Vincent F. Bralts

Rill erosion and morphological evolution: A simulation model

A mathematical model is advanced to simulate dynamically and spatially varied shallow water flow and soil detachment, transport, and deposition in rills. The model mimics the dynamic process of rill evolution, including variable rates of sediment redistribution along the bed and changes in local bed morphology. The sediment source term in the model uses a point scale, probabilistic relationship based on turbulent flow mechanics and a recently developed sediment transport relationship for rills based on stream power. The interdependent feedback loops between channel bed morphology, local flow hydraulics, and local scour and deposition, within the framework of the full hydrodynamic equations with inertial terms, constitute a mathematical model with the capacity to represent spatial variability and temporal evolution of the rill. Finite elements were applied to numerically solve the hydrodynamic and sediment continuity equations. A series of laboratory flume experiments were performed to evaluate the model. Initial bed slopes were 3, 5, and 7% with step increases of water inflow rates of 7.6, 11.4, and 15.2 L min−1. The soil material used in the flume was a kaolinitic, sandy-clay loam. The rill model equations were solved for increasingly complex cases of spatial and temporal variabilities. The model followed measured patterns of morphological changes as the rill evolved, which suggests that the feedback loops in the model between erosion, bed morphological changes, and hydraulics were adequate to capture the essence of rill evolution.

Enhancing a rainfall-runoff model to assess the impacts of BMPs and LID practices on storm runoff.

Best management practices (BMPs) and low impact development (LID) practices are increasingly being used as stormwater management techniques to reduce the impacts of urban development on hydrology and water quality. To assist planners and decision-makers at various stages of development projects (planning, implementation, and evaluation), user-friendly tools are needed to assess the effectiveness of BMPs and LID practices. This study describes a simple tool, the Long-Term Hydrologic Impact Assessment-LID (L-THIA-LID), which is enhanced with additional BMPs and LID practices, improved approaches to estimate hydrology and water quality, and representation of practices in series (meaning combined implementation). The tool was used to evaluate the performance of BMPs and LID practices individually and in series with 30 years of daily rainfall data in four types of idealized land use units and watersheds (low density residential, high density residential, industrial, and commercial). Simulation results were compared with the results of other published studies. The simulated results showed that reductions in runoff volume and pollutant loads after implementing BMPs and LID practices, both individually and in series, were comparable with the observed impacts of these practices. The L-THIA-LID 2.0 model is capable of assisting decision makers in evaluating environmental impacts of BMPs and LID practices, thereby improving the effectiveness of stormwater management decisions.

Evaluating the effectiveness of management practices on hydrology and water quality at watershed scale with a rainfall-runoff model.

The adverse influence of urban development on hydrology and water quality can be reduced by applying best management practices (BMPs) and low impact development (LID) practices. This study applied green roof, rain barrel/cistern, bioretention system, porous pavement, permeable patio, grass strip, grassed swale, wetland channel, retention pond, detention basin, and wetland basin, on Crooked Creek watershed. The model was calibrated and validated for annual runoff volume. A framework for simulating BMPs and LID practices at watershed scales was created, and the impacts of BMPs and LID practices on water quantity and water quality were evaluated with the Long-Term Hydrologic Impact Assessment-Low Impact Development 2.1 (L-THIA-LID 2.1) model for 16 scenarios. The various levels and combinations of BMPs/LID practices reduced runoff volume by 0 to 26.47%, Total Nitrogen (TN) by 0.30 to 34.20%, Total Phosphorus (TP) by 0.27 to 47.41%, Total Suspended Solids (TSS) by 0.33 to 53.59%, Lead (Pb) by 0.30 to 60.98%, Biochemical Oxygen Demand (BOD) by 0 to 26.70%, and Chemical Oxygen Demand (COD) by 0 to 27.52%. The implementation of grass strips in 25% of the watershed where this practice could be applied was the most cost-efficient scenario, with cost per unit reduction of

Optimal selection and placement of BMPs and LID practices with a rainfall-runoff model

1m3/yr for runoff, while cost for reductions of two pollutants of concern was

Sensitivity and Uncertainty Analysis of the L-THIA-LID 2.1 Model

445 kg/yr for Total Nitrogen (TN) and

Anti-clogging evaluation for drip irrigation emitters using reclaimed water

4871 kg/yr for Total Phosphorous (TP). The scenario with very high levels of BMP and LID practice adoption (scenario 15) reduced runoff volume and pollutant loads from 26.47% to 60.98%, and provided the greatest reduction in runoff volume and pollutant loads among all scenarios. However, this scenario was not as cost-efficient as most other scenarios. The L-THIA-LID 2.1 model is a valid tool that can be applied to various locations to help identify cost effective BMP/LID practice plans at watershed scales.

An approximate point source method for soil infiltration process measurement

A decision support tool, which links a hydrologic/water quality model (L-THIA-LID 2.1) with optimization algorithms (AMALGAM) using a computational efficiency framework (MLSOPT), was developed to optimally implement BMPs and LID practices to reduce runoff and pollutant loads. The decision support tool was applied in the Crooked Creek watershed, Indiana, USA. For initial expenditures on practices, the environmental benefits increased rapidly as expenditures increased. However, beyond certain expenditure levels, additional spending did not result in noticeable additional environmental impacts. Compared to random placement of practices, the optimization strategy provided 3.9-7.7 times the level of runoff/pollutant load reductions for the same expenditures. To obtain the same environmental benefits, costs of random practices placement were 4.2-14.5 times the optimized practice placement cost. The decision support tool is capable of supporting decision makers in optimally selecting and placing BMPs and LID practices to obtain maximum environmental benefits with minimum costs. A decision support tool was developed to optimally implement BMPs/LID practices.Decision support tool was applied at Crooked Creek watershed in Indiana, USA.Decision support tool is capable of optimally implementing BMPs/LID practices.

An analytical approximation method for the linear source soil infiltrability measurement and its application

Sensitivity analysis of a model can identify key variables affecting the performance of the model. Uncertainty analysis is an essential indicator of the precision of the model. In this study, the sensitivity and uncertainty of the Long-Term Hydrologic Impact Assessment-Low Impact Development 2.1 (L-THIA-LID 2.1) model in estimating runoff and water quality were analyzed in an urbanized watershed in central Indiana, USA, using Sobol′‘s global sensitivity analysis method and the bootstrap method, respectively. When estimating runoff volume and pollutant loads for the case in which no best management practices (BMPs) and no low impact development (LID) practices were implemented, CN (Curve Number) was the most sensitive variable and the most important variable when calibrating the model before implementing practices. When predicting water quantity and quality with varying levels of BMPs and LID practices implemented, Ratio_r (Practice outflow runoff volume/inflow runoff volume) was the most sensitive variable and therefore the most important variable to calibrate the model with practices implemented. The output uncertainty bounds before implementing BMPs and LID practices were relatively large, while the uncertainty ranges of model outputs with practices implemented were relatively small. The limited observed data in the same study area and results from other urban watersheds in scientific literature were either well within or close to the uncertainty ranges determined in this study, indicating the L-THIA-LID 2.1 model has good precision.

Methods for measuring soil infiltration: State of the art

Emitter clogging has a direct impact on the required operating time and benefit of a drip irrigation system, especially when using reclaimed water. Thus, accurately evaluating its anti-clogging ability is important to select an appropriate emitter under specific conditions. In his paper, a drip irrigation emitter clogging experiment was carried out, and the dynamic outflows of 14 emitter types using 3 kinds of reclaimed water and the groundwater in the experiment station in Tongzhou, Beijing, were tested. Then, the drip irrigation emitter anti-clogging ability evaluation index (Ia) was proposed, based on the measured emitter clogging characteristics. Ia ranked in consistent with average discharge variation rate (Dra) among different types of emitters. Thus, Ia is a valid performance indicator to evaluate anti-clogging ability, and an emitter with a relatively large value of Ia has a better anti-clogging ability. According to the calculated Ia, the same type of emitter showed better anti-clogging ability with the groundwater than with the reclaimed water, while cylindrical emitters were more likely to clog than flat emitters. Additionally, Ia was mainly affected by flow path length (L), flow path width/depth ratio (RW/D) and average near-wall water shear force (τ), as Ia increased with shorter L, smaller RW/D and larger τ. Furthermore, the quantitative estimating model of Ia was established through dimensional analysis and was predicted by an emitter’s rated outflow (Q) and flow path geometrical parameters (L, W and D).