Journal of Hydrologic Engineering

Numerical and experimental solutions to steady infiltration from a strip basin to a groundwater table of infinite horizontal extent are presented. Because of the unknown location of the phreatic surface, the flow domain is transformed into the complex potential plane using the inverse formulation method where the phreatic surfaces with and without recharge become straight lines. The method of finite differences was used to solve the boundary value problem in the transformed plane. The problem was also investigated experimentally using a sand tank model. For comparison purposes, a one-dimensional analytical solution is also presented. The results were compared with each other. The parameters affecting the seepage rate are investigated and the resulting relationships were presented in dimensionless graphs. It is believed that these graphs may be of use in design problems. The conditions for which the simplified one-dimensional analytical solution agrees well with the results of the sophisticated two-dimensional numerical solution are identified. The shape of the water table in response to recharge depends on the size of the recharging area, the hydraulic and geometric properties of the aquifer, and the recharge rate.

A liquid analog model (LAM) is presented as a new hydrological laboratory device for rainfall–runoff modeling. The model is applied to simulate Nash’s model in the laboratory for real rainfall–runoff data. Due to its simple structure and ease of operation, LAM can be an effective educational tool for rainfall–runoff modeling. It seems that LAM can also be used for simulating other flow processes in the laboratory.

Intense rainfall over coastal areas characterized by significant urban development, predominantly clay soils, and flat slopes can cause significant flooding problems. Extreme floods in coastal areas occur when storm-water systems lose capacity due to high levels in receiving streams. The Texas Medical Center is located near downtown in Houston, Texas, and extensive flooding during Tropical Storm Allison in June of 2001 crippled many of the facilities with approximately $1.5 billion in damages. In order to better understand dynamic responses and to design abatements to the existing infrastructure, the performance of the storm-water pipe systems under extreme receiving water conditions in a highly urbanized area was quantified by using an integrated model. A hydrologic/hydraulic model was created based on the storm water management model with NEXRAD radar rainfall and hydrographs generated from Hydrologic Engineering Center’s hydrologic modeling system. The model was accurately calibrated against historic storm events. The simulated double-peaked hydrographs explained that the significant backwater effects in Harris Gully worsened the flooding situation within streets by limiting storm-water outflow and overland flow. The analysis evaluated the existing storm-water system to identify potential pathways for overland flow and pipe flow to the receiving bayou, and proposed mitigation alternatives by incorporating additional major sewers to bypass the main culverts in the Harris Gully area in order to provide significant flood relief.

The riparian vegetation zone plays an important role in river ecosystems, flow resistance, water velocity distribution, and water level variation. In this paper, the impacts of riparian reed zones on river flow and water level were studied by comparing measurements in river reaches with or without riparian reed zones in the Chaodongweigang River of Taihu Lake Basin, China. The effects of the density, stem diameter, and rigidity of reeds on flow regime, water velocity, and water level were investigated. Subsequently, flow resistance on the river’s longitudinal water level caused by the riparian reed zone was studied. The results showed three water velocity zones in the river reach where there were riparian reeds, including the slack water zone, the transition zone of flow velocity, and the river’s main flow zone. The water velocities in the three zones were related to reed density, diameter, and rigidity. The water-surface slope in the river reach with a riparian reed zone was larger than that without a reed zone. It showed that the riparian reed zone influenced the river flood discharge to some degree and resulted in increased water level upstream. Additionally, the water level of the river cross section exhibited a concave shape that the water level was higher in the riparian reed zone than in the center of river midstream, section with a riparian reed zone exhibited a concave shape; the water level was higher in the riparian reed zone than in midstream, and the water level difference was influenced mainly by the reed density.

The flow and transport processes in a coastal aquifer are highly nonlinear, where both the flow and transport processes become density dependent. Therefore, numerical simulation of the saltwater intrusion process in such an aquifer is complex and time consuming. An approximate simulation of those complex flow and transport processes may be very useful, if sufficiently accurate, especially where repetitive simulations of these processes are necessary. A simulation methodology using a trained artificial neural network model (ANN) is developed to approximate the three-dimensional density dependent flow and transport processes in a coastal aquifer. The data required for initially training the ANN model is generated by using a numerical simulation model (FEMWATER). The simulated data consisting of corresponding sets of input and output patterns are used to train a multilayer perceptron using the back-propagation algorithm. The trained ANN predicts the concentration at specified observation locations at different times. The performance of the ANN as a simulator of the density dependent saltwater intrusion process in a coastal aquifer is evaluated using an illustrative study area. These evaluation results show that the ANN technique can be successfully used for approximating the three-dimensional flow and transport processes in coastal aquifers.

The current methodology recommended for flood-frequency analyses by U.S. Federal agencies is presented in Bulletin 17B. Bulletin 17 was first published in 1976, minor corrections were made in 1977 resulting in Bulletin 17A, which was later succeeded by Bulletin 17B published in 1982. Bulletin 17B sought to resolve ambiguities in the recommended procedures, including the treatment of low outliers, and the use of both regional skew and historical flood information. As the 25th anniversary of the publication of Bulletin 17B approaches, this paper provides a discussion and evaluation of the procedures that document recommends. The fields of hydrology and flood frequency analysis have substantially evolved since Bulletin 17 was first published. New techniques are now available which should become part of these standard procedures. A comparison is provided which demonstrates how the standard and weighted Bulletin 17B quantile estimators perform relative to alternative LP3 quantile estimators that also make use of regional information.

For the Great Lakes region, radar-based precipitation estimates provide valuable data for over-lake areas and may help to improve mean areal precipitation estimates over land areas, particularly where precipitation gauges are sparse. To this end, potential biases in daily radar-based precipitation data are evaluated for several Great Lakes watersheds. Statistical analysis of gauge data (MAP) and radar-based data (MAPX) for the period 1996–2004 shows that, except for some summer months, MAPX values were consistently lower than MAP values. Possible reasons for this underestimation include truncation error, beam blockage and overshoot, and variability in radar reflectivity-surface precipitation relationships. Application of the precipitation data to continuous simulation and forecasting models of the Great Lakes shows that the observed biases are generally magnified by the hydrology models, i.e., even larger discrepancies are observed between simulated runoff values generated with MAP and MAPX inputs. Discrepancies in observed runoff and simulated runoff with MAPX inputs are deemed unacceptable for hydrologic prediction, and procedures for adjusting the MAPX data are developed and verified.

The two-dimensional linear and nonlinear stochastic groundwater flow equations in an unconfined heterogeneous aquifer with Dupuit assumptions and mixed boundary conditions is solved using analytical decomposition, which does not require perturbation, linearization, discretization, or knowledge of a particular probability distribution. New simple analytical expressions for the mean of the hydraulic head and its variance distribution are given for two common sets of field boundary conditions and recharge. This procedure allows the calculation of the head mean and error bounds in practical situations when only a limited sample allows the estimation of the mean and correlation structure of the transmissivity or the hydraulic conductivity. The results indicate that the head statistics are not only dependent on the transmissivity or the conductivity statistics (i.e., mean, variance parameter, and correlation structure), but also on the magnitude and type of boundary conditions, recharge, and other hydrogeological parameters. The new methodology offers a procedure to calculate the second-order statistics of the hydraulic head when stochasticity in the hydraulic conductivity, nonlinearity in the differential equation, recharge from rainfall, and mixed boundary conditions are all considered.

The climate change and variability phenomenon, because of its potential to exert significant influences on the hydrologic cycle, the economy, and human society as a whole, has drawn considerable attention from the scientific community and government agencies worldwide. In response to growing concerns, we are attempting to expand our understanding of the relationship between land-use heterogeneities, water availability, and climate change/variability in the southeastern United States. Specifically, this paper describes the coupling and validation of a hydrologic-forest productivity model (PnET-II3SL) with a hydrologic-agricultural productivity model to represent the hydrologic response characteristics of large spatial areas. The resulting code is capable of generating scientifically sound predictions of the effects of future climatic conditions, with regards to water availability, in the heterogeneous watersheds of the southeast. Validation efforts are described, utilizing long-term historical records, for 12 experimental watersheds. Selected sites represent a diversity of climatic regimes, topographic conditions, soil types, area, and vegetal species.

The probable maximum precipitation (PMP), an estimate of the upper limit to storm rainfall, is determined using a catalog of extreme rainstorms. The effect of a recent extreme rainstorm—the northeastern Illinois storm of July 17–18, 1996—on PMP estimates for the Chicago area, is evaluated using standard PMP moisture maximization procedures. The results show that although the storm is a record rainfall event, its maximized precipitation is still below the PMP estimates for the Chicago area. Instead, a storm that occurred in Oklahoma, or perhaps another in Iowa, established the 24-h, 26- ${\mathrm{km}}^2$ (10- ${\mathrm{mi}}^2$ ) PMP estimate for Chicago. In either case, the higher maximized precipitation can be attributed to the combination of a larger storm rainfall amount, and a larger in-place moisture maximization factor. The case study also illustrates potential limitations with using standard PMP procedures. For instance, it is difficult to obtain an objective index to represent the mean moisture availability for this storm, since it has multiple rain periods. In addition, the estimated precipitable water based on standard PMP assumptions is much greater than that observed with upper-air soundings. Finally, for the same storm to occur under climatological maximum moisture conditions, a fundamental assumption in moisture maximization, dew points in the atmospheric profile would need to be increased beyond the observed air temperatures for the storm, a situation that is physically impossible.

A real-time flood forecast algorithm was developed using a distributed hydrologic model together with recursive state variables updating to utilize online hydrologic information. The Kalman filter was applied to the distributed model using Monte Carlo simulation methods and several other techniques. The Monte Carlo simulation methods permit the algorithm to successfully project forward the state variables and their error covariance through the nonlinear hydrologic system. A huge computation burden would arise if the filter were applied to update the very large number of distributed state variables at the same time; this was avoided by assuming spatial similarity for the distributed state variables. Applying a factor, calculated from the total amount of the model internal variables, to the distributed state variables provided computational efficiency in the update algorithm. The distributed hydrologic model coupled with the Kalman filter algorithm offers improved simulation results with encouraging forecast accuracy.