Destination Area: Global Systems Science (GSS)

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https://hdl.handle.net/10919/78630

GSS fosters transdisciplinary study of the dynamic interplay between natural and social systems. Faculty in this area collaborate to discover creative solutions to critical social problems emergent from human activity and environmental change, in areas such as freshwater and coastal water systems, rural environments, infectious disease, and food production and safety. Work in this area also embraces equity in the human condition by seeking the equitable distribution and availability of physical safety and well-being, psychological well-being, respect for human dignity, and access to crucial material and social resources throughout the world’s diverse communities.

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Assessing Strontium and Vulnerability to Strontium in Private Drinking Water Systems in Virginia
Scott, Veronica; Juran, Luke; Ling, Erin; Benham, Brian L.; Spiller, Asa (MDPI, 2020-04-08)
A total of 1.7 million Virginians rely on private drinking water (PDW) systems and 1.3 million of those people do not know their water quality. Because most Virginians who use PDW do not know the quality of that water and since strontium poses a public health risk, this study investigates sources of strontium in PDW in Virginia and identifies the areas and populations most vulnerable. Physical factors such as rock type, rock age, and fertilizer use have been linked to elevated strontium concentrations in drinking water. Social factors such as poverty, poor diet, and adolescence also increase social vulnerability to health impacts of strontium. Using water quality data from the Virginia Household Water Quality Program (VAHWQP) and statistical and spatial analyses, physical vulnerability was found to be highest in the Ridge and Valley province of Virginia where agricultural land use and geologic formations with high strontium concentrations (e.g., limestone, dolomite, sandstone, shale) are the dominant aquifer rocks. In terms of social vulnerability, households with high levels of strontium are more likely than the average VAHWQP participant to live in a food desert. This study provides information to help 1.7 million residents of Virginia, as well as populations in neighboring states, understand their risk of exposure to strontium in PDW.
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.
Assessment and validation of total water storage in the Chesapeake Bay watershed using GRACE
Sridhar, Venkataramana; Ali, Syed Azhar; Lakshmi, Venkataraman (Elsevier, 2019-05-22)
The Chesapeake Bay is the largest estuary in the United States, and its catchment has heterogeneous hydrological and geomorphologic characteristics. It includes seven major river basins: James, Patuxent, Potomac, Rappahannock, Susquehanna, Western Shore, Eastern Shore, and York. Remote sensing data, along with in-situ observations of streamflow and simulated water budget components, can provide significant understanding of variability in water resources availability in this diverse watershed. In this study, we quantify the terrestrial water storage using both remote sensing and in-situ data and hydrologic model outputs in the Chesapeake Bay watershed. Total water storage change (TWSC) was calculated based on the combination of three methods to identify the best approach in estimating TWSC. These methods evaluated different sources of data, including Parameter elevation Regression on Independent Slopes Model (PRISM) precipitation, MODIS ET, U.S. Geological Survey observed streamflow, and the Variable Infiltration Capacity (VIC) model. Estimated TWSC were in close agreement with GRACE-derived TWSC when we employed VIC-simulated streamflow after calibration with observed streamflow. However, the use of VIC-simulated ET or MODIS-derived ET yielded similar results for TWSC. Assessment of TWSC during extreme events (drought) during the summer months revealed that predicting ET is critical for TWSC in June–August and that VIC-simulated TWSC could be a reliable proxy for GRACE data to assess the water availability in the watershed.
Assessment of rice yield gap under a changing climate in India
Debnath, Subhankar; Mishra, Ashok; Mailapalli, D. R.; Raghuwanshi, N. S.; Sridhar, Venkataramana (2021-06)
Climate change evokes future food security concerns and needs for sustainable intensification of agriculture. The explicit knowledge about crop yield gap at country level may help in identifying management strategies for sustainable agricultural production to meet future food demand. In this study, we assessed the rice yield gap under projected climate change scenario in India at 0.25 degrees x 0.25 degrees spatial resolution by using the Decision Support System for Agrotechnology Transfer (DSSAT) model. The simulated spatial yield results show that mean actual yield under rainfed conditions (Y-a) will reduce from 2.13 t/ha in historical period 1981-2005 to 1.67 t/ha during the 2030s (2016-2040) and 2040s (2026-2050), respectively, under the RCP 8.5 scenario. On the other hand, mean rainfed yield gap shows no change (approximate to 1.49 t/ha) in the future. Temporal analysis of yield indicates that Y-a is expected to decrease in the considerably large portion of the study area (30-60%) under expected future climate conditions. As a result, yield gap is expected to either stagnate or increase in 50.6 and 48.7% of the study area during the two future periods, respectively. The research outcome indicates the need for identifying plausible best management strategies to reduce the yield gap under expected future climate conditions for sustainable rice production in India.
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.
Combined statistical and spatially distributed hydrological model for evaluating future drought indices in Virginia
Kang, Hyunwoo; Sridhar, Venkataramana (Elsevier, 2017-06-06)
Study region: Virginia, United States. Study focus: Climate change is expected to impact the intensity and severity of droughts; therefore, it is necessary to simulate future drought conditions using temperature and precipitation projections and hydrological models to derive reliable hydrological variables and drought indices. The objective of this study was to evaluate climate change influences on future drought potential and water resources in five major river basins in Virginia. In this study, the Soil and Water Assessment Tool (SWAT) and Coupled Model Intercomparison Project Phase 5 (CMIP5) climate models were used to compute a Standardized Soil Moisture Index (SSI), a Multivariate Standardized Drought Index (MSDI), and a Modified Palmer Drought Severity Index (MPDSI) for both historic and future periods. The drought conditions were evaluated, and their occurrences were determined at river basin scales. New hydrological insights for the region: The results of the ensemble mean of SSI indicated that there was an overall increase in agricultural drought occurrences projected in the New (> 1.3 times) and Rappahannock (> 1.13 times) river basins due to increases in evapotranspiration and surface and groundwater flow. However, MSDI and MPDSI exhibited a decrease in projected future drought, despite increases in precipitation, which suggests that it is essential to use hybridmodeling approaches and to interpret application-specific drought indices that consider both precipitation and temperature changes.
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.
Data on floating treatment wetland aided nutrient removal from agricultural runoff using two wetland species
Spangler, Jonathan T.; Sample, David J.; Fox, Laurie J.; Owen, James S. Jr.; White, Sarah A. (Elsevier, 2018-12-15)
The data presented in this article are related to the research article entitled “Floating treatment wetland aided nutrient removal from agricultural runoff using two wetland species” (Spangler et al., 2018). This Data in Brief article provides data on concentrations of common ions, macro- and micro-nutrients and metals every other week during a floating treatment wetland (FTW) mesocosm experiment, and macro- and micro-nutrient contents in cumulative plant tissues, data on continuously monitored water temperature, and nitrogen and phosphorus removal curves assessed every other week. The full data set is made available to enable critical or extended analysis of the research.
Denitrification Management
Easton, Zachary M.; Lassiter, Emily (Virginia Cooperative Extension, 2013-03-27)
Provides an explanation of denitrification and how it occurs including descriptions of the nitrogen cycle, environmental impacts of nitrogen levels, denitrification management, limitation, and unknowns.
Denitrifying Bioreactors: An Emerging Best Management Practice to Improve Water Quality
Lassiter, Emily; Easton, Zachary M. (Virginia Cooperative Extension, 2013-04-12)
This fact sheet discusses denitrifying bioreactors, what they are, how they work, applications, current research, expected costs and includes a glossary of terms.
Deriving the Reservoir Conditions for Better Water Resource Management Using Satellite-Based Earth Observations in the Lower Mekong River Basin
Ali, Syed Azhar; Sridhar, Venkataramana (MDPI, 2019-12-03)
The Mekong River basin supported a large population and ecosystem with abundant water and nutrient supply. However, the impoundments in the river can substantially alter the flow downstream and its timing. Using limited observations, this study demonstrated an approach to derive dam characteristics, including storage and flow rate, from remote-sensing-based data. Global Reservoir and Lake Monitor (GRLM), River-Lake Hydrology (RLH), and ICESat-GLAS, which generated altimetry from Jason series and inundation areas from Landsat 8, were used to estimate the reservoir surface area and change in storage over time. The inflow simulated by the variable infiltration capacity (VIC) model from 2008 to 2016 and the reservoir storage change were used in the mass balance equation to calculate outflows for three dams in the basin. Estimated reservoir total storage closely resembled the observed data, with a Nash-Sutcliffe efficiency and coefficient of determination more than 0.90 and 0.95, respectively. An average decrease of 55% in outflows was estimated during the wet season and an increase of up to 94% in the dry season for the Lam Pao. The estimated decrease in outflows during the wet season was 70% and 60% for Sirindhorn and Ubol Ratana, respectively, along with a 36% increase in the dry season for Sirindhorn. Basin-wide demand for evapotranspiration, about 935 mm, implicitly matched with the annual water diversion from 1000 to 2300 million m³. From the storage–discharge rating curves, minimum storage was also evident in the monsoon season (June–July), and it reached the highest in November. This study demonstrated the utility of remote sensing products to assess the impacts of dams on flows in the Mekong River basin.
Description of future drought indices in Virginia
Kang, Hyunwoo; Sridhar, Venkataramana (Elsevier, 2017-07-20)
This article presents projected future drought occurrences in five river basins in Virginia. The Soil and Water Assessment Tool (SWAT) and the Coupled Model Intercomparison Project Phase 5 (CMIP5) climate models were used to derive input variables of multiple drought indices, such as the Standardized Soil Moisture index (SSI), the Multivariate Standardized Drought Index (MSDI), and the Modified Palmer Drought Severity Index (MPDSI) for both historic and future periods. The results of SSI indicate that there was an overall increase in agricultural drought occurrences and that these were caused by increases in evapotranspiration and runoff. However, the results of the MSDI and MPDSI projected a decrease in drought occurrences in future periods due to a greater increase in precipitation in the future. Furthermore, GCM-downscaled products (precipitation and temperature) were verified using comparisons with historic observations, and the results of uncertainty analyses suggest that the lower and upper bounds of future drought projections agree with historic conditions.
Evaluating the bio-hydrological impact of a cloud forest in Central America using a semi-distributed water balance model
Caballero, Luis A.; Easton, Zachary M.; Richards, Brian K.; Steenhuis, Tammo S. (De Gruyter, 2013-03-01)
Water scarcity poses a major threat to food security and human health in Central America and is increasingly recognized as a pressing regional issues caused primarily by deforestation and population pressure. Tools that can reliably simulate the major components of the water balance with the limited data available and needed to drive management decision and protect water supplies in this region. Four adjacent forested headwater catchments in La Tigra National Park, Honduras, ranging in size from 70 to 635 ha were instrumented and discharge measured over a one year period. A semi-distributed water balance model was developed to characterize the bio-hydrology of the four catchments, one of which is primarily cloud forest cover. The water balance model simulated daily stream discharges well, with Nash Sutcliffe model efficiency (E) values ranging from 0.67 to 0.90. Analysis of calibrated model parameters showed that despite all watersheds having similar geologic substrata, the bio-hydrological response the cloud forest indicated less plant available water in the root zone and greater groundwater recharge than the non cloud forest cover catchments. This resulted in watershed discharge on a per area basis four times greater from the cloud forest than the other watersheds despite only relatively minor differences in annual rainfall. These results highlight the importance of biological factors (cloud forests in this case) for sustained provision of clean, potable water, and the need to protect the cloud forest areas from destruction, particularly in the populated areas of Central America.
Factors Affecting Phosphorous in Groundwater in an Alluvial Valley Aquifer: Implications for Best Management Practices
Flores-López, Francisco; Easton, Zachary M.; Geohring, Larry D.; Vermeulen, Peter J.; Haden, Van R.; Steenhuis, Tammo S. (MDPI, 2013-05-02)
Many streams in the US are impaired because of high Soluble Reactive Phosphorous (SRP) contributions from agriculture. However, the drivers of ecological processes that lead to SRP loss in baseflow from groundwater are not sufficiently understood to design effective Best Management Practices (BMPs). In this paper, we examine how soil temperature and water table depth influence the SRP concentrations in groundwater for a dairy farm in a valley bottom in the Catskills (NY, USA). Measured SRP concentrations in groundwater and baseflow were greater during the fall, when soil temperatures are warmer, than during winter and spring. The observed concentrations were within the bounds predicted by groundwater temperatures using the Arrhenius equation, except during fall, when concentrations rose above these predictions. These elevated concentrations were likely caused by mineralization and consequent accumulation of phosphorous (P) in summer. In addition, SRP concentrations were greater in near-stream areas, where water tables where higher. In short, SRP concentrations are dependent on temperature, demonstrating the importance of understanding the underlying mechanism of ecological processes. In addition, results suggest BMPs that apply manure on land having a deep groundwater, instead of on land with a shallow water table will lower overall SRP contributions.
Factors When Considering an Agricultural Drainage System
Easton, Zachary M.; Bock, Emily; Collick, Amy S. (Virginia Cooperative Extension, 2017-02-23)
A well designed drainage system can improve crop yield, and lower the variation in crop yield by removing excess water in the soil.
Fecal Indicator Bacteria and Antibiotic Resistance Genes in Storm Runoff from Dairy Manure and Compost-Amended Vegetable Plots
Jacobs, Kyle; Wind, Lauren L.; Krometis, Leigh-Anne H.; Hession, W. Cully; Pruden, Amy (American Society for Agronomy, 2019-07-01)
Given the presence of antibiotics and resistant bacteria in livestock manures, it is important to identify the key pathways by which land-applied manure-derived soil amendments potentially spread resistance. The goal of this field-scale study was to identify the effects of different types of soil amendments (raw manure from cows treated with cephapirin and pirlimycin, compost from antibiotic-treated or antibiotic-free cows, or chemical fertilizer only) and crop type (lettuce [Lactuca sativa L.] or radish [Raphanus sativus L.]) on the transport of two antibiotic resistance genes (ARGs; sul1 and ermB) via storm runoff from six naturally occurring storms. Concurrent quantification of sediment and fecal indicator bacteria (FIB; Escherichia coli and enterococci) in runoff permitted comparison to traditional agricultural water quality targets that may be driving factors of ARG presence. Storm characteristics (total rainfall volume, storm duration, etc.) significantly influenced FIB concentration (two-way ANOVA, p < 0.05), although both effects from individual storm events (Kruskal-Wallis, p < 0.05) and vegetative cover influenced sediment levels. Composted and raw manure-amended plots both yielded significantly higher sul1 and ermB levels in runoff for early storms, at least 8 wk following initial planting, relative to fertilizer-only or unamended barren plots. There was no significant difference between sul1 or ermB levels in runoff from plots treated with compost derived from antibiotic-treated versus antibiotic-free dairy cattle. Our findings indicate that agricultural fields receiving manure-derived amendments release higher quantities of these two “indicator” ARGs in runoff, particularly during the early stages of the growing season, and that composting did not reduce effects of ARG loading in runoff.
Finding What Is Inaccessible: Antimicrobial Resistance Language Use among the One Health Domains
Wind, Lauren L.; Briganti, Jonathan; Brown, Anne M.; Neher, Timothy P.; Davis, Meghan F.; Durso, Lisa M.; Spicer, Tanner; Lansing, Stephanie (MDPI, 2021-04-03)
The success of a One Health approach to combating antimicrobial resistance (AMR) requires effective data sharing across the three One Health domains (human, animal, and environment). To investigate if there are differences in language use across the One Health domains, we examined the peer-reviewed literature using a combination of text data mining and natural language processing techniques on 20,000 open-access articles related to AMR and One Health. Evaluating AMR key term frequency from the European PubMed Collection published between 1990 and 2019 showed distinct AMR language usage within each domain and incongruent language usage across domains, with significant differences in key term usage frequencies when articles were grouped by the One Health sub-specialties (2-way ANOVA; p < 0.001). Over the 29-year period, “antibiotic resistance” and “AR” were used 18 times more than “antimicrobial resistance” and “AMR”. The discord of language use across One Health potentially weakens the effectiveness of interdisciplinary research by creating accessibility issues for researchers using search engines. This research was the first to quantify this disparate language use within One Health, which inhibits collaboration and crosstalk between domains. We suggest the following for authors publishing AMR-related research within the One Health context: (1) increase title/abstract searchability by including both antimicrobial and antibiotic resistance related search terms; (2) include “One Health” in the title/abstract; and (3) prioritize open-access publication.
Genome analysis of a major urban malaria vector mosquito, Anopheles stephensi
Jiang, X.; Peery, A.; Hall, B.; Sharma, A.; Chen, X.-G.; Waterhouse, R. M.; Komissarov, A.; Riehle, M. M.; Shouche, Y.; Sharakhova, Maria V.; Lawson, D.; Pakpour, Nazzy; Arensburger, Peter; Davidson, V. L. M.; Eiglmeier, K.; Emrich, S.; George, P.; Kennedy, R. C.; Mane, S. P.; Maslen, G.; Oringanje, C.; Qi, Y.; Settlage, Robert E.; Tojo, M.; Tubio, J. M. C.; Unger, Maria F.; Wang, B.; Vernick, K. D.; Ribeiro, J. C.; James, A. A.; Michel, K.; Riehle, M. A.; Luckhart, Shirley; Sharakhov, Igor V.; Tu, Zhijian Jake (Biomed Central, 2014-01-01)
Background: Anopheles stephensi is the key vector of malaria throughout the Indian subcontinent and Middle East and an emerging model for molecular and genetic studies of mosquito-parasite interactions. The type form of the species is responsible for the majority of urban malaria transmission across its range. Results: Here, we report the genome sequence and annotation of the Indian strain of the type form of An. stephensi. The 221 Mb genome assembly represents more than 92% of the entire genome and was produced using a combination of 454, Illumina, and PacBio sequencing. Physical mapping assigned 62% of the genome onto chromosomes, enabling chromosome-based analysis. Comparisons between An. stephensi and An. gambiae reveal that the rate of gene order reshuffling on the X chromosome was three times higher than that on the autosomes. An. stephensi has more heterochromatin in pericentric regions but less repetitive DNA in chromosome arms than An. gambiae. We also identify a number of Y-chromosome contigs and BACs. Interspersed repeats constitute 7.1% of the assembled genome while LTR retrotransposons alone comprise more than 49% of the Y contigs. RNA-seq analyses provide new insights into mosquito innate immunity, development, and sexual dimorphism. Conclusions: The genome analysis described in this manuscript provides a resource and platform for fundamental and translational research into a major urban malaria vector. Chromosome-based investigations provide unique perspectives on Anopheles chromosome evolution. RNA-seq analysis and studies of immunity genes offer new insights into mosquito biology and mosquito-parasite interactions.
Groundwater influence on water budget of a small constructed floodplain wetland in the Ridge and Valley of Virginia, USA
Ludwig, Andrea L.; Hession, W. Cully (Elsevier, 2015-12-01)
Study region: A floodplain in the headwaters of a tributary to the Chesapeake Bay, Ridge and Valley of the Eastern United States. Study focus: This study investigated the influence of groundwater exchange in the annual wetland hydrologic budget and identified spatial and temporal variability in groundwater hydraulic gradients using an array of nested piezometers. New hydrological insights for the region: Data showed that the created wetland met hydrologic success criteria, and that the wetland storage was fully connected with the groundwater table. Water-surface storage fluctuation was not fully explained by precipitation and evapotranspiration, suggesting that storage was highly influenced by ground water inputs. The potentiometric surface showed that hill slope seep recharge was the dominant groundwater vector. However, during the summer and fall months, the adjacent stream channel was a losing system, and storm-driven rise in stream stage affected wetland storage.The complex hydrology of this relatively small wetland indicates that predicting the fluctuations of storage for design of unconfined floodplain wetlands is challenging, and that if the influence of groundwater seepage is negated, then fluctuations may be underestimated to the point of harming vegetation.

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Browsing Destination Area: Global Systems Science (GSS) by Department "Biological Systems Engineering"

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