Conceptual Framework of Connectivity for a National Agroecosystem Model Based on Transport Processes and Management Practices

There is a critical need for a national agroecosystem model for conservation policy and environmental planning, driven by issues including harmful algal blooms, water scarcity, flooding, and other weather‐related extremes. In this study, we illustrate the feasibility of a national agroecosystem model that will downscale processes to individual fields and first‐order channels. We propose to conceptually divide the conterminous United States (U.S.) into process domains as a framework for simulating processes and management at relevant scales. Specifically, we are proposing five domains: field (1–50 ha), transition (0.2–2.0 km²), headwater (1–15 km²), tributaries (15–150 km²), and main river (>150 km²). The proposed conceptual framework hydrologically connects fields across the U.S. using the National Hydrography Dataset (NHDPlus version 2). Parameterizing the Soil and Water Assessment Tool for the national agroecosystem model resulted in 4,880,000 agricultural fields, 2,250,000 non‐agricultural hydrologic response units, and 7,130,000 transition, 1,610,000 headwater, 591,000 tributary, and 432,400 main channels. Application of this framework was shown for Hydrologic Unit Code 07120002 in central Illinois and Indiana to demonstrate the feasibility of the approach using data that is readily available across the U.S. The new connectivity framework has the potential to dramatically improve national conservation and environmental assessments performed by U.S. Department of Agriculture and U.S. Environmental Protection Agency.     

Addressing data challenges in riverine nutrient load modeling of an intensively managed agro-industrial watershed

Data limitations often challenge the reliability of water quality models, especially in intensively managed watersheds. While numerous studies report successful hydrological model setup and calibration, few have addressed in detail the data challenges for multisite and multivariable model calibration to an intensively managed watershed. In this study, we address some of these challenges based on our reflective experience calibrating the Soil and Water Assessment Tool (SWAT) to the Upper Sangamon River Watershed in central Illinois based on daily flow, annual crop yield, and monthly sediment, nitrate, and total phosphorus loads. We highlight some challenges in SWAT calibration processes due to data errors and inconsistencies, and insufficient precipitation and water quality observations. Following, we demonstrate the merits of additional weather and water quality observations that could help reduce input uncertainties, and we provide suggestions for selecting appropriate observations for the model calibration. After dealing with the data issues, we show that the SWAT model could be calibrated with acceptable results for the case study watershed.     

MONTHLY RUNOFF DISTRIBUTION RELATED TO BASIN GEOGRAPHY1

ABSTRACT: Mean monthly runoff from ungaged drainage basins that have significant snowpacks each year can be estimated quite well by assuming that the time duration between snowfall and snowmelt is the predominant factor in temporal runoff distribution. That time span is related to basin temperatures which are, in turn, functions of basin elevation and latitude. Regional hydrologic analyses of gaged basin data create regression equations for estimating runoff distribution by month. These equations then can be applied to ungaged basins. Basin latitude and mean elevation are two independent variables that can be used in estimating monthly runoff distributions.     

Modeling Changes to Streamflow,Sediment, and Nutrient Loading from Land Use Changes Due to Potential Natural Gas Development

Natural gas development using hydraulic fracturing has many potential environmental impacts, but among the most certain is the land disturbance required to build the well pads and other infrastructure required to drill and extract the gas. We used the Soil and Water Assessment Tool (SWAT) model to investigate how natural gas development could impact streamflow and sediment, total nitrogen (TN), and total phosphorous (TP) loadings in the upper Delaware River Basin (DRB), a relatively undeveloped watershed of 7,950 km² that lies above the Marcellus Shale formation. If gas development was permitted, our projections show the DRB could experience development of over 600 well pads to extract natural gas at build out, which, with supporting infrastructure (roads, gathering pipelines), could convert over 5,000 ha from existing land uses in the study area. In subbasins with development activity we found sediment, TN, and TP yields could increase by an average of 15, 0.08, and 0.03 kg/ha/yr, respectively (an increase of 2, 3, and 15%, respectively) for each one percent of subbasin land area converted into natural gas infrastructure. At the study area outlet on the Delaware River at Port Jervis, New York, we found increases in the annual average streamflow and sediment, nitrogen, and phosphorus loads of up to 0.01, 0.2, 0.2, and 1%, respectively, for a rapid development year, and 0.08, 1.3, 2.0, and 11%, respectively, for the full development scenario. Editor's note : This paper is part of the featured series on SWAT Applications for Emerging Hydrologic and Water Quality Challenges. See the February 2017 issue for the introduction and background to the series.     

Ohio's Balanced Growth Program: a case study of collaboration for planning and policy design

This paper describes the collaborative planning process for a new landscape planning programme in Ohio that seeks to influence land urbanisation patterns through joint local land use decision making on a watershed basis. The programme was developed through a collaborative process by a state agency-appointed task force that included agency staff and a wide range of stakeholders. The paper describes the process in terms of the collaborative mechanisms, the participants, the programmatic outputs, and the social and organisational outcomes that set the foundation for enhanced watershed quality through better land use decision-making practices. Key collaborations formed during the process were inter-agency collaborations, a non-profit organisation that partnered with the agencies, and that of state agencies with local governments to develop watershed-based land use plans. A most critical outcome was creation of a learning community, through an exploratory research process that used multiple methods of data gathering and consensus-building deliberation. The paper is based on a review of published documents and plans, meeting minutes, participant observation of committee and workgroup meetings and interactive research.     

Predicting Debris Yield From Burned Watersheds: Comparison of Statistical and Artificial Neural Network Models1

Abstract: Alluvial fans in southern California are continuously being developed for residential, industrial, commercial, and agricultural purposes. Development and alteration of alluvial fans often require consideration of mud and debris flows from burned mountain watersheds. Accurate prediction of sediment (hyper‐concentrated sediment or debris) yield is essential for the design, operation, and maintenance of debris basins to safeguard properly the general population. This paper presents results based on a statistical model and Artificial Neural Network (ANN) models. The models predict sediment yield caused by storms following wildfire events in burned mountainous watersheds. Both sediment yield prediction models have been developed for use in relatively small watersheds (50‐800 ha) in the greater Los Angeles area. The statistical model was developed using multiple regression analysis on sediment yield data collected from 1938 to 1983. Following the multiple regression analysis, a method for multi‐sequence sediment yield prediction under burned watershed conditions was developed. The statistical model was then calibrated based on 17 years of sediment yield, fire, and precipitation data collected between 1984 and 2000. The present study also evaluated ANN models created to predict the sediment yields. The training of the ANN models utilized single storm event data generated for the 17‐year period between 1984 and 2000 as the training input data. Training patterns and neural network architectures were varied to further study the ANN performance. Results from these models were compared with the available field data obtained from several debris basins within Los Angeles County. Both predictive models were then applied for hind‐casting the sediment prediction of several post 2000 events. Both the statistical and ANN models yield remarkably consistent results when compared with the measured field data. The results show that these models are very useful tools for predicting sediment yield sequences. The results can be used for scheduling cleanout operation of debris basins. It can be of great help in the planning of emergency response for burned areas to minimize the damage to properties and lives.     

Morphology Characteristics of Southern Appalachian Wilderness Streams1

Zink, Jason M., Gregory D. Jennings, and G. Alexander Price, 2012. Morphology Characteristics of Southern Appalachian Wilderness Streams. Journal of the American Water Resources Association (JAWRA) 48(4): 762‐773. DOI: 10.1111/j.1752‐1688.2012.00647.x Abstract: Watersheds without urbanization or impacts from logging are rare in the southern Appalachian Mountains. The Joyce Kilmer/Slickrock Wilderness of North Carolina and Tennessee contains 24 km² of old‐growth forest, with the balance of the wilderness in a mature second‐growth forest. The watersheds of Little Santeetlah and Slickrock Creek are located within the wilderness. Morphological information, including channel dimensions and longitudinal profiles, was gathered from 14 alluvial stream reaches in these watersheds. The study sites had drainage areas from 0.25 to 41.6 km² and stream slopes from 0.014 to 0.104 m/m. Bankfull cross‐section dimensions of the study stream reaches were strongly correlated to drainage area across the observed range of slopes and bed morphology. Cross‐section area and width relationships for the streams in this study did not differ significantly from regional curves for the mountain physiographic region of North Carolina. Observations of these reaches did not suggest a definitive rule regarding the proportion of steps and riffles in streams. Pools occupied greater than 50% of the length in all stream reaches with slopes less than 0.07 m/m. Significant correlation existed between step height ratio and slope, suggesting that step height can be approximated as the product of channel width and slope. Riffle length and riffle slope ratios were also significantly correlated with slope, though pool spacing was not.     

Assessing land-use/water-quality relationships across contrasting geologic areas in New Jersey

In all, 13 stream water-quality parameters, including specific conductance (SC), pH, dissolved oxygen (DO), dissolved organic carbon (DOC), three nutrients, and six major ions were compared between the northern bedrock and southern coastal plain regions of New Jersey, USA and related to watershed-disturbance gradients characterized by the percentage of urban land, impervious surface (IS), agriculture, and altered land (sum of urban land and agriculture) in the watersheds. SC, DO, calcium, magnesium, sodium, and chloride concentrations were greater in the north. DOC was higher and pH was lower in the south. Nutrient, potassium, and sulfate concentrations did not differ between regions. Regional water-quality differences are attributed to geologic setting and land use. Except for DO in southern streams, all water-quality parameters were related to urban land, agriculture, or both. Significant correlations between urban land and IS and water-quality variables were similar in both regions with differences in unitless correlation coefficients ranging from 0.00 to 0.06. Compared to urban land and agriculture, relationships between most water-quality variables and altered land were stronger in the south. The extent of urban and agricultural lands in the watersheds did not differ by region. Altered land was correlated with urban land in both regions and with agriculture only in the south. Although focused on New Jersey, this study has broader implications for watershed planning.     

Using Multiple Watershed Models to Predict Water,Nitrogen, and Phosphorus Discharges to the Patuxent Estuary1

Boomer, Kathleen M.B., Donald E. Weller, Thomas E. Jordan, Lewis Linker, Zhi‐Jun Liu, James Reilly, Gary Shenk, and Alexey A. Voinov, 2012. Using Multiple Watershed Models to Predict Water, Nitrogen, and Phosphorus Discharges to the Patuxent Estuary. Journal of the American Water Resources Association (JAWRA) 1‐25. DOI: 10.1111/j.1752‐1688.2012.00689.x Abstract: We analyzed an ensemble of watershed models that predict flow, nitrogen, and phosphorus discharges. The models differed in scope and complexity and used different input data, but all had been applied to evaluate human impacts on discharges to the Patuxent River or to the Chesapeake Bay. We compared predictions to observations of average annual, annual time series, and monthly discharge leaving three basins. No model consistently matched observed discharges better than the others, and predictions differed as much as 150% for every basin. Models that agreed best with the observations in one basin often were among the worst models for another material or basin. Combining model predictions into a model average improved overall reliability in matching observations, and the range of predictions helped describe uncertainty. The model average was not the closest to the observed discharge for every material, basin, and time frame, but the model average had the highest Nash–Sutcliffe performance across all combinations. Consistently poor performance in predicting phosphorus loads suggests that none of the models capture major controls. Differences among model predictions came from differences in model structures, input data, and the time period considered, and also to errors in the observed discharge. Ensemble watershed modeling helped identify research needs and quantify the uncertainties that should be considered when using the models in management decisions.     

The Impact of Asynchronicity on Event‐Flow Estimation in Basin‐Scale Hydrologic Model Calibration1

Abstract: The calibration of basin‐scale hydrologic models consists of adjusting parameters such that simulated values closely match observed values. However, due to inevitable inaccuracies in models and model inputs, simulated response hydrographs for multiyear calibrations will not be perfectly synchronized with observed response hydrographs at the daily time step. An analytically derived formula suggests that when timing errors are significant, traditional calibration approaches may generally underestimate the total event‐flow volume. An event‐adaptive time series is developed and incorporated into the Nash‐Sutcliffe Efficiency objective function to diagnose the potential impact of event‐flow synchronization errors. Test sites are the 50 km² Subwatershed I of the Little River Experimental Watershed (LREWswI) in southeastern Georgia, and the 610 km² Little Washita River Experimental Watershed (LWREW) in southwestern Oklahoma, with the Soil and Water Assessment Tool used as the hydrologic model. Results suggest that simulated surface runoff generation is 55% less for LREWswI when the daily time series is used compared with when the event‐adaptive technique is used. Event‐flow generation may also be underestimated for LWREW, but to a lesser extent than it may be for LREWswI, due to a larger portion of the event flow being lateral flow.