David M. Wolock 2003 raster digital data U.S. Geological Survey Open-File Report 03-264 Reston, VA U.S. Geological Survey http://water.usgs.gov/lookup/getspatial?satof48 This 5-kilometer resolution raster (grid) dataset for the conterminous United States represents the average percentage of saturation overland flow in total streamflow estimated by the watershed model TOPMODEL. Saturation overland flow is simulated in TOPMODEL as precipitation that falls on saturated land-surface areas and enters the stream channel. TOPMODEL was applied to 5- by 5-kilometer areas across the conterminous United States using national climate, soils, and terrain GIS datasets. The model was run for 1,000 days for each 5- by 5-kilometer area. The average percentage of saturation overland flow in total streamflow was computed for the 1,000-day simulation in each grid cell. The saturation overland-flow dataset was developed to assist the U.S. Geological Survey's National Water-Quality Assessment (NAWQA) Program (Gilliom and others, 1995). The dataset was produced to help NAWQA national synthesis teams identify and quantify the watershed characteristics that theoretically affect flow paths of water through watersheds and their effects on water quality. Purpose references: Gilliom, R.J., Alley, W.M., and Gurtz, M.E., 1995, Design of the National Water-Quality Monitoring Program--Occurrence and distribution of water-quality conditions: U.S. Geological Survey Circular 1112, 33 p., available on the World Wide Web, accessed July 7, 2003, at URL http://water.usgs.gov/pubs/circ/circ1112/ TOPMODEL background: TOPMODEL (Beven and Kirkby, 1979) simulates the movement of water through a watershed from the time that it enters the watershed as precipitation to the time that it exits the watershed as streamflow. The version of TOPMODEL used to generate the saturation overland-flow dataset simulates the variable-source-area concept of streamflow generation (Dunne and Black, 1970) and the Betson (1964) partial-area modification of the Horton (1933) concept of infiltration-excess overland flow. The Horton concept states that streamflow during high flow conditions is generated by overland flow that is produced when precipitation rates exceed infiltration rates at the land-atmosphere interface. In the original concept of infiltration-excess overland flow, Horton (1933) assumed that streamflow during high flow conditions was produced by overland flow generated throughout the entire area of a watershed. Later, Betson (1964) proposed that in some watersheds streamflow during high flow conditions was generated from infiltration-excess overland flow produced on only a small part of the watershed area, an idea known as the "partial-area concept." Infiltration-excess overland flow is believed to constitute a major part of the storm hydrograph in areas where infiltration rates are less than precipitation rates; for example, in disturbed or poorly vegetated areas in subhumid and semiarid regions. In the variable-source-area concept (Dunne and Black, 1970), streamflow during high flow conditions is generated on saturated surface areas called "source areas," which occur in places where the water table rises to the land surface. The water table rises because precipitation infiltrates into the soil, moves down to the saturated subsurface zone, and then subsequently moves downslope in the saturated subsurface zone. Saturated land-surface areas commonly develop near existing stream channels and expand as more water enters the subsurface through infiltration and then moves downslope as saturated subsurface flow. Variable-source-area flow is thought to be an important streamflow-generation mechanism where infiltration rates are greater than precipitation rates; for example, in undisturbed vegetated areas in humid, temperate regions. Saturated land-surface areas are sources of streamflow during high flow conditions in several ways. Saturation overland flow (also called Dunne overland flow) is generated if subsurface hydraulic characteristics are not transmissive and if slopes are gentle and convergent. Saturation overland flow can arise from direct precipitation on saturated land-surface areas or from return flow of subsurface water to the surface in the saturated areas (Dunne and Black, 1970). The saturation overland-flow values in this dataset include only direct precipitation on saturated areas; return flow is treated as a separate flow component. Rain (or snowmelt) first is partitioned into infiltration-excess overland flow and infiltrated water. The infiltration rate and time to ponding computations are based on the Green-Ampt assumptions (see Beven, 1984). Soil permeability is assumed in the model to be spatially variable; this assumption allows infiltration-excess overland flow to be simulated for partial areas of the watershed according to Betson's (1964) concept. Water that infiltrates into the upper soil zone can evaporate or transpire at a rate dependent on the potential evapotranspiration rate (computed from air temperature and latitude) and the amount of moisture available in the upper soil zone. Some rain (or snowmelt) can bypass the unsaturated subsurface zone and move directly into the saturated subsurface zone through macropores, which are large pores in the soil that conduct water downward before the soil is completely saturated (Beven and Germann, 1982). The depth to the water table is decreased by water draining down from above or moving laterally from other parts of the watershed. If this contribution of water to the saturated subsurface zone at a particular location in the watershed is large enough, then the water table rises to the land surface, and the area becomes saturated. Saturation overland flow is produced by direct precipitation (rain or snowmelt) on saturated areas. The saturated land-surface area also can produce return flow if the water table rises above the land surface and exfiltration occurs. During all streamflow conditions, any water stored in the saturated subsurface zone is assumed to move downslope towards the stream channel. A portion of the subsurface zone water, depending on the volume stored and TOPMODEL parameters, drains into the stream. TOPMODEL assumes that the rate of subsurface flow into the stream increases exponentially as the water table moves closer to the land surface. This assumption is based on the idea that macropores can increase hydraulic transmissivity in the lateral direction and that macropores become increasingly abundant near the soil surface (Beven, 1984; Elsenbeer and others, 1992). Any drainage from the saturated subsurface zone into the stream increases the depth to the water table. The location of source areas (the saturated land-surface areas) within the watershed are affected by basin topography and soil hydraulic characteristics. This is consistent with observed spatial distributions of soil moisture and potentiometric surfaces (for example, Kirkby and Chorley, 1967; Dunne and others, 1975; Anderson and Burt, 1978). Source areas are found where subsurface water collects; these are locations where large upslope areas are drained, and where there is limited capacity for continued downslope movement. Topography, the three-dimensional configuration of gravitational effects on drainage, affects the location of source areas. As subsurface water moves downslope, it collects in topographically flatter convergent areas. The degree of convergence determines how much upslope area drains down to a given location. The slope of the flat areas affects the "ability" of water to move farther downslope. Soil hydraulic characteristics (hydraulic conductivity and soil depth) determine the transmissivity at a location and affect the ability of water to move farther downslope. Topography and soil characteristics, watershed latitude, and a time series of precipitation and air temperature must be specified to use TOPMODEL. (The methods used to compute the soil and topography parameters are described in the Process_Step sections.) The watershed latitude is used to generate a time series of day length that, along with the time series of temperature, is used to calculate potential evapotranspiration. The precipitation and temperature time series are generated in the model internally using stochastic equations and climate characteristics such as average storm intensity and mean daily temperature. Description of the climate characteristics and the stochastic approach also are given in the Process_Step sections of the metadata. TOPMODEL is run on a daily time step for days with no precipitation and on an hourly time step for days with precipitation. TOPMODEL predicts streamflow, estimates overland and subsurface flow, and estimates the depth to the water table. Infiltration-excess overland flow for a given time step is calculated from the estimated time to ponding and the precipitation intensity. Saturation overland flow is calculated from the areal extent of the saturated land-surface areas and the precipitation intensity. Subsurface flow is computed as a function of the maximum subsurface-flow rate (determined by topography and soil characteristics) and the watershed average depth to the water table. The watershed average depth to the water table is computed by water balance; that is, by tracking input (precipitation) and output (overland flow, subsurface flow, and evapotranspiration). A more detailed description of TOPMODEL can be found in Wolock (1993). TOPMODEL references: Anderson, M.G., and Burt, T.P., 1978, The role of topography in controlling throughflow generation: Earth Surface Processes, v. 3, p. 331-344. Betson, R.P., 1964, What is watershed runoff?: Journal of Geophysical Research, v. 69, p. 1541-1552. Beven, K.J., 1984, Infiltration into a class of vertically nonuniform soils: Hydrological Sciences Journal, v. 29, p. 425-434. Beven, K.J., and Germann, P., 1982, Macropores and water flow in soils: Water Resources Research, v. 18, p. 1311-1325. Beven, K.J., and Kirkby, M.J., 1979, A physically based, variable contributing area model of basin hydrology: Hydrological Sciences Bulletin, v. 24, p. 43-69. Dunne, T., and Black, R.D., 1970, Partial area contributions to storm runoff in a small New England watershed: Water Resources Research, v. 6, p. 1296-1311. Dunne, T., Moore, T.R., and Taylor, C.H., 1975, Recognition and prediction of runoff-producing zones in humid regions: Hydrological Sciences Bulletin, v. 20, p. 305-327. Elsenbeer, H., Cassel, K., and Castro, J., 1992, Spatial analysis of soil hydraulic conductivity in a tropical rain forest catchment: Water Resources Research, v. 28, p. 3201-3214. Horton, R.E., 1933, The role of infiltration in the hydrologic cycle: EOS, Transactions, American Geophysical Union, v. 14, p. 446-460. Kirkby, M.J., and Chorley, R.J., 1967, Throughflow, overland flow and erosion: Bulletin of the International Association of Scientific Hydrology, v. 12, p. 5-21. Wolock, D.M., 1993, Simulating the variable-source-area concept of streamflow generation with the watershed model TOPMODEL: U.S. Geological Survey Water-Resources Investigations Report 93-4124, 33 p. The use of firm, trade, and brand names is for identification purposes only and does not constitute endorsement by the U.S. Government. unknown publication date Complete None planned -128.046430 -64.080993 51.967053 23.254317 None TOPMODEL Dunne overland flow Saturation overland flow Streamflow generation None. The values of saturation overland flow in the dataset should be viewed as highly uncertain. Uncertainty in the saturation overland-flow percentages is high because there are many sources of potential error and uncertainty in the TOPMODEL simulations. For example, the climate, soils, and terrain data required by the model are spatially coarse and possibly inaccurate. The spatial coarseness of the climate data produces a noticeable coarseness in the estimated percentages of saturation overland flow in total streamflow. In some Western States, there are very few meteorological stations for computing the climate characteristics. This data sparseness propagates into the TOPMODEL results and creates a splotchy pattern in the estimated percentage of saturation overland flow. Another important source of uncertainty in TOPMODEL (and any other model) is termed "model uncertainty." This type of uncertainty exists because the model is only a simple representation of the hydrologic processes assumed to be most important in determining how water moves through the environment. The estimated flow components from TOPMODEL will be in error to the extent that the model does not represent important complexities in the real hydrologic system. David M. Wolock U.S. Geological Survey Research Hydrologist mailing address

4821 Quail Crest Place

Lawrence KS 66049 USA 785-832-3528 785-832-3500 dwolock@usgs.gov Leon Kauffman and Charles Crawford, both of the U.S. Geological Survey, reviewed the metadata. None Unclassified None Microsoft Windows 2000 Version 5.1 (Build 2600) Service Pack 1; ESRI ArcCatalog 8.2.0.700 None None Easterling, D. R., T. R. Karl, J. H. Lawrimore, and S. A. Del Greco 1999 Unknown tabular digital data NDP 070 Oak Ridge, TN Carbon Dioxide Information Analysis Center, Oak Ridge National http://cdiac.esd.ornl.gov/epubs/ndp/ndp070/ndp070.html online 1871 unknown 1997 unknown ground condition ndp070 Daily time series of precipitation and temperature were used to compute climate characteristics at the locations of 1,060 meteorological station locations. David M. Wolock 1997 Unknown raster digital data U.S. Geological Survey Open-File Report 97-656 Reston, Virginia U.S. Geological Survey http://water.usgs.gov/lookup/getspatial?muid online 1997 unknown publication date muid The soils data were used to estimate spatial distributions of soil thickness, permeability, available water capacity and bulk density. U.S. Geological Survey 1987 Unknown raster digital data http://edc.usgs.gov/geodata/ http://rockyweb.cr.usgs.gov/nmpstds/demstds.html online 1987 publication date dem250 The 1:250,000-scale DEM datasets were used to compute the spatial distribution of the topographic wetness index at 100-m resolution. Computation of the topographic wetness index (TWI): The effects of topography on hydrologic processes in TOPMODEL are quantified as a topographic wetness index (TWI). The TWI was derived from 1:250,000-scale digital elevation model (DEM) datasets available for the entire United States at 3-arcseconds resolution (U.S. Geological Survey, 1987). There are about 1,000 DEMs covering the conterminous United States. Each 3-arcsecond resolution DEM was first projected from spherical coordinates to the Albers Conical Equal Area coordinate system; the resolution of the DEMs in the Albers coordinate system is about 100 meters. The spatial distribution of the TWI then was computed for each DEM using algorithms based on those reported in Jenson and Domingue (1988). These algorithms are incorporated in the geographic-information-system package Arc/Info (ESRI, 2000), which was used to derive the TWI distributions. The steps to compute the TWI distribution are described in detail in Wolock and McCabe (1995). Statistics (minimum, maximum, mean, variance, and skew) of the TWI distribution were computed for 5- by 5-kilometer areas overlain on the 100-meter resolution TWI grid. The statistics then were used to estimate the frequency distribution of the TWI in each TOPMODEL simulation. TWI references: ESRI, 2000, ArcInfo, version 8.0.2: Redlands, CA, Environmental Systems Research Institute, various pagination. Jenson, S.K., and Domingue, J.O., 1988, Extracting topographic structure from digital elevation data for geographic information system analysis: Photogrammetric Engineering and Remote Sensing, v. 54, p. 1593-1600. U.S. Geological Survey, 1987, Digital elevation models--data users guide 5: Reston, VA, U.S. Geological Survey, various pagination. Wolock, D.M., and McCabe, G.J., Jr., 1995, Comparison of single and multiple flow direction algorithms for computing topographic parameters in TOPMODEL: Water Resources Research, v. 31, p. 1315-1324. The use of firm, trade, and brand names is for identification purposes only and does not constitute endorsement by the U.S. Government. Unknown David M. Wolock U.S. Geological Survey Research Hydrologist mailing address

4821 Quail Crest Place

Lawrence KS 66049 USA 785-832-3528 785-832-3500 dwolock@usgs.gov Estimation of soil characteristics: The critical soil characteristics for TOPMODEL are the spatial distributions of soil thickness, permeability, available water capacity, and porosity. Values for the soil characteristics can be derived from county soil surveys conducted by the U.S. Department of Agriculture's National Resource Conservation Service (NRCS, formerly the Soil Conservation Service, SCS). Results of the county soil surveys have been generalized and made available for the entire United States in a digital database called the State Soil Geographic Data Base (STATSGO) (U.S. Department of Agriculture, 1993). These data are Arc/Info (ESRI, 2000) polygon coverages that are based on 1:250,000-scale maps. A map unit identification code (MUID) is associated with each polygon; the MUIDs relate to a table that gives the soil characteristics composition of each map unit. A map unit, for example, may be composed of five components, each of which is associated with a percentage composition. (The percentages sum to 100 percent.) The soil characteristics (for example, permeability) may vary with each component. The components can be aggregated to obtain a single value for each soil characteristic for each map unit. Ranges in soil characteristics also can be assigned to each map unit. Details on how the STATSGO data were processed can be found in Wolock (1997). The STATSGO data were used to estimate spatial distributions of soil thickness, permeability, available water capacity, and bulk density using ARC/INFO. Saturated hydraulic conductivity was assumed to be equal to the permeability. Soil porosity (n), expressed as a fraction of the soil volume, was computed from bulk density (bd) and soil particle density (pd) using the relation: n = 1 - ( bd / pd ). A particle density value of 2.65 grams per cubic centimeter was assumed for all soils. This assumption is commonly made by soil scientists and usually is reasonable (Brady, 1974). The STATSGO data consist of separate polygon coverages for each State. These polygons were gridded to 5-kilometer resolution for each State and then merged to derive 5-kilometer resolution grids for the conterminous United States. Soil references: Brady, N.C., 1974, The nature and property of soils: New York, MacMillan Publ. Co., 639 p. ESRI, 2000, ArcInfo, version 8.0.2: Redlands, CA, Environmental Systems Research Institute, various pagination. U.S. Department of Agriculture, 1993, State Soil Geographic Data Base (STATSGO), data users guide: Soil Conservation Service, Miscellaneous Publication Number 1492, various pagination. Wolock, D.M., 1997, STATSGO soil characteristics for the conterminous United States: USGS Open-File Report 97-656, digital data release, available on the World Wide Web, accessed June 27, 2003, at URL http://water.usgs.gov/GIS/metadata/usgswrd/muid.html The use of firm, trade, and brand names is for identification purposes only and does not constitute endorsement by the U.S. Government. Unknown David M. Wolock U.S. Geological Survey Research Hydrologist mailing and physical address

4821 Quail Crest Place

Lawrence KS 66049 USA 785-832-3528 785-832-3500 dwolock@usgs.gov Computation of climate characteristics: Daily precipitation and temperature data for 1,060 meteorological stations distributed throughout the United States (Easterling and others, 1999) were obtained from the Carbon Dioxide Information Analysis Center (CDIAC) at Oak Ridge National Laboratory in Oak Ridge, Tennessee. Only stations with a period of record greater than 30 years were included in the analysis. The CDIAC data were used to calculate point values for the average storm intensity, average storm duration, average interstorm period, average daily temperature, and standard deviation of daily temperature. The climate characteristics were computed for each month of the year. The point values of the climate characteristics were interpolated onto a 5-kilometer resolution grid for the conterminous United States using ArcInfo. Grid cells that did not correspond in space to a point measurement of climate were assigned the climate characteristic values of the nearest climate station. The climate characteristics were used with a random-number generator to produce the input time series of precipitation and temperature needed to run TOPMODEL. Daily precipitation values were derived from a simple storm-based model similar to that used by Beven (1986) and described in Wolock and Hornberger (1991). The model assumes that storm intensity (depth of precipitation per day), storm duration (number of consecutive days of precipitation), and interstorm period (number of consecutive days between storms) are distributed exponentially over a long period and that these distributions are independent of each other. The daily precipitation time series is specified by repeated random sampling of the distributions of storm intensity, storm duration, and interstorm period. Daily average temperature for a given day of the year is simulated as a function of the average daily temperature for that month of the year and the standard deviation of the daily temperature for that month of the year. The average daily temperature is computed by interpolating between the average daily temperatures for the 2 months that bracket that day of the year. A simple snow accumulation and melt model, similar to one developed by the U.S. Army Corps of Engineers (U.S. Corps of Engineers, 1960; Chow, 1964), was incorporated into TOPMODEL. In the model, snow accumulates when the observed air temperature is less than a specified temperature cutoff value. The value of the temperature cutoff value depends on the vegetative cover, slope, and aspect of the site, and suggested values are given in the literature (for example, see Chow, 1964). Snow melts when the air temperature is above the temperature cutoff value. The rate at which snow melts depends on the air temperature and whether it is raining. Potential evapotranspiration (PET) was estimated with the Hamon formula (Hamon, 1961). This is an empirical relation in which PET is estimated from latitude and air temperature. Latitude is used to compute the maximum possible clear-sky duration of sunshine by calculating the solar declination and the sunset-hour angle (Kreith and Kreider, 1978). Air temperature is used to calculate the mass density of water in air. Climate references: Beven, K.J., 1986, Runoff production and flood frequency in catchments of order n--an alternative approach, in Gupta, V.K., Rodriguez-Iturbe, I., and Wood, E.F., eds., Scale problems in hydrology: Dordrecht, D. Reidel Publ. Co., p. 107-131. Chow, V.T., 1964, Handbook of applied hydrology: New York, McGraw Hill, 1418 p. Easterling, D. R., T. R. Karl, J. H. Lawrimore, and Del Greco, S.A., 1999, United States Historical Climatology Network Daily Temperature, Precipitation, and Snow Data for 1871-1997: ORNL/CDIAC-118, NDP-070, Carbon Dioxide Information Analysis Center, Oak Ridge National Laboratory, Oak Ridge, Tennessee, 84 p. Hamon, W.R., 1961, Estimating potential evapotranspiration: Journal of the Hydraulics Division, Proceedings of the American Society of Civil Engineers, v. 87, p. 107-120. Kreith, F., and Kreider, J.F., 1978, Principles of solar engineering: Washington, D.C., Hemisphere Publ. Corp., 778 p. U.S. Army Corps of Engineers, 1960, Manuals--engineering and design, runoff from snowmelt: EM1110-2-1406, various pagination Wolock, D.M., and Hornberger, G.M., 1991, Hydrological effects of changes in atmospheric carbon dioxide levels: Journal of Forecasting, v. 10, p. 105-116. The use of firm, trade, and brand names is for identification purposes only and does not constitute endorsement by the U.S. Government. Unknown David M. Wolock U.S. Geological Survey Research Hydrologist mailing and physical address

4821 Quail Crest Place

Lawrence KS 66049 USA 785-832-3528 785-832-3500 dwolock@usgs.gov TOPMODEL simulations: TOPMODEL simulations were run on a 5-kilometer resolution grid for the conterminous United States using the 5-kilometer grids of topography, soil, and climate characteristics. A total of 213,088 individual simulations were completed. The topography characteristics for each grid cell were the minimum, maximum, mean, variance, and skew of the TWI distribution. These statistics were used to generate a gamma frequency distribution, and the model equations were evaluated for each of 30 TWI intervals. The soil characteristics for each grid cell were the average available water capacity, soil thickness, permeability, and porosity. The saturated hydraulic conductivity (that is, the permeability) value was assumed to represent the effective saturated conductivity of the soil matrix excluding the effects of macropores. It was assumed for these simulations that the effective saturated hydraulic conductivity of the soil at the surface, including the effects of macropores, was two orders of magnitude greater than the saturated hydraulic conductivity value of the soil matrix. It was further assumed that the fraction of the soil volume that is hydrologically active during high-flow conditions was 0.15, and that the effective rooting depth was 1 meter. The climate characteristics for each grid cell were used to generate daily precipitation and temperature time series that were 1,000 days each in length. The model was run at daily time steps for days without precipitation and at hourly time steps for days with precipitation. For days with precipitation, the total daily precipitation was distributed over a randomly selected number of consecutive hours within the day. The model was run without calibrating any of the model parameters. The first year of each simulation was discarded because the arbitrary initial conditions can affect the simulation results during this time period. Statistics for the simulated hydrologic characteristics, including the percentage of saturation overland flow in total streamflow, were computed for the remaining 2 years of the simulation. Unknown David M. Wolock U.S. Geological Survey Research Hydrologist mailing and physical address

4821 Quail Crest Place

Lawrence KS 66049 USA 785-832-3528 785-832-3500 dwolock@usgs.gov Raster Grid Cell 580 940 1 Albers Conical Equal Area 29.500000 45.500000 -96.000000 23.000000 0.000000 0.000000 row and column 5000.000000 5000.000000 meters North American Datum of 1983 Geodetic Reference System 80 6378137.000000 298.257222 satof48 Saturation overland flow Wolock ObjectID Internal feature number. ESRI Sequential unique whole numbers that are automatically generated. Value TOPMODEL-estimated saturation overland flow, in percent Wolock 0 69 Percent Count The number of grid cells in the dataset with the corresponding "VALUE" Wolock 1 133685 Number of grid cells The data structure of the INFO table is: COLUMN ITEM NAME WIDTH OUTPUT TYPE 1 VALUE 4 10 B 5 COUNT 4 10 B The item VALUE in the grid is the estimated percentage of saturation overland flow in total streamflow. The item COUNT is the number of grid cells in the dataset with the corresponding "VALUE." Wolock U.S. Geological Survey Ask USGS - Water Webserver Team mailing

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Reston VA 20192 1-888-275-8747 (1-888-ASK-USGS) http://answers.usgs.gov/cgi-bin/gsanswers?pemail=h2oteam&subject=GIS+Dataset+satof48 Although this data set has been used by the U.S. Geological Survey, U.S. Department of the Interior, no warranty expressed or implied is made by the U.S. Geological Survey as to the accuracy of the data and related materials. The act of distribution shall not constitute any such warranty, and no responsibility is assumed by the U.S. Geological Survey in the use of this data, software, or related materials. Any use of trade, product, or firm names is for descriptive purposes only and does not imply endorsement by the U.S. Government. Other Full coverage zipped 1 http://water.usgs.gov/GIS/dsdl/satof48.tgz http://water.usgs.gov/GIS/dsdl/satof48.e00 None. This dataset is provided by USGS as a public service. 20041108 U.S. Geological Survey Ask USGS -- Water Webserver Team mailing

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Reston VA 20192 1-888-275-8747 (1-888-ASK-USGS) http://answers.usgs.gov/cgi-bin/gsanswers?pemail=h2oteam&subject=GIS+Dataset+satof48 FGDC Content Standards for Digital Geospatial Metadata FGDC-STD-001-1998