Simulation results and the figures in the manuscript that are generated. This dataset is associated with the following publication: Shang, F., J. Burkhardt, and R. Murray. Random Walk Particle Tracking to Model Dispersion in Steady Laminar and Turbulent Pipe Flow. JOURNAL OF HYDRAULIC ENGINEERING. American Society of Civil Engineers (ASCE), Reston, VA, USA, 149(7): 04023022, (2023).

Two model input files and all the simulation results in the paper. This dataset is associated with the following publication: Shang, F., H. Woo, J. Burkhardt, and R. Murray. Lagrangian Method to Model Advection-Dispersion-Reaction Transport in Drinking Water Pipe Networks. JOURNAL OF WATER RESOURCES PLANNING AND MANAGEMENT. American Society of Civil Engineers (ASCE), Reston, VA, USA, 147(9): 04021057, (2021).

Two model input files and all the simulation results in the paper. This dataset is associated with the following publication: Shang, F., H. Woo, J. Burkhardt, and R. Murray. Lagrangian Method to Model Advection-Dispersion-Reaction Transport in Drinking Water Pipe Networks. JOURNAL OF WATER RESOURCES PLANNING AND MANAGEMENT. American Society of Civil Engineers (ASCE), Reston, VA, USA, 147(9): 04021057, (2021).

Simulation results for one dimensional advection-dispersion-reaction modeling withing drinking water distribution system. Analytical solutions are provided when possible.

Model input data in InputData.xls. Table and figure data in stored_results.xls. This dataset is associated with the following publication: Burkhardt, J., B. Burkhart, and F. Shang. Modeling Nicotine-Induced Chlorine Loss in Drinking Water Using Updated EPANET-MSX. JOURNAL OF ENVIRONMENTAL ENGINEERING. American Society of Civil Engineers (ASCE), Reston, VA, USA, 149(12): 04023086, (2023).

Simulation results on water age analysis. Comparison of the results between EPAENT 2.2 and 2.0. This dataset is associated with the following publication: Burkhart, B., and R. Janke. Understanding Water Age in Distribution Systems with EPANET. Journal AWWA. American Water Works Association, Denver, CO, USA, 115(2): 24-34, (2023).

Simulation results on water age analysis. Comparison of the results between EPAENT 2.2 and 2.0. This dataset is associated with the following publication: Burkhart, B., and R. Janke. Understanding Water Age in Distribution Systems with EPANET. Journal AWWA. American Water Works Association, Denver, CO, USA, 115(2): 24-34, (2023).

The full report on sediment resuspension in drinking water storage tanks and a link to an animation of results. This dataset is associated with the following publication: Ho, C., R. Murray , J. Christian, E. Ching, J. Slavin, J. Ortega, and L. Rossman. Sediment Resuspension and Transport in Water Distribution Storage Tanks. JOURNAL OF THE AMERICAN WATER WORKS ASSOCIATION. American Water Works Association, Denver, CO, USA, 108(6): ., (2016).

The full report on sediment resuspension in drinking water storage tanks and a link to an animation of results. This dataset is associated with the following publication: Ho, C., R. Murray , J. Christian, E. Ching, J. Slavin, J. Ortega, and L. Rossman. Sediment Resuspension and Transport in Water Distribution Storage Tanks. JOURNAL OF THE AMERICAN WATER WORKS ASSOCIATION. American Water Works Association, Denver, CO, USA, 108(6): ., (2016).

This dataset contains files used in this Monte Carlo simulation study comparing the performance of five statistical models for adjusting design floods for current conditions at sites with known trends. These files include (i) the observed annual peak-flow series in the conterminous US used to inform ranges of known moments and trends used in the simulation experiment, (ii) the 3,000 combinations of Monte Carlo experiment parameters (including sample moments, trends, distribution types, and record lengths), (iii) the 5,000 100-year time series of random uniform variates used as annual non-exceedance probabilities in the generation of synthetic annual peak-flow series, (iv) the simulated and true (known) quantiles associated with the 10% and 1% annual exceedance probabilities conditioned on the last years of the synthetic annual peak-flow series generated through the experiment. This dataset also contains a model archive with the R statistical software code used to execute the study along with a document describing the contents of the archive and providing instructions for reproducing results.