Journal of Hydrologic Engineering

To reduce the ineffective evaporation of plain reservoirs in inland arid areas and improve the effective utilization of reservoirs, this work uses floating plates and floating balls as the main covering materials to reduce water surface evaporation. This paper investigates the motion characteristics of two covering materials with different structures under wind and waves through laboratory and field experiments. It analyzes the relation of evaporation inhibition rate of the floating plates and its area and thickness, and adopts the method of adding a counterweight to solve the problem of irregular rotation and easily rolling of the floating balls (the floating ball that serves as the added counterweight is called a tumbler floating ball). Then, it discusses the influence of diameter, counterweight, density, and type of the floating ball on evaporation inhibition rate by using the orthogonal design method and establishes a calculation equation of the water surface evaporation inhibition rate, which is applicable to the experiment area. Results show that: (1) the evaporation inhibition rate of the floating plates is positively correlated with the surface area and thickness, and (2) the influence degree of the four factors on the evaporation rate of the floating balls is diameter > counterweight > density > type of floating balls.

Bioretention facilities have commonly been used to reduce the runoff volume, peak discharge, and pollution in runoff to the downstream drainage system during sponge city construction. The curb inlet interception efficiency determines how much of the runoff from the road surface enters the bioretention cell directly. Most previous studies have focused on the method of designing the curb inlet itself, whereas few have paid attention to evaluating the curb inlet efficiency in unsteady rainfall situations. In this study, a full-scale rainfall simulation system and a road surface with a curb inlet were built to examine the curb inlet efficiency under such conditions. It was found that methods from the literature for predicting the curb inlet efficiency produced large errors in small rainfall (low runoff depth of upstream inflow) situations. Therefore, a modified method was proposed based on experimental results to evaluate the curb inlet efficiency more accurately under unsteady rainfall situations.

Wadis, an Arabic term referring to a wadi, in the Eastern Desert of Egypt have undergone rapid unsustainable development in areas vulnerable to flash flooding and water scarcity. To reduce the risk of damage and loss of life from flash floods to a wadi’s new residents, the priority is to develop mitigation strategies with distributed (watershed scale) or concentrated (localized) mitigation structures to promote sustainable development. The focus of this study is to develop a new approach that will help in assessing various flood mitigation scenarios in Wadi Abadi in the Eastern Desert of Egypt. The proposed approach considers the limited data availability in the wadi system and utilizes spatial analysis and an in-house developed distributed hydrological model, Hydrological River Basin Environmental Assessment Model (Hydro-BEAM), upgraded with a reservoir routing module. Sensitivity analysis of the key Hydro-BEAM model parameters indicated that the most significant parameters controlling the wadi flood peaks are soil thickness and porosity, runoff coefficient, subsurface layer outlet coefficient, and channel roughness. Digital Elevation Model (DEM) data and satellite imagery were utilized to propose the locations and derive design characteristics of the mitigation structures. The mitigation strategies evaluated in this study resulted in a peak flood reduction percentage of 90% and 86% for the distributed and concentrated dam scenarios, respectively. The results show that a group of distributed dams could outperform a single concentrated dam when flood mitigation and water resources management aspects are considered in the wadi region, where the distributed dams scenario has 600% more protected area and 21% more reservoir volume than the concentrated scenario (i.e., use of one dam). However, the concentrated dam scenario may have advantages due to the cost of construction and operations. The proposed approach can assess the flood risk reduction due to different mitigation measures and provide strategies for development and planning in wadi regions.

Runoff prediction plays a crucial role in the scheduling and management of water resources. A novel enhanced long short-term memory (LSTM) model called LN-LSTM-PSO is proposed by integrating layer normalization (LN), LSTM network, and particle swarm optimization (PSO) to improve prediction accuracy. The model in general is a data-driven model, and compared with the traditional mechanism model, its most notable advantage is that it has a flexible structure. In the enhanced LSTM model, LN is added to the hidden layer of the LSTM model, and PSO is used to determine the optimal parameters. The application of the proposed enhanced model is illustrated using hydrological and meteorological data from Jiulong River Basin in Fujian Province, China, to test model accuracy. Results indicate that the proposed model has high accuracy. Specifically, the enhanced LSTM model has a root mean square error of 0.142, mean absolute percentage error of 0.032, Nash–Sutcliffe efficiency of 0.968, and determination coefficient of 0.968. The enhanced runoff prediction model exhibits improved performance compared with a support vector regression model, an artificial neural network, a recurrent neural network, and a long short-term memory network. LN can accelerate the convergence speed of the LSTM network, and PSO substantially increases model performance by automating the hyperparameter selection. The virtual runoff input of the current time step can also remarkably improve model accuracy.

A two-dimensional diffusive wave framework is proposed for modeling interaction between flow through and outside porous media. The depth-integrated parabolic model was developed with an assumption of zero temporal/convective accelerations, making it appropriate for field-scale simulations. The effects of bed shear arising from the bathymetry, roughness, and properties of granular media are consolidated into a single hydraulic diffusivity coefficient. The equation is resolved in a structured finite-volume grid with implicit time stepping. The proposed framework was validated with a standard analytical solution and small-scale experimental results. A synthetic test case containing irregular ground surface demonstrated the capability of the proposed model for real-time simulation.

In the context of urban flood management, it is necessary to estimate flood depth and area accurately. Therefore, development of a flood simulation models with acceptable accuracy could be the first step to fulfill this goal. This study developed the Storm Water Management Model Two-Dimensional Cellular Automata (SWMM-2DCA) to simulate inundation characteristics and flow interaction between urban drainage system and surface runoff. The SWMM is used for rainfall-runoff simulation and one-dimensional channel flow routing. The 2DCA model is applied for simulating two-dimensional surface flow as well as the flow interaction between drainage system and catchment surface. The performance of the developed 2D hydraulic model was evaluated using one analytical solution and three benchmark tests. The obtained results were compared with those of other hydraulic models, and indicated acceptable accuracy. The developed model was used to simulate flood in a study area located in Tehran, Iran. The obtained results were compared with the recorded inundation maps, and confirmed the accuracy of the proposed model.

Stream depletion is the reduction in flow rate in a stream due to pumping in an aquifer that is hydraulically connected to the stream. We developed a semianalytical expression for stream depletion for pumping in a homogeneous aquifer, with an infinitely long, straight stream with a streambed conductance, $C$, that varies cosinusoidally in space and time in the range $C_L\le C\le C_H$. The wavelength of the spatial variations is equal to twice the distance between adjacent pools in a pool and riffle sequence, and the period of the temporal fluctuations represents alternating high and low flows. These spatiotemporal variations in streambed conductance produce temporal fluctuations of stream depletion superimposed on a trend that increases at a decreasing rate. Certain combinations of streambed and aquifer hydraulic parameters lead to exaggerated stream depletion, in which the temporally fluctuating stream depletion is not bracketed by the amount that would be obtained with steady, homogeneous streambed conductance of $C_L$ and $C_H$. After sufficient time has passed, the same parameter sets produce excessive stream depletion, in which stream depletion exceeds the pumping rate at certain times. The degree of exaggerated stream depletion increases with the distance between pools, and is high if the temporal period of fluctuation matches the times of high rate of change of stream depletion.

The estimation of long-term flow duration curves (FDC) and annual flow duration curves (AFDC) are frequently required for water resources planning and management at ungauged catchments. The index flow framework provides a simple mathematical model for linking both approaches in regionalization procedures. However, the reliable transfer of information may be unfeasible with established regression techniques due to the complex structure of variation between the statistical model parameters and catchments’ characteristics. This paper explores the evolutionary polynomial regression (EPR) technique for identifying regional equations for the parameters of the index flow model. Results showed that, at the expense of increased structural complexity, EPR might be an effective and robust tool for transferring information to ungauged sites. Long-term streamflow variability was relatively well captured under cross-validation, although the low flow regimes were misrepresented in most cases. As for the AFDCs, the model proved able to synthesize flow regimes in typical and wet years but failed to do so in dry conditions. Despite these limitations, the proposed approach may constitute a useful tool for supporting water resources management at the regional scale.

Estimating discharges is a major challenge in water resources management, and techniques such as data assimilation (DA) can be used to improve these estimates. This study assessed application of the local ensemble Kalman filter (LEnKF) DA scheme within a large-scale hydrological-hydrodynamic model to improve discharge estimates. Different scenarios with assimilation and validation gauges were performed to obtain an optimal setup of localization, ensemble size, assimilation parameters, and observation type (discharge or logarithm of discharge). These parameters were used to analyze the estimated discharge series and reference discharge values for maximum, minimum, and average flows. Results showed that joint perturbation of precipitation and groundwater reservoir volume leads to the most sensitive model responses. Furthermore, using the adequate setup of LEnKF parameters and assimilating the logarithm of discharge, better estimates of reference discharge values were obtained with the DA scheme when compared to a simple regionalization method, leading to reduction of errors of more than double in many cases.

In the continually climate change scenario, it is of great concern to revisit, rethink, and improve the existing computational aspects of drought indexes. In general, the commonly used drought indexes do not encompass environmental changes. Hence, the primary objective of this study was to incorporate large-scale climatic oscillations in developing the nonstationary Standardized Precipitation Index (${\mathrm{SPI}}_{\mathrm{N}}$) and Reconnaissance Drought Index (${\mathrm{RDI}}_{\mathrm{N}}$). The nonstationary modeling of the drought index is performed using the generalized additive model for location, scale and shape (GAMLSS) over 103 grid points covering Maharashtra state in India. The computed nonstationary drought indexes are then used to examine the spatiotemporal variability of drought over the province. The outcomes from the analysis indicate that nonstationary modeling outperforms a stationary approach over the study area for different drought scales. In addition, notable differences are observed while comparing the different drought properties using stationary and nonstationary drought indexes. A comparative analysis of the historical drought that occurred in 2013 reveals that nonstationarity in the meteorological data sets cannot be ignored for developing a sustainable mitigation and adaptation strategy against drought hazard. The proposed nonstationarity-based drought indexes for Maharashtra can be a feasible alternative of drought assessment in a changing climate scenario.