Journal of Hydrologic Engineering

Forum papers are thought-provoking opinion pieces or essays founded in fact, sometimes containing speculation, on a civil engineering topic of general interest and relevance to the readership of the journal. The views expressed in this Forum article do not necessarily reflect the views of ASCE or the Editorial Board of the journal.

Porous media such as fractured rock and aggregated soils consist of two pore domains with distinct transport properties. A numerical code was developed to simulate solute concentrations in the two domains using a partitioned solution procedure to efficiently model transport in dual-permeability media. Furthermore, an approximate analytical solution was obtained that allows for different advective and dispersive terms in both flow domains, for a first-type or a third-type inlet condition. Solutions were obtained for local concentrations in both domains as well as effluent concentration and the concentration per medium volume. The problem was solved by decoupling the transport equations using diagonalization. This involves an error for the dispersivity matrix that is related to the difference in dispersivity of both domains. The correctness of the solution was assessed by comparison with numerical results. For low Damköhler numbers the solution was accurate even for a dispersivity ratio of 10. The need for a dual-dispersivity instead of a single-dispersivity model was illustrated with sample breakthrough curves and the solution was applied to optimize experimental breakthrough curves for an Andisol with a distinct intraaggregate and interaggregate porosity.

Improving river flow forecasts for longer lead times by incorporating numerical weather predictions (NWP) into streamflow forecasting systems has attracted hydrologists in recent years. The process turns considerably complex and resource hungry when ensembles of NWP forecasts instead of any single NWP output are used to feed the flow forecasting models in order to capture the uncertainties in hydrological forecasting. This paper presents, for the first time, a comparison of three statistical stratification techniques for simplifying the input precipitation ensemble forecasts driving a river flow forecasting system. A data-driven flow forecasting model developed for the Waikato River in New Zealand using genetic expression programming (GEP) was forced by the 10-days-ahead ensemble precipitation forecasts issued by three meteorological .centers in different parts of the world including the United Kingdom, Canada, and China. The three precipitation ensembles, comprising 51, 21, and 15 members respectively, were reduced to a smaller ensemble consisting of only 5 members by static, dynamic, and cluster stratification. The 10-days-ahead river flow forecasts resulting from the full and reduced precipitation ensembles were compared against the corresponding flows observed during the whole year 2012. The three stratification mechanisms vary in complexity, and two of them are novel in their application to streamflow forecasting. The forecasts were compared for four different attributes including accuracy, reliability, resolution skill, and the maximum flow limit, each targeting a different aspect of the forecast performance. The results indicate that, in general, the flow forecasts driven by all three smaller ensembles were comparable with their full counterpart for all three forecasting centers. The cluster-stratified approach outperformed all others for most of the tested forecast attributes. The performance of static-stratified ensembles was not too far from the cluster-stratified ensembles despite it being significantly simple compared to the latter. The dynamic-stratified ensembles were least in competing with the full ensembles except for the maximum flow limit.

In this study the generalized Darcy-Forchheimer model is used to characterize two-phase fluid flow where spatial flow characteristics may transition between Darcy and Forchheimer flow behavior. The local transition between the two flow regimes is characterized using the Forchheimer number as the criterion. A three-dimensional numerical model is developed that utilizes a control-volume method to simulate two-phase inertial, immiscible, and incompressible flow in a nondeformable homogeneous porous medium. The numerical model is validated by comparing its results with those obtained using a semianalytical solution of the Buckley-Leverett problem. The critical Forchheimer number is characterized using experimental data and is used to transition the local flow domain between Darcy and Forchheimer flow regions for both single-phase and multiphase analysis. The saturation-dependent distribution of the critical Forchheimer number is then used to analyze the Darcy and Forchheimer flow regions to provide a coupled solution to the problem. The proposed approach simulates injection of ${\mathrm{CO}}_2$ into saline aquifers. The simulation results show that local Forchheimer flow transition reveals critical conditions that need to be addressed in field applications. The findings are discussed in reference to deep saline injection of ${\mathrm{CO}}_2$.

The transport of reactive solutes can be influenced by transport-related and sorption-related nonequilibrium processes. The reactive contaminant transport model for fracture and the multiprocess nonequilibrium (MPNE) model for porous formation is considered. Two coupled transport equations, one for the porous formation and the other for the fracture, were solved numerically using a hybrid finite-volume method. The numerical model employs a globally second-order accurate explicit finite-volume method for the advective transport and a finite-difference method for the dispersive transport and coupled reaction terms. An attempt is made to investigate the effects of various MPNE model parameters on the concentration profile in the fracture. It was found that the higher values of mass transfer coefficient, sorption coefficient, matrix diffusion coefficient, fracture retardation coefficient, and matrix porosity in the advective and nonadvective regions of the porous matrix leads to a decrease in the solute concentration in the fracture. This numerical model might be useful in simulating the reactive transport through fractured porous media at field scale for both dispersion-dominated and advection-dominated transport.

Reservoir inflow forecasting plays an essential role in reservoir operation and management. Considering the characteristics of monthly inflow (trend, seasonality, and randomness throughout the hydrologic year), an additive model is proposed to forecast monthly reservoir inflow. Because different features are represented by different frequency bands of the time series, historical time series of the monthly inflow are decomposed by ensemble empirical mode decomposition into several intrinsic mode functions and a residue. According to frequency signatures analyzed by Fourier spectral representation, all intrinsic mode functions and residue are grouped into three terms: trend term, periodic term, and stochastic term. To accommodate the different characteristics of the three terms, an autoregressive model, a least-squares support vector machine, and an adaptive neuro-fuzzy inference system model are adopted for the three subforecasts, respectively. The additive model is subsequently used to integrate the three subforecasts representing different characteristics to achieve the final forecasting results. The proposed method is applied to the Three Gorges Reservoir in China, using data from January 2000 to December 2012. For comparison, the three terms’ models and two peer models—back-propagation neural network and autoregressive integrated moving average—are adopted for monthly inflow forecasting. Among all six approaches, the present additive model exhibits the best forecasting performance of mean absolute percentage error, 11.36%, normalized root-mean-square error, 0.15, and correlation coefficient 0.97.

A variety of computational techniques have been developed to efficiently and effectively draw realizations from the parameter space of watershed models for parameter estimation. However, to date, it has not been clearly understood how these techniques should be evaluated side by side. The main goal of this study is to develop and demonstrate a computational procedure for evaluating parameter sampling techniques. The analysis hinges on the evaluation of (1) efficiency in minimizing objective functions at the lowest required realizations; (2) effectiveness in drawing samples that adequately represent watershed characteristics based on automatic calibration results, and (3) effectiveness in enhancing the identifiability of the effective parameter space. The proposed procedure was applied to evaluate the performance of six commonly implemented sampling techniques for multisite, multiresponse parameter estimation of a river basin scale model in the Eagle Creek Watershed, Indiana, in the Midwestern United States. Results show that a particular technique surpassed all other methods in convergence speed and behavioral statistics. In addition, solutions derived using that technique were distributed closely in relatively small regions of the whole domain space, which enhanced the efficiency of the parameter search process.

The paper deals with the transient semi-analytical solution of linearized Boussinesq equations characterizing the development of groundwater mound in an unconfined two-dimensional heterogeneous aquifer under vertical recharge conditions. The finite aquifer consists of two rectangular basins surrounded by open water bodies and shares a common impermeable or permeable boundary at the mid plane. The governing equations are solved by applying the Laplace transform and finite Fourier sine transform techniques. Accordingly, analytical expressions for water heads for two rectangular basins are obtained for various scenarios. The applicability of the solutions has been illustrated with the help of a case study and numerical examples, considering various cases. The region wise development of the groundwater mound indicates that the effect of heterogeneity becomes significant for small time duration whereas for long time it becomes insignificant. This result can have application in land reclamation problems in the presence of localized recharge where the reclamation displaces the ground water divide and changes the groundwater conditions in the entire region.

The physics-based Gridded Surface Subsurface Hydrologic Analysis (GSSHA) model was developed by the U.S. Army Corps of Engineers for hydrologic, sediment transport, and water quality analyses. GSSHA simulates erosion and transport of sediments on the overland flow plain based on rainfall intensity and overland flow depth and velocity. The original sediment transport capabilities in GSSHA were taken from the GSSHA predecessor, CASC2D-SED. Independent testing of the sediment transport methods in CASC2D-SED by researchers identified several deficiencies in the formulation that caused significant overestimation of sediment yield during hydrologic events that were much larger than a calibration event. Sediment detachment limits and a variety of overland sediment transport equations were incorporated into the GSSHA model to address these deficiencies. This paper presents an evaluation of these modifications in terms of GSSHA sediment yield predictions of both single-event and summer growing season sediment yields. Simulation results are compared with research-quality sediment discharge data set from the USDA Goodwin Creek Experimental Watershed (GCEW). Results show that the reformulated GSSHA sediment transport model predicts event-total sediment discharge volume within ($\pm$) 50% over hydrologic events that vary by three orders of magnitude. The transport capacity method selected for use in the simulation had a large effect on the model results.

This paper investigates the hydrological scenarios of the Renaissance Dam being constructed on the Blue Nile in Ethiopia and the dam’s impact on the water balance downstream. Landsat 8 satellite images from 2013 were obtained and interpreted to identify locations for the Renaissance Dam and its saddle dam. Shuttle radar topography mission (SRTM) data were also obtained and processed to create a digital elevation model (DEM) for upstream areas. The DEM was analyzed to estimate water volumes that will fill the reservoir at various operational levels. The estimations were computed by filling the DEM to certain heights equivalent to the arbitrary barriers added to the original DEM at locations of the dams, and the stored volumes were computed from the resulting surface extent and spatially variable depths for the lakes. Different scenarios for dam height and resulting storage were proposed to estimate the resulting abstraction of the Blue Nile flows until completion of the project and the annual losses due to evaporation thereafter. The current site [506 m above sea level (asl)] for the Renaissance Dam allows the creation of a 100-m deep reservoir with a total storage of $17.5{\mathrm{km}}^3$; overflows will occur at the reservoir’s level (606 m asl) from its northwestern part into Rosaires downstream. Construction of the saddle dam to control the overflow area can allow the creation of a 180-m deep lake that stores up to $173{\mathrm{km}}^3$ in a lake that will cover $3{,130\mathrm{km}}^2$. The negative hydrological impacts of the Renaissance Dam will increase by creating the saddle dam because increasing the storage capacity can affect the strategic storage of the reservoirs in Egypt and Sudan. It is strongly recommended that an agreement be reached regarding the storage capacities and water supplies for all dams on the Nile to thoroughly satisfy all necessary demands.

Understanding the persistence in land surface processes, such as that in the deep subsurface moisture storage, has great implications for seasonal weather prediction over a drainage basin. The Canadian Prairies is a region of intense and recurrent drought outbreaks with myriad negative impacts on the regional ecosystem as well as on all sectors of the Prairies’ economy due to high mitigation costs associated with these frequent outbreaks. Given that there are neither physical observations of soil moisture at depths of hydrological importance nor measurements of the total water storage over drought-prone Canadian Prairies subcatchments, this places constraints on studies that focus on the assessments of the interrelationship between the land surface and atmospheric processes. This study focuses on the estimation of the memory in the simulated deep soil moisture and total water storages over the $\mathrm{406,000}{\mathrm{km}}^2$ Saskatchewan River Basin (SRB) in the Canadian Prairies using a physically based land surface model. The variable infiltration capacity (VIC) hydrological model was developed and deployed in simulating the deep soil moisture in conjunction with the total water storage over this large catchment. In developing a suitable hydrological model for the SRB, parameters estimated from the calibrated and validated hydrological model for the adjacent Upper Assiniboine River Basin (UARB) were transferred. Subsequently, the memory in the anomalies associated with the meteorological variables, simulated deep moisture and total water storage components in conjunction with the computed terrestrial storage deficit indices (TSDIs) estimated from the gravity recovery and climate experiment (GRACE) remote-sensing satellite system and the VIC model were assessed. Given the degree of agreement in the estimated memory associated with the hydrologic model-based terrestrial storage deficit indices with those estimated for the simulated deep moisture storage anomalies over this catchment, this study concludes that the latter could also be used in characterizing the severity of frequent Canadian Prairies droughts.

In urban areas, there is concern that storm water runoff and flooding may be intensified because of the effect of climate change on precipitation amounts, intensities, and frequencies. Studies are needed to help storm water managers to plan and design effective adaptation and mitigation measures. This paper presents a study of the effects of climate change on urban storm water runoff in the Bronx River watershed in New York City. To show the effects of climate change on future precipitation, projections by 134 general circulation models (GCMs) from the fifth phase of the coupled model intercomparison project (CMIP5) are used. A new change factor method is proposed to select minimum, maximum, and mean daily precipitation scenarios for a future time period of 2030–2059. Because of the importance of short duration for extreme storm events, the daily precipitation is disaggregated to hourly increments. The U.S. Environmental Protection Agency storm water management model (SWMM) is used to model the hydrologic response and is driven by 30 years of the produced hourly precipitation corresponding to the three climate change scenarios. The simulated runoff results showed increase in volume and peak discharge. Considering the climate scenarios for future planning purposes, frequency analysis is performed on the projected runoff which shows a considerable increase in the frequency of occurrence of extreme storm events and their peak values. To further analyze the runoff response at the subwatershed level, a storm water climate sensitivity factor (SCSF) is proposed. This sensitivity factor indicates the potential of subwatersheds’ runoff sensitivity to climate change based on the subwatersheds’ characteristics such as area, width, slope, and imperviousness. Results of analysis of SCSF show that storm water runoff in a changing climate is more sensitive to subwatershed slope, rather than the other subwatershed characteristics. Subwatersheds with SCSF more than 0.1 show a runoff volume increase of 40% or more, under the effects of climate change. Based on the potential increase in peak discharges, retrofit measures are recommended to provide additional storm water management capacity.

This paper presents a hydrologic drought atlas for the state of Texas. The atlas depicts the spatial variation of drought severity for durations of 3, 6, 12, and 24 months corresponding to the return periods of 10, 25, 50, and 100 years. Using the variable infiltration capacity model which is a large-scale land surface model, drought characteristics were derived from monthly stream flow simulated at $1/8°$ resolution over the state of Texas. Appropriate marginal distributions of drought severity and duration were selected from amongst exponential, gamma, log-normal, and Weibull distributions, whereas the joint distribution of severity and duration was selected from the Archimedean, extreme value, Plackett, and elliptical families. Then, severity-duration-frequency (SDF) curves were obtained which were used for preparing the drought atlas that depicts the drought severity for any drought duration and return period at any location in Texas. Results indicate a decreasing pattern of severities from west to east. Humid and semihumid regions show a concave pattern in the SDF curves, whereas arid and semiarid regions show a convex pattern. The nonparametric Mann Kendall test was used to analyze the long-term drought trend that indicated a downward trend in arid and continental regions and an upward trend along the Gulf Coast, humid, and semihumid regions.

Soil moisture variability has a major impact on runoff generation. In this study, the dynamics and variability of soil moisture at small hillslope transects were analyzed by artificial rainfall simulation experiments in which the influence of crop type and slope angle were considered. Soil moisture variability and dynamics during the rainfall-runoff process were monitored by capacitance sensors (EC-5) with high temporal resolution (1 min) and continuously measured after rainfall ceased to investigate soil moisture dynamics and patterns by the method of data visualization. Relationships between soil moisture and runoff (surface and subsurface flow) and response lag times of soil moisture at different slope positions and soil layers were investigated. The dynamics of soil moisture during the entire crop growth stage were also analyzed. Results showed that soil moisture exerted strong influence on runoff generation, but the relationships were strongly affected by crop type. There was an obvious threshold (approximately 30% vol soil moisture content) between soil moisture and runoff coefficients/surface flow for the wheat crops for both slope angles, but the relationship between soil moisture and runoff was more scattered for spring maize. The response of subsurface flow to soil moisture exhibited hysteretic behavior attributable to soil moisture characteristics and a long recession process and was significantly influenced by slope angle. Lag times between soil moisture and the generation of subsurface flow were both controlled by antecedent soil moisture conditions. During wet conditions, differences in soil moisture response time at different soil layers were small, and obvious subsurface flow could be observed. Conversely, there were large differences between the response times (e.g., the increase in soil moisture for 40-cm depth was close to 0) for rainfall events during dry conditions, and little lateral subsurface flow was observed. Understanding relationships between soil moisture and subsurface flows under different slop angles and vegetation covers will help to improve models that aim to predict the impact of land-use change on runoff and provide useful information for evaluating the effects of soil conservation measures on runoff and sediments in north China.

In 2009, Typhoon Morakot made landfall in central Taiwan causing significant damage to property on the island. The Linbian Creek Basin, located in southern Taiwan, which suffered from destructive flooding, was selected as study site. Observations show that high tides downstream obstructed water flow from the Linbian Creek so that it could not be flushed out. The overflow continued to grow because of the accumulation of heavy rainfall in the upper parts of the watershed. In the end, three typical sections of the levee, at (1) Zhuzaijiao, (2) Jiadong, and (3) the Railway Bridge, sustained damage. This overflow from the Linbian Creek resulted in the occurrence of destructive inland typhoon induced flooding. This paper probes into the possible reasons for such extensive flooding along the Linbian Creek. For describing the extremely chaotic flow conditions the writers developed a decoupled model that links three models. Generate waves, wave-induced setups, and storm surges used as a downstream boundary condition in the hydrological model for simulating surface inundation. Numerical results reveal that two key factors caused the flood damage, as follows: (1) the spring tide caused by the storm surge blocked the floodwater from emptying downstream and resulted in a rapid rise of the water level, and (2) scouring and liquefaction at the foot of the creek bank by the discharge. Both lead to broken embankments and water overflowing across the banks at three typical locations. The rapid increase in water from the tributaries and the chaotic water flow inside the channels were construed to be major reasons causing the embankments to collapse.

A power-law cross section is very versatile and can be used for a number of practical applications. It allows the modeling of natural rivers (channels) and artificial channels. Normal depth is of high practical importance. This depth is used for computing water surface profiles and for the design, operation, and maintenance of open channels. No direct solution is available in the technical literature for normal depth in power-law channels for an arbitrary value of the exponent. For this channel, the normal depth is presently obtained by trial procedures. The main challenge with power-law sections is the calculation of the wetted perimeter. In this study, the wetted perimeter is estimated by calibrating the method of undetermined coefficients, which results in a simple and accurate expression for the wetted perimeter with the exponent $m$ arbitrary between the limits 1 and 2 (case of practical interest). Then, this expression is used to develop an accurate direct solution that can be used to calculate the uniform flow depth of open channels with a power-law cross section.

Effects of groundwater use and land-cover change on stream runoff are major concerns of integrated water-resource management in agriculture-dominated watersheds. Stream depletion-rate analyses commonly utilize various analytical approaches, but little progress was made in analytical evaluation of land-use change effects on stream runoff. The purpose of this note is to revise and generalize analytical solutions for stream-aquifer exchange rates and volumes that account for different geometries of the land uses and aquifers. This approach utilizes integration of point-source solutions. Results are illustrated by sensitivity analyses using parameters that are typical of many watersheds. New solutions incorporate and extend previously known results and are sufficient to cover the entire range of practical applications.