Physical Sciences and Mathematics Commons^™

Enhancing Urban Water Quality Through Biological-Chemical Treatment: Aquatic Macroinvertebrate Community And Temporal Chlorophyll-A Response, Matthew Chaffee

Department of Biological Systems Engineering: Dissertations and Theses

With a growing human population, urbanization is impeding a plethora of natural waterways. Of these, urban ponds play a vital role in nutrient sequestration, flood prevention, and habitat sanctuaries. However, nutrient loading can reduce habitat effectiveness and promote harmful algae blooms. To reduce internal nutrient loads, a biological-chemical treatment strategy consisting of floating treatment wetlands (FTWs) and lanthanum were applied to two urban retention ponds, Densmore and Wilderness Ridge Ponds. To measure effectiveness, chlorophyll-a samples were collected and correlated with Sentinel-2. A novel band algorithm termed 3BR1 produced a strong correlation (R² = 0.72) to physical chlorophyll-a …

Causes And Effects Of Shisper Glacial Lake Outburst Flood Event In Karakoram In 2022, Sandeep Kumar Mondal, Vatsal D. Patel, Rishikesh Bharti, Ramesh P. Singh

Biology, Chemistry, and Environmental Sciences Faculty Articles and Research

Karakoram Himalayas are vulnerable to glacial lake outburst floods (GLOFs), which cause catastrophic floods in the surrounding areas. The increasing natural and anthropogenic activities, especially in the Indo-Gangetic Plains at the southern flank of the towering Himalayas, could be the cause of climate change affecting the frequency of the natural hazards in the Himalayas. In the present study, a detailed analysis of the Shisper Lake breach of 7 May 2022 is carried out using satellite remote sensing. A decreasing trend in the glacial mass balance is observed between 2017 and 2021; in this period, frequent GLOF episodes occurred. A pronounced …

Snowpack Relative Permittivity And Density Derived From Near-Coincident Lidar And Ground-Penetrating Radar, Randall Bonnell, Daniel Mcgrath, Andrew R. Hedrick, Ernesto Trujillo, Tate G. Meehan, Keith Williams, Hans-Peter Marshall, Graham Sexstone, John Fulton, Michael J. Ronayne, Steven R. Fassnacht, Ryan Webb, Katherine E. Hale

Geosciences Faculty Publications and Presentations

Depth-based and radar-based remote sensing methods (e.g., lidar, synthetic aperture radar) are promising approaches for remotely measuring snow water equivalent (SWE) at high spatial resolution. These approaches require snow density estimates, obtained from in-situ measurements or density models, to calculate SWE. However, in-situ measurements are operationally limited, and few density models have seen extensive evaluation. Here, we combine near-coincident, lidar-measured snow depths with ground-penetrating radar (GPR) two-way travel times (twt) of snowpack thickness to derive >20 km of relative permittivity estimates from nine dry and two wet snow surveys at Grand Mesa, Cameron Pass, and Ranch Creek, Colorado. …

A Neural-Network-Based Landscape Search Engine: Lse Wisconsin, Matthew Haffner, Matthew Dewitte, Papia F. Rozario, Gustavo A. Ovando-Montejo

Environment and Society Faculty Publications

The task of image retrieval is common in the world of data science and deep learning, but it has received less attention in the field of remote sensing. The authors seek to fill this gap in research through the presentation of a web-based landscape search engine for the US state of Wisconsin. The application allows users to select a location on the map and to find similar locations based on terrain and vegetation characteristics. It utilizes three neural network models—VGG16, ResNet-50, and NasNet—on digital elevation model data, and uses the NDVI mean and standard deviation for comparing vegetation data. The …

Hyperspectral Point Cloud Projection For The Semantic Segmentation Of Multimodal Hyperspectral And Lidar Data With Point Convolution-Based Deep Fusion Neural Networks, Kevin T. Decker, Brett J. Borghetti

Faculty Publications

The fusion of dissimilar data modalities in neural networks presents a significant challenge, particularly in the case of multimodal hyperspectral and lidar data. Hyperspectral data, typically represented as images with potentially hundreds of bands, provide a wealth of spectral information, while lidar data, commonly represented as point clouds with millions of unordered points in 3D space, offer structural information. The complementary nature of these data types presents a unique challenge due to their fundamentally different representations requiring distinct processing methods. In this work, we introduce an alternative hyperspectral data representation in the form of a hyperspectral point cloud (HSPC), which …

Coupling Dendroecological And Remote Sensing Techniques To Assess The Biophysical Traits Of Juniperus Virginiana And Pinus Ponderosa Within The Semi-Arid Grasslands Of The Nebraska Sandhills, R. Allen, Anastasios Mazis, Brian Wardlow, P. Cherubini, J. Hiller, David A. Wedin, Tala Awada

School of Natural Resources: Faculty Publications

Woody species encroachment is occurring within the semi-arid grasslands of the Nebraska Sandhills U.S., primarily driven by native Juniperus virginiana and Pinus ponderosa, altering ecosystems and the services they provide. Effective, low cost, and cross-scale monitoring of woody species growth and performance is necessary for integrated grassland and forest management in the face of climate variability and change. In this study, we sought to establish a relationship between remote sensing-derived vegetation indices (VIs), tree dendrochronological (raw and standardized tree ring width) measurements, and the abiotic environment [(precipitation, temperature, Palmer Drought Severity Index (PDSI), and soil water content (0–300 cm …

A Satellite-Based Monitoring System For Quantifying Surface Water And Mesic Vegetation Dynamics In A Semi-Arid Region, N. E. Kolarik, A. Roopsind, A. Pickens, J. S. Brandt

Human-Environment Systems Research Center Faculty Publications and Presentations

Semi-arid and arid systems cover one third of the earth’s land surface, and are becoming increasingly drier, but existing datasets do not capture all of the types of water resources that sustain these systems. In semi-arid environments, small surface water bodies and areas of mesic vegetation (wetlands, wet meadows, riparian zones) function as critical water resources. However, the most commonly-used maps of water resources are derived from the Landsat time series or single date aerial photographs, and are too coarse either spatially or temporally to effectively monitor water resource dynamics. In this study, we produced a Sentinel Fusion (SF) water …

Increased Floodplain Inundation In The Amazon Since 1980, Ayan Fleischmann, Fabrice Papa, Stephen K. Hamilton, Alice Fassoni-Andrade, Sly Wongchuig, Jhan Carlo Espinoza, Rodrigo Paiva, John Melack, Etienne Fluet-Chouinard, Rafael M. Almeida

School of Earth, Environmental, and Marine Sciences Faculty Publications and Presentations

Extensive floodplains throughout the Amazon basin support important ecosystem services and influence global water and carbon cycles. A recent change in the hydroclimatic regime of the region, with increased rainfall in the northern portions of the basin, has produced record-breaking high water levels on the Amazon River mainstem. Yet, the implications for the magnitude and duration of floodplain inundation across the basin remain unknown. Here we leverage state-of-the-art hydrological models, supported by in situ and remote sensing observations, to show that the maximum annual inundation extent along the central Amazon increased by 26% since 1980. We further reveal increased flood …

Dynamic Mass Loss From Greenland's Marine-Terminating Peripheral Glaciers (1985–2018), Katherine E. Bollen, Ellyn M. Enderlin, Rebecca Muhlheim

Geosciences Faculty Publications and Presentations

Global glacier mass balance decreased rapidly over the last two decades, exceeding mass loss from the Greenland and Antarctic Ice Sheets. In Greenland, peripheral glaciers and ice caps (GICs) cover only ~5% of Greenland's area but contributed ~20% of the island's ice mass loss between 2000 and 2018. Although Greenland GIC mass loss due to surface meltwater runoff has been estimated using atmospheric models, mass lost to changes in ice discharge into oceans (i.e., dynamic mass loss) remains unquantified. We use the flux gate method to estimate discharge from Greenland's 585 marine-terminating peripheral glaciers between 1985 and 2018, and compute …

Revisiting The Carbon–Biodiversity Connection, John Gamon

School of Natural Resources: Faculty Publications

This article is a Commentary on Schuldt et al., https://doi.org/10.1111/gcb.16697

The link between biodiversity and ecosystem function has long been a subject of intense interest and debate among biologists, going back to the time of Charles Darwin, whose ideas on species interactions presaged subsequent discussions of biodiversity and ecosystem function (Peterson et al., 1998). Since then, many considerations of community diversity have centered on the importance of species or functional diversity for maintaining system resilience in the face of disturbance, analogous to the way that interwoven threads maintain the function and integrity of fabric. While our language, concepts, and methods …

Multispectral Image Analysis Using Convolution Neural Networks, Arun D. Kulkarni

Computer Science Faculty Publications and Presentations

Machine learning (ML) techniques are used often to classify pixels in multispectral images. Recently, there is growing interest in using Convolution Neural Networks (CNNs) for classifying multispectral images. CNNs are preferred because of high performance, advances in hardware such as graphical processing units (GPUs), and availability of several CNN architectures. In CNN, units in the first hidden layer view only a small image window and learn low level features. Deeper layers learn more expressive features by combining low level features. In this paper, we propose a novel approach to classify pixels in a multispectral image using deep convolution neural networks …

The Impact Of Climate Change On Environmental Sustainability And Human Mortality, Xingzhi Mara Chen, Andrew Sharma, Hua Liu

Political Science & Geography Faculty Publications

Climate dictates the critical aspects of human environmental conditions. The frequency and intensity of extreme weather conditions due to human-induced climate change have alarmingly increased. Consequently, climate change directly affects environmental sustainability and human mortality in the short term and creates prolonged and complicated long-term indirect grave risks. This paper examines three-level environmental impact risks associated with climate change on human mortality. It proposes a conceptual framework for developing an empirical event-based human mortality database related to climate change and communication strategies to enhance global environmental adaptation, resilience, and sustainability.

Assessment Of An Evapotranspiration Algorithm Accounting For Land Cover Types And Photosynthetic Perspectives Using Remote Sensing Images, C. Sur, W. H. Nam, X. Zhang, Tsegaye Tadesse, Brian D. Wardlow

School of Natural Resources: Faculty Publications

No abstract provided.

Biophysical Interactions Control The Progression Of Harmful Algal Blooms In Chesapeake Bay: A Novel Lagrangian Particle Tracking Model With Mixotrophic Growth And Vertical Migration, Jilian Xiong, Jian Shen, Qubin Qin, Michelle C. Tomlinson, Yinglong J. Zhang, Xun Cai, Fei Yi, Linlin Cui, Margaret R. Mulholland

OES Faculty Publications

Climate change and nutrient pollution contribute to the expanding global footprint of harmful algal blooms. To better predict their spatial distributions and disentangle biophysical controls, a novel Lagrangian particle tracking and biological (LPT-Bio) model was developed with a high-resolution numerical model and remote sensing. The LPT-Bio model integrates the advantages of Lagrangian and Eulerian approaches by explicitly simulating algal bloom dynamics, algal biomass change, and diel vertical migrations along predicted trajectories. The model successfully captured the intensity and extent of the 2020 Margalefidinium polykrikoides bloom in the lower Chesapeake Bay and resolved fine-scale structures of bloom patchiness, demonstrating a reliable …

The Vulnerability And Resilience Of Seagrass Ecosystems To Marine Heatwaves In New Zealand: A Remote Sensing Analysis Of Seascape Metrics Using Planetscope Imagery, Ken Joseph E. Clemente, Mads S. Thomsen, Richard C. Zimmerman

OES Faculty Publications

Seagrasses are foundation species that provide ecosystem functions and services, including increased biodiversity, sediment retention, carbon sequestration, and fish nursery habitat. However, anthropogenic stressors that reduce water quality, impose large-scale climate changes, and amplify weather patterns, such as marine heatwaves, are altering seagrass meadow configurations. Quantifying large-scale trends in seagrass distributions will help evaluate the impacts of climate drivers on their functions and services. Here, we quantified spatiotemporal dynamics in abundances and configurations of intertidal and shallow subtidal seagrass (Zostera muelleri) meadows in 20 New Zealand (NZ) estuaries that span a 5-year period (mid/late 2016–early 2022) just before, …

A Workshop On Using Nasa Airs Data To Monitor Drought For The U.S. Drought Monitor, Alireza Farahmand,, Sharon Ray, Heidar Thrastarson, Stephen Licata, Stephanie Granger, Brian Fuchs

Drought Mitigation Center: Faculty Publications

Recent studies indicate that drought indicators based on near-surface air relative humidity (RH), air temperature (T), and air vapor pressure deficit (VPD), derived from the Atmospheric Infrared Sounder (AIRS) instrument aboard NASA’s Aqua satellite can detect the onset of drought earlier than other drought indicators, specifically standardized precipitation index (SPI), which is widely used for drought onset detection. A recent study showed that standardized relative humidity index (SRHI) can detect drought signals earlier than SPI (Farahmand et al. 2015). Relative humidity is a climate variable defined as the ratio of air vapor pressure to saturated vapor pressure. Precipitation and relative …