Related Experiment Video
Updated: Jul 19, 2025
06:37
Continuous Hydrologic and Water Quality Monitoring of Vernal Ponds
Published on: November 13, 2017
9.3K
Monthly runoff prediction based on a coupled VMD-SSA-BiLSTM model.
Xianqi Zhang1,2,3, Xin Wang4, Haiyang Li1
1Water Conservancy College, North China University of Water Resources and Electric Power, Zhengzhou, 450046, China.
Scientific Reports
|August 12, 2023
Summary
A new VMD-SSA-BiLSTM model accurately predicts monthly Yellow River runoff. This hybrid approach improves water resource management and flood prevention by enhancing prediction accuracy over existing methods.
Area of Science:
- Hydrology and Water Resources Engineering
- Artificial Intelligence in Environmental Science
- Time Series Forecasting
Background:
- Accurate monthly runoff prediction in the lower Yellow River is vital for water resource management, allocation, and flood control.
- Existing prediction models may not fully capture the complex dynamics of river runoff processes.
Purpose of the Study:
- To develop and evaluate a novel hybrid model, Variational Modal Decomposition-Sparrow Search Algorithm-Bi-directional Long and Short-Term Memory Neural Network (VMD-SSA-BiLSTM), for monthly runoff prediction.
- To assess the performance of the VMD-SSA-BiLSTM model against conventional BiLSTM and VMD-BiLSTM models.
Main Methods:
- Variational Modal Decomposition (VMD) was employed for signal decomposition and preprocessing of runoff data.
- Sparrow Search Algorithm (SSA) was utilized to optimize the parameters of the Bi-directional Long and Short-Term Memory Neural Network (BiLSTM).
- The coupled VMD-SSA-BiLSTM model was applied to predict monthly runoff at the GaoCun hydrological station.
Main Results:
- The VMD-SSA-BiLSTM model demonstrated superior prediction accuracy compared to BiLSTM and VMD-BiLSTM models.
- Significant improvements were observed in Root-mean-square deviation (RMSD), Mean Absolute Percentage Error (MAPE), Mean Absolute Error (MAE), coefficient of determination (R²), and Nash-Sutcliffe Efficiency (NSE).
- Specifically, RMSD decreased by 242.5124 and 39.9835, MAPE by 35.5937% and 6.3856%, MAE by 136.7288 and 25.7274, R² increased by 0.53059 and 0.14739, and NSE increased by 0.4994 and 0.1122, respectively.
Conclusions:
- The VMD-SSA-BiLSTM model effectively enhances the smoothness of monthly runoff series and improves point prediction accuracy.
- The proposed hybrid model offers a promising tool for reliable monthly runoff forecasting in the lower Yellow River basin.
- This approach contributes to better water resource management and flood risk mitigation strategies.
More Related Videos
Related Concept Videos
01:30Typical Model Studies
382
Fluid mechanics model studies often utilize scaled-down systems to predict fluid behavior in full-scale environments, such as river flows, dam spillways, and structures interacting with open surfaces. Maintaining Froude number similarity in river models is crucial, as it replicates surface flow features like wave patterns and velocities.
382
01:14Conservation of Mass in Moving, Nondeforming Control Volume
1.1K
Stormwater detention basins are essential in managing runoff during heavy rainfall, particularly in urban areas where impervious surfaces increase the risk of flooding. Understanding the conservation of mass in these systems allows engineers to optimize basin performance, balancing inflow, outflow, and water storage.
In the context of a detention basin, the conservation of mass states that the total mass of water entering the basin must equal the mass leaving the basin plus any accumulation of...
In the context of a detention basin, the conservation of mass states that the total mass of water entering the basin must equal the mass leaving the basin plus any accumulation of...
1.1K
01:21Design Example: Creating a Hydraulic Model of a Dam Spillway
217
Scaled hydraulic models of dam spillways provide a practical way to replicate and study the intricate flow dynamics of these structures. Often built to a 1:15 ratio, these models allow for observing critical water behavior, such as velocity distribution, flow patterns, and energy dissipation.
217
01:12Modeling and Similitude
290
Scaled modeling is a fundamental technique in engineering, enabling the study of large and complex systems by creating smaller, manageable replicas that recreate critical characteristics of the original. In hydrology and civil infrastructure, for example, scaled models of dams help analyze water flow, turbulence, and pressure. This method allows for accurate predictions of real-world behavior within a controlled environment, significantly reducing the cost and time involved in full-scale...
290
01:17Design Example: Analyzing Capacity Contours for Flood Risk Assessment
71
Flood risk assessment involves careful planning and analysis to ensure the safety of communities near water retention structures. Capacity contours are a vital tool in this process, as they illustrate the potential spread of water at specific levels in a given area. In the context of building a bund across a small valley, these contours play a critical role in evaluating the safety of nearby residential areas.In this example, the bund is intended to store stormwater in the valley. The engineers...
71
01:12Precipitation Processes
486
The experimental conditions in a gravimetric analysis should be optimized to maximize the particle size and purity of the obtained precipitate. Ideally, the concentration of the precipitating reagent should be low with effective stirring to maintain low relative supersaturation for the growth of large crystals. In homogeneous precipitation, the precipitant is slowly generated by a chemical reaction in the solution to avoid local reagent excesses. For example, urea decomposes gradually to...
486