SWAT ungauged: Water quality modeling in the Upper Mississippi River Basin.

Improving model performance in ungauged basins has been a chronic challenge in watershed model application to understand and assess water quality impacts of agricultural conservation practices, land use change, and climate adaptation measures in large river basins. Here, we evaluate a modified version of SWAT2012 (referred to as SWAT-EC hereafter), which integrates an energy balanced soil temperature module (STM) and the CENTRUY-based soil organic matter algorithm, for simulating water quality parameters in the Upper Mississippi River Basin (UMRB), and compare it against the original SWAT2012. Model evaluation was performed for simulating streamflow, sediment, and nitrate-N (NO3-N) and total nitrogen (TN) loadings at three stations near the outlets of UMRB. The model comparison was conducted without parameter calibration in order to assess their performance under ungauged conditions. The results indicate that SWAT-EC outperformed SWAT2012 for stream flow and NO3-N and TN loading simulation on both monthly and annual scales. For sediment, SWAT-EC performed better than SWAT2012 on a monthly time step basis, but no noticeable improvement was found at the annual scale. In addition, the performance of the uncalibrated SWAT-EC was comparable to other calibrated SWAT models reported in previous publications with respect to sediment and NO3-N loadings. These findings highlight the importance of advancing process representation in physically-based models to improve model credibility, particularly in ungauged basins.

Cost-effective targeting of conservation investments to reduce the northern Gulf of Mexico hypoxic zone.

A seasonally occurring summer hypoxic (low oxygen) zone in the northern Gulf of Mexico is the second largest in the world. Reductions in nutrients from agricultural cropland in its watershed are needed to reduce the hypoxic zone size to the national policy goal of 5,000 km(2) (as a 5-y running average) set by the national Gulf of Mexico Task Force's Action Plan. We develop an integrated assessment model linking the water quality effects of cropland conservation investment decisions on the more than 550 agricultural subwatersheds that deliver nutrients into the Gulf with a hypoxic zone model. We use this integrated assessment model to identify the most cost-effective subwatersheds to target for cropland conservation investments. We consider targeting of the location (which subwatersheds to treat) and the extent of conservation investment to undertake (how much cropland within a subwatershed to treat). We use process models to simulate the dynamics of the effects of cropland conservation investments on nutrient delivery to the Gulf and use an evolutionary algorithm to solve the optimization problem. Model results suggest that by targeting cropland conservation investments to the most cost-effective location and extent of coverage, the Action Plan goal of 5,000 km(2) can be achieved at a cost of $2.7 billion annually. A large set of cost-hypoxia tradeoffs is developed, ranging from the baseline to the nontargeted adoption of the most aggressive cropland conservation investments in all subwatersheds (estimated to reduce the hypoxic zone to less than 3,000 km(2) at a cost of $5.6 billion annually).

Regional Effects of Agricultural Conservation Practices on Nutrient Transport in the Upper Mississippi River Basin.

Despite progress in the implementation of conservation practices, related improvements in water quality have been challenging to measure in larger river systems. In this paper we quantify these downstream effects by applying the empirical U.S. Geological Survey water-quality model SPARROW to investigate whether spatial differences in conservation intensity were statistically correlated with variations in nutrient loads. In contrast to other forms of water quality data analysis, the application of SPARROW controls for confounding factors such as hydrologic variability, multiple sources and environmental processes. A measure of conservation intensity was derived from the USDA-CEAP regional assessment of the Upper Mississippi River and used as an explanatory variable in a model of the Upper Midwest. The spatial pattern of conservation intensity was negatively correlated (p = 0.003) with the total nitrogen loads in streams in the basin. Total phosphorus loads were weakly negatively correlated with conservation (p = 0.25). Regional nitrogen reductions were estimated to range from 5 to 34% and phosphorus reductions from 1 to 10% in major river basins of the Upper Mississippi region. The statistical associations between conservation and nutrient loads are consistent with hydrological and biogeochemical processes such as denitrification. The results provide empirical evidence at the regional scale that conservation practices have had a larger statistically detectable effect on nitrogen than on phosphorus loadings in streams and rivers of the Upper Mississippi Basin.

The role of interior watershed processes in improving parameter estimation and performance of watershed models.

Watershed models typically are evaluated solely through comparison of in-stream water and nutrient fluxes with measured data using established performance criteria, whereas processes and responses within the interior of the watershed that govern these global fluxes often are neglected. Due to the large number of parameters at the disposal of these models, circumstances may arise in which excellent global results are achieved using inaccurate magnitudes of these "intra-watershed" responses. When used for scenario analysis, a given model hence may inaccurately predict the global, in-stream effect of implementing land-use practices at the interior of the watershed. In this study, data regarding internal watershed behavior are used to constrain parameter estimation to maintain realistic intra-watershed responses while also matching available in-stream monitoring data. The methodology is demonstrated for the Eagle Creek Watershed in central Indiana. Streamflow and nitrate (NO) loading are used as global in-stream comparisons, with two process responses, the annual mass of denitrification and the ratio of NO losses from subsurface and surface flow, used to constrain parameter estimation. Results show that imposing these constraints not only yields realistic internal watershed behavior but also provides good in-stream comparisons. Results further demonstrate that in the absence of incorporating intra-watershed constraints, evaluation of nutrient abatement strategies could be misleading, even though typical performance criteria are satisfied. Incorporating intra-watershed responses yields a watershed model that more accurately represents the observed behavior of the system and hence a tool that can be used with confidence in scenario evaluation.

Simulating Landscape Sediment Transport Capacity by Using a Modified SWAT Model.

Sediment delivery from hillslopes to rivers is spatially variable and may lead to long-term delays between initial erosion and related sediment yield at the watershed outlet. Consideration of spatial variability is important for developing sound strategies for water quality improvement and soil protection at the watershed scale. Hence, the Soil and Water Assessment Tool (SWAT) was modified and tested in this study to simulate the landscape transport capacity of sediment. The study area was the steeply sloped Arroio Lino watershed in southern Brazil. Observed sediment yield data at the watershed outlet were used to calibrate and validate a modified SWAT model. For the calibration period, the modified model performed better than the unaltered SWAT2009 version; the models achieved Nash-Sutcliffe efficiency (NSE) values of 0.7 and -0.1, respectively. Nash-Sutcliffe efficiencies were less for the validation period, but the modified model's NSE was higher than the unaltered model (-1.4 and -12.1, respectively). Despite the relatively low NSE values, the results of this first test are promising because the model modifications lowered the percent bias in sediment yield from 73 to 18%. Simulation results for the modified model indicated that approximately 60% of the mobilized soil is deposited along the landscape before it reaches the river channels. This research demonstrates the modified model's ability to simulate sediment yield in watersheds with steep slopes. The results suggest that integration of the sediment deposition routine in SWAT increases accuracy in steeper areas while significantly improving its ability to predict the spatial distribution of sediment deposition areas. Further work is needed regarding (i) improved strategies for spatially distributed sediment transport measurements (for improving process knowledge and model evaluation) and (ii) extensive model tests in other well instrumented experimental watersheds with differing topographic configurations and land uses.

The LTAR Cropland Common Experiment at the Texas Gulf.

Texas Gulf is one of the 18 regional sites that is part of the USDA-ARS Long-Term Agroecosystem Research (LTAR) Network and focuses on cropland and integrated grazing land research in Central Texas, addressing challenges posed by soil characteristics, climate variability, and urbanization. This paper provides brief site descriptions of the two Cropland Common Experiments being conducted in the Texas Gulf LTAR region, emphasizing conservation tillage practices and precision agriculture techniques. The plot-scale study is located in Temple, TX, at the USDA-ARS Grassland, Soil and Water Research Laboratory and examines conventional tillage, strip tillage, and no tillage practices. The field-scale study, located in Riesel, TX, at the USDA-ARS Riesel Watersheds, assesses the impact of no tillage, cover crops, fertility management, adaptive management, and precision conservation on crop yield, profitability, and environmental footprint. Key measurements include soil and plant analyses, greenhouse gas fluxes, runoff water quantity and quality, and field operations recorded with precision agriculture equipment. Despite challenges posed by urban encroachment, future research aims to incorporate new technologies, such as unmanned ground vehicles, to enhance sustainability and productivity of the agricultural landscape. These experiments provide valuable insights for stakeholders, contributing to the development of sustainable agricultural practices tailored to the unique challenges within the Texas Gulf LTAR region.

Evaluation of the hooghoudt and kirkham tile drain equations in the soil and water assessment tool to simulate tile flow and nitrate-nitrogen.

Subsurface tile drains in agricultural systems of the midwestern United States are a major contributor of nitrate-N (NO-N) loadings to hypoxic conditions in the Gulf of Mexico. Hydrologic and water quality models, such as the Soil and Water Assessment Tool, are widely used to simulate tile drainage systems. The Hooghoudt and Kirkham tile drain equations in the Soil and Water Assessment Tool have not been rigorously tested for predicting tile flow and the corresponding NO-N losses. In this study, long-term (1983-1996) monitoring plot data from southern Minnesota were used to evaluate the SWAT version 2009 revision 531 (hereafter referred to as SWAT) model for accurately estimating subsurface tile drain flows and associated NO-N losses. A retention parameter adjustment factor was incorporated to account for the effects of tile drainage and slope changes on the computation of surface runoff using the curve number method (hereafter referred to as Revised SWAT). The SWAT and Revised SWAT models were calibrated and validated for tile flow and associated NO-N losses. Results indicated that, on average, Revised SWAT predicted monthly tile flow and associated NO-N losses better than SWAT by 48 and 28%, respectively. For the calibration period, the Revised SWAT model simulated tile flow and NO-N losses within 4 and 1% of the observed data, respectively. For the validation period, it simulated tile flow and NO-N losses within 8 and 2%, respectively, of the observed values. Therefore, the Revised SWAT model is expected to provide more accurate simulation of the effectiveness of tile drainage and NO-N management practices.

Sediment measurement and transport modeling: impact of riparian and filter strip buffers.

Well-calibrated models are cost-effective tools to quantify environmental benefits of conservation practices, but lack of data for parameterization and evaluation remains a weakness to modeling. Research was conducted in southwestern Oklahoma within the Cobb Creek subwatershed (CCSW) to develop cost-effective methods to collect stream channel parameterization and evaluation data for modeling in watersheds with sparse data. Specifically, (i) simple stream channel observations obtained by rapid geomorphic assessment (RGA) were used to parameterize the Soil and Water Assessment Tool (SWAT) model stream channel variables before calibrating SWAT for streamflow and sediment, and (ii) average annual reservoir sedimentation rate, measured at the Crowder Lake using the acoustic profiling system (APS), was used to cross-check Crowder Lake sediment accumulation rate simulated by SWAT. Additionally, the calibrated and cross-checked SWAT model was used to simulate impacts of riparian forest buffer (RF) and bermudagrass [ (L.) Pers.] filter strip buffer (BFS) on sediment yield and concentration in the CCSW. The measured average annual sedimentation rate was between 1.7 and 3.5 t ha yr compared with simulated sediment rate of 2.4 t ha yr Application of BFS across cropped fields resulted in a 72% reduction of sediment delivery to the stream, while the RF and the combined RF and BFS reduced the suspended sediment concentration at the CCSW outlet by 68 and 73%, respectively. Effective riparian practices have potential to increase reservoir life. These results indicate promise for using the RGA and APS methods to obtain data to improve water quality simulations in ungauged watersheds.

Is the correlation between hydro-environmental variables consistent with their own time variability degrees in a large-scale loessial watershed?

Temporal scale is an important keyword in environmental hydrology but little information is available in the relationship between correlation and time variability degree of hydro-environmental variables at a watershed scale, which makes it difficult to design effective real-time management strategies. Here we take the Yanhe River Watershed as a study case to simulate and inventory the fractal characteristics of correlation and time variability degree of runoff, rainfall, and NH4+-N at different time scales, focusing on the long-term series of 1984-2012. (i) The coupled modeling framework based on SWAT (Soil and Water Assessment Tool), statistics and fractal theory is a time series analysis method that is particularly suitable for the evaluation of long-range correlation of non-linear time series. The Nash-Sutcliffe Efficiency coefficient (NSE), R2 and PBIAS during the calibration and verification period proved the reliability and acceptability of the established SWAT model in modeling multi-time scale runoff and NH4+-N load in the upstream catchment of Ganguyi hydrological station. (ii) Runoffs at all time scales showed positive correlations with rainfall although the significant level had a certain time scale differences. More interestingly, the correlation between NH4+-N loss and runoff at different time scales was significantly higher than that of rainfall. (iii) Each hydro-environmental variable has different fractal and time variation characteristics at different time scales, and the correlation levels between different hydrological variables are not completely consistent with their own time variability degrees at different time scales. These findings point to a fundamental challenge in managing regions with leading infiltration-excess runoff and uneven nutrient loading because the meteorological and hydrological variables in these regions exhibit the strongest temporal variability, which will affect the effective allocation and implementation in management practices.

Projecting the effects of agricultural conservation practices on stream fish communities in a changing climate.

How anticipated climate change might affect long-term outcomes of present-day agricultural conservation practices remains a key uncertainty that could benefit water quality and biodiversity conservation planning. To explore this issue, we forecasted how the stream fish communities in the Western Lake Erie Basin (WLEB) would respond to increasing amounts of agricultural conservation practice (ACP) implementation under two IPCC future greenhouse gas emission scenarios (RCP4.5: moderate reductions; RCP8.5: business-as-usual conditions) during 2020-2065. We used output from 19 General Circulation Models to drive linked agricultural land use (APEX), watershed hydrology (SWAT), and stream fish distribution (boosted regression tree) models, subsequently analyzing how projected changes in habitat would influence fish community composition and functional trait diversity. Our models predicted both positive and negative effects of climate change and ACP implementation on WLEB stream fishes. For most species, climate and ACPs influenced species in the same direction, with climate effects outweighing those of ACP implementation. Functional trait analysis helped clarify the varied responses among species, indicating that more extreme climate change would reduce available habitat for large-bodied, cool-water species with equilibrium life-histories, many of which also are of importance to recreational fishing (e.g., northern pike, smallmouth bass). By contrast, available habitat for warm-water, benthic species with more periodic or opportunistic life-histories (e.g., northern hogsucker, greater redhorse, greenside darter) was predicted to increase. Further, ACP implementation was projected to hasten these shifts, suggesting that efforts to improve water quality could come with costs to other ecosystem services (e.g., recreational fishing opportunities). Collectively, our findings demonstrate the need to consider biological outcomes when developing strategies to mitigate water quality impairment and highlight the value of physical-biological modeling approaches to agricultural and biological conservation planning in a changing climate.

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.

Large quantities of biofuel production are expected from bioenergy crops at a national scale to meet US biofuel goals. It is important to study biomass production of bioenergy crops and the impacts of these crops on water quantity and quality to identify environment-friendly and productive biofeedstock systems. SWAT2012 with a new tile drainage routine and improved perennial grass and tree growth simulation was used to model long-term annual biomass yields, streamflow, tile flow, sediment load, and nutrient losses under various bioenergy scenarios in an extensively agricultural watershed in the Midwestern US. Simulated results from bioenergy crop scenarios were compared with those from the baseline. The results showed that simulated annual crop yields were similar to observed county level values for corn and soybeans, and were reasonable for Miscanthus, switchgrass and hybrid poplar. Removal of 38% of corn stover (3.74Mg/ha/yr) with Miscanthus production on highly erodible areas and marginal land (17.49Mg/ha/yr) provided the highest biofeedstock production (279,000Mg/yr). Streamflow, tile flow, erosion and nutrient losses were reduced under bioenergy crop scenarios of bioenergy crops on highly erodible areas and marginal land. Corn stover removal did not result in significant water quality changes. The increase in sediment and nutrient losses under corn stover removal could be offset with the combination of other bioenergy crops. Potential areas for bioenergy crop production when meeting the criteria above were small (10.88km2), thus the ability to produce biomass and improve water quality was not substantial. The study showed that corn stover removal with bioenergy crops both on highly erodible areas and marginal land could provide more biofuel production relative to the baseline, and was beneficial to water quality at the watershed scale, providing guidance for further research on evaluation of bioenergy crop scenarios in a typical extensively tile-drained watershed in the Midwestern U.S.

Western Lake Erie Basin: Soft-data-constrained, NHDPlus resolution watershed modeling and exploration of applicable conservation scenarios.

Complex watershed simulation models are powerful tools that can help scientists and policy-makers address challenging topics, such as land use management and water security. In the Western Lake Erie Basin (WLEB), complex hydrological models have been applied at various scales to help describe relationships between land use and water, nutrient, and sediment dynamics. This manuscript evaluated the capacity of the current Soil and Water Assessment Tool (SWAT) to predict hydrological and water quality processes within WLEB at the finest resolution watershed boundary unit (NHDPlus) along with the current conditions and conservation scenarios. The process based SWAT model was capable of the fine-scale computation and complex routing used in this project, as indicated by measured data at five gaging stations. The level of detail required for fine-scale spatial simulation made the use of both hard and soft data necessary in model calibration, alongside other model adaptations. Limitations to the model's predictive capacity were due to a paucity of data in the region at the NHDPlus scale rather than due to SWAT functionality. Results of treatment scenarios demonstrate variable effects of structural practices and nutrient management on sediment and nutrient loss dynamics. Targeting treatment to acres with critical outstanding conservation needs provides the largest return on investment in terms of nutrient loss reduction per dollar spent, relative to treating acres with lower inherent nutrient loss vulnerabilities. Importantly, this research raises considerations about use of models to guide land management decisions at very fine spatial scales. Decision makers using these results should be aware of data limitations that hinder fine-scale model interpretation.

Cost of areal reduction of gulf hypoxia through agricultural practice.

A major share of the area of hypoxic growth in the Northern Gulf of Mexico has been attributed to nutrient run-off from agricultural fields, but no estimate is available for the cost of reducing Gulf hypoxic area using agricultural conservation practices. We apply the Soil and Water Assessment Tool using observed daily weather to simulate the reduction in nitrogen loading in the Upper Mississippi River Basin (UMRB) that would result from enrolling all row crop acreage in the Conservation Reserve Program (CRP). Nitrogen loadings at the outlet of the UMRB are used to predict Gulf hypoxic area, and net cash farm rent is used as the price for participation in the CRP. Over the course of the 42 year simulation, direct CRP costs total more than $388 billion, and the Inter-Governmental Task Force goal of hypoxic area less than 5000 square kilometers is met in only two years.

Software for pest-management science: computer models and databases from the United States Department of Agriculture-Agricultural Research Service.

We present an overview of USDA Agricultural Research Service (ARS) computer models and databases related to pest-management science, emphasizing current developments in environmental risk assessment and management simulation models. The ARS has a unique national interdisciplinary team of researchers in surface and sub-surface hydrology, soil and plant science, systems analysis and pesticide science, who have networked to develop empirical and mechanistic computer models describing the behavior of pests, pest responses to controls and the environmental impact of pest-control methods. Historically, much of this work has been in support of production agriculture and in support of the conservation programs of our 'action agency' sister, the Natural Resources Conservation Service (formerly the Soil Conservation Service). Because we are a public agency, our software/database products are generally offered without cost, unless they are developed in cooperation with a private-sector cooperator. Because ARS is a basic and applied research organization, with development of new science as our highest priority, these products tend to be offered on an 'as-is' basis with limited user support except for cooperating R&D relationship with other scientists. However, rapid changes in the technology for information analysis and communication continually challenge our way of doing business.

Metal and nanoparticle occurrence in biosolid-amended soils.

Metals can accumulate in soils amended with biosolids in which metals have been concentrated during wastewater treatment. The goal of this study is to inspect agricultural sites with long-term biosolid application for a suite of regulated and unregulated metals, including some potentially present as commonly used engineered nanomaterials (ENMs). Sampling occurred in fields at a municipal and a privately operated biosolid recycling facilities in Texas. Depth profiles of various metals were developed for control soils without biosolid amendment and soils with different rates of biosolid application (6.6 to 74 dry tons per hectare per year) over 5 to 25 years. Regulated metals of known toxicity, including chromium, copper, cadmium, lead, and zinc, had higher concentrations in the upper layer of biosolid-amended soils (top 0-30 cm or 0-15 cm) than in control soils. The depth profiles of unregulated metals (antimony, hafnium, molybdenum, niobium, gold, silver, tantalum, tin, tungsten, and zirconium) indicate higher concentrations in the 0-30 cm soil increment than in the 70-100 cm soil increment, indicating low vertical mobility after entering the soils. Titanium-containing particles between 50 nm and 250 nm in diameter were identified in soil by transmission electron microscopy (TEM) coupled with energy dispersive x-ray spectroscopy (EDX) analysis. In conjunction with other studies, this research shows the potential for nanomaterials used in society that enter the sewer system to be removed at municipal biological wastewater treatment plants and accumulate in agricultural fields. The metal concentrations observed herein could be used as representative exposure levels for eco-toxicological studies in these soils.

Modifying the Soil and Water Assessment Tool to simulate cropland carbon flux: model development and initial evaluation.

Climate change is one of the most compelling modern issues and has important implications for almost every aspect of natural and human systems. The Soil and Water Assessment Tool (SWAT) model has been applied worldwide to support sustainable land and water management in a changing climate. However, the inadequacies of the existing carbon algorithm in SWAT limit its application in assessing impacts of human activities on CO2 emission, one important source of greenhouse gasses (GHGs) that traps heat in the earth system and results in global warming. In this research, we incorporate a revised version of the CENTURY carbon model into SWAT to describe dynamics of soil organic matter (SOM)-residue and simulate land-atmosphere carbon exchange. We test this new SWAT-C model with daily eddy covariance (EC) observations of net ecosystem exchange (NEE) and evapotranspiration (ET) and annual crop yield at six sites across the U.S. Midwest. Results show that SWAT-C simulates well multi-year average NEE and ET across the spatially distributed sites and capture the majority of temporal variation of these two variables at a daily time scale at each site. Our analyses also reveal that performance of SWAT-C is influenced by multiple factors, such as crop management practices (irrigated vs. rainfed), completeness and accuracy of input data, crop species, and initialization of state variables. Overall, the new SWAT-C demonstrates favorable performance for simulating land-atmosphere carbon exchange across agricultural sites with different soils, climate, and management practices. SWAT-C is expected to serve as a useful tool for including carbon flux into consideration in sustainable watershed management under a changing climate. We also note that extensive assessment of SWAT-C with field observations is required for further improving the model and understanding potential uncertainties of applying it across large regions with complex landscapes.

Assessment of MODIS-EVI, MODIS-NDVI and VEGETATION-NDVI composite data using agricultural measurements: an example at corn fields in western Mexico.

Although several types of satellite data provide temporal information of the land use at no cost, digital satellite data applications for agricultural studies are limited compared to applications for forest management. This study assessed the suitability of vegetation indices derived from the TERRA-Moderate Resolution Imaging Spectroradiometer (MODIS) sensor and SPOT-VEGETATION (VGT) sensor for identifying corn growth in western Mexico. Overall, the Normalized Difference Vegetation Index (NDVI) composites from the VGT sensor based on bi-directional compositing method produced vegetation information most closely resembling actual crop conditions. The NDVI composites from the MODIS sensor exhibited saturated signals starting 30 days after planting, but corresponded to green leaf senescence in April. The temporal NDVI composites from the VGT sensor based on the maximum value method had a maximum plateau for 80 days, which masked the important crop transformation from vegetative stage to reproductive stage. The Enhanced Vegetation Index (EVI) composites from the MODIS sensor reached a maximum plateau 40 days earlier than the occurrence of maximum leaf area index (LAI) and maximum intercepted fraction of photosynthetic active radiation (fPAR) derived from in-situ measurements. The results of this study showed that the 250-m resolution MODIS data did not provide more accurate vegetation information for corn growth description than the 500-m and 1000-m resolution MODIS data.