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.     

PHYSICAL DETERMINANTS OF ECONOMIC VALUE OF RIPARIAN BUFFERS IN AN AGRICULTURAL WATERSHED1

ABSTRACT: Economic values of riparian buffers in a watershed are evaluated by the changes in the net economic return for farming with and without riparian buffers when achieving the same water quality objectives. The simulated water quality impacts of alternative farming systems using SWAT and experimental data for riparian buffers are used in a mathematical optimization model to estimate net economic return for farming subject to a water quality objective. Physical characteristics such as stream length, channel slope, average land slope, cropland percentage and several soil attributes are identified in the watershed using ARC/INFO GIS. A regression model is then used to evaluate the impacts of these physical characteristics on the estimated economic values of buffers. The study is conducted in Goodwater Creek watershed, Missouri. The results show the estimated economic value of buffers is significantly affected by some soil properties, stream length, and cropland percentage in watershed and can be used to improve the effectiveness of riparian buffers at watershed and regional levels.     

Modeling Stream Channel Characteristics From Drainage‐Enforced DEMs in Puget Sound,Washington, USA1

Abstract: Mapping stream channels and their geomorphic attributes is an important step in many watershed research and management projects. Often insufficient field data exist to map hydromorphologic attributes across entire drainage basins, necessitating the application of hydrologic modeling tools to digital elevation models (DEMs) via a geographic information system (GIS). In this article, we demonstrate methods for deriving synthetic stream networks via GIS across large and diverse basins using drainage‐enforced DEMs, along with techniques for estimating channel widths and gradient on the reach scale. The two‐step drainage enforcement method we used produced synthetic stream networks that displayed a high degree of positional accuracy relative to the input streams. The accuracies of our estimated channel parameters were assessed with field data, and predictions of bankfull width, wetted width and gradient were strongly correlated with measured values (r² = 0.92, r² = 0.95, r² = 0.88, respectively). Classification accuracies of binned channel attributes were also high. Our methodology allows for the relatively rapid mapping of stream channels and associated morphological attributes across large geographic areas. Although initially developed to provide salmon recovery planners with important salmon habitat information, we suggest these methodologies are relevant to a variety of research and management questions.     

INTEGRATING GEOGRAPHIC INFORMATION SYSTEMS AND MODFLOW FOR GROUND WATER RESOURCE ASSESSMENTS1

ABSTRACT: The Floridan Aquifer is the primary source of water in the coastal area of Santa Rosa County, Florida. In order to optimize well field design and analyze aquifer stress problems, the USGS MODFLOW code (McDonald and Harbaugh, 1988) is applied to develop a numerical computer model of the aquifer. The Geographical Information System (GIS) is the primary tool used in the development of the model grid, performance of the modeling procedure, and model analysis. The GIS is used in generating multiple grids in which to simulate both regional scale and local scale flow. The grid topology is recorded in geographic coordinates which facilitates geo-referencing and orientation of the grid to base maps and data coyerages. The GIS allows data transfer from various coverages to the nodes of the block centered grid where hydrogeologic information is stored as attributes to the grid coverage. From this grid coverage, pertinent information is queried within the GIS environment and used to generate the input files for the MODFLOW simulation. After MODFLOW execution, simulated heads and drawdown are imported into the grid coverage where residual error and recharge rates can be calculated. Contoured surfaces are then created for selected data sets including simulated heads, drawdown, residual error, and recharge rates. Model calibration is conducted utilizing the GIS to generate and process data sets associated with model simulations.     

A Quantitative Method for Delineating Regions: An Example for the Western Corn Belt Plains Ecoregion of the USA

/ A method was developed to systematically delineate boundaries forecological classification of regions. The process entailed the use ofsmall-scale digital data to quantify spatial concordance among environmentalattribute data sets. The data sets were grouped into spatially related themesusing cluster analysis and multidimensional scaling. Selected data sets werethen used either individually or collectively to divide the study area intosubregions that exhibited different environmental attributes. The method wasapplied to a previously defined ecological unit, the western Corn Belt of thecentral United States. The results showed that the portion of the study areawith intensive corn and soybean production was identifiable using each of thethree input data sets selected for partitioning (soil associations; AVHRRremote-sensing imagery; and a combined data set of landform, forest, andsoils data). The classification of other portions of the study area washighly dependent on the type and scale of the input data. The systematicmethodology used here offers advantages over other methods for identifyingecological regions in that the results from the systematic approach can bereproduced, the boundaries between ecological units can be revised based onnew or more accurate data, important ecological processes are explicitlychosen to delineate boundaries, and transition zones between regions can bequantified.KEY WORDS: Ecoregions; Spatial analysis; Corn Belt; Iowa; GIS;Regionalization     

A FAST ALGORITHM FOR AUTOMATICALLY COMPUTING STRAHLER STREAM ORDER1

ABSTRACT: An efficient algorithm was developed to determine Strahler stream order for segments of stream networks represented in a Geographic Information System (GIS). The algorithm correctly assigns Strahler stream order in topologically complex situations such as braided streams and multiple drainage outlets. Execution time varies nearly linearly with the number of stream segments in the network. This technique is expected to be particularly useful for studying the topology of dense stream networks derived from digital elevation model data.     

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.     

Regional and Local Scale Modeling of Stream Temperatures and Spatio-Temporal Variation in Thermal Sensitivities

Understanding variation in stream thermal regimes becomes increasingly important as the climate changes and aquatic biota approach their thermal limits. We used data from paired air and water temperature loggers to develop region-scale and stream-specific models of average daily water temperature and to explore thermal sensitivities, the slopes of air–water temperature regressions, of mostly forested streams across Maryland, USA. The region-scale stream temperature model explained nearly 90 % of the variation (root mean square error = 0.957 °C), with the mostly flat coastal plain streams having significantly higher thermal sensitivities than the steeper highlands streams with piedmont streams intermediate. Model R ² for stream-specific models was positively related to a stream’s thermal sensitivity. Both the regional and the stream-specific air–water temperature regression models benefited from including mean daily discharge from regional gaging stations, but the degree of improvement declined as a stream’s thermal sensitivity increased. Although catchment size had no relationship to thermal sensitivity, steeper streams or those with greater amounts of forest in their upstream watershed were less thermally sensitive. The subset of streams with three or more summers of temperature data exhibited a wide range of annual variation in thermal sensitivity at a site, with the variation not attributable to discharge, precipitation patterns, or physical attributes of streams or their watersheds. Our findings are a useful starting point to better understand patterns in stream thermal regimes. However, a more spatially and temporally comprehensive monitoring network should increase understanding of stream temperature variation and its controls as climatic patterns change.     

MULTIVARIATE CLASSIFICATION OF SMALL ORDER WATERSHEDS IN THE QUABBIN RESERVOIR BASIN,MASSACHUSEVFS1

ABSTRACT: A multivariate approach was used to analyze hydrologic, geologic, geographic, and water-chemistry data from small order watersheds in the Quabbin Reservoir Basin in central Massachusetts. Eighty three small order watersheds were delineated and landscape attributes defining hydrologic, geologic, and geographic features of the watersheds were compiled from geographic information system data layers. Principal components analysis was used to evaluate 11 chemical constituents collected bi-weekly for 1 year at 15 surface-water stations in order to subdivide the basin into subbasins comprised of watersheds with similar water quality characteristics. Three principal components accounted for about 90 percent of the variance in water chemistry data. The principal components were defined as a biogeochemical variable related to wet. land density, an acid-neutralization variable, and a road-salt variable related to density of primary roads. Three subbasins were identified. Analysis of variance and multiple comparisons of means were used to identify significant differences in stream water chemistry and landscape attributes among subbasins. All stream water constituents were significantly different among subbasins. Multiple regression techniques were used to relate stream water chemistry to landscape attributes. Important differences in landscape attributes were related to wetlands, slope, and soil type.     

Application of a GIS-based stream buffer generation model to environmental policy evaluation

In this article a GIS method is presented for riparian environmental buffer generation. It integrates a scientifically tested buffer width delineation model into a GIS framework. Using the generally available data sets, it determines buffer widths in terms of local physical conditions and expected effectiveness. Technical burdens of data management, computation, and result presentation are handled by the GIS. The case study in which the method was used to evaluate the stream buffer regulations in a North Carolina county demonstrates its capability as a decision support tool to facilitate environmental policy formulation and evaluation, and environmental dispute resolution.     

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.     

COMPARISON OF REGRESSION AND TIME-SERIES METHODS FOR SYNTHESIZING MISSING STREAMFLOW RECORDS1

ABSTRACT: Regression and time-series techniques have been used to synthesize and predict the stream flow at the Foresta Bridge gage from information at the upstream Pohono Bridge gage on the Merced River near Yosemite National Park. Using the available data from two time periods (calendar year 1979 and water year 1986), we evaluated the two techniques in their ability to model the variation in the observed flows and in their ability to predict stream flow at the Foresta Bridge gage for the 1979 time period with data from the 1986 time period. Both techniques produced reasonably good estimates and forecasts of the flow at the downstream gage. However, the regression model was found to have a significant amount of autocorrelation in the residuals, which the time-series model was able to eliminate. The time-series technique presented can be of great assistance in arriving at reasonable estimates of flow in data sets that have large missing portions of data.     

SPATIALLY DISTRIBUTED MODELING OF STREAM FLOW DURING STORM EVENTS1

ABSTRACT: The purpose of this paper is to present a new approach for the spatially distributed modeling of water flow during storm events. Distributed modeling of flow during storm events is an important basis for any environmental modeling, including turbidity or sediment transport. During the initial phase of a rainstorm, surface runoff is the main contributor of flow. To provide the spatial components for distributed hydrological modeling a Geographic Information System (GIS) was used to map and visualize contributing areas around a stream channel. Stream segments were defined using the hydrologic response unit (HRU) concept. Lateral flows were derived from GIS output for each segment of the stream and at each time interval of the rain storm and were routed using the kinematic routing equation. This approach is new in hydrological modeling and can be used to enhance many existing simulations. The model is also unique in the fine time scale (i.e., intervals are on the order of minutes). Model results showed good correlation with measured discharge values; however, further studies of contributing area behavior, its relationship with soil types and slope categories, and the influence of watershed size are needed to improve model performance. This model will be used in the future as the basis to model turbidity in streams.     

Modeling Streams and Hydrogeomorphic Attributes in Oregon From Digital and Field Data1

Abstract: Managers, regulators, and researchers of aquatic ecosystems are increasingly pressed to consider large areas. However, accurate stream maps with geo‐referenced attributes are uncommon over relevant spatial extents. Field inventories provide high‐quality data, particularly for habitat characteristics at fine spatial resolutions (e.g., large wood), but are costly and so cover relatively small areas. Recent availability of regional digital data and Geographic Information Systems software has advanced capabilities to delineate stream networks and estimate coarse‐resolution hydrogeomorphic attributes (e.g., gradient). A spatially comprehensive coverage results, but types of modeled outputs may be limited and their accuracy is typically unknown. Capitalizing on strengths in both field and regional digital data, we modeled a synthetic stream network and a variety of hydrogeomorphic attributes for the Oregon Coastal Province. The synthetic network, encompassing 96,000 km of stream, was derived from digital elevation data. We used high‐resolution but spatially restricted data from field inventories and streamflow gauges to evaluate, calibrate, and interpret hydrogeomorphic attributes modeled from digital elevation and precipitation data. The attributes we chose to model (drainage area, mean annual precipitation, mean annual flow, probability of perennial flow, channel gradient, active‐channel width and depth, valley‐floor width, valley‐width index, and valley constraint) have demonstrated value for stream research and management. For most of these attributes, field‐measured, and modeled values were highly correlated, yielding confidence in the modeled outputs. The modeled stream network and attributes have been used for a variety of purposes, including mapping riparian areas, identifying headwater streams likely to transport debris flows, and characterizing the potential of streams to provide high‐quality habitat for salmonids. Our framework and models can be adapted and applied to areas where the necessary field and digital data exist or can be obtained.     

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.     

Assessment Tools for Urban Catchments: Developing Biological Indicators Based on Benthic Macroinvertebrates1

Abstract: Biological indicators, particularly benthic macroinvertebrates, are widely used and effective measures of the impact of urbanization on stream ecosystems. A multimetric biological index of urbanization was developed using a large benthic macroinvertebrate dataset (n = 1,835) from the Baltimore, Maryland, metropolitan area and then validated with datasets from Cleveland, Ohio (n = 79); San Jose, California (n = 85); and a different subset of the Baltimore data (n = 85). The biological metrics used to develop the multimetric index were selected using several criteria and were required to represent ecological attributes of macroinvertebrate assemblages including taxonomic composition and richness (number of taxa in the insect orders of Ephemeroptera, Plecoptera, and Trichoptera), functional feeding group (number of taxa designated as filterers), and habit (percent of individuals which cling to the substrate). Quantile regression was used to select metrics and characterize the relationship between the final biological index and an urban gradient (composed of population density, road density, and urban land use). Although more complex biological indices exist, this simplified multimetric index showed a consistent relationship between biological indicators and urban conditions (as measured by quantile regression) in three climatic regions of the United States and can serve as an assessment tool for environmental managers to prioritize urban stream sites for restoration and protection.     

PREDICTION OF STREAM TEMPERATURE IN FORESTED WATERSHEDS1

ABSTRACT: Removal of streamside vegetation changes the energy balance of a stream, and hence its temperature. A common approach to mitigating the effects of logging on stream temperature is to require establishment of buffer zones along stream corridors. A simple energy balance model is described for prediction of stream temperature in forested headwater watersheds that allows evaluation of the performance of such measures. The model is designed for application to “worst case” or maximum annual stream temperature, under low flow conditions with maximum annual solar radiation and air temperature. Low flows are estimated via a regional regression equation with independent variables readily accessible from GIS databases. Testing of the energy balance model was performed using field data for mostly forested basins on both the west and east slopes of the Cascade Mountains, and was then evaluated using the regional equations for low flow and observed maximum reach temperatures in three different east slope Cascades catchments. A series of sensitivity analyses showed that increasing the buffer width beyond 30 meters did not significantly decrease stream temperatures, and that other vegetation parameters such as leaf area index, average tree height, and to a lesser extent streamside vegetation buffer width, more strongly affected maximum stream temperatures.     

EXAMINING LAND USE INFLUENCES ON STREAM HABITATS AND MACROINVERTEBRATES: A GIS APPROACH1

ABSTRACT: Geographic Information Systems (GIS) were used to assess the relationships between land use patterns and the physical habitat and macroinvertebrate fauna of streams within similar sized watersheds. Eleven second or third order watersheds ranging from highly urbanized to heavily forested were selected along Lake Superior's North Shore. Land use patterns within the watersheds were quantified using readily available digital land use/land cover information, with a minimum mapping resolution of 16 ha. Physical habitat features, describing substrate characteristics and stream morphology, were characterized at sample points within each stream. Principle component and correlation analyses were used to identify relationships between macroinvertebrates and stream physical habitat, and between habitat and land use patterns. Substrate characteristics and presence of coarse woody debris were found to have the strongest correlations with macreinvertebrate assemblage richness and composition. Agricultural and urban land use was correlated with substrate characteristics. Algal abundance, associated with macroinvertebrate compositional differences, was correlated with housing density and non-forest land covers. The use of readily available spatial data, even at this relatively coarse scale, provides a means to detect the primary relationships between land use and stream habitat quality; finer-resolution GIS databases are needed to assess more subtle influences, such as those due to riparian conditions.     

HYDROLOGIC PARAMETERIZATION OF WATERSHEDS FOR RUNOFF PREDICTION USING SWAT1

ABSTRACT: The use of continuous time, distributed parameter hydrologic models like SWAT (Soil and Water Assessment Tool) has opened several opportunities to improve watershed modeling accuracy. However, it has also placed a heavy burden on users with respect to the amount of work involved in parameterizing the watershed in general and in adequately representing the spatial variability of the watershed in particular. Recent developments in Geographical Information Systems (GIS) have alleviated some of the difficulties associated with managing spatial data. However, the user must still choose among various parameterization approaches that are available within the model. This paper describes the important parameterization issues involved when modeling watershed hydrology for runoff prediction using SWAT with emphasis on how to improve model performance without resorting to tedious and arbitrary parameter by parameter calibration. Synthetic and actual watersheds in Indiana and Mississippi were used to illustrate the sensitivity of runoff prediction to spatial variability, watershed decomposition, and spatial and temporal adjustment of curve numbers and return flow contribution. SWAT was also used to predict stream runoff from actual watersheds in Indiana that have extensive subsurface drainage. The results of this study provide useful information for improving SWAT performance in terms of stream runoff prediction in a manner that is particularly useful for modeling ungaged watersheds wherein observed data for calibration is not available.     

LARGE AREA HYDROLOGIC MODELING AND ASSESSMENT PART II: MODEL APPLICATION1

ABSTRACT: This paper describes the application of a river basin scale hydrologic model (described in Part I) to Richland and Chambers Creeks watershed (RC watershed) in upper Trinity River basin in Texas. The inputs to the model were accumulated from hydro-graphic and geographic databases and maps using a raster-based GIS. Available weather data from 12 weather stations in and around the watershed and stream flow data from two USGS stream gauge station for the period 1965 to 1984 were used in the flow calibration and validation. Sediment calibration was carried out for the period 1988 through 1994 using the 1994 sediment survey data from the Richland-Chambers lake. Sediment validation was conducted on a subwatershed (Mill Creek watershed) situated on Chambers Creek of the RC watershed. The model was evaluated by well established statistical and visual methods and was found to explain at least 84 percent and 65 percent of the variability in the observed stream flow data for the calibration and validation periods, respectively. In addition, the model predicted the accumulated sediment load within 2 percent and 9 percent from the observed data for the RC watershed and Mill Creek watershed, respectively.