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Geology topics

M.R. Karlinger

Publications and source records attributed to M.R. Karlinger.

At least 19 recordsLinked to original sources
USGS2024

Chemistry of illite/smectite and end-member illite

Chemical data from three different series of diagenetic illite/smectites (I/S), analyzed statistically by two regresion techniques, indicate that the content of fixed-K per illite layer is not constant, but ranges from ∼0.55 per O 10 (OH) 2 for illite layers in randomly interstratified I/S (R=0; > 50% smectite layers) to ∼1.0 per O 10 (OH) 2 for illite layers formed in ordered I/S (R>0; <50% smectite layers). By extrapolation of the experimental data, the following chemical characteristics were obtained for end-member illite derived from the alteration of smectite in bentonite: average fixed-K per illite layer = 0.75 per O 10 (OH) 2 ; total charge = about −0.8; cation-exchange capacity = 15 meq/100 g; surface area (EGME) = 150 m 2 /g.

Clays and Clay Minerals↗
USGS2010

Economic basis of resource information systems: The case of streamflow network design

A general method for the economic design of natural resource information systems is presented for a certain class of natural phenomena. The system design is determined by the interaction of the technical input‐output relationship, i.e., the production function, the set of resource constraints, and an economic loss function defined in terms of parameter uncertainty. An application of the proposed method to streamflow network design is presented. Results of this analysis indicate that the method is fairly robust with respect to the assumptions. Observations are made which suggest extensions to flood measurement networks, long‐term precipitation networks, and seismic observation network design.

Water Resources Research↗
USGS2010

Worth of data and natural disaster insurance

The Federal Government in the past has provided medical and economic aid to victims of earthquakes and floods. However, regulating the use of hazard-prone areas would probably be more efficient. One way to implement such land use regulation is through the national flood and earthquake insurance program. Because insurance firms base their premium rates on available information, the benefits from additional data used to improve parameter estimates of the probability distribution (governing actual disaster events) can be computed by computing changes in the premiums as a function of additional data. An insurance firm is assumed to set rates so as to trade off penalties of overestimation and underestimation of expected damages. A Bayesian preposterior analysis is applied to determine the worth of additional data, as measured by changes in consumers’ surplus, by examining the effects of changes in premiums as a function of a longer hydrologic record.

Water Resources Research↗
USGS2010

Flood risks and the willingness to purchase flood insurance

Computer simulation experiments were conducted to determine the effects of alternative sources of uncertainty on the willingness to pay for flood insurance. Two alternative insurance protection schemes were investigated: coinsurance and fixed coverage. The question investigated here is to what extent does the insurance scheme influence how purchasers respond to flood risks? Floods were assumed to be log normally distributed and the effects on the purchase of insurance of uncertainties in the parameters of the distribution were explored using response surface analysis. Results indicate that fixed coverage insurance provisions shift most of the uncertainty in the physical parameters governing natural disaster occurrences away from the insuree and onto the insurer. The results also show that the form of the damage function has little effect on the demand for flood insurance.

Water Resources Research↗
USGS2008

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↗
USGS2007

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↗
USGS2007

Climate factor for small-basin flood frequency

A climate factor, CT, (T = 2-, 25-, and 100-year recurrence intervals) that delineates regional trends in small-basin flood frequency was derived using data from 71 long-term rainfall record sites. Values of CT at these sites were developed by a regression analysis that related rainfall-runoff model estimates of T-year floods to a sample set of 50 model calibrations. CT was regionalized via kriging to develop maps depicting its geographic variation for a large part of the United States east of the 105th meridian. Kriged estimates of CT and basin-runoff characteristics were used to compute regionalized T-year floods for 200 small drainage basins. Observed T-year flood estimates also were developed for these sites. Regionalized floods are shown to account for a large percentage of the variability in observed flood estimates with coefficients of determination ranging from 0.89 for 2-year floods to 0.82 for 100-year floods. The relative importance of the factors comprising regionalized flood estimates is evaluated in terms of scale (size of drainage area), basin-runoff characteristics (rainfall-runoff model parameters), and climate (CT).

Water Resources Bulletin↗
USGS1995

Spatial trends in Pearson Type III statistical parameters

Spatial trends in the statistical parameters (mean, standard deviation, and skewness coefficient) of a Pearson Type III distribution of the logarithms of annual flood peaks for small rural basins (less than 90 km2) are delineated using a climate factor CT, (T=2-, 25-, and 100-yr recurrence intervals), which quantifies the effects of long-term climatic data (rainfall and pan evaporation) on observed T-yr floods. Maps showing trends in average parameter values demonstrate the geographically varying influence of climate on the magnitude of Pearson Type III statistical parameters. The spatial trends in variability of the parameter values characterize the sensitivity of statistical parameters to the interaction of basin-runoff characteristics (hydrology) and climate. -from Authors

Journal of Hydraulic Engineering↗
USGS1989

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↗
USGS1989

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↗
USGS1988

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↗
USGS1985

Error bounds in cascading regressions

Cascading regressions is a technique for predicting a value of a dependent variable when no paired measurements exist to perform a standard regression analysis. Biases in coefficients of a cascaded-regression line as well as error variance of points about the line are functions of the correlation coefficient between dependent and independent variables. Although this correlation cannot be computed because of the lack of paired data, bounds can be placed on errors through the required properties of the correlation coefficient. The potential meansquared error of a cascaded-regression prediction can be large, as illustrated through an example using geomorphologic data.

Journal of the International Association for Mathe↗
USGS1982

Worth of geophysical data in natural- disaster- insurance rate setting.

Insurance firms that offer natural-disaster insurance base their rates on available information. The benefits from collecting additional data and incorporating this information to improve parameter estimates of probability distributions that are used to characterize natural-disaster events can be determined by computing changes in premiums as a function of additional data. Specifically, the worth of data can be measured by changes in consumer's surplus (the widely applied measure of benefits to consumers used in benefit-cost analysis) brought about when the premiums are adjusted. In this paper, a formal model of the process for setting insurance rates is hypothesized in which the insurance firm sets rates so as to trade off penalties of overestimation and underestimation of expected damages estimated from currently available hydrologic data. A Bayesian preposterior analysis is performed which permits the determination of the expected benefits of collecting additional geophysical data by examining the changes in expected premium rates as a function of the longer record before the data are actually collected. An estimate of the expected benefits associated with collecting more data for the representative consumer is computed using an assumed demand function for insurance. In addition, a sensitivity analysis of expected benefits to changes in insurance demand and firm rate-setting procedures is carried out. From these results, conclusions are drawn regarding aggregate benefits to all flood insurance purchasers.

Journal of Applied Meteorology and Climatology↗
USGS1982

Design of surface-water data networks for regional information

This report describes a technique, Network Analysis of Regional Information (NARI), and the existing computer procedures that have been developed for the specification of the regional information-cost relation for several statistical parameters of streamflow. The measure of information used is the true standard error of estimate of a regional logarithmic regression. The cost is a function of the number of stations at which hydrologic data are collected and the number of years for which the data are collected. The technique can be used to obtain either (1) a minimum cost network that will attain a prespecified accuracy and reliability or (2) a network that maximizes information given a set of budgetary and time constraints.

Water Supply Paper↗
USGS1981

Modification of the Tangborn short-term hydrometeorological model, with trial results from the Baker River basin, Washington

This report presents a modification of the short-term hydrometeorological model (Tangborn, 1978) for estimating river-basin snowmelt runoff. A multiple linear regression replaces a nonlinear regression scheme to correct for temperature effects of snowmelt runoff. Results based on data from the Baker River basin, Washington, indicate that model performance is improved by the modification in a majority of applications, and, additionally, use of the model is simplified and computer time is reduced.

Washington↗