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B.M. Troutman

Publications and source records attributed to B.M. Troutman.

15 recordsLinked to original sources

Scaling of flow distance in random self-similar channel networks

Natural river channel networks have been shown in empirical studies to exhibit power-law scaling behavior characteristic of self-similar and self-affine structures. Of particular interest is to describe how the distribution of distance to the outlet changes as a function of network size. In this paper, networks are modeled as random self-similar rooted tree graphs and scaling of distance to the root is studied using methods in stochastic branching theory. In particular, the asymptotic expectation of the width function (number of nodes as a function of distance to the outlet) is derived under conditions on the replacement generators. It is demonstrated further that the branching number describing rate of growth of node distance to the outlet is identical to the length ratio under a Horton-Strahler ordering scheme as order gets large, again under certain restrictions on the generators. These results are discussed in relation to drainage basin allometry and an application to an actual drainage network is presented. ?? World Scientific Publishing Company.

Fractals

Assessment of the instantaneous unit hydrograph derived from the theory of topologically random networks

An instantaneous unit hydrograph (iuh) based on the theory of topologically random networks (topological iuh) is evaluated in terms of sets of basin characteristics and hydraulic parameters. Hydrographs were computed using two linear routing methods for each of two drainage basins in the southeastern United States and are the basis of comparison for the topological iuh's. Elements in the sets of basin characteristics for the topological iuh's are the number of first-order streams only, ( N ), or the nuber of sources together with the number of channel links in the topological diameter ( N, D ); the hydraulic parameters are values of the celerity and diffusivity constant. Sensitivity analyses indicate that the mean celerity of the internal links in the network is the critical hydraulic parameter for determining the shape of the topological iuh, while the diffusivity constant has minimal effect on the topological iuh. Asymptotic results (source-only) indicate the number of sources need not be large to approximate the topological iuh with the Weibull probability density function.

Water Resources Research

A consistent framework for Horton regression statistics that leads to a modified Hack's law

A statistical framework is introduced that resolves important problems with the interpretation and use of traditional Horton regression statistics. The framework is based on a univariate regression model that leads to an alternative expression for Horton ratio, connects Horton regression statistics to distributional simple scaling, and improves the accuracy in estimating Horton plot parameters. The model is used to examine data for drainage area A and mainstream length L from two groups of basins located in different physiographic settings. Results show that confidence intervals for the Horton plot regression statistics are quite wide. Nonetheless, an analysis of covariance shows that regression intercepts, but not regression slopes, can be used to distinguish between basin groups. The univariate model is generalized to include n > 1 dependent variables. For the case where the dependent variables represent ln A and ln L, the generalized model performs somewhat better at distinguishing between basin groups than two separate univariate models. The generalized model leads to a modification of Hack's law where L depends on both A and Strahler order ??. Data show that ?? plays a statistically significant role in the modified Hack's law expression. ?? 2008 Elsevier B.V.

Geomorphology

Use of topological information in hydrograph estimation

Discharge hydrographs computed from the theory of linear flow through topologically random channel networks are compared to actual discharge hydrographs for basins in semiarid regions of central Wyoming. The basins drained by the channel networks range in size from 0.69 to 10.8 square miles. Topological information consisting of stream-network magnitude and link -length distribution parameters are used in calibrating celerity values that ensure that the peak discharge and excess rainfall volume of the resulting computed hydrographs match the peak discharge and excess-rainfall volume of the actual hydrographs. Results indicate that, for a given peak discharge and excess-rainfall volume in a basin, the sensitivity of the calibrated celerity values to excess-rainfall duration is small if the ratio of excess-rainfall volume to peak discharge is at least 1.75 times the excess-rainfall duration.

Journal of the American Water Resources Associatio

Power-law tail probabilities of drainage areas in river basins

The significance of power-law tail probabilities of drainage areas in river basins was discussed. The convergence to a power law was not observed for all underlying distributions, but for a large class of statistical distributions with specific limiting properties. The article also discussed about the scaling properties of topologic and geometric network properties in river basins.

Physical Review E - Statistical, Nonlinear, and So

River flow mass exponents with fractal channel networks and rainfall

An important problem in hydrologic science is understanding how river flow is influenced by rainfall properties and drainage basin characteristics. In this paper we consider one approach, the use of mass exponents, in examining the relation of river flow to rainfall and the channel network, which provides the primary conduit for transport of water to the outlet in a large basin. Mass exponents, which characterize the power-law behavior of moments as a function of scale, are ideally suited for defining scaling behavior of processes that exhibit a high degree of variability or intermittency. The main result in this paper is an expression relating the mass exponent of flow resulting from an instantaneous burst of rainfall to the mass exponents of spatial rainfall and that of the network width function. Spatial rainfall is modeled as a random multiplicative cascade and the channel network as a recursive replacement tree; these fractal models reproduce certain types of self-similar behavior seen in actual rainfall and networks. It is shown that under these modeling assumptions the scaling behavior of flow mirrors that of rainfall if rainfall is highly variable in space, and on the other hand flow mirrors the structure of the network if rainfall is not so highly variable. ?? 2001 Elsevier Science Ltd. All rights reserved.

Advances in Water Resources

Evaluation of the depth-integration method of measuring water discharge in large rivers

The depth-integration method of measuring water discharge makes a continuous measurement of the water velocity from the water surface to the bottom at 20 to 40 locations or verticals across a river. It is especially practical for large rivers where river traffic makes it impractical to use boats attached to taglines strung across the river or to use current meters suspended from bridges. This method has the additional advantage over the standard two- and eight-tenths method in that a discharge-weighted suspended-sediment sample can be collected at the same time. When this method is used in large rivers such as the Missouri, Mississippi and Ohio, a microwave navigation system is used to determine the ship's position at each vertical sampling location across the river, and to make accurate velocity corrections to compensate for shift drift. An essential feature is a hydraulic winch that can lower and raise the current meter at a constant transit velocity so that the velocities at all depths are measured for equal lengths of time. Field calibration measurements show that: (1) the mean velocity measured on the upcast (bottom to surface) is within 1% of the standard mean velocity determined by 9–11 point measurements; (2) if the transit velocity is less than 25% of the mean velocity, then average error in the mean velocity is 4% or less. The major source of bias error is a result of mounting the current meter above a sounding weight and sometimes above a suspended-sediment sampling bottle, which prevents measurement of the velocity all the way to the bottom. The measured mean velocity is slightly larger than the true mean velocity. This bias error in the discharge is largest in shallow water (approximately 8% for the Missouri River at Hermann, MO, where the mean depth was 4.3 m) and smallest in deeper water (approximately 3% for the Mississippi River at Vickbsurg, MS, where the mean depth was 14.5 m). The major source of random error in the discharge is the natural variability of river velocities, which we assumed to be independent and random at each vertical. The standard error of the estimated mean velocity, at an individual vertical sampling location, may be as large as 9%, for large sand-bed alluvial rivers. The computed discharge, however, is a weighted mean of these random velocities. Consequently the standard error of computed discharge is divided by the square root of the number of verticals, producing typical values between 1 and 2%. The discharges measured by the depth-integrated method agreed within ±5% of those measured simultaneously by the standard two- and eight-tenths, six-tenth and moving boat methods.

Journal of Hydrology

Comparison of structural and least-squares lines for estimating geologic relations

Two different goals in fitting straight lines to data are to estimate a "true" linear relation (physical law) and to predict values of the dependent variable with the smallest possible error. Regarding the first goal, a Monte Carlo study indicated that the structural-analysis (SA) method of fitting straight lines to data is superior to the ordinary least-squares (OLS) method for estimating "true" straight-line relations. Number of data points, slope and intercept of the true relation, and variances of the errors associated with the independent (X) and dependent (Y) variables influence the degree of agreement. For example, differences between the two line-fitting methods decrease as error in X becomes small relative to error in Y. Regarding the second goal-predicting the dependent variable-OLS is better than SA. Again, the difference diminishes as X takes on less error relative to Y. With respect to estimation of slope and intercept and prediction of Y, agreement between Monte Carlo results and large-sample theory was very good for sample sizes of 100, and fair to good for sample sizes of 20. The procedures and error measures are illustrated with two geologic examples. ?? 1990 International Association for Mathematical Geology.

Mathematical Geology

Predictors of the peak width for networks with exponential links

We investigate optimal predictors of the peak (S) and distance to peak (T) of the width function of drainage networks under the assumption that the networks are topologically random with independent and exponentially distributed link lengths. Analytical results are derived using the fact that, under these assumptions, the width function is a homogeneous Markov birth-death process. In particular, exact expressions are derived for the asymptotic conditional expectations of S and T given network magnitude N and given mainstream length H. In addition, a simulation study is performed to examine various predictors of S and T, including N, H, and basin morphometric properties; non-asymptotic conditional expectations and variances are estimated. The best single predictor of S is N, of T is H, and of the scaled peak (S divided by the area under the width function) is H. Finally, expressions tested on a set of drainage basins from the state of Wyoming perform reasonably well in predicting S and T despite probable violations of the original assumptions. ?? 1989 Springer-Verlag.

Stochastic Hydrology and Hydraulics

Basin-scale relations via conditioning

A rainfall-runoff model is used in conjunction with a probabilistic description of the input to this model to obtain simple regression-like relations for basin runoff in terms of basin and storm characteristics. These relations, similar to those sought in regionalization studies, are computed by evaluating the conditional distribution of model output given basin and storm characteristics. This method of conditioning provides a general way of examining model sensitivity to various components of model input. The resulting relations may be expected to resemble corresponding relations obtained by regionalization using actual runoff to the extent that the rainfall-runoff model and the model input specification are physically realistic. The probabilistic description of model input is an extension of so-called "random-model" of channel networks and involves postulating an ensemble of basins and associated probability distributions that mimic the variability of basin characteristics seen in nature. Application is made to small basins in the State of Wyoming. Parameters of the input variable distribution are estimated using data from Wyoming, and basin-scale relations are estimated both, parametrically and nonparametrically using model-generated runoff from simulated basins. Resulting basin-scale relations involving annual flood quantiles are in reasonable agreement with those presented in a previous regionalization study, but error estimates are smaller than those in the previous study, an artifact of the simplicity of the rainfall-runoff model used in this paper. We also obtain relations for peak of the instantaneous unit hydrograph which agree fairly well with theoretical relations given in the literature. Finally, we explore the issues of sensitivity of basin-scale, relations and error estimates to parameterization of the model input probability distribution and of how this sensitivity is related to making inferences about a particular ungaged basin. ?? 1989 Springer-Verlag.

Stochastic Hydrology and Hydraulics

Regression models for estimating urban storm-runoff quality and quantity in the United States

Urban planners and managers need information about the local quantity of precipitation and the quality and quantity of storm runoff if they are to plan adequately for the effects of storm runoff from urban areas. As result of this need, linear regression models were developed for the estimation of storm-runoff loads and volumes from physical, land-use, and climatic characteristics of urban watersheds throughout the United States. Three statistically different regions were delineated, based on mean annual rainfall, to improve linear regression models. One use of these models is to estimate storm-runoff loads and volumes are gaged and ungaged urban watersheds. The most significant explanatory variables in all linear regression models were total storm rainfall and total contributing drainage area. Impervious area, land-use, and mean annual climatic characteristics were also significant explanatory variables in some linear regression models. Models for dissolved solids, total nitrogen, and total ammonia plus organic nitrogen as nitrogen were the most accurate models for most areas, whereas models for suspended solids were the least accurate. The most accurate models were those for the more arid western United States, and the least accurate were those for areas that had large quantities of mean annual rainfall.

Journal of Hydrology

Asymptotic Rayleigh instantaneous unit hydrograph

The instantaneous unit hydrograph for a channel network under general linear routing and conditioned on the network magnitude, N, tends asymptotically, as N grows large, to a Rayleigh probability density function. This behavior is identical to that of the width function of the network, and is proven under the assumption that the network link configuration is topologically random and the link hydraulic and geometric properties are independent and identically distributed random variables. The asymptotic distribution depends only on a scale factor, {Mathematical expression}, where ?? is a mean link wave travel time. ?? 1988 Springer-Verlag.

Stochastic Hydrology and Hydraulics

Precipitation-runoff modeling system; user's manual

The concepts, structure, theoretical development, and data requirements of the precipitation-runoff modeling system (PRMS) are described. The precipitation-runoff modeling system is a modular-design, deterministic, distributed-parameter modeling system developed to evaluate the impacts of various combinations of precipitation, climate, and land use on streamflow, sediment yields, and general basin hydrology. Basin response to normal and extreme rainfall and snowmelt can be simulated to evaluate changes in water balance relationships, flow regimes, flood peaks and volumes, soil-water relationships, sediment yields, and groundwater recharge. Parameter-optimization and sensitivity analysis capabilites are provided to fit selected model parameters and evaluate their individual and joint effects on model output. The modular design provides a flexible framework for continued model system enhancement and hydrologic modeling research and development. (Author 's abstract)

Water-Resources Investigations Report