WATER RESOURCES
The quality and security of water resources are critical issues across the region and around the world. Syracuse Center of Excellence Members have exceptional capabilities to analyze the complex dynamics of entire watersheds and to develop innovations that promote healthy ecosystems.
Current projects include operation of an extensive system of robots to monitor the quality of surface waters in Central New York, development of new sensors to detect harmful contaminants, and monitoring and modeling of watersheds.
More information on Syracuse CoE-funded projects can be found below:
Development and Application of an Intelligent System for the Management of Environmental Quality in Urban Watershed Ecosystems
Principal Investigators: Charles Driscoll, Civil and Environmental Engineering, Syracuse University and Steven Effler, Upstate Freshwater Institute
Project Abstract: Traditional modeling and manual monitoring programs have the inherent shortcoming of delaying the supply of potentially critical information to public health officials and managers. In this study we will rectify this limitation through the development, integration, demonstration, and application of innovative technologies in water quality monitoring and modeling. Our overall objective is to develop, test, and conduct preliminary demonstrations of an intelligent environmental control system (i-ECS) for a large urban watershed in central New York. Our specific objectives and approaches to achieve these objectives are to: 1) develop and demonstrate the operation of an integrated network of robotic monitoring units to assess temporal and spatial patterns in the quality of water supplies and receiving waters, and support near real time (NRT) modeling, 2) develop a “spill-response” model from an existing framework to simulate the response of water supplies in the urban watershed ecosystem to the introduction of a contaminant, 3) develop and demonstrate NRT water quality forecasting for a portion of the watershed, utilizing a tested model, and driven by inputs from a robotic monitoring network, 4) collect sediment cores and analyze patterns of contaminant deposition to the sediments of lakes within the urban watershed, and 5) demonstrate the power of the robotic monitoring data sets through limnological and process-level studies with these data. Utilization of such intensive, NRT data-gathering techniques may better enable future management policies to make informed decisions concerning ecosystem regulation. The NRT data are available to stakeholders at www.ourlake.org.
A Direct Sequence Analysis Method for Rapid Discovery of DNA Ligand Binding Sequences for Biosensor Technologies
Principal Investigators: Philip N. Borer and Mark P. McPike, Chemistry Department, Syracuse University and OrthoSystems, Inc.
Project Abstract: Nucleic acid constructs have been found that have a high affinity and specificity to biological targets, making them candidates for capture-based biosensor technologies. However, this area of biosensor development is currently unmet due to (1) the complexity of the existing nucleic acid discovery method (called SELEX) which is prone to errors and difficult to automate and (2) the expensive upfront cost and terms for licensing the SELEX platform. Here we propose a novel alternative to SELEX called the Direct Sequence Analysis (DSA) method. The DSA method will use a structurally defined library of short, variable DNA oligomers that can be rapidly screened, cloned and sequenced in a single cycle to identify DNA constructs that bind biological targets with high affinity, called ligand binding sequences (LBS). Sequences generated from these screens will be easier to characterize, cheaper to synthesize and very simple to engineer into bistable molecular sensors, termed OrthoSwitches™ or AlloSwitches™ (OrthoSystem, Inc.). In this project we aim to develop and optimize the DSA technique using polyvalent biological targets. If successful the method will be automated to allow us to create a screening platform to rapidly screen a collection of biological targets in parallel.
Development and Deployment of a Remote Observing System for Determination of Taxon-specific Phytoplankton Abundance
Principal Investigators: Gregory Boyer, Chemistry Department, SUNY-ESF and Michael R. Twiss, Great Rivers Center, Clarkson University
Project Abstract: Development of advanced water quality sensors suitable for robotic deployment is a critical need for CEEES. We propose to develop three unique sensor systems that will provide near real time information on changes in taxon-specific phytoplankton abundance. This information is important both as an estimate of ecosystem health and for the development and monitoring of remediation efforts. The first system is based on the BBE FluoroProbe and uses a combination of excitation and emission wavelengths to distinguish phytoplankton at the division level (e.g. green algae, diatoms, cyanobacteria). The second and third systems uses specific algal pigment signatures in the visible region (second system) or their fluorescence fingerprint (third system) to distinguish phytoplankton below the division level. The FluoroProbe system will be validated at the ESF testing facility and deployed on a buoy in the St. Lawrence River. The other two systems will be constructed and deployed in Onondaga Lake, Oneida Lake and/or Lake Ontario to test their ability to distinguish between benign and potentially harmful cyanobacterial blooms. All three systems have the potential to provide critical information for immediate use in management decisions and for incorporation into the existing CEEES network of water quality monitors.
An Integrated Monitoring/Modeling Framework for Assessing Human-Nature Interactions in Urbanizing Watersheds: Onondaga and Wappinger Creeks
Karin E. Limburg, Environmental and Forest Biology, SUNY-ESF; Myrna Hall, Environmental Studies, SUNY-ESF; Bongghi Hong, Environmental and Forest Biology, SUNY-ESF; Giorgos Mountrakis, Forest and Resource Engineering, SUNY-ESF; and Peter Groffman, Institute of Ecosystem Studies
Project Abstract: Urbanization and sprawl rank among the most serious threats to watershed ecosystems, water quality, and biotic integrity in much of the U.S. and elsewhere. We have been developing an integrated assessment tool that links economic activity to land use change, and land use change to changes in watershed ecological condition (“watershed health”). However, there are shortcomings with the approach that we propose to remedy within the scope of the proposed project. Specifically, we propose to improve the assessment tool by: (1) collecting advanced monitoring data with a stream and meteorological monitoring network,(2) reducing uncertainties in model prediction by incorporating the monitoring data through a state-of-the-art Bayesian estimation technique, (3) developing and incorporating a cutting-edge model that estimates impervious surfaces at 30-m resolution with high accuracy and advanced uncertainty metrics, (4) adding a hydrological sub-model with algorithms to relate land cover (including ISA) to water, sediment, and nutrient loading to streams, and (5) developing a decision support system with full capability of scenario evaluation and uncertainty analysis. Watershed managers, urban and regional planners, educators, as well as the research and business community would be among the beneficiaries as they would gain insight into decisions to support environmental sustainability.
Monitoring and controlling biofilm formation in waters: development of a platform for studying bacterial-surface interactions
Dacheng Ren, Biomedical and Chemical Engineering, Syracuse University; Yan-Yeung Luk, Chemistry, Syracuse University; Ashok Sangani, Biomedical and Chemical Engineering, Syracuse University
Project Abstract: Assessment and control of bacterial contamination in waters is critically important for public health. Whereas the planktonic (free-swimming) cells are routinely monitored, the vast majority of bacteria exist attached to solid surfaces (known as biofilms) in natural environments and water distribution systems. Hence, they are not readily detected by routine measurement. In addition, biofilm cells are more resistant to environmental stresses and disinfectants than planktonic cells, and cause serious damages to water distribution and filtering systems by microbial-induced corrosion. Thus, development of efficient and environmentally friendly anti-biofilm approaches is necessary.
To achieve this long-term objective, this work is proposed as a preliminary study to develop a platform for studying bacteria-surface interactions and preventing biofilm formation. We propose the following specific aims:
Aim #l. Synthesize alkanethiolates presenting mannitol, mannose, and brominated furanone groups.
Aim #2. Modify the surfaces of gold and stainless steel with SAMs of alkanethiolates described above. Study biofilm formation of Escherichia coli, Pseudomonas aeruginosa, and Bacillus subtilis on the engineered surfaces using confocal laser scanning microscope and imaging analysis.
Aim #3. Corroborate the results in Aim #2 by studying bacterial gene expression in contact with the surfaces.
Aim #4. Develop numerical simulations to aid in understanding the cells attachment and biofilm formation.