161 research outputs found
Center for Earth and Environmental Science: A Program of Excellence in Water Resources Research
No full textposter abstractResearch and training into the impacts of environmental insults on water systems and the links between water resources and human health are critical needs nationally and internationally. IUPUI is in an excellent position to take on a leadership role in scholarship and teaching about water quality and health.
CEES has built its program and reputation around excellence in water resources and ecosystem restoration research. Key to our success has been the development of a research network founded on strong corporate, governmental and community partnerships and collaborations. This framework is strengthened by the mutual benefit realized by all partners and helps to support IUPUI’s core value of community engagement as an urban research university.
In order to maximize the efficient use of resources, CEES is pursuing four strategic objectives in a manner that will further the universities goals of pursuing excellence in 1) research, scholarship and creative activity, 2) teaching and learning, and 3) civic engagement while also enhancing the resource base of the university.
The Center places the highest priority on four strategic initiatives:
1. The Center will engage in cutting-edge research and training for mixed agricultural and urban watersheds
2. Evaluate and assess watershed Best Management Practices targeting atrazine, nutrients and emerging contaminants and pathogens
3. Establish a K-12 technology based science education program in water, air and energy
4. Work with state agencies to identify watershed issues associated with Major Moves and other economic development initiatives, the standards to be applied and training needs
To this end, the Signature Center program in CEES has focused on building new collaborations with water resources and human health risks. Signature Center funding has provided for new faculty member Dr. Meghna Babbar-Sebens to join the Earth Sciences faculty as an Assistant Professor. Her research is focused on the modeling of water-borne contaminants, and decision support systems for management of water quality and associated ecological and human health risks. Dr. Babbar-Sebens research focuses on a) analysis of uncertainty when models are used to conduct spatially referenced systems-scale environmental assessments, b) incorporation of uncertainty analysis within decision support systems used for risk assessment and management, and c) optimization of water resources planning and management strategies for emergency response and water-borne disease prevention
Center for Earth and Environmental Science: A Program of Excellence in Water Resources Research
No full textposter abstractResearch and training into the impacts of environmental insults on water systems and the links between water resources and human health are critical needs nationally and internationally. IUPUI is in an excellent position to take on a leadership role in scholarship and teaching about water quality and health.
CEES has built its program and reputation around excellence in water resources and ecosystem restoration research. Key to our success has been the development of a research network founded on strong corporate, governmental and community partnerships and collaborations. This framework is strengthened by the mutual benefit realized by all partners and helps to support IUPUI’s core value of community engagement as an urban research university.
In order to maximize the efficient use of resources, CEES is pursuing four strategic objectives in a manner that will further the universities goals of pursuing excellence in 1) research, scholarship and creative activity, 2) teaching and learning, and 3) civic engagement while also enhancing the resource base of the university.
The Center places the highest priority on four strategic initiatives:
1. The Center will engage in cutting-edge research and training for mixed agricultural and urban watersheds
2. Evaluate and assess watershed Best Management Practices targeting atrazine, nutrients and emerging contaminants and pathogens
3. Establish a K-12 technology based science education program in water, air and energy
4. Work with state agencies to identify watershed issues associated with Major Moves and other economic development initiatives, the standards to be applied and training needs
To this end, the Signature Center program in CEES has focused on building new collaborations with water resources and human health risks. Signature Center funding has provided for new faculty member Dr. Meghna Babbar-Sebens to join the Earth Sciences faculty as an Assistant Professor. Her research is focused on the modeling of water-borne contaminants, and decision support systems for management of water quality and associated ecological and human health risks. Dr. Babbar-Sebens research focuses on a) analysis of uncertainty when models are used to conduct spatially referenced systems-scale environmental assessments, b) incorporation of uncertainty analysis within decision support systems used for risk assessment and management, and c) optimization of water resources planning and management strategies for emergency response and water-borne disease prevention
Practitioner Interview
No full textPhone interview with Walter Grayman from Walter Grayman Cons. by Meghna Babbar-Sebens and Marcio Giacomoni. Interview questions asked inquired about (i) practitioner’s professional background, (ii) practitioner’s personal experience with systems analysis techniques and software in their job, (iii) role, benefits, and challenges in using systems analysis concepts in the water resources engineering profession, and (iv) recommendations for improving education of environmental and water resources systems analysis in universities
Practitioner Interview
No full textPhone interview with Richard Males from RMM Technical Services, Inc. by Meghna Babbar-Sebens and Marcio Giacomoni. Interview questions asked inquired about (i) practitioner’s professional background, (ii) practitioner’s personal experience with systems analysis techniques and software in their job, (iii) role, benefits, and challenges in using systems analysis concepts in the water resources engineering profession, and (iv) recommendations for improving education of environmental and water resources systems analysis in universities
REMOTE SENSING DATA ASSIMILATION IN WATER QUALITY NUMERICAL MODELS FOR SIMULATION OF WATER COLUMN TEMPERATURE
No full textIndiana University-Purdue University Indianapolis (IUPUI)Numerical models are important tools for simulating processes within complex natural systems, such as hydrodynamics and water quality processes within a water body. From decision makers’ perspectives, such models also serve as useful tools for predicting the impacts of water quality problems or develop early warning systems. However, accuracy of a numerical model developed for a specific site is dependent on multiple model parameters and variables whose values are attained via calibration processes and/or expert knowledge. Real time variations in the actual aquatic system at a site necessitate continuous monitoring of the system so that model parameters and variables are regularly updated to reflect accurate conditions. Multiple sources of observations can help adjust the model better by providing benefits of individual monitoring technology within the model updating process. For example, remote sensing data provide a spatially dense dataset of model variables at the surface of a water body, while in-situ monitoring technologies can provide data at multiple depths and at more frequent time intervals than remote sensing technologies. This research aims to present an overview of an integrated modeling and data assimilation framework that combines three-dimensional numerical model with multiple sources of observations to simulate water column temperature in a eutrophic reservoir in central Indiana. A variational data assimilation approach is investigated for incorporating spatially continuous remote sensing observations and spatially discrete in-situ observations to change initial conditions of the numerical model. This research addresses the challenge of improving the model performance by combining water temperature from multi-spectral remote sensing analysis and in-situ measurements. Results of the approach on a eutrophic reservoir in Central Indiana show that with four images of multi-spectral remote sensing data assimilated, the model results oscillate more from the in-situ measurements during the data assimilation period. For validation, the data assimilation has negative impacts on the root mean square error. According to quantitative analysis, more significant water temperature stratification leads to larger deviations. Sampling depth differences for remote sensing technology, in-situ measurements and model output are considered as possible error source
Practitioner Interview
No full textPhone interview with Eric Loucks from CDM Smith by Marcio Giacomoni and Meghna Babbar-Sebens. Interview questions asked inquired about (i) practitioner’s professional background, (ii) practitioner’s personal experience with systems analysis techniques and software in their job, (iii) role, benefits, and challenges in using systems analysis concepts in the water resources engineering profession, and (iv) recommendations for improving education of environmental and water resources systems analysis in universities
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Assessment of Multi-year Hydrologic Performance of Bioretention Facility using Real-Time Sensors
No full textBioretention facilities are emerging as a popular way to deal with stormwater runoff in urban environments and address its concerns. Real-time sensors installed in bioretention facilities aid in understanding the performance and feasibility of such facilities over time. A bioretention facility in Corvallis, Oregon was monitored for a study period of 3 years using real-time sensors deployed to measure flows in and out of the facility along with soil moisture content in the bioretention cells. Flow was monitored using Steven’s SDX sensor, and Decagon’s CTD sensor. The soil moisture content was monitored using Steven’s Hydra Probes. Overall, results have indicated that performance of CTD sensors was significantly better than SDX sensors in both inlets and outlets. There was large variability in captured runoff ranging from high 94% water treatment to as low as 6% treatment. The bioretention cells were able to maintain peak flow reduction ratio of 0.87, 0.82, 0.85 and 0.76 for fall, winter, spring and summer respectively throughout the study period. Mean peak delays was 44, 19, 150 and 55mins for fall, winter, spring and summer respectively. Soil moisture reading were dependent on the longitudinal distance away from the inlet. The mean values increased from 2015 to 2017, however the variability and standard deviation decreased. Decay rates during drying periods had high variability in 2015 but showed stability after that year.
Lead Distribution in Urban Soils: Relationship Between Lead Sources and Children's Blood Lead Levels
No full textIndiana University-Purdue University Indianapolis (IUPUI
Prediction of Spatial-Temporal Distribution of Algal Metabolites in Eagle Creek Reservoir, Indianapolis, IN
No full textIndiana University-Purdue University Indianapolis (IUPUI)In this research, Environmental Fluid Dynamic Code (EFDC) and Adaptive- Networkbased
Fuzzy Inference System Models (ANFIS) were developed and implemented to
determine the spatial-temporal distribution of cyanobacterial metabolites: 2-MIB and
geosmin, in Eagle Creek Reservoir, IN. The research is based on the current need for
understanding algae dynamics and developing prediction methods for algal taste and odor
release events.
In this research the methodology for prediction of 2-MIB and geosmin production was
explored. The approach incorporated a combination of numerical and heuristic modeling
to show its capabilities in prediction of cyanobacteria metabolites. The reservoir’s
variable data measured at monitoring stations and consisting of chemical/physical and
biological parameters with the addition of calculated mixing conditions within the
reservoir were used to train and validate the models. The Adaptive – Network based
Fuzzy Inference System performed satisfactorily in predicting the metabolites, in spite of
multiple model constraints. The predictions followed the generally observed trends of
algal metabolites during the three seasons over three years (2008-2010). The randomly
selected data pairs for geosmin for validation achieved coefficient of determination of
0.78, while 2-MIB validation was not accepted due to large differences between two
observations and their model prediction. Although, these ANFIS results were accepted,
the further application of the ANFIS model coupled with the numerical models to predict
spatio-temporal distribution of metabolites showed serious limitations, due to numerical
model calibration errors. The EFDC-ANFIS model over-predicted Pseudanabaena spp.
biovolumes for selected stations. The predicted value was 18,386,540 mm3/m3, while
observed values were 942,478 mm3/m3. The model simulating Planktothrix agardhii gave
negative biovolumes, which were assumed to represent zero values observed at the
station. The taste and odor metabolite, geosmin, was under-predicted as the predicted
v
concentration was 3.43 ng/L in comparison to observed value of 11.35 ng/l. The 2-MIB
model did not validate during EFDC to ANFIS model evaluation.
The proposed approach and developed methodology could be used for future applications
if the limitations are appropriately addressed
Analysis of Mercury Concentrations in Indiana Soil to Evaluate Patterns of Long-Term Atmospheric Mercury Deposition
No full textIndiana University-Purdue University Indianapolis (IUPUI)Mercury (Hg) has proven to be a risk to the public, mainly through the consumption of fish. Because of this, many fish consumption advisories have been issued in Indiana. Although much is known about the global cycle of mercury, little is known about how local and regional emission sources of mercury impact local and regional mercury cycling. This study’s objective was to determine the scope of mercury concentration in central Indiana by using a broad grid of soil mercury measurements. Sampling was designed to capture the net retained mercury content in soils, and to determine whether spatial patterns in exist in soil mercury contents that could be related to emission sources of mercury and post-emission transport patterns from wind. Results from this study revealed significant differences in mercury concentrations for soils in central Indiana. The core of the study area, concentrated in the urban area of Indianapolis, exhibited soil mercury contents that were 20 times higher than values in the outskirts of the study area. The spatial pattern resembled a bulls-eye shape centered on Indianapolis, and with comparison to the reported Hg emission from local sources, including a coal-fired power plant, indicates a strong regional deposition signal linked to those emission sources but marked by wind-driven transport to the northeast. This effect of local emission sources
resulting in local deposition indicates that limiting mercury emissions will have a net beneficial impact on local environmental quality and human health
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