Journal of Hydrologic Engineering

One of the main obstacles in making reliable predictions of extreme events is the apparent shortness of the time series available in hydrology. There is a common advantage of both regional flood-frequency analysis and partial duration series (PDS) in which both of them allow a reduction of uncertainty by introducing more data to the site of interest. Therefore, a new regional index flood method for ungauged sites based on the PDS model is presented. The PDS model considered in this case assumes a Poisson-distributed number of threshold exceedances and generalized Pareto-distributed peak magnitudes. A new objective approach for the selection of the threshold in the context of regionalization is introduced. This approach estimates a range of reasonable thresholds (or an average annual number of events) for every site. Consequently, the regional average annual number of events can be determined as a common value for all sites in the homogeneous region. The delineation of hydrologically homogeneous regions is determined using the scaling approach. The feasibility of the proposed method was assessed using the available daily flow series from 57 watersheds in Quebec (Canada). Furthermore, the new method is compared with two existing methods for regionalization: the region of influence and canonical correlation analysis methods. Results of the numerical application indicate that the quantile estimates obtained from the new method provide the best values of the performance criteria (e.g., root-mean-square error). Hence, the new method not only eliminates subjective decisions but also greatly improves the predicted floods for ungauged sites.

Bridge designs are commonly based on a criterion to withstand the n-year flood event. For example, a highway bridge might be designed to pass the 100-year flood. Failure may occur if the structure faces an event larger than this. Climate change may necessitate different design criteria because of changes to flood frequency behavior. This study examines the consequences for bridge design for flooding under the influence of climate change. In this study, climate change is quantified simply as a change in the frequency of a given precipitation or flood event. Flood discharges for current conditions are estimated from the applicable U.S. Geological Survey regression equations. Natural Resources Conservation Service methods are used to inverse calculate the causal precipitation for such floods. Return frequency for this causal precipitation is determined from both the current national precipitation frequency source and future climate intensity-duration-frequency curves. This study specifically looks at the freeboard criteria for bridges of different road classifications and how the margin of safety associated with a designed freeboard is reduced under future climate conditions. The results demonstrate that all categories of roadways are vulnerable to climate change and that the magnitude of bridge vulnerability to future climate change is variable depending on which climate model projection is used. The results show that increases in impervious area upstream of a bridge crossing increase the susceptibility of the bridge to failure. Holding other watershed characteristics constant, increased impervious cover leads to a greater loss in the margin of safety represented by the designed freeboard, suggesting that limiting the development to control imperviousness can bolster resilience of bridge infrastructure to climate change. A sensitivity analysis shows that uncertainty in both flood and precipitation frequency estimates is at least of comparable magnitude to projected changes in flood risk posed by climate change.

Crop coefficients ($k_c$) were calculated for three different species of common green roof succulents from March to November in 2011, to parameterize the Food and Agricultural Organization of the United Nations (FAO) Penman-Monteith equation for use in a mechanistic green roof water-balance model. Seasonally averaged $k_c$ values for each species for 2011 were used to predict plant evapotranspiration ($E_T$) in 2012. The adjusted FAO Penman-Monteith equation predicted the total annual $E_T$ within 3–13 mm, a substantial improvement over model predictions with $k_c$ set to 1, which overpredicted $E_T$ by 100 mm or more, depending on the species. The adjusted equation was inserted in water-balance models, which predicted runoff within 2–13% of measured totals for 2012. This discrepancy may be explained by variability in maximum water-holding capacity, which is difficult for two-dimensional models to predict. Nevertheless, these results provide increased confidence in the use of models to predict stormwater runoff from green roofs, and evaluate performance. Monitoring multiple green roof installations with cost-effective sensor networks will increase the ability to identify the key components to enhance green roof function, reduce stormwater runoff, and inform future design.

The soil and water assessment tool (SWAT) was used to investigate the effects of hydrologic response unit (HRU) thresholds (0–20%) on predictions of multiple variables by calibrated and uncalibrated models in a $10.4\text{-}{\mathrm{km}}^2$ urban watershed in the U.S. Mid-Atlantic region. Surface runoff, discharge, sediment yield, and nutrient yield were simulated in stream and on land, and used to spatially identify hotspots for each constituent. SWAT2012 was able to produce accurate discharge and nitrogen estimates that were not sensitive to HRU thresholds. HRU thresholds significantly affected sediment and phosphorus predictions in calibrated and uncalibrated models. Constituent hotspots identified by an uncalibrated model with a 0% HRU threshold were found to be acceptable for the urban watershed under study, except for sediment. Hotspots identified with calibrated models, with HRU thresholds of 5% or less, fit with the identification of on-land sediment and nutrient hotspots. These findings suggest that researchers should carefully consider HRU thresholds when predicting on-land variables of small urban watersheds similar to the watershed in this study when using SWAT.

Based on the multiscale finite-element method (MSFEM) and Yeh’s finite-element model, this paper proposes a MSFEM–Yeh model (MSFEM-Y) for solving nodal Darcian velocities in porous media. The main idea of this method is to solve Darcy’s law directly by MSFEM so as to obtain continuous coarse-scale velocities with high efficiency, while ensuring the mass conservation is satisfied to an acceptable degree. The MSFEM features allow this method to obtain fine-scale velocities directly by an interpolation equation, which only consists of coarse-scale velocities and base functions. Because the base functions have been constructed in head computation, the computation of fine-scale velocities does not need much cost. Furthermore, MSFEM-Y also ensures the continuity of fluxes, so that the MSFEM-Y fluxes are more accurate than those obtained by the original MSFEM. Numerical experiments indicate that the MSFEM-Y can achieve more accurate heads, velocities, and fluxes with high efficiency.

In this work, a simple computational scheme with the pragmatic purpose of augmenting the efficiency of river discharge measurements is proposed. Observing the functional form of the velocity profile versus depth, applying polynomial regression for each vertical, and finally interpolating between the verticals, the authors develop a continuous approximation for the velocity across the entire vertical section, which turns out to be rather robust to the removal of individual measurement points. In particular, numerical data analysis shows that the number of measurements can be significantly reduced without a significant loss of accuracy of the discharge estimate. This procedure has been tested on the data obtained experimentally on the Exu, Capibaribe, and Ipojuca rivers, in the state of Pernambuco, northeast of Brazil, with different streamflow patterns exhibiting multiple local velocity maxima on and below the surface.

Widespread dam construction has significantly altered natural hydrologic processes and consequently affected river ecosystems. The concept of self-organized criticality (SOC) implies the ability of a system to create and maintain its own function and has important implications for the entire ecosystem, thus can be used to assess anthropogenic disturbances. This study focuses on how reservoir operations affect the SOC behavior of river flows. Taking five large-sized reservoirs in China as examples, the maximum likelihood methods, Kolmogorov Smirnov testing and Detrended Fluctuation Analysis, are used to examine the typical SOC fingerprints for daily river flow series, including their power law frequency-magnitude distributions and long-range correlations. The results show that with increasing reservoir-modified pressure, the frequency-magnitude relationships of natural flows gradually deviate from heavy-tailed power laws and tend to behave as normal or lognormal distributions, characterized by vanishing tails and narrower spans. Furthermore, dam-influenced flows tend to display delayed scaling break times, decreased fluctuations, and increased long-range persistence, and their variations demonstrate more anisotropic. The results indicate that a loss of hydrologic diversity is gradually revealed because of reservoir regulation, and further emphasize restoration of the distributional and temporal characteristics of natural flows rather than a focus on simple ecoflow constraints.

Permeable road pavement has been used widely as a sustainable alternative to the traditional impervious pavement and has become an increasingly important component of the hydrological cycle. The benefits of permeable pavement depend on its hydraulic performance and drainage efficiency, for which there have been very few rigorously tested numerical models. In this paper, a new computational model is presented to simulate fluid motion above and within the porous road pavement. This model solves the coupled equation system for surface and subsurface flows using a finite-volume method. The surface flow and the subsurface flow are modeled by the two-dimensional diffusive wave equation and the three-dimensional Richards equation, respectively. A modified Dirichlet-Neumann partitioning method is used as the coupling algorithm to ensure the continuity of pressure head and the conservation of mass. The diffusive wave model for the surface flow is solved with a flux correction transport (FCT) scheme that considers the dry/wet interface and guarantees the positiveness of the water depth. The three-dimensional Richards equation for the subsurface makes it possible to model complex drainage configurations. With the present model, the infiltration process from the road surface into the permeable pavement can be captured more accurately in comparison with many previous models that assumed direct rainfall recharge into the free surface without the leaching process. This capability is important for predicting the timing of road surface ponding, which is critical for safety. The proposed model is extensively validated and an example application for porous pavement design is provided. Results show that the porous pavement with limited thickness considered in this research delays the timing of surface ponding but has less impact on the steady-state water depth and spread.

In urban hydrology, accurate temporal and spatial rainfall observations are a key factor for managing urban hydrologic systems and stormwater runoff, particularly in the current era of higher variability in recent rainfall events. To study this issue, rain gauge data from a ground-based rainfall measurement network operated by the local stormwater management agency, Metropolitan Sewer District (MSD), in Jefferson County, Kentucky is evaluated. Rainfall spatial characteristics are evaluated through correlation spectrum by distance indicating a spatial rainfall variation concave relationship. The correlations at a 5-km distance are [0.63, 0.74, 0.80, and 0.86] for temporal resolutions of (15 min, 30 min, 1 h, and 3 h), respectively. A decreasing correlation with increased rainfall intensity is observed at temporal resolutions less than 1 h, and correlation increases at higher rainfall intensities and temporal resolution coarser than 1 h. This case study provides a context for the use of recent historical information to guide urban stormwater management planning through rain gauge deployment and detection of regional rainfall characteristics.

Assessing the impacts of El Niño Southern Oscillation (ENSO) on hydrological cycle is critical for irrigation scheduling and water resources management. The ENSO-rainfall teleconnections in Venna River Basin in Maharashtra, India, and its impacts on vegetation have been identified in this study by using rainfall data, moderate resolution imaging spectroradiometer (MODIS) normalized difference vegetation index (NDVI) and geographic information system (GIS) techniques. Spatiotemporal analysis indicates correlation of rainfall with ENSO. Spatial variation in rainfall harmonizes with topography of the region, and a respective decrement and increment of 200–400 mm of rainfall at higher and lower elevations are seen to be associated with El Niño and La Niña events. This study also records the impacts of varying intensities of ENSO, causing inconsistencies in parameters, namely, premonsoon and postmonsoon vegetation growth, phenological parameters, and crop water requirements. The correlation of NDVI-precipitation studied by mean square error (MSE) and lagged correlation analyses shows a time-lag effect of 2 months. It is estimated that the percentage area of dense vegetation is maximum in La Niña (15.6% in 2011) and minimum in El Niño (1.2% in 2009). A “20% threshold graphical method” introduced in the study reveals that El Niño and La Niña are associated with late (July) and early (June) start of season ($S_s$), respectively. This study also reveals that crop coefficient and water requirements are more for the ENSO cold phase than for the warm phase.

Trends and variability of hydrological variables can reflect the redistribution of seasonal patterns that can be caused by both climatic and anthropic factors. In this paper, China’s East River, the most regulated tributary in the Pearl River Delta (PRD), is selected to be a typical study case. Annual and seasonal-scale analyses of the river regime are performed, in conjunction with a correlation analysis between runoff and suspended sediment concentration (SSC). Noteworthy results include the strong increasing trends in dry season (October–March) runoff, as well as a significant decreasing trend in annual and wet season (April–September) SSC. Moreover, the continuous wavelet transform, runoff, and SSC display a degenerative annual fluctuation signal gain and a nearly total signal loss after 1990, respectively. All these results can be ascribed to an intra-annual redistribution of hydrological series, which bridges the gap between the wet and dry season and leads to a weakened seasonal difference. Furthermore, a changing correlation is detected with sediment rating curve at the seasonal scale. Finally, the river regime index (RRI) is calculated to quantify the impacts of river regulation. The results indicate that the East River is becoming a more uniform regulated river. Precipitation series, the most representative hydrological signal of climate factors, show no obvious temporal variations at the annual or seasonal scale over the whole study period. Therefore, the seasonal pattern alteration can be mainly attributed to human activities, in particular the construction of reservoirs in the East River.

Projection of floodplain extents is extremely important in identifying solutions that will establish the controls of land use in flood-loss reduction studies. The Riviere des Prairies, located in the province of Quebec, Canada, has many rapids that make the river basin highly vulnerable to potential flood loss. The aim of this study was to evaluate the hydrological and environmental impacts that climate change may have on the Riviere des Prairies basin. The design rainfalls considered are 50-year return period events lasting for 24 hours each and built using the Chicago method. The future intensity-duration-frequency (IDF) curves were derived from IDF_CC tool, which is especially designed for updating these curves under a changing climate. Representative concentration pathway (RCP) scenarios are used to simulate climate change for this purpose. The future flow hydrographs are obtained through rainfall-runoff transformations and results have been inputted into the Hydrologic Engineering Center’s River Analysis System (HEC-GeoRAS) (calibrated with known water elevations and flows). The calibration results give a peak flow margin of error of $+2\%$ and a volume margin of error of $-24\%$. Water levels are better simulated at the upstream portion of the Riviere des Prairies dam, with errors ranging from 16 to 95 cm. Despite the rising water, clearance remains higher than 3 meters for most of the bridges, which indicates that corresponding bridges will not be submerged or swept away. However, two bridges appear to be submerged with a water depth in range of 0.36 to 0.90 m for the first bridge (Ile Bizard), and 0.36 to 1.31 m for the second one (Lachapelle Bridge), depending on the model and simulated scenario. The results of the hydrodynamic simulations showed that some large flood zones were expected along the Riviere des Prairies from upstream up to the Médéric Martin A15 Bridge, as well as near the outlet. To mitigate the potential effects of flooding in the Riviere des Prairies basin, some adaptation and prevention measures have been recommended.

In this study, non-Darcian flow to a partially penetrating pumping well in a leaky aquifer was investigated. The aquifer system is composed of a main aquifer with an aquitard bounded on the top of the aquifer. The storage of the aquitard was considered in this study, which is the main contribution of this study. The horizontal flow in the main aquifer is assumed to be non-Darcian, while both the vertical flows in the main aquifer and the aquitard were assumed to be Darcian due to the relative low velocities. The non-Darcian flow was described by the Izbash equation. A linearization procedure associated with Laplace transform and separate variable method were used to solve the non-Darcian flow model. Semianalytical solutions (Laplace-domain solutions) were obtained then inverted to time domain by using the Stehfest method. The results indicated that the power index $n$ in the Izbash equation results in a smaller drawdown at late times, the flow approaches quasi steady state earlier, and the leakage has little impact on the drawdowns in the main aquifer when $n$ is larger. The drawdowns are quite different from each other for different $z$ positions even at the same radial distance. The sensitivity analysis indicated that the drawdown in the main aquifer is very sensitive to the power index $n$, moderately sensitive to the parameters of the main aquifer, and relatively not sensitive to the parameters of the aquitard.

An acoustic Doppler current profiler (ADCP) was used to measure a wide range of velocity profiles and flow rates within the Red River in Winnipeg, Manitoba, Canada, over 2 years. The river is highly sinuous with approximate sinuosity of 2. Chiu’s entropy-based velocity profile equation was used to find the best fitted curve to the measured data and an $M$ value of 4 was found to be adequate to predict the velocity profile within the Red River in Winnipeg. Moreover, several water samples were collected from the river under different flow rates to investigate a relationship between total suspended solids concentration ($C_{\text{TSS}}$) in the river and measured signal to noise ratio (SNR) by an ADCP. The best fit was an exponential function with $R^2=0.54$.

In the context of urbanization and waterworks construction, detention basins located in upstream tributaries have become one of the most-effective technical solutions for downstream flood reduction. This technical note proposes a new optimal approach for determining the most-effective design combination of detention basins (in terms of their sizes and locations) in a watershed utilizing linear reservoir theory. The optimal detention basin is obtained by minimizing the deviation of downstream peak discharge from river capacity discharge. With the presence of a detention basin in an upstream river, the flood peak downstream decreases by 33%, corresponding to two scenarios of rainfall duration with a return period $T=100$ years. The storage volume estimation of the optimal detention reservoir proposed in the present paper demonstrates the high applicability of this optimization approach.

Monthly precipitation hindcasts/projections for various climate change scenarios have been available for over a decade. More recently, daily precipitation hindcasts/projections using downscaled bias-corrected constructed analog (BCCA) have garnered wide usage for climate change investigations. Dry bias and drizzle effect reported in previous studies are among known limitations of downscaled BCCA precipitation hindcasts/projections which affect end-user applications. End users also require a reliable representation of precipitation sequence as well as physical consistency of precipitation series for climate change impact assessment applications. This study focuses on the evaluation of the daily sequence of downscaled BCCA precipitation hindcasts. Herein, direct use of BCCA daily precipitation hindcasts are further assessed to determine their suitability to study daily soil moisture dynamics at the field-scale for central Oklahoma climatic conditions. Three daily precipitation data sets were considered: (1) the 1961–1999 BCCA precipitation hindcasts for a 12 km grid in central Oklahoma, (2) the 1961–1999 spatially interpolated daily precipitation data used in the BCCA downscaling procedure, and (3) the 1961–1999 observed daily precipitation observations at the Weatherford COOP Weather Station located within the 12 km BCCA grid. The BCCA daily precipitation hindcasts showed a larger number of rainy days, lower rainfall amounts per rainy day, and longer sequences of consecutive rainy-day clusters than found in observations. These differences were large enough to suggest that BCCA daily precipitation hindcasts may not reflect the characteristics of actual precipitation observations at a point location, i.e., weather station. Additional analyses at Walnut Creek, Iowa and Moorhead, Mississippi confirmed the results are not location specific but numerically induced as a result of the downscaling process. The underlying cause for the noted differences was traced back to the differences in spatial scales of the BCCA outputs and observed daily precipitation at a station. Thus, caution is advised to end users using BCCA daily rainfall hindcasts/projections directly in local and field-scale water investigations, particularly for applications requiring reliable representation of precipitation sequence. Alternatively, a statistical downscaling method based on stochastic weather generation that includes wet-day dry-day transition probabilities would provide the desired temporal disaggregation and sequencing of daily rainfall events.

The sheet piles are used below hydraulic structures to reduce seepage flow rate and hydraulic gradients at the outlet of such structures that are rested on the permeable foundations. Up to now, for analysis of seepage under hydraulic structures, a number of research works have been conducted in the form of numerical models. However, less field and laboratory works have been done to study the boiling phenomenon for the evaluation of the numerical models. In the present research work, a laboratory model was made to simulate seepage flow and its behavior downstream of a sheet pile under vertical and inclined configurations. The model consisted of a flume 2.2 m long, 0.8 m deep, and 0.4 m wide, in which vertical and inclined sheet piles were provided by cast acrylic sheet. The flume was made of steel frame and Perspex as well as thick glass sheets. Fine clean sand was used as an alluvial foundation and then compacted to a uniform density at the bottom of 40 cm of flume. Perspex sheets were used as sheet pile variable depth. The piezometric heads were measured both downstream and upstream of the sheet pile using small-diameter clear plastic tubes. The results indicated that the optimal ratio of sheet pile depths for both vertical and inclined sheet piles to reduce boiling under maximum upstream water level were $d/D=0.44$ and $d/D=0.34$, respectively. Finally, it could be concluded that the inclined configuration with the angle of 60° (to the horizontal direction) performed well to reduce boiling compared with the vertical case.