S1063: Quantification of best management practice effectiveness for water quality protection at the watershed scale

(Multistate Research Coordinating Committee and Information Exchange Group)

Status: Inactive/Terminating

SAES-422 Reports

Annual/Termination Reports:

[10/31/2015] [11/01/2016] [01/03/2018] [01/18/2019] [09/11/2019] [01/01/1970]

Date of Annual Report: 10/31/2015

Report Information

Annual Meeting Dates: 05/13/2015 - 05/14/2015
Period the Report Covers: 01/01/2015 - 09/30/2015

Participants

Brian Benham (V Tech),
Prem Parajuli (MSS),
François Birgand (NCSU),
Indrajeet Chaubey (Purdue),
Fouad Jaber (TAMU),
Dharmendra Saraswat (U Ark/Purdue),
Aleksey Sheshukov (KSU),
Bruce Wilson (UMN),
Art Gold (URI),
Soni Pradhanang (URI),
Prasanta Kalita (UIUC),
Sunday Tim (IaSU),
Mike Hirschi (Waterborne Environmental),
Sara McMillan (Purdue),
Zhuping Sheng (TAMU),
David Sample (V Tech)

Brief Summary of Minutes

Accomplishments

<p>For this first year of this project, the accomplishments are goals set during the first annual meeting for each of objective. &nbsp;These accomplishments are summarized in tables corresponding to each obective.</p><br /> <p><strong>Objective 1:&nbsp;</strong>Monitor water quality from a variety of watersheds with a range of conditions (e.g., differing landuse and associated implemented BMPs, varying geographic/geologic conditions)</p><br /> <table><br /> <tbody><br /> <tr><br /> <td style="width: 486px; background-color: #c1ffc1;" width="486"><br /> <p>1.&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; Meta-analysis of past datasets of BMPs</p><br /> <p>a.&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; Add data to Art&rsquo;s existing meta-analysis of bioreactors. - output is removal/time/volume, effect of T&deg;C, design, hardwood/softwood, where they are functioning better/worse,</p><br /> <p>b.&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; do we include peer-reviewed journals&nbsp;or other non-public datasets?</p><br /> </td><br /> <td rowspan="4" width="90"><br /> <p style="text-align: center;">Easily attainable</p><br /> <p style="text-align: center;">&nbsp;</p><br /> <p style="text-align: center;">&nbsp;</p><br /> <p style="text-align: center;">&nbsp;</p><br /> <p style="text-align: center;"><strong>&darr;</strong>&nbsp;</p><br /> <p style="text-align: center;">&nbsp;</p><br /> <p style="text-align: center;">&nbsp;</p><br /> <p style="text-align: center;">&nbsp;</p><br /> <p style="text-align: center;">&nbsp;</p><br /> <p style="text-align: center;"><strong>&darr;</strong>&nbsp;&nbsp;</p><br /> <p style="text-align: center;">&nbsp;</p><br /> <p style="text-align: center;">&nbsp;</p><br /> <p style="text-align: center;">&nbsp;</p><br /> <p style="text-align: center;"><strong>&darr;</strong>&nbsp;&nbsp;</p><br /> <p style="text-align: center;">&nbsp;</p><br /> <p style="text-align: center;">&nbsp;</p><br /> <p style="text-align: center;">&nbsp;</p><br /> <p style="text-align: center;">&nbsp;</p><br /> <p style="text-align: center;"><strong>&darr;</strong>&nbsp;</p><br /> <p style="text-align: center;">&nbsp;</p><br /> <p style="text-align: center;">&nbsp;</p><br /> <p style="text-align: center;">&nbsp;</p><br /> <p style="text-align: center;"><strong>&darr;</strong>&nbsp;</p><br /> <p style="text-align: center;">&nbsp;</p><br /> <p style="text-align: center;">&nbsp;</p><br /> <p style="text-align: center;">Desirable</p><br /> <p style="text-align: center;">But not easy</p><br /> </td><br /> </tr><br /> <tr><br /> <td style="width: 486px; background-color: #9bcd9b;" width="486"><br /> <p>2.&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; Critique of monitoring:&nbsp;are we&nbsp;measuring the right thing?&nbsp;Are we considering the right factors for monitoring?</p><br /> <p>a.&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; Edict BMP monitoring guidelines</p><br /> <p>b.&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; Case studies are valid way of sharing results in other disciplines - is this an appropriate approach for a monitoring critique?</p><br /> <p>c.&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; High intensity sampling vs. low frequency: what are we really gaining by one or the other</p><br /> <p>d.&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; What can one do/obtain with EC, Q, pH, etc.?</p><br /> </td><br /> </tr><br /> <tr><br /> <td style="width: 486px; background-color: #6495ed;" width="486"><br /> <p>3.&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; Editorial article on BMPs in series</p><br /> <p>a.&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; When used in series to BMPs function synergistically?</p><br /> <p>b.&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; Are there rules for BMP placement in watersheds?</p><br /> </td><br /> </tr><br /> <tr><br /> <td style="width: 486px; background-color: #ffd39b;" width="486"><br /> <p>4.&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; New proposal effort: What is the impact of climate change on BMP&nbsp;design guidelines and predicted success</p><br /> <p>a.&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; Governing agencies do not measure each BMP but assign % removal based on design. What are the effects of changing precipitation patterns on this removal efficiency?</p><br /> <p>b.&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; How resilient are BMPs? If not resilient, what are the consequences&nbsp;of failure?</p><br /> <p>c.&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; Updating return intervals continuously so question related to older BMPs using &ldquo;old&rdquo; return intervals</p><br /> </td><br /> </tr><br /> </tbody><br /> </table><br /> <p>&nbsp;</p><br /> <p><strong>Objective 2:&nbsp;</strong>&nbsp;Develop and evaluate models for predicting BMP performance and water quality at the field and watershed-scales when considering climate change</p><br /> <p>&nbsp;</p><br /> <table width="575"><br /> <tbody><br /> <tr><br /> <td style="width: 462px; background-color: #c1ffc1;" width="462"><br /> <p>1.&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; Review paper &ndash; What current model does what BMP? Using what concept/simplification? Do current models sufficiently represent BMPs? (pick 10 models?)</p><br /> <p>a.&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; How does one modify design criteria in light of climate change? How robust are BMPs? What consequences of climate change on BMPs, and can they be modeled?</p><br /> <p>&nbsp;</p><br /> </td><br /> <td rowspan="4" width="114"><br /> <p style="text-align: center;">Easily attainable</p><br /> <p style="text-align: center;">&nbsp;&nbsp;</p><br /> <p style="text-align: center;"><strong>&darr;</strong>&nbsp;</p><br /> <p style="text-align: center;">&nbsp;</p><br /> <p style="text-align: center;"><strong>&darr;</strong>&nbsp;&nbsp;</p><br /> <p style="text-align: center;">&nbsp;</p><br /> <p style="text-align: center;"><strong>&darr;</strong>&nbsp;&nbsp;</p><br /> <p style="text-align: center;">&nbsp;</p><br /> <p style="text-align: center;">&nbsp;</p><br /> <p style="text-align: center;"><strong>&darr;</strong>&nbsp;</p><br /> <p style="text-align: center;">&nbsp;</p><br /> <p style="text-align: center;">&nbsp;</p><br /> <p style="text-align: center;">&nbsp;</p><br /> <p style="text-align: center;"><strong>&darr;</strong>&nbsp;</p><br /> <p style="text-align: center;">&nbsp;</p><br /> <p style="text-align: center;">&nbsp;</p><br /> <p style="text-align: center;">Desirable</p><br /> <p style="text-align: center;">But not easy</p><br /> </td><br /> </tr><br /> <tr><br /> <td style="width: 462px; background-color: #9bcd9b;" width="462"><br /> <p>2.&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; Produce new modules within existing models&nbsp;- use benchmark datasets to test these</p><br /> <p>b.&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; Most new modules created on modeling plateforms (e.g. SWAT) should be validated on benchmark datasets</p><br /> <p>c.&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; Generate a modeling QA/QC and accreditation</p><br /> <p>d.&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; Benchmark datasets require creating database for public access with citations</p><br /> <p>&nbsp;</p><br /> </td><br /> </tr><br /> <tr><br /> <td style="width: 462px; background-color: #6495ed;" width="462"><br /> <p>3.&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; BMPs in series/cumulative impacts&ndash; ties back to same issue raised during discussion of Objective 1.</p><br /> <p>e.&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; How do you modify design criteria in light of climate change?</p><br /> <p>f.&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; How are BMP spatial placement, cumulative vs. counteractive effects taken into account?</p><br /> </td><br /> </tr><br /> <tr><br /> <td style="width: 462px; background-color: #ffd39b;" width="462"><br /> <p>4.&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; Review of realtime datasets with new sensor data (see later discussion of this in Objective 3)</p><br /> <p>&nbsp;</p><br /> </td><br /> </tr><br /> </tbody><br /> </table><br /> <p>&nbsp;</p><br /> <p><strong>Objective 3:</strong>&nbsp;Develop methods to quantify modeling and monitoring uncertainty as affected by model representations of watershed processes and model input data</p><br /> <table width="575"><br /> <tbody><br /> <tr><br /> <td style="width: 448px; background-color: #c1ffc1;" width="448"><br /> <p>1.&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; Quality control&nbsp;methodology to reduce uncertainty in sampling collection&nbsp;and holding.</p><br /> <p>a.&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; Bruce suggested a standards/protocol: "ASABE engineering practice"</p><br /> <p>b.&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; EPA 319 QA/QC document designed for discrete sampling. needs to include sensors as well.</p><br /> <p>&nbsp;</p><br /> </td><br /> <td rowspan="6" width="127"><br /> <p style="text-align: center;">Easily attainable</p><br /> <p style="text-align: center;">&nbsp;</p><br /> <p style="text-align: center;">&nbsp;</p><br /> <p style="text-align: center;">&nbsp;&nbsp;</p><br /> <p style="text-align: center;"><strong>&darr;</strong>&nbsp;</p><br /> <p style="text-align: center;">&nbsp;</p><br /> <p style="text-align: center;">&nbsp;</p><br /> <p style="text-align: center;">&nbsp;</p><br /> <p style="text-align: center;"><strong>&darr;</strong>&nbsp;&nbsp;</p><br /> <p style="text-align: center;">&nbsp;</p><br /> <p style="text-align: center;">&nbsp;</p><br /> <p style="text-align: center;">&nbsp;</p><br /> <p style="text-align: center;"><strong>&darr;</strong>&nbsp;&nbsp;</p><br /> <p style="text-align: center;">&nbsp;</p><br /> <p style="text-align: center;">&nbsp;</p><br /> <p style="text-align: center;">&nbsp;</p><br /> <p style="text-align: center;">&nbsp;</p><br /> <p style="text-align: center;"><strong>&darr;</strong>&nbsp;</p><br /> <p style="text-align: center;">&nbsp;</p><br /> <p style="text-align: center;">&nbsp;</p><br /> <p style="text-align: center;">&nbsp;</p><br /> <p style="text-align: center;"><strong>&darr;</strong>&nbsp;</p><br /> <p style="text-align: center;">&nbsp;</p><br /> <p style="text-align: center;">&nbsp;</p><br /> <p style="text-align: center;">Desirable</p><br /> <p style="text-align: center;">But not easy</p><br /> </td><br /> </tr><br /> <tr><br /> <td style="width: 448px; background-color: #9bcd9b;" width="448"><br /> <p>2.&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; SW&nbsp;BMP&nbsp;sampling - composite vs discretized data</p><br /> <p>&nbsp;</p><br /> </td><br /> </tr><br /> <tr><br /> <td style="width: 448px; background-color: #6495ed;" width="448"><br /> <p>3.&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; Effect of sampling frequency on monitoring uncertainty and model output</p><br /> <p>a.&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; A lot of high temporal frequency sensor data within the group</p><br /> <p>b.&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; Run existing engines to quantify uncertainties and extract rules</p><br /> <p>c.&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; Outliers&nbsp;- do they cluster by region, seasonality,</p><br /> <p>d.&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; Run Global Sensitivity Analysis (GSA) to apportion the source of uncertainty for monitoring</p><br /> <p>&nbsp;</p><br /> </td><br /> </tr><br /> <tr><br /> <td style="width: 448px; background-color: #ffd39b;" width="448"><br /> <p>4.&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; Model calibration - broad opinion paper: uncertainty bands in model input and output to see if they overlap.</p><br /> <p>a.&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; paper on calibration&nbsp;ignores uncertainty in input; next paper went a little further (basic guidelines) -&nbsp;issues of temporal/spatial scales, constituent specific.</p><br /> <p>&nbsp;</p><br /> </td><br /> </tr><br /> <tr><br /> <td style="width: 448px; background-color: #ffd39b;" width="448"><br /> <p>5.&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; Land use / climate change projections, can use techniques such as GSA to apportion sources of error to LU and CC.</p><br /> <p>&nbsp;</p><br /> </td><br /> </tr><br /> <tr><br /> <td style="width: 448px; background-color: #ffd39b;" width="448"><br /> <p>6.&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; Paper on protocol (scholarship of sharing data) - thought piece that lays this out. Many papers on this already, our contribution to this literature would be specific to the high resolution sensor data</p><br /> <p>&nbsp;</p><br /> </td><br /> </tr><br /> </tbody><br /> </table>

Publications

<p>Between the first meeting (May 2015) and the writing of this report (September 2015), there has not been substantial time to generate publications relevant to the project. &nbsp;A substantial list of&nbsp;publications will be available in the final report of year 2.</p>

Impact Statements

  1. A conference on quantification of best management practice effectiveness for water quality protection at the watershed and subwatershed scales
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Date of Annual Report: 11/01/2016

Report Information

Annual Meeting Dates: 09/12/2016 - 09/13/2016
Period the Report Covers: 10/01/2015 - 09/30/2016

Participants

David Sample (Virginia Tech); François Birgand (NCSU) Fouad Jaber (TAMU) ; Changyoon Jeong (LSU); Trisha Moore (KSU); Joel Paz (MSU); Rabin Bhattarai (UIUC); Eric Drumm (UTK); Parajuli, Prem (MSU) Soni Pradhanang (URI) Ramirez Avila, John (MSU); Luis Alfonso Laurens Vallejo (MSU); Aleksey Sheshukov (KSU); Zhulu Lin (NDSU); Adel Shirmohammadi (UMD); Sara McMillan (Purdue); Jasmeet Lamba (Auburn)

Brief Summary of Minutes

Accomplishments

<p>The principle focus of this project is to evaluate the effectiveness of best management practices (BMPs) at the watershed scale. This includes the water quality and environmental benefits of mitigation practices as well as their cost effectiveness. This will be achieved through monitoring at sub-watershed scales, modeling at larger spatial scales, and analysis of uncertainty in both monitoring and modeling efforts. This report summarizes the first year of activity on this project and the following sections highlight accomplishments from project teams.</p><br /> <p><em>Objective 1: </em><em> Monitor water quality from a variety of watersheds with a range of conditions (e.g., differing landuse and associated implemented BMPs, varying geographic/geologic conditions).</em></p><br /> <p><span style="text-decoration: underline;">University of Rhode Island (A Gold, S Pradhanhang, K Addy) </span>Water quality sensors (YSI EXO2 and the s::can spectro::lyser) were deployed in three streams from October 2015 to early January 2016 and April to September 2016. The three streams were selected as each watershed has a different dominant land use &ndash; forested, agricultural, and urban. Grab samples were collected weekly during baseflow and storm event samples were collected using a series of samples via an ISCO automatic water sampler during nine rain events from October 2015-September 2016. We are collecting stream stage data every 10-30 minutes with HOBO water level data loggers. We finalized the stage to field measured discharge relationship with the goal of estimating pollutant fluxes in our streams.</p><br /> <p><span style="text-decoration: underline;">Mississippi State University (J Czarnecki)</span> The objective of this study was to quantify capture and use of water within tailwater recovery systems, including the tailwater recovery ditch (TWR) and the on-farm storage reservoir (OFS) so that the conservation benefit they provide could be evaluated. This effort resulted in a dataset of 31 systems, monitored in 15-min intervals over an entire year. Domain decomposition methods were employed to calculate volumes of water in systems with complicated geometric shapes of OFS based on USDA NRCS build designs and water levels collected with data loggers. Rainfall, evaporation, and infiltration volumes were also calculated. Using these values, future plans are to model the effects of climate change by altering the rainfall values. Systems had a net positive balance of approximately 2,200 ML of captured surface water. Losses from evaporation and infiltration were between 8.68 mm d<sup>-1</sup> and 10.97 mm d<sup>-1</sup> for TWR and 4.96 mm d<sup>-1 </sup> to 8.40 mm d<sup>-1</sup> for OFS. The highest losses occurred in the fall for TWR due to the installation cycle, whereas they were highest in the summer for OFS, driven by evaporation. Producers irrigated with an average of 41 ML (TWR) and 84 ML (OFS) of surface water. Irrigation levels were generally below thresholds set by the government for sufficient use. Some producers used their systems at high rates, capturing large volumes of surface water and re-using it for irrigation, while others used their systems very little.</p><br /> <p><em>Objective 2: Develop and evaluate models for predicting BMP performance and water quality at the field and watershed&shy;scales when considering climate change.</em></p><br /> <p><span style="text-decoration: underline;">Purdue University (S. McMillan)</span> We developed and implemented an integrated monitoring and modeling approach to address our goal of understanding and predicting the impact of stormwater best management practices in urban areas at the reach and watershed scales. We applied the Regional Hydro-Ecological Simulation System (RHESSys) model to define the relationship between stormwater mitigation and export of water and nutrients as a function of environmental and hydrometeorological drivers. We first constructed a model of the existing conditions in a larger suburban watershed that includes other land uses as well (e.g., forested, commercial). We also refined the modeling framework to directly represent multiple types of SCMs (e.g., wet ponds, wetlands) within the landscape and simulate their impacts on water, carbon and nitrogen cycling. These refinements included a new representation of SCM storage and drainage within the hillslope hydrology routing network and the inclusion of a SCM algae growth/decay biogeochemical cycling routine. These additions were successfully calibrated with monitoring data from individual BMPs. We are currently applying the revised version of RHESSys to evaluate how different SCM strategies at the watershed scale interact with climate scenarios to alter water and nutrient exports. Model-based scenarios will be designed to understand interactions among topography, the size and spatial arrangement of the SCMs, and climate and land use drivers. Bell, C. , S. McMillan, and C. Tague. 2017. A model of hydrology and water quality in stormwater control measures. Environmental Modeling and Software 95:29-47.</p><br /> <p><span style="text-decoration: underline;">University of Rhode Island (A Gold, S Pradhanhang, K Addy) </span>The SWAT watershed water quality model has been calibrated for streamflow and nitrate loadings in Maidford River (predominantly agricultural). Climate sensitivities to flow and nutrients loadings have been tested. Similarly a SWAT model has been developed for Cork Brook Watershed (predominantly forested) to assess thermally stressful events. We contributed to database development and statistical modeling efforts to predict riparian zone function with respect to nitrogen and phosphorus cycling in agricultural areas of glaciated regions.&nbsp;&nbsp; We also began to calibrate the Riparian Ecosystem Management Model (REMM) with new default model parameters specific to dominant riparian geomorphic types in these glaciated regions.</p><br /> <p><span style="text-decoration: underline;">Auburn University (P Srivastava)</span> We investigated potential changes in flow, Total Suspended Solid (TSS) and nutrient (nitrogen and phosphorous) loadings under future climate change, land use/cover (LULC) change and combined change scenarios in the Wolf Bay watershed, southern Alabama, USA. Four Global Circulation Models (GCMs) under three Special Report Emission Scenarios (SRES) of greenhouse gas were used to assess the future climate change (2016-2040). Three projected LULC maps (2030) were employed to reflect different extents of urbanization in future. Results indicate that if future loadings are expected to increase/decrease under any individual scenario, then the combined change will intensify that trend. Conversely, if their effects are in opposite directions, an offsetting effect occurs. Science-based management practices are needed to reduce nutrient loadings to the Bay.</p><br /> <p><em>Objective 3: Develop methods to quantify modeling and monitoring uncertainty as affected by model representations of watershed processes and model input data.</em></p><br /> <p><span style="text-decoration: underline;">North Carolina State University (F. Birgand) </span>The increasing availability and use of high-frequency water quality sensors has enabled unprecedented observations of temporal variability in water chemistry in aquatic ecosystems. However, we remain limited by the prohibitive costs of these probes to explore spatial variability in natural systems. To overcome this challenge, we have developed a novel auto-sampler system that sequentially pumps water from up to 12 different sites located within a 12 m radius to a single water quality probe. This system is able to generate high temporal frequency in situ water chemistry data from multiple replicated units during experiments as well as multiple sites and depths within natural aquatic ecosystems. Thus, with one water quality probe, we are able to observe rapid changes in water chemistry concentrations over time and space. Here, we describe the coupled multiplexer-probe system and its performance in two case studies: a mesocosm experiment examining the effects of water current velocity on nitrogen dynamics in constructed wetland sediment cores and a whole-ecosystem manipulation of redox conditions in a reservoir. In both lotic and lentic case studies, we observed minute-scale changes in nutrient concentrations, which provide new insight on the variability of biogeochemical processes. Moreover, in the reservoir, we were able to measure rapid changes in metal concentrations, in addition to those of nutrients, in response to changes in redox. Consequently, we believe that this coupled system holds great promise for measuring biogeochemical fluxes in a diverse suite of aquatic ecosystems and experiments. Birgand, F., Aveni‐Deforge, K., Smith, B., Maxwell, B., Horstman, M., Gerling, A.B. and Carey, C.C., 2016. First report of a novel multiplexer pumping system coupled to a water quality probe to collect high temporal frequency in situ water chemistry measurements at multiple sites. Limnology and Oceanography: Methods, 14(12), pp.767-783.</p><br /> <p>In our initial proposal, we put forth the following expected outcomes and impacts:</p><br /> <ol><br /> <li>Coordination of research and outreach programs involving the use of BMPs for watershed management and mitigating diffuse pollution and the effects of climate change and other emerging environmental issues.</li><br /> <li>New knowledge and exchange of ideas/information/data on the biophysical functioning of BMPs to enable the development of better BMP submodels and watershed and subwatershed models for simulating BMP effectiveness and uncertainties associated with their performance.</li><br /> <li>Publication of joint research articles on BMP performance and monitoring and modeling methods at the watershed and subwatershed scales.</li><br /> <li>Evaluation and standardization of uncertainty analysis techniques for quantifying uncertainties associated with BMP performance and model predictions of BMP effectiveness at the watershed and subwatershed scales.</li><br /> <li>A conference on quantification of best management practice effectiveness for water quality protection at the watershed and subwatershed scales.</li><br /> </ol><br /> <p>Although the project is just completing our year, we have made significant progress on the first objectives. The coordination of research and outreach programs has lead to joint proposal submissions, invited seminars between participating universities, outreach activities with state and local watershed groups, and co-mentoring of students. During our regional project meeting several synthesis papers were proposed and initial outlines have been developed. In addition, we conducted the first quantitative synthesis of denitrifying woodchip bioreactors, a BMP designed to remove nitrate from agricultural watersheds. The meta-analysis assessed nitrate removal across environmental and design conditions from 26 published studies, representing 57 separate bioreactor units. This meta-analysis was published in the Journal of Environmental Quality, and results will be shared with researchers and practitioners. Addy, K., Gold, A.J., Christianson, L.E., David, M.B., Schipper, L.A. and Ratigan, N.A., 2016. Denitrifying bioreactors for nitrate removal: A meta-analysis.&nbsp;Journal of environmental quality,&nbsp;45(3), pp.873-881.</p><br /> <p>&nbsp;</p>

Publications

Impact Statements

  1. The coordination of research and outreach programs has lead to joint proposal submissions, invited seminars between participating universities, outreach activities with state and local watershed groups, and co-mentoring of students.
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Date of Annual Report: 01/03/2018

Report Information

Annual Meeting Dates: 10/05/2017 - 10/06/2017
Period the Report Covers: 10/01/2016 - 09/30/2017

Participants

Prem Parajuli (MSU), Aleksey Sheshukov (KSU), Soni Pradhanang (URI), Sunday Tim (ISU), Sara McMillan (Purdue), Zhuping Sheng (TAMU), John Ramirez Avilla (MSU), Dwayne Edwards (Kentucky), Joby Czarnecki (MSU), Joel Paz (MSU), Rabin Bhattarai (UI-UC), Tulia Delgado (MSU), Laura Wilson (MSU).

Brief Summary of Minutes

The annual meeting held in Mississippi State University in 2017 focussed on addressing S1063 objectives, accomplishments, and identifying gaps. To address each objectives of S1063 project in a realistic way, the participants focused their brainstorming information/ideas on measuring the success of practices (structural and non-structural) in maintaining water quality. Watershed-scale modeling has primarily focused on agricultural BMPs using SWAT. The existing models such as SWAT, AnnAGNPS still require many modifications to represent physical processes better. Modifications such as including adding routine to account for overland flow/transport and enhance overall spatial representation were discussed. The participants also reviewed past goals and discussed about how much of those goals have been addressed. All the participants acknowledged that there is an opportunity to make a big contribution in this area from the scientific perspective (both monitoring and modeling) and in outreach and communication with stakeholders.


The group toured multiple types of BMPs that are constructed and monitored various sites within Mississippi State University, Starkville. All the participants agreed to focus on proposal/grant writing in upcoming year(s). Some of the areas for colloaborative proposal included, but not limited to:



  • Ephemeral Gully Urban Sediment  

  • Safety concerns coupling waste water treatment with on-farm pond water irrigation

  • Ecological Ramifications of waste water reuse reduction efficiency

  • AnnAGNPS-subroutine development-pond/tailwater

  • Regional project- regional P indices

  • AGU Special Session Proposal?

  • Water use/allocation in water stressed regions/agriculture-irrigation water

  • Research coordination network both in monitoring and modeling  

  • Urban/rural BMPs comparison of models model integration climate/BMPs evaluation

  • Field vs watershed scale evaluation


The group agreed on forming a working group and have a monthly conference call to address important objectives/goals.

Accomplishments

<p>The principle focus of this project is to evaluate the effectiveness of best management practices (BMPs) at the watershed scale. This includes the water quality and environmental benefits of mitigation practices as well as their cost effectiveness. This will be achieved through monitoring at sub-watershed scales, modeling at larger spatial scales, and analysis of uncertainty in both monitoring and modeling efforts. his report summarizes the first year of activity on this project and the following sections highlight accomplishments from project teams.&nbsp;</p><br /> <p><em>Objective 1: Monitor water quality from a variety of watersheds with a range of conditions (e.g., differing landuse and associated implemented BMPs, varying geographic/geologic conditions).</em></p><br /> <p><span style="text-decoration: underline;">Kansas State University (A. Sheshukov); </span>In Northeast Kansas, Kansas state University Team continued data collection on a no-till field that contained 4 well-identified ephemeral gullies. The collection process was based on the photogrammetry approach. Surveying equipment (camera, software, backpack, frame) was either purchased or custom-made in KSU-BAE. The team collected micro-topographic information at 8 survey dates. Weather data (precipitation, temperature) was collected sub-hourly. Data is being processed and analzyed. KSU Team (Dr. Trisha Moore, Dr. Aleksey Sheshukov, Dr. Dan Devlin, Mr. Ron Graber) worked with the City of Wichita on off- site BMP trading program. This program could be adapted by MS4 communities elsewhere as a means of integrating water.&nbsp;</p><br /> <p><span style="text-decoration: underline;">Mississippi State University (J Czarnecki, J. Paz): </span>MSU team is currently quantifying benefits of BMPs by evaluating performance at discrete points, for example, with ISCO water quality sensors placed on the landscape to sample water at key points. Considering erosion and surface water quality, transferring monitoring capabilities to unmanned aerial vehicle (UAV)-based platforms would allow regulators to monitor larger areas, and provide more data over continuous surfaces. A low-cost, off-the-shelf UAV can quickly and easily gather data necessary to construct 3D models of landscapes. Eroded areas are easy to identify, and areas of loss and deposition are visible. More research is needed to determine the sources and magnitude of error present in 3D surfaces before they can confidently be used in watershed models. OFWS systems have been increasingly implemented in agricultural fields in Mississippi and other farmed regions within the Lower Mississippi River Valley because of their nutrient reduction and water supply benefits. Our study provides important information and seasonal analysis of the discharged water that was monitored over the course of a year (December 22, 2015 to December 21, 2016) and its associated nutrient load, monitored from March 2012 to May 2017.</p><br /> <p><span style="text-decoration: underline;">Purdue University (S. McMillan): </span>Assessment of ecosystem services of urban rain gardens: The goal of this project is to quantify and compare multiple ecosystem services in rain gardens from two different climatic regions in the US. We instrumented three rain gardens in each city (Charlotte, NC and Lafayette, IN) to sample influent stormwater runoff and infiltrating water via lysimeters during summer 2017. We measured plant and insect biodiversity and recorded landscape and residential use characteristics in the vicinity of each rain garden. Lastly, are conducting seasonal measurements of denitrification rates (i.e., the conversion of nitrate into dinitrogen gas) at two depths (0-5 cm; 10-20 cm) to quantify nitrogen removal. We are currently analyzing data from our summer and fall sampling and will continue seasonal sampling through 2018 and will associate these functions with characteristics of the structure itself and attributes of surrounding areas. This research is supported by with two undergraduates at Purdue University and one MS student at the University of North Carolina Charlotte.</p><br /> <p><span style="text-decoration: underline;">Texas A &amp; M University (F. Jaber, Z. Sheng; C. Munster ): </span>Texas A&amp; M Continued to update GIS coverages for the watershed, sub-basins, irrigation districts and aquifers within the USDA NIFA study area (from San Marcial in New Mexico to Presidio, Texas), crop acreage and flow data at gauge stations, irrigation diversions. Updated Paso del Norte Watershed Council Website. Shared data and GIS coverages with irrigation districts and regional water planning groups as well as researchers.</p><br /> <p><span style="text-decoration: underline;">Texas A &amp; M University (F. Jaber):</span> Identification of sediment loading sources to urban lakes. Water quality samples and flow rates are being currently collected in Fort Worth from different parts of an urban water shed to determine the sources and landuses associated with sediment load to a residential lake in Fort Worth Texas. Automatic water samplers and bubbler flowmeters are used for this task. Stream flow sampling is currently occurring before streambank restoration (to occur in March next year) to establish baseline data.</p><br /> <p><span style="text-decoration: underline;">University of Arkansas (B. Haggard): </span>The accomplishments included (1) evaluating how water quality has been at Big Creek, a tributary to the Buffalo (National) River, which has been under scrutiny do to a hog farm which was permitted a few years ago (Sharpley et al., 2017), (2) updating the scientific community on where we are in terms of edge of field monitoring to help quantify effects of humn land use and BMPs on nutrient and sediment loads (Harmel et al., 2017), (3) help watershed managers use land use information to select areas for BMPs focus and implementation in the Ozark Highlands ecoregion (McCarty et al., 2017 - submitted), and (4) we evaluated floodplain soils as a potential phosphorus source and how water treatment residuals can be used to mitigate this source (Reavis and Haggard, 2016).</p><br /> <p><span style="text-decoration: underline;">University of Illinois, UC (R. Bhattarai): </span>UI-UC recently published a paper, where a ceramic pellet was manufactured using fly ash (mixed with clay and lime) for the removal of dissolved phosphorus. The results indicated that the developed pellets had the potential to treat contaminated water with high phosphorus concentration from the point and non-point sources. In the follow up study (the manuscript is in review), they evaluated the efficacy of using woodchips and fly ash pellet in flow-through tests for their abilities to remove nitrate and phosphate from the agricultural runoff. The results of this study suggest that woodchip denitrification followed by fly ash pellet filtration can be an effective treatment technology for nitrate and phosphate removal in subsurface drainage.</p><br /> <p><span style="text-decoration: underline;">University of Rhode Island (A Gold, S Pradhanang, K Addy): </span>From October 2016 to early January 2017 and April to September 2017, URI team deployed two sensors (the YSI EXO2 and the s::can spectro::lyser) in three RI streams (only two streams in 2017) to collect a variety of water quality parameters every 30 minutes. The three streams were selected as each watershed has a different dominant land use &ndash; forested, agricultural, and urban. Data is transmitted remotely into an Aquarius data management system. QA/QC on sensor data is completed through 2016. Grab samples were collected weekly during baseflow and collected a series of samples via an ISCO automatic water sampler during rain events in the fall of 2016. URI team is in the process of assessing relationships between sensor data and lab-analyzed field sample data to create site specific calibrations at the three streams for nitrate, dissolved organic carbon, phosphate, total phosphorus, total nitrogen, and TSS.&nbsp;&nbsp; Data processing and paper development is in process.</p><br /> <p><span style="text-decoration: underline;">University of Tennessee (E. Drumm): </span>While manmade slopes are traditionally constructed with planar cross sections, natural stable slopes are usually curvilinear with significant concavity on the profile. This concavity occurs as a result of evolutionary processes where rain-driven erosion and sediment transport are balanced through slope shape adjustments; at the point of equilibrium, a relatively steady concavity with a uniform erosion rate is observed over time. Nevertheless, a true equilibrium state would be possible only if mechanical stability is satisfied. In this study, concave profiles in rainfall erosion equilibrium were found based on the principles of the well-known RUSLE2 model. Results show the existence of a family of steady shapes satisfying the condition of uniform erosion rate. Those steady concave shapes that also satisfy long-term mechanical stability were then investigated.&nbsp;The overall results suggest that concave slopes can be constructed to achieve both minimal steady-state erosion equilibrium and mechanical stability, leading to more "natural" and sustainable landforms with minimal sediment delivery during initial slope adjustments.</p><br /> <p><span style="text-decoration: underline;">Virginia Polytechnic Institute (D. Sample); </span>A proposal for monitoring a single watershed and a single BMP in the City of Virginia Beach was approved in August of 2017 and is underway. Another proposal was developed for monitoring small watersheds with homogenous land uses and to monitor stage at weirs near watershed outlets across the City of Virginia Beach; for purposes of water quality and quantity calibration of watershed models. A proposal submitted in 2016 that would provide partial funding for monitoring three BMPs and associated urban catchments at the Science Museum of Virginia (SMV) in Richmond, in collaboration with Virginia State University (VSU) was resubmitted in 2017, and was funded. This project will provide training opportunities for undergraduate students and faculty at VSU in surface water monitoring techniques.</p><br /> <p>Objective 2 <em>: Develop and evaluate models for predicting BMP performance and water quality at the field and watershed&shy;scales when considering climate change</em></p><br /> <p><span style="text-decoration: underline;">North Dakota State University (Z. Lin) </span>NDSU team modified a SWAT (Soil and Water Assessment Tool) model for the Red River of the North Basin to evaluate the effects of installing buffer strips along streams and drainage ditches on downstream water quality loads. The buffer strip law in Minnesota requires landowners to establish and maintain buffers along public waterways. The buffer strips range from 16.5 ft (5.0 m) to 50 ft (15.2 m). The deadline for farmers to create buffer strips is November 1, 2017. The modified SWAT model was run to compare the sediment and nutrient loads at the basin&rsquo;s outlet near the border of the US and Canada. Based on the 2013 landuse data obtained from CropScape, the buffer strips would reduce sediment load by 2.3%, total nitrogen by 15.5% (nitrate by 13.5%), and total phosphorus by 16.8%.</p><br /> <p><span style="text-decoration: underline;">Purdue University (S. McMillan) </span>Effectiveness and societal acceptance of best management practices across the rural-urban gradient: The goals of this project are to (1) characterize current pollutant loads from two representative watersheds draining to Lake Michigan based on resident group (i.e., urban residential, suburban residential, rural residential, small agricultural, and medium/large agricultural), (2) determine the willingness of resident groups to adopt conservation and management practices, and (3) aggregate potential pollutant reductions based on willingness scenarios and share results with stakeholders. Preliminary model results show that although agricultural land is the primary developed land use in both watersheds, the annual load of sediments is greater from suburban/urban lands while dissolved pollutant loads are greater from agricultural lands. We are currently interviewing water resource managers and developing surveys to send to residents in spring 2018. This project is currently supporting two MS students at Purdue University.</p><br /> <p><span style="text-decoration: underline;">Texas A &amp; M University (F. Jaber, Z. Sheng, C. Munster) </span>SWAT was used to model Green stormwater infrastructure (GSI) in a development in Houston to evaluate the impact of GSI on stormwater quality in three different residential and commercial urban density.
b- Data from field study was used to develop GSI subroutines to integrate in the next Release of SWAT. They developed SWAT model to simulate watershed hydrological processes and impacts of drought, initiate linkage between SWAT model with RiverWare model and MODFLOW, currently funded by two USDA NIFA grants.</p><br /> <p><span style="text-decoration: underline;">University of Rhode Island (A Gold, S Pradhanang, K Addy) </span>URI team conducted watershed modeling to predict stream flow, temperature and thermally stressful events within RI within the context of climate change and also developed hydrologic and water quality models to assess impacts of onsite waste water treatments systems in nitrogen loading in the bay area of RI. URI team contributed to database development and statistical modeling efforts to predict riparian zone function with respect to nitrogen and phosphorus cycling and greenhouse gas emission in agricultural areas of glaciated regions.&nbsp;&nbsp; They also began to calibrate the AnnAGNPS model and the Riparian Ecosystem Management Model (REMM) with new default model parameters specific to dominant riparian geomorphic types in these glaciated regions. URI selected and instrumented four riparian sites to serve as calibration sites for modeling efforts.</p><br /> <p><span style="text-decoration: underline;">Virginia Polytechnic Institute (D. Sample) </span>Several urban hydrologic/ water quality models were developed for Virginia Beach and Fairfax, Virginia watersheds. BMPs are explicitly incorporated in these models to explore their effectiveness under changing conditions such as climate. We are also creating HSPF models of each of the City's watersheds that match watershed delineations of the existing SWMM models. We will be using these to explore the effect of aggregation and asses the comparability of the mesoscale models with the large scale Chesapeake Bay watershed model.</p><br /> <p><em>Objective 3: Develop methods to quantify modeling and monitoring uncertainty as affected by model representations of watershed processes and model input data</em></p><br /> <p><span style="text-decoration: underline;">Mississippi State University (J. Paz)&nbsp;</span>The results from MSU work on OFWS indicate that the nutrient load transported downstream can be reduced by controlling the volume of water reaching the OFWS during winter and by minimizing spring fertilizer applications. For example, pumping water out of the ditch to an on-farm reservoir could be implemented prior to expected rainfall events, to help reduce the nutrient load discharged with winter outflow events. Outflow events from the OFWS system was different among seasons with respect to the volume, frequency, peak, and time to peak discharge.</p><br /> <p><span style="text-decoration: underline;">Purdue University (S. McMillan)</span> Environmental trade-offs in water quality and climate regulation resulting from floodplain restoration using the two-stage ditch: Our overall objective for this project is to assess the environmental tradeoffs between water quality and climate regulation that may exist when best management practices (BMPs) are implemented in agricultural watersheds. We are focusing on two-stage channels that are implemented in agricultural drainage networks. These practices are constructed by creating inset floodplains within the existing channel thereby tripling the overall width. Specifically, we are aim to answer the following questions: (1) what is the contribution of denitrification to N retention at the reach scale? (2) what biophysical processes control phosphorus retention/export in streams with two-stage floodplains? (3) what are the patterns of greenhouse gas emissions in restored floodplains and how do they compare to natural floodplains and agricultural riparian zones? We are monitoring three two-stage channels in Indiana for sediment and water characteristics, including surface water chemistry, soil carbon and extractable phosphorus. We are also measuring rates of denitrification and nutrient flux in floodplain sediments seasonally. In summer 2017 conducted a larger survey of 10 two-stage channels and focused identifying variability in phosphorus dynamics in the floodplains and streambed at sites of varied ages and soil types. This project has also formed the basis for the Masters thesis for two students at Purdue and a component of two students&rsquo; dissertations at the University of Notre Dame.</p>

Publications

<p><span style="text-decoration: underline;">PUBLICATIONS</span></p><br /> <p>Addy, K., A.J. Gold, J.A. Loffredo, A.W. Scroth, S.P. Inamdar and W.B. Bowden. In review. Stream response to an extreme drought induced defoliation event. Biogeochemistry.</p><br /> <p>Alamdari, N., &amp; Sample, D. J. (2017). Evaluating the Impacts of Climate Change on Urban Stormwater Quantity and Quality in Coastal Virginia. In ASCE/EWRI World Water and Water Resources Congress. Sacramento, CA.</p><br /> <p>Alamdari, N., Sample, D. J., Steinberg, P., Ross, A. C., &amp; Easton, Z. M. (2017). Assessing the Effects of Climate Change on Water Quantity and Quality in an Urban Watershed Using a Calibrated Stormwater Model. WATER, 9(7), 24 pages.doi:10.3390/w9070464</p><br /> <p>Ambrogi Ferreira do Lago, C., Rosa, A., Batalini Macedo, M., Sample, D. J., Caramori Borges de Souza, V., &amp; Mendiondo, E. (2017). Adaptive bioretention modular sizing (BioMS) evaluation under different occupation scenarios. In Proceedings of the 14th IWA/IAHR International Conference on Urban Drainage. Prague, Czech Republic.</p><br /> <p>Bandara, C., A.Y. Sheshukov (2017). Quantifying Ephemeral Gully Erosion with Photogrammetry Surveying. International ASABE Meeting. Spokane, WA, 16-19 July, 2017. ASABE Paper 1700474. doi:10.13031/aim.201700474.</p><br /> <p>Bell, C., S. McMillan, and C. Tague. 2017. A model of hydrology and water quality in stormwater control measures. Environmental Modeling and Software 95:29-47, doi:10.1016/j.envsoft.2017.05.007.</p><br /> <p>Bushira, K.M., Hernandez, J.R., and Sheng, Z. (2017). Surface and groundwater flow modeling for calibrating steady state using MODFLOW in Colorado River Delta, Baja California, Mexico, Modeling Earth Systems and Environment, 3(2): 815&ndash;824, DOI:10.1007/s40808-017-0337-5</p><br /> <p>Chambers, B., Pradhanang, S.M. and Gold, A.J., 2017. Assessing Thermally Stressful Events in a Rhode Island Coldwater Fish Habitat Using the SWAT Model. Water, 9(9), p.667. doi:10.3390/w9090667</p><br /> <p>Chambers, B., Pradhanang, S.M. and Gold, A.J., 2017. Simulating Climate Change Induced Thermal Stress in Coldwater Fish Habitat Using SWAT Model. Water, 9(10), p.732. doi:10.3390/w9100732</p><br /> <p>Gao, J., A.Y. Sheshukov, H. Yen, J. Kastens, D. Peterson (2017) Impacts of Incorporating Dominant Crop Rotation Patterns as Primary Land Use Change on Hydrologic Model Performance. Agriculture, Ecosystems &amp; Environment. 247: 33-42. doi:10.1016/j.agee.2017.06.019</p><br /> <p>Harmel, R., K. King, others, and B.E. Haggard. 2017. Measuring edge-of-field water quality: Where we have been and the path forward. Journal of Soil and Water Conservation [Accepted]</p><br /> <p>Her, Y., Jeong, J., Arnold, J., Gosselink, L., Glick, R., &amp; Jaber, F. (2017). A new framework for modeling decentralized low impact developments using Soil and Water Assessment Tool.&nbsp;&nbsp; Environmental Modelling &amp; Software, 96, 305-322.</p><br /> <p>Jefferson, A., A. Bhaskar, K. Hopkins, R. Fanelli, P. Avellaneda, and S. McMillan. 2017. Stormwater management network effectiveness and implications for urban watershed function: A critical review. Hydrological Processes, doi: 10.1002/hyp.11347.</p><br /> <p>Jeldes, Isaac A., Yoder, Daniel and Drumm, Eric &ldquo;Sustainable Slopes: Satisfying Rainfall-Erosion Equilibrium and Mechanical Stability&rdquo; submitted to Transactions of the ASABE, November 2017</p><br /> <p>Joby M. Prince Czarnecki, Lee A. Hathcock, John J. Ramirez-Avila, Anna C. Linhoss, and Timothy J. Schauwecker. 2017. Unmanned aerial vehicles and structure from motion techniques and their use in protecting surface water quality. 2017 American Water Resources Association Annual Conference, Nov. 5-9, 2017, Portland, OR</p><br /> <p>Kant S. Jaber F.H. and R Khartikeyan. 2017. Evaluation of a portable in-house greywater treatment system for potential water-reuse in urban areas. Submitted to Urban Journal. In Review.</p><br /> <p>Karimov, V., A.Y. Sheshukov (2017). Integrated process-based modeling of channelized flow and soil erosion in small watersheds. International ASABE Meeting. Spokane, WA, 16-19 July, 2017. ASABE Paper 1700566. doi:10.13031/aim.201700566.</p><br /> <p>Karimov, V., A.Y. Sheshukov (2017). Integrated process-based modeling of channelized flow and soil erosion in small watersheds. International ASABE Meeting. Spokane, WA, 16-19 July, 2017. ASABE Paper 1700566. doi:10.13031/aim.201700566.</p><br /> <p>Karki, R., M.L.M. Tagert, J.O. Paz, and R.L. Binger. 2017. Application of AnnAGNPS to model an agricultural watershed in East-Central Mississippi for the evaluation of an on-farm water storage (OFWS) system. Agricultural Water Management 192:103-114. doi:10.1016/j.agwat.2017.07.002</p><br /> <p>Ketabchy, M., 2017. Thermal Evaluation of an Urbanized Watershed using SWMM and MINUHET: a Case Study of the Stroubles Creek Watershed, Blacksburg, VA, p. 114.</p><br /> <p>Li, S., Cooke, R.A., Wang, L., Ma, F. and Bhattarai, R. 2017. Characterization of fly ash ceramic pellet for phosphorus removal. Journal of Environmental Management, 189, 67-74. NIFA Support Acknowledged</p><br /> <p>Liu, Y., B. Engel, D. Flanagan, M. Gitau, S. McMillan, and I. Chaubey. 2017. A review on effectiveness of best management practices in improving hydrology and water quality: needs and opportunities. Science of the Total Environment 601:580-593, doi:10.1016/j.scitotenv.2017.05.212.</p><br /> <p>Loy, S., Tahtouh, J., Munster, C., Wagner, K., Fares, A., Ale, S., Vierling, R., Jaber F., Jantrania, A. 2017. State of the Art of Water for Food Within the Nexus Framework. Current Sustainable/Renewable Energy Reports. doi:10.1007/s40518- 017-0084-2</p><br /> <ol start="2017"><br /> <li>Seo, F. Jaber, R. Srinivasan. 2017. Evaluating various low-impact development scenarios for optimal design criteriadevelopment. WaterSA, 9 (2017), p. 270</li><br /> </ol><br /> <p>McCarty, J.A., M.D. Matlock, J.T. Scott, and B.E. Haggard. 2017. Four risk indicators for prioritizing smaller watersheds to improve water quality. Transactions ASABE [Submitted]</p><br /> <p>McMillan, S. and G. Noe. 2017. Increasing floodplain connectivity through urban stream restoration increases nutrient and sediment retention. Ecological Engineering 108: 284-295, doi:10.1016/j.ecoleng.2017.08.006.</p><br /> <p>Moore, T., A.Y. Sheshukov, R. Graber. Integrating water quality management across the urban-rural interface: Opportunities for watershed extension programs. Journal of Extension (submitted)</p><br /> <p>Ouyang, Y., J.O. Paz, G. Feng, J. Read, and A. Adeli, and J. Jenkins. 2017. A Model to Estimate Hydrological Processes and Water Budget in an Irrigation Farm Pond. Water Resources Management 31:2225-2241. doi: 10.1007/s11269-017-1639-0.</p><br /> <p>Paul, S., Cashman, M.A., Szura, K. and Pradhanang, S.M., 2017. Assessment of Nitrogen Inputs into Hunt River by Onsite Wastewater Treatment Systems via SWAT Simulation. Water, 9(8), p.610. doi:10.3390/w9080610</p><br /> <p>Paz, J.O. 2017. Climate Impacts in the Southeast: Challenges and Opportunities for Agricultural Systems and Water Resources. SEC Academic Conference. The Future of Water: Regional Collaboration on Shared Climate, Coastlines, and Watersheds. March 27-28, 2017. Starkville, MS.</p><br /> <p>P&eacute;rez-Guti&eacute;rrez, J.D. 2017. Water quality monitoring and modeling studies of on-farm water storage systems in Mississippi Delta agricultural watersheds. PhD dissertation. Mississippi State University.</p><br /> <p>P&eacute;rez-Guti&eacute;rrez, J.D.,<strong> J.O. Paz</strong>, and M.L.M. Tagert. 2017. Irrigation water supply potential of on-farm water storage systems in Mississippi agricultural watersheds. University Council for Water Resources/National Institutes for Water Resources Annual Conference. June 13-15, 2017. Fort Collins, CO.</p><br /> <p>P&eacute;rez-Guti&eacute;rrez, J.D., J.O. Paz, and M.L.M. Tagert. 2017. Seasonal Water Quality Changes in On-Farm Water Storage Systems in a South-Central U.S. Agricultural Watershed. Agricultural Water Management 187:131-139. doi: 10.1016/j.agwat.2017.03.014</p><br /> <p>P&eacute;rez-Guti&eacute;rrez, J.D.,<strong> J.O. Paz</strong>, M.L.M. Tagert, L.W. Yasarer, and R.L. Bingner. 2017. Impact of On-farm Water Storage System Implementation on Agricultural Watersheds Using Assessments from AnnAGNPS Simulations. ASABE Paper 1701502. 2017 ASABE Annual International Meeting. Spokane, WA.</p><br /> <p>Pradhanang, S. M. 2017 Water-Energy-Food Nexus, in Water-Energy-Food Nexus: Principles and Practices (eds P. A. Salam, S. Shrestha, V. P. Pandey and A. K. Anal), John Wiley &amp; Sons, Inc., Hoboken, NJ, USA. doi: 10.1002/9781119243175.ch13</p><br /> <p>Sample, D. J. (2017). Emerging Innovations in Stormwater Design. In 8th Annual Bay-Wide. Shepherdstown, WV.</p><br /> <p>Sample, D. J. (2017). Floating Wetlands for Treatment of Urban and Agricultural Runoff in Virginia. In Webinar on Success Stories of HABs Prevention, Control and Management Techniques. Washington, DC: U.S. Environmental Protection Agency.</p><br /> <p>Sample, D. J., &amp; Licher, MK. (2017). Inspection, Enforcement, and Maintenance Costs of Stormwater Control Measures Results of a Nationwide Survey. In EWRI &ndash; ASCE Operation and Maintenance of Stormwater Control Measures. Denver, CO.</p><br /> <p>Schwartz, D., Sample, D. J., &amp; Grizzard, T. J. (2017). Evaluating the performance of a retrofitted stormwater wet pond for treatment of urban runoff. ENVIRONMENTAL MONITORING AND ASSESSMENT, 189(6), 19 pages. doi:10.1007/s10661-017-5930-6</p><br /> <p>Seo M., Jaber F.H., Srinivassan R. and Jeong. J. 2017. Modeling the Impact of Land Use Change Using Different Urban Developments on Water Quantity and Quality Using SWAT. Journal of irrigation and drainage Engineering</p><br /> <p>Seo M., Jaber F.H., Srinivassan R. and Jeong. J. 2017. Modeling the Impact of Land Use Change Using Different Urban Developments on Water Quantity and Quality Using SWAT. Journal of irrigation and drainage Engineering</p><br /> <p>Seo, M.; Jaber, F.; Srinivasan, R.; Jeong, J. 2017. Evaluating the impact of Low Impact Development (LID) practices on water quantity and quality under different development designs using SWAT. Water 2017, 9, 193</p><br /> <p>Sharpley, A.N., B.E. Haggard, L. Berry, J. Burke, K. Brye, M.D. Daniels, T. Glover, T. Kresse, P. Hays, and K.W. VanDevender. 2017. Nutrient concentrations in Big Creek correlate to regional watershed land use. Agricultural and Environmental Letters 2:170027</p><br /> <p>Sheshukov, A.Y., L. Sekaluvu, S.L. Hutchinson. Accuracy of Topographic Index Models at Identifying Ephemeral Gully Trajectories on Agricultural Fields. Geomorphology</p><br /> <p>Sheshukov, A.Y., S.L. Hutchinson, T. Moore (2017) Urban water quality BMPs. Publication MF-2732. Kansas State University, Manhattan, KS. 4 p</p><br /> <p>Sheshukov, A.Y., S.L. Hutchinson, T. Moore, D. Presley (2017) Stormwater Best Management Practice Maintenance. Publication MF-2814. Kansas State University, Manhattan, KS. 4 p.</p><br /> <p>Spangler, J.T., 2017. An Assessment of Floating Treatment Wetlands for Reducing Nutrient Loads from Agricultural Runoff in Coastal Virginia, MS Thesis, Virginia Polytechnic Institute and State University, p. 98.</p><br /> <p>Stack, W., Evanylo, G. K., Montalto, F., Papacosma, J., Sample, D., Shafer, J., &amp; Winston, R. (2017). Recommendations of the Expert Panel to define removal rates for disconnecting runoff from imperious areas onto amended soils or treatment in the stormwater conveyance system.</p><br /> <p>Tagert, M.L.M., <strong>J.O. Paz</strong>, J.D. P&eacute;rez-Guti&eacute;rrez, and R. Karki. 2017. Overview and benefits of on-farm water storage systems in Mississippi watersheds. University Council for Water Resources/National Institutes for Water Resources Annual Conference. June 13-15, 2017. Fort Collins, CO.</p><br /> <p>Vaughan, M.C.H., Bowden, W.B., Shanley, J.B., Vermilyea, A., Sleeper, R., Gold, A.J., Pradhanang, S., Inamdar, S.P., Levia, D.F., Andres, A.S. and Birgand, F., 2017. High‐frequency dissolved organic carbon and nitrate measurements reveal differences in storm hysteresis and loading in relation to land cover and seasonality. Water Resources Research 53, 5345&ndash;5363, doi:10.1002/2017WR020491.</p><br /> <p>Welsh, M., S. McMillan, and P. Vidon. 2017. Denitrification along the stream-riparian continuum in restored and unrestored agricultural streams. Journal of Environmental Quality 46(5): 1010-1019, doi:10.2134/jeq2017.01.0006.</p><br /> <p>Xiong, M., Z. Lin, and G. Padmanabhan (2017). Impact of bioenergy policy induced land use change on water quality under changing climate in the Northern Great Plains of the United States. International Journal of Global Environmental Issues, revised and submitted.</p><br /> <p>&nbsp;</p><br /> <p>Proceedings paper</p><br /> <p>Sheng, Z., Jia, S. Michelsen, A. and Abudu. S. (2017). Lessons learned from long term water resources plans: top town vs. bottom up, XVI World Water Congress, Cancun Mexico, May 29-June 2 [8p].</p><br /> <p>&nbsp;</p><br /> <p>Conference and Talks</p><br /> <p><strong>&nbsp;</strong></p><br /> <p>Abudu, S., Ahn, S. and Sheng, Z. (2017). Modeling Dissolved Solids in the Rincon Valley, New Mexico using RiverWare, 2017 AGU Fall Meeting, New Orleans, LA, December 11-15.</p><br /> <p>Addy, K., Gold, A., Pradhanang, S.M., Garfield, M., Steven-Murphy Nicole, Dunn, M., Lofredo, J., and Frazer, S. 2017 Nutrient and carbon loading from forested, urban and agricultural watersheds during extreme climatic events. American Geophysical Union, Chapman Conference on Extreme Climate Events on Aquatic Biogeochemical Cycles and Fluxes, January 2017, Puerto Rico.</p><br /> <p>Ahn, S., Abudu, S. and Sheng. Z. (2017). Hydrological Responses of Weather Conditions and Crop Change of Agricultural Area in the Rincon Valley, New Mexico, 2017 AGU Fall Meeting, New Orleans, LA, December 11-15.</p><br /> <p>Ahn, S., Abudu, S., and Sheng. Z. (2017). Hydrological cycle analysis of crop areas based on SWAT model for the Rincon Valley in New Mexico, 2017 UCOWR/NIWR Conference: Water in a Changing Environment, Fort Collins, CO, June 13-15.</p><br /> <p>Alford, C., and S. McMillan. 2017. The effect of floodplain creation on soil processes in agricultural channels. Indiana Water Resources Association Symposium, Marshall, IN.</p><br /> <p>Bushira K.M.*, Hernandez, J.R., and Sheng, Z. (2017). Surface and Ground water flow Modeling for Calibrating Steady State using MODFLOW in Colorado River delta, Baja California, Mexico, 2017 UCOWR/NIWR Conference: Water in a Changing Environment, Fort Collins, CO, June 13-15</p><br /> <p>Chavez, J., Sheng, Z., Abudu, S., Ahn, S., Liu, Q., Rodriguez, O., Reynoso, O., Prieto, D., Olivas, A.G., Mayer, A., Thiemann, K., Teasley, R., and Mancewicz, L. (2017). Delineation of USDA Project Study Area, Symposium on Sustainable Water Resources for Irrigated Agriculture in a Desert River Basin Facing Climate Change and Competing Demands: From Characterization to Solutions, USDA-NIFA and UTEP, El Paso, Texas, January 4</p><br /> <p>Dahal, V. and R. Bhattarai. 2017. Analysis of the impacts of climate and land use on the hydrological regime of Illinois watersheds. ASABE Annual Meeting, July 16-19, 2017, St. Joseph, MI.</p><br /> <p>Gold, A., K. Addy, A. Morrison and M. Simpson. 2017. Will Dam Removal Increase Nitrogen Flux to Estuaries? Hydro Eco, June 21, 2017. University of Birmighham, UK.</p><br /> <p>Gold, A., K. Addy, A. Morrison, and Marissa Simpson. 2016. Will dam removal increase nitrogen flux to estuaries? University of New Hampshire Seminar. October 14, 2016. Invited Talk.</p><br /> <p>Hassan, M.A., and Pradhanang, S.M., 2016. Large scale hydrologic modeling of ecologically important flow metrics of rivers of the Himalayas. 2016 American Geophysical Fall Meeting, San Francisco, CA.</p><br /> <p>Jang, C., Nguyen, H. and R. Bhattarai. 2017. The influence of the feed water chemical composition on the Bacteriophage MS2 removal by bio-sand filter. ASABE Annual Meeting, July 16-19, 2017, St. Joseph, MI.<br /> NIFA Support Acknowledged</p><br /> <p>Loffredo, J.A., K. Addy, and A. Gold. 2016. Water quality sensors offer insights into stream response to invasive gypsy moths. 2016 URI Coastal Fellows Program Poster Session, Kingston, RI.</p><br /> <p>Ma, Z., S.K. McMillan, J. Domenech, and R. Scarlett. 2017. Combining societal acceptance and biophysical drivers of conservation practices to improve water quality in multi-use landscapes. Soil and Water Conservation Society Annual Conference, Madison, WI.</p><br /> <p>McMillan, S., E. Looper, C. Bell, R. Scarlett, S. Clinton, and A. Jefferson. 2017. Influence of stormwater control measures on receiving stream ecosystems. American Geophysical Union Chapman Conference on Extreme Climate Event Impacts on Aquatic Biogeochemical Cycles and Fluxes, San Juan, PR.</p><br /> <p>McMillan, S.K. Assessing ecosystem function of headwater streams: influence of restoration on nutrient dynamics. Indiana University Purdue University Indianapolis (IUPUI), Center for Earth and Environmental Sciences Colloquium, February 27, 2017.</p><br /> <p>McMillan, S.K. Ecosystem restoration: Does restoring structure lead to function? University of North Carolina Chapel Hill, Curriculum for the Environment and Ecology Seminar Series, April 20, 2017.</p><br /> <p>McMillan, S.K. Restoring ecological function in urban landscapes: a case for combining watershed and stream based approaches. University of North Carolina at Charlotte, Department of Geography and Earth Sciences Seminar, April 21, 2017.</p><br /> <p>Paul, S., Pradhanang, S.M., and Islam, S.A., 2016 Sensitivity of different satellites gridded data over Brahmaputra Basin by using Soil and Water Assessment Tool (SWAT). 2016 American Geophysical Fall Meeting, San Francisco, CA.</p><br /> <p>Pokharel, H.K., Pradhanang, S.M., Gold, A and Addy K, 2017 Simulating Hydrology and Water Quality to Predict Stream Discharge, Nitrate Loads Under Climate Change Scenarios in Maidford River Basin, Rhode Island Using SWAT Model. American Geophysical Union, Chapman Conference on Extreme Climate Events on Aquatic Biogeochemical Cycles and Fluxes, January 2017, Puerto Rico.</p><br /> <p>Pradhanang, S. 2017 River basin management and water resource implications of changing climate in Western Nepal. Association of Geographers Annual Meeting in Boston, MA April 5-9, 2017 (Highlands to Ocean Session Chair and talk).</p><br /> <p>Pradhanang, S. M., Hassan, M.A, Booth, P., Fallatah, Otthman, 2016. Estimation of future flow regime for a spatially varied Himalayan watershed using improved multi-site calibration method of SWAT model. 2016 American Geophysical Fall Meeting, San Francisco, CA.</p><br /> <p>Pradhanang, S.M. 2016 Sustainable river basin management and water resource implications of changing climate. International Conference on Sustainable Built Environment (ICSBE), Yogyakarta, Indonesia Oct 12-14, 2016</p><br /> <p>Rodriguez, O., Sheng, Z., Abudu, S., Ahn, S., Reynoso, E., Chavez, J., and Prieto. D. (2017). Approaches for infilling the incomplete measured Eddy-Covariance pecan tree evapotranspiration data, Symposium on Sustainable Water Resources for Irrigated Agriculture in a Desert River Basin Facing Climate Change and Competing Demands: From Characterization to Solutions, USDA-NIFA and UTEP, El Paso, Texas, January 4</p><br /> <p>Rodriguez, O., Sheng, Z., S. Abudu. (2017). Comparison of Statistical Approaches for Infilling Gaps of Evapotranspiration Measurements in Pecan Orchard, NM Section ASABE Annual Meeting, Las Cruces, NM, March 31</p><br /> <p>Sheng, Z. (2017). Use of greywater and brackish water for agricultural production, The 4th Forum on Global Ecology, Agriculture and Rural-Uplift Program (GEAR-UP), Taiwan, November 11-14 [Invited Presentation].</p><br /> <p>Sheng, Z., Abudu, S., Michelsen, A., King, J.P. and Gunjegunte, G. (2017). Stochastic Modeling and Analysis of Salt Loading Variations in the Rio Grande Project Area, USA, International Perspective on Water Resources and the Environment, Wuhan, China, January 4-6.</p><br /> <p>Sultana, S., and Z. Lin (2017). Groundwater quality risk assessment in North Dakota. North Dakota EPSCoR 2017 State Conference, April 12, 2017, Fargo, North Dakota (Poster).</p><br /> <p>Welsh, M., S. McMillan, and P. Vidon. 2017. Changes in riparian and stream hydrology and biogeochemistry following storms in an agricultural watershed. American Geophysical Union Chapman Conference on Extreme Climate Event Impacts on Aquatic Biogeochemical Cycles and Fluxes, San Juan, PR.</p><br /> <p>Other:</p><br /> <p>Sultana, Sharmin (2017). Groundwater Quality Vulnerability Assessment in North Dakota. M.S. Thesis, North Dakota State University, Fargo, North Dakota.</p><br /> <p>Chambers, B. M., 2017. Simulating Thermal Stress in Rhode Island Coldwater Fish Habitat Using SWAT. University of Rhode Island</p><br /> <p>&nbsp;</p>

Impact Statements

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Date of Annual Report: 01/18/2019

Report Information

Annual Meeting Dates: 09/12/2018 - 09/14/2018
Period the Report Covers: 10/01/2017 - 09/30/2018

Participants

Aleksey Sheshukov (KSU), Soni Pradhanang (URI), Sunday Tim (ISU), Sara McMillan (Purdue), Zhuping Sheng (TAMU), Dwayne Edwards (Kentucky), Rabin Bhattarai (UI-UC), Fouad Jaber (TAMU), Fariborz Daneshvar (IC), Lawrence Sekaluvu (Margaret Gitau), Indrajeet Chaubey (Purdue), Jasmeet Lamba (Auburn University), Dwayne Edwards (UK), Rabin Bhattarai (UI-UC), Sunday Tim (ISU), Manish Srivastav (ISU), Mandy Limiac (Purdue), Rachel Scarlett (Purdue), A. J Reisinger (UF), Eban Bean (UF), Kevin Wagner (OSU), Femeena Pandara Valappil (IC).

Brief Summary of Minutes

The annual meeting held in Purdue University, IN in September 2018 focused on addressing S1063 objectives, accomplishments, and identifying potential tasks or research products to be initiated or continued by the members of the Multistate Exchange Group. Presentations of the different accomplishments and future goals to be pursued by members of S1063 were held during the annual meeting. Life and phone members’ presentations were grouped in three main tracks: monitoring, modeling and uncertainty, involving the three main objectives of the multistate group.


A discussion followed the set of presentations to include relevant topics such as analysis of monitoring procedures for watershed protection plans; nutrients sensor developments; use of monitoring data to accurately quantify implications of BMPs; preparation of peer reviewed publications; opportunities to modify functions within models to represent BMPs; scholarship of data and sensors monitoring; and the preparation of an urban stormwater monitoring proposal and the Regional Coordination Network NSF proposal, among others. The group also discussed how to go about the preparation of submission of the next 5 years proposal to USDA NIFA and the preparation of the 2019 annual meeting. The 2019 annual meeting will be held in Rhode Island.


During the annual meeting, a field trip to the Throckmorton Purdue Agricultural Center (TPAC) and the location of a stream restoration project on the Purdue University’s campus was completed.

Accomplishments

<p>The principle focus of this project is to evaluate the effectiveness of best management practices (BMPs) at the watershed scale. This includes the water quality and environmental benefits of mitigation practices as well as their cost effectiveness. This will be achieved through monitoring at sub-watershed scales, modeling at larger spatial scales, and analysis of uncertainty in both monitoring and modeling efforts.&nbsp; This report summarizes the activity on this project from October 2017 to September 2018, and the following sections highlight accomplishments from project teams:</p><br /> <p><span style="text-decoration: underline;">Texas A&amp;M (Fouad Jaber)</span></p><br /> <p>Streambank erosion studies are oriented to assess change in cross section, potential temporal changes in stream classification due to in-stream processes and estimation of the BEHI for studied reaches. Cross section surveys, pin erosion lines and pebble counting are part of the procedures followed by the research team.</p><br /> <p><span style="text-decoration: underline;">Auburn University (Jasmeet Lamba)</span></p><br /> <p>A sediment fingerprinting study is in progress to identify and quantify dominant sources of sediments in an urbanized watershed in Alabama. The study compares tracer properties of in-stream sediment and sediment sources. To fulfill monitoring needs for the study, an in-situ time integrated suspended sediment sampler was designed.&nbsp;&nbsp;</p><br /> <p><span style="text-decoration: underline;">University of Florida (A J Reisiger; Eban Bean)</span></p><br /> <p>A study focused on ecosystem ecology in urban and urbanizing landscapes is in progress at UF. As part of the study strategies, the study advances the monitoring of water quality and ecosystem function of urban streams, and the implementation and assessment of storm water pond for nutrient reduction efficiencies.</p><br /> <p>A second study at UF focuses on the assessment and quantification of urban water consumption and availability issues. The study relates the implementation of soil and water monitoring techniques to evaluate soil compaction during construction and how that impacts water quality at new model homes; water movement through soil with leachate lysimeters and other instrumentations; and the use of steel slag for P remediation along stormwater systems.</p><br /> <p><span style="text-decoration: underline;">Oklahoma State University (Kevin Wagner)</span></p><br /> <p>The main goal of the study in OSU is to determine impacts and implication of background bacterial sources on water quality management efforts. Two DNA fingerprinting methods are implemented as part of the project performance, which also expects to link watershed modeling and bacterial source tracking to better assess e-coli.</p><br /> <p><span style="text-decoration: underline;">&nbsp;</span></p><br /> <p><span style="text-decoration: underline;">Mississippi State University (J Czarnecki, J. Ramirez-Avila)</span></p><br /> <p>The assessment of in-stream process within the Catalpa Creek is advanced through monitoring, laboratory analysis and modeling procedures. Morphological cross section changes are monitored by using different techniques including conventional survey, GPS and UAVs. The use of channel evolution models (BSTEM and CONCEPTS) achieved comparing input and output processes for each source of survey dataset. Temporal and spatial variability of sediments and the potential impact of land use variation and riparian vegetation in stream water quality is also advanced along tributaries and main stream of Catalpa Creek. Studies are related to the implementation of the Water management Plan approved by EPA and the MWRRI.</p><br /> <p><span style="text-decoration: underline;">University of Rhode Island (S Pradhanang) </span></p><br /> <p>Supported by USDA-AFRI, the Pradhanang Lab is advancing research to evaluate riparian zone functions in glaciated settings for decision-support purposes with respect to N and P fluxes. The main goal of the current monitoring phase is to develop a set of Riparian Model parameters for the US Midwest, US Northeast and Southern Canada to facilitate the use of this model in these regions and improve its functionality with respect to N, P, and N<sub>2</sub>O.</p><br /> <p>Supported by the RI DOT, a study is in progress oriented to evaluate the effectiveness of improved roadside best management practices in maintaining storm water quality. The project considers the development of a stormwater runoff model for sub-urban areas in Southern Rhode Island, as well as assessing model uncertainty and calibration through the application of Bayesian statistics. In addition to these studies, Pradhanang Lab is also currently developing a reservoir mitigation model (SWAT and OASIS) for a drinking water reservoir in RI and a model (SWAT-MODFLOW) to assess impacts of salt water intrusion on coastal aquifer due to storm surges.&nbsp;</p><br /> <p><span style="text-decoration: underline;">&nbsp;</span></p><br /> <p><span style="text-decoration: underline;">Texas A &amp; M University (Z. Sheng)</span></p><br /> <p>An integrated surface and groundwater modeling study is in progress along for a region near E Paso and Fort Quitman in Texas. The model-coupling package SWAT-MODFLOW is used for the analysis. An initial assessment of the water balance and interactions between surface and groundwater for the area have been achieved.</p><br /> <p><span style="text-decoration: underline;">University of Illinois (R. Bhattarai)</span></p><br /> <p>Modeling efforts oriented to evaluate effects of implementing cover crops on water quality and crop yields are advanced in east central Illinois. SWAT model is used to evaluate water yield, nitrate uptake and losses, and crop yield from different crop management scenarios; economic benefits and regional differences.</p><br /> <p><strong>Outputs: </strong></p><br /> <p>Publications, conferences, reports and thesis:</p><br /> <p>Journals: 46; Conference Presentations: 45; Proceedings: 5; Reports/Other: 7; Thesis/Dissertations: 11; Model Development: 6.</p>

Publications

<p><strong>Peer Reviewed Journal Papers</strong></p><br /> <p>Addy, K., A.J. Gold, J.A. Loffredo, A.W. Scroth, S.P. Inamdar, W.B. Bowden, D.Q. Kellogg, and F. Birgand. 2018.&nbsp; Stream response to an extreme drought induced defoliation event.&nbsp; Biogeochemistry 140:199-215. https://doi.org/10.1007/s10533-018-0485-3</p><br /> <p>Abbaspour, K.C., S.A. Vaghefi and R. Srinivasan . 2018. A guideline for successful calibration and uncertainty analysis for Soil and Water Assessment: A review of papers from the 2016 International SWAT Conference. Water. Volume:10(1). DOI:10.3390/w10010006</p><br /> <p>Alamdari, N., Sample, D. J., Liu, J., and Ross, A., 2018. Water supply and runoff capture reliability curves for hypothetical rainwater harvesting systems for locations across the U.S. for historical and projected climate conditions.. Data in brief, 18, 441-447. doi:10.1016/j.dib.2018.03.024</p><br /> <p>Alamdari, N., Sample, D. J., Liu, J., and Ross, A., 2018. Assessing climate change impacts on the reliability of rainwater harvesting systems. Resources Conservation and Recycling, 132, 178-189. doi:10.1016/j.resconrec.2017.12.013</p><br /> <p>Alamdari, N., Sample, D. J., Steinberg, P., Ross, A. C., and Easton, Z. M., 2017. Assessing the Effects of Climate Change on Water Quantity and Quality in an Urban Watershed Using a Calibrated Stormwater Model. Water, 9(7), 24 pages. doi:10.3390/w9070464</p><br /> <p>Austin, B.J. S. Entrekin, M.A. Evans-White, J. Kelso, and B.E. Haggard. 2018. Can high volume hydraulic fracturing effects be detected in large watersheds? A case study of the South Fork Little Red River. Current Opinion in Environmental Science and Health 3:40-46</p><br /> <p>Campbell A., Pradhanang, S. M. Kouhi Anbaran, S, Sargent, J., Palmer, Z, and Audette, M. 2017. Assessing the impact of Urbanization on Flood Risk and Severity for the Pawtuxet Watershed, Rhode Island.Lake and Reservoir Management:1-14</p><br /> <p>Cavus, I., L. Kalin, F. Kara. 2018. "Impacts of upstream urban activities on downstream sediment production in the presence of best management practices", International Journal of Sediment Research. 32:555-563</p><br /> <p>Cibin, R., Chaubey, I., Sudheer, K. P., White, M., Arnold, J. G., &amp; Helmers, M. J. (2018). Improved filter strip representation in SWAT model to simulate energy crop filter strips. Transactions of the ASABE, 61(3), 1017-1024. DOI:10.13031/trans.12661</p><br /> <p>Dahal, V., Gautam, S., &amp; Bhattarai, R. (2018). Analysis of Long-Term Temperature Trend in Illinois and its Implication on the Cropping System. Environmental Processes, 5(3): 451&ndash;464.</p><br /> <p>Dahal, V., Gautam, S., &amp; Bhattarai, R. (2018). Analysis of the Long-term Precipitation Trend in Illinois and Its Implications for Agricultural Production. Water, 10(4), 433.</p><br /> <p>Entrekin, S., M.A. Evans-White, B.J. Austin, and B.E. Haggard. 2018. Ecological responses to surface water alterations from high-volume hydraulic fracturing: Fayetteville Shale as a case study. Current Opinion in Environmental Science and Health 3:27-32</p><br /> <p>Frazar, S., A.J. Gold, K. Addy, F. Moatar, F. Birgand, A.W. Schroth, S.P. Inamdar, W.B. Bowden, and D.Q. Kellogg.&nbsp; In prep.&nbsp; Nutrient flux from extreme climatic events in agricultural and urban watersheds. Journal of Environmental Quality.</p><br /> <p>Grantz, E., B.E. Haggard, and J.T. Scott. 2018. Censored data can inflate or obscure trends in analyses used for water quality target development. Environmental Monitoring and Assessment 190:394</p><br /> <p>Guo, T., M. Gitau, V. Merwade, J. Arnold, R. Srinivasan, M. Hirschi and B. Engel. 2018.&nbsp; Comparison of performance of tile drainage routines in SWAT 2009 and 2012 in an extensively tile-drained watershed in the Midwest. Hydrology and Earth System Sciences. Vol: 22, Pages: 89-110. DOI:10.5194/hess-22-89-2018</p><br /> <p>Guo, T., R. Cibin, I. Chaubey, M. Gitau, J.G. Arnold, R. Srinivasan, J.R. Kiniry and B.A. Engel. 2018.&nbsp; Evaluation of bioenergy crop growth and the impacts of bioenergy crops on streamflow, tile drain flow and nutrient losses in an extensively tile-drained watershed using SWAT. Science of the Total Environment. Volume:&nbsp;&nbsp; 613-614, Pages:&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; 724-735. DOI:&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; 10.1016/j.scitotenv.2017.09.148</p><br /> <p>Han, X., J. Liu, S. Mitra, X. Li, P. Srivastava, S. Guzman, and X. Chen. 2018. Selection of Optimal Scales for Soil Depth Prediction on Headwater Hillslopes: A Modeling Approach. CATENA, 163: 257-275.</p><br /> <p>Hanson, L., S. Habicht, P. Daggupati, R. Srinivasan and P. Faeth. 2017. Modeling changes to streamflow, sediment, and nutrient loading from land use changes due to potential natural gas development.&nbsp; Journal of the American Water Resources Association. Volume: 53(6), Pages: 1293-1312. DOI:10.1111/1752-1688.12588</p><br /> <p>Harmel, R., K. King, D. Busch, D. Smith, F. Brigand, and B.E. Haggard. 2018. Measuring edge-of-field water quality: Where we have been and the path forward. Journal of Soil and Water Conservation 73:86-96</p><br /> <p>Hasan, M.A., Pradhanang, S.M., 2017. Estimation of Flow Regime for a Spatially Varied Himalayan Watershed using Improved Multi-Site Calibration of the Soil and Water Assessment Tool (SWAT) model. Environmental Earth Sciences: 76(23): 787.</p><br /> <p>Hassanzadeh, Y.T., P.G. Vidon, A.J. Gold, S.M. Prafhanang, and K. Addy.&nbsp; In review.&nbsp; RZ-TRADEOFF: A new model to estimate riparian water and air quality functions.&nbsp; Journal of Environmental Quality.</p><br /> <p>Hassanzadeh, Y.T., P.G. Vidon, A.J. Gold, S.M. Prafhanang, and K. Addy.&nbsp; In review.&nbsp; A new approach to generalizing riparian water and air quality function across regions.&nbsp; Env. Monitoring and Assessment.</p><br /> <p>Jeldes, Isaac A., Yoder, Daniel and Drumm, Eric (2018) &ldquo;Sustainable Slopes: Satisfying Rainfall-Erosion Equilibrium and Mechanical Stability&rdquo; Transactions of the ASABE, Vol. 61(4): 1323-1333 American Society of Agricultural and Biological Engineers https://doi.org/10.13031/trans.12713</p><br /> <p>Jeong, H., &amp; Bhattarai, R. (2018). Exploring the effects of nitrogen fertilization management alternatives on nitrate loss and crop yields in tile-drained fields in Illinois. Journal of environmental management, 213, 341-352</p><br /> <p>Johnson, R. D., Sample, D. J., and McCoy, K. J., 2018. GIS-based method for estimating surficial groundwater levels in coastal Virginia using limited information. Journal of Irrigation and Drainage Engineering, 144(7). doi:10.1061/(ASCE)IR.1943-4774.0001313</p><br /> <p>Kaushal, S.S., A.G. Gold, S. Bernal, T.A. Newcomer Johnson, K. Addy, et al. 2018. Watershed &ldquo;chemical cocktails&rdquo;: forming novel elemental combinations in Anthropocene fresh waters.&nbsp; Biogeochemistry https://doi.org/10.1007/s10533-018-0502-6.</p><br /> <p>Ketabchy, M., Sample, D.J., Wynn-Thompson, T., and Nayeb Yazdi, M., 2018. Thermal evaluation of urbanization using a hybrid approach, Journal of Environmental Management, 226 (August), pp. 457&ndash;475, doi: 10.1016/j.jenvman.2018.08.016</p><br /> <p>Lamba J., P Srivastava, S. Mitra and T. Way. 2018. Using Soil Phosphorus Measurements to Assess the Effectiveness of Subsurface-Band Application of Broiler Litter in Reducing Phosphorus Leaching. Transactions of ASABE. 61(1): 133-138.</p><br /> <p>Li, S., Cooke, R. A., Huang, X., Christianson, L., &amp; Bhattarai, R. (2018). Evaluation of fly ash pellets for phosphorus removal in a laboratory scale denitrifying bioreactor. Journal of environmental management, 207, 269-275</p><br /> <p>Maeda, P. K.,&nbsp; V. Chanse , A. Rockler, H. Montas, A. Shirmohammadi , S. Wilson, P.l T. Leisnham. 2018. Linking stormwater Best Management Practices to social factors in two suburban watersheds. PLOS One: pp. 1-23.</p><br /> <p>Malhotra, K., J. Lamba, P. Srivastava, and S. Shepherd. 2018. Fingerprinting Suspended Sediment Sources in an Urbanized Watershed. Water, 10, 1573; doi:10.3390/w10111573McCarty, J.A., M.D. Matlock, J.T. Scott, and B.E. Haggard. 2018. Risk indicators for identifying critical source areas in five Arkansas watersheds. Transactions ASABE 61:1-8</p><br /> <p>McGehee, R. and P. Srivastava. 2018. Benchmarking reliable erosion indices from quarter-hour station data for climate studies in the southeastern United States. Journal of Soil and Water Conservation 73(4): 363-376.</p><br /> <p>Medina, H., D. Tian, P. Srivastava, A. Pelosi, and G. Chirico. 2018. Medium-range reference evapotranspiration forecasts for the contiguous United States based on multi-model numerical weather predictions. Journal of Hydrology, https://doi.org/10.1016/j.jhydrol.2018.05.029.</p><br /> <p>Merriman K.R., A.M. Russell, C.M. Rachol, P. Daggupati, R. Srinivasan, B.A. Hayhurst, and T.D. Stuntebeck. 2018.&nbsp; Calibration of a field-scale Soil and Water Assessment Tool (SWAT) Model with field placement of best management practices in Alger Creek, Michigan. Sustainability. Vol: 10(3), Pages: 851. DOI:10.3390/su10030851</p><br /> <p>Mitra, S., P. Srivastava, and J. Lamba. 2018. Probabilistic Assessment of Projected Climatological Drought Characteristics over the Southeast USA. Climatic Change, 147(3-4): 601-615.</p><br /> <p>Reavis, M.A., and B.E. Haggard. 2018. Mitigating soil phosphorus release using liquid water treatment residuals.&nbsp; Journal American Water Works Association 110:12</p><br /> <p>Renkenberger, J., H. Montas, P T. Leisnham, V. Chanse, A. Shirmohammadi, A. Sadeghi, K. Brubaker, A. Rockler, T. Hutson, D. Lansing. 2017. Effectiveness of best management practices with changing climate in a Maryland watershed. Transactions of the American Society of Agricultural and Biological Engineers (ASABE) 60(3): 769-789. (doi: 10.13031/trans.11691).</p><br /> <p>Renkenberger, J., H. Montas, P.T. Leisnham, V. Chanse, A. Shirmohammadi, A. Sadeghi, K. Brubaker, A. Rockler, T. Hutson, D. Lansing. 2016. Climate change impact on critical source area identification in a Maryland watershed. Transactions of the American Society of Agricultural and Biological Engineers (ASABE) 59(6): 1803-1819. (doi: 10.13031/trans.59.11677) @2018.</p><br /> <p>Rezaeianzadeh, M., L. Kalin, M. Hantush. 2018. An Integrated Approach for Modeling Wetland Water Level: Application to a Headwater Wetland in Coastal Alabama, USA, Water 10(7): 879; https://doi.org/10.3390/w10070879.</p><br /> <p>Schalla, D., D. Lansingb, P.&nbsp; Leisnhamc, A. Shirmohammadi, H. Montas, T. Hutson. 2018. Understanding stakeholder perspectives on agricultural best management practices and environmental change in the Chesapeake Bay: A Q methodology study. Journal of Rural Studies, 60: 21-31.</p><br /> <p>Simpson, Z.P., and B.E. Haggard. 2018. Optimizing the flow-adjustment of constituent concentrations via LOESS for trend analysis. Environmental Monitoring and Assessment 190:103</p><br /> <p>Singh, S., A. Abebe, and P. Srivastava. 2018. Evaluation of Nonparametric and Parametric Statistical Procedures for Modeling and Prediction of Cluster-Correlated Hydroclimatic Data. Water Resources Research, 54(9): 6948-6964.</p><br /> <p>Winchell, M.F., N. Peranginangin, R. Srinivasan and W. Chen. 2018. Soil and Water Assessment Tool model prediction of annual maximum pesticide concentrations in high vulnerability watersheds.&nbsp; Integrated Environmental Assessment and Management. Volume: 14(3), Pages: 358-368. DOI:10.1002/ieam.2014</p><br /> <p>Xiong, M., Z. Lin, and G. Padmanabhan (2018). Impact of bioenergy policy induced land use change on water quality under changing climate in the Northern Great Plains of the United States. International Journal of Global Environmental Issues 17(4): 364-390.</p><br /> <p>Wang, Y., H. Montas P.T. Leisnham, K. Brubaker, A. Shirmohammadi, V. Chanse, A. Rockler. 2017. A diagnostic decision support system for BMP selection in a small urban watershed. Water Resources Management 31(5): 1649-1664.</p><br /> <p>Wang, Y.*, H. Montas, K. Brubaker, P.T. Leisnham, A. Shirmohammadi, V. Chanse, A.K. Rockler (2016). Impact of spatial discretization of hydrologic models on spatial distribution of nonpoint source pollution hotspots. ASCE Journal of Hydrologic Engineering 10.1061/(ASCE)HE.1943-5584.0001455 , 04016047.</p><br /> <p><strong>Conference Proceedings</strong></p><br /> <p>Ly, P. and J. J. Ramirez-Avila. Hydrologic and Nutrient Removal Performance of Rain Gardens. Proceedings of the 2018 World Environmental and Water Resources Congress. Minneapolis, MN. 348-354 pp.</p><br /> <p>Saha, G., Cibin, R., Elliott, H. A., Gall, H. E., Shortle, J. S., &amp; Abler, D. G. 2018. Geospatial Landscape Analysis for Livestock Manure Management in Western Pennsylvania. (pp. 1:12). St. Joseph, MI: ASABE. DOI:10.13031/aim.201801218.</p><br /> <p>Steele, J., J. Grafe, J.J. Ramirez-Avila. 2018. Analyzing Suspended Sediment Transport in Catalpa Creek. Proceedings of the 2018 World Environmental and Water Resources Congress. Minneapolis, MN. 336-347 pp.</p><br /> <p>Wilkinson, H.M., B. Spiller, N. Forbes, S.L. Ortega-Achury and J.J. Ramirez-Avila. 2018. The Effects of Forested Riparian Zones on Stream Conditions.&nbsp; Proceedings of the 2018 World Environmental and Water Resources Congress. 318-326 pp.</p><br /> <p>Wilson, L. E., &amp; Ramirez-Avila, J. J. The Effects of Tillage Practices on the Nutrient Enrichment of Eroded Materials. Proceedings of the 2018 World Environmental and Water Resources Congress. Minneapolis, MN. 223-230 pp.</p><br /> <p>&nbsp;</p><br /> <p><strong>Conference presentations</strong></p><br /> <p>Addy, K., A.J. Gold, J.A. Loffredo, A.W. Scroth, S.P. Inamdar and W.B. Bowden. 2017. Stream response to an extreme drought induced defoliation event. American Geophysical Union Annual Conference.&nbsp; Dec 11-15, New Orleans, LA.</p><br /> <p>Alamdari, N., Sample, D., Lee, J. G., and Yazdi, M. ,2018. Comparing Tools for Integrating Cost Optimization with Simulation Modeling in Urban Watersheds. In Chesapeake Research and Modeling Symposium 2018. Annapolis, MD.</p><br /> <p>Alamdari, N., and Sample, D.J., 2018. Evaluating the impact of climate change on the effectiveness of Rainwater Harvesting Systems across the U.S.. In World Environmental and Water Resources Congress 2018. Minneapolis, MN.</p><br /> <p>Cibin, R., Saha, G., Abler, D. G., Elliott, H. A., Shortle, J. S., &amp; Gall, H. E. (October 2018). "Environmentally and Economically Sustainable Agricultural Development: Exploring Regional Animal Agriculture Potential," ASABE Global Water Security Conference, Hyderabad. India. International.</p><br /> <p>Czarnecki, J. Linhoss, A., Hathcock, L., Ramirez-Avila, J., &amp; Schauwecker, T. 2018. Assessing Soil Erosion with Unmanned Aerial Vehicles for Precision Conservation. 73rd Soil and Water Conservation Society International Annual Conference. Albuquerque, NM.</p><br /> <p>Guzman, S., R. Karki, and P. Srivastava. 2018. Nutrient and Water Transport and Uptake in Corn Production Systems: A Field Scale Assessment in Southern Georgia, US. Paper No. 18-01532. ASABE Annual International Meeting, Detroit, Michigan, July 28-August 1, 2018.</p><br /> <p>Guzman, S., R. Karki, and P. Srivastava. 2018. Effect of Climate Variability on Crop Yield in the Lower Flint River Basin in Southeastern United State. Paper No. 18-01534. ASABE Annual international meeting, Detroit, Michigan, July 28-August 1, 2018.</p><br /> <p>Grafe, J., Ramirez-Avila, J. J., Schauwecker, T., Ortega-Achury, S. L., Prince Czarnecki, J. M., &amp; Langendoen, E. 2018. Understanding Relations between Streamflow, Turbidity, and Suspended-Sediment Concentration in an Impaired Mississippian Stream. Proceedings Mississippi Water Resources Research institute. Jackson, MS.</p><br /> <p>Haas, H. and L. Kalin. 2018. Modelling the impacts of conservation practices on water quality at a reservoir catchment in southern Brazil. 2018 SWAT Conference, Sep 17-21, 2018, Brussels, Belgium.</p><br /> <p>Hassanzadeh, Y., Vidon, P., Gold, A., Pradhanang, S., and Addy, K., 2017 Modeling the effects of hydrogeomorphology and climatic factors on nitrogen, phosphorus and greenhours gase dynamics in riparian zones. American Geophysical Fall Meeting, New Orleans, LA</p><br /> <p>Jahan, K., and Pradhanang, S.M., 2017. Short-term forecast of total phosphorus concentration in New York City water supply system using artificial neural network, Geological Society of America, Annual meeting, Oct 22-25, 2017, Seattle, Washington</p><br /> <p>Johnson, Z., Julius, S., Fischbach, J., Bennett, M., Benham, B., Sample, D., and Stephenson, K., 2018. Monitoring and Assessing Impacts of Changes in Weather Patterns and Extreme Events on BMP Siting and Design. Annapolis, MD: Science and Technical Advisory Committee, Chesapeake Bay Program, 48 p.</p><br /> <p>Kanber, R. and L. Kalin. 2018. Assessing Input Uncertainty and Sensitivity of Process-based Wetland Water Quality Model WetQual, Alabama Water Resources Conference &amp; Symposium, September 5-7, Orange Beach, AL.</p><br /> <p>Karki, R., S. Guzman, and P. Srivastava. 2018. Recharge Potential during Wet and Dry Years of the Upper Floridan Aquifer in the Lower Apalachicola-Chattahoochee-Flint River Basin, USA. Paper No. 18-01491. ASABE Annual International Meeting, Detroit, Michigan, July 28-August 1.</p><br /> <p>Leisnham, P.T., H. Montas, A. Shirmohammadi. 2016. Watershed Diagnostics for Improved Adoption of Management Practices: Integrating Biophysical and Social Factors Across Urban and Agricultural Landscapes. 4th International One Health Congress &amp; 6th Biennial Congress of the International Association for Ecology and Health. Melbourne, Australia.</p><br /> <p>Lin, Z., and M. Anar (2018). Parameter Estimation, Transferability Evaluation and Predictive Uncertainty Analysis of a Sugarbeet Model Using PEST. ASABE Paper No. 1800231. St. Joseph, MI.: ASABE</p><br /> <p>Ly, P. and J. J. Ramirez-Avila. Hydrologic and Nutrient Removal Performance of Rain Gardens. Proceedings of the 2018 World Environmental and Water Resources Congress. Minneapolis, MN. 348-354 pp.</p><br /> <p>Ly, P., &amp; Ramirez-Avila, J. J. 2018. Hydrologic and Nutrient Removal Performance of Rain Gardens: A Review. Proceedings Mississippi Water Resources Conference. Jackson, MS.</p><br /> <p>Malhotra, K., J. Lamba, and S. Shepherd. 2018. Sediment Fingerprinting to Identify Sources of Stream bed Sediment in an Urbanized Watershed. ASABE Annual International Meeting, Detroit Michigan, July 29-August 1, 2018.</p><br /> <p>Malhotra, K., J. Lamba, P. Srivastava, and S. Shepherd. 2018. Sediment Fingerprinting to Identify Sources of In-Stream Sediment in an Urbanized Watershed, Alabama Water Resources Conference and Symposium, Orange Beach, Alabama, September 5-7, 2018.</p><br /> <p>Nayeb Yazdi, M., Sample, D.J., Scott, D., and Owen, J.S., 2018. Water Quality Characterization of Irrigation and Storm Runoff for a Nursery,&rdquo; in New Trends in Urban Drainage Modelling, International Conference on Urban Drainage Modeling, UDM 2018, Springer, pp. 788&ndash;793.</p><br /> <p>Nayeb Yazdi, M.Sample, D.J., and Owen, J. S., 2018. Water Quality Characterization for Nursery Irrigation and Storm Runoff. In World Environmental and Water Resources Congress 2018. Minneapolis, MN.</p><br /> <p>Nayeb Yazdi, M., Sample, D.J., and Scott, D., 2018. Comparing HSPF and SWMM Watershed Model Applications at Various Scales to Improve Selection of Stormwater Control Measures. In Virginia Water Conference. Richmond, VA.</p><br /> <p>Paul, S., Pradhanang, S. M., and Boving, T., 2018. Sensitivity Analysis of Multi-site Calibration and Validation for Scituate Reservoir-drinking Water Supply Watershed, RI AWRA 2018 Spring Specialty Conference, GIS and Water Resources: Spatial Analysis of Watersheds: Ecological, Hydrological and Societal Responses Orlando, FLApril 22 &ndash; 25, 2018</p><br /> <p>Paul, S., Pradhanang, S.M., and Boving, T., 2018. Effects of weather on defoliation of forest and impacts on hydrologic cycle. UCOWR/NIWR 2018, Annual Water Resource Confernce, June 26-28, 2018. Pittsburg, PA.</p><br /> <p>Prasad, R., B. Ortiz, A.L. Kipling and J. Lamba. 2018. Evaluation of Nitrogen Losses from a Corn System Receiving Two Nitrogen Sources, Rates and Application Time.&nbsp; ASA and CSSA Meeting, Baltimore, Maryland, November 4-7, 2018.</p><br /> <p>Ramesh, R. L. Kalin, M. Hantush, M. Rezaienzadeh, C. Anderson. 2018. Modeling Strategies for a Groundwater Dominated Headwater System, 2018 SWAT Conference, Sep 17-21, 2018, Brussels, Belgium.</p><br /> <p>Ramesh, R., C. Anderson, and L. Kalin. 2018. Characterizing the Hydrology and Water Quality Function of Headwater Slope Wetlands, Alabama Water Resources Conference &amp; Symposium, September 5-7, Orange Beach, AL.</p><br /> <p>Ramirez-Avila, J.J.; T. Schauwecker; J. Czarnecky; E. Langendoen; S. Ortega-Achury; J. Martin. 2018. Quantifying and Modeling in-Stream Processes: A first step to restore the Catalpa Creek. World Environmental and Water Resources Congress 2018.</p><br /> <p>Ramirez-Avila, J. J., Schauwecker, T., Martin, James L., Ortega-Achury, S. L., &amp; Prince Czarnecki, J. M. 2018. A Project Based Learning Study Oriented to Develop a Natural Stream Restoration Design. Proceedings Mississippi Water Resources Conference. Jackson, MS.</p><br /> <p>Ramirez-Avila, J. J., Grafe, J., Schauwecker, T., Ortega-Achury, S. L., Martin, James L., Noble, T., &amp; Prince Czarnecki, J. M. 2018. Impacts of Riparian Buffer Zones on Stream Water Quality: A Quantitative Assessment in the Catalpa Creek Watershed. Proceedings Mississippi Water Resources Conference. Jackson, MS.</p><br /> <p>Ramirez-Avila, J; Schauwecker, T; Czarnecki, J; Ortega-Achury, S. L.; Langendoen, L. and Martin, J. 2018. Identification and assessment of stream processes within the Catalpa Creek in Mississippi. Ecostream Conference. Asheville, NC.</p><br /> <p>Saha, A., Chen, Y., Cibin, R., &amp; Ambrose, K. (July 2018). "Estimation of slow release fertilizer impacts through development of computational algorithm for a watershed model," The Northeast Agricultural and Biological Engineering Conference (NABEC), Morgantown, West Virginia. USA. Regional.</p><br /> <p>Saha, G., Cibin, R., Gall, H. E., Elliott, H. A., &amp; Shortle, J. S. (August 2018). "Geospatial Landscape Analysis for Manure Management in Western Pennsylvania.," ASABE 2108 Annual International Meeting, Detroit, Michigan. USA. International.</p><br /> <p>Saha, A., &amp; Cibin, R. (July 2018). "Identifying Nutrient Loading Hotspots in Susquehanna River Basin Using SWAT," Chesapeake Community Research &amp; Modeling Symposium, Annapolis, MD. USA. Regional.</p><br /> <p>Saha, G., Cibin, R., Gall, H. E., Elliott, H. A., &amp; Shortle, J. S. (July 2018). "Quantifying Potential Environmental Impacts of Animal Agricultural Developments in Western Pennsylvania," The Northeast Agricultural and Biological Engineering Conference (NABEC), Morgantown, West Virginia. USA. Regional.</p><br /> <p>Sample, D.J., 2018. Urban Stormwater Research Optimization for Watershed Restoration. In Universities Council on Water Resources, Annual Conference 2018. Pittsburgh, PA</p><br /> <p>Sample, D., Alamdari, N., and Lee, J. G., 2018. Optimizing Watershed Improvement Strategies-Comparing RSWMM-Cost and SUSTAIN. In World Environmental and Water Resources Congress 2018. Minneapolis, MN.</p><br /> <p>Schauwecker, T.; J.J. Ramirez-Avila; J. Czarnecki, J; B. Baker. 2018. Hydraulic and vegetative modeling for the restoration design of the upper reach of catalpa creek, an impaired stream in northeast Mississippi. 2018 National Conference on Ecosystem Restoration. New Orleans, LA. Poster Presentation</p><br /> <p>Seybold, E.C., A. Gold, S. Inamdar, S. Pradhanang, W.B. Bowden, M. Vaughan, K. Addy, J. Shanley, A. Vermilyea, R. Sleeper, D. Levia, C. Adair, B. Wemple, and A. Scroth.&nbsp; 2017. Effects of land use on the timing and magnitude of dissolved organic carbon and nitrate fluxes: A regional analysis of high-frequency sensor measurements from forested, agricultural and urban watersheds.&nbsp; American Geophysical Union Annual Conference.&nbsp; Dec 11-15, New Orleans, LA.</p><br /> <p>Steele, J., J. Grafe, J.J. Ramirez-Avila. 2018. Analyzing Suspended Sediment Transport in Catalpa Creek. Proceedings of the 2018 World Environmental and Water Resources Congress. Minneapolis, MN. 336-347 pp.</p><br /> <p>Thompson, T. M., Ketabchy, M., Sample, D., and Yazdi, M., 2018. Modeling Thermal Pollution in Urbanized Watersheds using a Hybrid Approach. In EWRI World Environmental and Water Resources Congress. Minneapolis, MD.</p><br /> <p>Wilkinson, H.M., B. Spiller, N. Forbes, S.L. Ortega-Achury and J.J. Ramirez-Avila. 2018. The Effects of Forested Riparian Zones on Stream Conditions.&nbsp; Proceedings of the 2018 World Environmental and Water Resources Congress. 318-326 pp.</p><br /> <p>Wilson, L. E., &amp; Ramirez-Avila, J. J. The Effects of Tillage Practices on the Nutrient Enrichment of Eroded Materials. Proceedings of the 2018 World Environmental and Water Resources Congress. Minneapolis, MN. 223-230 pp.</p><br /> <p>Wilson, L. E., Ramirez-Avila, J. J., &amp; Almansa-Manrique, E. F. (2018). Predicting the Effects of Conservation Practices in Tropical Soils. Proceedings MWRRI. Mississippi Water Resources Research Institute. Jackson, MS.</p><br /> <p>&emsp;</p><br /> <p><strong>Thesis/Dissertation</strong></p><br /> <p>Alamdari, N., 2018. Modeling Climate Change Impacts on the Effectiveness of Stormwater Control Measures in Urban Watersheds, PhD, Virginia Polytechnic Institute and State University, 165 p.</p><br /> <p>Arora, P. 2018. Modeling Effectiveness of Broiler Litter Application Method and Timing for Reducing Phosphorus and Nitrogen losses in Big Creek Watershed,</p><br /> <p>Coleman, B., 2018. Impact of Biochar Amendment, Hydraulic Retention Time, and Influent Concentration on N and P Removal in Horizontal Flow-Through Bioreactors, MS, Virginia Polytechnic Institute and State University, 189 p.</p><br /> <p>Frazar, S. 2018. Nutrient flux from extreme climatic events: agricultural vs. urban watersheds.&nbsp; Major paper submitted in partial fulfillment of the requirements for the degree of Master of Environmental Science and Management.&nbsp; University of Rhode Island, Kingston, RI.</p><br /> <p>Keys, T.A., 2018. Monitoring and Managing River Corridors in the Midst of Growing Water Demand, PhD, Virginia Polytechnic Institute and State University, 105 p.</p><br /> <p>Ketabchy, M., 2017. Thermal Evaluation of an Urbanized Watershed using SWMM and MINUHET: a Case Study of the Stroubles Creek Watershed, Blacksburg, VA, MS, Virginia Polytechnic Institute and State University, 114 p.</p><br /> <p>Malhotra, K. 2018.&nbsp; Sediment Fingerprinting to Identify Sources of In-Stream Sediment in an Urbanized Watershed.</p><br /> <p>Robinson, D.J., 2018. Assessing Green Infrastructure Needs in Hampton Roads, Virginia and Identifying the Role of Virginia Cooperative Extension, MS, Virginia Polytechnic Institute and State University, 144 p.</p><br /> <p>Understanding Wetland Hydrology and Water Quality though Data/Process-based Modeling, Rasika Ramesh</p><br /> <p>Wade, T., 2018. Modeling Effects of Rainwater Harvesting Systems on Water Yield Increase and Non-Beneficial Evaporation Reduction to Sustain Agriculture in a Water-Scarce Region of China, MS, Old Dominion University, 51 p.</p><br /> <p>Wagena, M., 2018 Quantifying the Impact of Climate Change on Water Availability and Water Quality in the Chesapeake Bay Watershed, PhD, Virginia Polytechnic Institute and State University, 208 p.</p><br /> <p>&emsp;</p><br /> <p><strong>Reports</strong></p><br /> <p>Fox, L.J., Robinson, D.J., Sample, D. J. and Wolford, C.E, 2018. Stormwater Management for Homeowners Fact Sheet 1 Rooftop Redirection (disconnection), https://pubs.ext.vt.edu/SPES/SPES-9/SPES-9.html</p><br /> <p>Fox, L. J., Sample, D. J., and Robinson, D. J., 2018. Stormwater Management for Homeowners Fact Sheet 5 Rain Gardens, SPES-13P, https://pubs.ext.vt.edu/SPES/SPES-13/SPES-13.html</p><br /> <p>Fox, L. J., Sample, D. J., and Robinson, D. J., 2018. Stormwater Management for Homeowners Fact Sheet 6 Buffers, SPES-14P , https://pubs.ext.vt.edu/SPES/SPES-14/SPES-14.html</p><br /> <p>Fox, L. J., Sample, D. J., Robinson, D. J., and Nelson, G. E., 2018. Stormwater Management for Homeowners Fact Sheet 4 Grass Swale, SPES-12P, https://pubs.ext.vt.edu/SPES/SPES-12/SPES-12.html</p><br /> <p>Fox, L. J., Sample, D. J., Robinson, D. J., and Wolford, C. E., 2018. Stormwater Management for Homeowners Fact Sheet 3 Permeable Pavement, SPES-11P, https://pubs.ext.vt.edu/SPES/SPES-11/SPES-11.html</p><br /> <p>Fox, L. J., Sample, D. J., Robinson, D. J., and Nelson, G. E., 2018. Stormwater Management for Homeowners Fact Sheet 2 Rain Barrels, SPES-10P, https://pubs.ext.vt.edu/SPES/SPES-10/SPES-10.html</p><br /> <p>Pradhanang, S. M., Boving, T., Meadows, M., and Hadjeres, H. 2018. Occurrence and Formation of N-DBPs in Source Waters of Rhode Island, Water Resource Center, Annual Technical Report, USGS</p><br /> <p>&nbsp;</p><br /> <p><strong>Model development</strong></p><br /> <p>RSWMM-Cost was developed to provide support for optimizing the selection and placement of best management practices (BMPs) in an urban watershed using EPA-SWMM models.&nbsp; Model available at: https://github.com/nasrinalam/RSWMM-CostAutomation. Case study application p aper is in review: Alamdari, N., Sample, D.J., In Review. A Multiobjective Simulation-Optimization Tool for Assisting in Urban Watershed Restoration Planning, Journal of Cleaner Production.</p><br /> <p>SWMM: A novel application of EPA-SWMM to characterize runoff from a commercial nursery operation was developed.&nbsp; Case study application is described in Nayeb Yazdi, M., Sample, D.J., Scott, D., and Owen, J.S., 2018. Water Quality Characterization of Irrigation and Storm Runoff for a Nursery,&rdquo; in New Trends in Urban Drainage Modelling, International Conference on Urban Drainage Modeling, UDM 2018, Springer, pp. 788&ndash;793.</p><br /> <p>HSPF: Disaggregated HSPF models were developed for comparison with SWMM in various watersheds of the City of Virginia Beach.&nbsp; Research is ongoing (Nayeb Yazdi).</p><br /> <p>HSPF/SWMM: An HSPF and a SWMM model were developed for the Stroubles Creek watershed, Blacksburg, VA., and calibrated for a comparison study in Nayeb Yazdi, M., Ketabchy, M., Sample, D.J., Scott, D., 2018. Evaluating HSPF and SWMM Model Applications to Simulate Baseflow and Peak flow in a Large Urban Watershed. Environmental Modelling &amp; Software (In Review).:</p><br /> <p>SWMM/MINUHET: a novel hybrid of SWMM and MINUHET was developed for thermal modeling of urban runoff, model case study application in Ketabchy, M., Sample, D.J., Wynn-Thompson, T., and Nayeb Yazdi, M., 2018. Thermal evaluation of urbanization using a hybrid approach, Journal of Environmental Management, 226 (August), pp. 457&ndash;475, doi: 10.1016/j.jenvman.2018.08.016</p><br /> <p>Rainwater Harvesting (RWH): A model of RWH was improved and extended to incorporate climate change assessments, as described in Alamdari, N., Sample, D. J., Liu, J., and Ross, A., 2018. Assessing climate change impacts on the reliability of rainwater harvesting systems. Resources Conservation and Recycling, 132, 178-189. doi:10.1016/j.resconrec.2017.12.013</p>

Impact Statements

  1. Monthly conference calls were held since December 2017 searching to integrate and advance different tasks in the group. The integration of small subgroups interested in the preparation of peer reviewed journal papers and at least two research proposals were planned, and their progress was followed, during the celebration of the different calls along the year of 2018.
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Date of Annual Report: 09/11/2019

Report Information

Annual Meeting Dates: 05/29/2019 - 05/30/2019
Period the Report Covers: 05/29/2019 - 09/30/2019

Participants

Brief Summary of Minutes

Accomplishments

<p>Research highlights:</p><br /> <p>Zhuping Sheng (Texas A&amp;M) &ndash; urban stormwater management; community gardens; permeable surfaces; roof greenhouses.&nbsp;</p><br /> <ul><br /> <li>Challenge &ndash; salinity. Looking at potential reaction models.&nbsp; Looking to link GW models with SWAT (w/MODFLOW).&nbsp;</li><br /> <li>Recommendations &ndash; uncertainty of data, incorporate RS via UAVs; use UAVs to assess salinity; multispectral imaging to assess salinity??</li><br /> </ul><br /> <p>&nbsp;Rabin Bhattarai (UIUC) &ndash;</p><br /> <ul><br /> <li>challenges of assessing impact of NPS, specifically nutrients (nitrates, phosphates) on water quality; $4M project to collect data to assess farm BMPs and field response to different nutrient inputs vs. topography/soil/weather/drained &amp; undrained fields, etc. Farm-to-farm monitoring.</li><br /> <li>Looking at denitrification and phosphate removal media (ie. divert water for denitrification and phosphate removal media). Developing a web tool and enter their farming information, brings up wx, SSURGO info, to see implications and implement change in nutrient practices. Project to look at how drainage impacts yield and nutrient practices to optimize drainage system.</li><br /> <li>Side comments &ndash; scaling is important. We need to be able to look at large &amp; small-scale models (can we effectively up-scale small scale models)?&nbsp; Larger scale models give us regional assessments of environmental hydrologic issues.&nbsp; Smaller scale models are necessary for BMPs due to localities of water management.&nbsp;</li><br /> </ul><br /> <p>Sunday (Iowa) &ndash;</p><br /> <ul><br /> <li>Using techniques to input field strips (roadside ditches) into models and evaluate their effectiveness &ndash; looking at where they are in landscape, adding to maps, and using them to model hydrology w/roadside ditches.</li><br /> <li>Attempting for a comprehensive database of structural and non-structural BMPs. Question &ndash; 1) how do we extend the BMPs that are normally structured to small (field) scale, but when using watershed scale models to evaluate their effectiveness? Do we scale down models or scale up BMPs?&nbsp; 2) how do we integrate BMPs into models?&nbsp;</li><br /> </ul><br /> <p>&nbsp;Cibin Raj (Penn State)</p><br /> <ul><br /> <li>manure management &amp; &ldquo;manure-sheds&rdquo;; phosphorous index; built geospatial tool to look at landscape, proximity to streams, and various other indicators, and assess how suitable locations are for manure management.</li><br /> <li>Adaptability of BMPs and influence on riparian areas &ndash; looking at flexible buffer systems, what is grown &amp; how it is managed in the riparian buffers. Using SWAT and ANAGNPS for buffer-specific nutrient loading.</li><br /> <li>Using SWAT for Chesapeake Bay modeling (vice Ches Bay model).</li><br /> <li>Interested in uncertainty of BMPs. Exploring landscape optimization, nutrient management, and scalability.&nbsp; Looking at slow-release fertilizers.</li><br /> <li>Also looking at urban BMPs &ndash; identification, monitoring, quantification &amp; effectiveness.</li><br /> </ul><br /> <p>&nbsp;Art Gold (URI) &nbsp;</p><br /> <ul><br /> <li>UV vis sensors to understand contaminant fluxes during baseflow and storm events. Focus/challenge &ndash; concentration vs. flow (C vs. Q) &ndash; doesn&rsquo;t scale well &amp; see very different relationships in large vs. small catchments.</li><br /> <li>Algae/cynoabacteria blooms &ndash; increasing # of lakes closed due to algal blooms: what&rsquo;s the role of the timing and extent of nutrients on these algal blooms? EPA wants the right to measure nutrient outputs &amp; take action.</li><br /> </ul><br /> <p>&nbsp;David Sample (Virginia Tech)</p><br /> <ul><br /> <li>Temperature is not well-accounted for in ag or urban models (one motivator is toxicity to trout);</li><br /> <li>uses SWMM. R-SWMM optimizes. Monitoring:&nbsp; monitoring ponds as nutrient retention locations &ndash; is phosphorous getting bound in sediments, is it mobile, are they exporting nitrogen?&nbsp;</li><br /> <li>Looking at bioretention in ponds &amp; wetlands as a real-time control system for nutrient loading and flooding control.</li><br /> <li>Process based model</li><br /> </ul><br /> <p>&nbsp; Soni (URI)</p><br /> <ul><br /> <li>riparian buffer zones, modeling of N &amp; P loading (Marzia);</li><br /> <li>mitigation plan for reservoir flooding (SWAT integrated with OASIS for reservoir release operations) (Supria);</li><br /> <li>urban hydrology modeling &amp; effectiveness of roadside best-management practices &amp; impact of soil amendment via SWMM (Luna);</li><br /> <li>saltwater intrusion monitoring (GPR, electro resistivity, UAVs), MODFLOW coupled SEAWAT, &amp; requires climate input for storm surges (Jeeban &amp; Mamoon);</li><br /> <li>downscaling of climate data for RI &amp; machine-learning to assess high frequency signals (Shiva).</li><br /> <li>Precursors of disinfection by products (Maxwell and Hichem)</li><br /> <li>PRMS modeling for runoff prediction/climate change k-nn clustering, fourier transformation to understand baseflow and stream temperature (Kyle)</li><br /> </ul>

Publications

Impact Statements

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Date of Annual Report: 01/01/1970

Report Information

Annual Meeting Dates: 05/29/2019 - 05/30/2019
Period the Report Covers: 10/01/2018 - 09/30/2019

Participants

Soni M. Pradhanang (University of Rhode Island), Arthur Gold (University of Rhode Island), Kelly Addy (University of Rhode Island) , Zhuping Sheng (Texas A &M), Rabin Bhattarai (UIUC), Prasanta Kalita(University of Illinios-UC), Sunday Tim (IowaState), David Sample (Virginia Tech), Cibin Raj (Penn State), Kyle Young (URI), Marzia Tamanna (URI), Jeeban Panthi (URI), Khurshid Jahan (URI), Shiva Shrestha (URI), Mamoon Ismail (URI), Sarah McMillan (Purdue University), Adel Shirmohamadi (University of Maryland)

Brief Summary of Minutes

Accomplishments

Publications

Impact Statements

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