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DOE OSTI2019

Long-term phenology of two North American secondary cavity-nesters in response to changing climate conditions

Abstract Wildlife populations can respond to changes in climate conditions by either adapting or moving to areas with preferred climate regimes. We studied nesting responses of two bird species, western bluebird ( Sialia mexicana ) and ash-throated flycatcher ( Myiarchus cinerascens ), to changing climate conditions (i.e., rising temperatures and increased drought stress) over 21 years in northern New Mexico. We used data from 1649 nests to assess whether the two species responded to changing climate conditions through phenological shifts in breeding time or shifts in nesting elevation. We also examined changes in reproductive output (i.e., clutch size). Our data show that western bluebirds significantly increased nesting elevation over a 19-year period by approximately 5 m per year. Mean spring temperature was the best predictor of western bluebird nesting elevation. Higher nesting elevations were not correlated with hatch dates or clutch sizes in western bluebirds, suggesting that nesting at higher elevations does not affect breeding time or reproductive output. We did not observe significant changes in nesting elevation or breeding dates in ash-throated flycatchers. Nesting higher in elevation may allow western bluebirds to cope with the increased temperatures and droughts. However, this climate niche conservatism may pose a risk for the conservation of the species if climate change and habitat loss continue to occur. The lack of significant changes detected in nesting elevation, breeding dates, and reproductive output in ash-throated flycatchers suggests a higher tolerance for changing environmental conditions in this species. This is consistent with the population increases reported for flycatchers in areas experiencing dramatic climate changes.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2022

Statistical framework to assess long-term spatio-temporal climate changes: East River mountainous watershed case study

Abstract Evaluation of long-term temporal and spatial climatic change in mountainous regions is a critical challenge because of the interactive effects of multiple land and climatic factors and processes. Here we present the application of the statistical framework to the assessment of changes of climatic conditions, using data from 17 meteorological stations across the East River watershed near Crested Butte, Colorado, USA, and spanning the period from 1966 to 2021. The framework is developed based on (1) a time-series analysis of daily, monthly, and yearly averaged meteorological parameters (temperature, relative humidity, precipitation, wind speed, etc.), (2) evaluation and time series analysis of potential evapotranspiration (ET o ), actual evapotranspiration (ET), aridity index (AI), standard precipitation index (SPI) and standard precipitation-evapotranspiration index (SPEI), and (3) a temporal-spatial climatic zonation of the studied area based on the hierarchical clustering and PCA analysis of the SPEI, because the SPEI can be considered an integrative characteristic of the changes of climatic conditions. The Budyko model, with the application of the Penman–Monteith equation for the estimation of ET o , was used to determine the ET. The time series analysis of the AI is used to identify the periods with energy limited and water limited conditions. Hierarchical clustering of site locations for the three temporal segments of the SPEI showed a significant temporal-spatial shifts, indicating that dynamic climatic processes drive zonation patterns. Therefore, the watershed climatic zonation requires periodic re-evaluation based on the structural time series analysis of meteorological and water balance data.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2021

Climate Change Projection in the Twenty-First Century Simulated by NIMS-KMA CMIP6 Model Based on New GHGs Concentration Pathways

Abstract The National Institute of Meteorological Sciences-Korea Meteorological Administration (NIMS-KMA) has participated in the Coupled Model Inter-comparison Project (CMIP) and provided long-term simulations using the coupled climate model. The NIMS-KMA produces new future projections using the ensemble mean of KMA Advanced Community Earth system model (K-ACE) and UK Earth System Model version1 (UKESM1) simulations to provide scientific information of future climate changes. In this study, we analyze four experiments those conducted following the new shared socioeconomic pathway (SSP) based scenarios to examine projected climate change in the twenty-first century. Present day (PD) simulations show high performance skill in both climate mean and variability, which provide a reliability of the climate models and reduces the uncertainty in response to future forcing. In future projections, global temperature increases from 1.92 °C to 5.20 °C relative to the PD level (1995–2014). Global mean precipitation increases from 5.1% to 10.1% and sea ice extent decreases from 19% to 62% in the Arctic and from 18% to 54% in the Antarctic. In addition, climate changes are accelerating toward the late twenty-first century. Our CMIP6 simulations are released to the public through the Earth System Grid Federation (ESGF) international data sharing portal and are used to support the establishment of the national adaptation plan for climate change in South Korea.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2021

Climate Change Impacts on the South American Monsoon System and Its Surface–Atmosphere Processes Through RegCM4 CORDEX-CORE Projections

Here, we evaluate projected changes in surface water and energy balances and surface–atmosphere coupling in the South American Monsoon System (SAMS) for the end of the century (2080–2099). The analyses are based on two ensemble datasets, which follow Representative Concentration Pathway 8.5 in the future period, and cover four subdomains (Northern and Southern—NAMZ and SAMZ—Amazon, La Plata Basin—LPB, and Southern Southeast Brazil—SSB). One ensemble consists of three Global Climate Models (HadGEM2-ES, MPI-ESM-MR and NorESM1-M), while the other consists of their dynamically downscaled version at 25 km horizontal grid spacing using Regional Climate Model version 4 (RegCM4). As both ensembles are able in reproducing the annual cycle of the components of the surface water and energy balances in the present climate, they can be used in the study of future climate. During the wet season (November–March), both ensembles project a decrease in precipitation over NAMZ and SAMZ (an exception is RegCM4 that projects a slight increase in SAMZ), and an increase across the LPB and SSB. These changes do not cause retreat or expansion of the monsoon area over the continent, which is similar to the present climate (1995–2014). For the wet season, the ensembles are in line with the presence of a strong surface–atmosphere coupling in LPB and SSB, weak coupling in SAMZ and very weak coupling in NAMZ. For future climate, the coupling is even weaker in NAMZ, which may be a driver for the negative changes in precipitation. For the other subdomains, while the ensembles project similar signals of precipitation changes, they disagree with the surface-atmosphere coupling highlighting the uncertainties in future climate.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2023

Urbanization effects on the spatial patterns of spring vegetation phenology depend on the climatic background

Cities have been considered ideal surrogates for evaluating ecological responses to climate warming. Although research has revealed that the urban heat island effect is not the only determinant that drives the rural-urban difference in spring phenology, limited attempts further explore the effect of complex interactions between urbanization and climates on the start of the season (SOS). Here, we employed the percentage of impervious surface area as an indicator of urbanization levels, incorporating the urban heat island (UHI) effect and climates to decipher the multiple effects on the temporal shift in SOS. Our results suggest that urbanization, the UHI effect, and climates jointly drive the phenological timing in cities. Further, the SOS is highly linearly correlated with urbanization levels and UHI effects (p<0.001) in the zones with warm and humid climates, whereas relatively warmer, cooler, or arid climates break down the linearity. Geographically, the SOS is north-south symmetrical for the rural-urban ecosystem at the national scale, which initiates at the mid-latitudes (around 30 °N, 67.58 DOY ± 2.23 days) first and then towards the low (around 20 °N, 105.25 DOY ± 1.31 days) and high-latitudes (45 °N, 123.01 DOY ± 1.45 days). Chilling accumulation and spring temperature jointly contribute to this phenomenon. As the UHI effect is similar to the projected global warming in the future, understanding the phenological responses to urbanization in various climates is insightful for evaluating the impact of future warming on plants' phenological behavior in the global ecosystem.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2024

Methodology to evaluate design modifications intended to eliminate frosting and high discharge temperatures in air-source heat pumps (ASHPs) in cold climates

Air-source heat pumps (ASHPs) operating in cold climates experience problems with frosting and high refrigerant temperatures. These problems increase energy consumption, and their severity depends on the climatic conditions. In the present paper, a methodology for identifying the prevailing problem between frosting and high discharge temperatures is presented. Three performance indices, the frosting index (FI), the discharge index (DI), and the total loss index (TLI), are proposed to quantify the impacts of frosting and high discharge temperatures on the annual performance of ASHPs in different climatic conditions. The FI and DI show which problem (frosting or high discharge temperature) dominates, and the TLI indicates the combined effect of frosting and high discharge temperatures on the performance of an ASHP. A thermodynamic model of an ASHP coupled with the TRNSYS building simulation tool is used to estimate the performance of an ASHP and the proposed loss indices to estimate the impact of both frosting and high discharge temperatures for 45 cities in Canada. The results can be extended to other parts of the world that experience similar climatic conditions The results reveal that in cities in ASHRAE climatic zones 5 and 6 (classified as cold regions) where the ambient air temperatures are predominantly between -15 °C to 6 °C, ASHPs are heavily impacted by frosting. The problem of high discharge temperatures in ASHPs is predominant in cities in climate zones 7 and 8 (classified as very cold and subarctic regions) where the temperatures are frequently below -20 °C in winter. Among the cities considered, St. John, NL has the highest fraction of heating hours experiencing frosting (90 %), where the annual increase in energy consumption due to frosting is 13.5 % of the annual heating energy consumption. The highest annual increase in energy consumption due to high discharge temperatures is in Isachsen, NU (zone 8), where the increase is 30 % of the annual heating energy consumption. Based on the proposed indices, another index called the performance gain index (PGI) is created, which can be used as a first step to assess the energy-saving potential of design modifications applied to ASHPs to solve the problems of frosting and high discharge temperatures. The PGI will aid in developing climate specific ASHPs. One possible design modification is the use of a two-stage ASHP with an economizer. It is observed that the two-stage ASHP with economizer can mitigate high discharge temperatures and improve performance in very cold and subarctic regions (zones 7 and 8). However, it is not as beneficial in zones 5 and 6, where the impact of high discharge temperatures on performance is minimal and frosting dominates. Finally, a case study, using the PGI to evaluate the economic and environmental effectiveness of a two-stage ASHP with economizer is presented for the city of Saskatoon.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

DOE OSTI2025

Harvest legacies and climate change interact to shape forest structure and biomass through time

Forest structural change driven by climate trends has been observed worldwide and is expected to increase in the future. Management of forest structure has been an important tool for mitigating the impacts of climate change but forest structure may shift independently of management goals as it interacts with climate change. Here, we investigated the long-term impacts of harvest-based management strategies on structure and resistance to climate-induced biomass loss using a process-based ecosystem model for a midwestern USA hardwood forest. We identified aboveground biomass loss events and compared the cumulative number of these events following a five-year period of active management under four management strategies and two climate change scenarios. Management legacy had the clearest impact on climate-driven biomass loss over the mid-term (∼25 years) with the shelterwood scenario experiencing no loss events during this period. However, by the end of the century legacy effects faded and climate change severity became the driver of differences as greater warming scenarios experienced twice the loss events, and end-of-century loss events were 3–10 times more frequent than mid-century events. We found that while structure was distinct among harvest scenarios through the mid-century, differences were negligible by the end-of-century; identical to when management correlated with loss event frequency. Here, we found that loss events were preceded by a drop in precipitation two years prior, while no specific forest structure preceded a loss event. However, the structures preceding a biomass loss event were distinct across different legacies, implying additional influences of past management.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2023

Vegetation-induced asymmetric diurnal land surface temperatures changes across global climate zones

Unprecedented global vegetation greening during past decades is well known to affect annual and seasonal land surface temperatures (LST). However, the impact of observed vegetation cover change on diurnal LST across global climatic zones is not well understood. In this study, using global climatic time-series datasets, we investigated the long-term growing season daytime and nighttime LST changes globally and explored associated dominant contributors including vegetation and climate factors including air temperature, precipitation, and solar radiation. Results revealed asymmetric growing season mean daytime and nighttime LST warming (0.16 °C/10a and 0.30 °C/10a, respectively) globally from 2003 to 2020, as a result, the diurnal LST range (DLSTR) declined at 0.14 °C/10a. The sensitivity analysis indicated the LST response to changes in LAI, precipitation, and SSRD mainly concentrated during daytime instead of nighttime, however, which showed comparable sensitivities for air temperature. Combining the sensitivities results and the observed LAI and climate trends, we found rising air temperature contributes to 0.24 ± 0.11 °C/10a global daytime LST warming and 0.16 ± 0.07 °C/10a nighttime LST warming, turns to be the dominant contributor to the LST changes. Increased LAI cooled global daytime LST (–0.068 ± 0.096 °C/10a) while warmed nighttime LST (0.064 ± 0.046 °C/10a); hence LAI dominates declines in DLSTR trends (–0.12 ± 0.08 °C/10a), despite some daynight process variations across climate zones. In Boreal regions, reduced DLSTR was due to nighttime warming from LAI increases. In other climatic zones, daytime cooling, and DLSTR decline, was induced by increased LAI. Biophysically, the pathway from air temperature heats the surface through sensible heat and increased downward longwave radiation during day and night, while the pathway from LAI cools the surface by enhancing energy redistribution into latent heat rather than sensible heat during the daytime. These empirical findings of diverse asymmetric responses could help calibrate and improve biophysical models of diurnal surface temperature feedback in response to vegetation cover changes in different climate zones.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2023

Estimating Future Surface Water Availability Through an Integrated Climate‐Hydrology‐Management Modeling Framework at a Basin Scale Under CMIP6 Scenarios

Abstract Climate change and increasing water demand due to population growth pose serious threats to surface water availability. The biggest challenge in addressing these threats is the gap between climate science and water management practices. Local water planning often lacks the integration of climate change information, especially with regard to its impacts on surface water storage and evaporation as well as the associated uncertainties. Using Texas as an example, state and regional water planning relies on the use of reservoir “Firm Yield” (FY)—an important metric that quantifies surface water availability. However, this existing planning methodology does not account for the impacts of climate change on future inflows and on reservoir evaporation. To bridge this knowledge gap, an integrated climate‐hydrology‐management (CHM) modeling framework was developed, which is generally applicable to river basins with geographical, hydrological, and water right settings similar to those in Texas. The framework leverages the advantages of two modeling approaches—the Distributed Hydrology Soil Vegetation Model (DHSVM) and Water Availability Modeling (WAM). Additionally, the Double Bias Correction Constructed Analogues method is utilized to downscale and incorporate Coupled Model Intercomparison Project Phase 6 GCMs. Finally, the DHSVM simulated naturalized streamflow and reservoir evaporation rate are input to WAM to simulate reservoir FY. A new term—“Ratio of Firm Yield” (RFY)—is created to compare how much FY changes under different climate scenarios. The results indicate that climate change has a significant impact on surface water availability by increasing reservoir evaporation, altering the seasonal pattern of naturalized streamflow, and reducing FY.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2022

Predicting the effects of climate change on the cross-scale epidemiological dynamics of a fungal plant pathogen

The potential for climate change to exacerbate the burden of human infectious diseases is increasingly recognized, but its effects on infectious diseases of plants have received less attention. Understanding the impacts of climate on the epidemiological dynamics of plant pathogens is imperative, as these organisms play central roles in natural ecosystems and also pose a serious threat to agricultural production and food security. We use the fungal ‘flax rust’ pathogen (Melampsora lini) and its subalpine wildflower host Lewis flax (Linum lewisii) to investigate how climate change might affect the dynamics of fungal plant pathogen epidemics using a combination of empirical and modeling approaches. Our results suggest that climate change will initially slow transmission at both the within- and between-host scales. However, moderate resurgences in disease spread are predicted as warming progresses, especially if the rate of greenhouse gas emissions continues to increase at its current pace. These findings represent an important step towards building a holistic understanding of climate effects on plant infectious disease that encompasses demographic, epidemiological, and evolutionary processes. A core result is that neglecting processes at any one scale of plant pathogen transmission may bias projections of climate effects, as climate drivers have variable and cascading impacts on processes underlying transmission that occur at different scales.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2019

A round Earth for climate models

Sunlight drives the Earth’s weather, climate, chemistry, and biosphere. Recent efforts to improve solar heating codes in climate models focused on more accurate treatment of the absorption spectrum or fractional clouds. A mostly forgotten assumption in climate models is that of a flat Earth atmosphere. Spherical atmospheres intercept 2.5 W·m −2 more sunlight and heat the climate by an additional 1.5 W⋅m −2 globally. Such a systematic shift, being comparable to the radiative forcing change from preindustrial to present, is likely to produce a discernible climate shift that would alter a model’s skill in simulating current climate. Regional heating errors, particularly at high latitudes, are several times larger. Unlike flat atmospheres, constituents in a spherical atmosphere, such as clouds and aerosols, alter the total amount of energy received by the Earth. To calculate the net cooling of aerosols in a spherical framework, one must count the increases in both incident and reflected sunlight, thus reducing the aerosol effect by 10 to 14% relative to using just the increase in reflected. Simple fixes to the current flat Earth climate models can correct much of this oversight, although some inconsistencies will remain.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2021

Potential ecological impacts of climate intervention by reflecting sunlight to cool Earth

As the effects of anthropogenic climate change become more severe, several approaches for deliberate climate intervention to reduce or stabilize Earth’s surface temperature have been proposed. Solar radiation modification (SRM) is one potential approach to partially counteract anthropogenic warming by reflecting a small proportion of the incoming solar radiation to increase Earth’s albedo. While climate science research has focused on the predicted climate effects of SRM, almost no studies have investigated the impacts that SRM would have on ecological systems. The impacts and risks posed by SRM would vary by implementation scenario, anthropogenic climate effects, geographic region, and by ecosystem, community, population, and organism. Complex interactions among Earth’s climate system and living systems would further affect SRM impacts and risks. We focus here on stratospheric aerosol intervention (SAI), a well-studied and relatively feasible SRM scheme that is likely to have a large impact on Earth’s surface temperature. We outline current gaps in knowledge about both helpful and harmful predicted effects of SAI on ecological systems. Desired ecological outcomes might also inform development of future SAI implementation scenarios. In addition to filling these knowledge gaps, increased collaboration between ecologists and climate scientists would identify a common set of SAI research goals and improve the communication about potential SAI impacts and risks with the public. Without this collaboration, forecasts of SAI impacts will overlook potential effects on biodiversity and ecosystem services for humanity.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2022

Characterizing and quantifying uncertainty in projections of climate change impacts on air quality

Climate change can aggravate air pollution, with important public health and environmental consequences. While major sources of uncertainty in climate change projections - greenhouse gas (GHG) emissions scenario, model response, and internal variability - have been investigated extensively, their propagation to estimates of air quality impacts has not been systematically assessed. Here, we compare these uncertainties using a coupled modeling framework that includes a human activity model, an Earth system model of intermediate complexity, and a global atmospheric chemistry model. Uncertainties in projections of U.S. air quality under 21st century climate change are quantified based on a climate-chemistry ensemble that includes multiple initializations, representations of climate sensitivity, and climate policy scenarios, under constant air pollution emissions. We find that climate-related uncertainties are comparable at mid-century, making it difficult to distinguish the impact of variations in GHG emissions on ozone and particulate matter pollution. While GHG emissions scenario eventually becomes the dominant uncertainty based on the scenarios considered, all sources of uncertainty are significant through the end of the century. The results provide insights into intrinsically different uncertainties in projections of air pollution impacts and the potential for large ensembles to better capture them.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2019

Climatic impact, future biomass production, and local adaptation of four switchgrass cultivars

Abstract Previous studies have shown that switchgrass has a wide range of genetic variation and that productivity is linked to local adaptation to the location of origin for many cultivars. In this meta‐analysis, we compiled and analyzed 900 observations associated with 41 field trials for four switchgrass cultivars (two lowlands, Alamo and Kanlow, and two uplands, Cave‐In‐Rock and Shelter). This extensive dataset and machine learning were used to identify the most influential variables impacting switchgrass productivity, to search for evidence of local adaptation to each cultivar's location of origin, and to predict change in productivity under future climate for each cultivar. In general, variables associated with climate and management are more important predictors of productivity relative to soil variables. Three climatic variables, annual mean temperature, annual precipitation, and precipitation in the wettest month, are identified as key environmental variables for productivity of all cultivars. Productivity under future climate (2041–2060) is predicted to stay stable for all cultivars relative to the prediction under current climate (1986–2005) across all trial locations and over a 20‐year simulation period. However, the productivity of each cultivar varies from location to location and from year to year, although productivity varies more between locations than between years. Additionally, we observe shifts in the most productive cultivar at the local field scale depending on the combination of management practice and climates. The shape of the relationship between productivity and the annual mean temperature relative to the cultivar's location of origin is a bell‐shaped curve for Kanlow, Cave‐in‐Rock, and Shelter, indicative of local adaptation. Identifying influential environmental variables and their relationships to productivity with respect to cultivar's location of origin help predicting productivity on the local field scale, and will help with the biofuel production planning through the selection of suitable cultivars for different locations under climate changes.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2022

Politics of problem definition: Comparing public support of climate change mitigation policies using machine learning

Public support is a key contributor to successful policy adoption and implementation. Given the urgency of climate change mitigation, scholars have explored various determinants that affect public support for climate change mitigation policy. However, the relative decisiveness of these factors in shaping public support is insufficiently examined. Therefore, we deploy interpretable machine learning to understand which factors, among many previously investigated, are most decisive for structuring public support for various climate change mitigation policies. In this paper, we particularly look at the decisiveness of problem definition for shaping public support among various factors. Using U.S national survey data, we find that how individuals define the issue of climate change is more decisive for structuring public support for promoting renewable energy and regulating pollutants to mitigate the risks associated with climate change. However, the results also indicate that the most decisive factors associated with public support vary depending on the types of mitigation policy. Here, we conclude that different strategies should be utilized to increase public support for various climate change mitigation policy options. Our findings contribute to a scholarly understanding of the specific politics of problem definition in the context of environmental and climate change policy.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2018

Existing Climate Change Will Lead to Pronounced Shifts in the Diversity of Soil Prokaryotes

Soil bacteria are key to ecosystem function and maintenance of soil fertility. Leveraging associations of current geographic distributions of bacteria with historic climate, we predict that soil bacterial diversity will increase across the majority (~75%) of the Tibetan Plateau and northern North America if bacterial communities equilibrate with existing climatic conditions. This prediction is possible because the current distributions of soil bacteria have stronger correlations with climate from ~50 years ago than with current climate. This lag is likely associated with the time it takes for soil properties to adjust to changes in climate. The predicted changes are location specific and differ across bacterial taxa, including some bacteria that are predicted to have reductions in their distributions. These findings illuminate the widespread potential of climate change to influence belowground diversity and the importance of considering bacterial communities when assessing climate impacts on terrestrial ecosystems.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2020

Climate mediates continental scale patterns of stream microbial functional diversity

Understanding the large-scale patterns of microbial functional diversity is essential for anticipating climate change impacts on ecosystems worldwide. However, studies of functional biogeography remain scarce for microorganisms, especially in freshwater ecosystems. Here we study 15,289 functional genes of stream biofilm microbes along three elevational gradients in Norway, Spain and China. We find that alpha diversity declines towards high elevations and assemblage composition shows increasing turnover with greater elevational distances. These elevational patterns are highly consistent across mountains, kingdoms and functional categories and exhibit the strongest trends in China due to its largest environmental gradients. Across mountains, functional gene assemblages differ in alpha diversity and composition between the mountains in Europe and Asia. Climate, such as mean temperature of the warmest quarter or mean precipitation of the coldest quarter, is the best predictor of alpha diversity and assemblage composition at both mountain and continental scales, with local non-climatic predictors gaining more importance at mountain scale. Under future climate, we project substantial variations in alpha diversity and assemblage composition across the Eurasian river network, primarily occurring in northern and central regions, respectively. We conclude that climate controls microbial functional gene diversity in streams at large spatial scales; therefore, the underlying ecosystem processes are highly sensitive to climate variations, especially at high latitudes. This biogeographical framework for microbial functional diversity serves as a baseline to anticipate ecosystem responses and biogeochemical feedback to ongoing climate change.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2018

Impacts of Future Climate-Driven Runoff on Six County WWT Facilities in New Jersey

The occurrence of extreme storms and associated flood hazards has increased in most regions in recent decades (Groisman et al. 2005, Alexander et al. 2006, Hegerl et al. 2011, Min et al. 2011). Extensive data on weather extremes since 1910 kept by the National Oceanic and Atmospheric Administration (NOAA)’s National Climatic Data Center have shown an increasing trend (reaching more than 20%) in U.S. one-day extreme precipitation events. This trend is expected to continue in the future, with likely intensification of heavy precipitation events (Kunkel et al. 2010, Westra et al. 2013). Recently, Argonne has performed dynamic downscaling from global climate model (GCM) projections with high-resolution regional climate model, Weather Research and Forecasting (WRF) and projected future climate conditions for the middle of century (2035-2064). For this project, we incorporated our future climate projections into our hydrological modeling to evaluate potential effects of changing climate on streamflow near the six county WWT facilities in New Jersey to improve our understanding of climate-driven precipitation impacts and use this information to inform the potential risk of precipitation-affected infrastructures. The information for the future projected hydrological flow discharges was also provided to support a storm surge study. The study was expanded later to quantify likelihood of river discharges near WWT facilities with a statistical approach and informed the flood risk contributed by the river discharges.

54 ENVIRONMENTAL SCIENCES↗