Datalists & Features

STE is equipped with a primary database for storing hydrological information. It provides comprehensive data filtering capabilities based on all available parameters, as shown in the interface.

To ensure precise data selection, a dedicated data storage and management panel is available within the project file interface. Users can filter data based on the following parameters:

• Data ID
• River Name
• Station Name
• Sampling Year, Month, and Day
• Flow Discharge
• Bed Load Discharge
• Suspended Load Discharge
• Total Load Discharge

These filters enable users to quickly identify and select relevant datasets for analysis.

STE includes three advanced statistical methods for selecting data and improving regression curve fitting accuracy. Based on extensive research, these methods enhance sediment estimation precision when using fitted regression models.

Additionally, STE provides outlier detection and removal tools to increase reliability in sediment estimation calculations. These tools help refine datasets by eliminating anomalous or erroneous data points, ensuring robust and scientifically accurate results.

Manage Data #

Add Data #

Three methods are provided for adding data to the database in the hydrological calculations section. After clicking the Import Data button, the following window will appear:

1. STE Smart Data Manager
   Clicking this option will open the following window, where the user can enter the desired data into the table:

Using the Add Row button, you can add a new row to the table.

The Delete Last Row button removes the last row from the table.

The Clear button deletes all rows currently in the table.

The Import Data From Hydraulic Calculator Datalist option allows you to add data from the hydraulic calculations section of the project file. Clicking this option will open the following window:

On this page, you can filter the data using the Filters section. By checking the desired data items in the Selection area and clicking the Import button, you can add the selected data to the list on the previous page.

By clicking the OK button, the data will be added to the hydrological calculations database in the project file.

Please note:

• If you enter values for bed load and suspended load but leave the total load as zero or empty, the software will automatically calculate the total load.
• The day value must be an integer between 1 and 31.
• The month value must be an integer between 1 and 12.

2. STE Classic
   In this mode, data is added to the database using the following form:

After completing the form, clicking the Add button will add the entered data to the hydrological calculations database in the project file.
Please note:

• If you enter values for bed load and suspended load but leave the total load as zero or empty, the software will automatically calculate the total load.
• The day value must be an integer between 1 and 31.
• The month value must be an integer between 1 and 12.

3. Directly Using Access

In this mode, if Microsoft Access is installed on your computer, you can directly add, modify, or delete data through this software.
Please note:

• Data IDs (Data ID) must be sequential and properly ordered.
• The day value must be an integer between 1 and 31.
• The month value must be an integer between 1 and 12.

Edit Data #

To modify data, the process is similar to adding data, with the following differences:

• If you want to modify data using the STE Smart Data Manager method, first select the data you wish to edit by checking the boxes in the Selection section, then click the Edit Data button.
• If you want to modify data using the STE Classic method, simply enter the Data ID in the form to retrieve the corresponding data, and then you can make the necessary changes.

Delete Data #

To delete data from the database, first select the desired entries by checking the boxes in the Selection section, then click the Delete Data button to remove them.

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Data Selection & Filtering #

Tools for more precise selection and filtering of data based on hydrological criteria are provided on the left side of the data storage and management page in the project file of the software. Using these tools, you can filter data according to Data ID, River Name, Station Name, Sampling Year, Sampling Month, Sampling Day, Flow Discharge, Bed Load Discharge, Suspended Load Discharge, and Total Load Discharge to select the data for calculations.

By checking a desired parameter, you activate that parameter for data filtering.

For parameters such as Data ID, flow depth, flow discharge, bed load, suspended load, and total load, filtering is done by specifying minimum and maximum values. The minimum value entered on the left is considered as “greater than or equal to,” and the maximum value entered on the right is considered as “less than or equal to.”

To filter data based on river name or station name, after activating the filter, click the plus button and select the desired names from the displayed list.

On this page, by enabling the Select from List option, you can choose rivers that have been defined in the project file. Alternatively, by enabling the User Input option, you can directly enter the name of the desired river and add it to the river list.

Clicking the OK button will confirm the selected names for data filtering.

The same procedure applies for selecting station names.

When filtering data by the measurement year parameter, after clicking the plus option, you will be asked:
“Do you want to review the data and add the years present in the dataset but not currently selected to the list?”

By clicking Yes, the data will be reviewed, and all measurement years present in the dataset will be added to the list. Please note that if there is a large amount of data, this process may take some time.

Filtering data based on the day and month parameters works in the same way.

After selecting the parameters and values you want to filter by, click the OK button to apply the data filter.

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Statistical Methods for Improved Accuracy #

Statistical methods have also been added to the software to improve data selection and achieve better, more accurate regression line fitting. According to the research by Dehghani et al. (2014), these methods increase the accuracy of sediment quantity estimation using fitted regression lines.

To filter data using these methods, open the Tools menu on the data management page and click on Data Filtering Methods:

Data Filtering Based on High and Low Water Periods #

In this method, the software first calculates the annual average discharge and compares it with the monthly average discharge.
Months with an average discharge greater than or equal to the annual average are classified as high-water periods, while months with an average discharge less than the annual average are classified as low-water periods.

According to the user’s selection, the software will then filter and present the data accordingly.

Before using this tool, you can filter your data based on river name, station name, measurement year, and other criteria.
Only the filtered data will be used in the calculations performed by these tools.

By selecting the Low Water option, the data corresponding to the low-water period will be selected, and by selecting the High Water option, the data from the high-water period will be selected.
Clicking the OK button will perform the calculations and select the data in the table on the data management page.

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Data Filtering Using the Flow Discharge Classes Method #

In the Flow Discharge Classes method, the software first calculates the annual average discharge and divides the data into three categories:

• Class 1: Discharge values less than the average
• Class 2: Discharge values greater than or equal to the average and less than twice the average
• Class 3: Discharge values greater than or equal to twice the average

Based on the user’s selection, the software will filter and present the data accordingly.

Before using this tool, you can filter your data based on river name, station name, measurement year, and other criteria.
Only the filtered data will be used in the calculations performed by these tools.
The desired class can be selected by the user using the Data Selection section.

Clicking the OK button will perform the calculations and select the data in the table on the data management page.

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Middle of Data Classes Method #

In this method, the average sediment load of each class is estimated based on the average flow discharge within that class.
To do this, the software considers only the discharges for which sediment sampling has been conducted. These data are then sorted from smallest to largest based on flow discharge and divided into user-defined classes.

Next, the average discharge and the corresponding average sediment load are calculated for each class.

The entire process is carried out automatically by the software. The results are saved in a new list, ready for regression line fitting and neural network training.

Before using this tool, you can filter your data based on river name, station name, measurement year, and other criteria.
Only the filtered data will be used in the calculations performed by these tools.

Using the Number of Classes option, you can define how many classes to divide the data into. This parameter also determines the number of output data points generated by this method. The filtered data will be divided into the specified number of classes, and computations will be performed separately for each class.

Due to the nature of its process, this method is not a typical data filtering method. Instead, it produces new representative data derived from the original dataset. Therefore, these results must be stored directly in a child list.
You can use the ChildList Name field to enter the name of the child list where the results will be saved.

Clicking the OK button will execute the calculations, create a new child list with the specified name, and store the results in it.

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Calculation Lists (ChildLists) #

After filtering the data, in order to perform calculations, the filtered or selected data must be saved to new lists under user-defined names. In STE, these lists are referred to as ChildLists.

This feature allows users to easily create and manage different models for various months, years, or seasons, and to save and analyze the results accordingly.

To create a ChildList, click the Add List button. After clicking this button, a window will appear where you can enter a name for the new ChildList. Then, click OK to create it.

Using the Delete List option, you can delete a ChildList.
Using the Show List option, you can view and manage the data stored within the selected ChildList.

By selecting the data and clicking the Delete Selected Items button, you can remove the selected entries from the ChildList.

To add data to a ChildList, first create the desired ChildList. Then, select the data you want to add and click the Add Selected Items To the List button to add the selected data to the chosen ChildList.

Please note that the data added to ChildLists will not be removed from the main data list. Instead, a copy of the data, with the same Data ID, will be added to the ChildList.

To remove all data from a ChildList, use the Clear List option.

Also, keep in mind that only data stored in calculation ChildLists will be available for computations and building predictive models.
Therefore, before entering the computation section or creating estimation models, make sure the desired data is placed in the appropriate ChildLists.

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Outlier Detection #

To access the Outlier Detection page, open the Tools menu on the data management page and click on Outlier Detection.

Please note: This page analyzes data within ChildLists. Therefore, before accessing this page, make sure to place the desired data into the appropriate ChildLists.

Controls Section #

In this section, you can configure the settings for identifying outlier data.

• Using the DataList option, you can select the ChildList in which you want to detect outliers. After selecting the desired list, the data contained in that list will be displayed in the DataList area.
• Using the Focus On option, you need to specify whether the outlier detection should focus on bed load, suspended load, or total load data.
  It is important to note that after selecting this option, the sediment load data will be converted to sediment concentration based on the corresponding flow discharge in the selected list. Then, the logarithm of the sediment concentration values will be taken to generate a normal distribution for the data. The software uses the logarithm of sediment concentration to identify outliers.
• Using the Alpha option, you must specify a coefficient to define the acceptable data range. After calculating the mean and standard deviation, the software multiplies the alpha coefficient by the standard deviation and adds/subtracts this value from the mean to establish the upper and lower bounds of acceptable data.
  These parameters are reported to the user in the Info section.
• In the DataList Without Outlier Data section, data points that are within the acceptable range and are not outliers will be listed for the user.
  Data points outside this range are identified as outliers and will be shown to the user in the Outlier Data section.

For example, by selecting an alpha coefficient of 1, data points falling within the range (shown as dark blue in the figure above) are considered acceptable, while the rest are identified as outliers. (Here, μ denotes the mean and σ the standard deviation.)

In the Graph section, you can click on the XY Data button to examine the scatter plot of data points showing flow discharge versus corresponding sediment load. In this graph, outliers and acceptable data points are distinguished by different shapes and colors.

Using the Save option, you can save the filtered data back to the original ChildList from which the data was loaded.
Please note that the previous data in that ChildList will be completely deleted and replaced only with the accepted (non-outlier) data.

Using the Save As option, you can save the accepted data to a new ChildList.
When you click this option, a window will appear prompting you to enter a new name for creating the new ChildList.