Journal of Hydrologic Engineering

The role of cool (La Niña) and warm (El Niño) phases of El Niño Southern Oscillation (ENSO) on seasonal variations in atmospheric humidity which has impact on hydrological cycle is studied using global positioning system radio occultation (GPSRO), constellation observing system for meteorology ionosphere and climate (COSMIC) derived water vapor profiles after ensuring its accuracy with National Ocean and Atmospheric Administration (NOAA)/Earth System Research Laboratory (ESRL) radiosonde observations ($r^2=0.91$ at 850 hPa and $r^2=0.90$ at 500 hPa) and National Centers for Environmental Prediction (NCEP)/National Center for Atmospheric Research (NCAR) reanalysis data ($r^2=0.86$). Relative and absolute humidity are calculated using GPS RO data and their variation with ENSO phases is studied. Variation in humidity is linked with phase of ENSO, and NCEP/NCAR humidity shows positive deviation during months with La Niña phase. The analysis highlights the changes in the vertical profile of atmospheric humidity (both relative and atmospheric humidity) during El Niño/La Niña phases occurring between 2006 and 2012. Maximum difference in monthly deviation ($>96\%$) in vertical profile of humidity between both phases is observed at middle troposphere (7–8 km) in the month of September followed by June (93–96%) between 6.5 and 7 km. The difference between percent deviation during both phases of ENSO is the minimum (1.32%) in August in middle troposphere indicating less effect of ENSO phases. The effect of phases of ENSO on boundary layer height (BLH) is more prominent during the nonrainy season when, owing to low humidity, higher BLH is expected. Increase and decrease of atmospheric humidity with La Niña and El Niño phase, respectively, lowers/increases the BLH prominently during nonrainy season months of October–May. It was observed that there is delay in onset of monsoon during El Niño year, and the atmospheric vertical humidity profile by GPSRO also showed the high humidity at 5–7 km altitude one day prior to onset of monsoon and lowering of humidity on the day of monsoon. The results of the study show that seasonal variations in atmospheric humidity are induced by ENSO phases even over small geographical area and are discernible with COSMIC GPS RO data.

The occurrence of floods and their impacts on hydrologic systems and society are critical considerations in the design and management of a large number of water resources projects. As streamflow records are often limited or unavailable at many watersheds, it is necessary to develop better methods for regional estimation of floods at these partially-gauged or ungauged sites. In this paper, a comparative study of homogeneous region delineation approaches in the context of regional flood quantile estimation is presented. Three approaches were considered in this study using the available annual maximum series (AMS) of flood peaks for 57 watersheds in Québec, Canada. The first approach was the scaling method, which is a relatively new approach for homogeneous region delineation. This approach is based on the scaling behavior of the flood series with the basin area. The other two approaches were the region of influence (ROI) and canonical correlation analysis (CCA) methods. Regional flood estimation was carried out using the index flood method. The jackknife technique was used to represent the ungauged site condition. Analyses of hydrologic data from Québec have indicated that the AMS exhibited a simple scaling behavior and that the drainage area alone may describe most of the variability in the statistical moments of the AMS data. Results of this numerical application have found that the flood quantile estimates obtained from the scaling approach are more accurate and more robust than those given by the ROI or CCA methods. In addition, it was found that the grouping of similar basins on the basis of the scaling approach formed well-defined geographical regions with distinct climatic characteristics.

Identification of outliers in flood records can be an important step in a robust flood frequency analysis procedure. Bulletin 17B includes the Grubbs-Beck test (with $\alpha =10\%$) as an objective criterion of whether the smallest observations in a flood record are outliers. The Spencer-McCuen test extends the Grubbs-Beck test to consider explicitly whether the three smallest observations are outliers in log-Pearson Type 3 (or equivalently Pearson Type 3) distributed samples with log-space skew coefficients between $[-\mathrm{1,1}]$, and three significance levels [1, 5, and 10%]. Presented here are Monte Carlo experiments evaluating the performance of the Spencer-McCuen test. When that test relies on the sample skew coefficient as an estimate of the population skew, the test generally fails to achieve the nominal significance levels. The same is true when used with a generalized (weighted) skew coefficient. Thus, the test will often be inappropriate if used as originally proposed. More fundamentally, when a proposed test relies on the skew coefficient of a sample to test for outliers in that sample, it is no longer clear what it means for an observation to be an outlier.

Based on a core flooding experiment, a multiphase flow model considering the heterogeneity of porosity, permeability, capillary pressure, and relative permeability (i.e., the fully heterogeneous model) is proposed to analyze ${\mathrm{CO}}_2/\mathrm{water}$ displacement in a natural sandstone core. Our results indicate (1) the fractal model approximately represents the porosity-permeability relationship of the core and combining it with the Leverett’s $J$-function, it can be used to effectively describe the heterogeneity of capillary pressure; (2) although hypothetically assuming petro-physical properties at a few locations where obviously inhomogeneous structure and significant fluctuations of ${\mathrm{CO}}_2$ saturation are observed, the fully heterogeneous model is generally applicable to model ${\mathrm{CO}}_2/\mathrm{brine}$ two-phase flow in the sandstone core and can potentially reflect the ${\mathrm{CO}}_2$ saturation buildup; (3) the heterogeneity in capillary pressure plays an important role in generating local fluctuations of ${\mathrm{CO}}_2$ saturation profile and causing the heterogeneous ${\mathrm{CO}}_2$ saturation distribution, whereas the permeability heterogeneity can only result in slight fluctuations of ${\mathrm{CO}}_2$ saturation profile and has a small effect on the heterogeneous saturation distribution; and (4) an abrupt rise of ${\mathrm{CO}}_2$ saturation in the heterogeneous downstream region of the core cannot be fully reasonably interpreted by the heterogeneity of capillary pressure and permeability. The heterogeneity in the relative permeability can also possibly play an important role in causing such rise.

Little guidance is available on how to identify optimally managed surface flood routes that can be engineered into the existing built environment. This paper addresses that gap. A least-cost path analysis was used to develop a tool based on topography and land use that automates and reduces the subjectivity in the search for viable surface-water conveyance solutions. The method is aimed at planning authorities who may use the tool to develop long-term strategic planning initiatives that identify key areas within the catchment where there is the opportunity to implement and manage flood flow routes. The least-cost path methodology was applied to identify the optimum retrofit-managed surface-water flood routes in Keighley, West Yorkshire, U.K. Three potential solutions were selected, and all three solutions reduced the number of flooded properties and enabled the surface-water catchments to retain greater proportions of the excess surface water within the catchment at non risk locations. The methodology provides the opportunity to identify the effect of each solution and hence to optimally manage the potential flood risk at an estimated cost. The least-cost path analysis to identify retrofit solutions has exciting potential for studies that need to build capacity and cope with climate change. However, the methodology has limitations in that it is highly dependent on the cost function that represents topography and land use. Costs associated with selected flood routes are extremely difficult to quantify, but such limitations will be overcome as additional cost and benefit data are made available from the implementation of a wider number of flood mitigation and rehabilitation measures. The least-cost path analysis offers a simple optioneering method that does not involve hydraulic analysis. Once a number of options have been identified, hydraulic analysis would be the next step in finding a viable solution.

In this paper the well-known kinematic wave equation for computing the time of concentration for impervious surfaces has been extended to the case of pervious hillslopes, accounting for infiltration. An analytical solution for the time of concentration for overland flow on a rectangular plane surface is derived using the kinematic wave equation under the Green-Ampt infiltration. The relative time of concentration is defined as the ratio between the time of concentration of an infiltrating plane and the soil sorptivity time scale, depending on the normalized rainfall intensity and a parameter synthesizing the soil and hillslope characteristics. It is shown that for a more complex case (corresponding to the second domain of solution domain), the time of concentration can also be estimated by two simplified approximate procedures. An error analysis for the time of concentration computed for constant and time-varying infiltration is carried out. Finally, for a hillslope under the Green-Ampt infiltration, the time of concentration obtained by the kinematic wave equation is compared with that computed by a nonlinear storage model. An application of the proposed method for two different soils is shown and discussed.

Living roofs are a green infrastructure (GI)/low-impact development (LID) stormwater control measure (SCM) increasingly drawing worldwide attention. Despite substantial performance evidence in the literature, the lack of a curve number (CN) or volumetric runoff coefficient ($C_v$) to apply to prescribed methodologies for planning and regulatory submissions may be perceived as a barrier for implementation. Paired rainfall–runoff data were analyzed for up to 21 living roofs with varying configurations and in different climates from studies identified in the literature and previously-unpublished data. Frequency analysis of empirical performance evidence from 14 living roofs indicates that meaningful runoff is not generated from the majority of small rainfall events. Where planning requires the use of the CN method, a step function is suggested: (1) runoff $\text{volume}=0$ for design rainfall events up to 20–30 mm, if appropriate moisture storage capacity is provided by the substrate; (2) runoff volume is determined with $\mathrm{CN}=84$ for larger rainfall events, or for events that exceed the actual moisture storage capacity. $C_v$ increases with rainfall depth ($P$), and may be reasonably predicted for 16 living roofs by $C_v=a*\exp (b/P)$, where regression coefficients $a$ and $b$ were empirically determined for each climate zone. CN or $C_v$ values are considered best fit, but they are generally poor representations of actual living roof hydrology. Further work is required to develop living roof specific, verified continuous simulation computer-modeling techniques and to quantify the role of the plants in stormwater control.

Determining the impact of catchment flooding requires an estimate of extreme spatial rainfall intensity. Current flood design practice typically converts a point estimate of rainfall intensity into a spatial rainfall intensity using an areal reduction factor, assumed constant across an entire region. Areal reduction factors do not explicitly consider regional variations in extreme rainfall. Here, a new approach for spatial estimates of extreme rainfall is introduced that directly incorporates the spatial area (A) into an intensity-frequency-duration relationship (IFD). This IFDA approach uses spatial rainfall fields to overcome shortcomings of the areal reduction factor by explicitly incorporating spatial variations in the extreme rainfall intensity. The IFDA approach is evaluated for 11 case study regions in Australia, across climates (tropical to Mediterranean), areas ($25–\mathrm{7,225}{\mathrm{km}}^2$), durations (1–4 days), and average recurrence intervals (ARI 2–100 years). The change in extreme spatial rainfall with respect to area varies markedly within each region suggesting that constant areal reduction factors for a region are inappropriate. Constant areal reduction factors are shown to underestimate extreme spatial rainfall intensities by 5–15%. The IFDA approach avoids these biases and is a promising new technique for use in design flood estimation.

This study addresses the estimation of flow-duration curves (FDC) in ungauged sites through the catchment classification. Forty-six catchments in the Upper Po river basin (Italy) were analyzed and classified through two different frameworks: the first scheme consists of the application of two clustering methods in a series considering six streamflow signatures, and the second one treats indexes of climate, physiography, soil, and land-use with the same clustering procedure. Catchments have been classified into three homogeneous groups: the first one is characterized by the lowest runoff and flash-flood events, the second one includes maximum runoff, and the third one shows intermediate behaviour. The estimation of FDCs was done using a lognormal distribution, whereas the regionalization was constructed applying a stepwise multiple linear regression, followed by a leave-one-out cross-validation. The results show great performance improvement when the regionalization model is found by taking account of the three different hydrological classes, with a mean absolute percentage error that decreases from 11% for the single region case to 7% in the three homogeneous regions case.

One of the key inputs of a hydrological model is the potential evapotranspiration (PET), which sets an upper limit to evapotranspirative water demand. However, limited data availability often challenges the choice of a PET estimation method, which in turn affects the PET estimates as well as the water balance (WB) components. The objectives of this research are (1) to evaluate the use of different sources of weather input data to derive PET: Climate Forecast System Reanalysis (CFSR) data, Water and Global Change (WATCH) data, and data generated by the weather generator of the soil and water assessment tool (SWAT) (SWAT–WG); and (2) to investigate the effects of the Penman–Monteith and Hargreaves (HG) methods on WB components using a SWAT-based model for the Upper Mara Catchment (Kenya). It is shown that PET estimations using the CFSR, WATCH, and SWAT–WG data sets compare well with the average annual and seasonal PET estimates from local observations over a period of 20 years. This shows the potential of global reanalysis climate data sources for the computation of PET in data-limited catchments. The SWAT models forced by these data sets and by gauged rainfall show a modified Nash–Sutcliffe (${\mathrm{NS}}_{\mathrm{m}}$) efficiency ranging from 0.6 to 0.72 for the simulation of the flow, depending on the selected PET estimation method. Unlike water yield, the other WB components simulated by the SWAT models (ET, deep aquifer loss, and reevaporation from the shallow aquifer) vary in magnitude, depending on the data and methods being used. The sensitivity analysis and the calibration results show that the model parameters are sensitive to the choice of the PET estimation method. Therefore, for catchments where parameterization is a challenge owing to data scarcity, it is crucial to consider the appropriate PET estimation method for a realistic modeling of the hydrological processes. In our case study, the HG method gives more robust and realistic ET estimations.

It is generally recognized that fens and the rare species they support can only be effectively managed and protected by treating them as part of a larger, connected groundwater system. However, this underlying groundwater system is often not well understood. In this research, a geographic information system (GIS)-enabled, hierarchical modeling approach was applied to simulate the multiscale groundwater flow systems for several critical habitat units of the endangered Hine’s emerald dragonfly (HED) in Michigan. In particular, models for six habitat units were developed and calibrated to static water level measurements. Reverse particle tracking was used to trace source water and delineate the groundwater contribution areas for the habitat units. The results reveal that the units obtain water from regional groundwater mounds through direct or cascading connections. The travel time for groundwater from the mounds to reach the habitat units varied between 25 days and almost 11 years. These findings suggest that the current approach to fen conservation must be reassessed, from the protection of individual fens to conservation of the broad recharge areas and the multiple fens they support.

To evaluate the alteration of the hydrologic regime in the lower Yellow River caused by the different operational modes of the Sanmenxia and Xiaolangdi Reservoirs, daily stream flow data obtained from the Huayuankou Hydrological Station between 1949 and 2010 were analyzed. The hydrologic regimes before and after different reservoir operations were quantitatively analyzed using the range of variability approach (RVA) based on the indicators of hydrologic alteration (IHA). The results showed that the hydrologic regime of the lower Yellow River changed significantly after the reservoirs began operation, In addition, there was a significant difference in ecohydrological characteristics between operation modes. This research further explains the hydrologic regime of the river. It can be used for future water resources management and ecological scheduling within the lower Yellow River Basin.