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.     

STORM RUNOFF PREDICTION BASED ON A SPATIALLY DISTRIBUTED TRAVEL TIME METHOD UTILIZING REMOTE SENSING AND GIS1

ABSTRACT: In this study, remotely sensed data and geographic information system (GIS) tools were used to estimate storm runoff response for Simms Creek watershed in the Etonia basin in northeast Florida. Land cover information from digital orthophoto quarter quadrangles (DOQQ), and enhanced thematic mapper plus (ETM+) were analyzed for the years 1990, 1995, and 2000. The corresponding infiltration excess runoff response of the study area was estimated using the U.S. Department of Agriculture (USDA), Natural Resources Conservation Service Curve Number (NRCS‐CN) method. A digital elevation model (DEM)/GIS technique was developed to predict stream response to runoff events based on the travel time from each grid cell to the watershed outlet. A comparison of predicted to observed stream response shows that the model predicts the total runoff volume with an efficiency of 0.98, the peak flow rate at an efficiency of 0.85, and the full direct runoff hydrograph with an average efficiency of 0.65. The DEM/GIS travel time model can be used to predict the runoff response of ungaged watersheds and is useful for predicting runoff hydrographs resulting from proposed large scale changes in the land use.     

GENERALIZED WATERSHED LOADING FUNCTIONS FOR STREAM FLOW NUTRIENTS1

ABSTRACT: Loading functions are proposed as a general model for estimating monthly nitrogen and phosphorus fluxes in stream flow. The functions have a simple mathematical structure, describe a wide range of rural and urban nonpoint sources, and couple surface runoff and ground water discharge. Rural runoff loads are computed from daily runoff and erosion and monthly sediment yield calculations. Urban runoff loads are based on daily nutrient accumulation rates and exponential wash off functions. Ground water discharge is determined by lumped parameter unsaturated and saturated zone soil moisture balances. Default values for model chemical parameters were estimated from literature values. Validation studies over a three-year period for an 850 km² watershed showed that the loading functions explained at least 90 percent of the observed monthly variation in dissolved and total nitrogen and phosphorus fluxes in stream flow. Errors in model predictions of mean monthly fluxes were: dissolved phosphorus - 4 percent; total phosphorus - 2 percent; dissolved nitrogen - 18 percent; and total nitrogen - 28 percent. These results were obtained without model calibration.     

GIS BASED LONG TERM HYDROLOGIC IMPACT EVALUATION FOR WATERSHED URBANIZATION1

ABSTRACT: To adequately manage impacts of ongoing or future land use changes in a watershed, the magnitude of their hydrologic impacts needs to be assessed. A grid based daily streamflow model was calibrated with two years of observed streamflow data, using time periods when land use data are available and verified by comparison of model predictions with observed streamflow data. Streamflow data were separated into direct runoff and baseflow to estimate the impacts of urbanization on each hydrologic component. Analysis of the ratio between direct runoff and total runoff from 30 years of simulation results and the change in these ratios with urbanization shows that estimated annual direct runoff increased from 49.2 percent (1973) to 63.1 percent (1984) and 65.0 percent (1991), indicating the effects of urbanization are greater on direct runoff than on total runoff. The direct runoff ratio also varies with annual rainfall, with dry year ratios larger than those for wet years. This suggests that the impact of urbanization on areas that are sensitive to runoff ratios, such as stream ecosystems, might be more serious during drier years than in wetter years in terms of water quality and water yield. This indicates that sustainable base‐flow is important to maintaining sound stream ecosystems.     

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.     

Evaluation of the MIKE SHE Model for Application in the Loess Plateau,China1

Abstract: Quantifying the hydrologic responses to land use/land cover change and climate variability is essential for integrated sustainable watershed management in water limited regions such as the Loess Plateau in Northwestern China where an adaptive watershed management approach is being implemented. Traditional empirical modeling approach to quantifying the accumulated hydrologic effects of watershed management is limited due to its complex nature of soil and water conservation practices (e.g., biological, structural, and agricultural measures) in the region. Therefore, the objective of this study was to evaluate the ability of the distributed hydrologic model, MIKE SHE to simulate basin runoff. Streamflow data measured from an overland flow‐dominant watershed (12 km²) in northwestern China were used for model evaluation. Model calibration and validation suggested that the model could capture the dominant runoff process of the small watershed. We found that the physically based model required calibration at appropriate scales and estimated model parameters were influenced by both temporal and spatial scales of input data. We concluded that the model was useful for understanding the rainfall‐runoff mechanisms. However, more measured data with higher temporal resolution are needed to further test the model for regional applications.     

Random forest models to estimate bankfull and low flow channel widths and depths across the conterminous United States

Channel dimensions (width and depth) at varying flows influence a host of instream ecological processes, as well as habitat and biotic features; they are a major consideration in stream habitat restoration and instream flow assessments. Models of widths and depths are often used to assess climate change vulnerability, develop endangered species recovery plans, and model water quality. However, development and application of such models require specific skillsets and resources. To facilitate acquisition of such estimates, we created a dataset of modeled channel dimensions for perennial stream segments across the conterminous United States. We used random forest models to predict wetted width, thalweg depth, bankfull width, and bankfull depth from several thousand field measurements of the National Rivers and Streams Assessment. Observed channel widths varied from <5 to >2000 m and depths varied from <2 to >125 m. Metrics of watershed area, runoff, slope, land use, and more were used as model predictors. The models had high pseudo R² values (0.70–0.91) and median absolute errors within ±6% to ±21% of the interquartile range of measured values across 10 stream orders. Predicted channel dimensions can be joined to 1.1 million stream segments of the 1:100 K resolution National Hydrography Dataset Plus (version 2.1). These predictions, combined with a rapidly growing body of nationally available data, will further enhance our ability to study and protect aquatic resources.     

Linking Biological Integrity and Watershed Models to Assess the Impacts of Historical Land Use and Climate Changes on Stream Health

Land use change and other human disturbances have significant impacts on physicochemical and biological conditions of stream systems. Meanwhile, linking these disturbances with hydrology and water quality conditions is challenged due to the lack of high-resolution datasets and the selection of modeling techniques that can adequately deal with the complex and nonlinear relationships of natural systems. This study addresses the above concerns by employing a watershed model to obtain stream flow and water quality data and fill a critical gap in data collection. The data were then used to estimate fish index of biological integrity (IBI) within the Saginaw Bay basin in Michigan. Three methods were used in connecting hydrology and water quality variables to fish measures including stepwise linear regression, partial least squares regression, and fuzzy logic. The IBI predictive model developed using fuzzy logic showed the best performance with the R ² = 0.48. The variables that identified as most correlated to IBI were average annual flow, average annual organic phosphorus, average seasonal nitrite, average seasonal nitrate, and stream gradient. Next, the predictions were extended to pre-settlement (mid-1800s) land use and climate conditions. Results showed overall significantly higher IBI scores under the pre-settlement land use scenario for the entire watershed. However, at the fish sampling locations, there was no significant difference in IBI. Results also showed that including historical climate data have strong influences on stream flow and water quality measures that interactively affect stream health; therefore, should be considered in developing baseline ecological conditions.     

IMPACTS OF CALIFORNIA'S CLIMATIC REGIMES AND COASTAL LAND USE CHANGE ON STREAMFLOW CHARACTERISTICS1

ABSTRACT: To investigate the impacts of urbanization and climatic fluctuations on stream flow magnitude and variability in a Mediterranean climate, the HEC‐HMS rainfall/runoff model is used to simulate stream flow for a 14‐year period (October 1, 1988, to September 30, 2002) in the Atascadero Creek watershed located along the southern coast of California for 1929, 1998, and 2050 (estimated) land use conditions (8, 38 and 52 percent urban, respectively). The 14‐year period experienced a range of climatic conditions caused mainly by El Nino‐Southern Oscillation variations. A geographic information system is used to delineate the watershed and parameterize the model, which is calibrated using data from two stream flow and eight rainfall gauges. Urbanization is shown to increase peak discharges and runoff volume while decreasing stream flow variability. In all cases, the annual and 14‐year distributions of stream flow are shown to be highly skewed, with the annual maximum 24 hours of discharge accounting for 22 to 52 percent of the annual runoff and the maximum ten days of discharge from an average El Nino year producing 10 to 15 percent of the total 14‐year discharge. For the entire period of urbanization (1929 to 2050), the average increase in annual maximum discharges and runoff was 45 m³/s (300 percent) and 15 cm (350 percent), respectively. Additionally, the projected increase in urbanization from 1998 to 2050 is half the increase from 1929 to 1998; however, increases in runoff (22 m³/s and 7 cm) are similar for both scenarios because of the region's spatial development pattern.     

THE EFFECTS OF CLIMATE CHANGE ON STREAM FLOW AND NUTRIENT LOADING'

ABSTRACT: This study assesses the potential impact of climate change on stream flow and nutrient loading in six watersheds of the Susquehanna River Basin using the Generalized Watershed Loading Function (GWLF). The model was used to simulate changes in stream flow and nutrient loads under a transient climate change scenario for each watershed. Under an assumption of no change in land cover and land management, the model was used to predict monthly changes in stream flow and nutrient loads for future climate conditions. Mean annual stream flow and nutrient loads increased for most watersheds, but decreased in one watershed that was intensively cultivated. Nutrient loading slightly decreased in April and late summer for several watersheds as a result of early snowmelt and increasing evapotranspiration. Spatial and temporal variability of stream flow and nutrient loads under the transient climate scenario indicates that different approaches for future water resource management may be useful.     

MODELING FRAMEWORK FOR MANAGING COPPER RUNOFF IN URBAN WATERSHEDS1

ABSTRACT: A modeling framework was developed for managing copper runoff in urban watersheds that incorporates water quality characterization, watershed land use areas, hydrologic data, a statistical simulator, a biotic ligand binding model to characterize acute toxicity, and a statistical method for setting a watershed specific copper loading. The modeling framework is driven by export coefficients derived from water quality parameters and hydrologic inputs measured in an urban watershed's storm water system. This framework was applied to a watershed containing a copper roof built in 1992. A series of simulations was run to predict the change in receiving stream water chemistry caused by roof aging and to determine the maximum copper loading (at the 99 percent confidence level) a watershed could accept without causing acute toxicity in the receiving stream. Forecasting the amount of copper flux responsible for exceeding the assimilation capacity of a watershed can be directly related to maximum copper loadings responsible for causing toxicity in the receiving streams. The framework developed in this study can be used to evaluate copper utilization in urban watersheds.     

STORMFLOW SIMULATION USING A GEOGRAPHICAL INFORMATION SYSTEM WITH A DISTRIBUTED APPROACH1

ABSTRACT: With the increasing availability of digital and remotely sensed data such as land use, soil texture, and digital elevation models (DEMs), geographic information systems (GIS) have become an indispensable tool in preprocessing data sets for watershed hydrologic modeling and post processing simulation results. However, model inputs and outputs must be transferred between the model and the GIS. These transfers can be greatly simplified by incorporating the model itself into the GIS environment. To this end, a simple hydrologic model, which incorporates the curve number method of rainfall‐runoff partitioning, the ground‐water base‐flow routine, and the Muskingum flow routing procedure, was implemented on the GIS. The model interfaces directly with stream network, flow direction, and watershed boundary data generated using standard GIS terrain analysis tools; and while the model is running, various data layers may be viewed at each time step using the full display capabilities. The terrain analysis tools were first used to delineate the drainage basins and stream networks for the Susquehanna River. Then the model was used to simulate the hydrologic response of the Upper West Branch of the Susquehanna to two different storms. The simulated streamflow hydrographs compare well with the observed hydrographs at the basin outlet.     

Integrated Modular Modeling of Water and Nutrients From Point and Nonpoint Sources in the Patuxent River Watershed1

Abstract: We present a simple modular landscape simulation model that is based on a watershed modeling framework in which different sets of processes occurring in a watershed can be simulated separately with different models. The model consists of three loosely coupled submodels: a rainfall‐runoff model (TOPMODEL) for runoff generation in a subwatershed, a nutrient model for estimation of nutrients from nonpoint sources in a subwatershed, and a stream network model for integration of point and nonpoint sources in the routing process. The model performance was evaluated using monitoring data in the watershed of the Patuxent River, a tributary to the Chesapeake Bay in Maryland, from July 1997 through August 1999. Despite its simplicity, the landscape model predictions of streamflow, and sediment and nutrient loads were as good as or better than those of the Hydrological Simulation Program‐Fortran model, one of the most widely used comprehensive watershed models. The landscape model was applied to predict discharges of water, sediment, silicate, organic carbon, nitrate, ammonium, organic nitrogen, total nitrogen, organic phosphorus, phosphate, and total phosphorus from the Patuxent watershed to its estuary. The predicted annual water discharge to the estuary was very close to the measured annual total in terms of percent errors for both years of the study period (≤2%). The model predictions for loads of nutrients were also good (20‐30%) or very good (<20%) with exceptions of sediment (40%), phosphate (36%), and organic carbon (53%) for Year 1.     

The Watershed Flow and Allocation Model: An NHDPlus‐Based Watershed Modeling Approach for Multiple Scales and Conditions

The Watershed Flow and Allocation model (WaterFALL^®) provides segment‐specific, daily streamflow at both gaged and ungaged locations to generate the hydrologic foundation for a variety of water resources management applications. The model is designed to apply across the spatially explicit and enhanced National Hydrography Dataset (NHDPlus) stream and catchment network. To facilitate modeling at the NHDPlus catchment scale, we use an intermediate‐level rainfall‐runoff model rather than a complex process‐based model. The hydrologic model within WaterFALL simulates rainfall‐runoff processes for each catchment within a watershed and routes streamflow between catchments, while accounting for withdrawals, discharges, and onstream reservoirs within the network. The model is therefore distributed among each NHDPlus catchment within the larger selected watershed. Input parameters including climate, land use, soils, and water withdrawals and discharges are georeferenced to each catchment. The WaterFALL system includes a centralized database and server‐based environment for storing all model code, input parameters, and results in a single instance for all simulations allowing for rapid comparison between multiple scenarios. We demonstrate and validate WaterFALL within North Carolina at a variety of scales using observed streamflows to inform quantitative and qualitative measures, including hydrologic flow metrics relevant to the study of ecological flow management decisions.     

Predicting dissolved phosphorus in runoff from manured field plots

Dissolved inorganic P transport in runoff from agricultural soils is an environmental concern. Models are used to predict P transport but rarely simulate P in runoff from surface-applied manures. Using field-plot data, we tested a previously proposed model to predict manure P in runoff. We updated the model to include more data relating water to manure ratio to manure P released during water extractions. We verified that this update can predict P release from manure to rain using published data. We tested the updated model using field-plot and soil-box data from three manure runoff studies. The model accurately predicted runoff P for boxes, but underpredicted runoff P for plots. Underpredictions were caused by runoff to rain ratios used to distribute P into runoff or infiltration. We developed P distribution fractions from manure water extraction data to replace runoff to rain ratios. Calculating P distribution fractions requires knowing rainfall rate and times that runoff begins and rain stops. Using P distribution fractions gave accurate predictions of runoff P for soil boxes and field plots. We observed relationships between measured runoff to rain ratios and both P distribution fractions and a degree of error in original predictions, calculated as (measured runoff P/predicted runoff P). Using independent field-plot data, we verified that original underpredictions of manure runoff P can be improved by calculating P distribution fractions from measured runoff to rain ratios or adjusting runoff to rain ratios based on their degree of error. Future work should test the model at field or watershed scales and at longer time scales.     

Testing the Hydrological Landscape Unit Classification System and Other Terrain Analysis Measures for Predicting Low-Flow Nitrate and Chloride in Watersheds

Elevated nitrate concentrations in streamwater are a major environmental management problem. While land use exerts a large control on stream nitrate, hydrology often plays an equally important role. To date, predictions of low-flow nitrate in ungauged watersheds have been poor because of the difficulty in describing the uniqueness of watershed hydrology over large areas. Clearly, hydrologic response varies depending on the states and stocks of water, flow pathways, and residence times. How to capture the dominant hydrological controls that combine with land use to define streamwater nitrate concentration is a major research challenge. This paper tests the new Hydrologic Landscape Regions (HLRs) watershed classification scheme of Wolock and others (Environmental Management 34:S71-S88, 2004) to address the question: Can HLRs be used as a way to predict low-flow nitrate? We also test a number of other indexes including inverse-distance weighting of land use and the well-known topographic index (TI) to address the question: How do other terrain and land use measures compare to HLR in terms of their ability to predict low-flow nitrate concentration? We test this for 76 watersheds in western Oregon using the U.S. Environmental Protection Agency’s Environmental Monitoring and Assessment Program and Regional Environmental Monitoring and Assessment Program data. We found that HLRs did not significantly improve nitrate predictions beyond the standard TI and land-use metrics. Using TI and inverse-distance weighting did not improve nitrate predictions; the best models were the percentage land use—elevation models. We did, however, see an improvement of chloride predictions using HLRs, TI, and inverse-distance weighting; adding HLRs and TI significantly improved model predictions and the best models used inverse-distance weighting and elevation. One interesting result of this study is elevation consistently predicted nitrate better than TI or the hydrologic classification scheme.     

SUSCEPTIBILITY OF INDIANA WATERSHEDS TO HERBICIDE CONTAMINATION1

ABSTRACT: An index of watershed susceptibility to surface water contamination by herbicides could be used to improve source water assessments for public drinking water supplies, prioritize watershed restoration projects, and direct funding and educational efforts to areas where the greatest environmental benefit can be realized. The goal of this study is to use streamflow and herbicide concentration data to develop and evaluate a method for estimating comparative watershed susceptibility to herbicide loss. United States Geological Survey (USGS) concentration data for five relatively water soluble herbicides (alachlor, atrazine, cyanazine, metolachlor, and simazine) were analyzed for 16 Indiana watersheds. Correlation was assessed between observed herbicide losses and: (1) a herbicide runoff index using GIS‐based land use, soil type, SCS runoff curve number, tillage practice, herbicide use estimates, and combinations of these factors; and (2) predicted herbicide losses from a non‐point source pollution model (NAPRA‐Web, an Internet‐based interface for GLEAMS). The highest adjusted R²value was found between herbicide concentration and the runoff curve number alone, ranging from 0.25 to 0.56. Predictions from the simulation model showed a poorer correlation with observed herbicide loss. This indicates potential for using the runoff curve number as a simple herbicide contamination susceptibility index.     

APPLICATION OF THE RHESSys MODEL TO A CALIFORNIA SEMIARID SHRUBLAND WATERSHED1

ABSTRACT: Distributed hydrologic models which link seasonal streamflow and soil moisture patterns with spatial patterns of vegetation are important tools for understanding the sensitivity of Mediterranean type ecosystems to future climate and land use change. RHESSys (Regional Hydro‐Ecologic Simulation System) is a coupled spatially distributed hydroecological model that is designed to be able to represent these feedbacks between hydrologic and vegetation carbon and nutrient cycling processes. However, RHESSys has not previously been applied to semiarid shrubland watersheds. In this study, the hydrologic submodel of RHESSys is evaluated by comparing model predictions of monthly and annual streamflow to stream gage data and by comparing RHESSys behavior to that of another hydrologic model of similar complexity, MIKESHE, for a 34 km² watershed near Santa Barbara, California. In model intercomparison, the differences in predictions of temporal patterns in streamflow, sensitivity of model predictions to calibration parameters and landscape representation, and differences in model estimates of soil moisture patterns are explored. Results from this study show that both models adequately predict seasonal patterns of streamflow response relative to observed data, but differ significantly in terms of estimates of soil moisture patterns and sensitivity of those patterns to the scale of landscape tessellation used to derive spatially distributed elements. This sensitivity has implications for implementing RHESSys as a tool to investigate interactions between hydrology and ecosystem processes.     

Predicting soil erosion for alternative land uses

The APEX (Agricultural Policy-Environmental eXtender) model developed in the United States was calibrated for northwestern China's conditions. The model was then used to investigate soil erosion effects associated with alternative land uses at the ZFG (Zi-Fang-Gully) watershed in northwestern China. The results indicated that the APEX model could be calibrated reasonably well (+/-15% errors) to fit those areas with >50% slope within the watershed. Factors being considered during calibration include runoff, RUSLE (Revised Universal Soil Loss Equation) slope length and steepness factor, channel capacity flow rate, floodplain saturated hydraulic conductivity, and RUSLE C factor coefficient. No changes were made in the APEX computer code. Predictions suggest that reforestation is the best practice among the eight alternative land uses (the status quo, all grass, all grain, all grazing, all forest, half tree and half grass, 70% tree and 30% grain, and construction of a reservoir) for control of water runoff and soil erosion. Construction of a reservoir is the most effective strategy for controlling sediment yield although it does nothing to control upland erosion. For every 1 Mg of crop yield, 11 Mg of soil were lost during the 30-yr simulation period, suggesting that expanding land use for food production should not be encouraged on the ZFG watershed. Grass species are less effective than trees in controlling runoff and erosion on steep slopes because trees generally have deeper and more stable root systems.     

MOBILITY AND AQUATIC TOXICITY OF COPPER IN AN URBAN WATERSHED1

ABSTRACT: Abundant use of copper based products has resulted in increased violation of copper water quality criteria in runoff from urban storm water systems. The objectives of this work were to understand the mobility and toxicity of copper in an urban watershed and to apportion the amount of copper entering the freshwater receiving stream from different urban land covers using a mass balance approach. Sixteen rainfall events collected from the University of Connecticut study watershed between August 1998 and September 2000 were analyzed to assess copper flux in an urban storm water system. Mean flow weighted dissolved copper concentrations observed in the study for copper based architectural material runoff, pervious area runoff, impervious area runoff, and in the receiving stream were 1210 ± 840, 9 ± 3, 8 ± 2, and 14 ± 7 μg/L, respectively. Mean dissolved copper concentrations in the receiving stream exceeded Connecticut's water quality criteria. Despite exceeding the dissolved concentration based criteria, cupric ion concentrations at the system outlet remained below 0.05 μg/L for all storms analyzed, and no acute toxicity (using Daphnia pulex as the test organism) was measured in samples collected from the stream.