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The ResSim Blog

This blog was created by Kevin Fagot, a water resources engineer for the modeling of reservoir systems in HEC-ResSim. Programming examples in Python and Jython (scripting language used in HEC-ResSim) are also shown. Since data development and analysis plays an important part in the development and use of this model, you will also find examples of this using Python, Microsoft Excel, and HEC-DSSVue. The posts are labeled by topic so you can use the menu on the right or search by topic.

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Link to videos related to HEC-ResSim blog

on September 15, 2019

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Using HEC-DSSVue to Convert Irregular Data to Daily Data

on September 03, 2019

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Making Changes to an Induced Surcharge Envelope Curve

on August 19, 2019

General Reservoir Operations

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Interpreting Water Control Manuals - Spillway Gate Regulation Schedule

on August 19, 2019

General Reservoir Operations

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Basics of Reservoir Operations

on August 16, 2019

General Reservoir Operations

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Description of Reservoir Zones

on August 16, 2019

General Reservoir Operations

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Use of Induced Surcharge Envelope Curves

on April 29, 2019

General Reservoir Operations

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Development of Induced Surcharge Envelope Curve

on March 25, 2019

General Reservoir Operations

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Using Python to Extract Data from a Website

on December 19, 2018

Python Advanced

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Developing an Annual Time Series Axis in Excel

on December 10, 2018

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Rainfall forecasts and rainfall totals from Hurricane Florence

on September 21, 2018

General Reservoir Operations

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National Flood Insurance Program (NFIP) for an area impacted by Hurricane Harvey

on June 04, 2018

General Reservoir Operations

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General Reservoir Operations
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Microsoft Excel Basic #2 - Computations on multiple columns of data

In this post, we build on Microsoft Excel Basic #1 by adding additional columns of grades. We copy the average, minimum, and maximum grades for the class and compute the average for each student. In the figure below, we can see that the grades of three tests are now in the spreadsheet. The grades are in columns B, C, and D. To copy the formulas to columns C and D, we highlight cells B8 through B10. We left click on the square in the bottom right hand corner and drag over to column D. Excel automatically updates the formula for columns C and D. From the figure below, we can see that the average in column C has been automatically updated. To compute the average for each student, we are writing a formula in column F. For Bart, the formula is as follows: =AVERAGE(B2:D2) To apply the formula for all students, left click on the square in the bottom right hand corner and drag down to cell F6. Excel will update the formula by applying the incremented row

How to Develop a Working Model

The previous blog posts showed specific applications using the HEC-ResSim software. This post will show the creation of an HEC-ResSim model taking the reader through the Watershed Setup module, the Reservoir Network module, and the Simulation module. Note: I have developed a video showing the development of an HEC-ResSim model that can be viewed here: The initial model development will be that of a flow through model. It is recommended that the initial model setup be a flow through model to test the connectivity of the stream network and the overall behavior of the initial model setup. A flow through model consists of the following model characteristics: 1.) No rules of operation are entered into the model 2.) A constant inflow is applied at the upstream ends of the main stem and all tributaries 3.) The reservoirs are set to the top of the conservation pool and are releasing inflow in the lookback period. 4.) The routing is set to null routing. Once the re

Python Intermediate #3 - Random Multiplication Practice using randint

In our previous example, we used a list with a for loop in Python to print out multiplication tables. This example allows the user to practice multiplication of two random values. For this post, we will use an if statement along with the randint function from the random module. Additionally we will be using a while loop to ask the user if they want to keep playing. The coding of the randint function can be found at this site: https://docs.python.org/2/library/random.html Scrolling down to randint shows the following: This tells us that this function will produce an random integer from a to b. If we code the following: x = randint(0,9) print("The random integer is ",x) We would expect to get a message giving us a random number between 0 and 9. Instead, we get this: This is because we need to import randint from the random method. We do this as follows: from random import randint x = randint(0,9) print("The random integer is ",x) Now, we

Additional error fixing in HEC-ResSim

This post will cover two additional error messages that can occur in the development of an HEC-ResSim model. Special thanks to Logan Osgood-Jacobs of the Seattle District of the Corps of Engineers for supplying these screenshots. Error 1: Ghost Nodes Ghost nodes, or nodes that you did not intend to include in the model, seem to periodically occur in the development of ResSim models. I have gotten these when I have had to edit the watershed configuration and then perform an update to the reservoir network. However, I believe that others have gotten ghost nodes in the initial development of the model. So, how do you tell if you have a ghost node? The most direct way is getting an error message similar to the one below when you compute your simulation. This error message is indicating an issue with Node 81. In the Reservoir Network Module, go to Reports > Advanced > Node List. The report is shown below. There is a node named, "Node 81". Not havi

Computing Kendall's Tau parameter for time series data

Introduction. In this post, the Kendall's Tau parameter will be computed for the annual peak flow data for Dog Branch at St. Paul, Arkansas. This data was derived from the USGS website. The computation of the Kendall's Tau parameter was performed in Microsoft Excel for this analysis. Examining the Kendall's Tau parameter on time series data will help to indicate if a trend exists and how strong it is. If the Kendall's Tau parameter is close to 1, a strong rising trends exists. If the Kendall's Tau parameter is close to -1, a strong falling trend exists. If the parameter is close to zero, then neither a falling or rising trend exists. First Step - Visualize the Data. A good first step in determining a trend is to visually examine the time series data. This is shown below. From the chart above, it appears that a trend is not apparent. In the next steps, the Kendall's Tau parameter will be computed to see if that assumption holds. Next Step - How is the

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