Journal of Hydrologic Engineering

Peaks of suspended sediment concentration in rivers appear before peak discharge appears. The observation of discharge is usually done in many rivers for river management, but the suspended sediment concentration is not always observed. The suspended sediment concentration is expressed by a sediment-rating curve over a long period of time. Coefficients in the sediment-rating curve are time varying. The time variation of the suspended sediment concentration is predicted by the sediment-rating curve with the recursive least-squares and the linear minimum variance estimators. Because the sediment-rating curve is linearized by the logarithmic transformation, we can apply the simple linear models such as recursive least-squares and linear minimum variance estimators for the prediction of the suspended sediment concentration. These methods indicate that the coefficients in the sediment-rating curve are time varying. These methods can estimate sediment discharge by identifying the coefficients in the sediment-rating curve. Nash-Sutcliffe model efficiency coefficients indicate that the three-day ahead prediction is possible with accuracy. The recursive linear minimum variance estimator is compared with the recursive least-squares estimator. As a result, the recursive linear minimum variance estimator is not always better than the recursive least-squares estimator, although the former is theoretically superior to the latter as long as the assumption of the linear minimum variance estimator holds. The application of these methods to the prediction of the suspended sediment concentration is found to be possible because discharges are assumed to be observed daily in many rivers.

A five parameter, daily vegetated roof water balance model (VR-WBM) was developed, calibrated, and validated by using experimental vegetated roof data from the Seacoast, New Hampshire region. The lysimeter experiment on a sedum canopy characterized water storage with a 0.051 mm resolution. Overall, the results show that the average stormwater runoff reduction was 32% for the study period, and an average reduction per storm was 57%. Average daily evapotranspiration (ET) rates were $1.24\mathrm{mm}/\mathrm{day}$ during the warmest month and $0.52\mathrm{mm}/\mathrm{day}$ during the coolest month. For well-watered conditions, the ET losses were well-modeled by using a grass reference evapotranspiration (ET) value with a crop coefficient of 0.53 for the study’s sedum canopy in which the onset of stomatal closure occurs when the soil moisture is $0.11{\mathrm{m}}^3/{\mathrm{m}}^3$. When soil moisture content values are lower than $0.11{\mathrm{m}}^3/{\mathrm{m}}^3$, evapotranspiration rates decrease linearly with declining soil wetness. The VR-WBM does an excellent job predicting runoff ($R^2=0.98$) and storage ($R^2=0.94$). Although ET had a lower $R^2$ value, ($R^2=0.59$), the average ET values were within 3% of the observed values, and they do not appear to affect storage and runoff predictions. Additionally, the model demonstrated an ability to accurately quantify antecedent soil moisture and its effect on runoff generation.

Since a nonlinear partial differential equation was developed by Boussinesq based on Darcy’s law and the Dupuit-Forchheimer assumption, it has played an essential role in the development of simulation models for the solution of various flow problems in porous media. To solve Boussinesq’s equation, both analytical and numerical solutions, such as finite difference (FD) or finite element (FE), have been sought. The differential quadrature method (DQM) is a new numerical method frequently used by researchers to solve partial differential equations. In this paper, DQMs have been coupled with explicit, implicit, and Crank-Nicholson FD and applied to solve Boussinesq’s equation for a drainage problem. This case has been solved previously both analytically and numerically, including by DQM, by other researchers. Those who had employed DQM had linearized Boussinesq’s equation first and solved the linearized form implicitly. In this work, the nonlinear form of Boussinesq’s equation has been solved using three models based on DQM for solving the dimensionless form and on one approach for solving the dimensional form of Boussinesq’s equation. The obtained results and their degree of accuracy are compared with available experimental and numerical data found in the literature, and on that basis, it is concluded that DQM generates accurate results, is very easy to formulate and operate, does not need large mesh size, and is very time efficient.

Inflows to reservoir systems are affected by climatic changes. In the past, regional inflow trend analyses were conducted using statistical approaches. This research made use of an artificial intelligence technique called the self-organizing map (SOM) to perform trend and cluster analysis for the inflows into the flood-control reservoirs of Indiana. Along with SOM, this research also used the Mann-Kendall test and a revised Mann-Kendall test for regional analysis. Results indicate an increasing trend in the clusters that represent days with high inflows to the northern reservoirs of Indiana when inflows to the central and southern reservoirs were low or medium. A 7% increase was noticed in the annual daily counts belonging to this cluster during the past 20 years. Similar trends were observed concerning high-inflow days to the central reservoirs of Indiana. However, they are not statistically significant at a 95% confidence level. This study concludes that SOM is a useful tool for studying the trends at a regional level.

Studies on the effects of anthropogenic climate change have found that the magnitude and frequency of intense precipitation events are expected to increase over the next century for the midwestern United States. The goal of this study was to use statistically downscaled and debiased precipitation projections for the state of Wisconsin derived from 14 general circulation models (GCMs) to assess the projected precipitation changes for the mid–21st century in a way that is relevant to water-resource decision making. The authors analyzed metrics that are relevant to storm-water design, such as the 100-year, 24-h quantile, and the authors also evaluated the changes in a risk-assessment context using idealized damage functions that translate precipitation depths into economic damages. The results of our design-metric analysis show that the 100-year, 24-h quantiles for Wisconsin are projected to have significant but modest increases of approximately 11% over the next 50 years. Our risk assessment shows that the largest percent changes in risk for Wisconsin are projected to be in the northeast portion of the state. Both of these analyses will be used as part of the Wisconsin Initiative on Climate Change Impacts (WICCI) to develop climate-change adaptation strategies for communities throughout the state.

An array of ditches method of subsurface drainage is advantageous for various playgrounds, golf courses, parks, and also for orchard plantation where there is little farming operations. A comprehensive analytical solution for the problem of subsurface drainage of a ponded surface by an array of parallel ditches has been obtained by conformal mapping. The symmetry about the vertical axis has been considered in obtaining the solution for half of the drainage domain. The presented solution is applicable for the two dimensional steady drainage from a horizontal ponded surface of finite depth to an array of parallel ditches in homogeneous and isotropic porous medium having an impervious layer lying at finite depth or at infinite depth. The solution includes equations for the quantity of drainage from the seepage face part as well as the water depth part of the ditch. The solution also comprises expressions for the variation in seepage velocity at various locations along the porous medium. Further, particular solutions (e.g., single ditch, empty ditch, ditch of negligible width, impervious layer at infinite depth, or at the bottom of ditch) have been deduced from the proposed generalised solution. The single-ditch solutions have been verified with the existing results of previous work.

The moments (MOM1 and MOM2), maximum likelihood (ML), sextiles (SEX1 and SEX2) and probability weighted moments (PWM1 and PWM2) methods for estimating the parameters and quantiles of the general extreme value (GEV) distribution for the maxima were analyzed and compared by using data generation techniques of the type of distribution sampling experiments. Considering variance, bias, and mean square error criteria of estimates of parameters and quantiles, it is concluded that in general for the sample sizes analyzed $9\le N\le 99$ and nonexceedance probabilities in the range $0.90\le F\le 0.99$, the ML method is superior to the other six. However, the simpler methods may be as good depending on the sample size. The PWM2 is a good option to estimate the location and shape parameter, while MOM1 and MOM2 are an alternative when estimating the shape parameter. Thus, for estimating quantiles for $N\le 19$ the MOM1, MOM2, and PWM2 method compares quite well with the ML method, while for $N>19$ the PWM2 shows a better performance. When compared with ML, the PWM2 method showed an overall better performance in estimating the quantiles for large negative values of the shape parameter and for small sample sizes.

Over the past century, the City of Boston has periodically experienced a decline in groundwater elevations and the associated deterioration of untreated wood piles, which support building foundations. To combat declining water tables, Boston enacted a groundwater conservation overlay district enforced by city zoning boards to require storm water recharge practices for any activity that triggers the zoning bylaw. In Boston, recharge to the water table results from the infiltration of rainfall and snowmelt, leakage from water mains, and recharge from artificial systems. Increased mitigation activities to reduce unaccounted-for water have reduced leakage from water mains in the city. Given the high percentage of impervious cover in Boston, the remaining sources of recharge are primarily artificial systems, including pump and infiltrate systems and storm water recharge best management practices (BMPs). The primary objective of this research was to exploit existing information on groundwater elevations and recharge practices to quantify the effect of the required recharge BMPs on the behavior of groundwater elevations in the Back Bay region of Boston. Regional multivariate regression models were developed to determine the potential effects of recharge BMPs on observed groundwater elevations. The literature review revealed several analogous multivariate linear regression studies, none which focused on behavior of stormwater BMPs. The model reveals that the installation of recharge BMPs has a small but highly statistically significant positive effect on groundwater elevations in the Back Bay with the effect being proportional to their capacity and inversely proportional to their distance from the location of interest. The resulting model can be used to predict the effect on average groundwater elevations at a particular location resulting from the installation of a recharge BMP or a set of such BMPs of a particular capacity at a particular distance from the location of interest.

The focus of the present work is to characterize a tropical, coastal aquifer and to carry out its vulnerability to saltwater intrusion using hydrogeological parameters. The characterization of the aquifer involves pumping tests, vertical electrical sounding, and water quality analysis carried out at 41 monitoring wells. The area under investigation lies between two tropical, seasonal, tidal rivers, i.e., Pavanje and Gurpur rivers, joining the Arabian on the west coast of India. The aquifer is predominantly shallow and unconfined, having moderate to good groundwater potential with transimissivity and specific yield ranging from 49.2 to $461.4{\mathrm{m}}^2/\mathrm{day}$ and 0.00058 to 0.2805, respectively. The electrical resistivity tests indicated that the thickness of the aquifer ranges from 18 to 30 m. The study also investigates the saltwater affected areas in the region the vertical electrical sounding and water quality analysis. The resistivity results revealed several probable isolated saltwater intruded pockets in the region with resistivity less than 70 Ωm. From the salinity analysis of water, the locations that are affected during February to May (summer) and throughout the year are identified. The wells that are located close to the coast ($<350\mathrm{m}$) and at lower elevations (well bottom $<+1\mathrm{m}$) were found to be saline throughout the year. Also, wells along the banks of the river show considerable salinity ($>200\mathrm{ppm}$) during the summer period from tidal inflow along the rivers. The water samples were also analyzed for chloride to bicarbonate ratios during December to May at all the monitoring wells and were found to be exceeding the allowable limit at several locations. The saltwater vulnerability maps are derived for the area by the index-based method using the hydrogeological parameters. The method was found to be effective while compared to the field observations. The results from the analysis indicate that the aquifer is medium to highly vulnerable to saltwater intrusion at majority of the locations. The impact of projected sea level rise by 0.25 and 0.50 m from the climate change is also assessed on the vulnerability of the region to saltwater intrusion.

Conversion of a natural watershed into its equivalent kinematic wave rectangular plane has long been a concern in the practice of storm water numerical simulations. Based on the principles of mass and energy, the actual watershed and its virtual kinematic wave plane can be related by the watershed shape factor that involves the waterway length and slope and watershed area. In this study, two dimensionless watershed shape functions are derived to use parabolic function and trigonometric sine curve for watershed conversion. These two watershed shape functions produce good agreements with the maximum overland flow length method for hypothetical square watersheds. Also, these two watershed shape functions are able to reproduce similar kinematic wave plane widths as reported in a calibrated model. Furthermore, in this study, these two watershed shape functions are tested by nine observed rainfall events and three levels of modeling details. These 54 case studies reveal that the parabolic shape function consistently produces better agreements with the observed runoff hydrographs. Also, it is concluded that a model with more drainage details results in higher peak flows. On the contrary, a model with a low resolution tends to decrease the peak flow because of the significant surface detention volume spread in the overland flow.