Search for: All records

Sanitary sewer systems are critical urban water infrastructure that protect both human and environmental health. Their design, operation, and monitoring require novel modeling techniques that capture dominant processes while allowing for computationally efficient simulations. Open water flow in sewers and rivers are intrinsically similar processes. With this in mind, we formulated a new parsimonious model inspired by the Width Function Instantaneous Unit Hydrograph (WFIUH) approach, widely used to predict rainfallrunoff relationships in watersheds, to a sanitary sewer system consisting of nearly 10,000 sewer conduits and 120,000 residential and commercial sewage connections in Northern Virginia, U.S.A. Model predictions for the three primary components of sanitary flow, including Base Wastewater Flow (BWF), Groundwater Infiltration (GWI), and Runoff Derived Infiltration and Inflow (RDII), compare favorably with the more computationally demanding industry-standard Storm Water Management Model (SWMM). This novel application of the WFIUH modeling framework should support a number of critical water quality endpoints, including (i) sewer hydrograph separation through the quantification of BWF, GWI, and RDII outflows, (ii) evaluation of the impact of new urban developments on sewage flow dynamics, (iii) monitoring and mitigation of sanitary sewer overflows, and (iv) design and interpretation of wastewater surveillance studies. 

Abstract Analytical solutions for the three‐dimensional groundwater flow equation have been widely used to gain insight about subsurface flow structure and as an alternative to computationally expensive numerical models. Of particular interest are solutions that decompose prescribed hydraulic head boundaries (e.g., Dirichlet boundary condition) into a collection of harmonic functions. Previous studies estimate the frequencies and amplitudes of these harmonics with a least‐square approach where the amplitudes are fitted given a pre‐assigned set of frequencies. In these studies, an ad hoc and structured discretization of the frequency domain is typically used, excluding dominant frequencies while assigning importance to spurious frequencies, with significant consequences for estimating the fluxes and residence times. This study demonstrates the advantages of using a pre‐assigned frequency spectrum that targets the dominant frequencies based on rigorous statistical analysis with predefined significance levels. The new approach is tested for three hydrologic conceptualizations: (a) a synthetic periodic basin, (b) synthetic bedforms, and (c) a natural mountainous watershed. The performance of the frequency spectrum selection is compared with exact analytical or approximate numerical solutions. We found that the new approach better describes the fluxes and residence times for Dirichlet boundaries with well‐defined characteristics spatial scales (e.g., periodic basins and bedforms). For more complex scenarios, such as natural mountainous watersheds, both pre‐assigned frequency spectrums present similar performance. The spectral solutions presented here can play a central role in developing reduced‐complexity models for assessing regional water and solute fluxes within mountain watersheds and hyporheic zones. 

Abstract Although prior studies have evaluated the role of sampling errors associated with local and regional methods to estimate peak flow quantiles, the investigation of epistemic errors is more difficult because the underlying properties of the random variable have been prescribed using ad‐hoc characterizations of the regional distributions of peak flows. This study addresses this challenge using representations of regional peak flow distributions derived from a combined framework of stochastic storm transposition, radar rainfall observations, and distributed hydrologic modeling. The authors evaluated four commonly used peak flow quantile estimation methods using synthetic peak flows at 5,000 sites in the Turkey River watershed in Iowa, USA. They first used at‐site flood frequency analysis using the Pearson Type III distribution with L‐moments. The authors then pooled regional information using (1) the index flood method, (2) the quantile regression technique, and (3) the parameter regression. This approach allowed quantification of error components stemming from epistemic assumptions, parameter estimation method, sample size, and, in the regional approaches, the number ofpooledsites. The results demonstrate that the inability to capture the spatial variability of the skewness of the peak flows dominates epistemic error for regional methods. We concluded that, in the study basin, this variability could be partially explained by river network structure and the predominant orientation of the watershed. The general approach used in this study is promising in that it brings new tools and sources of data to the study of the old hydrologic problem of flood frequency analysis.