Journal of Hydrologic Engineering

A set of different methodologies are developed for multiple objective management of coastal aquifers. The coastal aquifer management models are developed using a numerical simulation model, meta-model, and the multiple objective optimization algorithm NSGA-II. The NSGA-II algorithm is also modified to accommodate initial solution generation using the Latin hypercube sampling for uniform sampling in bound space. These initial solutions are useful to improve the efficiency of the optimization algorithm. One important issue in developing management models for coastal aquifers incorporating the density dependent flow and transport processes is the computational feasibility. A few variations of the management model are also evaluated to test the potential for improving the computational efficiency. The variations in the formulation of management models include: direct linking of numerical simulation model, introducing meta-models [in this study artificial neural network (ANN)] in place of original numerical simulation model, using partially trained meta-model as a screening model for specifying initial solutions for the numerical simulation model linked optimization model. The developed models are capable of obtaining the nondominated front of the multiobjective management model without solving the modified single objective model iteratively. Also, the meta-model approach is shown to be computationally efficient in generating the nondominated front, especially when a partially trained (ANN-based) meta-model is used as an initial screening model for the nondominated front search process. These developed methodologies are tested for an illustrative coastal aquifer study area. The performance evaluations show potential applicability of developed methodologies for multiobjective management of saltwater intrusion in coastal aquifers.

Management of saltwater intrusion in coastal aquifers should be based on robust management strategies and monitoring of their impacts. A robust optimal management strategy is less sensitive to deviations from prescribed strategies at the field level. Development of robust management framework is an important issue that needs attention especially when it results in near optimal strategies even when deviations from prescribed strategies occur in the field implementation stage. Implementation of a strategy requires field scale monitoring to determine the impact in terms of compliance with management goals due to possible deviation from an optimal prescribed strategy. Design of such an optimal monitoring network for compliance also requires robust optimal design due to the uncertainties involved. Deviations from prescribed strategies in the field are often more sensitive to uncertainties in the implementation phase. A multiple objective management model for robust optimal management of saltwater intrusion in coastal aquifers is proposed. Both risk neutral and risk-based management model formulations are presented. A robust monitoring network design methodology is also proposed for compliance monitoring of proposed robust management strategies. Performances of the developed methodology are tested for an illustrative coastal aquifer study area, as presented by Dhar and Datta. Performance evaluations show potential applicability of the developed methodologies and some of the relative advantages.

The rational method for determining peak flood discharges has been used for the design of hydraulic structures for decades. Despite the popularity of the method, little attention has been paid to improving guidance for selection of the runoff coefficient. This study determined rational runoff coefficients (the rational $C$ ) for 72 gauged rural watersheds in Kansas ranging in size from 0.45 to $76.6{\text{km}}^2$ using a frequency-based approach. The median rational $C$ values for Kansas ranged from 0.17 for the 2-year recurrence interval in western Kansas up to 0.97 for the 100-year recurrence interval in eastern Kansas. This paper investigates the spatial variation in runoff coefficients and documents the dependence of the rational $C$ on recurrence interval. The rational $C$ values determined in this study do not exhibit dependence on drainage area, indicating that the method is acceptable for use on much larger basins than is typically assumed.

Investigation is provided concerning the variable behavior of specific yield $\left(S_Y\right)$ under shallow water table conditions ( $<2\text{m}$ below land surface). Traditionally, specific yield has been defined as the water released from pumping of a phreatic aquifer down by a unit head. It is often used as a fixed value in groundwater flow models. This study seeks to elucidate $S_Y$ variability due to natural processes of evapotranspiration (ET) and recharge. $S_Y$ variability is of fundamental importance for modeling hydrologic response from stresses and for determination of water budget of a catchment. HYDRUS 1D—a numerical model solving Richard’s equation for saturated—unsaturated flow in one dimension is used to simulate the behavior of specific yield for a soil type representative of west central Florida. It was found, that for various cases examined (e.g., ET and infiltration), the magnitude of specific yield varied with depth to water table. For infiltration response, the variation in the specific yield exhibited strong dependence on the interevent time. For ET stress, the specific yield first increased rapidly to attain a maximum value and then declined steadily to ultimately become less than specific yield at equilibrium moisture conditions. The study indicated that assumptions of constant specific yield for different stresses can yield erroneous results especially in shallow water table environments. For deeper water table it was found that variation was not that pronounced and a constant value of specific yield can be used as an approximate value for simulating water table fluctuations.

The Muskingum flow routing method has been successfully used in many hydrologic applications due to its simplicity in concept and calculation. This paper presents a bidirectional Muskingum water-stage routing model (BDMWSRM) for water-stage forecasting in a tidal river with consideration of flood and tidal influences. The BDMWSRM separates the hydrologic processes of the tidal river into upper reach flood and downstream tidal waves, respectively. Muskingum water-stage routing method was first used to calculate the propagation of the flood and tidal waves; for the case of multitributary upper reaches, a first routing-second combining approach is used and then routed streamflows are summed up by using different weight factors for two water-stages based on the water-stage threshold. All the parameters used in the model can be adjusted automatically or determined manually. The BDMWSRM was applied in the Jiaojiang River, China for evaluating the tidal effect on the streamflow in this study. The simulated streamflows at the basin outlet capture the seasonal trends which compare realistically well with the observed in both temporal variation and intensities. The results indicate that the BDMWSRM can be applied successfully with high accuracy and reliability on the water-stage forecasting in a tidal river and fewer parameters may be required for model calibration, displaying the relative advantage of the model.

The understanding of the model capabilities and inherent uncertainties is vital in river flood prediction systems. This paper addresses the need by considering two conventional models: hydrodynamic (HD) model and Muskingum-Cunge (MC) hydrologic routing model, and two data-driven models: artificial neural network and adaptive network based fuzzy inference system. A major source of uncertainty in all of these models is in input discharge due to the stage-discharge relationship. The study considers the uncertainty by defining fuzzy uncertainty bounds of relationship, which is used for propagation of uncertainties in each of these models. This approach is applied to the Rhine-Neckar river confluence in Germany. The results of the study indicate that all four models are capable of producing good results. While the statistical performance of the MC routing model and two data-driven models are slightly better than the HD model, the HD model is more robust in handling uncertainties. The study therefore suggests that it is important to consider both the performance and uncertainties in these models and it is more appropriate to use more than one model for river flood prediction.

Using flow equations for overflow region and force balance for vegetation region, a vertical two-dimensional incompressible combined flow field of waves, current, and submerged vegetation is mathematically formulated. Stream functions for these regions are separately derived using appropriate boundary conditions and extended for weak damping of waves in the direction of propagation. Both stream functions are coupled using the interface boundary condition to derive a mathematical model for the combined wave-current-vegetation flow field that provides insights into the combined flow structure for no-damping and damping cases. The internal wave at the interface (vegetation top) is also derived and found to be in phase with the surface wave. The dispersion relations explicit in wave frequency are derived for the following/opposing wave-current environment. The model is extended for the emergent vegetation case with wave damping. The proposed model is compatible and covers a wide range of hydrodynamic characteristics of wetland flows.

Standard methods for determining pollutant loads in streams typically require the collection of separate instantaneous measurements of water velocities and solute concentrations at discrete points in space and time. A recently developed device, the passive surface water flux meter (PSFM), has been introduced as an alternate method for the measurement of time-integrated surface water flux (velocity) and solute mass flux. This paper extends PSFM development by evaluating and comparing two PSFM designs in laboratory flumes, as well as reporting on initial steady-state field testing. The shape of the PSFM body determines the velocity with which water passes through the device, and different designs may thus be preferred for different applications. Experiments compared the accuracy of flux measurement by the previously introduced hydrofoil-shaped PSFM and nitrate-sorbing cartridge with that of a newly designed cylindrical-shaped PSFM and phosphate-sorbing cartridges. Testing was performed in a laboratory flume at steady water velocities between 0.2–0.58 m/s and results verified the ability of the new PSFM designs to accurately measure solute and water flux under steady-state conditions. Water fluxes were measured to be within 4 and 7% of true water fluxes for the hydrofoil PSFM and cylindrical PSFM, respectively. The accuracy of solute flux estimates was similar to those found in the water flux experiments. While both PSFM designs exhibited similar accuracy, the cylindrical-shaped PSFM with phosphate-sorbing cartridges was chosen for field testing because of the relative ease of construction compared to the hydrofoil-shaped device. Field experiments performed under natural steady-flow stream velocities in Sweetwater Branch, Gainesville, Florida indicated that in relatively stable field conditions, the cylindrical PSFM was able to accurately measure water and phosphate mass fluxes to within 3 and 7% of true fluxes, respectively.

A new method of calibration of the Australian Water Balance Model (AWBM) daily rainfall-runoff model allows for errors in the estimation of areal rainfall over the catchment. The result of applying the method to a group of gauged catchments is the production of a single set of parameter values for the AWBM that can be used with any catchment in the group or used to estimate runoff on ungauged catchments in the same locality. The method is demonstrated on 121 catchments, comprising groups in five States of Australia from the tropics to temperate zones and over a wide range of catchment sizes and runoff characteristics. With adjustments to input rainfall of less than 20%, the average annual runoff from any catchment in a group can be reproduced by a single set of parameter values to any required degree of precision. The ability of a single set of parameter values to estimate average annual runoff from a group of catchments with only small adjustments of input rainfall raises doubts about the ability to determine the effects of catchment characteristics on runoff with current rainfall-runoff data sets.

Analytical solutions for forced well recharge currently in use were initially developed for pumping scenarios and applied for recharge cases assuming that radial flow in the recharge well replicates a mirror image of that in to a pumping well. Moreover these solutions were not extended to multiaquifer systems. Well bore numerical solutions were generally not considering the effect of well bore interaction, which has a significant effect in the case of a recharge well. In the present paper, improved analytical solutions are developed for a well fully penetrating either single or multiaquifers in respect to of well storage, well loss, and interactions between the individual aquifers through well bore. The solution developed for constant and variable rates of injection and well loss is applied to the experimental data of the Hansol well injection project near the city of Ahmedabad in the Gujarat state in India. The paper also discusses the difference in well hydraulics of recharge and recovery wells.

Flood events consist of flood peaks and flood volumes for various durations that are mutually correlated and need to be described by multiple variables. Conventional flood frequency analysis methods are generally based on the univariate distributions of either flood peaks or flood volumes, and hence only provide a limited assessment of flood events. In this paper, a multicharacteristic synthesis index (MSI) method is developed to describe flood hydrographs in an integrated way by considering the multiple characteristics synthetically, such as flood peak, 1-day maximum flood volume, 3-day maximum flood volume, 7-day maximum flood volume, etc. Annual maximum flood hydrograph series are sampled and then are transformed into corresponding MSI series by the MSI method. The quantile of the MSI series corresponding to a specified design return period is estimated by conventional flood frequency analysis method. A procedure for derivation of design flood hydrograph based on the MSI quantile is proposed. An application at the Geheyan reservoir in China is given. Results show that the MSI method can provide a new way for derivation and reassessment of design flood hydrographs.

The least tern and piping plover are threatened and endangered species that are indigenous to at least part of the natural Missouri River. However, would the river’s natural hydrograph near Sioux City, Iowa, including the spring rise, have historically been harmful to the birds? Three methods of hydrograph analysis, which were based on 1938–1939 stream-flow measurements at the Sioux City gauge site and based on new information of the time needed for mating, nesting, and rearing of the birds, were made. The results of the analyses are consistent with historical biologic observations of June rise flooding and suggest that the natural hydrograph of the Missouri River near Sioux City was not “friendly” to the two bird species as the hydrograph likely did not result in long-term recruitment.

Modeling of hydrologic processes using multiphysics modeling packages shows significant promise in a number of applications. However, these packages have not yet developed a complete set of implementations for boundary conditions important in hydrologic modeling. Three such boundary conditions—rainfall infiltration, seepage faces, and evapotranspiration fluxes—are implemented using the generic boundary condition and internal sink routines provided in one multiphysics package, COMSOL multiphysics. Comparison with results from previous simulations using dedicated hydrologic models demonstrates that with care and creativity these boundary conditions can be implemented accurately and efficiently. Boundary condition implementation should not limit the applicability of multiphysics models to a broad set of problems of interest to the hydrologic community.

Poisson rectangular pulses (PRPs) model describes the probabilistic nature of the average intensity and duration of storms. However, no consideration is given to the peak intensity or the relative position of the peak intensity of the storm. PRP model simplifies the procedure, and makes it attractive to hydrologists; however it can often produce inconsistencies and significant bias in flood estimates, which can lead to the under- or overdesign of engineering structures. This article proposes a model that overcomes the limitations of PRP model by treating the three storm rainfall components (i.e., storm duration, intensity, and the relative position of the peak intensity) as random variables. Their marginal distributions are modeled by using a heavy tailed law, namely, a generalized Pareto as well as Gumbel distributions. The statistical dependence between these three random variables is then modeled using 2-copulas. Finally, the model proposed in this article is applied to the predesign of a detention basin in the city of Granada (Spain).

Using a Freundlich adsorption isotherm for bromide $\left({\text{Br}}^{-}\right)$ published earlier, we used two-dimensional groundwater simulations to compare the dispersion of a conservative tracer to ${\text{Br}}^{-}$ undergoing mildly nonlinear adsorption ( $\text{exponent}=0.893$ ; $\text{coefficient}=0.0412$ ). Variances of the natural logarithm of hydraulic conductivity fields were varied over an order of magnitude to simulate mildly and strongly heterogeneous flow fields. To estimate the apparent accuracies of longitudinal $\left(A_L\right)$ and horizontal transverse $\left(A_T\right)$ dispersivities measured using conservative tracers in field experiments, we considered two operationally defined decisions: the amount of ${\text{Br}}^{-}$ injected (1.0 and 0.1 kg) and the lowest tracer concentration value used in dispersivity computations as a result of analytical quantification limits or background concentrations (0.1 ppm). Results from both operational criteria were compared using hypothesis testing. $A_L$ values for the conservative simulations in mild heterogeneity were within a factor of 2, as were $A_T$ values at confidence levels $>95\%$ . $A_L$ values for the conservative simulations in strong heterogeneity were within a factor of 2 at confidence levels $>90\%$ ; similarly for $A_T$ values the confidence levels were $>80\%$ . These results support the convention that the most reliable macrodispersivity values are accurate within a factor of 2. Comparisons of dispersivities calculated from the reactive runs to those of the conservative simulations for the same travel distance, all other parameters being the same and only using concentrations $>0.1\text{ppm}$ , yielded identical confidence levels for the respective dispersivities as the conservative runs reported above. This conclusion was true for both masses of the tracer considered. A practical result of this research is that we cannot exclude the use of a mildly sorbed tracer, as modeled herein, in making dispersivity measurements as accurate as those of a conservative tracer.

Artificial neural networks (ANN) have experienced a major breakthrough in civil engineering topics throughout the past 15 years, especially in the hydroinformatics field. Fewer attempts have been made to unveil any feasible physical meaning behind the ANN and their probable application for solving day to day engineering problems. This work explores the possibility of linking the weights of simple multilayer perceptrons with some physical characteristics of watersheds, by means of statistical regressions. The procedure is applied to the forecast of monthly streamflows in the central region of Colombia. Nineteen watersheds were delimited within the zone of study, using geographic information system software. Obtained results allow to foresee that watersheds characteristics such as area, length, and slope of the main stream could be connected with the ANN weights. Better results are expected when daily records and other variables such as rain, evaporation, etc. be included.