Research and Publications - Department of Civil, Construction & Environmental Engineering

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The Western U.S. Drought: How Bad Is It?
(2004-08-10) Piechota, Thomas C.; Timilsena, Janak; Tootle, Glenn; Hidalgo, Hugo; University of Alabama Tuscaloosa
Historical stream flow records and the forecast for 2004 make the current (1999–2004) drought in the southwestern United States the worst one in the past 80 years for portions of the Upper Colorado River Basin (UCRB).For the Colorado River (near Cisco, Utah), the cumulative stream flow deficit (departure from long‐term mean) for the current drought is almost 11 km8, or approximately 2 years of average stream flow Although the current drought is the most significant, based on historical stream flow records, is it the worst ever?
Coupled oceanic-atmospheric variability and U.S. streamflow
(American Geophysical Union, 2005-12-06) Tootle, GA; Piechota, TC; Singh, A; University of Wyoming; Nevada System of Higher Education (NSHE); University of Nevada Las Vegas; University of Alabama Tuscaloosa
[1] A study of the influence of interdecadal, decadal, and interannual oceanic-atmospheric influences on streamflow in the United States is presented. Unimpaired streamflow was identified for 639 stations in the United States for the period 1951 - 2002. The phases (cold/negative or warm/positive) of Pacific Ocean ( El Nino - Southern Oscillation (ENSO) and Pacific Decadal Oscillation (PDO)) and Atlantic Ocean ( Atlantic Multidecadal Oscillation (AMO) and North Atlantic Oscillation (NAO)) oceanic-atmospheric influences were identified for the year prior to the streamflow year (i.e., long lead time). Statistical significance testing of streamflow, based on the interdecadal, decadal, and interannual oceanic-atmospheric phase (warm/positive or cold/negative), was performed by applying the nonparametric rank-sum test. The results show that in addition to the well-established ENSO signal the PDO, AMO, and NAO influence streamflow variability in the United States. The warm phase of the PDO is associated with increased streamflow in the central and southwest United States, while the warm phase of the AMO is associated with reduced streamflow in these regions. The positive phase of the NAO and the cold phase of the AMO are associated with increased streamflow in the central United States. Additionally, the coupled effects of the oceanic-atmospheric influences were evaluated on the basis of the long-term phase (cold/negative or warm/ positive) of the interdecadal ( PDO and AMO) and decadal ( NAO) influences and ENSO. Streamflow regions in the United States were identified that respond to these climatic couplings. The results show that the AMO may influence La Nina impacts in the Southeast, while the NAO may influence La Nina impacts in the Midwest. By utilizing the streamflow water year and the long lead time for the oceanic-atmospheric variables, useful information can be provided to streamflow forecasters and water managers.
Oceanic-atmospheric variability and western US snowfall
(American Geophysical Union, 2006-07-08) Hunter, Thad; Tootle, Glenn; Piechota, Thomas; University of Wyoming; Nevada System of Higher Education (NSHE); University of Nevada Las Vegas; University of Alabama Tuscaloosa
A study of the influences of interdecadal and interannual oceanic-atmospheric influences on April 1 Snow-Water Equivalent (SWE) in the western U. S. is presented. SWE data was identified at 323 Natural Resources Conservation Service ( NRCS) SNOTEL (SNOwpack TELemetrysites) stations for the period of 1961 to 2004 and for 121 SNOTEL stations for the period 1941 to 2004. The phases (cold/negative or warm/positive) of Pacific Ocean [ El Nino-Southern Oscillation (ENSO) and Pacific Decadal Oscillation (PDO)] and Atlantic Ocean [ Atlantic Multidecadal Oscillation ( AMO) and North Atlantic Oscillation (NAO)] oceanic-atmospheric influences were identified for the year prior to the SWE data set. Statistical significance testing of SWE data set, based on the interdecadal and interannual oceanic-atmospheric phase (warm/positive or cold/negative) was performed by applying the nonparametric rank-sum test. The results show that in addition to the well established ENSO signal in the northwest, the PDO and AMO influence SWE variability. Additionally, the coupled effects of the oceanic-atmospheric influences were evaluated on the basis of the long-term phase (cold/negative or warm/positive) of the interdecadal ( PDO, AMO, NAO) influences and the interannual ENSO. Finally, the coupled effects of the oceanic-atmospheric influences were evaluated on the basis of the long-term phase (cold/negative or warm/positive) of the interdecadal ( AMO, PDO, NAO) phenomena. Regions in the west were identified that responded to the interdecadal/ decadal climatic coupling. By utilizing the April 1 SWE and the long lead-time approach for the oceanic-atmospheric variables, useful information can be provided to snow forecasters and water managers.
Relationships between Pacific and Atlantic ocean sea surface temperatures and US streamflow variability
(American Geophysical Union, 2006-07-19) Tootle, Glenn A.; Piechota, Thomas C.; University of Wyoming; Nevada System of Higher Education (NSHE); University of Nevada Las Vegas; University of Alabama Tuscaloosa
[ 1] An evaluation of Pacific and Atlantic Ocean sea surface temperatures (SSTs) and continental U. S. streamflow was performed to identify coupled regions of SST and continental U. S. streamflow variability. Both SSTs and streamflow displayed temporal variability when applying the singular value decomposition (SVD) statistical method. Initially, an extended temporal evaluation was performed using the entire period of record (i.e., all years from 1951 to 2002). This was followed by an interdecadal-temporal evaluation for the Pacific ( Atlantic) Ocean based on the phase of the Pacific Decadal Oscillation (PDO) ( Atlantic Multidecadal Oscillation (AMO)). Finally, an extended temporal evaluation was performed using detrended SST and streamflow data. A lead time approach was assessed in which the previous year's spring-summer season Pacific Ocean ( Atlantic Ocean) SSTs were evaluated with the current water year continental U. S. streamflow. During the cold phase of the PDO, Pacific Ocean SSTs influenced streamflow regions ( southeast, northwest, southwest, and northeast United States) most often associated with El Nino-Southern Oscillation (ENSO), while during the warm phase of the PDO, Pacific Ocean SSTs influenced non-ENSO streamflow regions ( Upper Colorado River basin and middle Atlantic United States). ENSO and the PDO were identified by the Pacific Ocean SST SVD first temporal expansion series as climatic influences for the PDO cold phase, PDO warm phase, and the all years analysis. Additionally, the phase of the AMO resulted in continental U. S. streamflow variability when evaluating Atlantic Ocean SSTs. During the cold phase of the AMO, Atlantic Ocean SSTs influenced middle Atlantic and central U. S. streamflow, while during the warm phase of the AMO, Atlantic Ocean SSTs influenced upper Mississippi River basin, peninsular Florida, and northwest U. S. streamflow. The AMO signal was identified in the Atlantic Ocean SST SVD first temporal expansion series. Applying SVD, first temporal expansions series were developed for Pacific and Atlantic Ocean SSTs and continental U. S. streamflow. The first temporal expansion series of SSTs and streamflow were strongly correlated, which could result in improved streamflow predictability.
Five Hundred Years of Hydrological Drought in the Upper Colorado River Basin
(2007-06) Timilsena, Janak; Piechota, Thomas C.; Hidalgo, Hugo; Tootle, Glenn; University of Alabama Tuscaloosa
This article evaluates drought scenarios of the Upper Colorado River basin (UCRB) considering multiple drought variables for the past 500 years and positions the current drought in terms of the magnitude and frequency. Drought characteristics were developed considering water-year data of UCRB’s streamflow, and basin-wide averages of the Palmer Hydrological Drought Index (PHDI) and the Palmer Z Index. Streamflow and drought indices were reconstructed for the last 500 years using a principal component regression model based on tree-ring data. The reconstructed streamflow showed higher variability as compared with reconstructed PHDI and reconstructed Palmer Z Index. The magnitude and severity of all droughts were obtained for the last 500 years for historical and reconstructed drought variables and ranked accordingly. The frequency of the current drought was obtained by considering two different drought frequency statistical approaches and three different methods of determining the beginning and end of the drought period (annual, 5-year moving, and ten year moving average). It was concluded that the current drought is the worst in the observed record period (1923-2004), but 6th to 14th largest in terms of magnitude and 1st to 12th considering severity in the past 500 years. Similarly, the current drought has a return period ranging from 37 to 103 years based on how the drought period was determined. It was concluded that if the 10-year moving average is used for defining the drought period, the current drought appears less severe in terms of magnitude and severity in the last 500 years compared with the results using 1- and 5-year averages.
Estimated Wind River Range (Wyoming, USA) Glacier Melt Water Contributions to Agriculture
(MDPI, 2009-10-28) Cheesbrough, Kyle; Edmunds, Jake; Tootle, Glenn; Kerr, Greg; Pochop, Larry; University of Tennessee System; University of Tennessee Knoxville; University of Wyoming; University of Alabama Tuscaloosa
In 2008, Wyoming was ranked 8th in barley production and 20th in hay production in the United States and these crops support Wyoming's $800 million cattle industry. However, with a mean elevation of 2,040 meters, much of Wyoming has a limited crop growing season (as little as 60 days) and relies on late-summer and early-fall streamflow for agricultural water supply. Wyoming is host to over 80 glaciers with the majority of these glaciers being located in the Wind River Range. These "frozen reservoirs" provide a stable source of streamflow (glacier meltwater) during this critical late-summer and early-fall growing season. Given the potential impacts of climate change (increased temperatures resulting in glacier recession), the quantification of glacier meltwater during the late-summer and early-fall growing seasons is needed. Glacier area changes in the Wind River Range were estimated for 42 glaciers using Landsat data from 1985 to 2005. The total surface area of the 42 glaciers was calculated to be 41.2 +/- 11.7 km(2) in 1985 and 30.8 +/- 8.2 km(2) in 2005, an average decrease of 25% over the 21 year period. Small glaciers experienced noticeably more area reduction than large glaciers. Of the 42 glaciers analyzed, 17 had an area of greater than 0.5 km(2) in 1985, while 25 were less than 0.5 km(2) in 1985. The glaciers with a surface area less than 0.5 km(2) experienced an average surface area loss (fraction of 1985 surface area) of 43%, while the larger glaciers (greater than 0.5 km(2)) experienced an average surface area loss of 22%. Applying area-volume scaling relationships for glaciers, volume loss was estimated to be 409 x 106 m(3) over the 21 year period, which results in an estimated 4% to 10% contribution to warm season (July-October) streamflow.
The 2009-2010 El Niño: Hydrologic Relief to U.S. Regions
(2009-12-15) Tootle, G. A.; Piechota, T. C.; Aziz, O.; Miller, W. P.; Lakshmi, V.; Dracup, J. A.; Jerla, C.; University of Alabama Tuscaloosa
Current forecasts by the U.S. National Oceanic and Atmospheric Administration (NOAA) are that the Pacific Ocean will experience El Niño conditions in late 2009 and into 2010. These forecasts are similar to past El Niño events in 1972–1973, 1982–1983, 1986–1987, and 2002–2003.Evaluating the hydrologic conditions for these past El Niño events reveals that during these times, surface water supply conditions improved in many parts of the United States, including the Southeast, Midwest, and Southwest. At the same time, the Pacific Northwest and other specific regions of the United States experienced below‐average water supply conditions. This is consistent with the long‐established linkages between oceanic‐atmospheric phenomena, El Niño, and streamflow [e.g., Kahya and Dracup, 1993; Tootle et al., 2005].
Identification of Pacific Ocean sea surface temperature influences of Upper Colorado River Basin snowpack
(American Geophysical Union, 2010-07-27) Aziz, Oubeidillah A.; Tootle, Glenn A.; Gray, Stephen T.; Piechota, Thomas C.; University of Tennessee System; University of Tennessee Knoxville; University of Wyoming; Nevada System of Higher Education (NSHE); University of Nevada Las Vegas; University of Alabama Tuscaloosa
Given the importance of Upper Colorado River Basin (UCRB) snowpack as the primary driver of streamflow (water supply) for the southwestern United States, the identification of Pacific Ocean climatic drivers (e. g., sea surface temperature (SST) variability) may prove valuable in long-lead-time forecasting of snowpack in this critical region. Previous research efforts have identified El Nino-Southern Oscillation (ENSO) and Pacific Decadel Oscillation (PDO) as the main drivers for western U. S. snowpack, but these drivers have limited influence on regional (Utah and Colorado) UCRB snowpack. The current research applies for the first time the Singular Value Decomposition (SVD) statistical method to Pacific Ocean SSTs and continental U. S. snowpack to identify the primary Pacific Ocean climatic driver of UCRB snowpack. The use of SSTs eliminates any "bias" as to specific climate signals. The second mode of SVD identified a UCRB snowpack region (Colorado and Utah) and a corresponding Pacific Ocean SST region. A "non-ENSO/non-PDO" Pacific Ocean SST region between 34 degrees N-24 degrees S and 150 degrees E-160 degrees W was identified as being the primary driver of UCRB snowpack. To confirm the UCRB snowpack results, data from 13 unimpaired (or naturalized) streamflow gages in Colorado and Utah were used to evaluate and support the snowpack findings. Finally, a new and beneficial data set (western U.S. 1 March, 1 April, and 1 May snow water equivalent) was developed, which may be used in future research efforts.
Greening China Naturally
(Springer, 2011) Cao, Shixiong; Sun, Ge; Zhang, Zhiqiang; Chen, Liding; Feng, Qi; Fu, Bojie; McNulty, Steve; Shankman, David; Tang, Jianwu; Wang, Yanhui; Wei, Xiaohua; United States Department of Agriculture (USDA); United States Forest Service; Beijing Forestry University; Chinese Academy of Sciences; Research Center for Eco-Environmental Sciences (RCEES); Cold & Arid Regions Environmental & Engineering Research Institute, CAS; University of Alabama Tuscaloosa; Marine Biological Laboratory - Woods Hole; Chinese Academy of Forestry; Research Institute of Forest Ecology, Environment and Protection, CAF; University of British Columbia; University of British Columbia Okanagan
China leads the world in afforestation, and is one of the few countries whose forested area is increasing. However, this massive "greening" effort has been less effective than expected; afforestation has sometimes produced unintended environmental, ecological, and socioeconomic consequences, and has failed to achieve the desired ecological benefits. Where afforestation has succeeded, the approach was tailored to local environmental conditions. Using the right plant species or species composition for the site and considering alternatives such as grassland restoration have been important success factors. To expand this success, government policy should shift from a forest-based approach to a results-based approach. In addition, long-term monitoring must be implemented to provide the data needed to develop a cost-effective, scientifically informed restoration policy.
Snowpack Reconstructions Incorporating Climate in the Upper Green River Basin (Wyoming)
(2012) Anderson, Sallyrose; Moser, Cody L.; Tootle, Glenn A.; Grissino-Mayer, Henri D.; Timilsena, Janak; Piechota, Thomas; University of Alabama Tuscaloosa
The Green River is the largest tributary of the Colorado River. Given that snowpack is the primary driver of streamflow, information on the long-term regional snowpack (regionalized April 1 Snow Water Equivalent (SWE)) variability would provide useful information for water managers and planners. Previous research efforts were unable to develop skillful SWE reconstructions using tree-ring chronologies in the Upper Green River Basin (UGRB) of Wyoming because of limited tree-ring chronologies in the area. The current research uses Principal Components Analysis to regionalize April 1 snowpack data in the UGRB. Recent research efforts developed six new tree-ring chronologies in and adjacent to the UGRB. These new chronologies, along with 38 existing chronologies, were correlated with the regionalized SWE data. Chronologies positively correlated at a 95% confidence level or higher were retained. Stepwise linear regressions were performed and a reconstruction of UGRB regional April 1 SWE was achieved (R2 = 0.21). Climate signals (Pacific Decadal Oscillation (PDO) and Southern Oscillation Index (SOI)) were introduced to the predictor variables and an additional regression was performed. Inclusion of the SOI resulted in a statistically skillful reconstruction (R2 = 0.58). Temporal drought periods for SWE and for streamflow were examined for the UGRB and a direct relationship was observed.
Polycyclic Aromatic Hydrocarbons in Urban Stream Sediments
(2012) Bathi, Jejal Reddy; Pitt, Robert E.; Clark, Shirley E.; University of Alabama Tuscaloosa
Polycyclic aromatic hydrocarbons (PAHs) are persistent organic pollutants of high environmental concern with known carcinogenic activity. Although literature documents PAH fate in urban runoff, little is known about their distribution on sediment sizes, which is essential for determining their treatability and fate in receiving waters. This paper has quantified the concentrations of selected PAHs in urban creek sediments and examined possible relationships between sediment PAH content and sediment characteristics, such as particle size, volatile organic content (VOC), and sediment chemical oxygen demand (SCOD). SCOD, VOC, and PAH concentrations of sediments showed a bimodal distribution by particle size. The large diameter sediments had the highest VOC and also had the highest PAH concentrations. The spatial variation of PAH content by sediment sizes also was statistically significant; however, the mass of the PAH material was significantly affected by the relative abundance of the different particle size classes in the sediment mixtures.
Does Global Progress on Sanitation Really Lag behind Water? An Analysis of Global Progress on Community- and Household-Level Access to Safe Water and Sanitation
(PLOS, 2014) Cumming, Oliver; Elliott, Mark; Overbo, Alycia; Bartram, Jamie; University of London; London School of Hygiene & Tropical Medicine; University of Alabama Tuscaloosa; University of North Carolina; University of North Carolina Chapel Hill
Safe drinking water and sanitation are important determinants of human health and wellbeing and have recently been declared human rights by the international community. Increased access to both were included in the Millennium Development Goals under a single dedicated target for 2015. This target was reached in 2010 for water but sanitation will fall short; however, there is an important difference in the benchmarks used for assessing global access. For drinking water the benchmark is community-level access whilst for sanitation it is household-level access, so a pit latrine shared between households does not count toward the Millennium Development Goal (MDG) target. We estimated global progress for water and sanitation under two scenarios: with equivalent household-and community-level benchmarks. Our results demonstrate that the "sanitation deficit" is apparent only when household-level sanitation access is contrasted with community-level water access. When equivalent benchmarks are used for water and sanitation, the global deficit is as great for water as it is for sanitation, and sanitation progress in the MDG-period (1990-2015) outstrips that in water. As both drinking water and sanitation access yield greater benefits at the household-level than at the community-level, we conclude that any post-2015 goals should consider a household-level benchmark for both.
A large-scale, high-resolution hydrological model parameter data set for climate change impact assessment for the conterminous US
(Copernicus GmbH, 2014-01-07) Oubeidillah, A. A.; Kao, S. -C.; Ashfaq, M.; Naz, B. S.; Tootle, G.; United States Department of Energy (DOE); Oak Ridge National Laboratory; University of Alabama Tuscaloosa
To extend geographical coverage, refine spatial resolution, and improve modeling efficiency, a computation and data-intensive effort was conducted to organize a comprehensive hydrologic data set with post-calibrated model parameters for hydro-climate impact assessment. Several key inputs for hydrologic simulation - including meteorologic forcings, soil, land class, vegetation, and elevation - were collected from multiple best-available data sources and organized for 2107 hydrologic subbasins (8-digit hydrologic units, HUC8s) in the conterminous US at refined 1/24 degrees (similar to 4 km) spatial resolution. Using high-performance computing for intensive model calibration, a high-resolution parameter data set was prepared for the macro-scale variable infiltration capacity (VIC) hydrologic model. The VIC simulation was driven by Daymet daily meteorological forcing and was calibrated against US Geological Survey (USGS) WaterWatch monthly runoff observations for each HUC8. The results showed that this new parameter data set may help reasonably simulate runoff at most US HUC8 subbasins. Based on this exhaustive calibration effort, it is now possible to accurately estimate the resources required for further model improvement across the entire conterminous US. We anticipate that through this hydrologic parameter data set, the repeated effort of fundamental data processing can be lessened, so that research efforts can emphasize the more challenging task of assessing climate change impacts. The pre-organized model parameter data set will be provided to interested parties to support further hydro-climate impact assessment.
Recent Alpine Glacier Variability: Wind River Range, Wyoming, USA
(2014-08-24) Maloof, Abigail; Piburn, Jesse; Tootle, Glenn; Kerr, Greg; University of Alabama Tuscaloosa
Glacier area and volume changes were quantified through the use of historical aerial photographs in the Wind River Range, Wyoming. Forty-four glaciers in the Wind River Range were analyzed using orthorectified aerial photography from 2012. This is an update to the work of Thompson et al. [1] in which the surface area changes of the 44 glaciers were estimated from 1966 to 2006. The total surface area of the glaciers was estimated to be 27.8 ± 0.8 km2, a decrease of 39% from 1966 and a decrease of 2% from 2006. The 2012 volume changes for the 44 glaciers were estimated using the Bahr et al. [2] volume-area scaling technique. The total glacier volume in 2012 was calculated to be 1.01 ± 0.21 km3, a decrease of 63% from 1966. These results, once compared to temperature and snowpack trends, suggest that the downward trend in snowpack as well as increasing temperatures seem to be the most likely driver of the glacier recessions. With Global Circulation Models (GCMs) forecasting higher temperatures and lower precipitation in the western U.S., it is likely that glaciers will continue to recede.
Renovation versus New Construction and Building Decision Tool for Educational Facilities
(2016) Pope, Carrie; Marks, Eric; Back, Edward; Leopard, Tim; Love, Thomas; University of Alabama Tuscaloosa
Renovation of an existing building is an accomplished stem of the construction industry because it supplies financial diversification for construction stakeholders. Although several construction planning tools and stakeholder alignment exercises have been developed, no tool exists to assist project owners to decide between renovating an existing building and new construction with a comprehensive decision criteria. The objective of this research is to create and test a renovation versus new building support decision tool for construction project stakeholders. The renovation versus new building support decision tool was created based on an extensive review of existing support tools and construction industry needs. The created tool was implemented to evaluate decisions of educational facilities by university officials experienced in project management. Results show the tool was effective in identifying relevant topics for discussion and guiding a group of stakeholders through an exercise in decision-making. Specifically, the tool was implemented by construction management personnel for university facilities currently under construction to evaluate the decision to renovate an existing building or new construction. The main contribution of this research is a framework and support decision tool readily implementable for construction project stakeholders desiring to determine if renovation or new construction is the optimal path for their specific objectives.
GIS-Enabled Culvert Design: A Case Study in Tuscaloosa, Alabama
(Hindawi, 2018) Greer, Ashton D.; Wilbanks, Zachary B.; Clifton, Leah D.; Wilson, Bradford; Graettinger, Andrew J.; University of Alabama Tuscaloosa
A GIS-enabled culvert design module is presented. This module employs Python programming to combine a proposed culvert location, topography, land use, and rainfall data to automatically design a culvert. The module is embedded within ESRI ArcGIS 10.4 software, providing a seamless single platform that eliminates error propagation associated with cross-platform data transfer as well as providing 95% time savings over traditional calculation methods. The module uses United States Geological Survey digital elevation data to analyze watershed topography. Runoff coefficients are determined from data available through the National Land Cover Database. Rainfall data are retrieved from the National Oceanic and Atmospheric Administration and combined with watershed and land use information to calculate peak discharge using the rational method. Peak discharge is then combined with culvert design parameters to design a single-barrel culvert. The module was used to redesign ten existing culverts along a highway in Tuscaloosa, Alabama, resulting in designs for updated land cover and rainfall conditions. Results from the techniques developed herein can be used for planning purposes and to highlight vulnerabilities in the existing infrastructure. The automation methods may be extended to other hydrologic objectives and runoff mitigation design such as open-channel design and detention or retention ponds.
Development of a field testing protocol for identifying Deepwater Horizon oil spill residues trapped near Gulf of Mexico beaches
(PLOS, 2018) Han, Yuling; Clement, T. Prabhakar; Auburn University; University of Alabama Tuscaloosa
The Deepwater Horizon (DWH) accident, one of the largest oil spills in U.S. history, contaminated several beaches located along the Gulf of Mexico (GOM) shoreline. The residues from the spill still continue to be deposited on some of these beaches. Methods to track and monitor the fate of these residues require approaches that can differentiate the DWH residues from other types of petroleum residues. This is because, historically, the crude oil released from sources such as natural seeps and anthropogenic discharges have also deposited other types of petroleum residues on GOM beaches. Therefore, identifying the origin of these residues is critical for developing effective management strategies for monitoring the long-term environmental impacts of the DWH oil spill. Advanced fingerprinting methods that are currently used for identifying the source of oil spill residues require detailed laboratory studies, which can be cost-prohibitive. Also, most agencies typically use untrained workers or volunteers to conduct shoreline monitoring surveys and these worker will not have access to advanced laboratory facilities. Furthermore, it is impractical to routinely fingerprint large volumes of samples that are collected after a major oil spill event, such as the DWH spill. In this study, we propose a simple field testing protocol that can identify DWH oil spill residues based on their unique physical characteristics. The robustness of the method is demonstrated by testing a variety of oil spill samples, and the results are verified by characterizing the samples using advanced chemical fingerprinting methods. The verification data show that the method yields results that are consistent with the results derived from advanced fingerprinting methods. The proposed protocol is a reliable, cost-effective, practical field approach for differentiating DWH residues from other types of petroleum residues.
Rapid Disaster Data Dissemination and Vulnerability Assessment through Synthesis of a Web-Based Extreme Event Viewer and Deep Learning
(Hindawi, 2018-11-13) Crawford, P. Shane; Al-Zarrad, Mohammad A.; Graettinger, Andrew J.; Hainen, Alexander M.; Back, Edward; Powell, Lawrence; University of Alabama Tuscaloosa
Infrastructure vulnerability has drawn significant attention in recent years, partly because of the occurrence of low-probability and high-consequence disruptive events such as 2017 hurricanes Harvey, Irma, and Maria, 2011 Tuscaloosa and Joplin tornadoes, and 2015 Gorkha, Nepal, and 2017 Central Mexico earthquakes. Civil infrastructure systems support social welfare, thus viability and sustained operation is critical. A variety of frameworks, models, and tools exist for advancing infrastructure vulnerability research. Nevertheless, providing accurate vulnerability measurement remains challenging. This paper presents a state-of-the-art data collection and information extraction methodology to document infrastructure at high granularity to assess preevent vulnerability and postevent damage in the face of disasters. The methods establish a baseline of preevent infrastructure functionality that can be used to measure impacts and temporal recovery following a disaster. The Extreme Events Web Viewer (EEWV) presented as part of the methodology is a GIS-based web repository storing spatial and temporal data describing communities before and after disasters and facilitating data analysis techniques. This web platform can store multiple geolocated data formats including photographs and 360 degrees videos. A tool for automated extraction of photography from 360 degrees video data at locations of interest specified in the EEWV was created to streamline data utility. The extracted imagery provides a manageable data set to efficiently document characteristics of the built and natural environment. The methodology was tested to locate buildings vulnerable to flood and storm surge on Dauphin Island, Alabama. Approximately 1,950 buildings were passively documented with vehicle-mounted 360 degrees video. Extracted building images were used to train a deep learning neural network to predict whether a building was elevated or nonelevated. The model was validated, and methods for iterative neural network training are described. The methodology, from rapidly collecting large passive datasets, storing the data in an open repository, extracting manageable datasets, and obtaining information from data through deep learning, will facilitate vulnerability and postdisaster analyses as well as longitudinal recovery measurement.
Mobile device use while crossing the street: Utilizing the theory of planned behavior
(Pergamon, 2019) Piazza, Andrew J.; Knowlden, Adam P.; Hibberd, Elizabeth; Leeper, James; Paschal, Angelia M.; Usdan, Stuart; University of Alabama Tuscaloosa; Worcester State University
Every year, thousands of pedestrians are killed and tens-of-thousands are nonfatally injured as a result of traffic crashes. The year 2016 holds the record for the most pedestrians killed in one year since 1990. Mobile device use while crossing the street has been associated with unsafe crossing behaviors and gait abnormalities, potentially increasing the risk of pedestrian injury or death. Expanding upon the small body of literature, the present study utilized the theory of planned behavior to guide the development of a questionnaire used to collect data from 480 adults on predictors of intentions to use a mobile device while crossing the street. Questionnaire development involved one round of expert panel review (N = 4), subsequent pilot testing of a revised questionnaire, and a test-retest reliability assessment. Results demonstrate that attitude toward the behavior, subjective norm, and perceived behavioral control significantly predicted the intention to use a mobile device while crossing the street in this population. Such a questionnaire can be used in the design and evaluation of TPB-based inter-ventions to decrease distracted mobile device use while crossing the street.
Comparison of RUSLE and MMF Soil Loss Models and Evaluation of Catchment Scale Best Management Practices for a Mountainous Watershed in India
(MDPI, 2020) Das, Susanta; Deb, Proloy; Bora, Pradip Kumar; Katre, Prafull; Punjab Agricultural University; University of Alabama Tuscaloosa; Indira Gandhi Krishi Vishwavidyalaya (IGKV)
Soil erosion from arable lands removes the top fertile soil layer (comprised of humus/organic matter) and therefore requires fertilizer application which affects the overall sustainability. Hence, determination of soil erosion from arable lands is crucial to planning conservation measures. A modeling approach is a suitable alternative to estimate soil loss in ungauged catchments. Soil erosion primarily depends on soil texture, structure, infiltration, topography, land uses, and other erosive forces like water and wind. By analyzing these parameters, coupled with geospatial tools, models can estimate storm wise and annual average soil losses. In this study, a hilly watershed called Nongpoh was considered with the objective of prioritizing critical erosion hazard areas within the micro-catchment based on average annual soil loss and land use and land cover and making appropriate management plans for the prioritized areas. Two soil erosion models namely Revised Universal Soil Loss Equation (RUSLE) and Modified Morgan-Morgan-Finney (MMF) models were used to estimate soil loss with the input parameters extracted from satellite information and automatic weather stations. The RUSLE and MMF models showed similar results in estimating soil loss, except the MMF model estimated 7.74% less soil loss than the RUSLE model from the watershed. The results also indicated that the study area is under severe erosion class, whereas agricultural land, open forest area, and scrubland were prioritized most erosion prone areas within the watershed. Based on prioritization, best management plans were developed at catchment scale for reducing soil loss. These findings and the methodology employed can be widely used in mountainous to hilly watersheds around the world for identifying best management practices (BMP).

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