Journal of Hydrologic Engineering

Green infrastructure (GI) practices are an effective means for improving the sustainability of stormwater management. Optimized combinations of GI practices with other management practices, such as detention basins, can maximize performance and cost effectiveness, and simple methods for identifying these combinations will promote more widespread use of GI. We created a spreadsheet-based decision-support tool to help designers to develop cost-effective stormwater management plans that integrate GI practices with detention basins. The hydrologic impact on detention storage of using GI practices is modeled with rainfall-runoff simulations. An optimization model for a detention basin was developed to be used in conjunction with the spreadsheet tool. We applied the tool to a representative case study site for which the actual design and cost estimates of stormwater infrastructure were known. The tool provided realistic results and the case study revealed that successive applications of the tool could easily provide the user with a site design that improved cost-effectiveness. A sensitivity analysis illustrated the critical trade-off relationship between GI costs and detention basin costs.

Unit hydrograph (UH) is widely used for predictions of flood hydrograph from a known storm. Its concept and theory are simple and straightforward, but its practical applications are cumbersome because it is discrete and inflexible for different rainfall durations. An internet search indicates that though Nash’s gamma function is widely accepted as a theoretical model, it is not a true form of instantaneous UH. Briefly, a simple, general, and analytic model for UH has not been found in the literature, which forms the objective of this research. To this end, we first make three hypotheses on instantaneous UH based on empirical observations; we next find a general unit-volume hydrograph for S-hydrograph that leads to analytic expressions for interval and instantaneous unit-volume hydrographs; we then apply the proposed method to simplify applications of the Soil Conservation Society (SCS) dimensionless UH. After that, we examine the proposed method with real-world data. We confirmed that the proposed general and analytic UH predicts flood hydrograph simply and accurately, and it agrees with data better than the classic Nash instantaneous UH model.

This study attempts to identify a threshold in the bias of potential evapotranspiration (PET) forcing data beyond which output from hydrological models will be significantly impacted. The sensitivity of a widely used conceptual rainfall–runoff model to systematic errors in PET inputs is investigated for a sample of 57 US catchments across energy- and water-limited regions. PET forcing data are biased by a constant factor ranging from $\pm 5\%$ to $\pm 25\%$. The sensitivity of hydrologic models to PET data quality was found to be primarily driven by the long-term ratio of actual evapotranspiration (AET) to PET of catchments, which determines the energy availability of catchments. Energy-limited catchments were more sensitive to PET errors than water-limited catchments, and the PET error threshold was found to decrease along the water- to energy-limited continuum. Moreover, model performance of rainfall–runoff models was found to be more sensitive to negative PET biases than to positive PET biases. In practice, this means negatively biased PET causes catchments to artificially shift toward energy limitation, resulting in higher model sensitivity. Given the decreasing pattern of PET error threshold in catchments along the water- to energy-limited continuum, energy availability of catchments can be used as a predictor for the requirements of accuracy in PET data for conceptual hydrological models.

The present study aims to develop a steady two-dimensional suspended sediment transport model in an open channel for turbulent flow-carrying sediments. In such a flow, if sediment concentration is high, hindered settling occurs, meaning that the settling velocity of a particle reduces than that in clear water flow and should be considered in the mathematical modeling. Inclusion of hindered settling into the governing equation of transport leads to a highly nonlinear parabolic-type partial differential equation (PDE) with variable coefficients. Physically realistic and generalized boundary conditions are considered at the free surface and at the bed. A semianalytical solution of the nonlinear PDE together with these boundary conditions is proposed using two different approaches, namely, the Laplace transform-based homotopy analysis method (Laplace-HAM) and the method of lines-based HAM (MOL-HAM). Unlike existing analytical/semianalytical methods, the convergence behavior of the proposed solution can be handled efficiently through a convergence-control parameter. The proposed solutions have been validated with the numerical solution and the solution of an existing model under limited conditions. Further, the derived solution is also validated with experimental data for the far-field solution. The two derived solutions are compared with each other, and both are found to provide an approximate series solution. The concentration profiles of suspended sediment particles with different physical parameters and conditions are interpreted physically. This study can be extended to address other suspended sediment transport problems.

A two-stage physically-based detention model has been developed for green roof systems. Vertical flow in the substrate is represented by the Richards equation, and horizontal flow in the underlying drainage layer is modeled by the Saint Venant equation. This two-stage physically-based model (2SPB) and the stormwater management model (SWMM) green roof low impact development control model (SWMM-GR) were validated using measured runoff profiles from two contrasting green roof systems: a conventional green roof system; and an innovative system intended to enhance detention. The substrate and drainage layer model parameters were identified from independent physical tests. The 2SPB model provides a reasonable estimation of runoff profiles from a conventional green roof system. However, the model is not capable of representing the flow conditions in the innovative green roof system’s detention layer, such that model results were less accurate for this system compared with the conventional green roof system. SWMM-GR model results for the conventional system were less representative of its overall detention performance due to the assumptions inherent in the substrate percolation model.

Understanding climate data is essential for water resource management, flood risk assessment, agricultural planning, ecological modeling, and climate change adaptation. This study investigated the trends and variability of precipitation extremes to explore statistically significant trends in extreme hydrological conditions over the last 35 years in the Wabi Shebele basin of Ethiopia. Two reanalysis climate products: Enhancing National Climate Services (ENACTS) and Climate Hazards Group InfraRed Precipitation with Stations (CHIRPS) were evaluated against ground observations using cumulative distribution function and statistical measures. The result shows that the CHIRPS data set performed well and captured the precipitation extremes measured by rain gauges. The Mann–Kendall trend test analysis conducted using three extreme precipitation indices: annual maximum precipitation (AMP) (i.e., annual highest 1-day precipitation amount), R10 (i.e., the yearly count of days when precipitation $\ge 10\mathrm{mm}$), and R95P (i.e., 95% percentile precipitation events). The result indicates an increasing tendency over the western–eastern highland and southern part of the basin; In contrast, it indicates decreasing trends over the middle of the study area. Quantile perturbation analysis using R95P reveals high oscillations at 5-year intervals within a confidence interval (CI), particularly at the basin’s western–eastern highlands and southern lowlands. Since the 2000s, a periodicity analysis of maximum yearly precipitation using the autocorrelation function has revealed cycles at 2-year to 5-year intervals over the western–eastern highlands of the basin.