Journal of Hydrologic Engineering

The unstable and unreasonable parameter identification results are achieved because of the nonlinear effect (e.g., the cross-autocorrelation parameters). The XAJ (Xin’anjiang) model shows a certain correlation among confluence parameters, which primarily causes calibration results to be instable and unreasonable. To address the mentioned problem, the correlation between parameters should be overcome, and more estimation information should be presented. Accordingly, a novel objective function based on the Fourier expansion (FOF) was introduced to calibrate confluence parameters in the XAJ model. The flow processes were separately expanded with the Fourier series, and the independent and frequency-dependent objective functions were yielded with different frequency structures of the surface flow, interflow, and groundwater. To prove that the method is feasible, theoretic derivation and application analysis in a case of the Changzao basin were conducted. As revealed from the results, the method is capable of effectively increasing the information in parameter calibration and fully exploiting the physical mechanism of confluence parameters to calibrate the decomposition dimensionality reduction of confluence parameters.

The interface of freshwater and saltwater plays an important role in the economic and social dynamics along the coast and estuaries. Droughts in coastal areas have ecological impacts and affect socioeconomic dynamics and public health. In this study, we developed a bivariate and multivariate drought index that can quantify and indicate drought conditions in coastal, bay, and estuarine areas by integrating the meteorological and hydrological drought variables. The bivariate coastal drought index (BCDI) was developed using copula theory, which includes streamflow and salinity levels in the bay areas. Further, the entropy-weighted Euclidean distance method was used to develop the multivariate coastal drought (MCDI) index using precipitation, salinity, and streamflow datasets. Both the BCDI and MCDI were able to capture the major drought events occurring in the southeast region (2000, 2007, and 2011–2012) of the United States. Correlation analysis showed that both the BCDI and MCDI were highly correlated with the standardized univariate drought indices. One of the better features of the MCDI was that it was able to capture the dynamics and trends of the variables involved and, thus, was a better indicator of droughts in the coastal regions. Hit rates and false alarm ratios showed that both the indices were able to capture the droughts in coastal regions. The coastal drought indices developed in the study can be used by the National Integrated Drought Information System (NIDIS) and other agencies as drought indicators for coastal regions, along the coastal regions, estuaries, and bays in the United States.

A novel analysis procedure, referred to as variable-sized cluster analysis (VSCA), was developed to identify trends and change points in precipitation time series data set. The procedure involved station-scale rainfall data of $100\mathrm{years}$ from seven districts (Saharanpur, Bareilly, Agra, Jhansi, Lucknow, Varanasi, and Gorakhpur) of the state of Uttar Pradesh (UP), India. In contrast with the traditional Mann-Kendall (MK) test that yields a monotonic trend for the whole span of time, VSCA enables one to detect multiple change points while characterizing the pattern of precipitation trends over the historical time period. The Pettitt-Mann-Whitney (PMW) test was also modified to graphically represent the multiple change points, which confirmed the results of VSCA. Thus, VSCA demonstrated the unified strength of MK and PMW tests. The three-dimensional (3D) figures drawn for visualizing the changing trend of precipitation utilized 100-year-long time series data set with the minimum size of data cluster as 10, which resulted in the right triangular shape of the graphs due to the repeated application of the MK test to variable-sized data clusters. Application of VSCA showed a decreasing trend of precipitation over Lucknow, Gorakhpur, and Varanasi around 1990 onward, with major changes in the decades of 1970–1980. Saharanpur and Agra contrarily displayed an increasing trend until 1940 and no trend thereafter; however, Bareilly and Jhansi showed reducing trends in precipitation.

Flood forecasting in urban and semiurban catchments is often limited by the capability of the combined hydrological models and forecast inputs to predict floods accurately. The objective of this research is to develop an approach (1) to identify the best model forecast from multiple integrations of various hydrological models and numerical weather predictions (NWP), and (2) to find the best forecast combination method for an improved short-range flood forecasting. Seven selected hydrological models were coupled, each with two high-resolution NWP forecasts to provide several alternatives of deterministic hydrological forecasts at a catchment outlet. As such, the different model-input combinations were used to generate 14 hydrological forecasts. Hydrological forecast verification was then carried out over a one-year hindcast period. A comparison between six forecast combination methods, including a benchmark Bayesian model averaging (BMA) method, was also performed for the multiple available short-term streamflow forecasts. Results indicate that the coupling of the Sacramento soil moisture accounting (SACSMA) model with both High-Resolution Deterministic Precipitation System and High-Resolution Rapid Refresh inputs outperformed other model-input integrations. Maximum forecast errors in all model-input integration outputs occurred at forecast lead times of $12–14\mathrm{h}$, corresponding to the time of concentration of the catchment. Providing constraints on the estimation of model weights was found to be a significant factor for obtaining an improved combined streamflow forecast. In general, the regression-based forecast combination method of the constrained ordinary least squares (CLS) has emerged as a possible alternative to the widely used BMA method for hydrology application.

A 3D mathematical model that describes transport of volatile organic compounds in a coupled vadose-saturated zone system is proposed. The subsurface processes incorporated in the model include advection, dispersion, interphase mass transfer, and diffusive mass exchange between two horizontal porous media formations, as well as the time-dependent mass loading from a source zone. The analytical solutions are derived subject to the specific initial and boundary conditions. The solutions are evaluated by numerical Laplace inverse transform. The model solutions can be used to study the fate and transport in subsurface formations composed of a vadose zone and a water table aquifer, where the volatile organic compound is released from entrapped nonaqueous phase liquid in the vadose zone, or the dissolved volatile organic compound transports with groundwater accompanied by diffusive mass transfer into the overlying soil formations. Mass transfer between two layers is demonstrated to have back-diffusion characteristics, which results in secondary contamination and retains low levels of contaminant concentrations over a prolonged period of time. The model solutions are specifically useful in assessing the vapor intrusion process in a contaminated site where a vadose zone is underlain by a water table aquifer contaminated with volatile organic compounds.

Stormwater management has traditionally focused on increased runoff from impervious areas (IAs) accompanying urbanization. Far less consideration has been directed to significant changes in the hydrologic characteristics of urban soils that also accompany urban development. Mass grading and standard site development practices disturb and compact urban soil profiles, dramatically reducing infiltration capacity, rooting depths, and the stormwater services provided by urban green spaces. Stormwater services may be purposefully restored using soil decompaction and amendment to rebuild porous permeable organic-rich soil profiles in urban pervious landscapes. In this study, the use of suburban subsoiling (SS) (soil decompaction and compost amendment) for restoring stormwater services was evaluated on a decommissioned highway roadbed and construction staging area that had been designated for afforestation by the Maryland Department of Transportation State Highway Administration. Suburban subsoiling increased the mean infiltration capacity of the site’s disturbed compacted soils by more than an order of magnitude, with dramatic improvements in the bulk density ($-28\%$), organic matter ($+82\%$), and potential rooting depth ($+20$ to $+30\mathrm{cm}$) of the restored soil profile. Integrating SS with standard mass grading and land development practices can transform the built environment by cultivating sustainable stormwater services in anthropogenic landscapes.

Reference crop evapotranspiration (${\mathrm{ET}}_0$) is of great importance in assessing the potential impacts of climate changes on hydrological cycles and the global energy balance. The spatiotemporal change of ${\mathrm{ET}}_0$ and the drought response over Poyang Lake watershed of China from 2011 to 2100 are the main concern in this work. Based on the meteorological data and the output of the general circulation model (GCM) from the Coupled Model Intercomparison Project Phase 5 (CMIP5), we used the Penman–Monteith formula and downscaling model to calculate the history and future ${\mathrm{ET}}_0$ in Poyang Lake watershed, respectively. Major results are drawn as follows. First, the annual average ${\mathrm{ET}}_0$ decreased during 1961–2014 and the average ${\mathrm{ET}}_0$ of the basin is high in the north and south, but low in the middle. The ${\mathrm{ET}}_0$ was most dominated by sunshine duration in the spring, summer, and fall and by relative humidity in the winter. Second, the downscaling model has a good simulation effect, and the GCM data-downscaling simulation results are significantly improved after the deviation correction. Third, under the representative concentration pathway (RCP) 4.5 and RCP 8.5 scenarios, ${\mathrm{ET}}_0$ in the Poyang Lake watershed will increase over the next three periods, with the middle future (2041–2070) as the largest increase period. The spatial distribution of ${\mathrm{ET}}_0$ is generally high in the east and low in the west. Fourth, under the RCP 8.5 scenario, the drought index (DI) of the watershed showed an increasing trend, the seasonal distribution of DI is $\mathrm{fall}>\mathrm{summer}>\mathrm{spring}>\mathrm{winter}$, and the Ganjiang River subbasin will be the key prevention area for future drought risks. The results can provide basic data support for the optimal management of water resources and scientific response to the impact of climate change on agricultural production in the watershed for associated policymakers and stakeholders.

The main aim of this study is to improve the underestimation of spatial snowfall distributions by using assimilation. Although measuring snowfall depth is crucial to evaluate snow water resources and predict snowmelt runoff in spring season, it is difficult to measure snow depth correctly with a gauge because wind speed strongly influences the capture ratio. Snowfall observation errors have a significant influence on the accuracy of hydrological model output. An evaluation of the distributed hydrological model was carried out in the Yoneshiro River Basin in Japan with a modification of the model using snow depth data. To reduce the measurement error using the snowmelt-runoff model, an assimilation policy based on the observed snow depth is included in the snow water equivalent (SWE) model at regular intervals. As a result, the assimilation improves the accuracy of both the snow depth estimation and the snowmelt-runoff simulation. The Nash-Sutcliffe coefficient is improved from 0.63 to 0.86 throughout the year and from 0.21 to 0.82 from March to May. The assimilation of snow depth can contribute to improvement of the hydrological model with higher accuracy compared with direct use of gauge data. Also, how to assimilate snow depth, such as an interval of the assimilation and its applicable timing, is discussed. The model suggested in this study can be helpful for water management–related activities and decision making.

Modeling urban flooding is challenging because of complex spatial variations and interactions between precipitation, land cover, and drainage networks. This paper presents a case study of the development of two hydrology and hydraulics models—the semidistributed storm water management model (SWMM) and the fully distributed gridded surface/subsurface hydrologic analysis (GSSHA) model—to simulate the hydrologic response of two neighboring urban watersheds with large storm sewer networks in the city of Roanoke, Virginia. Both models were calibrated and validated for the two watersheds based on nine events (May–October 2018), and the models were assessed on their ability to replicate measured stream discharge and storm sewer flow depths. The findings from the study indicate that both models reasonably capture the observed hydrologic responses but that each model offers unique benefits. Overall, SWMM’s value to the city is its ability to provide detailed information regarding the hydraulic conditions within the city’s storm sewer network, whereas GSSHA’s value to the city is its ability to predict the duration and spatial extent of flooding in two dimensions.

The Tonle Sap Lake (TSL), located in southwestern Mekong Basin, is the largest freshwater lake in Southeast Asia. The water-level regime of the TSL has been changing over the last few decades due to the rapid development of water infrastructures and climate change in the Mekong Basin. This paper makes efforts to quantify the water-level regime alterations of the TSL by analyzing the pre- and post-1991 historical data of daily water levels from Kompong Luong Station. The method of modified indicators of hydrologic alteration was utilized, and the TSL’s hydrological behavior was explored further by focusing on the redistribution of hydrology and unfavorable disturbances. The results reveal that the coefficients of variation of most indicators in recent years increase compared with the preimpact years from 1960 to 1990. This demonstrates that the Mekong Basin and TSL are experiencing an increasingly unstable and varied hydrological cycle, which is more susceptible to interference with increased frequency and degree. Moreover, the system may have suffered more unfavorable human interference in dry years and in the dry season. It is expected that the findings in this paper will contribute to the protective development and adaptive management of the Mekong Basin and the TSL in the future.

This case study describes an economically feasible approach to generate synthetic rating curves that enhance utility of stage-only river gauges. The study is based on a network of 250 bridge-mounted river-stage sensors (BMRSS) that the Iowa Flood Center has deployed in Iowa. The authors investigated using the step-backwater model with the Hydrologic Engineer Center’s River Analysis System (HEC-RAS) to develop a stage-discharge relationship. The authors installed BMRSS at eight sites collocated with USGS gauging stations with well-established stage-discharge ratings to serve as reference. They also surveyed the channel cross sections in the upstream and downstream vicinity of the sensor locations. To account for uncertainty of channel roughness and free surface slope, they ran the model using a Monte Carlo simulation. The resulting rating curve realizations were compared with the USGS reference. The study reports the distribution of relative errors in the synthetic curve estimates, conditioned on the value of discharge. The results show average discharge errors of less than 5% for flows within the main channel banks and less than 3% in the floodplain. The average stage error is 0.43 m (range of 0.2–0.9 m). The authors also explored the error induced by using airborne light detection and ranging (LiDAR)-based topographic surveys for the cross-sectional geometry. They assessed the model-based methodology at an additional 19 locations where USGS maintains rating curves and concluded that the results were inferior compared with those obtained using conventional geodetic surveys. The study provides a basis for expanded monitoring of streams and rivers with stage-only sensors.