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Sankar Arumugam

Professor and University Faculty Scholar

Fitts-Woolard Hall 3321


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Date: 12/15/21 - 11/30/23
Amount: $299,543.00
Funding Agencies: National Science Foundation (NSF)

Recently released the Sixth assessment report of Intergovernmental Panel on Climate Change highlights the role of humans in warming the climate and also attribute it to the increase in the frequency of occurrence of hydroclimatic extremes. To obtain these future projections of hydroclimatic extremes, Global Climate Models (GCMs), with coarser resolutions, are typically used to develop climate projections until the end of the century. Due to continually increasing computational power, spatial resolution of GCM projections have improved a lot (around 1ï‚°), but still they are inadequate for watershed-scale (e.g., HUC8) applications. Further, historical projections of GCMs inherently have bias with observed climate. Hence, they have been bias-corrected and statistically downscaled (BCSD) and such products are available for the past CMIP runs. Existing BCSD methods (e.g., asynchronous regression) have been shown not to preserve the spatio-temporal dependency across variables due to the high dimensionality in the data. But, Artificial Intelligence (AI) techniques are highly equipped to handle high dimensional data and can preserve spatio-temporal dependency across the variables. Hence, we propose an innovative, high risk and high reward, AI-based probabilistic approach that uses Quantile Regression based Artificial Neural Network (ANN) (QR-AI) model for BCSD CMIP6 projections. The main objective of this EAGER proposal is to develop a BCSD methodology using QR-AI and apply them for recently issued CMIP6 projections to facilitate the rapid uptake of the AI methodology and BCSD products. Specifically, we will develop three BCSD data products of CMIP6 projections over the CONUS: 1) Historical simulations (1950-2014) of precipitation and temperature of GCMs; 2) Near-term (30 year) hindcasts of precipitation and temperature from relevant GCMs and 3) Near-term (30 year) projections of precipitation and temperature for four different Shared Socioeconomic Pathways.

Date: 01/01/22 - 6/30/23
Amount: $79,999.00
Funding Agencies: Tampa Bay Water

The objective of this project is to a) develop streamflow scenarios based on the precipitation and temperature scenarios under stationary conditions as well as under changing precipitation and temperature scenarios; b) run those scenarios with the rainfall-runoff model from TBW and develop streamflow scenarios for the considered precip and temp scenarios; c) use the current synthetic climate generation model and develop streamflow generation scenarios for stationary and potentially changing conditions and d) run the TBW system with the above streamflow generation scenarios (from (b) and (c)) along with current and potential demand scenarios to assess the system performance.

Date: 08/15/18 - 1/31/23
Amount: $380,219.00
Funding Agencies: National Science Foundation (NSF)

Economic development and environmental sustainability are often conflicting objectives (Rogers, 1997). Continued economic development often arises from ensuring environmental safeguards and sustainability (Rogers,1997). This Food-Water-Energy System (FEWS) study presents a synthesis on understanding the regional and global FEW impacts due to uncertain climate and development scenarios on two regions – Southeast US (SEUS) and North China Plain (NCP) – that experience contrasting settings on water and energy availability, but have similar portfolios on crop production (corn, soybeans, fruits, vegetables and cereals – wheat/rice) and water (primarily groundwater) and energy (coal/natural gas) appropriation. FEW system is complex and their nexus typically organizes under different spatial and temporal scales. For instance, pollution from agricultural runoff usually have local signature and has lesser impacts and the energy grid water issues typically organize at watershed scale. However, events triggered by large-scale climatic conditions such as multi-year droughts could impact both surface water and groundwater availability which could impact hydropower generation, cooling of power plants and irrigated and rainfed agriculture. But, it is unclear how much the climatic impacts on regional FEWS could impact global food prices and commodity flow. Similarly, federal policy changes (e.g., tax deductions for solar PV installation) could potentially make the nexus resilient, depending on the nature of FEWS, against climate variability. We intend to explore these research issues and perform a cross-regional synthesis on two regions, Southeast US and North China Plain, for improving food-energy-water system sustainability.

Date: 08/01/21 - 7/31/22
Amount: $50,000.00
Funding Agencies: National Science Foundation (NSF)

Lucas Ford will develop a geospatial model to improve stream flow prediction in ungauged and controlled basins. He will also attend the mandatory workshops/seminars at NCSA- UIUC as part of his fellowship.

Date: 08/01/17 - 7/31/22
Amount: $4,500,000.00
Funding Agencies: US Dept. of Interior (DOI)

The guiding strategy of the Southeast Climate Science Center (SE CSC) is to provide staffing and institutional support for core SE CSC mission areas. The SE CSC's mission involves supporting researchers and managers to co-produce science connected to management decisions (actionable science), coordinating logistics and communications to bring partners and the community together (within NCSU, with USGS researchers, and across the broader community) to discuss global change impacts to the DOI mission, and training the next generation (graduate students) and current managers on how to use and develop global change science.

Date: 10/01/20 - 3/31/22
Amount: $79,962.00
Funding Agencies: Tampa Bay Water

Tampa Bay Water, the largest wholesale water provider in the southeast United States, provides drinking water to its six-member governments; three cities including New Port Richey, St. Petersburg and Tampa and three counties including Hillsborough, Pasco and Pinellas. Total service population is about 2.5 million residents. Tampa Bay Water, the operating agency, has built an integrated water supply system which includes a surface water system, groundwater wells, and a seawater desalination plant. This has enabled the Tampa Bay to shift from being 100 percent reliant on groundwater to a mixture of sources with an increasing reliance on surface waters. Close monitoring of hydroclimatic variables is thus important for the agency to rotate different supply sources to meet regional demands. Examining the impact of potential hydroclimatic changes, e.g., changes in precipitation, temperature, and streamflow, on Tampa Bay water supply system (TBWSS) is critical to understand the system vulnerability and reliability under potential climate change.

Date: 07/01/21 - 12/31/21
Amount: $14,412.00
Funding Agencies: Mesa Associates, Inc.

The Sponsor's project team will need help from North Carolina State University (NCSU) to support Mesa’s Principal Investigator (PI) and the Mesa team with these preliminary assessments. Specific tasks for NCSU are summarized below: • Help and support with data analysis and site assessments, approximate storage, water flows, installed capacity, and potential energy produced. • Help and support with conceptual design and preliminary cost estimates • Help and support with the technical approach and analysis. • Help and support with the estimated cost (construction and equipment) for the sites. • Review draft and final reports

Date: 03/01/20 - 12/31/21
Amount: $59,999.00
Funding Agencies: NCSU Water Resources Research Institute

Anthropogenic nutrient loading is a critical driver of water quality throughout North Carolina and much of the world. Nutrient loading has increased over the last century due to fertilization of crops and green spaces, as well as waste from humans, pets, and livestock. The most salient outcome of nutrient loading is increased eutrophication (organic matter accumulation in surface waters), often leading to harmful algal blooms and hypoxia, which jeopardize water supplies and public recreation. As such, developing nutrient criteria and management strategies is a timely objective for state water resources managers. While sources of nutrients have been identified and many nutrient control measures have been proposed, there remains a need to quantitatively assess these sources and controls, particularly at the watershed scale. In this study, we propose a modern, data-driven approach to update our knowledge of the magnitudes of various sources and the effectiveness of various nutrient control strategies. The approach leverages large databases of water quality, hydro-meteorology, and watershed attributes, which have been developed by federal, state, and local governments over the last few decades. The approach will also leverage a sophisticated “hybrid” watershed model that combines a mechanistic representation of nutrient fate and transport within a probabilistic (Bayesian) framework where prior knowledge of loading and transport rates is updated through data-driven inference, and where uncertainty is rigorously quantified. Our project will focus on the Falls and Jordan Lake watersheds of North Carolina, for which preliminary models and data are already available. Key objectives include (1) development of an integrated geospatial database on watershed development, (2) adaptation of the hybrid watershed model to assess watershed development practices, and (3) application of the model to assess future management scenarios. Expected outcomes include quantitative guidance for developing nutrient reduction goals and watershed management strategies.

Date: 11/21/19 - 11/20/21
Amount: $24,871.00
Funding Agencies: US Geological Survey (USGS)

Global hydroclimate over the last century has been significantly altered by anthropogenic influences that arise from changes in global climate and also from local impacts stemming from man-made storage structures, increased groundwater withdrawal and land-use changes. Understanding and explaining how the spatio-temporal variability of land-surface fluxes differs in natural and human-altered watersheds is the goal of this synthesis study focusing at the global scale. For instance, annual average flow and annual total precipitation have increased during the period of 1948–1997 across the eastern United States, and the trends appear to arise primarily from the increase in autumn precipitation (Small et al., 2006). Irrigation in the U.S. high plains increases the rainfall and streamflow during the summer season in the Midwest (Kustu et al., 2011). Based on hydroclimatic observations in 100 large hydrological basins from 1901 to 2008, globally, Jaramillo and Destouni (2015) found consistent and dominant effects of increasing relative evapotranspiration from flow regulation and irrigation, and decreasing temporal runoff variability from flow regulation. Understanding the hydroclimatology and associated changes in natural/virgin (human-altered) watersheds will quantify the influence/role of changes in global hydroclimate (and local anthropogenic influences), thereby providing a perspective on the local vs global signals that impact watershed-level hydroclimate.

Date: 09/01/20 - 8/31/21
Amount: $206,058.00
Funding Agencies: National Science Foundation (NSF)

Floods impact a series of interconnected urban systems (referred to in this project as the Urban Multiplex) that include the power grid and transportation networks, surface water and groundwater, sewerage and drinking water systems, inland navigation and dams, and other system, all of which are intertwined with the socioeconomic and public health sectors. This project uses a convergent approach to integrate these multiple interconnected systems and merges state-of-the-art practices in hydrologic and hydraulic engineering; systems analysis, optimization and control; machine learning, data and computer science; epidemiology; socioeconomics; and transportation and electrical engineering to develop an Urban Flood Open Knowledge Network (UF-OKN). The UF-OKN will be built by bringing together academic and non-academic researchers from engineering, computer science, social science, and economics. The UF-OKN is envisioned to empower decision makers and the general public by providing information not just on how much flooding may occur from a future event, but also to show the cascading impact of a flood event on natural and engineered infrastructure of an urban area, so that more effective planning and decision-making can occur.

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