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At least 1,315 records · Page 73Linked to original sources
USGS1985

Spirit Lake dam-failure flood routing assessment

Potential clear-water floodflows resulting from uncontrolled breaching by Spirit Lake of a debris dam deposited by the May 18 , 1980, eruption of Mount St. Helens, Washington, were evaluated. U.S. Geological Survey dam-break model K-634 was utilized, first to compute clear-water flood hydrographs for various hypothetical breach scenarios, and then to hydraulically route them downstream to the mouth of the Toutle River. Dam-break computations were obtained for 12 breach-development scenarios. Eight of the scenarios modeled breaches caused by overtopping of the June 1982 crest of the debris dam, while the other four modeled breaches resulting from overtopping of the debris dam at a possible future crest altitude of 3,490 feet. Equal numbers of scenarios, six each, were modeled for breach development durations of 0.25 hour and 1.0 hour. Peak discharges and times of arrival at selected locations for scenarios with breach development durations of 1.0 hour are presented in tables. Peak discharges computed for dam-break scenarios with breach crest widths of 400 feet are almost twice the magnitude of those computed for scenarios identical in all other respects, but with widths of 200 feet. Peak discharges computed for breaches caused by overtopping of the debris dam at an altitude of 3,531.8 feet were generally found to be roughly five times greater than those caused by overtopping at an altitude of 3,490 feet, if the breaches had identical crest elevations and crest widths. Decreases in peak discharge from Spirit Lake to the mouth of the Toutle River ranged from 16 to 26 percent for the scenarios modeled. This lack of significant attenuation is primarily due to the large volume and surface area of Spirit lake (in excess of 360,000 acre-feet and 3,000 acres, respectively, for all scenarios modeled), which result in the continued discharge of high flows long after breach development is complete. The degree of attenuation is also minimized by the generally steep narrow valleys through which the North Fork Toutle and Toutle Rivers flow. Elapsed time from beginning of breach development to arrival of peak discharges at the mouth of the Toutle River ranged from 4.3 to 7.4 hours for the scenarios modeled. (USGS)

Open-File Report↗
USGS1993

Procedures for adjusting regional regression models of urban-runoff quality using local data

Statistical operations termed model-adjustment procedures (MAP’s) can be used to incorporate local data into existing regression models to improve the prediction of urban-runoff quality. Each MAP is a form of regression analysis in which the local data base is used as a calibration data set. Regression coefficients are determined from the local data base, and the resulting ‘adjusted’ regression models can then be used to predict storm-runoff quality at unmonitored sites. The response variable in the regression analyses is the observed load or mean concentration of a constituent in storm runoff for a single storm. The set of explanatory variables used in the regression analyses is different for each MAP, but always includes the predicted value of load or mean concentration from a regional regression model. The four MAP’s examined in this study were: single-factor regression against the regional model prediction, P, (termed MAP-lF-P), regression against P,, (termed MAP-R-P), regression against P, and additional local variables (termed MAP-R-P+nV), and a weighted combination of P, and a local-regression prediction (termed MAP-W). The procedures were tested by means of split-sample analysis, using data from three cities included in the Nationwide Urban Runoff Program: Denver, Colorado; Bellevue, Washington; and Knoxville, Tennessee. The MAP that provided the greatest predictive accuracy for the verification data set differed among the three test data bases and among model types (MAP-W for Denver and Knoxville, MAP-lF-P and MAP-R-P for Bellevue load models, and MAP-R-P+nV for Bellevue concentration models) and, in many cases, was not clearly indicated by the values of standard error of estimate for the calibration data set. A scheme to guide MAP selection, based on exploratory data analysis of the calibration data set, is presented and tested. The MAP’s were tested for sensitivity to the size of a calibration data set. As expected, predictive accuracy of all MAP’s for the verification data set decreased as the calibration data-set size decreased, but predictive accuracy was not as sensitive for the MAP’s as it was for the local regression models.

Open-File Report↗
USGS2007

A Deep Percolation Model for Estimating Ground-Water Recharge: Documentation of Modules for the Modular Modeling System of the U.S. Geological Survey

A daily water-budget model for estimating ground-water recharge, the Deep Percolation Model, was modularized for inclusion into the U.S. Geological Survey's Modular Modeling System. The model was modularized in order to facilitate estimation of ground-water recharge under a large range in climatic, landscape, and land-use and land-cover conditions. The model can be applied to areas as large as regions or as small as a field plot. An overview of the Modular Modeling System and the Deep Percolation Model is presented. Data requirements, parameters, and variables for the model are described. The modules that compose the Deep Percolation Model are documented.

Scientific Investigations Report↗
USGS2007

Effects of the temporal variability of evapotranspiration on hydrologic simulation in central Florida

The transient response of a hydrologic system can be of concern to water-resource managers, because it is often extreme relatively short-lived events, such as floods or droughts, that profoundly influence the management of the resource. The water available to a hydrologic system for stream flow and aquifer recharge is determined by the difference of precipitation and evapotranspiration (ET). As such, temporal variations in precipitation and ET determine the degree of influence each has on the transient response of the hydrologic system. Meteorological, ET, and hydrologic data collected from 1993 to 2003 and spanning 1- to 3 2/3 -year periods were used to develop a hydrologic model for each of five sites in central Florida. The sensitivities of simulated water levels and flows to simple approximations of ET were quantified and the adequacy of each ET approximation was assessed. ET was approximated by computing potential ET, using the Hargreaves and Priestley-Taylor equations, and applying vegetation coefficients to adjust the potential ET values to actual ET. The Hargreaves and Priestley-Taylor ET approximations were used in the calibrated hydrologic models while leaving all other model characteristics and parameter values unchanged. Two primary factors that influence how the temporal variability of ET affects hydrologic simulation in central Florida were identified: (1) stochastic character of precipitation and ET and (2) the ability of the local hydrologic system to attenuate variability in input stresses. Differences in the stochastic character of precipitation and ET, both the central location and spread of the data, result in substantial influence of precipitation on the quantity and timing of water available to the hydrologic system and a relatively small influence of ET. The temporal variability of ET was considerably less than that of precipitation at each site over a wide range of time scales (from daily to annual). However, when precipitation and ET are of similar magnitude, small errors in ET can produce relatively large errors in available water, and accurate estimates of actual ET are more important. Local hydrologic conditions can also be an important factor influencing the hydrologic response to ET variability. Various points along a flow path in a hydrologic system respond differently to temporal variations in ET. For example, soil moisture contents in the root zone are sensitive to daily variations in ET, whereas spring flow responds to only longer term variations in ET. Both the Hargreaves and Priestley-Taylor equations for potential ET, when applied with an annually invariant monthly vegetation coefficient derived from comparison of measured ET with computed potential ET values, can be used with a hydrologic model to produce reasonable predictions of water levels and flows. Baseline-adjusted modified coefficients of efficiency for simulated water levels ranged from 0.0, indicating that water levels were simulated equally as well with approximated ET as with actual ET values, to -0.6, indicating that water levels were simulated better with actual ET values. Simulations using the Hargreaves approximation consistently yielded larger absolute and relative errors than the Priestley-Taylor approximation. However, the differences between the Hargreaves and Priestley-Taylor simulations generally were much smaller than differences between these simulations and the simulations using actual ET. This suggests that the simpler Hargreaves equation may be an adequate substitute for the more complex Priestley-Taylor equation, depending on the level of accuracy required to satisfy the particular modeling objectives.

Florida↗
USGS2017

Fena Valley Reservoir watershed and water-balance model updates and expansion of watershed modeling to southern Guam

In 2014, the U.S. Geological Survey, in cooperation with the U.S. Department of Defense’s Strategic Environmental Research and Development Program, initiated a project to evaluate the potential impacts of projected climate-change on Department of Defense installations that rely on Guam’s water resources. A major task of that project was to develop a watershed model of southern Guam and a water-balance model for the Fena Valley Reservoir. The southern Guam watershed model provides a physically based tool to estimate surface-water availability in southern Guam. The U.S. Geological Survey’s Precipitation Runoff Modeling System, PRMS-IV, was used to construct the watershed model. The PRMS-IV code simulates different parts of the hydrologic cycle based on a set of user-defined modules. The southern Guam watershed model was constructed by updating a watershed model for the Fena Valley watersheds, and expanding the modeled area to include all of southern Guam. The Fena Valley watershed model was combined with a previously developed, but recently updated and recalibrated Fena Valley Reservoir water-balance model. Two important surface-water resources for the U.S. Navy and the citizens of Guam were modeled in this study; the extended model now includes the Ugum River watershed and improves upon the previous model of the Fena Valley watersheds. Surface water from the Ugum River watershed is diverted and treated for drinking water, and the Fena Valley watersheds feed the largest surface-water reservoir on Guam. The southern Guam watershed model performed “very good,” according to the criteria of Moriasi and others (2007), in the Ugum River watershed above Talofofo Falls with monthly Nash-Sutcliffe efficiency statistic values of 0.97 for the calibration period and 0.93 for the verification period (a value of 1.0 represents perfect model fit). In the Fena Valley watershed, monthly simulated streamflow volumes from the watershed model compared reasonably well with the measured values for the gaging stations on the Almagosa, Maulap, and Imong Rivers—tributaries to the Fena Valley Reservoir—with Nash-Sutcliffe efficiency values of 0.87 or higher. The southern Guam watershed model simulated the total volume of the critical dry season (January to May) streamflow for the entire simulation period within –0.54 percent at the Almagosa River, within 6.39 percent at the Maulap River, and within 6.06 percent at the Imong River. The recalibrated water-balance model of the Fena Valley Reservoir generally simulated monthly reservoir storage volume with reasonable accuracy. For the calibration and verification periods, errors in end-of-month reservoir-storage volume ranged from 6.04 percent (284.6 acre-feet or 92.7 million gallons) to –5.70 percent (–240.8 acre-feet or –78.5 million gallons). Monthly simulation bias ranged from –0.48 percent for the calibration period to 0.87 percent for the verification period; relative error ranged from –0.60 to 0.88 percent for the calibration and verification periods, respectively. The small bias indicated that the model did not consistently overestimate or underestimate reservoir storage volume. In the entirety of southern Guam, the watershed model has a “satisfactory” to “very good” rating when simulating monthly mean streamflow for all but one of the gaged watersheds during the verification period. The southern Guam watershed model uses a more sophisticated climate-distribution scheme than the older model to make use of the sparse climate data, as well as includes updated land-cover parameters and the capability to simulate closed depression areas. The new Fena Valley Reservoir water-balance model is useful as an updated tool to forecast short-term changes in the surface-water resources of Guam. Furthermore, the now spatially complete southern Guam watershed model can be used to evaluate changes in streamflow and recharge owing to climate or land-cover changes. These are substantial improvements to the previous models of the Fena Valley watershed and Reservoir. Datasets associated with this report are available as a U.S. Geological Survey data release (Rosa and Hay, 2017; DOI:10.5066/F7HH6HV4).

Scientific Investigations Report↗