The Atlantic Coastal Plain aquifers and confining units of South Carolina are composed of crystalline carbonate rocks, sand, clay, silt, and gravel containing large volumes of high-quality groundwater. The aquifers have a long history of use dating back to the earliest days of European settlement in the late 1600s. Although extensive areas of some of the aquifers have or currently (2018) are experiencing groundwater-level declines from large-scale, concentrated pumping centers, large areas of the South Carolina (SC) Atlantic Coastal Plain contain substantial quantities of high-quality groundwater that currently are unused.

Groundwater use from the SC Atlantic Coastal Plain aquifers has increased during the past 70 years as the population has increased along with public supply, industrial, and agricultural water demands. While South Carolina works to increase development of water supplies in response to the population growth, the State is facing a number of unanswered questions regarding availability of future groundwater resources and the best methods to manage these important water sources. Uncertainty regarding future climate variability and related effects on groundwater recharge rates is a concern for South Carolina water managers and regulators.

A groundwater flow model of the entire SC Atlantic Coastal Plain constructed and calibrated to predevelopment through 2015 conditions is used to simulate possible future (2019-2065) groundwater conditions. The groundwater model is paired with a model of past groundwater recharge (1979-2015) that has significantly improved the understanding of recharge processes in the SC Atlantic Coastal Plain. The groundwater model simulates the entire surficial aquifer layer and includes groundwater base flow to a simulated stream network.

The groundwater recharge model is modified to incorporate possible future scenarios of groundwater recharge for the years 2019-2065. These modifications include 2 possible land use/land cover scenarios and 3 possible future scenarios of precipitation and temperature. The land use / land cover and climatic scenarios are incorporated into the groundwater recharge model to produce simulations of possible future spatially and temporally varying recharge arrays. These recharge arrays are input into the groundwater flow model, and a series of model runs are performed with the results (groundwater levels and water budgets) evaluated. Changes in groundwater levels, water budgets, and stream base flows are quantified and summarized. The modeling tools can be used to simulate alternative scenarios to evaluate their relative impact on groundwater resources of the SC Atlantic Coastal Plain.

Background: Climate change has been predicted to impact and increase the incidence of future water- and food-borne illnesses diseases, including gastrointestinal or diarrheal diseases. However, the relationship between weather/climate and gastrointestinal diseases is complex and can vary by pathogen and geographically. Variation between study and analytical methods in different settings makes between-study estimates more difficult to compare. An improved understanding of the historical relationships and sources of variation between weather and gastrointestinal diseases is critical for better predictions of the likely impacts of climate change.

Methods: This dissertation research uses a daily time series of emergency department (ED) visit data from North Carolina (2008-2015) to investigate the relationship between acute gastrointestinal (AGI) illnesses and antecedent temperature and rainfall. First, we compare multiple temperature and rainfall exposure variable definitions and constructions, including measures of relative and absolute temperature and rainfall and compare AGI incidence following heavy rain events after dry versus wet periods. Second, we use multiple statistical time series models and data mining techniques to compare the sensitivity of estimates to model type and specification. Third, we include sociodemographic, environmental, and geographic covariates, such as poverty, water supply source, and proximity to emergency departments and livestock facilities, to investigate potential effect modifiers and identify vulnerable populations or geographic variation across North Carolina.

Results & Discussion: We investigate three hypotheses. First, that AGI incidence increases with increased temperature for all-cause and bacterial diarrhea, but decreases with viral diarrhea and AGI. Second, that AGI incidence increases after heavy rain events following wet periods compared to dry periods. Third, we hypothesize that populations with increased vulnerability to AGI incidence are those with lower socioeconomic status, private well users compared to those with municipal water supply connections, and populations living closer to concentrated animal feeding operations (CAFOs). We discuss the relative risk estimates for temperature-AGI and rainfall-AGI in North Carolina and the sensitivity of these estimates to weather exposure definitions, model type and specification, and sociodemographic and environmental factors.

Diverse in both climate and topography, the southern Appalachian Mountains are prone to extreme precipitation and flooding that often threaten the socio-economically vulnerable citizens that live in this rural region. Already waterlogged from an above average month of precipitation in April, the arrival of Subtropical Storm Alberto in late May threatened residents still recovering from prior flood damage. In Polk County alone, severely damaged roadways and the effects of a deadly debris flow in an earlier storm had effectively cut off communities. Due to the weak nature of Alberto, many living along the Blue Ridge were unprepared for the rate at which the rain would fall. The ensuing flash flooding and mudslides resulted in the closure of Highway 9 and Interstate 40, destroyed homes, threatened the collapse of Lake Tahoma Dam, and claimed at least 5 lives. By the end of the storm, portions of the Blue Ridge escarpment exceeded 400% of average monthly rainfall. Despite the event resulting in precipitation totals and flooding similar to Hurricanes Frances and Ivan, western North Carolina was denied a disaster declaration by FEMA as the month long flooding was deemed as separate and distinct events. As a result, crucial roadways remain damaged or closed, hindering the ability for some of the hardest hit communities to recover. Despite being disproportionately affected by extreme precipitation and flooding events such as Alberto, citizens of rural Southern Appalachia are among the least concerned about future impacts of climate change in the country. By better addressing climate change and extremes on a regional scale, we will be more equipped to engage with rural communities and improve disaster response in the future.

The objective of this poster is to investigate the recent climate change in North and South Carolina and to study the relationship of global climate change and the regional climates in these two states. The time series of annual temperature and precipitation at the six selected weather stations in Carolinas from 1950-2017 are plotted to show the temporal trends of both variables. The drought data from these stations are also analyzed from 1950 to 2016. Additionally, decadal variations of severe weather such as tropical cyclones and tornadoes from 1950-2016 are spatially illustrated using ArcGIS software. It is noted that there is no significant trends or patterns in these data that indicate any conspicuous shifts of climates in Carolinas. However, climate change does occur and always will, and the short length of the studied period in this study may obscure the signature of climate change.

Transportation infrastructure is critical for emergency response during hazard events. Understanding vulnerabilities in a community’s road network before an event can reduce the overall impact, and can prepare emergency managers with better information for response and recovery.

An analysis performed for the Triangle region of North Carolina seeks to inform emergency managers about vulnerability with the following three products:

1. Response Drive-Times: Identifies three-, five-, and eight-minute response scenarios from fire stations in the road network.

2. Infrastructure Inundation: Calculates the number of linear miles of roadway potentially inundated within a floodway and during 100-year and 500-year flood events.

3. Critical Access and Isolation: Identifies properties that are potentially isolated from emergency response efforts due to hazards such as flooding.

The results of this type of analysis can be used to help a community and its emergency responders understand potential road connectivity issues caused by flooding and other hazards, which affect response times to neighborhoods. Ultimately, emergency managers can use this information to develop resilience strategies.

Increasing resilience can improve a community’s ability to respond to and recover from a hazard more quickly and with fewer resources. Often, the ecosystem services provided by natural landscapes can be leveraged to benefit nearby communities and reduce a community’s exposure. Identifying hazards and areas exposed to these threats are necessary beginning steps to improving resilience.

To locate areas facing potential flood hazard exposure, the National Fish and Wildlife Foundation partnered with UNC Asheville’s NEMAC to develop a coastal resilience assessment along the Carolina coast. Following a resilience framework, this assessment uses geospatial analyses and modeling to identify several coastal flood hazards and critical community assets. The results from these models will be used to explore and understand vulnerabilities, leading to potential management, mitigation, or restoration options.

Current production agriculture systems are heavily focused on yield outcomes at all costs. By shifting to regenerative farming practices (having a live root in the soil as many days as possible, always having soil covered, reducing tillage, and increasing biodiversity), however, agricultural systems worldwide could maintain or even improve yields while sequestering atmospheric carbon (C) into soil organic matter (SOM), reducing greenhouse gasses and ensuring healthy, fertile soil for future generations. Roughly 37% of the earth’s land mass (excluding Antarctica and Greenland) is agricultural land, making agriculture the largest ecosystem on the planet. Monocropping practices of traditional agriculture are inherently low in biodiversity, meaning that the worlds largest ecosystem has restricted biodiversity and will, therefore, eventually exhaust terrestrial resources and continue to rapidly move C from the land to the atmosphere. To demonstrate the effectiveness of regenerative practices at reversing these effects while simultaneously benefiting agriculture, the C sequestration potential of these practices needs to be examined.

SOM data from 491 soil sampling points from various farms throughout the coastal plains of South Carolina were compared over varying multiple-year periods between 2013 and 2017 as they transitioned from conventional to regenerative agricultural practices. 438 of the sites have undergone two years of regenerative practices, 40 sites have undergone three years, and 13 sites have undergone four years. The implementation of multispecies cover crops between cash crop rotations and the reduction or elimination of tillage over this span of time has resulted in statistically significant average increases of 0.09 (p ≤ 0.001), 0.11 (p ≤ 0.001), and 0.55 (p ≤ 0.001) SOM percentage for the two-, three-, and four-year sampling sites, respectively. When averaged out per year for each sampling group, this results in increases of 877, 1,167, and 2,731 lbs of SOM per acre per year, meaning that an average of 509, 677, and 1,584 lbs per acre per year of C sequestered from the atmosphere and deposited into the soil.

The most recent USDA Census of Agriculture (2012) reports the total cropland in SC to be 1,967,288 acres and an average farm size of 197 acres, creating potential atmospheric C sequestration of 50–156 tons per year for a single average farm, and 500,647–1,558,092 tons statewide if regenerative practices are implemented. Additionally, the rate of C sequestration appears to increase exponentially as the duration of time managed regeneratively increases, but further studies will be necessary to determine if this is real or an effect of environmental factors.

Because the rate of soil atmospheric carbon sequestration is dependent not only on land management practices but also on environmental factors such as soil texture and structure, rainfall, and temperature, there will be variability across the state. The calculations based on the coastal plains soils studied here, however, demonstrate the promising potential of regenerative farming practices to not only restore degraded biodiversity, recycle nutrients, and reduce chemical inputs, but also to sequester atmospheric C and simultaneously help reduce the effect of global climate change while creating healthy soils.

A short summary of past and present AECOM projects that assess the vulnerability of municipal assets to Sea Level Rise and recommendations for prioritizing adaptation.

This study evaluates the feasibility of using satellite precipitation data from the REDR program (CMORPH-CDR) to detect and monitor drought on a global scale from 1998 to present. Monthly and daily (running mean) Standardized Precipitation Indexes (SPI) were implemented and computed over various time scales (1-, 3-, 6-, 9-, 12-, and 24-month resp. 30-, 90-, 180-, 270-, 360-, and 720-day). Preliminary results indicated that both monthly and daily SPIs presented the same timing and area for the major droughts episodes over the continental United States as well as for selected drought events around the globe. The SPI is evaluated primarily over CONUS where long-term drought monitoring exists based on in situ data. Showcases of selected severe drought events were used for validation (1998-2004 western US drought, 2006-2007 Southeastern US drought, 2010-2012 Texas-Mexican drought, 2012 summer Midwestern US drought). Following the assessment metrics in the NIDIS Drought Task Force (DTF) Protocol, each drought product is evaluated on the basis of its ability to estimate the onset and recovery, duration and severity, probability of drought condition, and the value given at the observed period.

In this poster presentation, we focus on the Carolinas and neighboring Southern States for which we provide an assessment and evaluation of the CMORPH-CDR derived SPI and in-situ drought monitoring products such as the United State Drought Monitor (USDM), the nClimGrid derived SPI, and the WestWide Drought Tracker (WWDT) derived from PRISM (Parameter-elevation Regression on Independent Slopes Model) data. Finally, we will present an interactive visualization tool that will allow easy comparison of the results for the selected drought events with the 2006-2007 Southeastern US drought as an example.

Impacts from climate-driven hazards threaten coastal and inland communities and the ecosystem services upon which they rely. Many of these communities are densely populated, economically and culturally important, and entwined with environmentally sensitive habitats and green spaces. To better prepare for climate change, community and ecosystem vulnerability assessments are necessary to plan for and improve community resilience to climate hazard impacts.

Our Integrated Vulnerability Assessment Framework utilizes a geospatial approach to intersect vulnerability and risk through quantitative and qualitative analyses. While many vulnerability assessments focus on a single aspect of vulnerability and/or risk, our Framework identifies and develops a variety of both vulnerability and risk profiles. These can include social, physical, and environmental vulnerability, in addition to both coastal and inland risks, such as coastal flooding, sea level rise, stormwater flooding, wildfire, and erosion.

Initially implemented in the Chesapeake Bay area and since extended to Los Angeles County, California, our Framework can easily be applied to the Carolinas for a single community, statewide, or regional (Carolinas) assessments. The Carolinas are home to a diverse range of ecosystems, human populations, and climate impacts, and may benefit from an integrated assessment. Further, our Framework relies upon existing, publicly available data, such as U.S. Census Bureau data sets or the National Hurricane Center’s storm surge modeling data. Our integrated approach provides the information needed for community planners to prioritize resources and areas for climate adaptation action.

The National Centers for Environmental Information provide monthly monitoring reports of temperature and precipitation trends for the United States, including Alaska, Hawaii, and Puerto Rico. While national reports provide useful information, most people really want to know what the weather was like in their own area, usually in daily increments, and from a nearby weather station. Luckily enough, the data used to compile the national reports originate from weather stations in the Global Historical Climatology Network - Daily (GHCN-D) dataset. Every day, stations around the world report information such as temperature, precipitation, and snowfall. These values are then sent to NCEI for processing, quality control, and archiving for public dissemination. More than 15,000 of these stations are located in the United States, and we can use that data to understand what the current year looks like so far on the local scale.

To that end, scientists at the North Carolina Institute for Climate Studies have developed an interactive GIS tool to help users see how current conditions stack up against previous years, and assess how far from normal conditions really are. The spatial map built in ESRIs ArcGIS online platform depicts temperature and precipitation values color-coded by their difference from the 1981–2010 mean. Only stations with 50 or more years of complete data are used in this analysis, and any data flagged by quality control were not included. Users can then inquire about a particular station, and load up a time series of the year-to-date conditions, including days that were considered extreme in the record. Using a few simple statistical routines, weather stations across the United States can tell a climate story. We hope these visualizations help better understand the data and answer questions of how warm, cold, wet, or dry it really has been in your neck of the woods.

In October 2015, the state of South Carolina experienced a record-breaking precipitation event leading to detrimental flooding that caused 19 fatalities and over one billion dollars of damages, which has prompted researchers and resource managers to enhance their understanding of extreme precipitation. This project explored multiple satellite-derived Quantitative Precipitation Estimates (QPE) in an effort to capture historical extreme precipitation patterns and risk-prone areas in both South Carolina and the greater southeastern United States. Using NASA Earth observations and NOAA Climate Data Records, we analyzed the benefits of using short-term, high-resolution datasets to measure extreme precipitation patterns compared to surface observations. Satellite observations included NASA’s Tropical Rainfall Measuring Mission (TRMM) and Global Precipitation Measurement (GPM) mission, as well as NOAA’s Precipitation Estimation from Remotely Sensed Information using Artificial Neural Networks Climate Data Record (PERSIANN-CDR). Surface observation records were retrieved from the Global Historical Climatology Network-Daily (GHCN-D) estimates, a network of global rain gauge stations. The team highlighted areas prone to extreme precipitation with bias adjusted precipitation estimates. Results also assessed variability in precipitation measurements for recent years in an effort to integrate high- resolution QPE into regional climate resilience planning and to address spatial gaps in surface observation datasets. This project served to provide a better understanding of climate stressors for the Carolinas and to pose a discussion on effective methods of developing climate resilience practices integrated with satellite-derived. datasets

Geopolitical mapping of NC's electricity system: Toward a comprehensive decentralized energy strategy for communities
— Report/poster/infographic outlining the geopolitics of energy service providers at the NC state level
— Report/poster/infographic to be handed to each legislator outlining the specific dynamics of their district
— Report/poster/infographic for each energy service provider detailing the landscape from its point of view
— The underlying source code
— The underlying data

As per federal sustainability requirements, all DOE facilities are directed to prepare for climate change at their respective sites, which must involve ‘detailing risk’ and ‘describing actions to build resilience’. To meet this obligation, the Atmospheric Technologies Group (ATG) at the Savannah River National Laboratory (SRNL) has developed a climate projection for the DOE’s Savannah River Site (SRS) near Aiken, SC, and performed a vulnerability assessment describing the specific threat to site assets. The site activities most in danger of being impaired by climate change include the maintenance of indoor temperatures, ensuring the safety of outdoor workers, and maintaining successful operation of site cooling towers. The next phase of the work involves the formation of a climate change group comprising SRS personnel responsible for those operations, with the goal of determining the best way to mitigate the threats. A series of meetings is now ongoing to develop a concrete plan of action.