Browsing by Author "Fuka, Daniel R."
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- Brokered Alignment of Long-Tailed Observations (BALTO) Applications in GeoscienceStamps, 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 GeoscienceStamps, 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.
- Comparison of short-term streamflow forecasting using stochastic time series, neural networks, process-based, and Bayesian modelsWagena, 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 Model Workbenches for Earth Science Information SystemsFuka, Daniel R.; Easton, Zachary M. (2020-11-05)Watershed models have traditionally been used for watershed management planning and research purposes, though as we bring sub-field-scale process initialization into them, and make them initializable globally with data brokering systems, we are covering the gamut of all of the Federal and International Data Centers, as well as locally stored data that are utilized during the initialization process. The wide variety of data required by these models opens up another use for these models; as Data Model Workbenches for Computer & Information Science & Engineering, Advanced Cyberinfrastructure, Computing and Communication Foundations, and Information & Intelligent Systems data sources.
- Environmental flows in the context of unconventional natural gas development in the Marcellus ShaleBuchanan, Brian P.; Auerbach, Daniel A.; McManamay, Ryan A.; Taylor, Jason M.; Flecker, Alexander S.; Archibald, Josephine A.; Fuka, Daniel R.; Walter, M. Todd (2017-01)Quantitative flow-ecology relationships are needed to evaluate how water withdrawals for unconventional natural gas development may impact aquatic ecosystems. Addressing this need, we studied current patterns of hydrologic alteration in the Marcellus Shale region and related the estimated flow alteration to fish community measures. We then used these empirical flow-ecology relationships to evaluate alternative surface water withdrawals and environmental flow rules. Reduced high-flow magnitude, dampened rates of change, and increased low-flow magnitudes were apparent regionally, but changes in many of the flow metrics likely to be sensitive to withdrawals also showed substantial regional variation. Fish community measures were significantly related to flow alteration, including declines in species richness with diminished annual runoff, winter low-flow, and summer median-flow. In addition, the relative abundance of intolerant taxa decreased with reduced winter high-flow and increased flow constancy, while fluvial specialist species decreased with reduced winter and annual flows. Stream size strongly mediated both the impact of withdrawal scenarios and the protection-afforded by environmental flow standards. Under the most intense withdrawal-scenario, 75% of reference headwaters and creeks (drainage areas < 99 km(2)) experienced at least 78% reduction in summer flow, whereas little change was predicted for larger rivers. Moreover, the least intense withdrawal scenario still-reduced summer flows by at least 21% for 50% of headwaters and creeks. The observed 90th quantile flow-ecology relationships indicate that such alteration could reduce species richness by 23% or more. Seasonally varying environmental flow standards and high fixed minimum flows protected the most streams from hydrologic alteration, but common minimum flow standards left numerous locations vulnerable to substantial flow alteration. This study clarifies how additional water demands in the region may adversely affect freshwater biological integrity. The-results make clear that policies to limit or prevent water withdrawals from smaller streams can reduce the risk of ecosystem impairment.
- Estimating dominant runoff modes across the conterminous United StatesBuchanan, Brian; Auerbach, Daniel A.; Knighton, James; Evensen, Darrick; Fuka, Daniel R.; Easton, Zachary M.; Wieczorek, Michael; Archibald, Josephine A.; McWilliams, Brandon; Walter, Todd (2018-12-30)Effective natural resource planning depends on understanding the prevalence of runoff generating processes. Within a specific area of interest, this demands reproducible, straightforward information that can complement available local data and can orient and guide stakeholders with diverse training and backgrounds. To address this demand within the contiguous United States (CONUS), we characterized and mapped the predominance of two primary runoff generating processes: infiltration-excess and saturation-excess runoff (IE vs. SE, respectively). Specifically, we constructed a gap-filled grid of surficial saturated hydraulic conductivity using the Soil Survey Geographic and State Soil Geographic soils databases. We then compared surficial saturated hydraulic conductivity values with 1-hr rainfall-frequency estimates across a range of return intervals derived from CONUS-scale random forest models. This assessment of the prevalence of IE versus SE runoff also incorporated a simple uncertainty analysis, as well as a case study of how the approach could be used to evaluate future alterations in runoff processes resulting from climate change. We found a low likelihood of IE runoff on undisturbed soils over much of CONUS for 1-hr storms with return intervals <5 years. Conversely, IE runoff is most likely in the Central United States (i.e., Texas, Louisiana, Kansas, Missouri, Iowa, Nebraska, and Western South Dakota), and the relative predominance of runoff types is highly sensitive to the accuracy of the estimated soil properties. Leveraging publicly available data sets and reproducible workflows, our approach offers greater understanding of predominant runoff generating processes over a continental extent and expands the technical resources available to environmental planners, regulators, and modellers.
- Impact of climate change and climate anomalies on hydrologic and biogeochemical processes in an agricultural catchment of the Chesapeake Bay watershed, USAWagena, Moges B.; Collick, Amy S.; Ross, Andrew C.; Najjar, Raymond G.; Rau, Benjamin; Sommerlot, Andrew R.; Fuka, Daniel R.; Kleinman, Peter J. A.; Easton, Zachary M. (2018-10-01)Nutrient export from agricultural landscapes is a water quality concern and the cause of mitigation activities worldwide. Climate change impacts hydrology and nutrient cycling by changing soil moisture, stoichiometric nutrient ratios, and soil temperature, potentially complicating mitigation measures. This research quantifies the impact of climate change and climate anomalies on hydrology, nutrient cycling, and greenhouse gas emissions in an agricultural catchment of the Chesapeake Bay watershed. We force a calibrated model with seven downscaled and bias-corrected regional climate models and derived climate anomalies to assess their impact on hydrology and the export of nitrate (NO3-), phosphorus (P), and sediment, and emissions of nitrous oxide (N2O) and di-nitrogen (N-2). Modelaverage (+/- standard deviation) results indicate that climate change, through an increase in precipitation and temperature, will result in substantial increases in winter/spring flow (10.6 +/- 12.3%), NO3-(17.3 +/- 6.4%), dissolved P (32.3 +/- 18.4%), total P (24.8 +/- 16.9%), and sediment (25.2 +/- 16.6%) export, and a slight increases in N2O (0.3 +/- 4.8%) and N-2 (0.2 +/- 11.8%) emissions. Conversely, decreases in summer flow (-29.1 +/- 24.6%) and the export of dissolved P (-15.5 +/- 26.4%), total P (-16.3 +/- 20.7%), sediment (-20.7 +/- 18.3%), and NO3-(-29.1 +/- 27.8%) are driven by greater evapotranspiration from increasing summer temperatures. Decreases in N2O (-26.9 +/- 15.7%) and N-2 (-36.6 +/- 22.9%) are predicted in the summer and driven by drier soils. While the changes in flow are related directly to changes in precipitation and temperature, the changes in nutrient and sediment export are, to some extent, driven by changes in agricultural management that climate change induces, such as earlier spring tillage and altered nutrient application timing and by alterations to nutrient cycling in the soil. (C) 2018 Elsevier B.V. All rights reserved.
- Impacts of climate change on terrestrial hydrological components and crop water use in the Chesapeake Bay watershedModi, Parthkumar A.; Fuka, Daniel R.; Easton, Zachary M. (2021-06)This study assessed the impacts of climate change on terrestrial hydrological components and Crop Water Use (CWU) over the Chesapeake Bay watershed using a combination of Global Climate Models (GCMs) and a land surface model. To better understand the impacts of climate change on the hydrological cycle, long-term simulations of multiple earth system models from the Coupled Model Intercomparison Project (CMIP Phase 5) are statistically downscaled and bias-corrected using Multivariate Adaptive Constructed Analogs (MACA) scheme for use as model forcing. Precipitation indices from the twenty MACA-based GCMs are used to identify six best performing models. A mesoscale approach is developed, where CWU is estimated by accounting for the impacts of changing climate conditions and rising CO2 levels. Daily grid-based crop coefficients are derived from evapotranspiration data. The findings indicate a significant annual increase in precipitation (10 %) and temperature (+4.5 K) for the RCP 8.5 scenario towards the end of the 21st century. A significant reduction (13 % and 17 % respectively) in CWU is estimated for corn and soybeans, resulting from increased total precipitation and rising CO2 levels suppressing evapotranspiration. Our results indicate that even in a warmer regime, crop water use decreased due to rising CO2 concentrations due to climate change.
- Improved Simulation of Edaphic and Manure Phosphorus Loss in SWATCollick, Amy S.; Veith, Tamie L.; Fuka, Daniel R.; Kleinman, Peter J. A.; Buda, Anthony R.; Weld, Jennifer L.; Bryant, Ray B.; Vadas, Peter A.; White, Mike J.; Harmel, R. Daren; Easton, Zachary M. (2016-07)Watershed models such as the Soil Water Assessment Tool (SWAT) and the Agricultural Policy Environmental EXtender (APEX) are widely used to assess the fate and transport of agricultural nutrient management practices on soluble and particulate phosphorus (P) loss in runoff. Soil P-cycling routines used in SWAT2012 revision 586, however, do not simulate the short-term effects of applying a concentrated source of soluble P, such as manure, to the soil surface where it is most vulnerable to runoff. We added a new set of soil P routines to SWAT2012 revision 586 to simulate surface-applied manure at field and subwatershed scales within Mahantango Creek watershed in south-central Pennsylvania. We corroborated the new P routines and standard P routines in two versions of SWAT (conventional SWAT, and a topographically driven variation called TopoSWAT) for a total of four modeling "treatments". All modeling treatments included 5 yr of measured data under field-specific, historical management information. Short-term "wash off" processes resulting from precipitation immediately following surface application of manures were captured with the new P routine whereas the standard routines resulted in losses regardless of manure application. The new routines improved sensitivity to key factors in nutrient management (i.e., timing, rate, method, and form of P application). Only the new P routines indicated decreases in soluble P losses for dairy manure applications at 1, 5, and 10 d before a storm event. The new P routines also resulted in more variable P losses when applying manure versus commercial fertilizer and represented increases in total P losses, as compared with standard P routines, with rate increases in dairy manure application (56,000 to 84,000 L ha(-1)). The new P routines exhibited greater than 50% variation among proportions of organic, particulate, and soluble P corresponding to spreading method. In contrast, proportions of P forms under the standard P routines varied less than 20%. Results suggest similar revisions to other agroecosystem watershed models would be appropriate.
- Improving the spatial representation of soil properties and hydrology using topographically derived initialization processes in the SWAT modelFuka, Daniel R.; Collick, Amy S.; Kleinman, Peter J. A.; Auerbach, Daniel A.; Harmel, R. Daren; Easton, Zachary M. (2016-11-29)Topography exerts critical controls on many hydrologic, geomorphologic and biophysical processes. However, many watershed modelling systems use topographic data only to define basin boundaries and stream channels, neglecting opportunities to account for topographic controls on processes such as soil genesis, soil moisture distributions and hydrological response. Here, we demonstrate a method that uses topographic data to adjust spatial soil morphologic and hydrologic attributes: texture, depth to the C-horizon, saturated conductivity, bulk density, porosity and the water capacities at field (33 kpa) and wilting point (1500 kpa) tensions. As a proof of concept and initial performance test, the values of the topographically adjusted soil parameters and those from the Soil Survey Geographic Database (SSURGO; available at 1 : 20 000 scale) were compared with measured soil pedon pit data in the Grasslands Soil and Water Research Lab watershed in Riesel, TX. The topographically adjusted soils were better correlated with the pit measurements than were the SSURGO values. We then incorporated the topographically adjusted soils into an initialization of the Soil and Water Assessment Tool model for 15 Riesel research watersheds to investigate how changes in soil properties influence modelled hydrological responses at the field scale. The results showed that the topographically adjusted soils produced better runoff predictions in 50% of the fields, with the SSURGO soils performing better in the remainder. In addition, the a priori adjusted soils result in fewer calibrated model parameters. These results indicate that adjusting soil properties based on topography can result in more accurate soil characterization and, in some cases, improve model performance. Copyright (C) 2016 John Wiley & Sons, Ltd.
- A LoRa sensor network for monitoring pastured livestock location and activityDos Reis, Barbara R.; Easton, Zachary M.; White, Robin R.; Fuka, Daniel R. (Oxford University Press, 2021-01-21)Precision technologies for confinement animal agricultural systems have increased rapidly over the past decade, though precision technology solutions for pastured livestock remain limited. There are a number of reasons for this limited expansion of technologies for pastured animals, including networking availability and reliability, power requirements, and expense, among others. The objective of this work was to demonstrate a rapidly deployable long-range radio (LoRa) based, low-cost sensor suite that can be used to track location and activity of pastured livestock. The sensor is comprised of an inexpensive Arduino-compatible microprocessor, a generic MPU-9250 motion sensor which contains a 3-axis accelerometer, 3-axis magnetometer, and a 3-axis gyroscope, a generic GPS receiver, and a RFM95W generic LoRa radio. The microprocessor can be programmed flexibly using the open source Arduino IDE software to adjust the frequency of sampling, the data packet to send, and what conditions are needed to operate. The LoRa radio transmits to a Dragino LoRa gateway which can also be flexibly programmed through the Arduino IDE software to send data to local storage or, in cases where a web or cellular connection is available, to cloud storage. The sensor was powered using a USB cord connected to a 3,350 mAh lithium-ion battery pack. The Dragino gateway was programmed to upload data to the ThingSpeak IoT application programming interface for data storage, handling, and visualization. Evaluations showed minimal benefit associated with reducing sampling frequency as a strategy to preserve battery life. Packet loss ranged from 40% to 60%. In a 3 d evaluation on pastured sheep, the sensor suite was able to report GPS locations, inertial sensor readings, and temperature. Preliminary demonstrations of our system are satisfactory to detect animal location based on GPS data in real-time. This system has clear utility as a lower-cost strategy to deploy flexible, useful precision technologies for pasture-based livestock species.
- Real-Time Forecast of Hydrologically Sensitive Areas in the Salmon Creek Watershed, New York State, Using an Online Prediction ToolDahlke, Helen E.; Easton, Zachary M.; Fuka, Daniel R.; Walter, M. Todd; Steenhuis, Tammo S. (MDPI, 2013-07-02)In the northeastern United States (U.S.), watersheds and ecosystems are impacted by nonpoint source pollution (NPS) from agricultural activity. Where agricultural fields coincide with runoff-producing areas—so called hydrologically sensitive areas (HSA)—there is a potential risk of NPS contaminant transport to streams during rainfall events. Although improvements have been made, water management practices implemented to reduce NPS pollution generally do not account for the highly variable, spatiotemporal dynamics of HSAs and the associated dynamics in NPS pollution risks. This paper presents a prototype for a web-based HSA prediction tool developed for the Salmon Creek watershed in upstate New York to assist producers and planners in quickly identifying areas at high risk of generating storm runoff. These predictions can be used to prioritize potentially polluting activities to parts of the landscape with low risks of generating storm runoff. The tool uses real-time measured data and 24–48 h weather forecasts so that locations and the timing of storm runoff generation are accurately predicted based on present-day and future moisture conditions. Analysis of HSA predictions in Salmon Creek show that 71% of the largest storm events between 2006 and 2009 were correctly predicted based on 48 h forecasted weather data. Real-time forecast of HSAs represents an important paradigm shift for the management of NPS in the northeastern U.S.
- Reviews and syntheses: The promise of big diverse soil data, moving current practices towards future potentialTodd-Brown, Katherine E. O.; Abramoff, Rose Z.; Beem-Miller, Jeffrey; Blair, Hava K.; Earl, Stevan; Frederick, Kristen J.; Fuka, Daniel R.; Santamaria, Mario Guevara; Harden, Jennifer W.; Heckman, Katherine; Heran, Lillian J.; Holmquist, James R.; Hoyt, Alison M.; Klinges, David H.; LeBauer, David S.; Malhotra, Avni; McClelland, Shelby C.; Nave, Lucas E.; Rocci, Katherine S.; Schaeffer, Sean M.; Stoner, Shane; van Gestel, Natasja; von Fromm, Sophie F.; Younger, Marisa L. (Copernicus, 2022-07-28)In the age of big data, soil data are more available and richer than ever, but - outside of a few large soil survey resources - they remain largely unusable for informing soil management and understanding Earth system processes beyond the original study. Data science has promised a fully reusable research pipeline where data from past studies are used to contextualize new findings and reanalyzed for new insight. Yet synthesis projects encounter challenges at all steps of the data reuse pipeline, including unavailable data, labor-intensive transcription of datasets, incomplete metadata, and a lack of communication between collaborators. Here, using insights from a diversity of soil, data, and climate scientists, we summarize current practices in soil data synthesis across all stages of database creation: availability, input, harmonization, curation, and publication. We then suggest new soil-focused semantic tools to improve existing data pipelines, such as ontologies, vocabulary lists, and community practices. Our goal is to provide the soil data community with an overview of current practices in soil data and where we need to go to fully leverage big data to solve soil problems in the next century.
- Watershed model parameter estimation in low data environmentsGarna, Roja K.; Fuka, Daniel R.; Faulkner, Joshua W.; Collick, Amy S.; Easton, Zachary M. (Elsevier, 2022-12)Study region: Three watersheds in the Lake Champlain Basin of Vermont, USA. Study focus: Watershed models are essential for evaluating the impact of watershed management; however, they contain many parameters that are not directly measurable. These parameters are commonly estimated by calibration against observed data, often streamflow. Unfortunately, many areas lack long-term streamflow records, making parameter estimation in low data environments (LDE) challenging. A new calibration technique, simultaneous multi-basin calibration (MBC), was developed to estimate model parameters in LDE. Three Soil and Water Assessment Tool (SWAT) model initializations for USGS gages with ~ 2-year records in the Lake Champlain Basin of Vermont, USA, were evaluated by comparing MBC and the commonly used similarity-based regionalization (SBR) approach, where calibrated parameters from a watershed with an extended data record are transferred to the LDE receptor watersheds. In MBC, each watershed is initialized, and observed flows from each initialization are aggregated to generate a combined streamflow record of sufficient length to calibrate using a differential evolution algorithm. New hydrological insights for the region: Using this new MBC method, we demonstrate improved model performance and more realistic model parameter values. This study demonstrates that short periods of hydrological measurement from multiple locations in a basin can represent a system similarly to long term measurements and that even short records taken at multiple locations significantly improve our hydrologic knowledge of a system as compared to relying on the similarity of a basin with a long record of flow. In addition, this study revealed that the hydrologic response is mediated by the interplay of very low soil-saturated hydraulic conductivity (Ksat) and cracking soils. As a result, even if Ksat is very low, cracking clays have a large impact on runoff production Garna et al. (2022).