Research on the Longitudinal Section of River Restoration Using Probabilistic Theory

Area of Science:

• Hydrology
• Geomorphology
• Environmental Science

Background:

• Urbanization has led to river degradation since the 1960s, necessitating accurate topographic data for restoration.
• Traditional river surveying methods are challenging during rapid flow changes (e.g., floods) and costly for frequent measurements.
• Existing research often lacks sufficient data on river longitudinal profiles, focusing primarily on cross-sections.

Purpose of the Study:

• To develop real-time equations for calculating average river slope, river slope, and river longitudinal elevation using informational entropy theory.
• To address the limitations of traditional surveying methods for obtaining river characteristic factors, especially during dynamic flow conditions.
• To provide a more comprehensive understanding of river longitudinal profiles.

Main Methods:

• Application of informational entropy theory to derive new equations for river characteristic factors.
• Utilizing nonlinear regression analysis with actual river data to calculate parameters.
• Comparing the derived equations with measured river topographic data to assess applicability.

Main Results:

• Developed equations demonstrated high accuracy, with R-squared values consistently above 0.80.
• Root Mean Square Error (RMSE) values ranged from 0.54 to 2.79, indicating reliable predictions.
• The study successfully calculated longitudinal elevation entropy equations and average river slope.

Conclusions:

• The presented equations offer a valid and accurate method for calculating essential river characteristic factors in real-time.
• Informational entropy theory provides a powerful tool for analyzing and quantifying river longitudinal profiles.
• This research contributes to improved river management and restoration strategies by enabling more accessible and accurate data acquisition.