comment Letter For The Butte Priority Soils Operable Unit (Bpsou) 2022 Draft Final Insufficiently Reclaimed Sites Sampling Bres No. 30 – Atlantic 1 Site Evaluation Summary Report (Dated February 24, 2025), Molly Roby
Silver Bow Creek/Butte Area Superfund Site
No abstract provided.
Hyperspectral Band Selection Via Heterogeneous Graph Convolutional Self-Representation Network, Junde Chen, Wenzhao Li, Surendra Maharjan, Hesham El-Askary
Hyperspectral Band Selection Via Heterogeneous Graph Convolutional Self-Representation Network, Junde Chen, Wenzhao Li, Surendra Maharjan, Hesham El-Askary
Mathematics, Physics, and Computer Science Faculty Articles and Research
Hyperspectral image (HSI) band selection (BS) plays a crucial role in HSI dimensionality reduction, aiming to identify a representative subset of bands with minimal redundancy. However, conventional BS approaches primarily operate in the Euclidean domain, often overlooking the structural characteristics of pixels and spectral bands, such as spatial continuity and spectral dependencies. In addition, they handle each HSI as an integrated unit to harness implicit spatial information, disregarding spatial distribution variations across different homogeneous regions. To fully leverage structural information, this study introduces a novel BS method, termed the dual heterogeneous graph convolutional network with enhanced self-representation (ESR-HGCN), for HSI …
Re: Comment Letter For The Butte Priority Soils Operable Unit (Bpsou) 2022 Draft Final Insufficiently Reclaimed Sites Sampling: Bres No. 32 Site Evaluation Summary Report (Dated December 11, 2024), Molly Roby
Silver Bow Creek/Butte Area Superfund Site
No abstract provided.
Re: Comment Letter For The Butte Priority Soils Operable Unit (Bpsou) 2022 Draft Final Insufficiently Reclaimed Sites Sampling: Bres No. 38 – Sister Dump Site Evaluation Summary Report (December 31, 2024), Molly Roby
Silver Bow Creek/Butte Area Superfund Site
No abstract provided.
Re: Approval Of The Butte Priority Soils Operable Unit (Bpsou) Butte Reclamation Evaluation System (Bres) Revised Draft 2024 Field Evaluation Summary And Technical Recommendations Report (Dated June 4, 2025), Molly Roby
Silver Bow Creek/Butte Area Superfund Site
No abstract provided.
Re: Approval Letter For The Response To Comment Letter And The Butte Priority Soils Operable Unit (Bpsou) Draft 2024 Butte Reclamation Evaluation System (Bres) Corrective Action Plans For Reclaimed Sites (Both Dated June 6, 2025), Molly Roby
Silver Bow Creek/Butte Area Superfund Site
No abstract provided.
Re: Comment Letter For 2024 Annual Operations And Maintenance Report Butte Reclamation Evaluation System (Bres) Annual Summary Report For Work Completed In Quadrant 4 (Dated May 1, 2025), Molly Roby
Silver Bow Creek/Butte Area Superfund Site
No abstract provided.