Digital Commons Network^™

Life Cycle Assessment Of New Jersey Offshore Wind, Meghann Smith, Nawal Shoaib, Pankaj Lal

Department of Earth and Environmental Studies Faculty Scholarship and Creative Works

As offshore wind gains momentum within US (United States) renewable energy goals, New Jersey's ambitious targets for offshore wind development represent a significant opportunity to reduce emissions and transition towards cleaner energy sources. This study presents a life cycle assessment (LCA) of a planned offshore wind farm off of New Jersey's coast, emphasizing the implications of a domestic supply chain. Key findings suggest that the offshore wind farm is projected to produce 0.013 kg CO2 kWh−1 of electricity generated, reflecting a 98 % decrease in carbon emissions compared to natural-gas-derived electricity. Further, when compared to carbon emissions from other renewable …

Limited Soil Water Recharge In Summer Affects Seasonal Isotopic Signatures Of Tree Xylem Water, Marius G. Floriancic, Gregory R. Goldsmith, Harsh Beria, Scott T. Allen, James W. Kirchner

Biology, Chemistry, and Environmental Sciences Faculty Articles and Research

Recent studies have reported that xylem waters in forest trees during the summer growing season are often isotopically similar to winter, rather than summer, precipitation. Several hypotheses have been proposed to explain this observation, which can be viewed as a form of ecohydrological separation, but empirical tests spanning space and time remain limited. We hypothesise that variations in the seasonal origin of precipitation found in tree xylem waters can be explained by seasonal differences in soil water recharge. We test this hypothesis by evaluating to what extent climatic aridity can explain seasonal signals in extensive surveys of the isotope ratios …

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 …

Analyzing Environmental Health: Air Pollution And Human Health Using Geospatial Data Science, Yanhong Huang

Geography ETDs

Air pollution from industrial emissions and wildfire smoke poses growing threats to public health. This dissertation employs geospatial data science to examine these challenges through three interrelated studies. The first study investigates the relationship between maternal residential exposure to industrial pollutants and low birth weight, identifying five chemicals as significant risk factors. The second study assesses the impact of industrial air pollution on lung and bronchus cancer survival, finding that exposure to 1,1,1-trichloroethane and cobalt is associated with reduced survival. The third study explores disparities in wildfire smoke PM_2.5 exposure and its association with asthma exacerbations. Results show disparities …

An Upper-Mesopelagic-Zone Carbon Budget For The Subarctic North Pacific, Brandon M. Stephens, Montserrat Roca-Martí, Amy E. Maas, Vinícius J. Amaral, Samantha Clevenger, Shawnee Traylor, Claudia R. Benitez-Nelson, Philip W. Boyd, Ken O. Buesseler, Craig A. Carlson, Nicolas Cassar, Margaret Estapa, Andrea J. Fassbender, Yibin Huang, Phoebe J. Lam, Oliver Marchal, Susanne Menden-Deuer, Nicola L. Paul, Alyson E. Santoro, David A. Siegel, David P. Nicolson

Faculty Publications

Mesopelagic zone (MZ) carbon budgets comparing supply with demand can be difficult to constrain due to the temporal and spatial offsets between key sources and sinks, their associated uncertainties, and potential sampling biases. To address these challenges, the EXport Processes in the Ocean from RemoTe Sensing (EXPORTS) campaign increased the number and variety of simultaneous measurements to monitor temporal variability in the MZ carbon budget using both a Lagrangian frame of reference and long-term autonomous observations. In this study, we collate a comprehensive combination of new and previously published organic carbon supply and demand measurements collected from the surface (5 …

Predicting The Impact Of Climate Change On The Distribution Of Monodelphis Domestica (Wagner, 1842), Salise Sepulveda, Noé U. De La Sancha

DePaul Discoveries

Understanding the impact of climate change on species distribution is necessary to properly develop plans that conserve or prepare for maintenance of crucial ecosystems. Monodelphis domestica is a small mammal species native to Argentia, Bolivia, Brazil, and Paraguay. This species is known for its high adaptability and preference for living in wet conditions. Using bioclimatic variables, generalized linear models (GLM), and Coupled Model Intercomparison Project Phase 6 (CMIP6) we predicted how this species distribution will change within the next 75 years under different climate and anthropogenic changes. The results have shown that the distribution of M. domestica will remain relatively …

Measuring And Mapping Spatial Distributions Of Soil Lead Concentrations Across An Urban-To-Rural Gradient In Chicagoland, Lulia Woldemicael, Andrea Stoeva

DePaul Discoveries

Lead (Pb), a highly toxic chemical has found its way into many aspects of our communities through a plethora of different pathways such as paint, gasoline, and industrial activity. Exposure to lead poses harmful risks to all age groups as a higher blood lead level is associated with higher mortality. Although actions have been taken to eliminate lead from the atmosphere, it remains in the environment, especially accumulating in urban areas where the use of automobiles and highly industrialized landscapes are prevalent. This study examines the soil lead concentrations along an urban-to-rural gradient connecting Humboldt Park, Skokie, and Buffalo Grove, …

Race/Ethnicity, Living Arrangements, And Access To Healthcare Among Older Adults With Alzheimer’S Disease In The United States: Multiple Systematic Reviews In Relation To Health Outcomes, Chela Reiss, Grace Vethacke

DePaul Discoveries

Alzheimer’s disease (AD) is a neurodegenerative condition primarily affecting older adults. It is a growing public health crisis that affects memory, thinking, and behavior. The number of adults aged 65 and older is projected to reach 98.2 million by 2060, leading to a continued rise in the prevalence of AD. Understanding the socioeconomic factors that influence health outcomes in patients with Alzheimer's Disease and Related Dementias (ADRD) is essential in addressing the disparities within patient care and quality of life. This systematic review examined three socioeconomic factors - race/ethnicity, living arrangements, and access to healthcare - and their related health …

Microplastics In The Mississippi, Jozey Goodall

Arts & Sciences Undergraduate Showcase

This poster explores the presence and impact of microplastics in the Mississippi River through the analysis of two research studies. The first study examined surface water samples to measure microplastic concentration and to assess how land use and geography influence their distribution along the river. The second study looks in on identifying microplastics in the digestive systems of fish collected from different locations along the river. Both studies have shown that microplastics are widespread throughout the river, with higher levels found downstream and in highly populated areas. The research highlights the ways in which microplastics enter freshwater environments, from urban …

Remote Sensing-Based Assessment Of Evapotranspiration Patterns In A Unesco World Heritage Site Under Increasing Water Competition, Maria C. Moyano, Monica Garcia, Luis Juana, Laura Recuero, Lucia Tornos, Joshua B. Fisher, Néstor Fernández, Alicia Palacias-Orueta

Biology, Chemistry, and Environmental Sciences Faculty Articles and Research

In water-scarce regions, natural ecosystems and agriculture increasingly compete for limited water resources, intensifying stress during periods of drought. To assess these competing demands, we applied a modified PT-JPL model that incorporates the thermal inertial approach as a substitute for relative humidity (RH) in estimating soil evaporation—a method that significantly outperforms the original PT-JPL formulation in Mediterranean semi-arid irrigated areas. This remote sensing framework enabled us to quantify spatial and temporal variations in water use across both natural and agricultural systems within the UNESCO World Heritage site of Doñana. Our analysis revealed an increasing evapotranspiration (ET) trend in intensified agricultural …

Du Undergraduate Showcase Abstracts: Research, Scholarship, And Creative Works, Kabe Aberle, Nadia Kako, Kateri Mcrae, Brooke Agulnek, Sky Palmon, Yasmine Ramirez, Francisca Aguirre Beltran, Ashley Juarez, Bridget Kim, Tessa Appel, Sterling Kerr, Spencer Ingley, Gabe Meyer, Robin Tinghitella, Dale Broder, Lily Baeza, Chloe Beers, Julia Coakley, Whitney Kelsey, Sydney Gainforth, Gabi Wing, Audrey Martin, Aaliyah Amore Berry, Brooke Watley, Kiruthika Venkatesan, Rachel Bienstock, Annabella Brotherston, Madison Bryant, Mia Burgener, Emma P. Lieb, Rachel A. Johnson, Jennifer L. Hoffman, Kania Campbell, Kiena Campbell, Courtney Cassidy, Sage Krzyzkowski, Maddox Jones, Skylar Abookire, Luke Hawkins, Sunnah Yoon, Andrea Chu, Yan Qin, Nyah Cubbison, Brian Gearity, Daniel Mcintosh, Mariely Cruz, Edward Garrido, Grady Dionne, Nicole Doris, Lyndsie Salvagio, Ann-Charlotte Granholm-Bentley, Anna Dymov, Hannah Eckert, Gabrielle Welsh, Erica Larson, Charlie Ernst, Anna Zhou, Sarah Watamura, Larissa Fedorovich-Klein, Georgie Fields, Kimberly A. Guevara, Aven Mccall, Ben Peltier, Feruz Yahia, Patrick Flores, Jadyn Floyd, Sophia Forcier, J. Von R. Monteza, Peter Sokol-Hessner, Gwendolyn Geiger, Scott Nichols, Camryn Gunter, Kendal Hengst, Charlie Bednarz, Issy Garside, Addison Baker, Rachel Mina, Brooke Hermanson, Amanda Klingler, William Highfill, Sydney Jaques, Kerstin Lewey, Allison Grossery, Daniel Linseman, Ethan Lim, Jagger Livengood, Owen Mantelli, Gabby Pappas, Abby Mcdonald, Madeleine Dierking, Eve Miller, Emma Loeber, Anna Marlow, Michael Kerwin, Ella Mathews, Hillary Hamann, Khadija Mohamed, Vivian Nguyen, Gabri Notov, Ifunayachi Ogbonna-Ukuku, Sunil Kumar, Charles Baysah, Sarah Olson, Don Sullivan, Anna Paradiso, Jay Parrish, Mira Pronobis, Alisha Pravasi, Kerstin Haring, Diego Ramirez, Christopher Reardon, Juliana Ramirez, Casey Doherty, Ella Kestner, Teagan Weindel, Cate Billings, Pablo Torre-Walter, Lucy Rand, Samantha Reynolds, Mark Siemens, Khadeeja Rashid, Laine Satterlee, Piper Heilbronner, Lily Pound, Ben Whitehurst, Anna Respet, Lizzie Lesoing, Sydney Hertel, Aya Saad-Masri, Brooke Ballenger, Max Proske, Hannah Rosenberg, Ellia Nakahara, Sophia Espinoza, Ivan Woolhouse, Simon Ruland, Gorkem Er, Timothy Sweeny, Melaku Saketa, Michela Schenk, Maren Lynch, Madi Hamm, Grace Schroeder, Michelle Rozenman, Rana Seif, Jackson Hall, Marisela Simental, Daniel Paredes, Aaron Mena, Preston Spaan, Evelyn Stovin, David Andrew Swartz, Anh Tran, Daniel Pittman, Luke Farchione, Emily Boyer, Ukari Verner, Lacey Conrad, Jonathan Velotta, James Weiner, Jagger Gossett, Noah Sherry, Sam Proud, Ben Block, Avi Narayana, Zoey Weiss, Alyssa Wilson, Gabrielle Walsh, David Zonana, Keely Wright, Kena Riveria, Lillybelle Deer, Jena Doom, Elysia Davis, Isabelle Yaremenko, Caitlyn Young

DU Undergraduate Research Journal Archive

Abstracts from the DU Undergraduate Research Showcase.

A Novel Approach To Increase Accuracy In Remotely Sensed Evapotranspiration Through Basin Water Balance And Flux Tower Constraints, Kul Khand, Gabriel B. Senay, Mackenzie Friedrichs, Koong Yi, Joshua B. Fisher, Lixin Wang, Kosana Suvočarev, Arman Ahmadi, Housen Chu, Stephen Good, Kanishka Mallick, Justine Missik, Jacob A. Nelson, David E. Reed, Tianxin Wang, Xiangming Xiao

Biology, Chemistry, and Environmental Sciences Faculty Articles and Research

Remote sensing-derived evapotranspiration (RSET) products capture the spatiotemporal variations of evapotranspiration (ET) from field to basin scales with unprecedented details. However, their accuracy varies across RSET estimation methods and diverse hydroclimate regions. While ET modeling efforts to account for biophysical processes and controlling parameters have made good progress in recent years, a parallel approach of integrating in-situ ET with RSET could reduce biases in RSET products. Basin water balance ET (WBET) and flux tower ET are widely applied to evaluate RSET accuracy, yet such ET measurements are rarely used for RSET bias corrections, especially for large area applications. To address …

The Astrobiological Figure Of Humboldt As Pioneer In The Rock Varnish Research, Jose Jordan-Soria

Homage to Alexander von Humboldt: Travels to and from Spain Throughout the Centuries / Homenaje a Alexander von Humboldt: Viajes hacia y desde España de todos los siglos

From Humboldt is particularly interesting -and little know- his description of mineral coatings on rocks 200 years ago, reported in his book Personal Narrative of Travels to the Equinoctial Regions of the New Continent during the years 1799-1804, co-written with Aimé Bonpland, for which is considerate the father of rock coating research. On June 5th 1799 set sail from A Coruña -Spain- to Cumaná -Venezuela- beginning five years of expedition. While they explored the Orinoco River system, in th eriver basin waterfalls, Humboldt observed the presence of dark coating depositions. He ascertained a manganese-rich accretion, reporting similar structures in other …

Analyzing Racial And Geographic Distribution In Clinical Trial Enrollment Among Women With Advanced Stage Ovarian Cancer, Paxton Gillispie, Dhruva Dave, Gerald Mcgwin, Ashwini Katre, Ashley Anderson, Teresa Boitano, Nneka Ijeli, Purva Pawar, Rebecca Arend

Expo Student Presentations

2025 Summer Expo Poster Presentation

• Physical & Applied Sciences
• Health Sciences & Health Professions

Adaptation Planning To Mitigate Flood Risk: Bellevue, Nebraska As A Case Study, Michael Nti Ababio

Community and Regional Planning Program: Theses

Flooding remains one of the most pressing natural hazards in the United States, with increasing frequency and intensity driven by climate change. This thesis explores the adaptation planning strategies employed to mitigate flood risks in Bellevue, Nebraska, a city significantly impacted by the 2019 floods in eastern Nebraska. Using a mixed-methods approach, the study combines quantitative analysis of flood vulnerability with a critical review of local planning policies using documents, zoning ordinances and institutional frameworks. Spatial analytical tools such as Global Moran’s I and Hot Spot Analysis (Getis-Ord Gi*) were used to detect clustering of inundated buildings during the 2019 …

Assessment Of Spatial Autocorrelation And Scalability In Fine-Scale Wildfire Random Forest Prediction Models, Madeleine Pascolini-Campbell, Joshua B. Fisher, Kerry Cawse-Nicholson, Christine M. Lee, Natasha Stavros

Biology, Chemistry, and Environmental Sciences Faculty Articles and Research

Wildfire prediction models that can be applied across diverse regions at fine scales (<  100 m) are critical for wildfire management. Remote sensing offers a path forward by providing heterogeneous and dynamic measurements of fuel load, type, and flammability. Machine learning methods such as random forests provide an empirical framework that are high-accuracy, computationally efficient, interpretable and able to model complex ecological relationships. Here we use high resolution (70 m, every 3–5 days) remote sensing observations of evapotranspiration and evaporative stress index, which represent plant water stress, from Ecosystem Spaceborne Thermal Radiometer on Space Station (ECOSTRESS), as well as topography and weather data, to predict burn severity and occurrence for 8 large wildfires that burned 3715 km² from 2021 and 2022 in New Mexico, USA. These fires ranged from low to high burn intensity, and covered a diverse range of ecoregions (deserts, grasslands, forests), plant species, and topographies. We used a single model to predict the burn severity of all wildfires one week before occurrence. The prediction accuracy was greatest when using all predictors (ECOSTRESS, weather, topography) (R² = 0.77). We assessed the role of spatial autocorrelation in driving model performance by: (1) increasing the sample spacing of our dataset, (2) …

Ai Tools In Natural Resources And Environmental Systems For The Classroom, Research, Extension And Industry, Derek M. Heeren, C. T. Agouridis, Debabrata Sahoo, Isaya Kisekka, Trisha L. Moore

Department of Agricultural and Biological Systems Engineering: Presentations and White Papers

This white paper synthesizes a series of panel insights on AI adoption across education, Extension, research and industry contexts within natural resources and environmental systems. It emphasizes that while advanced machine learning and generative AI introduce structural shifts in autonomy, scale, and cognitive augmentation, their value lies in augmenting, not replacing, human expertise. Applied tool examples include decision‑support systems for rural water operators, HAB‑diagnosis apps integrating image classification and natural‑language guidance, an irrigation educational chatbot tailored to user background, and sensor‑driven orchard AI for light interception estimation and data gap filling. A recurring design imperative involves co‑development with end users, …

Use Of High-Throughput Phenomics With And Without Fungicide As A Wheat Breeding Tool, Gerardo Ivan Rivera Collazo

Dissertations and Doctoral Documents, University of Nebraska-Lincoln, 2023–

Wheat (Triticum aestivum) is an important food staple for many countries around the world and current consumption and production data demonstrate a production deficit. Breeders are challenged to help close this gap in production by selecting better cultivars with improved yields. Several methods aim to accelerate the breeding process to reduce the time required for releasing an elite variety. One of the main breeding bottlenecks is the lack of fast and reliable phenotypic data acquisition that could dissect physiological and morphological plant data. High-throughput remote sensing could have the potential to reduce this bottleneck by streamlining data acquisition, …

Experimental Analysis Of Satellite Operator Training Using Game-Based Virtual Reality Simulation, Lana Laskey

Doctoral Dissertations and Master's Theses

Satellite data plays a vital role in modern global infrastructure by enabling communications, navigation, and weather forecasting. As demand for satellite technology grows, so does the need for highly trained satellite ground operators. Traditional training regimens for satellite operators employ simulation using two-dimensional computer console displays paired with the varied ability of trainees to generate abstract mental imagery of the scenario. However, this development of mental imagery imposes a considerable learning curve and cognitive workload on the trainee, which may negatively impact the user experience and knowledge gained during the training scenario.

This experimental study investigated the effects of game-based …

Aircraft Bird Strike Risk Prediction Using Machine Learning And Analytic Hierarchy Process, Jason Anthony Powell

Doctoral Dissertations and Master's Theses

To address the limitations of Next Generation Radar-based bird strike forecasting, this study modeled 12 spatiotemporal weather features from the National Oceanic and Atmospheric Administration alongside bird strike risk using Long Short-Term Memory Recurrent Neural Network (LSTM-RNN), XGBoost regression tree, and Bayesian network algorithms. Five years of bird strike data from four geographically diverse airfields served as the target risk variable, categorized as low, moderate, or severe based on Department of the Air Force risk models. The ensemble model, which combines the LSTM-RNN and XGBoost regression algorithms, yielded the most accurate forecasts, achieving 80% to 93% accuracy across all airfields, …

The Surface Water And Ocean Topography (Swot) Mission For River And Lake Ice Application, Sunwoo Yoon

Earth Sciences Theses and Dissertations

The Surface Water and Ocean Topography (SWOT) mission, launched in December 2022, is designed for global survey of Earth’s surface water. However, the seasonal freezing of lakes and rivers combined with SWOT’s unique interferometric radar characteristics presents a valuable opportunity to assess its potential for river and lake ice applications. In this dissertation, I first compare backscatter characteristics over open water and frozen lakes and rivers. I demonstrate strong contrast in backscatter between water and ice while accounting for incidence angle, highlighting SWOT’s capability to discriminate between surface cover types. However, overlapping backscatter signatures suggest further investigation of drivers of …

First Detrital Zircon Provenance Data From Oligocene-Pleistocene Sediment In The Beaufort-Mackenzie Basin, Arctic Ocean, Joseph Martina

Theses and Dissertations

Sediment, runoff, and nutrient input to the Arctic Ocean plays a critical role in both physical and biological processes that impact regional and global systems. The Beaufort-Mackenzie Basin, situated in the Arctic Ocean offshore northwestern Canada, contains more than 14 km of clastic strata and provides a record of erosion and sediment transport from the Cretaceous to present. Pliocene sedimentation rates within the basin jump nearly 2000% relative to underlying units, but the cause of this shift remains unknown. We used cuttings from the N. Issungnak L-86 well, focusing on the Oligocene-lower Miocene Kugmallit and Mackenzie Bay sequences and the …

Spatio-Temporal Modeling & Goodness Of Fit Testing For Ecological Fire Data, Jedidiah Olof Lindborg

Theses and Dissertations

An analysis of fire data sets resulting from controlled burns was performed. Spatio-temporal models were applied to the data sets to determine which covariates are significant in predicting fire temperature. The data sets were censored and only contain temperatures above 300C, due to a limitation in the measuring device. To handle the censoring, an extrapolation was used to reconstruct the temperatures below 300C. Models were created and run for a data set with the extrapolated temperatures and a data set with all censored temperatures removed. Several aspects of the model were evaluated, such as the chosen hyperparameters, the spatial covariance …

Mo Isotopes In The Aleutian And Costa Rican Arcs: Source Variability And Juvenile Crust Formation, Ekaterina Rojas Kolomiets

Theses and Dissertations

Chemical and physical transfer between the surface, lithosphere and asthenosphere at subduction zones leads to arc magmatism and continental crust (CC) production. Subduction zones magmas and associated volcanic products sample a variety of magmatic sources that contribute to their chemical compositions in various proportions. This dissertation contributes to the study of subduction zones magmatism by assessing the relative role of subduction inputs (sediments, altered oceanic crust – AOC – and serpentinite) as flux agents in the arc magmatism and in CC formation in subduction zones under the scope of Mo isotope systematics.

I present the first Mo isotope analyses form …

Some Likelihood-Based Methods For Clustering Functional Data, Tong Shan

Theses and Dissertations

The analysis of functional data is an increasingly relevant part of statistics. The exploratory data analytic method of cluster analysis plays a very important role in different fields. Over the years, researchers have developed many clustering approaches, striving to achieve more accurate and efficient clustering. In Chapter 1, we aim to improve the accuracy of our outcome when clustering functional data. To achieve this goal, we use a predictive likelihood function which serves as an objective function to optimize in order to determine the most appropriate clusters. To optimize the objective function over the space of clustering partitions, we produce …

A Spatial Scan Statistic For Group Testing Data, Vincent Onyame

Theses and Dissertations

Group testing involves pooling specimens from multiple individuals and offers an efficient means to surveil low-prevalence pathogens, but poses challenges for spatial cluster detection when only pooled results are observed. In this thesis, we develop a spatial scan statistic tailored to group-testing data with variable pool sizes. The statistic compares a null hypothesis of a homogeneous infection rate across all clusters to an alternative hypothesis that infection probabilities differ inside and outside a candidate cluster, with both models fitted by maximum likelihood estimation. We approximate the null distribution of the maximum likelihood ratio test via Monte Carlo simulation.

Through a …

Political Ecologies Of Storage For The 21st Century, Sayd Randle, Matthew Archer

Research Collection College of Integrative Studies

New resource storage arrangements are proliferating rapidly both in terms of physical infrastructures-for the storage of things like "clean" energy, nuclear waste, carbon dioxide, fresh water, and data-and as part of a set of discursive moves that reinforce a vision of a near future world in which problems of climate change mitigation and adaptation in particular (but also issues like energy security, water security, industry growth, etc.) are solved through eco-modernist techno-fixes. This Symposium sketches the contours of a framework we term political ecologies of storage. In doing so, we treat storage as both a potent imaginary and a concrete …

Towards Future Sustainable Infrastructure: The Role Of Technical Audit In Tanzania’S Public Works, George C. Haule

Tanzania Journal of Engineering and Technology (TJET)

This study aimed to investigate the vital role and impact of technical audits in promoting sustainable infrastructure development in Tanzania. The role and effects of technical audits in long-term infrastructure development were studied using a mixed-methods approach with both quantitative and qualitative parts. Data were collected through analysis of technical audit documentation, a semi-structured questionnaire, and stakeholder interviews. The study revealed the various dimensions of infrastructure investment projects, including initiation and planning, design, procurement of contractors and consultants, contract management, environment, health, and safety. The technical audit findings reported weaknesses or non-performance issues in infrastructure planning at the national level …

Fuzzy-Ahp Based Decision Support System For The Selection Of Optimal Maintenance Strategy For Meter Gauge Railway Infrastructure: A Review, Hamisi J. Maulid

Tanzania Journal of Engineering and Technology (TJET)

There are many uncertainties and complexities associated with maintaining Meter Gauge Railway (MGR) infrastructure, which calls for a methodical approach to decision-making. The development and application of a fuzzy-AHP-based decision support system (DSS) to select the optimal maintenance strategy for the MGR are presented in this study. The review covers research from 2013 to 2023 and focusses on the use of Multi-Criteria Decision Making (MCDM) and Fuzzy Analytic Hierarchy Process (Fuzzy-AHP) techniques in railway infrastructure maintenance. To manage the inherent uncertainties and subjective judgements involved in maintenance decision-making, the Fuzzy-AHP methodology combines fuzzy logic with the Analytic Hierarchy Process (AHP). …

Flash Flood Modelling In The Brantas Hulu Sub-Watershed, Batu City, Indonesia, Listyo Yudha Irawan, Vischawafiq Azizah, Siti Nur Farihah, Luisa Fernanda Medina, Puspita Indra Wardhani, Nanda Regita Cahyaning Putri, Mellinia Regina Heni Prastiwi, Mohammad Rendra Magandhi Arizal

Jurnal Pendidikan Geografi: Kajian, Teori, dan Praktek dalam Bidang Pendidikan dan Ilmu Geografi

Flash floods are especially hazardous hydrological phenomena, noted for their abrupt occurrence and capacity to inflict severe damage on infrastructure, farmlands, and residential zones, often leading to substantial socio-economic upheaval and fatalities. A flash flood struck the Upper Brantas watershed on November 4, 2021, at 14:00, precipitated by intense rainfall over a short duration, leading to significant hydrological impacts. The event manifested at six critical points within Batu City, with Sambong Hamlet and Beru Hamlet experiencing severe inundation. The flash floods disrupted residential areas and severely affected agricultural lands through debris flows. Preliminary assessments indicated that approximately 35 houses were …