VTechWorks Repository :: Browsing by Author "Easton, Zachary M."

Browsing by Author "Easton, Zachary M."

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Artificial sinks to treat legacy nutrients in agricultural landscapes
Bock, Emily; Stephenson, Stephen Kurt; Easton, Zachary M. (2019-06-05)
Legacy nutrients introduce a critical time lag between changes in nutrient application or implementation of best management practices (BMPs) and observable reductions in loads delivered to downstream waters. Nitrogen and phosphorus leached through soils into groundwater may take decades to eventually be discharged to surface waters and, consequently, often prevent the attainment of water quality improvement goals. For example, the National Resource Council has cautioned that in the Chesapeake Bay watershed legacy nutrients, particularly nitrogen (N), could delay achievement of nutrient load reductions needed to meet Total Maximum Daily Load (TMDL) requirements.. Groundwater discharge transporting legacy N has been identified specifically as a significant nutrient source to the Bay. Unfortunately, most existing BMPs cannot remediate these nutrient reservoirs and the Chesapeake Bay Program has not active policy to address legacy nutrients; better management options are needed...
Assessing Green Infrastructure Needs in Hampton Roads, Virginia and Identifying the Role of Virginia Cooperative Extension
Robinson, Daniel J. (Virginia Tech, 2018-08-08)
The Hampton Roads region of southeast Virginia is largely defined by its abundant water resources. These water resources are also a source of unique issues for the region. Specifically, water quality challenges related to the Chesapeake Bay and recurrent flooding are the major concerns. Green infrastructure (GI) has emerged in recent years as an alternative to traditional stormwater conveyance and detention focused systems. GI practices focus on integrating infiltration, evapotranspiration, and other components of the water cycle into more conventional stormwater management systems. These systems provide several positive benefits, including local water quality and quantity control, community revitalization, and various public health benefits. In addition, GI implementation has seen strong levels of support from the Cooperative Extension System, with Extension faculty and staff around the U.S. supporting local municipalities through GI research, promotion, and program development. Despite widespread interest, GI has been slow to be adopted due to various barriers to its implementation. This study sought to identify the major barriers to the implementation of GI practices in Hampton Roads by conducting a needs assessment. Municipal stormwater staff were invited to participate in an online survey aimed at identifying the most significant barriers in the region. At the same time, local staff with Virginia Cooperative Extension (VCE) were interviewed to explore their potential to become involved in promoting GI adoption in Hampton Roads. Survey respondents and interview participants found common ground in identifying costs, funding, and maintenance issues as the most significant barriers to GI implementation in Hampton Roads. In addition, VCE staff were found to be well suited to support widespread GI adoption in the region, having familiarity with the GI concept and access to unique resources in the form of knowledgeable Master Gardener volunteers and connections to Virginia Tech. Recommendations for VCE involvement in promoting GI in Hampton Roads include conducting cost studies, developing and hosting maintenance training programs, and taking advantage of partnerships to identify and obtain funding from diverse sources. By focusing on these widely acknowledged challenges at the regional scale, VCE can support GI implementation throughout all of Hampton Roads.
Assessing the Effects of Climate Change on Water Quantity and Quality in an Urban Watershed Using a Calibrated Stormwater Model
Alamdari, Nasrin; Sample, David J.; Steinberg, Peter; Ross, Andrew C.; Easton, Zachary M. (MDPI, 2017-06-27)
Assessing climate change (CC) impacts on urban watersheds is difficult due to differences in model spatial and temporal scales, making prediction of hydrologic restoration a challenge. A methodology was developed using an autocalibration tool to calibrate a previously developed Storm Water Management Model (SWMM) of Difficult Run in Fairfax, Virginia. Calibration was assisted by use of multi-objective optimization. Results showed a good agreement between simulated and observed data. Simulations of CC for the 2041–2068 period were developed using dynamically downscaled North American Regional CC Assessment Program models. Washoff loads were used to simulate water quality, and a method was developed to estimate treatment performed in stormwater control measures (SCMs) to assess water quality impacts from CC. CC simulations indicated that annual runoff volume would increase by 6.5%, while total suspended solids, total nitrogen, and total phosphorus would increase by 7.6%, 7.1%, and 8.1%, respectively. The simulations also indicated that within season variability would increase by a larger percentage. Treatment practices (e.g., bioswale) that were intended to mitigate the negative effects of urban development will need to deal with additional runoff volumes and nutrient loads from CC to achieve the required water quality goals.
Basin-scale spatiotemporal analysis of hydrologic floodplain connectivity
McCann, David Michael (Virginia Tech, 2014-05-30)
Floodplain inundation often provides water quality benefits by trapping sediment and biogeochemically transforming other pollutants. Hydrologic floodplain connectivity is a measure of water exchanges and interactions between the main channel and the floodplain via surface (inundation) and subsurface (groundwater) connections. Using an automated model combining GIS and numerical analysis software, this study examined floodplain inundation patterns and measured floodplain connectivity for the Mahantango Creek watershed (Pennsylvania, USA). Connectivity was quantified by developing a metric that included inundation area and duration. Long-term hydrographs at each reach in the watershed were developed via QPPQ (Flow-Percentile-Percentile-Flow) methodology using regional regression analysis to calculate the ungauged flow duration curves (FDC). Inundation area (normalized to stream length) was found to increase with drainage area, suggesting larger streams have more area available for biogeochemical activity. Annual connectivity increased with drainage area, suggesting larger streams, having higher connectivity, should be the focus of individual reach restoration projects due to higher potential for water quality benefits. Across the watershed as a whole, however, the total annual connectivity across first order streams was greater than higher order streams, suggesting the collection of small streams in a watershed may have a stronger effect on outlet water quality. Connectivity was consistently higher during the non-growing season, which was attributed to higher flows. Despite higher connectivity during the non-growing season, increased floodplain biological activity may be negated by low temperatures, reducing microbial activity. Correlations between land use and connectivity were also found, emphasizing dynamics between flow, channel morphology, and floodplain inundation.
Biochar and pH as Drivers of Greenhouse Gas Production in Denitrification Systems
Davis, James Martin IV (Virginia Tech, 2016-01-05)
Nitrous oxide (N2O) is a greenhouse gas (GHG) with 300 times the radiative forcing in the atmosphere of carbon dioxide (CO2), and has recently become a subject of great concern because the nitrogen (N) fertilizers which have been necessary to increase agricultural productivity have also dramatically increased N2O emissions from agroecosystems. Many N control practices have been suggested and implemented in agroecosystems, but their ability to simultaneously remove reactive N from the environment and prevent the production of N2O is, at best poorly understood. The goal of this work is to characterize environmental controls on production of N2O in denitrifying bioreactors. The review portion of this work first discusses the geologic history of the N cycle, how its past and present processes differ, and how it is being affected by human activity. It then explores the N cycle's biochemical pathways, reviews the controls for each of its steps, and discusses the environmental drivers of these controls. The review closes with a discussion of environmental N management strategies. The experimental portion of this work further explores these concepts by observing how biochar amendment and the modification of pH affect N2O production in the denitrification pathway in denitrifying bioreactors. Both pH and biochar have previously been shown to affect N2O production and many N management practices utilize biochar or manipulate pH to increase N retention. The objectives of the experiment were to: 1) Examine headspace N2O concentration in sealed, biochar-amended, denitrifying bioreactors; 2) Determine if the effects of pH on N2O production differ in biochar-amended systems versus controls (under acidic, unbuffered, and buffered conditions); 3) Quantify key denitrification genes (nirK, nirS, nosZ) in each treatment combination. Experimental results showed biochar treatment to significantly increase N2O emissions, a result which runs contrary to most, but not all studies regarding its effects on N2O production. Differences between treatments decreased with increasing pH levels. Biochar did not exhibit significant effects on individual denitrification genes, but it did show influence on the ratios of their populations. On the other hand, pH was found to have significant effects on nirS and nosZ populations. Differences in N2O production between biochar and controls were thus explained by biochar's chemical effects, likely its ability to increase denitrification activity. Developing an understanding of the mechanisms behind these differences will require using a combination of isotope tracing, enzyme assays, and mass balance approaches. Future microbial work in biochar-amended systems should attempt to characterize differences in gene expression, overall community structure, and long-term population trends in the genes of interest. The combination of these approaches should allow researchers to better predict where N2O production will occur and develop strategies to mitigate it while simultaneously increasing food production to meet the demands of a growing population.
Biotic and Abiotic Remediation of Acetaminophen with Woodchip and Biochar-amended Woodchip Adsorbents
Wade, James Patrick (Virginia Tech, 2015-11-13)
Pharmaceuticals and personal care products found in the environment pose a significant hazard to human and ecosystem health. While there has been significant work on the fate and remediation of pharmaceuticals and personal care products in wastewater treatment, relatively little work has explored the fate, transport and remediation of these compounds in non-point source input. This is concerning given the increasing use of pharmaceuticals in livestock production and wastewater treatment derived biosolids frequently applied to land. These experiments aimed to quantify the abiotic adsorption and biotic transformation and uptake potential of woodchips and biochar-amended woodchips as a potential sorbent strategy for diffuse acetaminophen (ACT) pollution. Batch reactions were created in triplicate, supplied with 5 mM ACT, and analyzed over an eight hr period using ultraviolet spectrophotometry (298 nm). Ultraviolet absorbance readings for each time step then were compared to standard curves and solution ACT concentration was determined. Decreases in ACT from initial concentrations were the result of either abiotic and/or biotic. Overall, the woodchips and biochar-amended woodchips showed similar removal efficiency (16-21% of initial concentration). Whole model ANOVA analysis showed biologic activity having no significant effect on ACT solution concentration. However, within group ANOVA comparison showed significant differences between abiotic and biotic WC and abiotic and biotic WC treatments (controlling for media). Thus, the media effect could have masked the effect of biology on ACT removal. Species capable of degrading ACT exist and further study into their ability to grow and survive on these sorbents requires further work.
Brokered Alignment of Long-Tailed Observations (BALTO) Applications in Geoscience
Stamps, D. Sarah; Gallagher, James; Peckham, Scott; Sheehan, Anne; Potter, Nathan; Stoica, Maria; Njinju, Emmanuel A.; Fulker, David; Neumiller, Kodi; Easton, Zachary M.; White, Robin R.; Fuka, Daniel R. (2019-06-13)
Driven by data-rich use cases that span geodesy, geodynamics, seismology, and ecohydrology, the BALTO project enables brokered access to diverse geoscience data, including data that have been collected/organized by individual scientists in novel or unusual forms, also known as “long-tail” datasets. In BALTO, “brokering” means Web services that match diverse data-usage needs with heterogeneous types of source-data. This matching addresses form and semantics, which includes protocols, data structures, encodings, units of measure, variable names, and sampling meshes. The BALTO broker employs an extensible hub-and-spoke architecture: its hub will combine well-established, open-source, data-as-service software (from OPeNDAP) with the Geoscience Standard Names (GSN) to establish canonical representations for brokered datasets; each spoke—called an accessor—comprises (source-specific) data-access software along with metadata mappings that yield GSN-compliant variable names.
Brokered Alignment of Long-Tailed Observations (BALTO) Applications in Geoscience
Stamps, D. Sarah; Gallagher, James; Peckham, Scott; Sheehan, Anne; Potter, Nathan; Stoica, Maria; Njinju, Emmanuel A.; Fulker, David; Neumiller, Kodi; Easton, Zachary M.; White, Robin R.; Fuka, Daniel R. (2019-07-17)
The Internet of Things (IoT), interconnection of computing devices embedded in everyday objects, has given geo-data scientists access to quickly growing numbers of devices for sensing; at costs no longer requiring hardware grants to access. The BALTO project has realized the importance of these growing sensor networks and has been working to integrate these sensors that can be combined into sustainable and synergistic research and education programs, from K-16 through senior researchers, centered on real-time monitoring and analytics of coupled ecosystems. BALTO takes advantage of the OpenSource Long-Range communication protocol (LoRa) to connect sensors to EarthCube Architectures.
Challenges and Opportunities for Denitrifying Bioreactors in the Mid-Atlantic
Bock, Emily (Virginia Tech, 2018-01-18)
Sustaining the global population depends upon modern agricultural practices reliant on large inputs of nitrogen (N) fertilizer, but export of excess N from agroecosystems has negative environmental consequences, such as accelerated eutrophication and associated water quality degradation. The challenges posed by diffuse and widespread nutrient pollution in agricultural drainage waters necessitate cost-effective, adaptable, and reliable solutions. In this context, enhanced denitrification approaches developed over the last several decades have produced denitrifying bioreactors that harness the ability of ubiquitous soil microorganisms to convert bioavailable N into inert N gas, thereby removing bioavailable N from an ecosystem. Denitrifying bioreactors are edge-of-field structures that consist of organic carbon substrate and support the activity of denitrifying soil bacteria that remove N from intercepted nutrient-enriched drainage waters. The potential to improve bioreactor performance and expand their application beyond the Midwest to the agriculturally significant Mid-Atlantic region was investigated with a three-pronged approach: 1) a pilot study investigating controls on N removal, 2) a laboratory study investigating controls on emission of greenhouse gases nitrous oxide (N2O), methane (CH4), and carbon dioxide (CO2), and 3) a field study of one of the first denitrifying bioreactors implemented in the Atlantic Coastal Plain. The pilot and laboratory studies tested the effect of amending woodchip bioreactors with biochar, an organic carbon pyrolysis product demonstrated to enhance microbial activity. The pilot-scale study provides evidence that either hardwood- of softwood-feedstock biochar may increase N removal in woodchip bioreactors, particularly under higher N loading. The results from the laboratory experiment suggest the particular pine-feedstock biochar tested may induce greater greenhouse gas emissions, particularly of the intermediate product of denitrification and potent GHG nitrous oxide. The field study evaluated performance of a biochar-amended woodchip bioreactor installed on a working farm. Two years of monitoring data demonstrated that the bioreactor successfully removed N from drainage waters, but at relatively low rates constrained by low N loading that occurred in the absence of fertilizer application during continuous soy cropping at the site (10.0 kg NO3--N ha-1 yr-1 or 4.86 g NO3- -N m-3 d-1 on the basis of bed volume reached the bioreactor.) Removal rates averaged 0.41 g m-3 d-1 (8.6% removal efficiency), significantly lower than average rates in systems receiving greater N loading in the Midwest, and more similar to installations in the Maryland Coastal Plain. Greenhouse gas fluxes were within the range reported for other bioreactors, and of the N removed an average of only 0.16% was emitted from the bed surface as N2O. This case study provides useful measurements of bioreactor operation under low N loading that informs the boundaries of bioreactor utility, and may have particular regional relevance. The pilot and field studies suggest that wood-based biochars may enhance N removal and may not produce problematic quantities of greenhouse gases, respectively. However, the laboratory study raises the need for caution when considering the costs and benefits amending woodchip bioreactors with biochar and accounting for the effect on greenhouse gas emissions in this calculation, because the tested pine biochar significantly increased these emissions.
The Chesapeake Bay program modeling system: Overview and recommendations for future development
Hood, Raleigh R.; Shenk, Gary W.; Dixon, Rachel L.; Smith, Sean M. C.; Ball, William P.; Bash, Jesse O.; Batiuk, Rich; Boomer, Kathy; Brady, Damian C.; Cerco, Carl; Claggett, Peter; de Mutsert, Kim; Easton, Zachary M.; Elmore, Andrew J.; Friedrichs, Marjorie A. M.; Harris, Lora A.; Ihde, Thomas F.; Lacher, Lara; Li, Li; Linker, Lewis C.; Miller, Andrew; Moriarty, Julia; Noe, Gregory B.; Onyullo, George E.; Rose, Kenneth; Skalak, Katie; Tian, Richard; Veith, Tamie L.; Wainger, Lisa A.; Weller, Donald; Zhang, Yinglong Joseph (2021-09-15)
The Chesapeake Bay is the largest, most productive, and most biologically diverse estuary in the continental United States providing crucial habitat and natural resources for culturally and economically important species. Pressures from human population growth and associated development and agricultural intensification have led to excessive nutrient and sediment inputs entering the Bay, negatively affecting the health of the Bay ecosystem and the economic services it provides. The Chesapeake Bay Program (CBP) is a unique program formally created in 1983 as a multi-stakeholder partnership to guide and foster restoration of the Chesapeake Bay and its watershed. Since its inception, the CBP Partnership has been developing, updating, and applying a complex linked modeling system of watershed, airshed, and estuary models as a planning tool to inform strategic management decisions and Bay restoration efforts. This paper provides a description of the 2017 CBP Modeling System and the higher trophic level models developed by the NOAA Chesapeake Bay Office, along with specific recommendations that emerged from a 2018 workshop designed to inform future model development. Recom-mendations highlight the need for simulation of watershed inputs, conditions, processes, and practices at higher resolution to provide improved information to guide local nutrient and sediment management plans. More explicit and extensive modeling of connectivity between watershed landforms and estuary sub-areas, estuarine hydrodynamics, watershed and estuarine water quality, the estuarine-watershed socioecological system, and living resources will be important to broaden and improve characterization of responses to targeted nutrient and sediment load reductions. Finally, the value and importance of maintaining effective collaborations among jurisdictional managers, scientists, modelers, support staff, and stakeholder communities is emphasized. An open collaborative and transparent process has been a key element of successes to date and is vitally important as the CBP Partnership moves forward with modeling system improvements that help stakeholders evolve new knowledge, improve management strategies, and better communicate outcomes.
Climate Change Adaptation for Agriculture. Mitigating Short- and Long-Term Impacts of Climate on Crop Production
Easton, Zachary M.; Faulkner, Joshua W. (Virginia Cooperative Extension, 2014-09-24)
Climate change and climate variability pose a great risk to agricultural production and farm livelihoods, and producers will need to adapt to a changing climate that is expected to be significantly more variable in order to meet these challenges. Agricultural producers have a long record of successful adaptation to a host of internal and external pressures and have made remarkable strides in the face of these pressures.
Climate Change Adaptation for Agriculture: Mitigating Short and Long-Term Impacts of Climate on Crop Production
Easton, Zachary M.; Faulkner, Joshua W. (Virginia Cooperative Extension, 2020)
This publication outlines some of the climate related challenges facing agriculture and then proposes some steps to mitigate and adapt to these challenges
Communicating Climate Change to Agricultural Audiences
Easton, Zachary M.; Faulkner, Joshua W. (Virginia Cooperative Extension, 2016-11-15)
Discusses climate change and challenges related to climate change, in relation to agriculture.
Comparison of short-term streamflow forecasting using stochastic time series, neural networks, process-based, and Bayesian models
Wagena, Moges B.; Goering, Dustin; Collick, Amy S.; Bock, Emily; Fuka, Daniel R.; Buda, Anthony R.; Easton, Zachary M. (2020-04)
Streamflow forecasts are essential for water resources management. Although there are many methods for forecasting streamflow, real-time forecasts remain challenging. This study evaluates streamflow forecasts using a process-based model (Soil and Water Assessment Tool-Variable Source Area model-SWAT-VSA), a stochastic model (Artificial Neural Network -ANN), an Auto-Regressive Moving-Average (ARMA) model, and a Bayesian ensemble model that utilizes the SWAT-VSA, ANN, and ARMA results. Streamflow is forecast from 1 to 8 d, forced with Quantitative Precipitation Forecasts from the US National Weather Service. Of the individual models, SWAT-VSA and the ANN provide better predictions of total streamflow (NSE 0.60-0.70) and peak flow, but underpredicted low flows. During the forecast period the ANN had the highest predictive power (NSE 0.44-0.64), however all three models underpredicted peak flow. The Bayesian ensemble forecast streamflow with the most skill for all forecast lead times (NSE 0.49-0.67) and provided a quantification of prediction uncertainty.
Comparison Watershed Selection When Applying the AllForX Approach for Sediment TMDL Development
Bronnenkant, Kristine Nicole (Virginia Tech, 2014-04-15)
This study compared physical characteristics used when selecting comparison (healthy) watersheds for the All-Forested Load Multiplier (AllForX) Approach, and examined a quantitative watershed characteristic as a selection criterion. The AllForX Approach uses a regression relationship between Virginia Stream Condition Index (VSCI) scores and AllForX values (a unit-less multiplier that is the ratio of a modeled existing sediment load divided by a modeled all-forested load condition) for an impaired watershed and several comparison watersheds to develop sediment TMDL target loads. The Generalized Watershed Loading Function (GWLF) model was used to simulate sediment loads for 20 watersheds (four impaired and 16 comparison) in the Upper James and New River basins in Virginia's Ridge and Valley physiographic region. Results suggest that within Virginia's Ridge and Valley physiographic region it may be possible to select comparison watersheds that are of a different stream order (watershed size) and lie in different river basins from the impaired watershed. Results further indicated that the topographic index (TI) distributions were not different across the modeled watersheds, indicating the watersheds are hydrologically similar. These results support selecting comparison watersheds regardless of river basin or stream order within Virginia's Ridge and Valley physiographic region. Finally, there was no statistical difference between the AllForX regressions when using the entire period of record or the two most recent VSCI data points. Therefore, for the watersheds modeled for this study, either all of the VSCI samples or the two most recent may be used in the AllForX Approach.
Compartmental Process-based Model for Estimating Ammonia Emission from Stored Scraped Liquid Dairy Manure
Karunarathne, Sampath Ashoka (Virginia Tech, 2017-07-06)
The biogeochemical processes responsible for production and emission of ammonia from stored liquid dairy manure are governed by environmental factors (e.g. manure temperature, moisture) and manure characteristics (e.g. total ammoniacal nitrogen concentration, pH). These environmental factors and manure characteristics vary spatially as a result of spatially heterogeneous physical, chemical, and biological properties of manure. Existing process-based models used for estimating ammonia emission consider stored manure as a homogeneous system and do not consider these spatial variations leading to inaccurate estimations. In this study, a one-dimensional compartmental biogeochemical model was developed to (i) estimate spatial variation of temperature and substrate concentration (ii) estimate spatial variations and rates of biogeochemical processes, and (iii) estimate production and emission of ammonia from stored scraped liquid dairy manure. A one-dimension compartmentalized modeling approach was used whereby manure storage is partitioned into several sections in vertical domain assuming that the conditions are spatially uniform within the horizontal domain. Spatial variation of temperature and substrate concentration were estimated using established principles of heat and mass transfer. Pertinent biogeochemical processes were assigned to each compartment to estimate the production and emission of ammonia. Model performance was conducted using experimental data obtained from National Air Emissions Monitoring Study conducted by the United States Environmental Protection Agency. A sensitivity analysis was performed and air temperature, manure pH, wind speed, and manure total ammoniacal nitrogen concentration were identified as the most sensitive model inputs. The model was used to estimate ammonia emission from a liquid dairy manure storage of a dairy farm located in Rockingham and Franklin counties in Virginia. Ammonia emission was estimated under different management and weather scenarios: two different manure storage periods from November to April and May to October using historical weather data of the two counties. Results suggest greater ammonia emissions and manure nitrogen loss for the manure storage period in warm season from May to October compared to the storage period in cold season from November to April.
Confronting our Agricultural Nonpoint Source Control Policy Problem
Stephenson, Stephen Kurt; Shabman, Leonard; Shortle, James; Easton, Zachary M. (Wiley, 2022-06-07)
Federal and state agricultural and environmental agencies have spent enormous sums since the 1990s to reduce nonpoint source (NPS) water pollution from agriculture. Yet, water quality problems are pervasive, and agriculture is a major cause. The lack of progress is often attributed to insufficient funding for pollution control practices relative to the scale of the problem. However, we attribute the lack of progress to shortcomings in agricultural NPS pollution control policy. We illustrate our argument after considering nearly four decades of federal, state, and local efforts to reduce agricultural NPS pollution to the Chesapeake Bay. Additional funding for current programs, absent fundamental program reform, is unlikely to produce reductions from agriculture needed to achieve desired water quality outcomes.
Consideration of BMP Performance Uncertainty in Chesapeake Bay Program Implementation: Workshop Report
Benham, Brian L.; Easton, Zachary M.; Hanson, Jeremy; Hershner, Carl; Julius, Susan; Stephenson, Stephen Kurt; Hinrich, Elaine (Scientific and Technical Advisory Committee, Chesapeake Bay Program, 2018-02-21)
Achieving Chesapeake Bay Program (CBP) nutrient and sediment reduction goals will require securing reductions largely from agricultural and urban nonpoint sources. While state and local governments rely largely on best management practices (BMPs) to achieve these goals, uncertainty surrounds the pollutant control effectiveness of these investments. Currently, the variation of BMP performance is not well documented or characterized in the CBP. Furthermore, knowledge gaps exist surrounding the sources and extent of the variation surrounding BMP performance. The purpose of this workshop was to make recommendations for improving the documentation and characterization of BMP performance uncertainty and to suggest how more detailed information on BMP uncertainty could be used to inform management decisions. Through this report, the workshop participants make several recommendations for characterizing uncertainty during the process of generating BMP effectiveness estimates (BMP Expert Panel Process). These include recommendations that the Chesapeake Bay Program partnership take measures to:

Systematically document and represent uncertainties throughout the BMP treatment process;

Produce information about the distribution of removal effectiveness of each BMP;

Develop a method for simply and effectively communicating the degree and type of uncertainty across all approved BMPs; and

Provide additional guidance for how to most effectively solicit “best professional judgment” as part of the expert panel process, including best practices for structured literature syntheses, identifying and avoiding potentially inappropriate heuristics (shortcuts) and biases when obtaining expert opinion, and expert elicitation.
Coupling a land surface model with a hydrodynamic model for regional flood risk assessment due to climate change: Application to the Susquehanna River near Harrisburg, Pennsylvania
Modi, Parthkumar A.; Czuba, Jonathan A.; Easton, Zachary M. (2021-11-19)
An increase in heavy precipitation associated with climate change has exacerbated flooding in the Eastern U.S. To assess regional flood risk with changing climatic conditions, we demonstrate the application of a novel hydrologic modeling framework that integrates climate projections with a coupled Noah-MP land surface model and a two-dimensional HEC-RAS hydrodynamic model. We employ this framework along a 41 km reach of the Susquehanna River near Harrisburg, Pennsylvania, where recent flood damages exceeded $2 billion (2011 Irene and Lee floods). Historical and future 30-year and 100-year peak-discharge estimates were compared to assess how flood risk might be altered due to climate change. Results indicate that precipitation increases from climate change do not always lead to increases in flood risk, because interplay of hydrological components in the watershed, which are considered by Noah-MP, largely controls flooding severity. However, climate change is expected to increase the severity of extreme events; if a 50-year flood (the recurrence interval of Tropical Storm Lee) occurred toward the end of the 21st century in the worst-case emission scenario, then flood volume would increase by 40% and flood extent by 15%, due to an increase in soil moisture from a wetter overall climate.
Coupling Physical and Machine Learning Models with High Resolution Information Transfer and Rapid Update Frameworks for Environmental Applications
Sommerlot, Andrew Richard (Virginia Tech, 2017-12-13)
Few current modeling tools are designed to predict short-term, high-risk runoff from critical source areas (CSAs) in watersheds which are significant sources of non point source (NPS) pollution. This study couples the Soil and Water Assessment Tool-Variable Source Area (SWAT-VSA) model with the Climate Forecast System Reanalysis (CFSR) model and the Global Forecast System (GFS) model short-term weather forecast, to develop a CSA prediction tool designed to assist producers, landowners, and planners in identifying high-risk areas generating storm runoff and pollution. Short-term predictions for streamflow, runoff probability, and soil moisture levels were estimated in the South Fork of the Shenandoah river watershed in Virginia. In order to allow land managers access to the CSA predictions a free and open source software based web was developed. The forecast system consists of three primary components; (1) the model, which preprocesses the necessary hydrologic forcings, runs the watershed model, and outputs spatially distributed VSA forecasts; (2) a data management structure, which converts high resolution rasters into overlay web map tiles; and (3) the user interface component, a web page that allows the user, to interact with the processed output. The resulting framework satisfied most design requirements with free and open source software and scored better than similar tools in usability metrics. One of the potential problems is that the CSA model, utilizing physically based modeling techniques requires significant computational time to execute and process. Thus, as an alternative, a deep learning (DL) model was developed and trained on the process based model output. The DL model resulted in a 9% increase in predictive power compared to the physically based model and a ten-fold decrease in run time. Additionally, DL interpretation methods applicable beyond this study are described including hidden layer visualization and equation extractions describing a quantifiable amount of variance in hidden layer values. Finally, a large-scale analysis of soil phosphorus (P) levels was conducted in the Chesapeake Bay watershed, a current location of several short-term forecast tools. Based on Bayesian inference methodologies, 31 years of soil P history at the county scale were estimated, with the associated uncertainty for each estimate. These data will assist in the planning and implantation of short term forecast tools with P management goals. The short term modeling and communication tools developed in this work contribute to filling a gap in scientific tools aimed at improving water quality through informing land manager's decisions.

Browsing by Author "Easton, Zachary M."

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