Weighting Nitrogen and Phosphorus Pixel Pollutant Loads to Represent Runoff and Buffering Likelihoods

Watershed models often estimate annual nitrogen (N) or phosphorus (P) pollutant loads in rural areas with export coefficient (EC) (kg/ha/yr) values based on land cover, and in urban areas as the product of spatially uniform event mean concentration (EMC) (mg/L) values and runoff volume. Actual N and P nonpoint source (NPS) pollutant loading has more spatial complexity due to watershed variation in runoff likelihood and buffering likelihood along surface and subsurface pathways, which can be represented in a contributing area dispersal area (CADA) NPS model. This research develops a CADA NPS model to simulate how watershed properties of elevation, land cover, and soils upslope and downslope of each watershed pixel influence nutrient loading. The model uses both surface and subsurface runoff indices (RI), and surface and subsurface buffer indices (BI), to quantify the runoff and buffering likelihood for each watershed pixel, and generate maps of weighted EC and EMC values that identify NPS pollutant loading hotspots. The research illustrates how CADA NPS model maps and pixel loading values are sensitive to the spatial resolution and accuracy of elevation and land cover data, and model predictions can represent the lower and upper bounds of NPS loading. The model provides managers with a tool to rapidly visualize, rank, and investigate likely areas of high nutrient export.     

Assessing Surface Water Quality and Its Relation with Urban Land Cover Changes in the Lake Calumet Area, Greater Chicago

Urban land use and land cover change significantly affect spatial and temporal patterns of runoff, which in turn impacts surface water quality. With the exponential growth in urban areas over the past three decades, changes in land use and land cover to cater for the growth of cities has been a conspicuous spectacle in urban spaces. The main goal of this study was to assess the impacts of land cover change on runoff and surface water quality using a partial area hydrology framework. The study employed ArcHydro GIS extension and a modified version of Long-Term Hydrologic and Nonpoint Source Pollution model (L-THIA-NPS) in estimating runoff and nonpoint source pollutant concentration around Lake Calumet between 1992 and 2001. Data employed include National Land Cover Data set, rainfall data, digital elevation model (DEM), Soil Survey Geographic (SSURGO) data, and The United States Environmental Protection Agency’s STORET (storage and retrieval) water quality data. The model was able to predict surface water quality reasonably well over the study period. Sensitivity analysis facilitated a manual calibration of the model. Model validation was executed by comparing simulated results following calibration and observed water quality data for the study area. The study demonstrates that the level of concentration of nonpoint source pollutants in surface water within an urban watershed heavily depends on the spatiotemporal variations in areas that contribute towards runoff compared to the spatial extent of change in major land use/land cover.     

IDENTIFICATION OF CRITICAL NONPOINT POLLUTION SOURCE AREAS USING GEOGRAPHIC INFORMATION SYSTEMS AND WATER QUALITY MODELING1

n integrated approach coupling water quality computer simulation modeling with a geographic information system (GIS) was used to delineate critical areas of nonpoint source (NPS) pollution at the watershed level. Two simplified pollutant export models were integrated with the Virginia Geographic Information System (VirGIS) to estimate soil erosion, sediment yield, and phosphorus (P) loading from the Nomini Creek watershed located in Westmoreland County, Virginia. On the basis of selected criteria for soil erosion rate, sediment yield, and P loading, model outputs were used to identily watershed areas which exhibit three categories (low, medium, high) of non-point source pollution potentials. The percentage of the watershed area in each category, and the land area with critical pollution problems were also identified. For the 1505-ha Nomini Creek watershed, about 15, 16, and 21 percent of the watershed area were delineated as sources of critical soil erosion, sediment, and phosphorus pollution problems, respectively. In general, the study demonstrated the usefulness of integrating GIS with simulation modeling for nonpoint source pollution control and planning. Such techniques can facilitate making priorities and targeting nonpoint source pollution control programs.     

Stormwater runoff and export changes with development in a traditional and low impact subdivision

Development continues at a rapid pace throughout the country. Runoff from the impervious surfaces in these watersheds continues to be a major cause of degradation to freshwater bodies and estuaries. Low impact development techniques have been recommended to reduce these impacts. In this study, stormwater runoff and pollutant concentrations were measured as development progressed in both a traditional development, and a development that used low impact development techniques. Increases in total impervious area in each watershed were also measured. Regression relationships were developed between total impervious area and stormwater runoff/pollutant export. Significant, logarithmic increases in stormwater runoff and nitrogen and phosphorus export were found as development occurred in the traditional subdivision. The increases in stormwater runoff and pollutant export were more than two orders of magnitude. TN and TP export after development was 10 and 1 kg ha(-1) yr(-1), respectively, which was consistent with export from other urban/developed areas. In contrast, stormwater runoff and pollutant export from the low impact subdivision remained unchanged from pre-development levels. TN and TP export from the low impact subdivision were consistent with export values from forested watersheds. The results of this study indicate that the use of low impact development techniques on a watershed scale can greatly reduce the impacts of development on local waterways.     

Nonpoint source pollution risk assessment in a watershed context

Nonpoint source pollution control requires assessment of the influence of dispersed runoff-contributing areas on downstream water quality. This evaluation must consider two separate phases: site-to-stream loading and downstream fluvial transport. Any model, combination of models, or procedure for making this assessment can be generalized to a simple spatial model or framework, which considers runoff or pollutant loading per unit area and down-stream attenuation, with drainage area as a scaling factor. This spatial model has a probabilistic interpretation and can be used in conjunction with a standard dilution model to give a probabilistic estimate of the impacts at the basin mouth of runoff from a specific upstream contributing area. It is illustrated by applying it to an assessment of the probability that various copper concentrations at the mouth of the urbanized South Platte River basin in Denver, Colorado, USA, will be exceeded as a result of runoff from a subbasin within the city. Determining the probability that a concentration of a pollutant at the basin mouth can be attributed to runoff from a discrete area within the basin is useful for targeting and risk assessment because it enables quantitative risk-based comparisons. The spatial framework is also useful for evaluating management and control options, since actions within the basin can be directly linked to water quality at a downstream point.     

Effects of calibration on L-THIA GIS runoff and pollutant estimation

Urbanization can result in alteration of a watershed's hydrologic response and water quality. To simulate hydrologic and water quality impacts of land use changes, the Long-Term Hydrologic Impact Assessment (L-THIA) system has been used. The L-THIA system estimates pollutant loading based on direct runoff quantity and land use based pollutant coefficients. The accurate estimation of direct runoff is important in assessing water quality impacts of land use changes. An automated program was developed to calibrate the L-THIA model using the millions of curve number (CN) combinations associated with land uses and hydrologic soil groups. L-THIA calibration for the Little Eagle Creek (LEC) watershed near Indianapolis, Indiana was performed using land use data for 1991 and daily rainfall data for six months of 1991 (January 1-June 30) to minimize errors associated with use of different temporal land use data and rainfall data. For the calibration period, the Nash-Sutcliffe coefficient was 0.60 for estimated and observed direct runoff. The calibrated CN values were used for validation of the model for the same year (July 1-December 31), and the Nash-Sutcliffe coefficient was 0.60 for estimated and observed direct runoff. The Nash-Sutcliffe coefficient was 0.52 for January 1, 1991 to December 31, 1991 using uncalibrated CN values. As shown in this study, the use of better input parameters for the L-THIA model can improve accuracy. The effects on direct runoff and pollutant estimation of the calibrated CN values in the L-THIA model were investigated for the LEC. Following calibration, the estimated average annual direct runoff for the LEC watershed increased by 34%, total nitrogen by 24%, total phosphorus by 22%, and total lead by 43%. This study demonstrates that the L-THIA model should be calibrated and validated prior to application in a particular watershed to more accurately assess the effects of land use changes on hydrology and water quality.     

A GIS-based technique for linking landscape characteristics to non-point source nitrogen export potential: implications for contributing areas management

A Nitrate-N Leaching Index (NLI) is calculated and the results indicate that nitrogen loss in the study area occurs through both leaching and surface runoff. A non-linear regression model of trapping efficiency was combined with a first order decay model to examine the impact of soil characteristics, slope, vegetative cover, land use and distance to streams on the spatial pattern of non-point source nitrogen inputs to streams. The model evaluates the statistical significance of each landscape factor and provides an easy interpretation of the landscape delivery ratio of nitrogen based on a pixel-based characterisation of the watershed. The model was validated by comparing the distributions of the observed and estimated monthly nitrogen concentrations. The exploratory GIS-based method presented here can improve the understanding of the impact of landscape characteristics on nitrate-nitrogen contributing areas and therefore assist watershed management efforts.     

EXPORT COEFFICIENT MODELING TO ASSESS PHOSPHORUS LOADING IN AN URBAN WATERSHED1

ABSTRACT: An export coefficient modeling approach was used to assess the influence of land use on phosphorus loading to a Southern Ontario stream. A model was constructed for the 1995–1996 water year and calibrated within ± 3 percent of the observed mean concentration of total phosphorus. It was found that runoff from urban areas contributed most to the loading of phosphorus to the stream. When the model was assessed by running it for the 1977–1978 water year, using water quality and land use data collected independently, agreement within ± 7 percent was obtained. The model was then used to forecast the impact of future urban development proposed for the watershed, in terms of phosphorus loading, and to evaluate the reduction in loading resulting from several urban best management practices (BMP). It was determined that phosphorus removal will have to be applied to all the urban runoff from the watershed to appreciably reduce stream phosphorus concentration. Of the BMP designs assessed, an infiltration pond system resulted in the greatest phosphorus load reduction, 50 percent from the 1995–1996 baseline.     

AGRICULTURE LAND‐USE EFFECTS ON NUTRIENT LOSSES IN WEST TIAOXI WATERSHED,CHINA1

ABSTRACT: Five types of land use/land covers in the West Tiaoxi watershed of China were studied for nutrient losses in artificial rainstorm runoff. A self‐designed rainfall simulator was used. In situ rainfall simulations were used to: (1) compare the concentrations of nitrogen and phosphorous in different land use/land covers and (2) evaluate the flux of nitrogen and phosphorous export from runoff and sediment in various types of land use/land covers. Three duplicated experiments were carried out under rain intensity of 2 mm/min, each lasting 32 minutes on a 3 m² plot. Characteristics of various species of nitrogen and phosphorous in runoff and sediment were investigated. The results showed that the concentrations of total nitrogen (TN) and total phosphorous (TP) were greatest in runoff from mulberry trees and smallest from pine forest. The TN and TP export was mainly from suspended particulate in runoff. TN and TP exports from the top 10 cm layer of five types of land use/land covers were estimated as high as 4.66 to 9.40 g/m² and 2.57 to 4.89 g/m², respectively, of which exports through sediment of runoff accounted for more than 90 percent and 97 percent. The rate of TN and TP exports ranged from 2.68 to approximately 14.48 and 0.45 to approximately 4.11 mg/m²/min in runoff; these rates were much lower than those of 100.01 to approximately 172.67 and 72.82 to approximately 135.96 mg/m²/min in the runoff sediment.     

INTEGRATING LANDSCAPE ASSESSMENT AND HYDROLOGIC MODELING FOR LAND COVER CHANGE ANALYSIS1

ABSTRACT: Significant land cover changes have occurred in the watersheds that contribute runoff to the upper San Pedro River in Sonora, Mexico, and southeast Arizona. These changes, observed using a series of remotely sensed images taken in the 1970s, 1980s, and 1990s, have been implicated in the alteration of the basin hydrologic response. The Cannonsville subwatershed, located in the Catskill/Delaware watershed complex that delivers water to New York City, provides a contrast in land cover change. In this region, the Cannonsville watershed condition has improved over a comparable time period. A landscape assessment tool using a geographic information system (GIS) has been developed that automates the parameterization of the Soil and Water Assessment Tool (SWAT) and KINEmatic Runoff and EROSion (KINEROS) hydrologic models. The Automated Geospatial Watershed Assessment (AGWA) tool was used to prepare parameter input files for the Upper San Pedro Basin, a subwatershed within the San Pedro undergoing significant changes, and the Cannonsville watershed using historical land cover data. Runoff and sediment yield were simulated using these models. In the Cannonsville watershed, land cover change had a beneficial impact on modeled watershed response due to the transition from agriculture to forest land cover. Simulation results for the San Pedro indicate that increasing urban and agricultural areas and the simultaneous invasion of woody plants and decline of grasslands resulted in increased annual and event runoff volumes, flashier flood response, and decreased water quality due to sediment loading. These results demonstrate the usefulness of integrating remote sensing and distributed hydrologic models through the use of GIS for assessing watershed condition and the relative impacts of land cover transitions on hydrologic response.     

Integrating contributing areas and indexing phosphorus loss from agricultural watersheds

Most states in the USA have adopted P Indexing to guide P-based management of agricultural fields by identifying the relative risk of P loss at farm and watershed scales. To a large extent, this risk is based on hydrologic principles that frequently occurring storms can initiate surface runoff from fields. Once initiated, this hydrological pathway has a high potential to transport P to the stream. In regions where hydrologically active areas of watersheds vary in time and space, surface runoff generation by "saturation excess" has been linked to distance from stream, with larger events resulting in larger contributing distances. Thus, storm-return period and P loss from a 39.5-ha mixed-land-use watershed in Pennsylvania was evaluated to relate return-period thresholds and distances contributing P to streams. Of 248 storm flows between 1997 and 2006, 93% had a return period of 1 yr, contributing 47% of total P (TP) export, while the largest two storms (10-yr return period) accounted for 23% of TP export. Contributing distance thresholds for the watershed were determined (50-150 m) for a range of storm-return periods (1-10 yr) from hydrograph analysis. By modifying storm-return period thresholds in the P Index and thereby contributing distance, it is possible to account for greater risk of P loss during large storms. For instance, increasing return period threshold from 1 (current P indices) to 5 yr, which accounted for 67% of TP export, increased the P-management restricted area from 20 to 58% of the watershed. An increase in impacted area relative to a decreased risk of P loss creates a management-policy dilemma that cannot be ignored.     

Modeling Watershed‐Scale Impacts of Stormwater Management with Traditional versus Low Impact Development Design

Stormwater runoff and associated pollutants from urban areas in the greater Chesapeake Bay Watershed (CBW) impair local streams and downstream ecosystems, despite urbanized land comprising only 7% of the CBW area. More recently, stormwater best management practices (BMPs) have been implemented in a low impact development (LID) manner to treat stormwater runoff closer to its source. This approach included the development of a novel BMP model to compare traditional and LID design, pioneering the use of comprehensively digitized storm sewer infrastructure and BMP design connectivity with spatial patterns in a geographic information system at the watershed scale. The goal was to compare total watershed pollutant removal efficiency in two study watersheds with differing spatial patterns of BMP design (traditional and LID), by quantifying the improved water quality benefit of LID BMP design. An estimate of uncertainty was included in the modeling framework by using ranges for BMP pollutant removal efficiencies that were based on the literature. Our model, using Monte Carlo analysis, predicted that the LID watershed removed approximately 78 kg more nitrogen, 3 kg more phosphorus, and 1,592 kg more sediment per square kilometer as compared with the traditional watershed on an annual basis. Our research provides planners a valuable model to prioritize watersheds for BMP design based on model results or in optimizing BMP selection.     

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.     

DETERMINING NUTRIENT EXPORT COEFFICIENTS AND SOURCE LOADING UNCERTAINTY USING IN‐STREAM MONITORING DATA1

ABSTRACT: Over a three‐year period, flow and nutrients were monitored at 13 sites in the upper North Bosque River watershed in Texas. Drainage areas above sampling sites differed in percent of dairy waste application fields, forage fields, wood/range, and urban land area. A multiple regression approach was used to develop total phosphorus (TP) and total nitrogen (TN) export coefficients for the major land uses in these heterogeneous drainage areas. The largest export coefficients were associated with dairy waste application fields followed by urban, forage fields, and wood/range. An empirical model was then established to assess nutrient contribution by major sources using developed export coefficients and point source loadings from municipal wastewater treatment. This model was verified by comparison of estimated loadings to measured in‐stream data. Monte Carlo simulation techniques were applied to provide an uncertainty analysis for nutrient loads by source, based on the variance associated with each export coefficient. The largest sources of nutrients contributing to the upper North Bosque River were associated with dairy waste application fields and forage fields, while the greatest relative uncertainty in source contribution was associated with loadings from urban and wood/range land uses.     

ANALYSIS AND PREDICTION OF SURFACE RUNOFF IN AN URBANIZING WATERSHED USING SATELLITE IMAGERY1

ABSTRACT: This paper demonstrates how satellite image data [e.g., from Landsat 5 Thematic Mapper (TM)], in conjunction with an urban growth model and simple runoff calculations, can be used to estimate future surface runoff and, by implication, water quality within a watershed. To illustrate the method, predictions of land use change and surface runoff are shown for Spring Creek Watershed, a medium sized urbanizing watershed in Central Pennsylvania. Land cover classifications for this watershed were created from images for summertime 1986 and 1996 and subsequently used as input to the Clarke urban growth model, called SLEUTH, to predict land use changes to the year 2025. Simulations with this model show a progressive growth in the percentage of urban pixels and in impervious surface area in the watershed but also an increase in woodland, primarily in previously clear‐cut areas. Given that woodland area will continue to increase in area, surface runoff into Spring Creek is predicted to remain only slightly above present level. However, should the woodland amount fail to increase, surface runoff is then predicted to increase more significantly during the next 25 years. Finally, the concept of urban sprawl is addressed within the context of predicted increases in urbanization by relating the implied increase in impervious surface area to population density within the watershed.     

EFFECTS OF PRECIPITATION AND LAND USE ON STORM RUNOFF1

ABSTRACT: Storm-runoff quantity and quality were studied in three watersheds located near St. Paul in Ramsey County, Minnesota, from April 15 through September 15 of 1984, 1985, and 1986 to qualitatively determine the effects of precipitation and selected land uses on storm runoff. In respect to precipitation effects, differences in stormrunoff quantity between years in an urban watershed that lacks wetlands appear to be related to the average storm size (amount of precipitation) during the study period of each year. In contrast, the differences in storm-runoff quantity from watersheds that contain wetlands appear to be related to total precipitation during study period of each year. In respect to land use, the differences in storm-runoff quantity appear to be related to the amounts of impervious and wetland area. The watershed that contains the largest amount of impervious area and smallest amount of wetland area has the largest amount of storm runoff. Differences in storm-runoff quality appear to be related to the amounts of wetland and lake area. The watershed that contains the largest amounts of wetland and lake area has the smallest storm-runoff loading of suspended solids, phosphorus, and nitrogen. The wetland and lake areas likely retain the loading and, subsequently, lower the amount of storm-runoff loading exported from a watershed.     

Boosted Regression Tree Models to Explain Watershed Nutrient Concentrations and Biological Condition

Boosted regression tree (BRT) models were developed to quantify the nonlinear relationships between landscape variables and nutrient concentrations in a mesoscale mixed land cover watershed during base‐flow conditions. Factors that affect instream biological components, based on the Index of Biotic Integrity (IBI), were also analyzed. Seasonal BRT models at two spatial scales (watershed and riparian buffered area [RBA]) for nitrite‐nitrate (NO₂‐NO₃), total Kjeldahl nitrogen, and total phosphorus (TP) and annual models for the IBI score were developed. Two primary factors — location within the watershed (i.e., geographic position, stream order, and distance to a downstream confluence) and percentage of urban land cover (both scales) — emerged as important predictor variables. Latitude and longitude interacted with other factors to explain the variability in summer NO₂‐NO₃ concentrations and IBI scores. BRT results also suggested that location might be associated with indicators of sources (e.g., land cover), runoff potential (e.g., soil and topographic factors), and processes not easily represented by spatial data indicators. Runoff indicators (e.g., Hydrological Soil Group D and Topographic Wetness Indices) explained a substantial portion of the variability in nutrient concentrations as did point sources for TP in the summer months. The results from our BRT approach can help prioritize areas for nutrient management in mixed‐use and heavily impacted watersheds.     

DEVELOPMENT OF WATERSIIED MODELS FOR TWO SIERRA NEVADA BASINS USING A GEOGRAPHIC INFORMATION SYSTEM1

ABSTRACT: Techniques were developed using vector and raster data in a geographic information system (GIS) to define the spatial variability of watershed characteristics in the north-central Sierra Nevada of California and Nevada and to assist in computing model input parameters. The U.S. Geological Survey's Precipitation-Runoff Modeling System, a physically based, distributed-parameter watershed model, simulates runoff for a basin by partitioning a watershed into areas that each have a homogeneous hydrologic response to precipitation or snowmelt. These land units, known as hydrologic-response units (HRU's), are characterized according to physical properties, such as altitude, slope, aspect, land cover, soils, and geology, and climate patterns. Digital data were used to develop a GIS data base and HRIJ classification for the American River and Carson River basins. The following criteria are used in delineating HRU's: (1) Data layers are hydrologically significant and have a resolution appropriate to the watershed's natural spatial variability, (2) the technique for delineating HRU's accommodates different classification criteria and is reproducible, and (3) HRU's are not limited by hydrographic-subbasin boundaries. HRU's so defined are spatially noncontiguous. The result is an objective, efficient methodology for characterizing a watershed and for delineating HRU's. Also, digital data can be analyzed and transformed to assist in defining parameters and in calibrating the model.     

Visualizing riparian ecotone fragmentation in urbanizing watersheds: A case study of upper Hickory Creek,north‐Central Texas

Many pollution sources and heavy runoff often plague urbanizing watersheds. Riparian ecotones can filter pollutants and attenuate runoff; however, changing land cover tends to diminish this buffering capacity. Visualizing riparian ecotone fragmentation at the watershed scale can help prioritize management efforts. A geographic information systems approach was developed to illustrate land cover and soil properties affecting buffering potential along riparian corridors. An application to the Hickory Creek watershed in north‐central Texas shows significant riparian ecotone fragmentation, suggesting high‐priority areas for preservation and restoration.