Journal of Hydrologic Engineering

Droughts cause severe damage in terms of both natural environments and human lives, and hydrologists and water resources managers are concerned with estimating the relative frequencies of these events. Univariate parametric methods for frequency analysis may not reveal significant relationships among drought characteristics. Alternatively, nonparametric methods provide local estimates of the univariate and multivariate density function by using weighted moving averages of the data in a small neighborhood around the point of estimation and opposed to parametric methods. A methodology for estimating the return period of droughts using a nonparametric kernel estimator is presented in order to examine the univariate as well as the bivariate behavior of droughts. After evaluating and validating a nonparametric kernel estimator, a drought frequency analysis is conducted to estimate the return periods of droughts for the Conchos River Basin in Mexico. The results show that, for the univariate analysis, the return periods of the severe drought occurring in the 1990s are 100 years or higher. For the bivariate analysis, the return periods are approximately 50 years for joint distributions and more than 120 years for the conditional distributions of severity and duration.

Droughts may be represented by two main characteristics—duration and severity. In this paper, a general methodology to evaluate the frequency and risk of the occurrence of droughts is presented using a bivariate drought characterization. The theory of runs is applied to model drought recurrence as an alternating renewal process, describing droughts simultaneously in terms of their durations and severities. Short historical records usually do not allow reliable bivariate analyses. However, tree ring reconstructions of droughts provide information about past events, allowing the analysis. An approach to adapt and include dendrochronology reconstructions combined with historical records to characterize droughts is presented. The proposed approach uses the stochastic structure of the residuals of paleo reconstructions to generate equally likely representations of past drought events. The procedure was applied to paleo and historical records in Texas Climatic Division 5 and compared with univariate analyses. The application shows the bivariate analysis advantages in drought characterization.

Using a reference Froude number, a nonlinear convection-diffusion equation was derived from the Saint-Venant equations of continuity and momentum, and was solved by a mixing-cell method. The method involves discretizing the nonlinear diffusion equation in space and transforming it to a first-order nonlinear ordinary differential equation where the optimal space interval is obtained to be the same as the characteristic reach length. The nonlinear ordinary differential equation was solved by the fourth-order Runge-Kutta method. The method was tested with numerical examples, and compared with the looped-rating Muskingum-Cunge model and a lambda scheme. The outflow hydrographs produced by this method were of comparable accuracy.

During the storm duration, the effects of surface resistance on the developing and receding overland flow depths $\left(h_j\right)$ on different flow parameters like the overland flow resistance coefficient $\left(N_j\right)\text{,}$ flow velocities $\left(v_j\right)\text{,}$ Reynolds number $\left(R_j\right)\text{,}$ and Froude number $\left(F_j\right)$ have been studied for the six natural catchments (0.012–92.5 km²) located in different agroclimatic regions of India. The kinematic wave (KW) equations are used for simulation of overland and channel flows using explicit methods for developing numerical solutions for the estimation of flow parameters at short durations. For the complete storm duration $h_j-N_j$ relationships have been found to form hysteresis loops. To predict resistance coefficients, simple $h_j-N_j$ relationships have been worked out separately for the rising and depleting overland flow conditions. Computed hydrographs simulated by incorporating these equations in the KW model agree well with the observed ones. The overall applicability of the suggested approach is successfully demonstrated under ungauged situations as well.

This study presents research on changes in hydrologic characteristics of disturbed land surfaces that have been treated with dust suppressants. Disturbed land surfaces, such as construction sites and unpaved roads, are sources of fine particulate matter. The application of dust suppressants affects the runoff characteristics as well as the water quality of the runoff. The changes in runoff characteristics were investigated in the field using a rainfall simulator on plots treated with 11 different dust suppressants. The rainfall simulation system was able to provide a uniform distribution of rainfall over a 2.4×2.4 m (approximately) plot at relatively low rainfall intensities (21 mm/h). Results of the study indicate changes in runoff rates and volume, and the timing of runoff initiation. The majority of the plots had higher runoff volumes and an earlier time of runoff initiation as compared to the control plot. The total suspended solids in the runoff were reduced for the majority of the plots. Extrapolation of the results to the Las Vegas Valley watershed indicates that the use of dust suppressants on large areas could significantly impact the amount of runoff.

Pumping of groundwater near a stream can induce infiltration of stream water into the surrounding aquifers. Analysis of the migration of the infiltrated stream water to the pumping well is important to better understand stream-aquifer interactions. The paper analyzes the effects of aquifer anisotropy on the migration process of infiltrated stream water to a partially penetrating well. MODFLOW is used to simulate the transient groundwater velocity fields, and MODPATH is used to record the locations of water particles. Pathlines were plotted over a cross section to show the hydraulic connectivity between the well and the stream for various levels of aquifer anisotropy. Travel times, infiltration rates, and fractions of pumped river water were determined to characterize the migration process. Generally, the movement of the infiltrated stream water is slow; the water can take several months to arrive at a well located a short distance from a stream. Results suggest that the rate of produced stream water at the well is higher for the anisotropy $K_h/K_z=10$ and 20 (ratio of horizontal to vertical hydraulic conductivity) than for $K_h/K_z<10\text{,}$ or $>20\text{.}$ On the other hand, when $K_h/K_z$ is between 20 and 100, the first water particle that gets to the pumping well needs a shorter travel time than that for other $K_h/K_z$ values. A gaining stream can significantly reduce the rate of stream infiltration and produced stream water. Areal recharge provides an additional source to the well, thus reducing the rate of stream infiltration as well as the rate of produced stream water.

Precipitation data collected at fixed time intervals will most likely miss true maximum accumulations for durations equal or close to the sampling interval. This becomes a problem when fixed-interval rainfall data are used for frequency analysis. Sampling adjustment factors (SAF) are often used to correct for this mismatch between true and observed maxima. An SAF is the average ratio of the true maximum accumulation to the maximum given by a fixed-interval gauge record. This paper uses high temporal-resolution data from ALERT-type rain gauges in the Kansas City area to derive an empirical relationship for SAF versus the sampling ratio, which is the ratio of the duration of interest to the sampling interval. This relationship is consistent across durations ranging from 1 to 24 h, and is in good agreement with other studies.