Browsing by Author "Tootle, Glenn A."
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Item Assessing the social and economic impacts of hydrologic extremes(University of Alabama Libraries, 2017) Zhu, Lian; Tootle, Glenn A.; University of Alabama TuscaloosaDisaster impact assessments are crucial for understanding disasters and effective disaster prevention. Deciding how to respond to disasters cannot be efficient without considering the disaster’s social and economic impacts. Among all types of disasters, drought and flood induce the largest human and economic cost. Interbasin transfer is a commonly used strategy to overcome the mismatch between water availability and water demand, and enhance economic development. The researches present within this dissertation discuss how can we develop an efficient economic impact model or models which can take into consideration sector vulnerability and resiliency strategies in response to extreme climate events, to assist decision makers in devising response strategies. The first and second studies in this dissertation investigate methods to assess the economic consequences of drought induced water restriction and the economic consequences of flood impact in public water supply systems. Drought and flood induce water outage, and cause substantial impacts in public water supply systems. However, researches and tools which assess drought and flood impact in water supply systems are uncommon. We adapt previous work on economic consequence assessment in the event of water services disruption to evaluate the economic impact of water restrictions resulting from extended drought conditions, and water contamination and outage resulting from flood conditions. These two models focus on all commercial and industrial economic sectors across multiple basins using a continuous dynamic social accounting matrix approach.The third study in this dissertation investigates the interbasin transfer impact to the basin(s), with a focus on agriculture production, and discusses the necessity to establish a state-level interbasin transfer regulation in Alabama. A framework for comprehensive impact assessment of interbasin transfer is developed in this dissertation. The interbasin transfer research reviews four representative interbasin transfer projects, concludes the triggers of interbasin transfer projects and impacts in economic, hydrologic, ecological, and social systems. The relation between irrigation and agriculture production is simulated with AquaCrop. Three states’ interbasin transfer regulations and acts are studied. Results indicate the required processes to establish a state-level interbasin transfer regulation and the focuses of future researches.Item Climate variability and southeast U.S. precipitation(University of Alabama Libraries, 2018) David, Christopher LeBlanc; Tootle, Glenn A.; University of Alabama TuscaloosaA study of the seasonal effects of interannual and interdecadal climactic influences on southeast U.S. precipitation is presented. Precipitation data was gathered from 183 precipitation gauges provided by The National Oceanic and Atmospheric Administration’s (NOAA) National Center for Environmental Information (NCEI). The phases (warm/positive or cold/negative) of oceanic-atmospheric influences of the Pacific Ocean [El Niño-Southern Oscillation (ENSO) and Pacific Decadal Oscillation (PDO)] and the Atlantic Ocean [Atlantic Multidecadal Oscillation (AMO)] were identified for the preceding year (1969-2013) to the precipitation data (1970-2014). Three statistical significance tests (1) two-sample t-test (90% significance), (2) rank-sum (90% significance) and (3) effect-size (threshold of 0.8 to -0.8) were used to evaluate precipitation response to the positive/negative phases of the oceanic-atmospheric influences of the Pacific and Atlantic Oceans. The warm phases of ENSO and PDO were associated with increased annual precipitation in the southeastern region of the United States, while the cold phase of the AMO was associated with increased annual precipitation. While providing affirmation of these associations, this study considers the variation in seasonal precipitation of the southeastern U.S. The results indicate strong winter [January-March (JFM)] signals by all three oceanic-atmospheric influences and a strong summer [July-September (JAS)] signal by the PDO.Item Expert systems for disaster forecasting warning recovery and response in water resources management(University of Alabama Libraries, 2017) Zhang, Xiaoyin; Moynihan, Gary P.; Ernest, Andrew N. S.; University of Alabama TuscaloosaDisaster forecasting, warning, recovery, and response in water resources management require the application of knowledge from a diverse range of domains. Identifying the appropriate approach necessitates integrating rules and requirements from these knowledge domains in such a way that the operational goals are achieved with minimally available situational information. Disaster forecasting, warning, recovery, and response must be able to adapt and evolve as new information becomes available. To date, there has been a limited amount of work developing expert systems in this area. In order to fill the knowledge gap, this study 1) identifies and assimilates the knowledge necessary for Water Distribution Network (WDN) decontamination, local flood forecasting and warning, and local flood response coordination and training; 2) determines the relative utility of architectures of expert systems and conventional codes; 3) evaluates the relative benefits of forward and backward chaining inferential logic in these scenarios. Based on the outcome of the conceptual systems, we develop three complete backward chaining expert systems, respectively. With extensible knowledge bases combined with the information provided by the users, the expert systems successfully provide reasoning routines, recommendations, and guidance on disaster forecasting, warning, recovery, and response in water resources management.Item 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 TuscaloosaGiven 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.Item A method for the quantification of spatial fluxes and associated uncertainty over heterogeneous agricultural landscape(University of Alabama Libraries, 2015) Peng, Wei; Williamson, Derek G.; University of Alabama TuscaloosaAircraft based measurement of surface exchange is now a widely used approach for determining fluxes. Since it requires 3-5km averaging length to generate meaningful fluxes, it is challenging to relate obtained flux signals to a single land cover type in heterogeneous or complex landscapes. The purpose of this research is to develop a new spatial flux calculation method (SFCM) for the quantification of terrestrial surface carbon exchange. The data used in method development, comparison and evaluation were obtained during summers of 2005 and 2006 in the agricultural ecosystem (corn and soybean) of the Midwestern United States. Four kilometers was used as the spatial averaging length to include all sizes of eddies. Then footprint analysis was interpolated to a resolution of 20m to provide estimates of fractional coverages for land surface components. Through application of the SFCM method, corn and soybean fluxes were calculated and displayed spatially along the flight transects. The associated uncertainties of fluxes were spatially located and plotted along the flight transects as a visual indicator of variability. These data complement fixed location and highly validated tower based measurements by providing surrounding spatial flux data and statistical confidences, which will aid in upscaling of fluxes from local to regional scale. Furthermore, with the additional knowledge of soil conditions, irrigation practices, crop planting times etc., these spatial fluxes can be used to help improve agricultural management. The dominant method proposed by Kirby et al. (2008) was reproduced in this research using the same datasets. By comparing fluxes calculated from the SFCM (developed herein) and the dominant method with tower data, it was found that they both can capture the diurnal patterns of fluxes, with some inevitable discrepancies in the values. Selection between these two methods should depend on desired use of such flux data. The dominant method can generate well separated component fluxes without explicitly providing spatial information while the SFCM is able to quantify both component fluxes and spatial information. Such capability of SFCM provides a new perspective (spatial component fluxes) in fluxes quantification and a deeper understanding in terrestrial carbon exchanges.Item Performance evaluation of stormwater treatment controls at an industrial site(University of Alabama Libraries, 2015) Eppakayala, Vijay Kumar; Pitt, Robert; University of Alabama TuscaloosaDischarges from industrial activities may contain various hazardous pollutants including metals, oils and grease, organic toxicants, chemical oxygen demand, nutrients and suspended sediment. Limited information is available on the characteristics of the pollutant constituents that affect treatment and treatment technologies that can effectively treat the runoff from industrial activities. Understanding the association of contaminants with different particle sizes is important for determining suitable treatment controls. The primary objective of this research was to evaluate the performance of treatment controls (a pre-treatment hydrodynamic separator device followed by a dry infiltration pond) at a heavy industrial site and describe the pollutant characteristics that affect stormwater treatability for different flow conditions. Water quality monitoring through a seven month monitoring period showed that suspended sediment concentrations (SSC), COD, nutrients, and heavy metals were commonly found in the industrial runoff. Multivariate analyses were performed to identify the correlations between site hydrological and water quality parameters. The calculations showed strong correlations between hydrological parameters. Strong correlations were also observed between suspended sediment and metal concentrations. Treatment performance was evaluated based on the particle size distributions using several data exploratory methods. These showed that the hydrodynamic separator device had low to moderate reductions for SSC and low reductions for metals. The Hydrodynamic separator device also showed moderate reductions for particle sizes greater than 12 µm. The dry infiltration pond showed very high removals for particulate solids concentrations and mass, medium to high removals for heavy metal concentrations and high removals for masses of the metals. Significant moderate to high reductions in concentration and mass were observed for particle sizes greater than 3µm. The dry pond also showed high runoff reductions (75 to 100%) for storm events smaller than 1.5 inches and associated high removals of pollutant masses for all constituents and moderate runoff reductions (about 50%) for events greater than 1.5 inches. As part of this research, groundwater contamination potential was evaluated based on measured metal concentrations in the soil profile under the dry infiltration pond and by using a water chemistry vadose zone fate model. The results indicated high retention capacity of both particulate-bound and filtered metals in the surface soils in the pond. Vadose zone chemical fate modeling showed retention of metals to the soils at depths well above the water table. However, the increased runoff entering the pond greatly accelerates the pollutant migration in the subsurface, with metals potential reaching about a meter below the ground surface during a 50 year operational period. Other pollutants having greater mobility (such as nitrates) could reach the several meter deep water table quickly and, if present in problematic concentrations, result in potential groundwater contamination.Item Rapid flood damage prediction in short lead-time scenarios(University of Alabama Libraries, 2016) Gutenson, Joseph Lee; Ernest, Andrew N. S.; University of Alabama TuscaloosaResearch on short lead-time flood inundation and damage assessment traditionally focuses on developing tools for long term planning. Studies that investigate the ability to provide short lead-time analyses are uncommon because of sparcity and spatial inconsistency of short-term hydrologic forecasts. Recent advances in continental scale hydrology make possible the ability to predict discharge at nearly all locations in the conterminous United States (CONUS). Theoretically, these discharge outputs enable investigation into the plausibility of short lead-time hydraulic, and damage analyses during flood events. A system predicting the hydraulics and damage potential of floods is only feasible after addressing a number of limitations. For instance, hydraulic models require a characterization of the stream channel, either through site surveys or through approximations. Further, the damage estimation methodology requires building inventories, which are developable by similar mechanisms. This dissertation advances knowledge on how to possibly address these limitations. The first study in this dissertation investigates the use of hydraulic geometries. Hydraulic geometries relate river channel geometry to bankfull discharge. However, the research presented here indicates that hydraulic geometries may estimate both the channel geometry and multiple depths of flow, under certain geomorphic and anthropogenic constraints. Accurate channel geometries are necessary for hydraulic modeling. Depth of flow estimates are useful in developing stage-discharge rating curves and possibly as a standalone means of estimating inundation grids. The second and third studies in this research look to investigate a framework for rapid flood damage assessment using public domain cadastral or parcel geospatial data. The second study discusses a fuzzy logic framework for meshing emergency response Address Points with parcel data and appropriate depth-damage relationships to determine both percent and fiscal impact of flood damage. Results of the second study highlight the effectiveness of determining flood damage with cadastral data using fuzzy text matching. The third study investigates what inputs from the cadastral data are necessary for the fuzzy logic framework to approximate a detailed flood damage investigation. Results indicate that fuzzy logic can approximate a detailed study when provided discrete use descriptions, market value, and square footage.Item 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.Item 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 TuscaloosaThe 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.Item Straight pipes and household wastewater discharges into the rural Alabama and impact on watershed water quality with wetland land-uses(University of Alabama Libraries, 2017) Aytekin, Erdogan; Elliott, Mark A.; University of Alabama TuscaloosaIn rural areas, untreated wastewater discharged from homes (commonly called “straight pipes”) can cause harmful effects on the region’s rivers, streams and lead to negative impacts on water quality and potentially ecological and human health. Determining and addressing the water quality and health of these aquatic ecosystems requires identification of the source of contamination. Surface water quality in Hale County was evaluated at least once a month at twenty sites in wet and dry seasons. Samples were analyzed for physical (turbidity), chemical (pH, conductivity, chloride, sulfate, calcium, iron, magnesium, potassium, sodium, ammonium, ortho-phosphorus, nitrite, nitrate, dissolved organic carbon, optical indices), and microbiological (E. coli) water quality parameters. Excitation-emission matrixes (EEMs) Parallel Factor Analysis (PARAFAC) was used to identify and classify fluorescence emitting organic substances based on fluorescence peak location. Three fluorescence components, terrestrial humic-like, microbial humic-like, and protein-like fluorophores were identified using the EEM-PARAFAC model. Principal component analysis (PCA) was used to identify analyte signatures associated with sewage contamination. The PCA (varimax rotation) identified three primary components (Eigenvalue >1), accounting for 40.4%, 19.0% and 8.7% of total variance respectively. In order to detect straight pipe wastewater impacts on water quality, three main sites were sampled upstream, midstream and downstream of the town of Newbern, Alabama over the three months of the drought period (i.e., from September to November 28th, 2016). Over 20 water quality parameters were analyzed and compared with the WHO, EPA, and ADEM standards. The results showed that E. coli values highly exceed water quality standards, particularly after the drought when peak E. coli concentrations downstream exceeded 100,000 per 100 mL. This study also investigated the impacts of wetland land use on stream water quality response at eight main sites. The results showed that potassium (R square 0.78), C3 (R square 0.58) and optical brighteners (R square 0.53) correlated positively with percent wetland in the draining watersheds. This study is one of the first to document the adverse impacts of straight pipe discharges on water quality in the United States.Item Synoptic characteristics of intense precipitation events in the southeastern united states(University of Alabama Libraries, 2018) Skeeter, Walker J.; Senkbeil, Jason C.; University of Alabama TuscaloosaThe Southeastern United States is a region where increases in temperature have been largely muted when compared to other regions of the country, although extremes in both temperature and precipitation have become more common over time. In the first part of this research, the strength and recurrence of Southeastern United States intense precipitation events (IPEs) was analyzed annually, seasonally, and sub-regionally with an emphasis on identifying trends and causal mechanisms at each of these temporal and spatial scales. Causal mechanisms responsible for IPE were investigated by utilizing the Spatial Synoptic Classification (SSC) to determine which surface weather types are associated with these events. Furthermore, a case study analysis of the most intense IPE in each physiographic province was performed with archived daily surface maps to classify the type of surface forcing mechanism that was responsible for the most exceptional IPE in each physiographic province. Results showed a statistically significant and regionally variable increase in both the recurrence and strength of IPE. A statistically significant increase in the number of moist tropical (MT) weather type IPEs per year was identified, and attributed to more common northward and inland encroachment of these events. Case study reveals that coastal areas depend heavily on tropical events and stationary fronts, while forcings in inland areas are more evenly distributed. In addition to surface characteristics, the second part of this research explored synoptic patterns found with the most intense IPE across the entire study area. Principal Component Analysis, and Cluster Analysis were employed with 500 and 850 mb geopotential heights and a variety of seed variables in subsequent analyses to discover distinct types of IPE. A manual classification based on IPE origin as either a warm or cold core system, and formation location of the IPE provided the best representation of the synoptic patterns responsible for types of IPE. These IPE types were portrayed via a series of mean flow maps of 500 and 850 mb geopotential height, sea level pressure, and 72 hour mean precipitation. The precipitation amounts of the 72 hour means for the five IPE types were statistically significantly different from each other.