Journal of Hydrologic Engineering

Pumping at a large rate can convert a confined flow to a confined–unconfined one in a confined aquifer. In this paper, a new semianalytical solution is proposed to investigate the mechanism of transient confined–unconfined flow under the non-Darcian condition in a fully penetrated confined aquifer. By using Izbash’s equation, a new linearization method was developed to approximate the nonlinear terms of the mathematical model of pumping-induced flow. The solution was derived by using the Laplace transform. The acceptability of the proposed solutions was verified by comparisons with numerical solutions by COMSOL Multiphysics and an analytical solution. The effects of the non-Darcian index, hydraulic conductivity, and the storativity ratio on developments of drawdown and the transient unconfined region were especially investigated. It is indicated that the non-Darcian index and the hydraulic conductivity have a positive effect on the drawdown in the confined region and a negative effect on that in the confined region, respectively. Otherwise, the drawdown simulation is negatively related to the storativity ratio. The result of this paper offers much-needed insights in the field of mine dewatering and the application of geological and hydrological conditions.

Accurate modeling of infiltration losses is vital for runoff estimation and thus the development of flood design/protection criteria and water management schemes, etc. In design flood practices, the initial abstraction and constant loss (IACL) method has been widely applied due to its simplicity. However, due to a lack of physical equivalent properties, the IACL method is often subject to issues in parametrization and has large dependency on calibration efforts for storm events. Despite the wide range/variability of IACL values, a single set of IA and CL values is normally adopted for specific flood frequency, which may introduce uncertainty and bias in resulting peak streamflow. In this study, we identified a total of 2,036 rainfall-runoff events for 18 watersheds in North Central Texas to estimate the total losses with their IA and CL components based on time-series of mean areal precipitation (MAP) and streamflow data. Threshold behavior is found for all studied subbasins between the summation of gross rainfall and antecedent soil moisture versus runoff depth: below the threshold, runoff depth is minimal; whereas above it, runoff is largely linearly correlated with the summation of rainfall and antecedent soil moisture. This finding provides a convenient way to estimate/predict total loss or runoff depth given MAP and antecedent soil moisture. In addition, this study shows that the IA and CL values can be approximated by the gamma and Weibull distributions, respectively. The fitted distributions of IA and CL values can be applied in a Monte Carlo simulation framework to stochastically simulate numerous rainfall-runoff events for a flood frequency analysis.

It is time to shift our paradigm of small watershed design from a graphic (or tabular) to a theoretical method, because (1) the recent general unit hydrograph (UH) model can convert a design hyetograph to a design hydrograph simply, accurately, and theoretically; (2) the Natural Resources Conservation Service (NRCS) has recommended that the National Oceanic and Atmospheric Administration (NOAA) Atlas 14 rainfall data of depths and distributions at a specific site, which is often called the NRCS-NOAA rainfall distributions, should be used for small watershed design if runoff data are unavailable; and (3) in this paper, we have presented a design procedure that formulates design hydrographs from the NRCS-NOAA Atlas 14 rainfall distributions and the general UH model automatically, using the MATLAB convolution function. A literature review indicated that the current practice for design hydrographs in small watersheds from hyetographs is laborious because both hyetographs and UHs are discrete. By contrast, the theoretical general UH model can significantly simplify this process. In this research, we first found analytic design hydrographs from rectangular and triangular hyetographs, which were next used to validate the MATLAB convolution method. We then proposed a double exponential rainfall distribution for both asymmetric and symmetric hyetographs. After that, we modified the symmetric exponential distribution model to describe NRCS-NOAA Atlas 14 data for site-specific hyetographs, which are finally convolved with the general UH model for site-specific design hydrographs, using the MATLAB convolution function. It is noteworthy that the proposed method extends the classic rational method from the peak discharge to the whole hydrograph; and it is valid for both continuous and discrete hyetographs. Hence, it provides a powerful tool in urban development, agriculture land use, roadway planning, and airport construction; it can also be used to evaluate an existing drainage system under various meteorologic–hydrologic conditions. Finally, we expect that this research will shift our current design practice and university UH teaching from an empirical to a theoretical paradigm in the near future.

The main objective of this study is to predict the transition probability of different classes of droughts in Iran. The daily precipitation data of 40 synoptic stations in Iran, for a period of 35 years (1983–2018) were used to access the main objective of this study. The effective drought index (EDI) was used to recognize the abundance of various drought classes in Iran. Using cluster analysis on the monthly values of EDI, Iran was divided into five separate regions. Homogenous and nonhomogenous Markov chains were used to extract four features, including the probability of occurrence of each class of drought severity, the average expected residence time in each class of drought severity, the average time of the first expected passage of different categories from drought to a wet class, and short-term drought prediction for five regions of drought in Iran. Results suggested that the probability of occurrence of various drought classes decreased with the increase of drought severity; therefore, the highest probability of drought pertained to the drought class. In all five regions under consideration, the homogenous Markov chain has demonstrated the continuity of the severe drought class more than other classes; in the nonhomogenous Markov chain, however, when the beginning month is April, the highest continuity of drought is noted in the severe drought class. The average time of the first expected passage to achieve a no-drought class increases with the severity of the beginning class of drought. Consistent with the nonhomogenous Markov chain formulation, the average time of the first expected passage from each drought class to the wet class is more significant in the beginning month of April than in other months. In regions where the precipitation regime is seasonal and limited to one or two seasons, as in Southeastern Iran, few diverse states of droughts are noted; as a result, drought predictions will be more uniform, and the continuity of their various drought classes will be far greater. However, in areas where their precipitation regime is not limited to a specific season and precipitation occurs all year long, as in the Southern Caspian Sea, the predictions are more diverse, and continuity of the various drought classes is less; thus, the accuracy of the nonhomogenous Markov chain predictions can be more significant for arid and semiarid regions.

The nonstationary hydrologic processes due to climate variability and intensification of human activities are challenging and questionable for researchers. This study investigates nonstationary partial duration series (PDS) records for the period 1971–2017 at 14 hydrological stations across the Gorganrood River Basin, Iran. The Gorganrood Basin is very diverse in terms of climate such as humid, semihumid, Mediterranean, semiarid, and arid climates. Change points are analyzed using the Pettitt technique. Trends of PDS are detected using the Mann–Kendall method. The nonstationarity of the PDS series is examined by generalized additive models for location, scale, and shape (GAMLSS). Results indicate that abrupt changes are significant for the PDS series in the Gorganrood River Basin. Change points have a considerable effect on trend detection, and these may be attributed to the fact that an abrupt increase or decrease in mean values affects trend changes. In addition, the GAMLSS results showed that the most suitable performance distribution was LNO distribution and then RGE distribution in the Gorganrood River Basin. On other hand, the GAMLSS model and the Pettitt test have good capability in detecting stationary and nonstationary PDS series.

Abstract

Daily reference evapotranspiration (${\mathrm{ET}}_{\mathrm{o}}$) is an essential component of the hydrologic processes of surface water generation from precipitation. Iraq suffers from a scarcity of surface water due to the erection of many dams on the Tigris and Euphrates Rivers by neighboring countries on upstream locations along these rivers. Therefore, ${\mathrm{ET}}_{\mathrm{o}}$ values should be measured more accurately in Iraq. In this study, the Penman–Monteith (PM) equation was used as the benchmark to calculate the standard values of ${\mathrm{ET}}_{\mathrm{o}}$ for 103 stations in Iraq using a daily meteorological data set from 2010 to 2019 (5 years each for calibration and validation periods). Three forms of the Hargreaves–Samani (HS) equation were evaluated for estimating the ${\mathrm{ET}}_{\mathrm{o}}$ values. The first two equations have common and optimum coefficient sets (HSC and HSO equations, respectively). The third equation is proposed in this study and modifies the HS equation by incorporating a wind speed variable with an optimum coefficient set (HSW equation). The coefficients of the HSO and HSW equations were optimized in terms of the Nash–Sutcliffe efficiency (NSE) coefficient and the coefficient of determination ($R^2$) using the shuffled complex evolution (SCE) optimization method. The respective success rates of ${\mathrm{ET}}_{\mathrm{o}}$ estimation during the calibration and validation periods are 37% and 39% when using the HSC equation, 96% and 95% with the HSO equation, and 100% and 100% with the HSW equation. Results indicated that the HSO and HSW equations enhance the estimation of ${\mathrm{ET}}_{\mathrm{o}}$ values relative to the HSC equation, and the HSW equation performs best among the three. Therefore, incorporating the wind speed in the HS equation with the optimum coefficient set increases the robustness of its predictive capacity for all regions of Iraq, including those with high altitudes.

Practical Applications

The applicability of the Hargreaves–Samani equation, which depends only on temperatures, was investigated using common coefficients in estimating daily evapotranspiration values for 10 years (2010–2019) in 103 regularly distributed stations covering the entire area of Iraq. It was found that the common form of the Hargreaves–Samani equation failed in most regions of Iraq except the northern and northeastern regions. Therefore, the Hargreaves–Samani equation was calibrated with new coefficients for Iraq in lieu of the common coefficients. The Hargreaves–Samani equation with the new calibration coefficients was more successful in calculating the evapotranspiration in 95% of all stations across Iraqi area; the exceptions were some stations located in northern and northeastern regions, in which the common equation succeeded. Thus, to obtain an equation that remains applicable for the entire area of Iraq, the Hargreaves–Samani equation was developed further by incorporating the wind speed and later calibrated to obtain the appropriate coefficients for Iraq. This developed Hargreaves–Samani equation was very successful in estimating the values of evapotranspiration in all regions of Iraq.

Nonstationarity in hydrology has aroused great concern among people, and various influence factors have been proved to challenge the assumptions of the traditional hydrological analysis. For the selection of a reasonable flood frequency model and rationality of hydraulic engineering design, it is of great significance to study the variation characteristics of rainfall and floods and their relationship under the nonstationary condition. Taking the Yue River Basin, a mountain basin in northwest China, as an example, the nonparametric Mann-Kendall test and moving $t$-test methods were used to test the temporal trends and mutation of hydrological variables during the recent 53 years. The recession curve was derived from the historical flood series by the genetic algorithm, and the flood hydrographs were separated by the constant-slope base flow separation method. The results showed that the annual rainfall and runoff in the Yue River Basin during the recent 53 years exhibited insignificant increasing and decreasing trends, respectively. The abrupt change point of annual runoff series occurred in 1985. The average proportion of underground runoff changed from 21% before 1985 to 17% after 1985, and the relationship between rainfall and floods became weakened after 1985, indicating that the stationarity of flood was challenged.