Zachary M. Easton

Applicability of models to predict phosphorus losses in drained fields: a review.

Most phosphorus (P) modeling studies of water quality have focused on surface runoff loses. However, a growing number of experimental studies have shown that P losses can occur in drainage water from artificially drained fields. In this review, we assess the applicability of nine models to predict this type of P loss. A model of P movement in artificially drained systems will likely need to account for the partitioning of water and P into runoff, macropore flow, and matrix flow. Within the soil profile, sorption and desorption of dissolved P and filtering of particulate P will be important. Eight models are reviewed (ADAPT, APEX, DRAINMOD, HSPF, HYDRUS, ICECREAMDB, PLEASE, and SWAT) along with P Indexes. Few of the models are designed to address P loss in drainage waters. Although the SWAT model has been used extensively for modeling P loss in runoff and includes tile drain flow, P losses are not simulated in tile drain flow. ADAPT, HSPF, and most P Indexes do not simulate flow to tiles or drains. DRAINMOD simulates drains but does not simulate P. The ICECREAMDB model from Sweden is an exception in that it is designed specifically for P losses in drainage water. This model seems to be a promising, parsimonious approach in simulating critical processes, but it needs to be tested. Field experiments using a nested, paired research design are needed to improve P models for artificially drained fields. Regardless of the model used, it is imperative that uncertainty in model predictions be assessed.

Phosphorus fate, management, and modeling in artificially drained systems.

Phosphorus (P) losses in agricultural drainage waters, both surface and subsurface, are among the most difficult form of nonpoint source pollution to mitigate. This special collection of papers on P in drainage waters documents the range of field conditions leading to P loss in drainage water, the potential for drainage and nutrient management practices to control drainage losses of P, and the ability of models to represent P loss to drainage systems. A review of P in tile drainage and case studies from North America, Europe, and New Zealand highlight the potential for artificial drainage to exacerbate watershed loads of dissolved and particulate P via rapid, bypass flow and shorter flow path distances. Trade-offs are identified in association with drainage intensification, tillage, cover crops, and manure management. While P in drainage waters tends to be tied to surface sources of P (soil, amendments or vegetation) that are in highest concentration, legacy sources of P may occur at deeper depths or other points along drainage flow paths. Most startling, none of the major fate-and-transport models used to predict management impacts on watershed P losses simulate the dominant processes of P loss to drainage waters. Because P losses to drainage waters can be so difficult to manage and to model, major investment are needed (i) in systems that can provide necessary drainage for agronomic production while detaining peak flows and promoting P retention and (ii) in models that can adequately describe P loss to drainage waters.

A Saturation Excess Erosion Model

Abstract. Scaling-up sediment transport has been problematic because most sediment loss models (e.g., the Universal Soil Loss Equation) are developed using data from small plots where runoff is generated by infiltration excess. However, in most watersheds, runoff is produced by saturation excess processes. In this article, we improve an earlier saturation excess erosion model that was only tested on a limited basis, in which runoff and erosion originated from periodically saturated and severely degraded areas, and apply it to five watersheds over a wider geographical area. The erosion model is based on a semi-distributed hydrology model that calculates saturation excess runoff, interflow, and baseflow. In the development of the erosion model, a linear relationship between sediment concentration and velocity in surface runoff is assumed. Baseflow and interflow are sediment free. Initially during the rainy season in Ethiopia, when the fields are being plowed, the sediment concentration in the river is limited by the ability of the surface runoff to move sediment. Later in the season, the sediment concentration becomes limited by the availability of sediment. To show the general applicability of the Saturation Excess Erosion Model (SEEModel), the model was tested for watersheds located 10,000 km apart, in the U.S. and in Ethiopia. In the Ethiopian highlands, we simulated the 1.1 km 2 Anjeni watershed, the 4.8 km 2 Andit Tid watershed, the 4.0 km 2 Enkulal watershed, and the 174,000 km 2 Blue Nile basin. In the Catskill Mountains in New York State, the sediment concentrations were simulated in the 493 km 2 upper Esopus Creek watershed. Discharge and sediment concentration averaged over 1 to 10 days were well simulated over the range of scales with comparable parameter sets. The Nash-Sutcliffe efficiency (NSE) values for the validation runs for the stream discharge were between 0.77 and 0.92. Sediment concentrations had NSE values ranging from 0.56 to 0.86 using only four calibrated sediment parameters together with the subsurface and surface runoff discharges calculated by the hydrology model. The model results suggest that correctly predicting both surface runoff and subsurface flow is an important step in simulating sediment concentrations.

Evaluating the bio-hydrological impact of a cloud forest in Central America using a semi-distributed water balance model

Abstract Water scarcity poses a major threat to food security and human health in Central America and is increasingly recognized as a pressing regional issues caused primarily by deforestation and population pressure. Tools that can reliably simulate the major components of the water balance with the limited data available and needed to drive management decision and protect water supplies in this region. Four adjacent forested headwater catchments in La Tigra National Park, Honduras, ranging in size from 70 to 635 ha were instrumented and discharge measured over a one year period. A semi-distributed water balance model was developed to characterize the bio-hydrology of the four catchments, one of which is primarily cloud forest cover. The water balance model simulated daily stream discharges well, with Nash Sutcliffe model efficiency (E) values ranging from 0.67 to 0.90. Analysis of calibrated model parameters showed that despite all watersheds having similar geologic substrata, the bio-hydrological response the cloud forest indicated less plantavailable water in the root zone and greater groundwater recharge than the non cloud forest cover catchments. This resulted in watershed discharge on a per area basis four times greater from the cloud forest than the other watersheds despite only relatively minor differences in annual rainfall. These results highlight the importance of biological factors (cloud forests in this case) for sustained provision of clean, potable water, and the need to protect the cloud forest areas from destruction, particularly in the populated areas of Central America.

Enhanced Nitrate and Phosphate Removal in a Denitrifying Bioreactor with Biochar

Denitrifying bioreactors (DNBRs) are an emerging technology used to remove nitrate-nitrogen (NO) from enriched waters by supporting denitrifying microorganisms with organic carbon in an anaerobic environment. Field-scale investigations have established successful removal of NO from agricultural drainage, but the potential for DNBRs to remediate excess phosphorus (P) exported from agricultural systems has not been addressed. We hypothesized that biochar addition to traditional woodchip DNBRs would enhance NO and P removal and reduce nitrous oxide (NO) emissions based on previous research demonstrating reduced leaching of NO and P and lower greenhouse gas production associated with biochar amendment of agricultural soils. Nine laboratory-scale DNBRs, a woodchip control, and eight different woodchip-biochar treatments were used to test the effect of biochar on nutrient removal. The biochar treatments constituted a full factorial design of three factors (biochar source material [feedstock], particle size, and application rate), each with two levels. Statistical analysis by repeated measures ANOVA showed a significant effect of biochar, time, and their interaction on NO and dissolved P removal. Average P removal of 65% was observed in the biochar treatments by 18 h, after which the concentrations remained stable, compared with an 8% increase in the control after 72 h. Biochar addition resulted in average NO removal of 86% after 18 h and 97% after 72 h, compared with only 13% at 18 h and 75% at 72 h in the control. Biochar addition also resulted in significantly lower NO production. These results suggest that biochar can reduce the design residence time by enhancing nutrient removal rates.

Agricultural BMP Effectiveness and Dominant Hydrological Flow Paths: Concepts and a Review

We present a conceptual framework that relates agricultural best management practice (BMP) effectiveness with dominant hydrological flow paths to improve nonpoint source (NPS) pollution management. We use the framework to analyze plot, field and watershed scale published studies on BMP effectiveness to develop transferable recommendations for BMP selection and placement at the watershed scale. The framework is based on the location of the restrictive layer in the soil profile and distinguishes three hydrologic land types. Hydrologic land type A has the restrictive layer at the surface and BMPs that increase infiltration are effective. In land type B1, the surface soil has an infiltration rate greater than the prevailing precipitation intensity, but there is a shallow restrictive layer causing lateral flow and saturation excess overland flow. Few structural practices are effective for these land types, but pollutant source management plans can significantly reduce pollutant loading. Hydrologic land type B2 has deep, well-draining soils without restrictive layers that transport pollutants to groundwater via percolation. Practices that increased pollutant residence time in the mixing layer or increased plant water uptake were found as the most effective BMPs in B2 land types. Matching BMPs to the appropriate land type allows for better targeting of hydrologically sensitive areas within a watershed, and potentially more significant reductions of NPS pollutant loading.

Economic analysis of best management practices to reduce watershed phosphorus losses.

In phosphorus-limited freshwater systems, small increases in phosphorus (P) concentrations can lead to eutrophication. To reduce P inputs to these systems, various environmental and agricultural agencies provide producers with incentives to implement best management practices (BMPs). In this study, we examine both the water quality and economic consequences of systematically protecting saturated, runoff-generating areas from active agriculture with selected BMPs. We also examine the joint water quality/economic impacts of these BMPs-specifically BMPs focusing on barnyards and buffer areas. Using the Variable Source Loading Function model (a modified Generalized Watershed Loading Function model) and net present value analysis (NPV), the results indicate that converting runoff-prone agricultural land to buffers and installing barnyard BMPs are both highly effective in decreasing dissolved P loss from a single-farm watershed, but are also costly for the producer. On average, including barnyard BMPs decreases the nutrient loading by about 5.5% compared with only implementing buffers. The annualized NPV for installing both buffers on only the wettest areas of the landscape and implementing barnyard BMPs becomes positive only if the BMPs lifetime exceeds 15 yr. The spatial location of the BMPs in relation to runoff producing areas, the time frame over which the BMPs are implemented, and the marginal costs of increasing buffer size were found to be the most critical considerations for water quality and profitability. The framework presented here incorporates estimations of nutrient loading reductions in the economic analysis, and is applicable to farms facing BMP adoption decisions.

Effect of Biochar on Nitrate Removal in a Pilot-Scale Denitrifying Bioreactor

Denitrifying bioreactors (DNBRs) harness the natural capacity of microorganisms to convert bioavailable nitrogen (N) into inert nitrogen gas (N) by providing a suitable anaerobic habitat and an organic carbon energy source. Woodchip systems are reported to remove 2 to 22 g N m d, but the potential to enhance denitrification with alternative substrates holds promise. The objective of this study was to determine the effect of adding biochar, an organic carbon pyrolysis product, to an in-field, pilot-scale woodchip DNBR. Two 25-m DNBRs, one with woodchips and the other with woodchips and a 10% by volume addition of biochar, were installed on the Delmarva Peninsula, Virginia. Performance was assessed using flood-and-drain batch experiments. An initial release of N was observed during the establishment of both DNBRs, reflecting a start-up phenomenon observed in previous studies. Nitrate (NO-N) removal rates observed during nine batch experiments 4 to 22 mo after installation were 0.25 to 6.06 g N m d. The presence of biochar, temperature, and influent NO-N concentration were found to have significant effects on NO-N removal rates using a linear mixed effects model. The model predicts that biochar increases the rate of N removal when influent concentrations are above approximately 5 to 10 mg L NO-N but that woodchip DNBRs outperform biochar-amended DNBRs when influent concentrations are lower, possibly reflecting the release of N temporarily stored in the biochar matrix. These results indicate that in high N-yielding systems the addition of biochar to standard woodchip DNBRs has the potential to significantly increase N removal.

Assessing BMP Effectiveness and Guiding BMP Planning Using Process-Based Modeling†

There is an increasing need for improved process-based planning tools to assist watershed managers in the selection and placement of effective best management practices (BMPs). In this article, we present an approach, based on the Water Erosion Prediction Project model and a pesticide transport model, to identify dominant hydrologic flow paths and critical source areas for a variety of pollutant types. We use this approach to compare the relative impacts of BMPs on hydrology, erosion, sediment, and pollutant delivery within different landscapes. Specifically, we focus on using this approach to understand what factors promoted and/or hindered BMP effectiveness at three Conservation Effects Assessment Project watersheds: Paradise Creek Watershed in Idaho, Walnut Creek Watershed in Iowa, and Goodwater Creek Experimental Watershed in Missouri. These watersheds were first broken down into unique land types based on soil and topographic characteristics. We used the model to assess BMP effectiveness in each of these land types. This simple process-based modeling approach provided valuable insights that are not generally available to planners when selecting and locating BMPs and helped explain fundamental reasons why long-term improvement in water quality of these three watersheds has yet to be completely realized.

Nutrient biofilters in the Virginia Coastal Plain: Nitrogen removal, cost, and potential adoption pathways

Excess nonpoint source nutrient loss presents one of the most vexing water management challenges for water quality managers. Agriculture is the single largest contributor of nutrients to the Chesapeake Bay, and achieving nutrient reduction targets for agriculture will be costly. Biofilters offer new opportunities to reduce nutrient loads from artificially drained agricultural land. Nutrient biofilters consist of organic carbon (C) medium, typically woodchips, that when saturated with nitrogen (N)-enriched waters supports the activity of naturally occurring soil microorganisms that convert bioavailable N into N gases via denitrification. This study estimates the cost and N removal effectiveness for a biochar-amended woodchip biofilter draining a 10 ha (25 ac) field planted in a corn (Zea mays L.)–soy (Glycine max [L.] Merr.) rotation in eastern Virginia as well as for alternative design scenarios for biofilters ranging 25 to 150 m3 (883 to 5,297 ft3) with either woodchips alone or biochar-amended woodchip C substrates. Nitrogen removal effectiveness is estimated using modeled site-specific influent loads and N removal effectiveness estimates derived from experimental trials in a pilot scale system on the Delmarva Peninsula. This analysis estimates N removal costs as a function of biofilter size, which directly relates to residence time, per unit of N removed. Modeled N removal estimates over a five-year period (2009 to 2013) for five bed volumes range from 88 to 391 kg (194 to 862 lb) for the woodchip biofilters (21% to 95% removal) and 132 to 412 kg (291 to 908 lb) for the biochar-amended woodchip biofilters (32% to 100% removal) of the 412 kg total N load exported to the biofilters during the five-year period. The N removal costs range from US