Hydrological Model Uncertainty Quantification via Segmented Runoff Multipliers
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Solution Overview
Problem
Current hydrological models fail to effectively quantify the uncertainty of runoff production structures, such as surface runoff, interflow, and base flow structures, and their impact on the surface-subsurface hydrological process, leading to low accuracy and high computational costs in simulations.
Innovation Solution
A modified hydrological model based on the SIMHYD model that collects hydrometeorological data to calculate evaporation loss, soil infiltration, and water storage, and uses random multipliers following a normal distribution to quantify the uncertainty of runoff components, incorporating a confluence module to adjust for river channel confluence and optimize parameters using the Shuffled Complex Evolution algorithm.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If multiple hydrological models with different structures are combined to analyze uncertainty, then the uncertainty of model structure can be analyzed, but the computational cost is high and practical application is low
Solution Approach 1:
The patent segments the uncertainty analysis into three distinct runoff production structures (surface runoff, interflow, and base flow) rather than treating all model structural uncertainties together. This segmentation allows targeted analysis of each structure's uncertainty contribution while reducing the overall computational burden compared to analyzing all possible model structure combinations.
Solution Approach 2:
The patent extracts and isolates the runoff production structure uncertainty from other sources of model uncertainty (parameter uncertainty, confluence structure uncertainty). By using random multipliers specifically applied to runoff production components, the method separates this specific uncertainty source for independent quantification, reducing the complexity of analyzing all uncertainties simultaneously.
2Measurement precision
If post-processing methods are used to describe differences in simulation results, then uncertainty can be quantified, but the uncertainty of specific processes cannot be analyzed separately
Solution Approach 1:
The patent divides the runoff production process into three distinct components (surface runoff, interflow, and base flow) and applies separate random multipliers to each component. This segmentation enables the uncertainty of each specific process to be analyzed independently while maintaining the overall simulation framework, preventing the loss of process-specific uncertainty information.
Solution Approach 2:
The patent applies different random multipliers (φSURF, φINTER, φBASE) to different runoff production components, allowing each component to have its own uncertainty characteristics. This local differentiation preserves the specific uncertainty information of each hydrological process rather than treating all uncertainties uniformly.
3Productivity
If traditional hydrological models are used, then the simulation can be performed, but the uncertainty of runoff production structure cannot be characterized
Solution Approach 1:
The patent introduces random multipliers (φSURF, φINTER, φBASE) as intermediary variables between the deterministic runoff production calculations and the final simulation results. These multipliers serve as mediators that incorporate structural uncertainty into the model without fundamentally changing the underlying hydrological processes, maintaining simulation capability while adding uncertainty characterization.
Solution Approach 2:
The patent transforms the deterministic runoff production structure into a probabilistic one by changing the parameters from fixed values to random variables with specific distributions. This parameter transformation allows the model to characterize structural uncertainty while maintaining the same basic simulation framework, improving measurement precision without sacrificing productivity.
Data Source
AI summary
The present invention discloses a hydrological model considering the uncertainty of a runoff production structure and a method for quantifying influence on a surface-subsurface hydrological process. The present invention quantifies the uncertainty of runoff production structures including a surface runoff structure, an interflow structure and a base flow structure by using parameters, and constructs a hydrological model considering the uncertainty of a runoff production structure by combining an added confluence module. Compared with an original hydrological model, the hydrological model has higher precision, which is capable to quantify the uncertainty of surface runoff, interflow and base flow of the runoff production structure and its impact on the surface-subsurface hydrological process, better improve precision of runoff simulation, and enhance understanding and cognition of the basic rule of a hydrological physical process.