Journal of Hydrologic Engineering

A study of the efficiency of a zero-inertia model (ZI) for two-dimensional (2D) overland flow simulation is presented in this work. An upwind numerical scheme is used for the spatial discretization in the frame of finite-volume methods and an implicit formulation is chosen to avoid numerical instability. The scheme is applied in both structured and unstructured meshes, focusing in the latter ones due to their good adaptability. The ZI equation has a nonlinear character; hence, a linearization is required in the implicit procedure. This is carried out by means of Picard iterations method as a previous step to the system matrix resolution, characteristic of implicit techniques. The BiConjugate Gradient Stabilized (BiCGStab) method combined with sparse storage strategies is selected for the system resolution. A dual-threshold incomplete lower upper factorization (ILUT) is chosen as matrix preconditioner. Computational efficiency of the implicit temporal discretization for ZI model is explored under both steady and unsteady flow conditions by comparing the CPU times against the explicit version of the same model.

A nonhomogeneous discrete-time three-state Markov chain model is developed in this study to quantify the bedload and suspended load discharge under unsteady flow for mixed size sediment particles. When flow is subject to sudden changes, the particle holding time, defined as the amount of time for a sediment particle staying on the bed or in the moving state, needs to be carefully evaluated. The time step used in this study for single-step motion in the discrete-time Markov chain is represented by a characteristic timescale for particle motion. The transition probabilities are functions of flow conditions and particle properties. Specifically, the likelihood of particle movement between the bedload layer and the bed surface is evaluated by the entrainment probability. Exchange of sediment particles between the bedload layer and suspended load layer is quantified by the suspension probability. A nonhomogeneous Markov chain ensures the transition probabilities are time dependent as they are a function of local conditions. The proposed sediment transport model can be used to calculate both bedload and suspended load as a function of time for any size fraction of mixed size sediment particles. The proposed sediment transport relation is compared with a classic sediment transport formula. The comparison shows that the proposed model performs better for particles of smaller grain size. It is also demonstrated that the quasi-steady assumption normally adopted in flow-sediment modeling appears to be a valid approximation when the time for the sediment transport rate to reach an equilibrium state is sufficiently small. The proposed model is also validated against unsteady bedload transport flume data, as well as flume data containing both bedload and suspended load.

To develop an empirical model for ground snow sublimation beneath canopy, a weighing measurement experiment was conducted using snow samples with different density in the broadleaved Koreanpine mixed forest in Changbai Mountains, Northeastern China. Eddy covariance measurement for water vapor flux was used to evaluate the model performance. Eddy covariance data showed that the daytime sublimation was much larger than the nighttime sublimation, and 94.3% of daily sublimation occurred within the 8 h from 8:00 to 16:00. Daytime sublimation showed a linear relationship with snow density, and the regression coefficients between them varied with meteorological variables. The regression slope was closely correlated to solar radiation ($R^2=0.92$) and water vapor pressure ($R^2=0.79$), whereas the regression intercept was closely correlated to air temperature ($R^2=0.92$). Based on the regression relationships among sublimation, snow density, and meteorological variables, a nonlinear empirical sublimation model with a combination of snow density, solar radiation, water vapor pressure, and air temperature was developed. Sublimation estimation of the empirical model matched the eddy covariance data giving $R^2=0.83$ and root mean square error $(\mathrm{RMSE})=0.05\mathrm{mm}·{\mathrm{d}}^{-1}$. The surface reflectivity decreased with the increase in snow density. Dense snowpack would absorb more energy and promote snow sublimation by increasing the vertical water vapor pressure deficit between snow surface and atmosphere.

Two nonlinear mathematical models are presented to predict peak discharge from a breached embankment dam based on evaluation of measured outflows from 41 dam failures. Reported outflow rates from these failures have been examined carefully for accuracy and are believed to be reliable. The first model is purely empirical, while the second is based on a semitheoretical approach that reduces the maximum possible peak discharge that would be produced by instantaneous formation of a breach having prescribed dimensions. Results given by the models are compared to those from other breach peak discharge calculation methods and are shown to produce considerably more accurate predictions of peak discharge from breached embankment dams.

Erosion and sediment control products have become an integral part of the construction industry as manufacturers now provide innovative alternatives to traditional practices. Ditch checks are used on construction sites to intercept channelized stormwater runoff to reduce flow velocity, minimize channel erosion, and promote sedimentation. A standardized metric is needed to evaluate the performance of various ditch check practices. Comparative analyses are difficult in the field and in large-scale testing environments because conditions can vary greatly. A hydraulic-based metric to evaluate performance was developed by researchers at the Auburn University-Erosion and Sediment Control Testing Facility (AU-ESCTF). This metric is based on hydraulic conditions created by a ditch check to slow flow velocity and transform kinetic energy to potential energy. Using the ratio of water depth ($y$) to specific energy ($E$), the average performance can be quantified and compared with counterparts and traditional practices, even if data were developed under different flow conditions or channel geometries. While using the $y/E$ ratio to determine kinetic energy reduction, a nonsubjective performance threshold of $y/E=0.75$ emerged.

Virtual experiments have been designed for the development and validation of coupled surface-subsurface modeling. Potentially, virtual experiments can guide model calibration as well. To address the role of virtual experiments in model calibration, a novel approach was described for a real watershed calibration of Penn State Integrated Hydrologic Model (PIHM) guided by the V-shaped catchment simulation. First, a benchmarking experiment of coupled surface-subsurface modeling was developed and documented on the V-shaped catchment. Then, the performance of hydrologic predictions for the V-shaped catchment was calculated and demonstrated different levels of correlations. The correlations were found stable, which had the potential to be used as the weights of multiobjective calibration. Therefore, a weighted multiobjective calibration was developed for a real-world watershed by transferring the correlations obtained from the virtual experiments. Expectedly, the parameters calibrated using the weighted approach indicated improvement of the model performance in simulating water-table depths and evapotranspiration with little sacrifice of model performance in streamflow. In addition, this study also compares the weighted average calibration and unweighted calibration. The results demonstrate the weighted objective optimization achieved satisfactory compromise for each calibration objective. Overall, the virtual experiment is proved to be an efficient tool to facilitate calibration of complex models. The proposed weighted objective approach provides an effective calibration strategy for the multiple observation constraints, which can be applied for the calibration of coupled environmental process models with multiple observations.

The hydrological behavior of a watershed is influenced by a multitude of factors that interact differently in time and space. The perspicacity of these interactions is critical for advancing water resource management. This article discusses an approach that entails an entropy-based disorder index for spatio-temporal pattern analysis. Based on a case study, the article reported the pertinence of the index for analyzing the hydrologic components of the watershed. Specifically, the approach examines the spatio-temporal patterns of streamflow, precipitation, and land-cover across the watershed. Indeed, each of these three variables is time-dependent and plays a determinant role in terrestrial hydrology. However, their joint functionality is more complex to elucidate, even though these variables frequently display meaningful variability in time and space. Within this contextual frame, application of the entropy-based index reveals prominent signals that are useful for water resources assessment. Moreover, the analysis using the entropy-based index provides realistic insights into the interactions between these hydrologic factors that interplay at the watershed scale.

For highly urbanized watersheds where space is limited, distributed low impact development (LID) stormwater controls could offer an effective retrofit to address flooding problems. The goal of this study is to determine the feasibility of using distributed LID controls within an urbanized watershed for flood mitigation. The Rocky Branch Watershed in Columbia, South Carolina, is an excellent case study because it experiences flash floods almost annually and has limited space for traditional, centralized stormwater controls to mitigate these floods. The Storm Water Management Model (SWMM) was used to model flooding with rain gardens as the LID approach for flood mitigation owing to their storage potential. The results of the study suggest that rain gardens with 30-cm berm heights and a total area equal to 20% of the impervious surfaces within the watershed should provide sufficient storage to mitigate flooding for rain events up to and including a 10-year storm event. Once sufficient storage is available, the challenge is diverting runoff generated from impervious surfaces into rain gardens. The results of this study suggest approximately 15, 27, and 38% of the runoff generated from impervious surfaces should be diverted to rain gardens to mitigate flooding from 2-, 5-, and 10-year storm events, respectively. Given prior work on the adoption of LID approaches for other watersheds, rain gardens could be effective at mitigating up to a 5-year storm event within the watershed, although further research on possible adoption rates in the study watershed is needed to more fully support this conclusion.

This study examines climate change impacts on water resources in the African country of Malawi. Downscaled outputs from six general circulation models, for the most extreme Representative Concentration Pathway (RCP 8.5), were used as inputs to the soil and water assessment tool to assess the impacts of climate change on evapotranspiration, surface runoff, water yield, and soil moisture content at the country, watershed, and subbasin levels by the 2050s. At the country level, the results showed a $–5.4\%$ to $+24.6\%$ change in annual rainfall, a $-5.0\%$ to $+3.1\%$ change in annual evapotranspiration, from $–7.5\%$ to over $+50\%$ change in annual surface runoff and water yield, and up to an 11.5% increase in annual soil moisture. At the watershed level, results showed an increase in annual rainfall and evapotranspiration in the north and a gradual decline towards the south. Subbasin-level analysis showed a large probability of increase in the annual precipitation, surface runoff, water yield, and soil moisture, especially in the north. Overall, the northern region was found to be more prone to floods, while the southern region was found to be more prone to droughts. On a positive note, more precipitation in the north can provide more opportunity for agricultural production.

The Brahmaputra River Basin (BRB) is one of the major fresh water sources in South Asia. The current research attempts to assess impacts of climate change on streamflow of BRB using a physically based semidistributed hydrological model, namely, soil and water assessment tool (SWAT). SWAT was calibrated and validated for the climate normal period (1981–2010) at the Bahadurabad station in Bangladesh, and good agreement between observed and simulated streamflow was found. The model was then applied to simulate 24 synthetic climate change scenarios (combination of perturbed precipitation and temperature) to investigate the basin’s sensitivity, in terms of streamflow, under the potential impact of climate change. It was found that the basin’s projected streamflow responded almost linearly with projected temperature and precipitation. Mean annual streamflow changes of the BRB due to 1°C change in temperature (keeping the 1981–2010 baseline precipitation unchanged) was about 1.35%, whereas about 1.37% changes in mean annual streamflow were projected for 1% change in precipitation (keeping the baseline temperature unchanged). The results obtained using perturbed scenarios were used to develop a multivariable linear regression model representing future streamflow of BRB under the projected changes in temperature and precipitation.

Drought is a natural phenomenon that can occur in almost any region. Vulnerability and resiliency are two important concepts in studying any natural hazard, including drought. This study investigates the application of both of these concepts in drought management in East Azerbaijan province in Iran. A vulnerability map of the region was developed by considering the spatial characteristics of some important parameters in drought in a geographic information system environment. A general framework is also presented for quantifying system’s resiliency to drought in the Aharchay watershed, which contains the important Sattarkhan Dam Reservoir. This watershed is one of the important watersheds in the case study. To develop this framework, the characteristics related to four resiliency components—rapidity, robustness, resourcefulness, and redundancy—are determined. The relative importance of these components is determined using multicriteria decision making (MCDM). By combining resiliency and vulnerability, it is demonstrated how vulnerable the different parts of a system are. The results show that the western part of the province has the highest vulnerability and the downstream area of Sattarkhan dam is more resilient in comparison to the upstream. The methodology proposed in this study can be used for drought preparedness planning and for allocating resources in a region.

The identification of base flow from an available record of streamflow measurements for recession rate analysis is often a difficult and time-consuming process affected by unavoidable errors and subjective aspects. Here, several stringent criteria are proposed for automated selection of base flows for this method and are applied to select pure base flows in 26 catchments from the United States, Australia, and China. The characteristic drainage timescale parameter ($K$) of the linear response function was chosen as the effectiveness measure of the automated method; the $K$ values estimated using this method are $44.5\pm 13.2$ days compared with $45.7\pm 10.5\mathrm{days}$ estimated manually for the catchments with long records. The effects of different imposed criteria on the base flow selection are also quantified using this parameter. The proposed algorithm provides a faster and more objective methodology for automated selection of base flows for recession rate analysis and will thus greatly facilitate its application.

This study assesses the role of spatial resolution in hydrologic and hydraulic models by means of two models developed at different resolutions for an urban block using the U.S. Environmental Protection Agency’s stormwater management model (SWMM). The first is a high-resolution model, in which distinct elements are represented as individual hydrologic response units (HRU). The second is a low-resolution model, in which the entire block is represented as a single HRU. Flow observations during five storms were used to calibrate the models, while a separate set of six storms was used to assess their performance. The high-resolution model was found to systematically underestimate peak flows, whereas the performance of the low-resolution model was found to be dependent on the type of storm. Overall, the two models displayed similar accuracy according to most metrics, thus justifying modeling at high resolution only in those cases where a detailed representation is necessary.

This paper proposes analytical inflection S-shaped (IS) approach for deriving smooth-shaped altered duration ($\tau -\mathrm{h}$) unit hydrographs (UHs) from a given unit duration ($D-\mathrm{h}$) parent UH. It was found to be superior to conventional S-curve approach as it has the ability to exactly reproduce a hunting-free $D-\mathrm{h}$ parent S-curve or its lagged version at a desired $\tau -\mathrm{h}$ duration. Chiefly, the complexity associated with the erroneous lagging of parent UH or S-curve, interpolation if altered UH duration is not an integral multiple of parent UH duration, tedious manual/visual smoothing of derived S-curve or altered duration UH and sustaining unit volume under UH has been fully resolved.