ABSTRACT:

This resource contains MATLAB scripts and input data needed to replicate results presented in "M. S. Riasi, A. Teklitz, W. Shuster, C. Nietch, L. Yeghiazarian, Reliability-Based Water Quality Assessment with Load Resistance Factor Design: Application to TMDL, Journal of Hydrologic Engineering, 2018."

This resource contains two separate packages:

1. LRFD_ShepherdsCreek.zip: This zipped folder contains MATLAB scripts and input data needed to replicate results presented in section 3.1 of the above-mentioned article. The contamination data for DIN and TP in 6 stations in Shepherds Creek watershed is stored in “Contamination Data” subfolder. The USGS flow data for these stations in stored in “Flow Data” subfolder.
To run the code, user need to run “MAIN_LRFD.m” script. Immediately after running the script, user will be prompted to choose the target station and target contaminant. User will also need to answer two questions: i) Would you like to keep all storm events?” ii) would you like to keep zero flow data?. To replicate our results, default answers must be selected (Yes and No respectively).
Once the run is complete, the results for “FORM reliability analysis”, “LRFD design for 25% probability of failure” and “post-design FORM reliability analysis” will be printed in the command window.

2. LRFD_UEFW_ExcelSheet.zip: This zipped folder contains MATLAB scripts and input data needed to replicate results presented in section 3.2 of the above-mentioned article.
To run the code, user need to run “MAIN_LRFD.m” script. Immediately after running the script, user will be prompted to select the input Excel sheet. The input Excel sheets for the 3 cases studied in this article can be found in “InputExcelLRFD” subfolder.
Once the run is complete, the results for “FORM reliability analysis” and “LRFD design for 25% probability of failure” will be printed in the command window.
Users can create their own cases by duplicating the Excel files and changing the numbers highlighted with blue font.

ABSTRACT:

This resource contains input ArcGIS files, input data and the results for the GRR subwatershed reliability analysis presented in "A. Teklitz, C. Nietch, M. S. Riasi, L. Yeghiazarian, Reliability Theory for Water Quality and Sustainability Assessment, Journal of Hydrology, 2020."

This resource contains two separate packages:

1. ArcGIS_InputFiles_GRR.zip: This zipped folder contains the ArcGIS files related to GRR subwatershed: Schematic network shapefiles (Schemanode, Schemalink and hillslope), NLCD land cover raster, and NHDplus_V2 shapefile used to extract streamflow and stream velocity.

2. GRR_ReliabilityAnalysis_Data&Results.xlsx: This Excel sheet contains the list of nodes, links and hillslopes in the schematic network of GRR subwatershed, the land cover distribution in each hillslope, the associated export coefficients, and the reliability analysis results for all stream reaches.

ABSTRACT:

This resource contains the MATLAB codes and data files needed to replicate the results presented in "M. S. Riasi, L. Yeghiazarian, Controllability of Surface Water Networks, Water Resources Research, 2017."
Theis resource contains two separate packages:

1. Controllability CODE: This folder contains the MATLAB scripts and data needed to perform structural controllability analysis. User can run the code simply by running the "MAIN.m" script. Immediately after running this script, user is prompted to select a text file that contains the directed graph of the network from "Input Data" folder. "Input Data" folder includes the digraphs of all 11 networks used in this study. For each network, two .txt file exist: "NetworkName.txt" and "NetworkName_XY". The first text file includes the edges of the the digraph and the latter includes coordinate of the nodes. For the MAIN script to work, user must select the "NetworkName.txt".

2. Network Extraction: The network extraction code only consists of one MATLAB script: "StreamNetReader.m". This script was written to extract the digraph of delta images. By running "StreamNetReader.m", user can select from a catalog of 7 delta images.

ABSTRACT:

Although controlling the level of contamination everywhere in the surface water network may not be feasible, it is vital to maintain safe water quality levels in specific areas, e.g. recreational waters. The question then is “what is the most efficient way to fully/partially control water quality in surface water networks?”.
This can be posed as a control problem where the goal is to efficiently drive the system to a desired state by manipulating few input variables. Such problems reduce to (1) finding the best control locations in the network to influence the state of the system; and (2) choosing the time-variant inputs at the control locations to achieve the desired state of the system with minimum effort. We demonstrate that the optimal solution to control the level of contamination in the network can be found through application of control theory concepts to transport in surface water networks.