Journal of Hydrologic Engineering

Research on the impact of sluice regulation on water quantity and quality (WQQ) processes in regulated rivers is a fundamental requirement in basin management at present but remains a research puzzle at the basin scale because of insufficient monitoring data, irregular order of sluice or dam regulation, and numerous influencing factors in real-world river basins. This paper presents a laboratory experiment in a single reach as an artificial case study and develops a dynamic numerical model. Through analysis of the observed data and modeling, the river WQQ processes under sluice regulation are investigated and the interaction of WQQ and its regulation capacity downstream of a sluice is explored. Furthermore, a sensitivity analysis of model parameters is carried out and the model validity is tested on a prototype (real-world) scale. Results show that the WQQ variation downstream of a sluice has complicated nonlinear relationships with upstream flow, pollutant load into a river, and sluice regulation. The impact of sluice regulation on water quantity and thus, water quality, is inversely proportional to the relative opening of sluice and upstream flow, respectively. The WQQ results simulated by the numerical model in a real-world-scale system are reasonable, and the patterns are similar to experimental observation. Thus, the experiment and the numerical model will provide a potential approach to mimicking real reaches in a river system with dense sluices where the reaches between adjacent sluices are short and the change in sluice regulation is a dominant factor, such as in the Huai River basin of China. This study provides the foundation and reference for exploration of the mechanism of WQQ changes in regulated river systems and the technical support for the joint WQQ regulation of dams and sluices in complicated real river basins.

The hydraulics of a gravel beach on Eleanor Island in Prince William Sound (PWS), Alaska, was investigated by measurements of the water table and by numerical simulations using the software SUTRA. Sediment samples were obtained from six wells at the approximate three depths: 0.30, 0.60, and 0.90 m, and they were sieved in the lab to generate the grain size distribution, and subsequently the saturated hydraulic conductivity, $K_0$. The results indicated that the beach consisted of two layers: an upper layer with a high $K_0$ and a lower layer with a low $K_0$. In the landward portion of the intertidal zone, $K_0$ was around ${10}^{-2}\mathrm{m}/\mathrm{s}$ and ${10}^{-5}\mathrm{m}/\mathrm{s}$ for the upper and lower layers, respectively. In the seaward portion of the intertidal zone, the $K_0$ values were ${10}^{-4}\mathrm{m}/\mathrm{s}$ and ${10}^{-6}\mathrm{m}/\mathrm{s}$ in the upper and lower layers, respectively. The agreement of the model with the observed water table data was very good. A decrease in the slope of the beach in the seaward direction caused water to flow out from the lower layer and propagate seaward within the upper layer. This ensured that the water table seaward of the exit point was replenished and remained above the interface of the layers. The results suggest that the porosity of the beach decreases from 0.33 at the surface to around 0.05 at 1.0 m deep. The absence of oil on this beach is probably because the beach water table remained above the layers’ interface during low tides. Using the calibrated model, it was found that the flow from land into the beach is around $6{\mathrm{m}}^3/\mathrm{day}$ (per meter parallel to the shoreline) and that the flow out of the lower layer varied with time reaching a maximum of $13{\mathrm{m}}^3/(\mathrm{day}·\mathrm{m})$ at low tide. The beach exchanges up to $7{\mathrm{m}}^3/(\mathrm{day}·\mathrm{m})$ with the sea.

Eutrophication is a major water quality problem throughout the world. An understanding of the pattern of phytoplankton variation and the relationships between chlorophyll a and environmental variables can contribute to eutrophic lake management. In this study, the copula method is applied to discern the inherent relationship between chlorophyll a and environmental variables of Wulihu Lake to the north of Taihu Lake, China. The results show that the method can not only determine the correlation between chlorophyll a and environmental variables through Kendall’s $\tau$ but also determine the joint distribution without assuming the variables to be independent. Moreover, the return period of chlorophyll a can be obtained for given different environmental variables. This study may provide insights for policy makers wishing to improve the water quality of lakes and reservoirs.

The process of creating flood inundation maps is affected by uncertainties in data, modeling approaches, parameters, and geoprocessing tools. Generalized likelihood uncertainty estimation (GLUE) is one of the popular techniques used to represent uncertainty in model predictions through Monte Carlo analysis coupled with Bayesian estimation. The objectives of this study are to (1) compare the uncertainty arising from multiple variables in flood inundation mapping using Monte Carlo simulations and GLUE and (2) investigate the role of subjective selection of the GLUE likelihood measure in quantifying uncertainty in flood inundation mapping. The role of the flow, topography, and roughness coefficient is investigated on the output of a one-dimensional Hydrologic Engineering Center–River Analysis System (HEC–RAS) model and flood inundation map for an observed flood event on East Fork White River near Seymour, Indiana (Seymour reach) and Strouds Creek in Orange County, North Carolina. Performance of GLUE is assessed by selecting three likelihood functions including the sum of absolute error (SAE) in water surface elevation and inundation width, sum of squared error (SSE) in water surface elevation and inundation width, and a statistic ($F$-statistic) on the basis of the area of observed and simulated flood inundation map. Results show that the uncertainty in topography, roughness and flow information created an uncertainty bound in the inundation area that ranged from 1.4 to 4.6% for Seymour reach and 4 to 29% for Strouds Creek of the base inundation areas. Additionally, flood inundation maps produced by applying GLUE have different uncertainty bounds depending on the selection of the likelihood functions. However, the overall difference in the flood inundation maps on the basis different likelihood functions is less than 2%, suggesting that the subjectivity involved in selecting the likelihood measure in GLUE did not create a significant effect on the overall uncertainty quantification in flood inundation mapping of the selected study areas.

The Wind River Range (WRR) of Wyoming is host to approximately 63 glaciers. Extensive research has been conducted using remote imagery to estimate the recent area and volume changes of these glaciers with the goal of estimating the potential effects of these changes on watershed streamflow. Results show that the glaciers were mostly in recession since 1966, the beginning of the study period. The current research was performed to supplement results from the remote imagery analyses. In this paper, streamflows from glaciated and nonglaciated watersheds in the WRR for the period 1967–1992 were analyzed. The difference in July-August-September (JAS) watershed flow magnitude for the 26-year period between glaciated (Green River and Bull Lake Creek) and nonglaciated (East Fork River and Wind River) watersheds ranged between 8 and 23%. As expected, the effects of glaciers on local streamflows during JAS were shown to be much greater than that of ice melt alone. The influence of glaciers accounted for 23–54% of the late summer (JAS) flow in glaciated watersheds with approximately 2–12% because of loss of glacial mass, whereas the remainder of the increased flow was because of the glaciers decelerating the snowmelt runoff through internal storage/delayed release of liquid water. The glaciated watersheds provided a more stable source of streamflow because they displayed less year-to-year streamflow variability with coefficients of variation of 0.36 (Green River) and 0.29 (Bull Lake Creek) compared with the nonglaciated values of 0.55 (East Fork River) and 0.45 (Wind River).

A flood is a common natural disaster that causes enormous economic, social, and human losses. Over the years, a number of management approaches have been developed for lowering flood damage. A rock-fill dam is a suitable structure made of rocks for lowering the output hydrograph and controlling floods in watershed management. On the basis of experimental data, numerical method, artificial neural network (ANN), and neural network-genetic algorithm (NNGA) approaches were applied for predicting flow through trapezoidal and rectangular rock-fill dams. Input parameters for this prediction were selected on the basis of sensitivity analysis. According to the results of the sensitivity analysis, the heights of water in the upstream and downstream sides of the dams were considered as the inputs of the models. The results indicated that the application of a genetic algorithm for optimization of ANN parameters improved the flow estimates. The Delta-Bar-Delta algorithm presented a better performance compared with the other learning algorithms for ANN models. Meanwhile, the NNGA models trained with the Momentum learning algorithm gave the best flow estimates. In general, the used approaches performed well in estimating flow through rock-fill dam; however, the numerical method showed superiority over the other methods.

The Illinois River is a tributary of the Mississippi River that connects Lake Michigan and the Mississippi River. Starting in 1848 when the Illinois and Michigan Canal began to open, the Illinois River has experienced some major human activities such as the Lake Michigan flow diversion, creation of levee and drainage districts on floodplains, and construction of locks and dams on the river. This paper uses Pettitt-Mann-Whitney change-point statistical analysis to identify the hydrologic change points caused by human activities and to quantify hydrologic alterations in the system. Observed stage data from 12 U.S. Army Corps of Engineers gauges and observed flows from three U.S. Geological Survey gauges were used to analyze human effects on hydrologic and hydraulic conditions in the Illinois River. The year 1938 was identified as the change point for low flows and low stages and 1972 as the change point for high flows and high stages. The low flow and stage condition changes were due to a combination of added flow from Lake Michigan, levee and drainage district construction, and construction of locks and dams, whereas the high flow and stage condition changes were due to hydroclimatic change within the Illinois River basin. Analyses based on the Indicators of Hydrologic Alteration (IHA) have shown that the magnitudes, frequency, duration, and number of reversals during low flood conditions were greatly modified by: (1) the construction of locks and dams on the Illinois River that were completed in 1938, (2) the reduction of flow diversion from Lake Michigan, and (3) the hydroclimatic condition change around 1972. The latter change probably contributed to the loss of both soil-moist plants and submerged aquatic plants that once provided several important ecosystem services in the system. The analyses described in this paper, coupled with hydraulic and ecological models, can help with site selection and management plans for the ecosystem restoration of floodplains in regulated rivers.

Multivariate regional statistical models were developed to estimate flood peak values of various return periods in the Peninsular Malaysia. Annual maximum flood peak data were collected, screened, and analyzed to identify the river gauging stations’ potential to produce identical flood frequency curves. The Peninsula was divided into 10 flood regions. The mean annual flood (MAF) for each region was considered as the function of catchment area ($A$) and mean annual rainfall (MAR). The regional equations exhibited good coefficient of determination ($R^2$). Except for the west of Johor Baru State (Region F6), which showed an $R^2$ value of 0.874, other regions had values greater than 0.90. The regions located along the eastcoast of the Peninsula exhibited better coefficients of determination compared with those for the westcoast, owing to the influence of the northeast monsoon along the eastcoast. Mean index errors (MIEs) with respect to the actual MAF of each flood region are provided to rationalize the design flood peak values to minimize the uncertainty in the predictions. Flood frequency values for the lower, mean, and upper limits were proposed to reduce the effect of outliers and uncertainty in prediction of flood peak values. Knowing the catchment area and MAR of the regions, the design flood peaks of various frequencies can be estimated for the rural ungauged catchments in the Peninsula.

Three automated base flow separation techniques based on linear and nonlinear reservoir approaches are used to identify the seasonal variation of base flow and to quantify the annual base flow for three subwatersheds of the Essex region in Southwestern Ontario, Canada. Significant differences in annual base flow estimated by linear and nonlinear reservoir algorithms are observed. In the nonlinear reservoir approach, the recession parameter is considered to be a seasonally variable parameter. The nonlinear reservoir approach fits streamflow recession better than the linear reservoir approach. The steeper slopes of seasonal flow duration curves in the 90% to 100% flow exceedance range show that the groundwater contribution to streamflow is relatively small in the study area. The precipitation-streamflow relationships show faster response of base flow during the period of high recharge. All of the methods show similar base flow estimation during the period of high evapotranspiration losses. The nonlinear reservoir approach represents the base flow response to precipitation better than the other methods. Therefore, the annual base flow estimated by the nonlinear reservoir approach is considered as the most reasonable estimation for the formulation of water budget of the study area. The method quantifies the occurrence of average annual baseflow as 34% of average annual streamflow.

The flow and thermal driven processes are crucial for the soil water dynamics in the vadose zone in arid regions. The understanding of the soil moisture and heat distribution is important for assessing the fate and transport of contaminants for the waste-burial site in a desert setting. A coupled water, vapor, and heat flow model was used in this study for evaluating the interactions of these processes and their influence on the moisture dynamics in the Amargosa Desert Research Site (ADRS) in southern Nevada. The treatment of preferential flow was also included in the model. Data from a previously conducted tracer experiment were used for estimating initial parameters of preferential flux and the parameters in pedotransfer functions (PTFs), while the Levenberg-Marquardt algorithm was used to optimize various parameters in the model calibration on the basis of the observation data. After the model calibration, three-year simulations (1998–2000) were conducted for evaluating the spatiotemporal variability of soil moisture and temperature in the site. The simulation results show that the performance of thermal model with vapor and preferential flow is close to those of isothermal model without vapor and preferential flow as compared with the observed records in ADRS, while critical physical mechanisms could be well described with the thermal model. The vapor flow for the water budget on the upper boundary is insignificant while it influences the water content distribution in the soil profile; the wetting front depth of preferential flow and water budget has increased in rain days; however, the high evaporation counteracts it in the annual water budget. The thermal diffusion of water vapor and thermal liquid fluxes were affected by temperature fluctuation and soil water saturation status. Comparison between the flux components shows that the thermal driven flux has more weight on the water movement in the soil profile. Results indicate that the coupled flow and thermal model could well describe the natural condition in arid regions and is more efficient in simulating mutual effects among various processes.

Remote sensing techniques enable estimation of regional evapotranspiration (AE) over large areas instead of point calculation and it also saves resources otherwise invested in monitoring instruments. The aim of this paper is to compare actual evapotranspiration (AE) estimated using the remote sensing method, the modified Thornthwaite water balance method (WB), and the complementary relationship method (GG) in the Blue Nile, Eastern Sudan. The satellite based Surface Energy Balance Algorithm for Land (SEBAL) model is used with Moderate Resolution Imaging Spectroradiometer (MODIS) satellite data to estimate daily AE. The WB method is used as benchmark data when comparing the three methods. The results show that: (1) In the dry season (November–April), the SEBAL and GG methods give higher values than the WB method; (2) during the rainy season (May–October), the three methods give comparable results, where there is better agreement between SEBAL and WB than between GG and WB; (3) the spatial distribution pattern of monthly AE estimated by the SEBAL method during the dry season is mainly determined by the land-use type and whether there is irrigation taking place or not. However, in the rainy season, the spatial distribution pattern of monthly AE is mainly determined by the seasonal spatial distribution pattern of rainfall in the region.

Quantitative relationships for converting recorded water levels to discharge records in urban streams typically have high levels of uncertainty, particularly for high flows. This problem results from the inherent difficulty in making direct discharge measurements during storms in urban watersheds with flashy runoff response. This paper describes an approach using a $2-\mathrm{D}$ depth-averaged numerical model (TUFLOW) to support rating curves for stream gauges in Baltimore. Multiple forms of field-measured data are used to test and adjust the model-based curves, including surveyed water-surface profiles and high-water marks. Discrepancies between modeled curves and discharge measurements were $0.021–0.085{\mathrm{m}}^3{\mathrm{s}}^{-1}$. The average of modeled and measured water-surface profiles matched to within 0.04–0.08 m of water depth. This method facilitates the generation of rating curves encompassing the full range of flows for which patterns of runoff response impede measurement of high flows allow simulation of complex flow behavior that may influence stage-discharge relationships.