Grantee Research Project Results
2016 Progress Report: Center for Integrated Multi-scale Nutrient Pollution Solutions
EPA Grant Number: R835568Center: Center for Integrated Multi‐scale Nutrient Pollution Solutions
Center Director: Shortle, James S.
Title: Center for Integrated Multi-scale Nutrient Pollution Solutions
Investigators: Shortle, James S. , Royer, Matthew B , Ready, Richard C , Brooks, Robert P. , Boyer, Elizabeth W. , Kemanian, Armen , Bills, Brian
Current Investigators: Shortle, James S. , Brooks, Robert P. , Boyer, Elizabeth W. , Ready, Richard C , Royer, Matthew B , Bills, Brian , Kemanian, Armen
Institution: Pennsylvania State University
Current Institution: Pennsylvania State University , University of Maryland - Eastern Shore , USDA
EPA Project Officer: Packard, Benjamin H
Project Period: September 1, 2013 through August 31, 2018
Project Period Covered by this Report: September 1, 2015 through August 31,2016
Project Amount: $2,220,649
RFA: Centers for Water Research on National Priorities Related to a Systems View of Nutrient Management (2012) RFA Text | Recipients Lists
Research Category: Watersheds , Water
Objective:
The Center for Integrated Multi-scale Nutrient Pollution Solutions (CNS) is a collaboration of scientists and community partners engaged in a "shared discovery" process to develop an integrated systems approach to enhance the decision making capacity of key water and nutrient management institutional agents. We seek to provide connections between policy directives and on-the-ground actions by moving beyond the old paradigm or "best management practice (BMP) fix" to discover optimal solutions that reduce nutrient pollution through understanding (1) the sources and flow paths of nutrients as they impact water quality and ecosystem function, (2) how individual management practices integrate and aggregate from field to watershed scales and beyond, (3) the importance of including socioeconomic and other local watershed issues, and (4) how this information is translated at different management levels to produce effective action and successful results. Our main objective is to use an integrated decision support process involving modeling, empirical data, and lessons learned to develop community-based, spatially-explicit, nutrient intervention scenarios that engage and inform stakeholders for high impact water management decisions. These intervention scenarios are alternative sets of tactics and strategies for meeting the 2025 nutrient and sediment reduction goals in the Chesapeake Bay (Table 1).
This process involves several steps, which are carried out via seven team projects: Team1—Drivers and Interventions; Team 2—Harmonizing Models; Team 3—Ecological Assessment; Team 4—Best Management Practices; Team 5—Informatics; Team 6—Economics and Ecosystem Services; and Team 7—Engagement, Education, and Outreach.
Project 1: Drivers and Interventions
Nutrient discharges into surface waters derive from many different sources, land-uses, and locations across the watersheds. Team 1 aims to guide the CNS with a regional-scale, systematic account of the sources and sinks of nutrients that impact watersheds in the Mid-Atlantic region. This approach provides a scientific perspective from which to understand drivers of the nutrient pollution problems and to explore potential intervention strategies and tactics to mitigate nutrient pollution problems. Specific objectives are to (1) develop nutrient input budgets, using a systematic nutrient accounting approach, at multiple spatial scales; and (2) use the nutrient budgets to explore fundamental drivers of nutrient pollution, and to evaluate the effects of potential interventions to mitigate nutrient pollution problems.
Project 2: Harmonizing Data and Decision Support Systems
In the United States, many fresh and estuarine waters remain polluted because efforts and technologies to control nutrients have not, in most cases, kept pace with the growth of nutrient inputs. Current advances in modeling nutrient fate and transport coupled with ongoing advances in big data management are opening new and promising opportunities for assessing and visualizing the impact of land use practices on water quality and overall ecosystem health.
Team 2's main tasks are (1) database and model fusion, and (2) multi-model comparison. We propose to couple a distributed database (Hydroterre) with a fully distributed hydrological model (Penn State Integrated Hydrologic Model or PIHM) and an agro-ecosystem model (Cycles) to simulate three of the four watersheds that are the target of CNS activities (Spring Creek, Mahantango Creek, and Conewago Creek watersheds). These watersheds are test beds that cover a wide range of agroecological conditions in the Mid-Atlantic Region (MAR), and will constitute our first step towards developing a model available for the whole nation. The model will also integrate the processes and findings of the other teams in CNS. Our conceptual proposition is that in the long-term, the tools of choice for analyzing such watersheds will be fully distributed biophysical models that are able to integrate multiple data sources along with dynamic simulations at stable, continuous, and scalable spatial and temporal scales.
In addition, we propose to compare the outputs of different models when applied at similar scales. Candidate models for the inter-comparison are the EPA Chesapeake Bay Model (CBM), the Unite States Department of Agriculture (USDA) Soil and Water Assessment Tool (SWAT), the United States Geological Survey (USGS) Sparrow model, and the PSU PIHM model. The comparison will include water, carbon, nitrogen, and phosphorous dynamics depending on the characteristics of the scenarios and the models and being compared. The model inter-comparison can help characterize the uncertainty around modeled results.
Project 3: Maintaining Ecological Integrity and Provisioning of Ecosystem Services
The purpose of this project is to aid the CNS in its integrated decision support process by validating model expectations and outcomes with ecological condition data followed by estimating ecological condition changes and resultant ecosystem services for a give set of interventions (scenarios). The main objectives for Team 3 are to: (1) establish baseline condition at three assessment levels (landscape, rapid, and intensive), (2) relate spatially targeted model estimates of nutrients and sediment yields to site condition, (3) estimate changes in ecological condition under different scenarios, and (4) translate this information into changes related to ecosystem services.
Project 4: Optimizing Best Management Practices and Determining Strategic Barriers to Success
Activities in the Project/Team 4 research area are organized under two major objectives: (1) optimize "tactical" options, and (2) define "strategic" barriers. For objective 1, we will work with the Community Partners Council to identify alternative suites of practices that may realistically be adopted under existing systems and constraints. Using the Nutrient Center's decision-support tools, iteratively adjust the tactical management options to develop optimal suites of tactical options. For objective 2, we will elucidate the boundaries of existing nutrient management systems that must be removed to achieve maximum potential for optimized tactical nutrient management options to improve health of the Bay and its tributaries.
Project 5: Informatics
The Informatics team develops and implements web-based tools (collaborative web portal, map-based discussion tool, and interactive model scenario browser) to aid in communicating CNS science information to watershed stakeholders.
Project 6: Economics and Ecosystem Services
Interventions aimed at reducing nutrient loadings to the Chesapeake basin, for example, through adoption of best management practices on agricultural lands, are costly but generate benefits in the form of increased ecosystem services. A challenge is that the individuals who bear the costs are not the same as those who enjoy the benefits.
Team 6's main task is to: (1) develop a system that can be used to measure the monetary value of ecosystem services generated by specific interventions in specific watersheds, including measurement of the spatial distribution of those benefits, and (2) use the system to evaluate the specific scenarios developed and modeled by Teams 2 and 4.
Project 7: Engagement/Education/Outreach
The Engagement/Education/Outreach team facilitates connections among all research teams and external stakeholders to ensure that research conducted by the Center will be connected to decision makers and stakeholders wrestling with nutrient management issues at a variety of spatial scales. By engaging key decision makers and stakeholders at all levels, the Center's phased outreach and engagement strategy will facilitate research outcomes related to understanding, evaluating and choosing integrated multi-scale solutions for nutrient pollution.
Progress Summary:
During the third year of the project, the Center focused primarily on (1) wrapping up Scenarios A and B; and (2) finalizing the approaches and steps for running Scenario C, Scenario D, and Scenario E in our focal watersheds (Spring Creek, Mahantango Creek, Conewago Creek, and Manokin River). Local watershed concerns and suggestions for the overall project were obtained from our watershed stakeholders, Community Partners Council (CPC), and Science Advisory Committee (SAC). This information formed the basis for the final revisions made to the latter scenario runs. As each team worked on their individual tasks through the winter, spring and summer of 2016, internal project meetings were held regularly to go over each team’s results and discuss how those results could be used by other teams and integrated to form the major findings, messages, and lessons learned from the project.
Significant Findings:
- Nutrient accounting helps to raise awareness of the sources of nutrients and the problems caused by nutrient pollution, while nutrient budgets provide a framework for benchmarking the current situation and for assessing future progress. However, quantifying the fluxes remains challenging and highlights the need for long term monitoring & data availability.
- Inputs of nutrients to the mid-Atlantic region have been increasing, largely due to human activities associated with agricultural food production and, to a lesser extent, fossil fuel combustion.
- Multiple modeling and ecosystem approaches indicate that space, place, and time of stressor and management-related activities matter greatly.
- The economic returns from local nutrient interventions reflect a cascade of accumulating benefits as water quality is improved through downstream stream systems and the Chesapeake Bay.
- Stakeholder meetings indicate that local communities are not being effectively informed and engaged in state and regional level planning.
Project 1
Major Activities. We are developing a contemporary account of nitrogen in the mid-Atlantic region. We have completed calculations for 2002, and are nearly complete with calculations for 2012. Nitrogen inputs include deposition, fertilizer, fixation, and tranfers in food & feed (including information on human consumption, crop and animal production, animal manure, human waste (septic and sewer). Results are being reported by state, and by hydrologic unit code.
Toward quantifying atmospheric inputs to the budgets, we have developed high resolution models of wet nitrogen deposition to the Chesapeake Bay, for nitrate and ammonium, from 1983-2014. We compared our estimates to lower resolution simulations from EPA models (community multi-scale air quality (CMAQ), total deposition maps (TDEP). We quantified differences in the wet deposition simulations using high-spatial-resolution synoptic precipitation data (from radar) to lower-spatial-resolution synoptic precipitation data (from the North American Land Data Assimilation System (NLDAS-2) that is used in the Chesapeake Bay model. We estimated dry atmospheric nitrogen deposition. The Chesapeake Bay Program is using our data in their model (high resolution simulations forced by NLDAS-2), and preliminary results have been delivered to Bay Program staff. In a separate project, we are quantifying inputs of organic matter (including N) to watersheds; to fill in missing information; where total N inputs must include wet+dry; and inorganic+organic species.
Toward exploring processes controlling nutrients in stream and river corridors, we considered relationships between nitrogen inputs to watersheds (from all sources) and nitrogen exports (to rivers at the watershed outlets) at multiple spatial and temporal scales; and by land use (agricultural, forested, urban). Further, we are quantifying factors affecting riverine N loads in the focal catchments. These efforts are ongoing.
Key Outcomes and Achievements. (1) Nutrient accounting helps to raise awareness of the sources of nutrients and the problems caused by nutrient pollution. (2) Nutrient budgets provide a framework for benchmarking the current situation and for assessing future progress. (3) Quantifying the fluxes remains challenging and highlights the need for long term monitoring & data availability. (4) Space and place matters: a targeted approach may be beneficial toward solving nitrogen pollution problems. (5) Inputs of nutrients to the mid-Atlantic region have been increasing, largely due to human activities associated with agricultural food production and, to a lesser extent, fossil fuel combustion. (6) Despite the obvious benefits of a plentiful supply of food & energy, the adverse consequences associated with the accumulation of reactive nitrogen in the environment are large, with implications for human health and the environment. (7) The greater the inputs of nutrients the landscape, the greater the potential for negative effects, including greenhouse gas production, ground level ozone, acid rain, degradation of soils and vegetation, acidification of river, lakes & streams, and coastal hypoxia & eutrophication. (8) Substantial efforts are needed in order to mitigate or reverse the effects of nutrient pollution in the Chesapeake Bay and its watershed. Conservation of natural resources in their native state, watershed management with BMPs, engineering approaches to treat and recover livestock waste, improved motor vehicle efficiencies, improved use of fertilizers, better landscapes, creation of wetlands, reductions in airborne emissions, and advances in wastewater treatment may all be beneficial.
Project 2
Major Activities. For task 1 (database and model fusion), we added the Gridded Soil Survey Geographic Database (GSSURGO) in PIHM compatible form and added an algorithm to read and condition the NLDAS climate database. We also combined the hydrological cycle attributes from PIHM and Cycles models to create a fused version (C-PIHM). For task 2 (multi-model comparison), we completed model calibration of WE38, a small sub-watershed of Mahantango Creek containing very detailed historic data measurements) and are setting up simulations in the remaining CNS focal watersheds (Spring Creek, Conewago Creek, and Manokin River). Developing a simulation model in PIHM for the Manokin, a relatively flat landscape in the Coastal Plain, has been difficult, requiring utilization of the drainage ditch network.
Key Outcomes and Achievements. Hydroterre (PSU’s in-house webservice for national data) was adapted and delivered for use in model simulations and accessible to any user (HydroTerre: Data services | Penn State Exit ). We completed fusion of the Penn State Integrated Hydrologic Model (PIHM) and Cycles to form C-PIHM, a functioning object-oriented, spatially-distributed hydrologic, nutrient cycling and watershed model designed to compute infiltration, groundwater recharge, lateral transport, evaporation and transpiration to simulate nutrient leaching under various land management/BMP scenarios. GitHub, a private portal, was set up to store and trach software code changes and distribute updated versions of Cycles, PIHM, and C-PIHM.
Project 3
Major Activities. Baseline ecological condition was determined at three assessment levels (coarse landscape, rapid stream/wetland/riparian, and intensive macroinvertebrate Index of Biotic Integrity) for multiple sub-basins within the Mahantango Creek, Conewago Creek, and Spring Creek watersheds. Restricted access limited assessments of the Manokin River to the stream habitat condition assessments in the stream wetland riparian (SWR) Index. We compared results between assessment levels to ascertain if coarser assessments could be used in place of more intensive assessments.
To compare SWAT model estimates of nutrient and sediment to ecological condition, sub-basins were delineated in SWAT for each monitoring point. We then compared changes in nutrient and sediment concentrations to changes in ecological condition across sub-basins. To determine if SWAT model relatonships with ecological condition improve at finer spatial scales, the Mahantango Creek watershed was evaluated in 3 ways: (1) monitoring points located within WE38, a small sub-basin of Mahantango Creek containing long-term water quality and field (e.g., crop rotations) management data, and the subject of the finest scale SWAT modeling; (2) monitoring points located in the rest of the watershed, typically larger streams; and (3) all monitoring points combined. In addition, SWAT model outputs were provided at multiple spatial and temporal scales.
To translate ecological condition to ecosystem services, we are evaluating carbon sequestration (amounts of carbon stored and sequestered in different types of carbon pools), flood storage and desynchronization (measures and scaling of flooding and floodplains in temperate riparian buffers), biodiversity (ranking multiple levels of biological assessments), water purification (association of assessment levels with water quality), and water-based recreation (association of selected stressors with degraded recreational experience).
Key Outcomes and Achievements. Although condition scores between assessment levels demonstrated positive relationships, results indicated landscape assessments typically scored sites in poorer condition, SWR assessments normally rated sites in suboptimal or marginal condition, while the intensive assessments ranked sites across a greater range of condition categories. Comparisons of assessment results for WE38 with results from the rest of the Mahantango Creek watershed revealed apparent differences in stressors and community responses, which are most likely due to stream size.
SWAT model comparisons with ecological metric results in WE38 revealed (1) accounting for instream processing of nutrients from upstream contributing reaches and local landscape and habitat influences greatly improves the ability of SWAT to predict ecological condition; (2) nutrients were highly correlated with each other, displaying similar patterns across spatial scales; (3) in contrast to SWAT-modeled estimates, grab samples of nutrients showed no relationship; and (4) annual averages (or spring averages to capture more peak flows) are better for analyzing relationships between nutrients and ecological condition than fall and summer averages. Preliminary results comparing SWAT runs and ecological metrics in the entire Mahantango Creek watershed supported many of the conclusions gained from the WE38 study and also found stronger correlations of modeled nitrate, total nitrogen, total phosphorus and mineral phosphorus concentrations with ecological metrics in the WE38 watershed than in the entire Mahantango Creek watershed when modeled at the scale of the local contributing area. No correlations were found with SWAT data modeled at larger spatial scales. SWAT/metric results for the rest of the Mahantango watershed (sans WE38) have not been analyzed yet, except through multivariate analysis of SWAT results with macroinvertebrate community composition data (i.e. relative abundances). These results revealed stronger associations between all modeled nutrient concentrations and ecological condition in the rest of the Mahantango watershed than in WE38. We will continue to explore these patterns as more SWAT results come in from Conewago Creek. Analyzation of the Spring Creek modeling and ecological results has been difficult, as this watershed is comprised primarily of limestone streams. Although relationships between macroinvertebrate communities and nutrients were discerned, they do not appear to be related to water quality. Impairment in a limestone stream is more likely to occur from substantial amounts of surface flow entering from pipes or other connections than from nutrients that typically get diluted from the large quanitites of deep groundwater. In addition, land use and physical habitat are also poor indicators of impairment.
Findings from exploring the carbon sequestration ecosystem service show that three pools hold the majority of carbon—soil, above-ground woody, and below-ground (roots). These sites span 3 of the 4 ecoregions in the CNS project (not the Manokin River of the Coastal Plain). We are aligning carbon values with expected vegetation (successional stage) and soil (degree of wetness) conditions found at sample sites throughout each watershed based on variables obtained from the landscape and SWR assessements. These estimates will also be used to forecast changing conditions under each scenario.
Significant Findings. Although additional work is needed, our initial conclusions are that space, place, and time matter. This applies to modeling decisions (e.g., entire basin vs local contributing area, overland vs instream, spring vs summer) and monitoring decisions (e.g., small streams vs large streams), any of which can affect the resulting data and relationships. Overall, however, SWAT modeling at finer spatial scales combined with targeting sub-basins (i.e. matching models to monitoring locations) appears to improve our ability to identify connections between model outputs of nutrients and sediment and ecological condition. This understanding may help define the link between the development and reporting of water quality standards (based on condition assessments), total maximum daily load (TMDL) development (based on water pollution models), and monitoring progress toward meeting water quality goals.
Project 4
Major Activities. Team 4 compared SWAT and Chesapeake Bay Model simulation results for each of the two Ridge and Valley province watersheds (Spring Creek, Mahantango). BMP cost-effectiveness selection and placement in each of the watersheds was then modified based on BMP application on acreage defined in the watershed implementation plan (WIP) and on BMP application in order of BMP cost.
Progress continued on a modeling study evaluating the trade-offs in phosphorus loss due to applying manure frequently during fall and winter, but at low rates, versus storing manure throughout the season or year and then applying at high rates in the spring and/or fall, are unclear. We simulated seasonal manure application timing and storage effects on phosphorus loss in a Pennsylvania watershed.
The Manokin Watershed on Maryland’s Eastern Shore has proven to be a modeling challenge not only due to its very flat terrain but its history of heavy poultry litter applications and the resulting high P levels in the soil. We made substantial progress on a suitable baseline representation in SWAT for the Taylor Branch subwatershed.
In year 3, Team 4 finalized the alternative practices to be considered for Conewago, based on the procedures used for Mahantango and Spring Creek. Additionally, simulation models for alternative dairy cropping conservation systems in the Spring Creek watershed were designed, based on previous field work. Preliminary results demonstrate the potential for improving watershed-level water quality through locally-appropriate variations of conservation cropping.
Key Outcomes and Achievements. Between the SWAT and Bay simulation models, the improvement in sediment loadings predicted by implementing the Bay TMDL was similar. However, SWAT predicted about half the improvement in N as did the Bay Model. For P loadings, predictions were similar for Spring Creek, but for Mahantango SWAT again predicted only half the improvement as did the Bay model.
Regarding phosphorus tradeoffs, winter and fall applications of manure resulted in risk of larger annual phosphorus losses from fields than spring application, but phosphorus loss could be reduced by applying manure to low-slope fields, not applying near streams, increasing crop cover in fall and winter, and decreasing manure rates. Although 12-month storage across the watershed (that is, spreading all manure in the spring), reduced total yearly amounts of phosphorus lost, compared to 6-month or 3-month storage, it led to great peaks of phosphorus concentrations in the stream in spring. Results point to the need to assess trade-offs associated with change in manure storage capacities in the region.
Significant Findings. (1) Spring manure application reduces annual P loss but increases seasonal loading; (2) Targeting application to low-slope, distant fields reduces stream P loadings; (3) Cover crops reduce field-level P losses, regardless of almost all other factors; (4) 12-month storage with spring application reduces dissolved, but not total, P loss.
Project 5
We continued to develop the collaborative project web portal (Center for Nutrient Solutions | Penn State Exit ) that enables team scientists, collaborators, and stakeholders to share information as well as communicate project work both internally and publicly. We prototyped a map-based web application to visualize outputs from the pilot scenario runs.
Project 6
Major Activities. A prototype GIS-based system has been developed that, for a specific intervention in a target watershed, (1) incorporates water quality changes from SWAT model runs done by Team 4; (2) models changes in water quality downstream of target watersheds, using delivery ratios obtained from the Bay Program; (3) calculates baseline values, with-intervention values, and changes in the Water Quality Index for each stream reach in the targeted watershed and for each downstream reach to the Bay; (4) calculates the resulting change in water quality in the Bay; (5) calculates the average benefit from the intervention to households living in different places relative to the target watershed; (6) multiplies average benefit per household by household density, to calculate spatially-specific total benefit from the intervention; and (7) aggregates total benefit across space to generate total benefit for each State in the basin. The system has been used to calculate the value of ecosystem services generated by the WIP scenario in the Mahantango watershed.
Key Outcomes and Achievements. Mahantango Creek WIP scenario results are as follows: (1) Benefits are highest for households located close to the targeted watershed and those living close to the Susquehanna River immediately downstream from the confluence with the Mahantango. (2) Regarding water quality improvement in the Bay, the WIP scenario interventions accomplish only a small percentage of the total TMDL goals. The change in nutrient flows into the Bay resulting from the scenario are calculated, and calculated as a percentage of the reductions required to meet TMDL goals. This percentage is then multiplied by the total benefit estimated in the EPA study to calculate the benefit from this scenario arising from improved water quality in the Bay. In this case, that calculated benefit was $11.6 million per year. Because of the way the EPA measured the benefit from improved Bay water quality, this value cannot be allocated across states.
Significant Findings. An important discovery from this effort is that the benefit from improved Bay water quality is much larger than the total benefit from improved river and stream water quality. The system will be used for other scenarios and other watersheds as developed by Teams 1, 2, and 4 to determine whether this result holds more generally.
Project 7
Major Activities. We continued to lead the project efforts toward community engagement through meetings with our Community Partners Council (CPC) and local watershed stakeholders. During this report period, we held several significant meetings with both that resulted in an increased level of collaboration and assurances that the research coming out of the Center will be connected to decision makers and stakeholders at all levels. The information gathered at these meetings was highly valuable and allowed us to piece together the nuts and bolts of our local and transformative scenarios.
Key Outcomes and Achievements. Stakeholder engagement results suggested standard approaches to watershed management and approaches designed entirely for pollutant reduction (e.g., WIPs) are less likely to produce effective action at local levels where desires and concerns of the community differ from regional goals. This information underscored the need for devleping multi-objective local scenarios and provided guidance for tailoring Scenario D to each watershed.
After consideration of the local water quality objectives and other local objectives beyond water quality, the following scenarios were developed for the four pilot watersheds. BMPs meant to address the sources of local water quality impairment (in most cases sediment) were chosen as top tactics, as these will be best able to meet local water quality goals. Next, interventions were chosen to meet other local objectives (e.g., cost effective BMPs to enhance bottom lines would help to preserve farming and rural lifestyle). Finally, specific placement of BMPs was suggested based on feedback of stakeholders and the need to meet certain local objectives identified by the watershed communities.
Significant Findings. We are finding varying levels of understanding of what regional water quality goals (i.e. TMDLs, WIPs) mean for local water quality stakeholders. While agricultural sector have low awareness with little communication of how WIPs relate to their management directives and goals, municipal authorities are more aware of challenges and need to meet water quality directives but are often uncertain of specific actions to meet those requirements.
Future Activities:
A top priority for the year is completing the individual team projects followed by synthesis activities across teams, which will be organized around the development of key messages of the research in collaboration with watershed stakeholders and the Community Partners Council.
Project 1
Activities for the upcoming year include (1) finalizing contemporary spatially explicit nutrient budgets, and (2) using these nutrient budgets to quantify the nitrogen and phosphorus inputs by watershed and relate these watershed drivers to intervention strategies.
Project 2
For next year, we plan to: (1) add rock volume, which drives the hydrological properties of the soil significantly, to the G-SSURGO database to improve model simulations; (2) add phosphorus cycling and stream processes to C-PIHM; (3) apply model to watershed scenarios to look at (a) impact on water budgets, (b) impacts on nutrient budgets, and (c) impacts on combined water and nutrient budgets; (4) identify ways to exploit model differences (e.g., SWAT vs. PIHM) to improve BMP targeting and optimization strategies; and (5) prepare publications on the distributed C-PIHM model, including a model presentation manuscript, an exercise describing the impact of grid size on modeled outputs, and representing the impact of targeting in the landscape on nutrients in streams.
Project 3
Final SWAT runs for the Conewago watershed are nearing completion. Although initial comparisons between modeled estimates of nutrients and sediment at various spatial and temporal scales revealed at best weak relationships, this is not surprising considering the fact that ecological metrics represent responses to multiple factors, not just nutrients and sediment. Further analysis will continue, focusing primarily on finalizing the relationship between SWAT-modeled nutrient runoff and ecological condition and determining the best predictive factors for suggesting ecological changes resulting from each CNS scenario.
We will complete the analyses underway for ecosystems services, as outlined above and evaluate the likely effects of different BMPs from the scenarios on each of the five services. These will be compared within and across watersheds.
Project 4
For next year, we plan to: (1) add rock volume, which drives the hydrological properties of the soil significantly, to the G-SSURGO database to improve model simulations; (2) add phosphorus cycling and stream processes to C-PIHM; (3) apply model to watershed scenarios to look at (a) impact on water budgets, (b) impacts on nutrient budgets, and (c) impacts on combined water and nutrient budgets; (4) identify ways to exploit model differences (e.g., SWAT vs. PIHM) to improve BMP targeting and optimization strategies; and (5) prepare publications on the distributed C-PIHM model, including a model presentation manuscript, an exercise describing the impact of grid size on modeled outputs, and representing the impact of targeting in the landscape on nutrients in streams.
Project 5
Based on feedback from the Community Partners Council and Science Advisory Committee at the December All Hands meeting, we are formulating a plan to design and implement multiple interactive web graphics/applications to illustrate specific concepts and outcomes from the modeling efforts. Our original plan was to design a single Web application to enable users to explore inputs and outputs of all model runs. However, discussions regarding the prototype resulted in the decision to select smaller sets of compelling data/information and present them individually in an effort to aid user understanding.
Project 6
Activities for the upcoming year include: (1) apply the system to value ecosystem services for all scenarios generated by Teams 1, 2, and 4; (2) incorporate estimates of cost savings to municipal water systems from decreases in nitrogen concentrations in source water streams and rivers; and (3) work with Team 3 to incorporate carbon sequestration benefits from specific BMPs.
Project 7
Major activities for the upcoming year include (1) reconvening stakeholder meetings in all four watersheds to hold "watershed planning" charrettes to explore the outcomes of scenario runs; (2) develop and deliver workshop to share research results (in collaboration with other high priority research and policy initiatives); (3) develop case study of watershed success stories; (4) focus on establishing a succinct set of "tried and true" practices that hit a sweet spot of local water quality, ecosystem services, and nutrient reductions that could then be used to create a validated “short cut” for watersheds without extensive data modeling recourses.
Journal Articles: 14 Displayed | Download in RIS Format
Other center views: | All 57 publications | 14 publications in selected types | All 14 journal articles |
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Amin MGM, Veith TL, Collick AS, Karsten HD, Buda AR. Simulating hydrological and nonpoint source pollution processes in a karst watershed: a variable source area hydrology model evaluation. Agricultural Water Management 2017;180(Part B):212-223. |
R835568 (2016) R835568 (2017) |
Exit Exit Exit |
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Amin M, Veith T, Shortle J, Karsten H, Kleinman P. Addressing the spatial disconnect between national-scale total maximum daily loads and localized land management decisions. JOURNAL OF ENVIRONMENTAL QUALITY 2020;49(3):613-627. |
R835568 (Final) |
Exit Exit |
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Coi D, Ready R, Shortle J. Valuing water quality benefits from adopting best management practices:A spatial approach. JOURNAL OF ENVIRONMENTAL QUALITY 2020;49(3):582-592. |
R835568 (Final) |
Exit Exit |
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DeWalle DR, Boyer EW, Buda AR. Exploring lag times between monthly atmospheric deposition and stream chemistry in Appalachian forests using cross-correlation. Atmospheric Environment 2016;146:206-214. |
R835568 (2016) R835568 (2017) |
Exit Exit Exit |
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Horan R, Shortle J. Endogenous Risk and Point-nonpoint Uncertainty Trading Ratios. AMERICAN JOURNAL OF AGRICULTURAL ECONOMICS 2017;99(2):427-446. |
R835568 (Final) |
Exit Exit |
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Iavorivska L, Boyer EW, Miller MP, Brown MG, Vasilopoulos T, Fuentes JD, Duffy CJ. Atmospheric inputs of organic matter to a forested watershed: variations from storm to storm over the seasons. Atmospheric Environment 2016;147:284-295. |
R835568 (2016) R835568 (2017) |
Exit Exit Exit |
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King MD, Bryant RB, Saporito LS, Buda AR, Allen AL, Hughes LA, Hashem FM, Kleinman PJ, May EB. Urea release by intermittently saturated sediments from a coastal agricultural landscape. Journal of Environmental Quality 2017;46(2):302-310. |
R835568 (2017) |
Exit Exit Exit |
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Kuwayama Y, Olmstead S. Hydroeconomic modeling of resource recovery from wastewater:Implications for water quality and quantity management. JOURNAL OF ENVIRONMENTAL QUALITY 2020;49(3):593-602. |
R835568 (Final) |
Exit Exit |
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Leonard L, Duffy CJ. Automating data-model workflows at a level 12 HUC scale: watershed modeling in a distributed computing environment. Environmental Modelling & Software 2014;61:174-190. |
R835568 (2014) R835568 (2015) R835568 (2016) |
Exit Exit Exit |
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Miller MP, Boyer EW, McKnight DM, Brown MG, Gabor RS, Hunsaker CT, Iavorivska L, Inamdar S, Johnson DW, Kaplan LA, Lin H, McDowell WH, Perdrial JN. Variation of organic matter quantity and quality in streams at Critical Zone Observatory watersheds. Water Resources Research 2016;52(10):8202-8216. |
R835568 (2016) R835568 (2017) |
Exit Exit |
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Ranjan R, Shortle J. Protecting and restoring aquatic ecosystems in multiple stressor environments. Water Economics and Policy 2017;3(2):650011. |
R835568 (2016) R835568 (2017) |
Exit Exit |
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Sebestyen SD, Shanley JB, Boyer EW, Kendall C, Doctor DH. Coupled hydrological and biogeochemical processes controlling variability of nitrogen species in streamflow during autumn in an upland forest. Water Resources Research 2014;50(2):1569-1591. |
R835568 (2015) R835568 (2016) |
Exit Exit Exit |
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Shortle J, Horan RD. Nutrient pollution: a wicked challenge for economic instruments. Water Economics and Policy 2017;3(02):1650033. |
R835568 (2016) R835568 (2017) |
Exit |
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Williams MR, Buda AR, Elliott HA, Hamlett J, Boyer EW, Schmidt JP. Groundwater flow path dynamics and nitrogen transport potential in the riparian zone of an agricultural headwater catchment. Journal of Hydrology 2014;511:870-879. |
R835568 (2014) R835568 (2015) R835568 (2016) |
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Supplemental Keywords:
Nutrient pollution, best management practices, nitrogen and phosphorus budgets, community engagement, hydrological models, stakeholders, shared discovery, scenarios, partnership, decision support, Pennsylvania Integrated Hydrologic Model (PIHM), cycles, agro-ecosystem models, model intercomparison, HydroTerre, cyber-infrastructure, nutrient and pollution transformation and transport, SWAT modeling, tactical interventions, Stream-Wetland-Riparian Index, ecological assessment, ecosystem services, nonmarket valuation, aquatic macroinvertebrates, watershed planning, Chesapeake Bay, Susquehanna River, Mid-Atlantic Region;Relevant Websites:
- Center for Nutrient Solutions | Penn State Exit
- Agricultural Research Service | United States Department of Agriculture
- Penn State » Ag Sciences » Environment and Natural Resources Institute Exit
- Penn State Integrated Hydrologic Modeling System Exit
- HydroTerre: Data services | Penn State Exit
- Riparia | Penn State Exit
- Elizabeth W. Boyer, Ph.D. | Penn State Exit
- Cycles | Kemanian Agroecosystems Modeling Laboratory | Penn State Exit
Progress and Final Reports:
Original AbstractThe perspectives, information and conclusions conveyed in research project abstracts, progress reports, final reports, journal abstracts and journal publications convey the viewpoints of the principal investigator and may not represent the views and policies of ORD and EPA. Conclusions drawn by the principal investigators have not been reviewed by the Agency.