Journal of Hydrologic Engineering

Wavelet transforms are combined with predictive methods to develop prediction approaches so that the prediction accuracy can be improved in hydrologic predictions. Although the wavelet transform generates several subseries that show similar characteristics, the predictive method is used to develop the model using those subseries. There are several examples of these kinds of combined models, such as wavelet–multilayer perceptron (MP), wavelet fuzzy, wavelet autoregressive, and so forth. Generally, discrete wavelet transformation is used in combined models rather than continuous wavelet transform for unexplained reasons. As a result, in this study emphasis was placed on the comparison of the continuous wavelet–multilayer perceptron (CWT-MP) and discrete wavelet–multilayer perceptron (DWT-MP) models, which were also compared with the stand-alone MP model. Daily precipitation time series from two stations were used in the model development and comparison process. The current precipitation values were predicted from previous precipitation values. Various scenarios were used for the establishment of the models. Mean square error (MSE), coefficient of efficiency (CE), and score skill (SS) were used as model evaluation criteria, and it was observed that the prediction performance of MP was significantly improved by using wavelet transforms as preprocessing techniques. However, the CWT-MP models were found to be better than the DWT-MP models based on the results of the evaluation criteria.

Effective, $f$-load, and functional-equivalent discharges are metrics that can be used as design flows for stream channel restoration and for eco-hydrologic and geomorphic studies. Previously published analytical estimators of these discharge indices are reviewed and new estimators are derived for gamma, lognormal, mixed gamma, and mixed lognormal flow frequency distributions of daily flows combined with a power-function approximation of sediment rating curves. For 19 small streams in Ontario, Canada, goodness-of-fit test statistics do not clearly show that mixed gamma distributions improve the fit with observed daily flow frequency distributions; however, the discharge indices determined analytically using mixed gamma distributions better match empirical estimates of these indices than those computed based upon gamma, lognormal, and mixed lognormal distributions. Comparative analysis of the three discharge indices also suggests that $f$-load discharge with a reasonable $f$ value provides a more consistent design flow for the restoration of small streams.

Both deterministic and probabilistic models have been developed to study the hydrologic operation of green roofs. Previously developed probabilistic models provide only approximate solutions because of simplifying assumptions. Exact analytical solutions are derived here for not only those variables that are solved for already but also some additional ones of interest. Analysis of the additional variables reveals that, depending on local climates, the average moisture level of a green roof may either always increase or increase first but reach a maximum and then even gradually decrease as the growing medium depth increases. Example results of analysis also demonstrate that with shallow growing medium depths, water required for irrigation may be greater than the runoff that can be reduced by green roofs. Taking advantage of the solution’s analytical tractability, similar insights can be easily obtained for locations of interest and used for the better design and operation of green roofs.

In this paper, new analytical solutions are presented to quantify interaction of water between a sloping aquifer and stream of varying heads in presence of a thin vertical sedimentary layer. The initial hydrogeological setting consist of an unconfined sloping aquifer of semi-infinite extent, a fully penetrating stream of varying water level, and a vertical layer of streambank deposits that acts as an interface between stream and aquifer. Unsteady groundwater flow is characterized by a nonlinear Boussinesq equation subject to Robin boundary condition (also referred to as third kind and Cauchy boundary condition). Unlike existing results, which focus only on step changes in stream stage, the current study accounts for gradual rise and decline in stream level. A closed-form analytical solution for water head distribution, discharge rate, and net volumetric exchange of water between stream and aquifer are developed from the solution of a linearized advection-diffusion equation. Performance of the analytical solution is compared with the numerical solution of the corresponding nonlinear Boussinesq equation using L2 and Tchebycheff norms. It is shown that the linearization yields acceptable solutions in many and varied situations where a stream interacts with an aquifer. The analytical solutions are presented in a manner that several other configurations, namely, zero slope, absence of vertical clogging layer, and abrupt changes in stream stage can be deduced as limiting cases of the main results. Combined effects of streambank leakance, bed slope, and stream-stage variation rate on the bank storage characteristic of the aquifer are illustrated with a numerical example.

Richards’ equation (RE) constitutes the most used physically based formula for transient infiltration modeling in unsaturated soils, and it can be solved by using analytical or numerical procedures. Analytical methods require that certain assumptions should be made regarding the closed-form equations that are derived; if the assumptions can be considered reasonable, then the analytical procedures can represent a simple and practical tool (except some cases in which complicated boundary conditions could make the application of the methodology more difficult). Numerical methods do not have the strong limitations of available analytic procedures, and for this reason many numerical schemes are proposed in technical literature to solve RE. Nevertheless, numerical techniques could require high computational costs for application in large areas with respect to analytical procedures. For the frequent case of layered unsaturated soils, analytical solutions were derived by only imposing equal values of capillarity rise for different layers, and this is a clear questionable assumption. A procedure for one dimension is proposed in this work in order to obtain analytical solutions for any soil property: different values of capillarity rise of considered layers, any variation of saturated hydraulic conductivity with depth. The obtained results highlight a good capability of the proposed methodology to reproduce all the considered benchmark cases, constituted by analytical solutions reported in technical literature and application of a software.

Common engineering methods for the computation of peak discharge are generally based on the assumption of a stationary watershed. This assumption can potentially lead to inaccurate estimates of peak discharge when considering the lifetime of engineering structures. Future land use change is one of the possible causes of non-stationarity in watershed runoff. This study focuses on a method to integrate the readily available integrated climate and land use scenarios (ICLUS) data sets from the environmental protection agency (EPA), with geographic information system (GIS) and hydrologic modeling. This framework is applied to evaluate the impact of the forecasted land use change on the design peak discharge in the rapidly urbanizing region in Northern Virginia (US) at the watershed (Anderson formula) and catchment [calibrated storm water management model (SWMM)] scales. The results show that the impervious area in the rapidly urbanizing Difficult Run watershed is expected to increase by 99.1% (2070) from the year 2010. This increase could cause the peak discharges to increase by 107.9% (SWMM) and 22.1% (Anderson formula) for the 2-year storm event. Simple and easy-to-use regression equation is presented to estimate the changes in design peak discharges based on drainage area and the change in percent of impervious area for the return periods of 2, 10, 25, 50, and 100 years. The results of this study, in addition to supporting local planning and managing of land development activities, also demonstrate a viable alternative to incorporate the impacts of future land use change on design peak discharge.

This study is aimed at understanding the behavior of a rainfall time series having a large number of continuous zero values. Forty-nine years of daily rainfall data pertaining to the Koyna Reservoir catchment in India is employed in the study. The majority of rainfall happens during the monsoon period from June to September; the rainfall during the non-monsoon period (October to May) is almost negligible. This phenomenon has been observed every year. Hence, 64% of the time series contains zero values. Six sets of rainfall time series along with the observed series are analyzed: (1) daily observed average rainfall data; (2) daily transformed average rainfall data; (3) daily wet-period average rainfall data; (4) phase-randomized average rainfall data; (5) daily average rainfall anomaly data; and (6) standardized daily average rainfall anomaly data. To understand the consequence of a greater length of zero values and constant values, daily observed average rainfall data results are compared with daily wet-period average rainfall data and daily transformed average rainfall data. The phase-randomized and the anomaly data of the rainfall series were used to cross verify the behavior. The correlation dimension method (CDM) based on the Grassberger–Procaccia algorithm was used in this study for behavioral analysis as well as to find the embedding dimension of the time series. The results reveal that the CDM underestimated the correlation dimension as one owing to a higher percentage of continuous zeros/constant values in the case of full-year rainfall data and transformed daily rainfall data, respectively, whereas the correlation dimension of the wet-period rainfall data is five. On the other hand, the optimum embedding dimension in all cases of full-year and wet-period rainfall data is estimated by the CDM turned out to be five. It is found that the correlation dimension method underestimates the correlation dimension if the series has a large number of zeros or constant values.

The increase of imperviousness due to urbanization creates adverse effects on the hydrological and environmental processes in a catchment. The increase in impervious areas leads to a higher runoff peak flow and stormwater pollution, even for a short duration of low-intensity rainfall. The present study focuses on the Bivio Vela catchment, an urban catchment of Pavia in northern Italy. This paper emphasizes both experimental and modeling approaches to the rainfall-runoff process and pollutant dynamics on the catchment surface and in the combined sewer system, considering significant increases in impervious area. Recent and future catchment developments caused the conversion of approximately 33% of the total area from nonurban pervious area to impervious area. The study also deals with the performance assessment of the wet-weather control system of the catchment, introducing simple indicators that account for the requirements of the urban drainage system and treatment plant. Imperviousness associated with urbanization in the catchment is invariably reflected in the receiving river flow regime and water quality. The simulation results indicate that the annual number and duration of sewer overflows and volume, peak flow, and pollutant mass discharged into the river have increased to different degrees due to urban expansion during the recent period and will continue to increase as urban areas increase in the future. The impact of urbanization on rainfall runoff and water quality should therefore be considered for effective urban and water infrastructure planning. The methodological approach and the proposed performance indicators, which take advantage of experimental data and are suitable for complex urban drainage systems, are original and promising for their help in formulating policy guidelines and intervention strategies that minimize the negative effects of urbanization on both the water environment and the treatment plant.

Efforts to retrofit pervious surfaces into urban landscapes are ongoing, yet the in situ infiltration rates of such surfaces have not been adequately studied. Of increasing interest in urban stormwater management is whether the infiltration rates of different permeable surfaces can be reliably estimated based on surface type alone. To this aim, a total of 139 infiltration tests were conducted using a Cornell sprinkle infiltrometer at 39 different sites distributed within New York City and Philadelphia. The results show significant statistical differences among surfaces: urban parks and tree pits without guards have the lowest infiltration rates; vegetated courtyards, tree pits with guards, porous pavers, backyards, and bioretention facilities display moderate infiltration rates; and porous concrete has the highest infiltration rate. The infiltration rates measured for most of the sites are similar or greater than the local design storm, suggesting that minimal rainfall excess would be generated from these surfaces as long as sufficient subsurface storage space is available.

Residence times of tracers in rectangular seepage lakes with wind-driven circulation are investigated in this paper. The key dimensionless parameters are $D_{T}W/q{L}_T^2$ and $VW/q{L}_L$, in which $D_T$ is the diffusion coefficient transverse to the wind direction, $W$ is the dimension of the lake aligned with the direction of groundwater inflow/outflow, $q$ is the specific discharge of groundwater entering and leaving the lake, $L_L$ and $L_T$ are the lake dimensions in the wind direction and transverse to the wind direction, respectively, and V is the wind speed. The well-mixed approximation in rectangular lakes is reasonable when $D_{T}W/q{L}_T^2>1$ and $VW/q{L}_L\gg 1$. Under these conditions, tracer particles are distributed uniformly over the outflow surface, and the probability distribution of tracer residence times can be estimated theoretically without the need to develop a numerical mixing model for the lake.