Evaluation of rainfall-runoff performance using the stochastic integral equation method

The stochastic integral equation method (S.I.E.M.) is used to evaluate the relative performance of a set of both calibrated and uncalibrated rainfall-runoff models with respect to prediction errors. The S.I.E.M. is also used to estimate confidence (prediction) interval values of a runoff criterion variable, given a prescribed rainfall-runoff model, and a similarity measure used to condition the storms that are utilized for model calibration purposes.Because of the increasing attention given to the issue of uncertainty in rainfall-runoff modeling estimates, the S.I.E.M. provides a promising tool for the hydrologist to consider in both research and design.     

Generous statistical tests

A common statistical problem is deciding which of two possible sources, A and B, of a contaminant is most likely the actual source. The situation considered here, based on an actual problem of polychlorinated biphenyl contamination discussed below, is one in which the data strongly supports the hypothesis that source A is responsible. The problem approach here is twofold: One, accurately estimating this extreme probability. Two, since the statistics involved will be used in a legal setting, estimating the extreme probability in such a way as to be as generous as is possible toward the defendant’s claim that the other site B could be responsible; thereby leaving little room for argument when this assertion is shown to be highly unlikely. The statistical testing for this problem is modeled by random variables {X _i } and the corresponding sample mean the problem considered is providing a bound ɛ for which for a given number a ₀. Under the hypothesis that the random variables {X _i } satisfy E(X _i ) ≤ μ, for some 0  < μ < 1, statistical tests are given, described as “generous”, because ɛ is maximized. The intent is to be able to reject the hypothesis that a ₀ is a value of the sample mean while eliminating any possible objections to the model distributions chosen for the {X _i } by choosing those distributions which maximize the value of ɛ for the test used.     

A two-dimensional dam-break flood plain model

A simple two-dimensional dam-break model is developed for flood plain study purposes. Both a finite difference grid and an irregular triangle element integrated finite difference formulation are presented. The governing flow equations are approximately solved as a diffusion model coupled to the equation of continuity. Application of the model to a hypothetical dam-break study indicates that the approach can be used to predict a two-dimensional dam-break flood plain over a broad, flat plain more accurately than a one-dimensional model, especially when the flow can break-out of the main channel and then return to the channel at other downstream reaches.     

Technical note: Estimating water shed S-graphs using a diffusion flow model

A simplification of the two-dimensional (2-D) continuity and momentum equations is the diffusion equation. This simpler dynamic model of two-dimensional hydraulics affords the hydrologist a means to quickly estimate floodflow effects for overland flow. To investigate its capability, a numerical model using the diffusion approach is applied to a set of hypothetical watersheds in order to develop unit hydrographs. The model is based on an explicit, integrated finite-difference scheme, and the floodplain is simulated by use of topographic elevation and geometric data. Synthetic unit hydrographs (S-graphs) developed from use of the simple 2-D model show interesting correlations to the well-known S.C.S. unit hydrograph (S-graph).     

A simple model of a phreatic surface through an earth dam

A simple numerical model for estimating a phreatic surface in an earthen dam is presented. The numerical approach is based upon the Complex Variable Boundary Element Method (CVBEM). By expanding the CVBEM approximation geometric functions into a first order Taylor series, the unknown phreatic surface location geometrics can be approximated without iteration by solving a single matrix system. The developed technique provides for the numerical solution of the inverse problem of locating the phreatic surface coordinates. A comparison of results produced from this simple approach to results produced from a finite element analog and an iterative CVBEM analog for an example problem is presented.     

Chowdhury and Stedinger's approximate confidence intervals for design floods for a single site

A basic problem in hydrology is computing confidence levels for the value of the T-year flood when it is obtained from a Log Pearson III distribution in terms of estimated mean, estimated standard deviation, and estimated skew. In an important paper Chowdhury and Stedinger [1991] suggest a possible formula for approximate confidence levels, involving two functions previously used by Stedinger [1983] and a third function, λ, for which asymptotic estimates are given. This formula is tested [Chowdhury and Stedinger, 1991] by means of simulations, but these simulations assume a distribution for the sample skew which is not, for a single site, the distribution which the sample skew is forced to have by the basic hypothesis which underlies all of the analysis, namely that the maximum discharges have a Log Pearson III distribution. Here we test these approximate formulas for the case of data from a single site by means of simulations in which the sample skew has the distribution which arises when sampling from a Log Pearson III distribution. The formulas are found to be accurate for zero skew but increasingly inaccurate for larger common values of skew. Work in progress indicates that a better choice of λ can improve the accuracy of the formula.