+publisher:"University of Oklahoma" +contributor:("Basara, Jeffrey")

University of Oklahoma

1. Zhou, Yuting. THE USE OF REMOTE SENSING AND EDDY COVARIANCE TECHNOLOGIES TO CHARACTERIZE CROPLAND, DROUGHT AND LAND MANAGEMENTS AND THEIR IMPACTS ON ECOSYSTEM DYNAMICS.

Degree: PhD, 2017, University of Oklahoma

URL: http://hdl.handle.net/11244/50829

► With the increasing population, human needs more food, fresh water, and other ecosystem services, which burdens the agricultural and natural ecosystems. Under the background of… (more)

▼ With the increasing population, human needs more food, fresh water, and other ecosystem services, which burdens the agricultural and natural ecosystems. Under the background of climate change, meeting these human needs becomes more challenging because of increasing temperature, climate extremes, etc. and their interaction with human activities. Thus, it is important to understand the impacts of climate change and human activities on ecosystem dynamics. The land-use and land-cover change, one of the most important human activities, greatly affects the function and dynamics of ecosystems. Drought is one of the most costly natural disasters and imposes wide-ranging impacts on the economy, environment, and society. This dissertation aimed to strengthen the usage of remote sensing and eddy covariance techniques in paddy rice mapping, agricultural drought monitoring, land management effects assessment, and evaluating the impacts of drought on cattle production. Chapter 2 identified the different flooding/transplanting periods of paddy rice and natural wetlands. The natural wetlands foods earlier and have a shorter duration than paddy rice in the Panjin Plain, a temperate region in China. Using this asynchronous flooding stages, this chapter extracted the paddy rice planting area from the rice-wetland coexistent area using MODIS and Landsat 8 imagery. The comparison and validation tests indicated high accuracy of our paddy rice map. Chapter 3 quantified the agricultural drought of tallgrass prairie in the SGP using a remotely sensed water-related vegetation index derived from MODIS. The results are comparable to other widely used drought products. The spatial pattern of drought duration was highly correlated with the decreasing precipitation gradient from east to west. LSWI-based drought depictions are sensitive to both precipitation anomalies from the historical mean and abnormal seasonal precipitation distributions. A comparison with other widely used drought products is made. Chapter 4 examined the impacts of burning, baling, and grazing on canopy and carbon fluxes in a pasture through integrating PhenoCam images, satellite remote sensing, and eddy covariance data. Landsat images were used to assess the baling area and the trajectory of vegetation recovery. MODIS vegetation indices (VIs) were used in the Vegetation Photosynthesis Model (VPM) to estimate gross primary production (GPPVPM) at a MODIS pixel for the flux tower (baled) site. Multiple datasets allowed studying intra-annual variations caused by various management practices. The larger increase of GPP after large rain in baled grassland (photosynthetically more active vegetation) compensated the reduction in GPP caused by baling. This result indicated that the interaction of management practices with climate is important when studying their impacts on GPP. Chapter 5 evaluated the impacts of drought on cattle production in the SGP during 2000-2015 use meteorological, remote sensing, and statistical data. The results showed that the consecutive years of… Advisors/Committee Members: Xiao, Xiangming (advisor), Basara, Jeffrey (committee member), Luo, Yiqi (committee member), Steiner, Jean (committee member), McCarthy, Heather (committee member).

Subjects/Keywords: Remote sensing; Eddy covariance; Land use and land cover change; drought

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APA (6^th Edition):

Zhou, Y. (2017). THE USE OF REMOTE SENSING AND EDDY COVARIANCE TECHNOLOGIES TO CHARACTERIZE CROPLAND, DROUGHT AND LAND MANAGEMENTS AND THEIR IMPACTS ON ECOSYSTEM DYNAMICS. (Doctoral Dissertation). University of Oklahoma. Retrieved from http://hdl.handle.net/11244/50829

Chicago Manual of Style (16^th Edition):

Zhou, Yuting. “THE USE OF REMOTE SENSING AND EDDY COVARIANCE TECHNOLOGIES TO CHARACTERIZE CROPLAND, DROUGHT AND LAND MANAGEMENTS AND THEIR IMPACTS ON ECOSYSTEM DYNAMICS.” 2017. Doctoral Dissertation, University of Oklahoma. Accessed January 23, 2021. http://hdl.handle.net/11244/50829.

MLA Handbook (7^th Edition):

Zhou, Yuting. “THE USE OF REMOTE SENSING AND EDDY COVARIANCE TECHNOLOGIES TO CHARACTERIZE CROPLAND, DROUGHT AND LAND MANAGEMENTS AND THEIR IMPACTS ON ECOSYSTEM DYNAMICS.” 2017. Web. 23 Jan 2021.

Vancouver:

Zhou Y. THE USE OF REMOTE SENSING AND EDDY COVARIANCE TECHNOLOGIES TO CHARACTERIZE CROPLAND, DROUGHT AND LAND MANAGEMENTS AND THEIR IMPACTS ON ECOSYSTEM DYNAMICS. [Internet] [Doctoral dissertation]. University of Oklahoma; 2017. [cited 2021 Jan 23]. Available from: http://hdl.handle.net/11244/50829.

Council of Science Editors:

Zhou Y. THE USE OF REMOTE SENSING AND EDDY COVARIANCE TECHNOLOGIES TO CHARACTERIZE CROPLAND, DROUGHT AND LAND MANAGEMENTS AND THEIR IMPACTS ON ECOSYSTEM DYNAMICS. [Doctoral Dissertation]. University of Oklahoma; 2017. Available from: http://hdl.handle.net/11244/50829

University of Oklahoma

2. Illston, Bradley. Near Surface Atmospheric Impacts Resulting From a Developing Metropolitan Area.

Degree: PhD, 2016, University of Oklahoma

URL: http://hdl.handle.net/11244/47037

► Over the past century, the population of the world has become increasingly urbanized. As a result, cities have become larger and more densely populated than… (more)

▼ Over the past century, the population of the world has become increasingly urbanized. As a result, cities have become larger and more densely populated than any time in history. This unprecedented growth and rapid modification of the surface has impacted the overlying boundary-layer of the atmosphere. As such, understanding the overall magnitude and spatial variability of these changes has critical value to the ever growing population living within the impacted regions. The goal of this study is to determine the impact of urbanization on near surface atmospheric conditions and how those impacts evolve with time. The Weather Research & Forecasting (WRF) model was utilized to simulate atmospheric conditions in and around the Oklahoma City area. The WRF output was compared to surface observations from the Oklahoma City Micronet and the Oklahoma Mesonet to quantify model accuracies and biases. The National Land Cover Dataset (NLCD) was subsequently modified to represent land use characteristics from 1890, following the Oklahoma Land Rush, to 2011 at intervals of every 30 years. The WRF model was initialized with modified NLCD land use datasets to determine the impact from a developing metropolitan area. An analysis of the optimal simulation run times demonstrated that the 24-hour run time provided the most accurate results in the variety of scenarios and the urban heat island index was within about 0.5°C of the verification from surface observing stations. The results yielded an increase in urban heat island indices of over 3.5°C throughout the past 120 years with an over 5.0°C magnitude warming of the near surface air temperatures over and around the developed urban areas. The analysis of the 1890 land use background showed that the natural variability of air temperatures without any influences from the metropolitan area are on the order of 1-2°C. Additionally, implementing unique methodologies for interpreting urban heat characteristics demonstrated that by utilizing the top 10, 100, 500, and 1000 warmest model simulation pixels as urban values instead of arbitrary points, a more representative value for urban heat island indices was calculated (resulting in a value of about 3.5°C in the summer in 2011). The use of air temperature histograms (in particular for the minimum temperature) of the model grid point’s output showed changes in the historical distribution of air temperature values indicating a transition towards warmer values over time. Additionally, an analysis of the distribution of air temperature values across the entire domain for each of the historical time periods showed the areal spread of air temperature impacts by over 20%. Advisors/Committee Members: Basara, Jeffrey (advisor), Klein, Petra (committee member), Richman, Michael (committee member), Hu, Xiaoming (committee member), Tarhule, Aondover (committee member).

Subjects/Keywords: Meteorology; Urban Heat Island; Numerical Modeling

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APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6^th Edition):

Illston, B. (2016). Near Surface Atmospheric Impacts Resulting From a Developing Metropolitan Area. (Doctoral Dissertation). University of Oklahoma. Retrieved from http://hdl.handle.net/11244/47037

Chicago Manual of Style (16^th Edition):

Illston, Bradley. “Near Surface Atmospheric Impacts Resulting From a Developing Metropolitan Area.” 2016. Doctoral Dissertation, University of Oklahoma. Accessed January 23, 2021. http://hdl.handle.net/11244/47037.

MLA Handbook (7^th Edition):

Illston, Bradley. “Near Surface Atmospheric Impacts Resulting From a Developing Metropolitan Area.” 2016. Web. 23 Jan 2021.

Vancouver:

Illston B. Near Surface Atmospheric Impacts Resulting From a Developing Metropolitan Area. [Internet] [Doctoral dissertation]. University of Oklahoma; 2016. [cited 2021 Jan 23]. Available from: http://hdl.handle.net/11244/47037.

Council of Science Editors:

Illston B. Near Surface Atmospheric Impacts Resulting From a Developing Metropolitan Area. [Doctoral Dissertation]. University of Oklahoma; 2016. Available from: http://hdl.handle.net/11244/47037

University of Oklahoma

3. Akumaga, Uvirkaa. UTILIZING PROCESS-BASED CROP MODELLING TO ASSESS CLIMATE-INDUCED CROP YIELDS AND ADAPTATION OPTIONS IN THE NIGER RIVER BASIN OF WEST AFRICA.

Degree: PhD, 2018, University of Oklahoma

URL: http://hdl.handle.net/11244/54430

► This dissertation used the FAO AquaCrop model to evaluate the impact of climate change on major cereal yields and adaptation options in three agro-ecological zones… (more)

▼ This dissertation used the FAO AquaCrop model to evaluate the impact of climate change on major cereal yields and adaptation options in three agro-ecological zones of the Niger River Basin. The crops analysed include maize, millet, and sorghum under rainfed cultivation systems in various agro-ecological zones within the Niger Basin. This work also investigated several adaptation strategies, including changes in the sowing dates, soil nutrient status, and cultivar. Future climate change is estimated using nine ensemble bias-corrected climate model projection results under rcp4.5 and rcp8.5 emissions scenario at mid future time period, 2021/25-2050. The study also analyzed the projected changes in the intra-seasonal rainfall characteristics in the region. The study includes three self-contained but related studies; (1) Validation and testing of the FAO AquaCrop model under different levels of nitrogen fertilizer on rainfed maize in Nigeria, West Africa; (2) Utilizing Process-based Modelling to Assess the Impact of Climate Change on Crop Yields and Adaptation Options in the Niger River Basin, West Africa, and (3) Projected changes in intra-seasonal rainfall characteristics in the Niger River Basin, West Africa. Broadly, the results of this study show that the AquaCrop model satisfactory simulated cereal yields at different nitrogen fertility levels in this region. The observed and simulated yields were evaluated to be satisfactory with a normalized root mean square error (NRMSE) between 8%-17% indicating excellent to good results for grain yield while the NRMSE for biomass yields were between 20-26% indicating good to satisfactory results. The results show that on average, temperature had a larger effect on crop yields so that the increase in precipitation could still be a net loss of crop yield. The simulated results showed that climate change effects on maize and sorghum yield will be mostly positive (2% to 6% increase) in the Southern Guinea savanna zone while at the Northern Guinea savanna zone it is mostly negative (2 to 20% decrease). The results also show that at the Sahelian zone the projected temperature and precipitation changes have little to no impacts on millet yield for the future time period, 2021/25-2050. In all agro-ecological zones, increasing soil fertility from poor fertility to moderate, near optimal and optimal level significantly reversed the negative yield change respectively by over 20%, 70% and 180% for moderate fertility, near optimal fertility, and optimal fertility. Thus, management or adaptation factors, such as soil fertility, had a much larger effect on crop yield than climatic change factors. The results further show an increase of the average rainfall of about 5%, 10-20% and 10-15% for the Southern Guinea, Northern Guinea and Sahelian Zones respectively. On the other hand, there is a significant mean change of rainfall intensities and the frequency of rainfall at the low, heavy and extreme rainfall events in the Niger River Basin. The results showed an increase in the frequency of… Advisors/Committee Members: Tarhule, Aondover (advisor), Hoagland, Bruce (committee member), McPherson, Renee (committee member), de Beurs, Kirsten (committee member), Basara, Jeffrey (committee member).

Subjects/Keywords: Geography; Agriculture; Crop Modelling; Climate Change

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APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6^th Edition):

Akumaga, U. (2018). UTILIZING PROCESS-BASED CROP MODELLING TO ASSESS CLIMATE-INDUCED CROP YIELDS AND ADAPTATION OPTIONS IN THE NIGER RIVER BASIN OF WEST AFRICA. (Doctoral Dissertation). University of Oklahoma. Retrieved from http://hdl.handle.net/11244/54430

Chicago Manual of Style (16^th Edition):

Akumaga, Uvirkaa. “UTILIZING PROCESS-BASED CROP MODELLING TO ASSESS CLIMATE-INDUCED CROP YIELDS AND ADAPTATION OPTIONS IN THE NIGER RIVER BASIN OF WEST AFRICA.” 2018. Doctoral Dissertation, University of Oklahoma. Accessed January 23, 2021. http://hdl.handle.net/11244/54430.

MLA Handbook (7^th Edition):

Akumaga, Uvirkaa. “UTILIZING PROCESS-BASED CROP MODELLING TO ASSESS CLIMATE-INDUCED CROP YIELDS AND ADAPTATION OPTIONS IN THE NIGER RIVER BASIN OF WEST AFRICA.” 2018. Web. 23 Jan 2021.

Vancouver:

Akumaga U. UTILIZING PROCESS-BASED CROP MODELLING TO ASSESS CLIMATE-INDUCED CROP YIELDS AND ADAPTATION OPTIONS IN THE NIGER RIVER BASIN OF WEST AFRICA. [Internet] [Doctoral dissertation]. University of Oklahoma; 2018. [cited 2021 Jan 23]. Available from: http://hdl.handle.net/11244/54430.

Council of Science Editors:

Akumaga U. UTILIZING PROCESS-BASED CROP MODELLING TO ASSESS CLIMATE-INDUCED CROP YIELDS AND ADAPTATION OPTIONS IN THE NIGER RIVER BASIN OF WEST AFRICA. [Doctoral Dissertation]. University of Oklahoma; 2018. Available from: http://hdl.handle.net/11244/54430

University of Oklahoma

4. Nemunaitis, Kodi. Observational and model analyses of the Oklahoma City urban heat island.

Degree: PhD, 2014, University of Oklahoma

URL: http://hdl.handle.net/11244/10422

► To date, much of the current understanding of the impacts of urban areas on atmospheric processes results from a number of field programs. Between 28… (more)

▼ To date, much of the current understanding of the impacts of urban areas on atmospheric processes results from a number of field programs. Between 28 June and 31 July 2003, a vast array of instrument systems collected high-resolution observations of meteorological variables in and around Oklahoma City during Joint Urban 2003, the largest urban dispersion field experiment to date. The data collected from the field measurements, combined with data collected from existing atmospheric observing systems in central Oklahoma presented a unique opportunity to investigate the urban heat island of Oklahoma City. As numerical weather prediction models continue to evolve toward finer grid spacing, it becomes increasingly important to properly represent urban effects in land surface, surface layer, and PBL schemes. Recent efforts have been undertaken to “urbanize” numerical weather prediction and climate models. One common approach is to couple an urban canopy model with a land surface model. For this study, the single-layer urban canopy model in the High-Resolution Land Data Assimilation System (HRLDAS) and Advanced Research Weather Research and Forecasting (ARW-WRF) modeling systems were used to investigate the sensitivity of near-surface air temperatures and energy fluxes to urban canopy parameters in uncoupled (land) and coupled (land-atmosphere) predictions. The model results were compared with observations collected by the Oklahoma Mesonet and Joint Urban 2003 collaborators. While the components of the surface energy balance were sensitive to albedo and thermal conductivity of the urban roof surface, and to the fraction of the grid cell that was impervious, near-surface air temperatures, particularly during the daytime, did not show significant variations with urban parameters. The sensitivity of near-surface temperatures to urban canopy parameters depended on the method used to calculate the skin temperature of the impervious surface. Advisors/Committee Members: Klein, Petra (advisor), Basara, Jeffrey (committee member), Fedorovich, Evgeni (committee member), Droegemeier, Kelvin (committee member), Tarhule, Aondover (committee member).

Subjects/Keywords: Meteorology

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APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6^th Edition):

Nemunaitis, K. (2014). Observational and model analyses of the Oklahoma City urban heat island. (Doctoral Dissertation). University of Oklahoma. Retrieved from http://hdl.handle.net/11244/10422

Chicago Manual of Style (16^th Edition):

Nemunaitis, Kodi. “Observational and model analyses of the Oklahoma City urban heat island.” 2014. Doctoral Dissertation, University of Oklahoma. Accessed January 23, 2021. http://hdl.handle.net/11244/10422.

MLA Handbook (7^th Edition):

Nemunaitis, Kodi. “Observational and model analyses of the Oklahoma City urban heat island.” 2014. Web. 23 Jan 2021.

Vancouver:

Nemunaitis K. Observational and model analyses of the Oklahoma City urban heat island. [Internet] [Doctoral dissertation]. University of Oklahoma; 2014. [cited 2021 Jan 23]. Available from: http://hdl.handle.net/11244/10422.

Council of Science Editors:

Nemunaitis K. Observational and model analyses of the Oklahoma City urban heat island. [Doctoral Dissertation]. University of Oklahoma; 2014. Available from: http://hdl.handle.net/11244/10422

University of Oklahoma

5. Flanagan, Paul. The Changing Hydroclimate of the United States Great Plains: Meteorological and Climatological Impacts on Water Resources.

Degree: PhD, 2018, University of Oklahoma

URL: http://hdl.handle.net/11244/316316

► In the United States Great Plains (GP), understanding precipitation variability is key in developing an understanding of the present and future availability of water in… (more)

▼ In the United States Great Plains (GP), understanding precipitation variability is key in developing an understanding of the present and future availability of water in the region. Numerous studies have investigated the hydroclimate, or the part of the climate relating to the hydrology of a region, of the GP from the soils, surface, vegetation and their impacts on water resources. Even so, there is still more to be understood from a climatological perspective. Further, analysis of the GP climate in terms of temperature and precipitation maxima in relation to the hydroclimate is not yet complete. While drought and its associated drivers have been studied in the GP region, periods of excessive precipitation (pluvials) at seasonal to interannual scales have received less attention. Thus, analysis of the GP climate in terms of features that directly impact water is required to more fully understand the GP climate and future impacts to water availability. The first part of this study investigated a long-term observational dataset to quantify the asynchronicity and address the impacts of climate variability and change. Global Historical Climate Network Daily (GHCN-Daily) data were utilized for this study; 352 GHCN-Daily stations were identified based on specific criteria and the dates of the precipitation and temperature maxima for each year were identified at daily and weekly intervals. An Asynchronous Difference Index (ADI) was computed by determining the difference between these dates averaged over each decade. Analysis of Daily and Weekly ADI revealed two physically distinct regimes of ADI (positive and negative), with comparable shifts in the timing of both the maximum of precipitation and temperature over all six states within the GP examined when comparing the two different regimes. Time series analysis of decadal average ADI yielded moderate shifts (~5-10 days from linear regression analysis) in ADI in several states with increased variability occurring over much of the study region. Utilizing the ERA-20C dataset, a climatological analysis of GP pluvials was completed. Through an analysis of GP precipitation, the region was split into two subregions; the Northern Great Plains (NGP) and the Southern Great Plains (SGP). Analysis of ERA-20C geopotential heights during NGP and SGP pluvial years reveals atmospheric anomaly patterns associated with the occurrence of pluvial years. In the SGP, this pattern is depicted by negative height anomalies over the southwestern United States, coincident with a southward shifted jet stream over the north Pacific allowing a more frequent passage of synoptic waves toward the southern United States. The NGP pluvial pattern shows negative height anomalies over the northwestern United States and an anomalously extended jet stream over the northern North Pacific. Further, analysis of sea surface temperatures (SST) and streamfunction aids in explaining the occurrence of these pluvial years. During SGP above average precipitation (i.e., pluvial) years, central tropical Pacific SST… Advisors/Committee Members: Basara, Jeffrey (advisor), Furtado, Jason (committee member), Martin, Elinor (committee member), Richman, Michael (committee member), Xiao, Xiangming (committee member).

Subjects/Keywords: Climate; Great Plains; Hydroclimate

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APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6^th Edition):

Flanagan, P. (2018). The Changing Hydroclimate of the United States Great Plains: Meteorological and Climatological Impacts on Water Resources. (Doctoral Dissertation). University of Oklahoma. Retrieved from http://hdl.handle.net/11244/316316

Chicago Manual of Style (16^th Edition):

Flanagan, Paul. “The Changing Hydroclimate of the United States Great Plains: Meteorological and Climatological Impacts on Water Resources.” 2018. Doctoral Dissertation, University of Oklahoma. Accessed January 23, 2021. http://hdl.handle.net/11244/316316.

MLA Handbook (7^th Edition):

Flanagan, Paul. “The Changing Hydroclimate of the United States Great Plains: Meteorological and Climatological Impacts on Water Resources.” 2018. Web. 23 Jan 2021.

Vancouver:

Flanagan P. The Changing Hydroclimate of the United States Great Plains: Meteorological and Climatological Impacts on Water Resources. [Internet] [Doctoral dissertation]. University of Oklahoma; 2018. [cited 2021 Jan 23]. Available from: http://hdl.handle.net/11244/316316.

Council of Science Editors:

Flanagan P. The Changing Hydroclimate of the United States Great Plains: Meteorological and Climatological Impacts on Water Resources. [Doctoral Dissertation]. University of Oklahoma; 2018. Available from: http://hdl.handle.net/11244/316316

University of Oklahoma

6. Zou, Zhenhua. MULTI-SCALE REMOTE SENSING OF OPEN SURFACE WATER BODY AREA AND QUALITY.

Degree: PhD, 2019, University of Oklahoma

URL: http://hdl.handle.net/11244/319681

► Water is one of the most important resources for life. Climate change and climate variability have caused dramatic variations and significant trends in surface water… (more)

▼ Water is one of the most important resources for life. Climate change and climate variability have caused dramatic variations and significant trends in surface water resources, while global population growth and increased food demand have greatly stressed and modified global surface water systems. These changes in surface water resources have huge consequences to human society, natural environment, and global biodiversity. Landsat satellites have scanned the entire earth in every 16 days since the 1980s. The historical information of surface water body spatial distribution, temporal variation, and multi-decadal trends documented in remote sensing images can aid in water resource research, planning, and management, yet it is not well explored. This dissertation aims to develop algorithms and generate open surface water body maps at state, national, and global scales. Based on these maps, the interannual variations and long-term trends of surface water body area were analyzed while their climatic and anthropogenic drivers were examined. The joint analysis of both surface water body area and land water storage was carried out to explore the consistency and divergence between surface and land water resource dynamics. The potential of satellite images in water chlorophyll-a concentration estimation was also evaluated. Chapter 2 used ~16,000 Landsat images to analyze surface water body dynamics in Oklahoma and found significant decreasing trends in both surface water body area (the maximum, year-long, seasonal, and average water body area) and water body number (maximum and year-long water body numbers) during 1984–2015. The decrease of water body area was mainly attributed to the shrinking of large water bodies (>1 km2) while the decrease in water body number was mainly caused by the vanishing of some small water bodies. Smaller water bodies have a higher risk of drying up under climate-warming scenarios. Chapter 3 used ~ 370,000 Landsat images and the Gravity Recovery and Climate Experiment (GRACE) land water storage data to analyze changes in surface water area and groundwater across the contiguous US (CONUS) during 1984–2016. Divergent trends of surface water area were found across the CONUS with water-poor regions of the Southwest and Northwest US getting poorer, while the water-rich regions of the Southeast US and far north Great Plains getting richer. In the 2012-2014 prolonged droughts, surface water body shrinkage had led to massive groundwater mining and the rapid decline of land water storage in California and the Southern Great Plains. Chapter 4 used ~3.8 million Landsat images and GRACE land water storage data to analyze surface water area and land water storage jointly during 1984–2017 at 0.01° grid cells, 0.5° grid cells, and 5° tiles across the globe. About 8.5 million 0.01° grid cells had significant increasing or decreasing trends in surface water area over the past decades, forming interesting spatial patterns in northern Greenland, Tibetan Plateau, western US, the Great Lakes, Gulf of Bothnia, central… Advisors/Committee Members: Xiao, Xiangming (advisor), Basara, Jeffrey (committee member), Hong, Yang (committee member), McCarthy, Heather (committee member), Souza, Lara (committee member).

Subjects/Keywords: Hydrology.; Biology, Limnology.

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APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6^th Edition):

Zou, Z. (2019). MULTI-SCALE REMOTE SENSING OF OPEN SURFACE WATER BODY AREA AND QUALITY. (Doctoral Dissertation). University of Oklahoma. Retrieved from http://hdl.handle.net/11244/319681

Chicago Manual of Style (16^th Edition):

Zou, Zhenhua. “MULTI-SCALE REMOTE SENSING OF OPEN SURFACE WATER BODY AREA AND QUALITY.” 2019. Doctoral Dissertation, University of Oklahoma. Accessed January 23, 2021. http://hdl.handle.net/11244/319681.

MLA Handbook (7^th Edition):

Zou, Zhenhua. “MULTI-SCALE REMOTE SENSING OF OPEN SURFACE WATER BODY AREA AND QUALITY.” 2019. Web. 23 Jan 2021.

Vancouver:

Zou Z. MULTI-SCALE REMOTE SENSING OF OPEN SURFACE WATER BODY AREA AND QUALITY. [Internet] [Doctoral dissertation]. University of Oklahoma; 2019. [cited 2021 Jan 23]. Available from: http://hdl.handle.net/11244/319681.

Council of Science Editors:

Zou Z. MULTI-SCALE REMOTE SENSING OF OPEN SURFACE WATER BODY AREA AND QUALITY. [Doctoral Dissertation]. University of Oklahoma; 2019. Available from: http://hdl.handle.net/11244/319681

7. Jin, Cui. SATELLITE-BASED CHARACTERIZATION OF CROP TYPE AND PRODUCTIVITY OF AGROECOSYSTEMS: CASE STUDIES IN NORTHEAST CHINA, SOUTHERN AFRICA, AND CONTERMINOUS USA.

Degree: PhD, 2016, University of Oklahoma

URL: http://hdl.handle.net/11244/34579

► Agroecosystem, or agricultural ecosystems, is the important anthropogenic ecosystem to meet the human demand for food, fiber, and feed, and it covers approximately 40-50% of… (more)

▼ Agroecosystem, or agricultural ecosystems, is the important anthropogenic ecosystem to meet the human demand for food, fiber, and feed, and it covers approximately 40-50% of the earth’s land surface. Accurate estimates of agricultural land use and land cover and Gross Primary Production (GPP) are indispensable for global food security and understanding variations in the terrestrial carbon budgets. This dissertation aimed to strengthen the capacities of remote sensing to produce the high-quality products of crop type maps and primary productivity on large regional scales. In chapter 2, we designed simple algorithms to identify paddy rice of two different phenological phases (flooding/transplanting and ripening) at regional scales using 30-m multi-temporal Landsat images. Sixteen Landsat images from 2010 - 2012 were used to generate the paddy rice map in the Sanjiang Plain, northeast China - one of the intensive paddy rice cultivation regions in Northern Asia. The user and producer accuracies of paddy rice on the resultant Landsat-based paddy rice map were 90% and 94%, respectively, and was an improvement over the paddy rice dataset derived through visual interpretation and digitalization on the fine-resolution satellite images and traditional agricultural census data. Chapter 3 evaluated the capacities of the temporal MODIS vegetation indices and the satellite-based Vegetation Photosynthesis Model (VPM) to describe phenology and model the seasonal dynamics of GPP for savanna woodlands in Southern Africa on the site level. The results showed that the VPM-based GPP estimates tracked the seasonal dynamics and interannual variation of GPP estimated from eddy covariance measurements at flux tower sites. This study suggests that the VPM is a valuable tool for estimating GPP of semi-arid and semi-humid savanna woodland ecosystems in Southern Africa. Chapter 4 assessed the accuracies of air temperature and downward shortwave radiation of the North America Regional Reanalysis (NARR) by the National Centers for Environmental Prediction (NCEP), and evaluated impacts of the accuracies of regional climate inputs on the VPM-based GPP estimates for U.S. Midwest cropland. The results implied that the bias of NARR downward shortwave radiation introduced significant uncertainties into the VPM-based GPP estimates, suggesting that more accurate surface radiation datasets are needed to estimate primary production of terrestrial ecosystems at regional and global scales. Chapter 5 presented independent and complementary analyses of the impact of 2012 flash drought on productivity in the U.S. Midwest using multiple sources of evidences, i.e., in-situ AmeriFlux CO2 data, satellite observations of vegetation indices and solar-induced chlorophyll fluorescence (SIF), and scaled ecosystem modeling. The results showed that phenological activities of all biomes advanced 1-2 weeks earlier in 2012 compared to other years of 2010-2014, and the drought threatened the U.S. Midwest agroecosystems. The growth of grassland/prairie and cropland was… Advisors/Committee Members: Xiao, Xiangming (advisor), Basara, Jeffrey (committee member), Dong, Jinwei (committee member), Steiner, Jean (committee member), McCarthy, Heather (committee member).

Subjects/Keywords: food security; remote sensing; primary production; land use and land cover change

11 more images…

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APA (6^th Edition):

Jin, C. (2016). SATELLITE-BASED CHARACTERIZATION OF CROP TYPE AND PRODUCTIVITY OF AGROECOSYSTEMS: CASE STUDIES IN NORTHEAST CHINA, SOUTHERN AFRICA, AND CONTERMINOUS USA. (Doctoral Dissertation). University of Oklahoma. Retrieved from http://hdl.handle.net/11244/34579

Chicago Manual of Style (16^th Edition):

Jin, Cui. “SATELLITE-BASED CHARACTERIZATION OF CROP TYPE AND PRODUCTIVITY OF AGROECOSYSTEMS: CASE STUDIES IN NORTHEAST CHINA, SOUTHERN AFRICA, AND CONTERMINOUS USA.” 2016. Doctoral Dissertation, University of Oklahoma. Accessed January 23, 2021. http://hdl.handle.net/11244/34579.

MLA Handbook (7^th Edition):

Jin, Cui. “SATELLITE-BASED CHARACTERIZATION OF CROP TYPE AND PRODUCTIVITY OF AGROECOSYSTEMS: CASE STUDIES IN NORTHEAST CHINA, SOUTHERN AFRICA, AND CONTERMINOUS USA.” 2016. Web. 23 Jan 2021.

Vancouver:

Jin C. SATELLITE-BASED CHARACTERIZATION OF CROP TYPE AND PRODUCTIVITY OF AGROECOSYSTEMS: CASE STUDIES IN NORTHEAST CHINA, SOUTHERN AFRICA, AND CONTERMINOUS USA. [Internet] [Doctoral dissertation]. University of Oklahoma; 2016. [cited 2021 Jan 23]. Available from: http://hdl.handle.net/11244/34579.

Council of Science Editors:

Jin C. SATELLITE-BASED CHARACTERIZATION OF CROP TYPE AND PRODUCTIVITY OF AGROECOSYSTEMS: CASE STUDIES IN NORTHEAST CHINA, SOUTHERN AFRICA, AND CONTERMINOUS USA. [Doctoral Dissertation]. University of Oklahoma; 2016. Available from: http://hdl.handle.net/11244/34579

University of Oklahoma

8. Zhang, Yao. DIAGNOSTIC ANALYSIS OF TERRESTRIAL GROSS PRIMARY PRODUCTIVITY USING REMOTE SENSING AND IN SITU OBSERVATIONS.

Degree: PhD, 2017, University of Oklahoma

URL: http://hdl.handle.net/11244/52420

► Vegetation play a critical role in the interactions between atmosphere and biosphere. CO2 fixed by plants through photosynthesis process at ecosystem scale is termed as… (more)

▼ Vegetation play a critical role in the interactions between atmosphere and biosphere. CO2 fixed by plants through photosynthesis process at ecosystem scale is termed as gross primary production (GPP). It is also the first step CO2 entering the biosphere from the atmosphere. It not only fuels the ecosystem functioning, but also drives the global carbon cycle. Accurate estimation of the ecosystem photosynthetic carbon uptake at a global scale can help us better understand the global carbon budget, and the ecosystem sensitivity to the global climate change. Satellite observations have the advantage of global coverage and high revisit cycle, hence, are ideal for global GPP estimation. The simple production efficiency model that utilize the remote sensing imagery and climate data can provide reasonably well estimates of GPP at a global scale. With the solar induced chlorophyll fluorescence (SIF) being retrieved from satellite observations, new opportunities emerge in directly estimating photosynthesis from the energy absorption and partitioning perspective. In this thesis, by combining observations from both in situ and remotely acquired, I tried to (1) investigate the GPP SIF relationship using data from observations and model simulations; (2) improve a production efficiency model (vegetation photosynthesis model, VPM) and apply it to the regional and global scale; (3) investigate the GPP and SIF sensitivity to drought at different ecosystems; (4) explore the global interannual variation of GPP and its contributing factors. Chapter 2 uses site level observations of both SIF and GPP to explore their linkage at both leaf and canopy/ecosystem scale throughout a growing season. Two drought events happened during this growing season also highlight the advantage of SIF in early drought warning and its close linkage to photosynthetic activity. Chapter 3 compares the GPP and SIF relationships using both instantaneous and daily integrated observations, the daily GPP and satellite retrieved SIF are latitudinal dependent and time-of-overpass dependent. Daily integrated SIF estimation shows better correlation with daily GPP observations. Chapter 4 compares different vegetation indices with SIF to get an empirical estimation of fraction of photosynthetically active radiation by chlorophyll (fPARchl). By comparing this fPARchl estimation with ecosystem light use efficiency retrieved from eddy covariance flux towers, the light use efficiency based on light absorption by chlorophyll shows narrower range of variation that can be used for improving production efficiency models. Chapter 5 investigates the drought impact on GPP through the change of vegetation canopy optical properties and physiological processes. Forest and non-forest ecosystems shows very different responses in terms of these two limitation and need to be treated differently in GPP modelling. Chapter 6 applies the improved VPM to North America and compared with SIF retrieval from GOME-2 instrument. The comparison shows good consistency between GPP and SIF in both spatial… Advisors/Committee Members: Xiao, Xiangming (advisor), Basara, Jeffrey (committee member), McCarthy, Heather (committee member), Souza, Lara (committee member), Hong, Yang (committee member).

Subjects/Keywords: remote sensing; light use efficiency; gross primary production

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APA (6^th Edition):

Zhang, Y. (2017). DIAGNOSTIC ANALYSIS OF TERRESTRIAL GROSS PRIMARY PRODUCTIVITY USING REMOTE SENSING AND IN SITU OBSERVATIONS. (Doctoral Dissertation). University of Oklahoma. Retrieved from http://hdl.handle.net/11244/52420

Chicago Manual of Style (16^th Edition):

Zhang, Yao. “DIAGNOSTIC ANALYSIS OF TERRESTRIAL GROSS PRIMARY PRODUCTIVITY USING REMOTE SENSING AND IN SITU OBSERVATIONS.” 2017. Doctoral Dissertation, University of Oklahoma. Accessed January 23, 2021. http://hdl.handle.net/11244/52420.

MLA Handbook (7^th Edition):

Zhang, Yao. “DIAGNOSTIC ANALYSIS OF TERRESTRIAL GROSS PRIMARY PRODUCTIVITY USING REMOTE SENSING AND IN SITU OBSERVATIONS.” 2017. Web. 23 Jan 2021.

Vancouver:

Zhang Y. DIAGNOSTIC ANALYSIS OF TERRESTRIAL GROSS PRIMARY PRODUCTIVITY USING REMOTE SENSING AND IN SITU OBSERVATIONS. [Internet] [Doctoral dissertation]. University of Oklahoma; 2017. [cited 2021 Jan 23]. Available from: http://hdl.handle.net/11244/52420.

Council of Science Editors:

Zhang Y. DIAGNOSTIC ANALYSIS OF TERRESTRIAL GROSS PRIMARY PRODUCTIVITY USING REMOTE SENSING AND IN SITU OBSERVATIONS. [Doctoral Dissertation]. University of Oklahoma; 2017. Available from: http://hdl.handle.net/11244/52420

University of Oklahoma

9. Timmer, Reed. Relationships between Monthly Agroclimate Variability and Local Crop Yield in the Central and Eastern United States and Southern Canada.

Degree: PhD, 2015, University of Oklahoma

URL: http://hdl.handle.net/11244/14671

► Short-term agroclimate is defined here as the monthly-to-seasonal meteorological, geological, biological, and psychological factors that modulate local and regional crop yield. Modern agricultural production in… (more)

▼ Short-term agroclimate is defined here as the monthly-to-seasonal meteorological, geological, biological, and psychological factors that modulate local and regional crop yield. Modern agricultural production in the central and eastern United States and southern Canada accounts for a vast majority of the global food supply as the leading producer annually for corn (~80%), soybeans (~50%) and the cereal grains (> 20%), since the new millennium (U.S. Grains Council, 2010; American Soybeans Association, 2014; EPA, 2014). Hence, the worldwide socioeconomic significance of study region (Fig. 1) crop production in the midst of ruthless monthly-to-seasonal agroclimate variability is ever increasing, and especially the mitigation of crop yield losses from growing season climate extremes such as heat waves and severe agricultural droughts and pluvials. The recently infamous Droughts of 1988 and 2012-14 are the two most costly natural disasters in U.S. history ahead of even Hurricane Katrina (2005) and Super Storm Sandy (2012), followed shortly by the agriculturally devastating Flood of 1993 in the Upper Mississippi River Basin, and show the enhanced sensitivity of modern farming to short-term agroclimate extremes. The present study represents the meteorological aspects of locally and regionally impactful agroclimate variability with growing season (March-October) monthly growing degree day (GDD) totals, precipitation anomalies, the Palmer Drought Indices (PDI), and midsummer extreme heat above crop-specific pollen sterilization thresholds; as based on the recently extended Lamb-Richman daily temperature and precipitation data sets for eastern North America (Skinner et al., 1999; Timmer and Lamb, 2007), and NCDC’s monthly PDI data by U.S. Climate Division (Karl et al., 1986; Heddinghaus and Sabol, 1991; NCDC, 2014). Five managers of large commercial farms across North America and prominent members of the Association of Agricultural Production Executives (AAPEX) provided expert opinion input on the relative severity of these agroclimate extremes from planting through harvest at six widely separated farming locations, cultivating five different focus crops (corn, soybeans, cotton, sorghum, spring wheat). These six AAPEX farming locations base the present study’s exhaustive analyses of local crop yield-agroclimate relationships, motivated to identify periods within the growing season when monthly extremes in GDD, precipitation, PDI, and temperature during flowering are most impactful. The local and regional predictability of growing season (March-October) monthly extremes in GDD, precipitation, and PDI across the central/eastern U.S. and southern Canada are assessed via time-lagged teleconnections with 3- and 6-month modes of Pacific Ocean SST variability. Several strong monthly-to-seasonal teleconnection patterns were identified for these agroclimate extremes with not only mature and transitional El Niño/La Niña patterns, but also the cold and warm phases of the Pacific Decadal Oscillation (PDO) and North Pacific… Advisors/Committee Members: Leslie, Lance (advisor), Lamb, Peter (advisor), Richman, Michael (advisor), Basara, Jeffrey (committee member), Carr, Frederick (committee member), McPherson, Renee (committee member).

Subjects/Keywords: climatology; agriculture; crop science; El Nino; Pacific Ocean

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APA (6^th Edition):

Timmer, R. (2015). Relationships between Monthly Agroclimate Variability and Local Crop Yield in the Central and Eastern United States and Southern Canada. (Doctoral Dissertation). University of Oklahoma. Retrieved from http://hdl.handle.net/11244/14671

Chicago Manual of Style (16^th Edition):

Timmer, Reed. “Relationships between Monthly Agroclimate Variability and Local Crop Yield in the Central and Eastern United States and Southern Canada.” 2015. Doctoral Dissertation, University of Oklahoma. Accessed January 23, 2021. http://hdl.handle.net/11244/14671.

MLA Handbook (7^th Edition):

Timmer, Reed. “Relationships between Monthly Agroclimate Variability and Local Crop Yield in the Central and Eastern United States and Southern Canada.” 2015. Web. 23 Jan 2021.

Vancouver:

Timmer R. Relationships between Monthly Agroclimate Variability and Local Crop Yield in the Central and Eastern United States and Southern Canada. [Internet] [Doctoral dissertation]. University of Oklahoma; 2015. [cited 2021 Jan 23]. Available from: http://hdl.handle.net/11244/14671.

Council of Science Editors:

Timmer R. Relationships between Monthly Agroclimate Variability and Local Crop Yield in the Central and Eastern United States and Southern Canada. [Doctoral Dissertation]. University of Oklahoma; 2015. Available from: http://hdl.handle.net/11244/14671

University of Oklahoma

10. McDaniel, Jay. Self-Packaged and Low-Loss Suspended Integrated Stripline Filters for Next Generation Systems.

Degree: PhD, 2018, University of Oklahoma

URL: http://hdl.handle.net/11244/301298

► The method in which the frequency spectrum is currently allocated is unsustainable. An increasing number of devices are becoming wireless, overcrowding an already crowded spectrum… (more)

▼ The method in which the frequency spectrum is currently allocated is unsustainable. An increasing number of devices are becoming wireless, overcrowding an already crowded spectrum (e.g., the ISM band). Therefore, future systems will be forced to move to higher frequencies in order to be allocated an unused slice of the spectrum and accumulate the desired/required bandwidth. Furthermore, with the continued desire to implement a multitude of sensors on unmanned aerial vehicles (UAVs), as well as the need for conformal small-cell repeaters for 5G communications, next generation systems will have to achieve unprecedented reductions in size, weight, power, and cost (SWaP-C). In order for future systems to become practical, several fundamental technological hurdles must be overcome including the development of low loss and highly integrated components used to build next generation systems. The RF/microwave filter is of particular interest, as it is not only crucial for conditioning the signal for transmission and/or digitization, but can also affect critical system parameters based on it's placement in the system. Due to the increased attenuative nature of the environment at microwave frequencies, the systems dynamic range will have to be maximized requiring an exceptionally low loss filter if placed close to the antenna in the receiver (Rx) chain, which is necessary for defense and adaptive/re-configurable systems. While low loss microwave filtering can be easily achieved using waveguide design techniques, it is much more difficult in a highly integrated planar design due to increased radiation and dielectric losses. A promising solution which minimizes these losses and offers a planar solution is the suspended integrated stripline (SISL) filter. In this research, a low loss fully-board integrated lowpass and highpass filter, using the suspended integrated stripline technology, are designed and studied, pushing the stat-of-the-art in planar filtering technologies. A multi-layer board stack-up, with internally buried hollowed cavities, is used to create the suspended stripline. The embedded filter is accessed through a co-planar waveguide-to-stripline vertical via transition and vice-versa. Simulated and measured results show that insertion losses of less than 1 dB are obtainable including the vertical via transition and associated trace losses. Compared to it's suspended substrate stripline (SSS) predecessor, the SISL filter is one order of magnitude smaller and lighter while achieving identical performance. Beyond the proposed filters, this technological solution can be applied to several other passive microwave components such as couplers, power dividers, and gain equalizers. The capabilities demonstrated in this research will be crucial to the design and integration of modern and next generation systems as it requires no mechanical housing, connectors, or assembly, resulting in a light weight, compact size, and low cost solution. Advisors/Committee Members: Sigmarsson, Hjalti (advisor), Yeary, Mark (committee member), Goodman, Nathan (committee member), Fulton, Caleb (committee member), Basara, Jeffrey (committee member).

Subjects/Keywords: Chebyshev; lowpass filter; suspended integrated stripline; suspended substrate stripline

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APA (6^th Edition):

McDaniel, J. (2018). Self-Packaged and Low-Loss Suspended Integrated Stripline Filters for Next Generation Systems. (Doctoral Dissertation). University of Oklahoma. Retrieved from http://hdl.handle.net/11244/301298

Chicago Manual of Style (16^th Edition):

McDaniel, Jay. “Self-Packaged and Low-Loss Suspended Integrated Stripline Filters for Next Generation Systems.” 2018. Doctoral Dissertation, University of Oklahoma. Accessed January 23, 2021. http://hdl.handle.net/11244/301298.

MLA Handbook (7^th Edition):

McDaniel, Jay. “Self-Packaged and Low-Loss Suspended Integrated Stripline Filters for Next Generation Systems.” 2018. Web. 23 Jan 2021.

Vancouver:

McDaniel J. Self-Packaged and Low-Loss Suspended Integrated Stripline Filters for Next Generation Systems. [Internet] [Doctoral dissertation]. University of Oklahoma; 2018. [cited 2021 Jan 23]. Available from: http://hdl.handle.net/11244/301298.

Council of Science Editors:

McDaniel J. Self-Packaged and Low-Loss Suspended Integrated Stripline Filters for Next Generation Systems. [Doctoral Dissertation]. University of Oklahoma; 2018. Available from: http://hdl.handle.net/11244/301298

University of Oklahoma

11. Wu, Xiaocui. Modelling terrestrial carbon fluxes and crop production with remote sensing and in-situ observations.

Degree: PhD, 2020, University of Oklahoma

URL: http://hdl.handle.net/11244/325433

► Plants fix carbon through photosynthesis, sequestering carbon dioxide from the atmosphere and substantially mitigating the climate warming effect induced by anthropogenic CO2 emissions. Terrestrial gross… (more)

▼ Plants fix carbon through photosynthesis, sequestering carbon dioxide from the atmosphere and substantially mitigating the climate warming effect induced by anthropogenic CO2 emissions. Terrestrial gross primary production (GPP) through photosynthesis is crucial for understanding the land-atmospheric carbon exchange, which is the largest component and one of the most uncertain aspects of the global carbon cycle. Thus, accurate estimation of GPP can help better understand the global carbon budget, and the ecosystem sensitivity to the global climate change. Data driven models that utilize the climate data and remote sensing-based observations can provide reasonable estimates of GPP. The emergence of the solar induced chlorophyll fluorescence (SIF) from both in-situ and satellite observations provides another tool to understand and estimate plant photosynthesis. Remote sensing-based observations and models are also widely used in crop monitoring. Timely and accurate crop production estimation are needed to sustain global food security under the background of climate change. My overall objective is to improve the data-driven models to provide better GPP estimates, to combine SIF with other data sources to advance our understanding of the photosynthesis process and ecosystem sensitivity to droughts, and to investigate the potential of a data-driven model, specifically, the vegetation photosynthesis model (VPM), in crop monitoring. In Chapter 2, we investigated the seasonal dynamics of eddy flux-derived GPP (GPPEC), solar-induced chlorophyll fluorescence (SIF), and four vegetation indices (VIs) and their relationships in a tall grassland site. We also examined drought impact on those structural and physiological proxies of plant photosynthesis. We found SIF explained 49% of the GPP variability at the seasonal scale, and had a stronger consistency with GPP than the four VIs. Among the four VIs, the soil background corrected VIs, near-infrared reflectance of vegetation (NIRv) and enhanced vegetation index (EVI) showed the best consistency with both GPP and SIF. In addition, SIF is more sensitive to drought than the VIs. This study suggested that the potential of SIF in tracking photosynthesis in grassland and drought impact on photosynthesis. In Chapter 3, we improved the vegetation photosynthesis model (VPM) by considering the difference of the maximum light use efficiency for C3 and C4 croplands. Model validation against GPPEC in multiple sites distributed over CONUS suggests better accuracy of GPP simulated by VPM (GPPVPM) in tracking the cross-site variability and interannual variability (R2 = 0.84 and 0.46, respectively) when compared to MOD17 GPP. We also assessed the spatial and temporal (seasonal) consistency of GPPVPM, MOD17 GPP and other two common-used GPP products with the Global Ozone Monitoring Experiment-2 (GOME-2) SIF. We found good consistency of GPPVPM with SIF across space and time. Anomaly analyses for those GPP products and GOME-2 SIF showed that high GPP during the 2012 spring compensated for low GPP… Advisors/Committee Members: Xiao, Xiangming (advisor), Basara, Jeffrey (committee member), McCarthy, Heather (committee member), Souza, Lara (committee member), Steiner, Jean (committee member).

Subjects/Keywords: Remote sensing; Gross primary production; Crop production; Solar-induced chlorophyll fluorescence

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APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6^th Edition):

Wu, X. (2020). Modelling terrestrial carbon fluxes and crop production with remote sensing and in-situ observations. (Doctoral Dissertation). University of Oklahoma. Retrieved from http://hdl.handle.net/11244/325433

Chicago Manual of Style (16^th Edition):

Wu, Xiaocui. “Modelling terrestrial carbon fluxes and crop production with remote sensing and in-situ observations.” 2020. Doctoral Dissertation, University of Oklahoma. Accessed January 23, 2021. http://hdl.handle.net/11244/325433.

MLA Handbook (7^th Edition):

Wu, Xiaocui. “Modelling terrestrial carbon fluxes and crop production with remote sensing and in-situ observations.” 2020. Web. 23 Jan 2021.

Vancouver:

Wu X. Modelling terrestrial carbon fluxes and crop production with remote sensing and in-situ observations. [Internet] [Doctoral dissertation]. University of Oklahoma; 2020. [cited 2021 Jan 23]. Available from: http://hdl.handle.net/11244/325433.

Council of Science Editors:

Wu X. Modelling terrestrial carbon fluxes and crop production with remote sensing and in-situ observations. [Doctoral Dissertation]. University of Oklahoma; 2020. Available from: http://hdl.handle.net/11244/325433

University of Oklahoma

12. Dower, William. Advances in Synthetic Aperture Radar from a Wavenumber Perspective.

Degree: PhD, 2017, University of Oklahoma

URL: http://hdl.handle.net/11244/52722

► This dissertation examines the wavenumber domain of Synthetic Aperture Radar (SAR) images. This domain is the inverse Fourier transform domain of a SAR image. The… (more)

Subjects/Keywords: synthetic aperture radar; image resolution; back projection; bistatic radar

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APA (6^th Edition):

Dower, W. (2017). Advances in Synthetic Aperture Radar from a Wavenumber Perspective. (Doctoral Dissertation). University of Oklahoma. Retrieved from http://hdl.handle.net/11244/52722

Chicago Manual of Style (16^th Edition):

Dower, William. “Advances in Synthetic Aperture Radar from a Wavenumber Perspective.” 2017. Doctoral Dissertation, University of Oklahoma. Accessed January 23, 2021. http://hdl.handle.net/11244/52722.

MLA Handbook (7^th Edition):

Dower, William. “Advances in Synthetic Aperture Radar from a Wavenumber Perspective.” 2017. Web. 23 Jan 2021.

Vancouver:

Dower W. Advances in Synthetic Aperture Radar from a Wavenumber Perspective. [Internet] [Doctoral dissertation]. University of Oklahoma; 2017. [cited 2021 Jan 23]. Available from: http://hdl.handle.net/11244/52722.

Council of Science Editors:

Dower W. Advances in Synthetic Aperture Radar from a Wavenumber Perspective. [Doctoral Dissertation]. University of Oklahoma; 2017. Available from: http://hdl.handle.net/11244/52722

University of Oklahoma

13. Saharia, Manabendra. Characterization and Prediction of Flash Flood Severity.

Degree: PhD, 2017, University of Oklahoma

URL: http://hdl.handle.net/11244/50784

► Flash floods, a subset of floods, are a particularly damaging natural hazard worldwide due to their multidisciplinary nature, difficulty in forecasting, and fast response that… (more)

▼ Flash floods, a subset of floods, are a particularly damaging natural hazard worldwide due to their multidisciplinary nature, difficulty in forecasting, and fast response that limits emergency responses. The purpose of this work is to develop a framework of characterizing floods and flash floods based on a multitude of explanatory variables that describe the geology, topography, pedology, climatology, and rainfall spatial variability. Until now, flash flood characterization studies in the United States have been limited in scope due to the lack of a comprehensive database matching flood characteristics such as peak discharges and flood duration with geospatial and geomorphologic information. In this study, A long data record spanning 78 years from the United States Geological Survey (USGS) stream gauge network is combined with National Weather Service (NWS) flooding thresholds to study floods at basin and event scale, with special focus on the rise time and unit peak discharge. A new metric for flash flood severity called ‘flashiness’ is also proposed that represents the rate of rise of the hydrograph during flooding conditions and thus captures both the magnitude and timing aspects of floods. Associations between flashiness and geophysical variables are initially constructed at locations where there is known information from both discharge observations and the geospatial datasets. These relationships are first investigated through first-order characterization of trends and their variability. Since we don’t have discharge observations everywhere, a multi-dimensional statistical modeling approach is built upon these associations to regionalize flashiness to all ungauged locations across the Continental United States (CONUS). Several localized flash flood hotspots were identified outside of the originally defined regions including the western slopes of the Appalachians in Tennessee, Kentucky, and West Virginia. Furthermore, a high-resolution Multi-Radar/Multi-Sensor (MRMS) rainfall reanalysis dataset (1 km/5-min resolution) from 2002-2011 was used to quantify the relative impact of sub-basin scale rainfall spatial variability and geomorphology on flashiness. It was found that the percentage contribution of rainfall spatial variability to flashiness is 9% more for flash floods compared to floods. Results from this research highlight how the trend and variability of flooding variables such as rise time, unit peak discharge, flash flood severity etc. could be explained using a large number of explanatory variables. It also demonstrates how complex non-linear association between the hydrologic response and variables representing causative processes could be modeled with reasonable skill to predict in ungauged locations. Advisors/Committee Members: Hong, Yang (advisor), Gourley, Jonathan J. (advisor), Kolar, Randall (committee member), Strevett, Keith A. (committee member), Basara, Jeffrey (committee member).

Subjects/Keywords: Hydrology.; flash flood; precipitation; multivariate modeling; big data

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APA (6^th Edition):

Saharia, M. (2017). Characterization and Prediction of Flash Flood Severity. (Doctoral Dissertation). University of Oklahoma. Retrieved from http://hdl.handle.net/11244/50784

Chicago Manual of Style (16^th Edition):

Saharia, Manabendra. “Characterization and Prediction of Flash Flood Severity.” 2017. Doctoral Dissertation, University of Oklahoma. Accessed January 23, 2021. http://hdl.handle.net/11244/50784.

MLA Handbook (7^th Edition):

Saharia, Manabendra. “Characterization and Prediction of Flash Flood Severity.” 2017. Web. 23 Jan 2021.

Vancouver:

Saharia M. Characterization and Prediction of Flash Flood Severity. [Internet] [Doctoral dissertation]. University of Oklahoma; 2017. [cited 2021 Jan 23]. Available from: http://hdl.handle.net/11244/50784.

Council of Science Editors:

Saharia M. Characterization and Prediction of Flash Flood Severity. [Doctoral Dissertation]. University of Oklahoma; 2017. Available from: http://hdl.handle.net/11244/50784

University of Oklahoma

14. Christian, Jordan. Flash Droughts: A Local to Global Analysis of Rapid Drought Intensification and their Associated Impacts.

Degree: PhD, 2020, University of Oklahoma

URL: http://hdl.handle.net/11244/326653

► Flash drought is characterized by the rapid intensification toward drought conditions and is primarily associated with detrimental impacts to agricultural production. Unlike conventional (slowly developing)… (more)

Subjects/Keywords: Atmospheric Sciences; Flash Drought; Evapotranspiration; Climatology

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APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6^th Edition):

Christian, J. (2020). Flash Droughts: A Local to Global Analysis of Rapid Drought Intensification and their Associated Impacts. (Doctoral Dissertation). University of Oklahoma. Retrieved from http://hdl.handle.net/11244/326653

Chicago Manual of Style (16^th Edition):

Christian, Jordan. “Flash Droughts: A Local to Global Analysis of Rapid Drought Intensification and their Associated Impacts.” 2020. Doctoral Dissertation, University of Oklahoma. Accessed January 23, 2021. http://hdl.handle.net/11244/326653.

MLA Handbook (7^th Edition):

Christian, Jordan. “Flash Droughts: A Local to Global Analysis of Rapid Drought Intensification and their Associated Impacts.” 2020. Web. 23 Jan 2021.

Vancouver:

Christian J. Flash Droughts: A Local to Global Analysis of Rapid Drought Intensification and their Associated Impacts. [Internet] [Doctoral dissertation]. University of Oklahoma; 2020. [cited 2021 Jan 23]. Available from: http://hdl.handle.net/11244/326653.

Council of Science Editors:

Christian J. Flash Droughts: A Local to Global Analysis of Rapid Drought Intensification and their Associated Impacts. [Doctoral Dissertation]. University of Oklahoma; 2020. Available from: http://hdl.handle.net/11244/326653

University of Oklahoma

15. Erlingis Lamers, Jessica. MOISTURE SOURCES FOR FLASH FLOODS IN THE UNITED STATES.

Degree: PhD, 2017, University of Oklahoma

URL: http://hdl.handle.net/11244/52250

► This dissertation uses backward trajectories derived from North American Regional Reanalysis data for 19,253 flash flood reports published by the National Weather Service to assess… (more)

▼ This dissertation uses backward trajectories derived from North American Regional Reanalysis data for 19,253 flash flood reports published by the National Weather Service to assess the nonlocal contribution of the land surface to the moisture budget for flash flood events in the conterminous United States. The impact of land surface interactions was evaluated seasonally and for six regions of interest: the West Coast, Arizona, the Front Range, Flash Flood Alley, the Missouri Valley, and the Appalachians. Parcels were released from flooded locations and traced backward in time for 120 hours. The boundary layer height was used to determine whether moisture increases occurred within the boundary layer or not. For moisture increases occurring within the boundary layer, moisture increases were attributed to evapotranspiration from the land surface. Surface properties were recorded from an offline run of the Noah land surface model. In general, moisture increases attributed to the land surface were associated with anomalously high surface latent heat fluxes and anomalously low sensible heat fluxes (resulting in a positive anomaly of evaporative fraction) as well as positive anomalies in top layer soil moisture. Over the ocean, uptakes were associated with positive anomalies in sea surface temperatures, the magnitude of which varies both regionally and seasonally. Major surface-based source regions of moisture for flash floods in the United States include the Gulf of Mexico, Gulf of California, and central United States, which are attributable in part to interactions between the land surface and the atmosphere. While much of this dissertation focuses on the large-scale sources for moisture for flash flood events, storm-scale phenomena are also investigated for a precipitation event during the Integrated Precipitation and Hydrology Experiment. A case of stratiform precipitation impinging on complex terrain was examined for its microphysical properties that could result in enhanced rainfall. The data from a field experiment show coalescence processes dominate within the upslope region, suggesting enhanced updrafts aided by orographic lift sustain convection over the upslope region, leading to larger median drop diameters. Advisors/Committee Members: Palmer, Robert (advisor), Gourley, Jonathan J. (committee member), Hong, Yang (committee member), Basara, Jeffrey (committee member), Cavallo, Steven (committee member), Kolar, Randall (committee member).

Subjects/Keywords: hydrometeorology; flash floods; moisture sources; trajectories

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APA (6^th Edition):

Erlingis Lamers, J. (2017). MOISTURE SOURCES FOR FLASH FLOODS IN THE UNITED STATES. (Doctoral Dissertation). University of Oklahoma. Retrieved from http://hdl.handle.net/11244/52250

Chicago Manual of Style (16^th Edition):

Erlingis Lamers, Jessica. “MOISTURE SOURCES FOR FLASH FLOODS IN THE UNITED STATES.” 2017. Doctoral Dissertation, University of Oklahoma. Accessed January 23, 2021. http://hdl.handle.net/11244/52250.

MLA Handbook (7^th Edition):

Erlingis Lamers, Jessica. “MOISTURE SOURCES FOR FLASH FLOODS IN THE UNITED STATES.” 2017. Web. 23 Jan 2021.

Vancouver:

Erlingis Lamers J. MOISTURE SOURCES FOR FLASH FLOODS IN THE UNITED STATES. [Internet] [Doctoral dissertation]. University of Oklahoma; 2017. [cited 2021 Jan 23]. Available from: http://hdl.handle.net/11244/52250.

Council of Science Editors:

Erlingis Lamers J. MOISTURE SOURCES FOR FLASH FLOODS IN THE UNITED STATES. [Doctoral Dissertation]. University of Oklahoma; 2017. Available from: http://hdl.handle.net/11244/52250

16. Clark III, Robert Allan. Machine Learning Predictions of Flash Floods.

Degree: PhD, 2016, University of Oklahoma

URL: http://hdl.handle.net/11244/44890

► This dissertation contains a literature review and three studies concerned with the development, assessment, and use of machine learning (ML) algorithms to explore automatically generated… (more)

▼ This dissertation contains a literature review and three studies concerned with the development, assessment, and use of machine learning (ML) algorithms to explore automatically generated predictions of flash floods. The literature review explores several relevant issues: how flash floods are defined, the organization and structure of the flash flood forecasting and alerting enterprise in the U.S., proposed methods and tools for understanding and forecasting flash floods, the statistical underpinnings of ML, and how ML techniques can be applied to a wide variety of complex scientific problems, including those of a meteorological bent. Using an archive of numerical weather predictions (NWP) from the Global Forecast System (GFS) model and a historical archive of reports of flash floods across the U.S., I develop a set of machine learning models that output forecasts of the probability of receiving a Storm Data report of a flash flood given a certain set of atmospheric and hydrologic conditions as forecast by the GFS model. I explore the statistical characteristics of these predictions, including their skill, across various regions and time periods. Then I expound upon how various atmospheric fields affect the probability of receiving a report of a flash flood and discuss different methods for interpreting the results from the proposed ML models. Finally, I explore how the mooted system could be operationalized, by delving into two case studies of past impactful flash floods in the U.S., by presenting results of National Weather Service forecasters using and interacting with the proposed tools in a research-to-operations testbed environment, and by geographically extending the predictions to cover additional parts of the world’s landmass via a set of case studies on the European continent. One ML algorithm in particular, the random forest technique, is used throughout the vast majority of the dissertation, because it is quite successful at incorporating large amounts of information in a computationally-efficient manner and because it results in reasonably skillful predictions. The system is largely successful at identifying flash floods resulting from synoptically-forced events, but struggles with isolated flash floods that arise as a result of weather systems largely unresolvable by the coarse resolution of a global NWP system. The results from this collection of studies suggest that automatic probabilistic predictions of flash floods are a plausible way forward in operational forecasting, but that future research could focus upon applying these methods to finer-scale NWP guidance, to NWP ensembles, to new regions of the world, and to longer forecast lead times. Advisors/Committee Members: Gourley, Jonathan J. (advisor), Palmer, Robert (advisor), Hong, Yang (advisor), Morrissey, Mark (committee member), Basara, Jeffrey (committee member), Shehab, Randa (committee member).

Subjects/Keywords: flash flood; machine learning; numerical weather prediction; hydrometeorology

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APA (6^th Edition):

Clark III, R. A. (2016). Machine Learning Predictions of Flash Floods. (Doctoral Dissertation). University of Oklahoma. Retrieved from http://hdl.handle.net/11244/44890

Chicago Manual of Style (16^th Edition):

Clark III, Robert Allan. “Machine Learning Predictions of Flash Floods.” 2016. Doctoral Dissertation, University of Oklahoma. Accessed January 23, 2021. http://hdl.handle.net/11244/44890.

MLA Handbook (7^th Edition):

Clark III, Robert Allan. “Machine Learning Predictions of Flash Floods.” 2016. Web. 23 Jan 2021.

Vancouver:

Clark III RA. Machine Learning Predictions of Flash Floods. [Internet] [Doctoral dissertation]. University of Oklahoma; 2016. [cited 2021 Jan 23]. Available from: http://hdl.handle.net/11244/44890.

Council of Science Editors:

Clark III RA. Machine Learning Predictions of Flash Floods. [Doctoral Dissertation]. University of Oklahoma; 2016. Available from: http://hdl.handle.net/11244/44890

17. Gagne, David John II. Coupling Data Science Techniques and Numerical Weather Prediction Models for High-Impact Weather Prediction.

Degree: PhD, 2016, University of Oklahoma

URL: http://hdl.handle.net/11244/44917

► Meteorologists have access to more model guidance and observations than ever before, but this additional information does not necessarily lead to better forecasts. New tools… (more)

▼ Meteorologists have access to more model guidance and observations than ever before, but this additional information does not necessarily lead to better forecasts. New tools are needed to reduce the cognitive load on forecasters and to provide them with accurate, reliable consensus guidance. Techniques from the data science community, such as machine learning and image processing, have the potential to summarize and calibrate numerical weather prediction model output and to generate deterministic and probabilistic forecasts of high-impact weather. In this dissertation, I developed data-science-based approaches to improve the predictions of two high-impact weather domains: hail and solar irradiance. Both hail and solar irradiance produce large economic impacts, have non-Gaussian distributions of occurrence, are poorly observed, and are partially driven by processes too small to be resolved by numerical weather prediction models. Hail forecasts were produced with convection-allowing model output from the Center for Analysis and Prediction of Storms and National Center for Atmospheric Research ensembles. The machine learning hail forecasts were compared against storm surrogate variables and physics-based diagnostic models of hail size. Initial machine learning hail forecasts reduced size errors but struggled with predicting extreme events. By coupling the machine learning model to predicting hail size distributions and estimating the distribution parameters jointly, the machine learning methods were able to show skill and reliability in predicting both severe and significant hail. Machine learning model and data configurations for gridded solar irradiance forecasting were evaluated on two numerical modeling systems. The evaluation determined how machine learning model choice, closeness of fit to training data, training data aggregation, and interpolation method affected forecasts of clearness index at Oklahoma Mesonet sites not included in the training data. The choice of machine learning model, interpolation scheme, and loss function had the biggest impacts on performance. Errors tended to be lower at testing sites with sunnier weather and those that were closer to training sites. All of the machine learning methods produced reliable predictions but underestimated the frequency of cloudiness compared to observations. Advisors/Committee Members: McGovern, Amy (advisor), Basara, Jeffrey (committee member), Fagg, Andrew (committee member), Richman, Michael (committee member), Williams, John (committee member), Xue, Ming (committee member).

Subjects/Keywords: Atmospheric Sciences.; Artificial Intelligence.; Meteorology; Machine Learning

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APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6^th Edition):

Gagne, D. J. I. (2016). Coupling Data Science Techniques and Numerical Weather Prediction Models for High-Impact Weather Prediction. (Doctoral Dissertation). University of Oklahoma. Retrieved from http://hdl.handle.net/11244/44917

Chicago Manual of Style (16^th Edition):

Gagne, David John II. “Coupling Data Science Techniques and Numerical Weather Prediction Models for High-Impact Weather Prediction.” 2016. Doctoral Dissertation, University of Oklahoma. Accessed January 23, 2021. http://hdl.handle.net/11244/44917.

MLA Handbook (7^th Edition):

Gagne, David John II. “Coupling Data Science Techniques and Numerical Weather Prediction Models for High-Impact Weather Prediction.” 2016. Web. 23 Jan 2021.

Vancouver:

Gagne DJI. Coupling Data Science Techniques and Numerical Weather Prediction Models for High-Impact Weather Prediction. [Internet] [Doctoral dissertation]. University of Oklahoma; 2016. [cited 2021 Jan 23]. Available from: http://hdl.handle.net/11244/44917.

Council of Science Editors:

Gagne DJI. Coupling Data Science Techniques and Numerical Weather Prediction Models for High-Impact Weather Prediction. [Doctoral Dissertation]. University of Oklahoma; 2016. Available from: http://hdl.handle.net/11244/44917

18. Flamig, Zachary Lolos. A HIGH RESOLUTION DISTRIBUTED HYDROLOGIC MODEL CLIMATOLOGY OVER THE CONTERMINOUS UNITED STATES FOCUSED ON FLASH FLOODING.

Degree: PhD, 2016, University of Oklahoma

URL: http://hdl.handle.net/11244/44865

► This study will describe the MRMS reanalysis precipitation dataset created for the time period from 2001 to 2011. This high resolution 1-km² 5-minute dataset is… (more)

Subjects/Keywords: Meteorology; Hydrology; Flooding

…University of Oklahoma (OU), NSSL, NASA, and commercial partner AccuWeather who owns the…

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APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6^th Edition):

Flamig, Z. L. (2016). A HIGH RESOLUTION DISTRIBUTED HYDROLOGIC MODEL CLIMATOLOGY OVER THE CONTERMINOUS UNITED STATES FOCUSED ON FLASH FLOODING. (Doctoral Dissertation). University of Oklahoma. Retrieved from http://hdl.handle.net/11244/44865

Chicago Manual of Style (16^th Edition):

Flamig, Zachary Lolos. “A HIGH RESOLUTION DISTRIBUTED HYDROLOGIC MODEL CLIMATOLOGY OVER THE CONTERMINOUS UNITED STATES FOCUSED ON FLASH FLOODING.” 2016. Doctoral Dissertation, University of Oklahoma. Accessed January 23, 2021. http://hdl.handle.net/11244/44865.

MLA Handbook (7^th Edition):

Flamig, Zachary Lolos. “A HIGH RESOLUTION DISTRIBUTED HYDROLOGIC MODEL CLIMATOLOGY OVER THE CONTERMINOUS UNITED STATES FOCUSED ON FLASH FLOODING.” 2016. Web. 23 Jan 2021.

Vancouver:

Flamig ZL. A HIGH RESOLUTION DISTRIBUTED HYDROLOGIC MODEL CLIMATOLOGY OVER THE CONTERMINOUS UNITED STATES FOCUSED ON FLASH FLOODING. [Internet] [Doctoral dissertation]. University of Oklahoma; 2016. [cited 2021 Jan 23]. Available from: http://hdl.handle.net/11244/44865.

Council of Science Editors:

Flamig ZL. A HIGH RESOLUTION DISTRIBUTED HYDROLOGIC MODEL CLIMATOLOGY OVER THE CONTERMINOUS UNITED STATES FOCUSED ON FLASH FLOODING. [Doctoral Dissertation]. University of Oklahoma; 2016. Available from: http://hdl.handle.net/11244/44865

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