Journal of Hydrologic Engineering

Statistical criteria used to evaluate the best distribution fit give large weights to the center of distributions. This is, however, not consistent with the objective of frequency analysis which is to estimate the quantiles with large return periods. In this study, the usefulness of a recently proposed decision support system (DSS), which defines the class of distributions prior to a model selection practice with respect to tail behavior of sample data, was investigated using three large hydroclimatic databases [Reference Hydrometric Basin Network (RHBN), precipitation, and UNESCO]. According to the DSS, although a considerable majority of RHBN flood sample data belonged to Class C (regularly varying distributions), a slight and great majority of UNESCO discharge as well as annual precipitation sample data, respectively, belonged to Class D (subexponential distributions). This difference in classification is attributed to the nature of studied variables: RHBN sample data represent extreme events with heavy tails (Class C), whereas UNESCO and especially precipitation sample data come from relatively lighter tailed processes and therefore belong mostly to Class D distributions. The impact of classification on model selection was the largest for the RHBN and the smallest for precipitation sample data. This confirms that discriminating between classes of competing models prior to model selection is critical when the sample data come from extreme events. Observed inconsistency in model selection for the RHBN database resulted in an underestimation of quantiles in more than 2/3 of the cases regardless of class of distributions. For the UNESCO and precipitation data, however, inappropriate model selection resulted equally in over- and under-estimation in Class C, whereas it resulted in underestimation of quantiles in Class D in the majority of observed inconsistencies. It can be concluded that an inappropriate model selection due to choosing a wrong class of distributions leads, in the majority of cases, to an underestimation of the quantity of the variable under study which is associated with a higher socioeconomy risk compared to that corresponding to an overestimation of a specific quantile. It was also observed that model selection using Bayesian Information Criterion (compared to Akaike Information Criterion) is more consistent with tail behavior of the natural processes.

To prevent erosion of polluted land and discharge of contaminated groundwater and surface water into the Venice Lagoon, a 57 km long cutoff wall has been designed by the Venice Water Authority and is currently under construction along the canal banks of the Venice, Italy industrial harbor. To predict the impact on the hydrologic regime and mitigate the related inundation hazard in the nearby urban areas, a complex three-dimensional finite-element model has been developed and implemented over the multiaquifer system down to a depth significantly larger than the wall bottom. The model is initially calibrated against the regional piezometry and then refined locally to reproduce the groundwater volume drained along a 5-km long bank of a harbor canal already bounded. Major results from the simulations show that after the wall completion the subsurface discharge into the lagoon is successfully abated by as much as 85% relative to the preexisting rate with, however, an expected 1-m increase of the water table in the inland city of Mestre, Italy thus pointing to the need for implementing a drainage trench upstream the wall to properly reduce the raised groundwater level. The model would also indicate that the shallowest aquifers may receive underground water from a large number of old deeper boreholes abandoned in the past and not properly sealed. From a more general perspective, the present study constitutes an important example where the reliable and sustainable design of a complex engineered structure bound to impact significantly on the surrounding environment can be much helped and improved by the use of advanced numerical models capable to capture the essential features of the underlying geohydrological processes.

This study investigated the sediment entrainment and critical shear stress in gravel-bed rivers. Measured rates of bed load transport were used to estimate the Shields stress parameter. The computed parameters were compared to those derived from the Meyer-Peter-Muller method. The agreement between these methods was good and the values of ${\tau }_{\ast c}$ obtained by the two methods can be justified by the Shields diagram and decreased with increasing $d_{50}/d_{90}$ (where ${\tau }_{\ast c}$ is critical Shields stress, $d_{50}$ is sediment size with 50% particles finer and $d_{90}$ sediment size with 90% particles finer).

The present paper presents a generalized solution for the hydrologic and hydraulic design of small to medium-sized storm-water pumping stations. The solution enables determination of pump capacity and the corresponding storage capacity. The benefits of the solution include: (1) the ability to consider the effects of storm duration rather than the fixed hydrology assumed in other methods; (2) a simpler and more intuitive design procedure than other available methods; and (3) enabling the calculation of storage requirements independent of the geometry of the wet well and any inundated upstream area. The relation of the method presented herein to several other available methods is presented and the other methods critiqued conceptually and by example. The example is favorably tested using commercial software, and the constant-pumped-discharge assumption of the example is further tested using that software for an actual pump discharge-total dynamic head and system flow-head relationship. Extension of the methods presented in this paper to more complex situations is discussed. The importance of considering different storm durations is emphasized.

This paper presents an analytical solution of linearized Boussinesq equation characterizing transient groundwater flow in a downward sloping unconfined aquifer of semiinfinite extent. The aquifer is in contact with a water body of constant water level at one end and receives localized vertical recharge at a constant rate from a linear recharge basin of finite width. In this idealization, the recharge basin can be located anywhere in the domain, thus its location is treated as an additional parameter. The flow equation is solved using Laplace transform to obtain transient expressions for aquifer piezometric head and flow rate at the interface. The effects of bed slope and the location of recharge basin on the phreatic surface are illustrated by taking a numerical example. The analytical results obtained for horizontal as well as sloping aquifers show that there is considerable increase in the mound height as the recharge basin is shifted away from the interface of aquifer and water body. Moreover, contrary to the results of a horizontal aquifer, the mound growth in a sloping aquifer stabilizes in considerably lesser time period. The computation of mound height for small sloping aquifers is outlined using a numerical method and the sensitivity of the flow rate with respect to the variation of various parameters is analyzed.

Application of Soil Conservation Service’s (SCS) dimensionless unit hydrograph method for ungauged basins in Indiana yields very high peak flows and short time to peaks for the northern region, thus producing unrealistic flow estimates for design purposes. It is hypothesized that the overestimation of peak flows in northern region using SCS method is due to the flat terrain and high surface storage caused by the Wiconsinan glaciations. To incorporate the slope and storage characteristics, the application of Clark synthetic unit hydrograph (SUH), which incorporates time of concentration $\left(t_c\right)$ and a storage parameter $\left(R\right)$ to produce runoff hydrograph, is explored for Indiana. A statistical analysis of 29 geomorphic attributes and past storm hydrographs for thirty watersheds in Indiana show that watersheds in north, central and southern regions are statistically different in terms of slope and storage characteristics. A statistical comparison of Clark parameters ( $R$ and $t_c$ ) estimated for past storm events also support the effect of storage (higher $R$ ) in the north, and slope (higher $t_c$ ) in the south. Linear and nonlinear regression models of $R$ and $t_c$ against all geomorphic attributes for all watersheds yielded storage and slope attributes as significant independent variables, thus providing a way to incorporate slope and storage into hydrograph predictions for ungauged watersheds through Clark SUH. Additionally, regional regression of $R$ and $t_c$ with geomorphic attributes produced equations that included attributes related to storage and slope for north, and attributes related to land use, slope and stream network for central and southern regions. Validation of regression equations using new storm events for seven watersheds show that the performance of Clark SUH is the best for northern region followed by central and southern regions. The peak estimated by Clark SUH is more than 60% lower compared to SCS method for northern watersheds, but comparable to observed peak. Overall, the use of $R$ and $t_c$ estimated through regression for Clark SUH yield better results compared to SCS method for the entire state including central and southern regions, thus providing more confidence in hydrograph prediction for ungauged basins in Indiana.

Soil particle size distribution (PSD) (i.e., clay, silt, sand, and rock contents) information is one of critical factors for understanding water cycle since it affects almost all of water cycle processes, e.g., drainage, runoff, soil moisture, evaporation, and evapotranspiration. With information about soil PSD, we can estimate almost all soil hydraulic properties (e.g., saturated soil moisture, field capacity, wilting point, residual soil moisture, saturated hydraulic conductivity, pore-size distribution index, and bubbling capillary pressure) based on published empirical relationships. Therefore, a regional or global soil PSD database is essential for studying water cycle regionally or globally. At the present stage, three soil geographic databases are commonly used, i.e., the Soil Survey Geographic database, the State Soil Geographic database, and the National Soil Geographic database. Those soil data are map unit based and associated with great uncertainty. Ground soil surveys are a way to reduce this uncertainty. However, ground surveys are time consuming and labor intensive. In this study, an inverse method for estimating mean and standard deviation of soil PSD from observed soil moisture is proposed and applied to Throughfall Displacement Experiment sites in Walker Branch Watershed in eastern Tennessee. This method is based on the relationship between spatial mean and standard deviation of soil moisture. The results indicate that the suggested method is feasible and has potential for retrieving soil PSD information globally from remotely sensed soil moisture data.

Sensitivity analysis is an important tool that can be used for calibration of river flow models. Generally, friction coefficient is used as a calibration parameter for steady-state one-dimensional shallow water flow models. In this study, the local sensitivity analysis is used to derive a general rule for calibration of prismatic open channel models. For this, the sensitivity of the water depth to the friction coefficient is analytically derived for one-dimensional steady flow conditions in a wide rectangular channel. Also, the parameter of influence distance is defined to calibrate a channel reach using stage measurement at a given location. This characteristic distance allows 90% of the maximum possible variation in the sensitivity of the water depth to the friction coefficient to be captured. This parameter estimates the optimal length of a channel reach over which the friction coefficient can be calibrated from stage measurement. This length locates downstream of the stage measurement point in subcritical flow regime and upstream in supercritical flow regime.