Lake Champlain Basin Research Articles

Watershed-scale spatial prediction of agricultural land phosphorus mass balance and soil phosphorus metrics: A bottom-up approach.

Analysis of nutrient balance at the watershed scale, including for phosphorus (P), is typically accomplished using aggregate input datasets, resulting in an inability to capture the variability of P status across the study region. This study presents a set of methods to predict and visualize partial P mass balance, soil P saturation ratio (PSR), and soil test P for agricultural parcels across a watershed in the Lake Champlain Basin (Vermont, USA) using granular, field-level data. K-means cluster analyses were used to group agricultural parcels by soil texture, average slope, and crop type. Using a set of parcels accounting for ∼21% of the watershed's agricultural land and having known soil test and nutrient management parameters, predictions of partial P mass balance, PSR, and soil test P for agricultural land across the watershed were made by cluster, incorporating uncertainty. This resulted in an average partial P balance of 5.5±0.2kg P ha-1year-1 and an average PSR of 0.0399±0.0002. Furthermore, approximately 30% of agricultural land had predicted soil test P values above optimum levels. Results were used to visualize areas with high P loss potential. Such data and visualizations can inform watershed P modeling and assist practitioners in nutrient management decision making. These techniques can also serve as a framework for bottom-up modeling of nutrient mass balance and soil metrics in other regions.

Evaluating opportunities for broad-scale remote sensing of total suspended solids on small rivers

Although broad-scale remote sensing applications are increasingly being integrated into water quality assessments, the feasibility of such applications on smaller rivers (<150 m. width) is not well understood, even though smaller rivers comprise most of the river network and can constitute significant sources of sediment and nutrients. We evaluated the application of a widely used Total Suspended Solid (TSS) algorithm within ten small (16–117 m wide) tributaries of the Lake Champlain Basin in the Northeastern US. Sentinel-2 images captured within 5 h of depth-integrated TSS samples were identified and corrected for atmospheric conditions to generate TSS estimates. Linkages between sample attributes and errors in the relationship between measured and predicted TSS values were explored to identify potential limits on the application of existing TSS algorithms to small rivers. From a dataset of 64 unique measured-predicted values on rivers whose channel width was greater than one pixel (i.e., 10 m), we found that there are settings along smaller rivers, and discrete flow and seasonal conditions, under which broad-scale remote sensing applications may be applicable. The remote sensing algorithm had the greatest success predicting TSS for rivers with high background levels of sediment (i.e., large concentrations during smaller discharges). Errors in estimated TSS were three times greater on rivers with low background levels (average error of 174%) of sediment than high levels (average error of 57%), likely due to differences in the proportion of fine-grained particle-sizes in transport. We also found that estimated TSS error was less outside the growing season, when biological activity was limited and plants were dormant, and when higher flows occurred such that backscatter from the channel bed is less likely to interfere with the reflective signal. This effect was most pronounced on rivers with low background sediment loads; errors in estimated TSS were more than six times greater during the growing season on rivers with low background loads (average error of 216%) than when plants were dormant (average error of 48%). We hypothesized that algorithm performance on smaller rivers, as measured by channel width, would be prone to larger errors due to the greater influence of contrasting reflectance signals from soils and vegetation along riverbanks. The degree of limitation from this adjacency effect was not evident in our dataset perhaps because of a correlation between river size and sediment characteristics unique to our study area. An alternative parameterization of a single-band empirical TSS model for small rivers in the region, based on inclusion of readily identifiable geologic and temporal characteristics, suggests improved predictive power for small rivers. Results highlight the feasibility of extending remote sensing applications throughout the river network in temperate regions of the Northeastern U.S. Certain geologic settings, specifically those that transport finer-grained loads, are more likely to have accurate predictions, especially during the colder months, when in situ monitoring is particularly challenging, yet highly important because a significant portion of runoff events in the Northeastern U.S. occur in this time.

Using the Transtheoretical Model of Behavior Change to Explore Forest Landowner Perspectives on Water Quality

Family forest owners (FFOs) are critical stakeholders in ensuring many conservation outcomes, including improved water quality. In the highly forested Lake Champlain basin of Vermont, FFOs likely play a particularly important role in addressing water quality impairment. This study focused on FFOs’ thinking and decision-making around management practices on their land. Based on a dataset of 28 interviews collected using a semi-structured interview approach, the interviews were qualitatively coded and analyzed using the Transtheoretical Model of behavior change (TTM) framework. Our findings suggest that interviewed landowners were concerned about basin water quality but generally not aware of the connection between watershed health and actions taken on their particular forest parcel. We further describe how three TTM Processes of Change (helping relationships, consciousness raising, and environmental re-evaluation) may influence landowners’ decisions to manage their forests with water quality in mind. Our results suggest pathways for the design and targeting of behavioral change interventions based on the TTM that should inform landowner outreach as well as further research.

Understanding reduced salt practices used by commercial snow removal businesses in the Lake Champlain Basin: A mixed methods analysis

Understanding reduced salt practices used by commercial snow removal businesses in the Lake Champlain Basin: A mixed methods analysis

Engagement in water governance action situations in the Lake Champlain Basin.

Water quality governance encompasses multiple "wicked" interacting problems that manifest within social-ecological systems. Concerned governments, institutions, and actors concerned with addressing these issues must wrestle with complex systems that span time, space, and scale. This complexity of connected systems requires the participation of multiple actors across political boundaries, problem areas, and hydrologic domains. In Lake Champlain (US), frequent cyanobacteria blooms negatively affect property values, recreational activities, and public infrastructure, in addition to their impacts on the aquatic ecosystem. Through a survey of actors working on water quality in the Lake Champlain Basin, we analyze how actor participation in structured issue forums creates a network of connected action situations across multiple spatial scales and problem domains. We apply exponential random graph models to quantify the effects of scale, issues, and homophily on actor participation in these forums. Our findings show that actors tend to favor participating in similarly scoped forums at their spatial scale, that actors are less likely to participate in structured forums focused on agriculture, and that actors participate independently of others with whom they have pre-existing collaborative relationships. Further, we find that in the case of the Lake Champlain Basin, actor participation in issues related to water quality is misaligned with modeled sources of nutrient pollution. This study demonstrates that the design and maintenance of water quality action situations play an important role in attracting the participation of actors working collaboratively to address wicked social-ecological problems. Further, linking current and potential configurations of governance networks to social-ecological outcomes can aid in the effective and efficient achievement of management objectives.

A network perspective on multi-scale water governance in the Lake Champlain Basin, Vermont

The prevalence and persistence of harmful cyanobacterial blooms demonstrate the importance of governance systems that effectively engage with many actors to address nonpoint pollution from a variety of sources across multiple spatial domains. Although the importance of social-ecological alignment on effective governance is increasingly clear, governance systems often evolve incrementally and in a manner that fails to adequately align resources and governance networks with biophysical structures, processes, and legacies. Through a survey of water governance actors in the Lake Champlain Basin, we map the structure of the water governance network and identify the key information brokers, flows of resources, and ongoing collaborative partnerships. We measure cross-scale and within-scale linkages to characterize the degree of coordination across space and scale using exponential random graph models, finding distinct differences in governance activities by mode of coordination. We also show that coordination in the system is largely a function of geographic proximity and shared issues of concern, demonstrating the importance of multidimensional, social-ecological perspectives in the collaborative governance of freshwater systems. Specific to the Lake Champlain Basin, our findings suggest that as the transformation of the governance system proceeds, cross-scale and inter-watershed coordination must be regularized to maintain learning and innovation across the system as it pursues its clean water goals.

Probabilistic simulation of phosphorus loss using the Vermont P-index: a bottom-up field to watershed approach

Abstract Anthropogenic nutrient loading from land use, especially agriculture, is a major threat to waterbodies worldwide. Efforts to govern nutrient pollution are increasingly based on simulation modeling for research, evaluation, and regulation. This study develops a novel approach to simulate nutrient losses from agriculture applied to the Lake Champlain basin in the US state of Vermont. The Vermont Phosphorus-Index—a farm-based empirical model regularly used for site evaluation—is scaled up to the basin level with high-resolution geographic data and probabilistic estimation of unknown parameters and management practices. Results are comparable with analyses using more data and computationally intensive tools. Important insights into basin-wide management include: (1) nutrient-management planning can significantly reduce P losses in a livestock-agriculture-dominated watershed by re-distributing manure applications from areas of high loss to low loss; (2) hotspot identification from geographic data alone may be deeply complicated by high underlying heterogeneity of soil phosphorus; and (3) probabilistic modeling using simple, field-scale models is a potentially useful complement to complex watershed process models. Findings suggest that currently available best-management practices will likely be insufficient to reach reduction targets in the most impaired sub-watersheds. Reductions of agricultural land use and herd size, particularly in intensive dairy operations, may be necessary.

Watershed model parameter estimation in low data environments

Study regionThree watersheds in the Lake Champlain Basin of Vermont, USA. Study focusWatershed models are essential for evaluating the impact of watershed management; however, they contain many parameters that are not directly measurable. These parameters are commonly estimated by calibration against observed data, often streamflow. Unfortunately, many areas lack long-term streamflow records, making parameter estimation in low data environments (LDE) challenging. A new calibration technique, simultaneous multi-basin calibration (MBC), was developed to estimate model parameters in LDE. Three Soil and Water Assessment Tool (SWAT) model initializations for USGS gages with ∼ 2-year records in the Lake Champlain Basin of Vermont, USA, were evaluated by comparing MBC and the commonly used similarity-based regionalization (SBR) approach, where calibrated parameters from a watershed with an extended data record are transferred to the LDE receptor watersheds. In MBC, each watershed is initialized, and observed flows from each initialization are aggregated to generate a combined streamflow record of sufficient length to calibrate using a differential evolution algorithm. New hydrological insights for the regionUsing this new MBC method, we demonstrate improved model performance and more realistic model parameter values. This study demonstrates that short periods of hydrological measurement from multiple locations in a basin can represent a system similarly to long term measurements and that even short records taken at multiple locations significantly improve our hydrologic knowledge of a system as compared to relying on the similarity of a basin with a long record of flow. In addition, this study revealed that the hydrologic response is mediated by the interplay of very low soil-saturated hydraulic conductivity (Ksat) and cracking soils. As a result, even if Ksat is very low, cracking clays have a large impact on runoff production Garna et al. (2022).

Multi‐scale drivers of spatial patterns in floodplain sediment and phosphorus deposition

AbstractThe capacity for floodplains to capture sediment and filter pollutants is spatially variable and depends on the complex interactions of geomorphic, geologic, and hydrologic variables that operate at multiple scales. In this study, we integrated watershed‐scale and local assessments to improve our understanding of floodplain depositional patterns. We developed a dataset of event‐scale observations of sediment and phosphorus deposition rates distributed at 129 plots across large environmental gradients of floodplain topography, valley geometry, and watershed characteristics in the Lake Champlain Basin, Vermont. Plot‐scale observations were used to evaluate the cross‐scale influence of environmental factors and were summarized into site‐scale averages to explore regional trends. Consistent with other studies, floodplain deposition generally scaled with drainage area, but trends were longitudinally discontinuous and depended on variations in valley width and slope. While variability in deposition patterns at the watershed‐scale was large (average of 2.0 (0.2–9.8) kg sediment m−2 yr−1; average of 1.4 (0.2–6.5) g phosphorus m−2 yr−1), the range in deposition rates locally across a floodplain was greater (average of 4.6 (0.06–21.7) kg sediment m−2 yr−1; average of 6.4 (0.1–41.1) g phosphorus m−2 yr−1). Local variables that described the proximity to water and sediment sources, and frequency with which the plot was activated by a flood, had the greatest relative contribution to boosted regression tree models of phosphorus deposition rates, highlighting the importance of river–floodplain connectivity for floodplain functioning and the profound impact of human activities that limit such connectivity. Patterns identified in our study may guide prioritization of restoration and conservation practices designed to capture sediment and phosphorus on floodplains.

Assessing Farmer Incentives for Transitioning Toward Sustainable Agriculture and Provisioning of Clean Water

Farms are a major source of water pollution in the form of nutrient run off that cause harmful algal blooms and anoxia, both signs of deteriorating water quality. Current policies that incentivize the adoption of nutrient management practices (NMPs) are insufficient, especially as climate change increases the frequency and intensity of flooding. To evaluate the incentives of current policy designs, we implemented a conjoint analysis on survey data collected in the Missisquoi and Lamoille watersheds of Lake Champlain Basin in three waves (2013, 2015, 2020). Using panel and cross-sectional observations over the three waves, we investigate farmers' willingness to accept (WTA) payment for NMPs that improve soil health and reduce nutrient runoff. We identified farmers' WTA for the adoption of three NMPs, cover cropping, conservation tillage, and buffer strips. The approach quantifies gaps between the incentives offered by the current federal conservation programs and payments preferred by farmers as well as the relative importance of NMP attributes. The influence of the payments decreased over the course of the three survey waves, suggesting the characteristics of NMPs are driving farmers' preferences for them. Our analysis shows farmers WTA is 1.13–6 times higher than what existing incentive programs offer. The incentive gaps between WTA and the cheapest of NMPs offered by EQIP are $55.61 for tillage, $103.60 for cover crop and $37.62 for buffers. Designing policy instruments to reduce this gap, the federal programs and policies will be more effective at scaling up the adoption of NMPs by farmers as a tool for sustainable watershed management.

Inequities in the distribution of flood risk under floodplain restoration and climate change scenarios

Abstract The combined impacts of climate change and ecological degradation are expected to worsen inequality within society. These dynamics are exemplified by increases in flood risk globally. In general, low‐income and socially vulnerable populations disproportionately bear the cost of flood damages. Climate change is expected to increase the number of people exposed to fluvial flood risk and cause greater property damages. Floodplain restoration has the potential to mitigate these impacts, but the distribution of future risks among different types of property owners under these altered conditions is often unknown. Here, we develop a simple probabilistic approach for estimating flood risk to property owners under floodplain restoration and climate change scenarios for a range of flood recurrence intervals. We apply this approach in the Vermont, USA portion of the Lake Champlain Basin. Over a 100‐year time horizon, we estimate that the value of property damages caused by flood inundation is approximately $2.13 billion under the baseline scenario. Climate change is expected to increase damages to $5.29 billion, a 148% increase; however, floodplain restoration has the potential to reduce these impacts by approximately 20%. For all scenarios, a larger proportion of lower‐value properties, specifically mobile homes, face greater flood risk compared to higher‐value properties. Climate change is expected to cost higher‐value properties and commercial properties more than other types of properties, but these same groups are also expected to benefit most from floodplain restoration. In general, these results raise concern that those least able to prepare for and recover from flood damages are also the people who face the greatest threats. In response, public policy interventions must consider not only where flood risk is most severe, but also the vulnerability of people exposed to such risk. Read the free Plain Language Summary for this article on the Journal blog.

Improving flood hazard datasets using a low-complexity, probabilistic floodplain mapping approach.

As runoff patterns shift with a changing climate, it is critical to effectively communicate current and future flood risks, yet existing flood hazard maps are insufficient. Modifying, extending, or updating flood inundation extents is difficult, especially over large scales, because traditional floodplain mapping approaches are data and resource intensive. Low-complexity floodplain mapping techniques are promising alternatives, but their simplistic representation of process falls short of capturing inundation patterns in all situations or settings. To address these needs and deficiencies, we formalize and extend the functionality of the Height Above Nearest Drainage (i.e., HAND) floodplain mapping approach into the probHAND model by incorporating an uncertainty analysis. With publicly available datasets, the probHAND model can produce probabilistic floodplain maps for large areas relatively rapidly. We describe the modeling approach and then provide an example application in the Lake Champlain Basin, Vermont, USA. Uncertainties translate to on-the-ground changes to inundated areas, or floodplain widths, in the study area by an average of 40%. We found that the spatial extent of probable inundation captured the distribution of observed and modeled flood extents well, suggesting that low-complexity models may be sufficient for representing inundation extents in support of flood risk and conservation mapping applications, especially when uncertainties in parameter inputs and process simplifications are accounted for. To improve the accuracy of flood hazard datasets, we recommend investing limited resources in accurate topographic datasets and improved flood frequency analyses. Such investments will have the greatest impact on decreasing model output variability, therefore increasing the certainty of flood inundation extents.

A mixed-methods analysis for improving farmer participation in agri-environmental payments for ecosystem services in Vermont, USA

We examine whether using a payment for ecosystem services (PES) framework for agri-environmental programs could increase farmer participation through a mixed methods approach. We assess the institutional design of two U.S. agri-environmental programs, the Environmental Quality Incentives Program (EQIP) and the Conservation Reserve Enhancement Program (CREP), in the Lake Champlain Basin in the northeastern US, where managing eutrophication from phosphorus pollution remains a challenge. We synthesize a checklist of institutional markers previously derived from past PES literature and assess the extent to which these two programs increase participation and achieve environmental goals. Our analysis demonstrates EQIP and CREP meet several PES principles. However, transaction costs present a barrier towards participation with both programs. We suggest these costs can be lowered by greater technical assistance. We categorize EQIP program data by their ecosystem service provision using the Millennium Ecosystem Assessment classification. We find EQIP demonstrates cost-effective targeting and conditionality yet may have an institutional focus on large-scale structural practices focused on “end of pipe” prevention of nutrient runoff. The positive effect that PES institutional design criteria have on participation in agri-environmental incentive programs motivates further research on synergies and tradeoffs between farmer participation and environmental outcomes.

Multivariate event time series analysis using hydrological and suspended sediment data

Hydrological storm events are a primary driver for transporting water quality constituents such as suspended sediments and nutrients. Analyzing the concentration (C) of these water quality constituents in response to river discharge (Q), particularly when monitored at high temporal resolution during a hydrological event, helps to characterize the dynamics and flux of such constituents. A conventional approach to storm event analysis is to reduce C-Q time series to two-dimensional (2-D) hysteresis loops and analyze these 2-D patterns. While informative, this hysteresis loop approach has limitations because projecting the C-Q time series onto a 2-D plane obscures detail (e.g., temporal variation) associated with the C-Q relationships. In this paper, we address this limitation using a multivariate event time series (METS) clustering approach that is validated using synthetically generated event times series. The METS clustering is then applied to river discharge and suspended sediment data (acquired through turbidity-based monitoring) from six watersheds in the Lake Champlain Basin located in the northeastern United States, and results in identifying four common types of hydrological water quality events. Statistical analysis on the events partitioned by both methods (METS clustering and 2-D hysteresis classification) helped identify hydrometeorlogical features of common event types. In addition, the METS and hysteresis analysis were simultaneously applied to a regional Vermont dataset to highlight the complimentary nature of using them in tandem for hydrological event analysis.

Modeling the Influence of Public Risk Perceptions on the Adoption of Green Stormwater Infrastructure: An Application of Bayesian Belief Networks Versus Logistic Regressions on a Statewide Survey of Households in Vermont

There is growing environmental psychology and behavior literature with mixed empirical evidence about the influence of public risk perceptions on the adoption of environmentally friendly “green behaviors”. Adoption of stormwater green infrastructure on residential properties, while costlier in the short term compared to conventional greywater infrastructure, plays an important role in the reduction of nutrient loading from non-point sources into freshwater rivers and lakes. In this study, we use Bayesian Belief Networks (BBNs) to analyze a 2015 survey dataset (sample size = 472 respondents) about the adoption of green infrastructure (GSI) in Vermont’s residential areas, most of which are located in either the Lake Champlain Basin or Connecticut River Basin. Eight categories of GSI were investigated: roof diversion, permeable pavement, infiltration trenches, green roofs, rain gardens, constructed wetlands, tree boxes, and others. Using both unsupervised and supervised machine learning algorithms, we used Bayesian Belief Networks to quantify the influence of public risk perceptions on GSI adoption while accounting for a range of demographic and spatial variables. We also compare the effectiveness of the Bayesian Belief Network approach and logistic regression in predicting the pro-environmental behaviors (adoption of GSI). The results show that influencing factors for current adoption differ by the type of GSI. Increased perception of risk from stormwater issues is associated with the adoption of rain gardens and infiltration trenches. Runoff issues are more likely to be considered the governments’ (town, state, and federal agencies) responsibility, whereas lawn erosion is more likely to be considered the residents’ responsibility. When using the same set of variables to predict pro-environmental behaviors (adoption of GSI), the BBN approach produces more accurate predictions compared to logistic regression. The results provide insights for further research on how to encourage residents to take measures for mitigating stormwater issues and stormwater management.

Social-psychological determinants of farmer intention to adopt nutrient best management practices: Implications for resilient adaptation to climate change

Successful adaptation to global climate change and enhancement of agricultural watersheds' resilience requires widespread use of Nutrient Best Management Practices (NBMPs) by farms of all sizes. In the US, adoption of many NBMP practices is voluntary and insufficient to achieve local and downstream conservation objectives. Despite evidence that both social-psychological factors and socio-economic factors influence farmer decision-making, very few studies of farmers' decision-making related to NBMP adoption combine these two factor groups in a theoretically rigorous way. To better understand farmers' management decisions, we test the social-psychological Theory of Planned Behavior (TPB) to determine the relative influence of attitudes, perceived social norms, and perceived behavioral control on adoption of nine NBMPs. A survey was designed by the research team and implemented by the U.S. Department of Agriculture-National Agricultural Statistics Service (USDA-NASS) in 2013, and replicated in 2016, on a stratified sample of 129 farmers (including panel data on 56 farmers). Farmers were located in the Missisquoi, and Lamoille River watersheds of the Lake Champlain Basin in the Northeast region of the United States. Survey responses revealed variation in past adoption of NBMPs was sensitive to practice type and farm size. We developed nine weighted structural equation models to test endogenous (social-psychological) and exogenous (policy, economic and demographic) predictors of farmer intention to adopt NBMPs. We found that perceived behavioral control had the largest effect size and strongest statistical significance on the farmers' expressed intentions to adopt NBMPs in the future. For a subset of NBMPs, perceived social norms and farmer attitudes toward these NBMPs were each also significant drivers of intention to adopt individual practices. Among the exogenous variables, we found that large farm size, college education, and having a conservation easement all had a positive influence on farmers' intention to adopt NBMPs. This study suggests that for widespread adoption of NBMPs, environmental managers, policy makers, and program developers should be attentive to farmers' perceived behavioral control, and support the design and execution of outreach and technical assistance programs that build on drivers of farmers’ decision making.

Modeling Alternative Collaborative Governance Network Designs: An Agent-Based Model of Water Governance in the Lake Champlain Basin, Vermont

AbstractWith the widespread use of collaborative governance mechanisms for mitigating water pollution, an opportunity exists to test alternative institutional designs based on collaborative governance theory using computer simulation models, particularly when there is a clear relationship between governance networks, observable resource allocation decisions, and measurable outcomes. This is especially the case for wicked problems like nonpoint source water pollution where there are compelling questions regarding how best to design policies, allocate funds, and build administrative capacity to meet water quality standards. We present an agent-based model (ABM) of water governance for the Lake Champlain Basin to simulate the impacts of alternative collaborative governance arrangements on the development of suites of water quality projects. The ABM is connected or coupled with land use and phosphorus load accumulation models that are informed by existing hydrologic models, project datasets, and state-set load reduction targets. We find that regionally arranged collaborative governance in water quality project planning and implementation can lead to better water quality outcomes, thereby affirming one of the central premises of collaborative governance regime theory. We also find that externally mandated collaboration, as opposed to voluntary, self-initiated collaboration, can lead to better water quality outcomes, adding to our understanding of which type of collaborative governance arrangement is best suited to the specific contexts of this case. Further, without adequate administrative capacity in the form of human resources located in central network actors to manage project funds, “administrative bottlenecks” may form and money can go unspent. This research demonstrates the efficacy of using simulations of alternative institutional design for theory testing and tuning, and policy prototyping.

Microhabitat use of landlocked juvenile Atlantic salmon (Salmo salar)

Large-scale reintroduction programs for landlocked Atlantic salmon Salmo salar are ongoing in Lakes Ontario and Champlain. Commonly, these programs involve stocking hatchery reared juveniles into streams and thus, quantifying the in situ habitat use of stocked fish can help support these efforts. To examine habitat use, we stocked young-of-the-year (YOY) Atlantic salmon into 14 reaches of the Boquet River in the Lake Champlain Basin. The habitat used by YOY Atlantic salmon, measured from microhabitats that were used versus not used, differed between early and late summer for water depth. In early summer, YOY Atlantic salmon used a more narrow range of habitats compared to late summer. However, in both early and late summer, YOY most often used intermediate values in habitat variables except for water velocity in early summer. In early summer, YOY Atlantic salmon had the highest probability of using a water depth of 26 cm, a water velocity of 1 cm/sec, and a pebble substrate. In late summer, the probability of use was highest at a water depth of 61 cm, a water velocity of 11 cm/sec, and a pebble substrate. Our results show that stocked landlocked YOY Atlantic salmon use similar habitats to anadromous populations and may help managers when determining stocking locations or habitat alterations.

Impacts of Tile Drainage on Phosphorus Losses from Edge-of-Field Plots in the Lake Champlain Basin of New York

Quantifying the influence of tile drainage on phosphorus (P) transport risk is important where eutrophication is a concern. The objective of this study was to compare P exports from tile-drained (TD) and undrained (UD) edge-of-field plots in northern New York. Four plots (46 by 23 m) were established with tile drainage and surface runoff collection during 2012–2013. Grass sod was terminated in fall 2013 and corn (Zea mays L.) for silage was grown in 2014 and 2015. Runoff, total phosphorus (TP), soluble reactive phosphorus (SRP), and total suspended solids (TSS) exports were measured from April 2014 through June 2015. Mean total runoff was 396% greater for TD, however, surface runoff for TD was reduced by 84% compared to UD. There was no difference in mean cumulative TP export, while SRP and TSS exports were 55% and 158% greater for UD, respectively. A three day rain/snowmelt event resulted in 61% and 84% of cumulative SRP exports for TD and UD, respectively, with over 100% greater TP, SRP and TSS exports for UD. Results indicate that tile drainage substantially reduced surface runoff, TSS and SRP exports while having no impact on TP exports, suggesting tile drains may not increase the overall P export risk.

Simulating precipitation and temperature in the Lake Champlain basin using a regional climate model: limitations and uncertainties

The Lake Champlain Basin has socioeconomic and ecological significance for the Northeastern United States and Quebec, Canada. Temperatures and extreme precipitation events have been increasing across this region over the past three decades. Accurate, high-resolution climate simulations are critical to assessing potential climate change risk in the Lake Champlain Basin. We evaluate the performance of a regional climate model, the Weather Research and Forecasting (WRF) model, to downscale ERA-Interim reanalysis data to 4 km for the Lake Champlain Basin. Specifically, we compare an ensemble of five WRF experiments with different physics configurations using a one-way, triple-nested domain (36, 12, and 4 km) over three 5-year periods (1980–1984, 1995–1999, and 2010–2014) to Daymet, a gridded observational dataset. We find that WRF simulations of the Lake Champlain Basin generally reproduce the observed temperature and precipitation seasonal cycles, but have cold and wet biases. The simulation of mean temperature by WRF is most sensitive to the choice of radiation scheme, while the simulation of mean precipitation is most sensitive to the choice of radiation, cumulus, and microphysics scheme. We find that turning the cumulus scheme on improves the simulation of the precipitation seasonal cycle at a 4 km resolution, but also substantially enhances the wet bias. Using a coarser resolution (36 km) produces smaller regionally averaged precipitation biases, but not improved correlations between simulated and observed monthly precipitation. Both spatial resolution and turning the cumulus scheme off have minor effects on simulated temperature.