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10:35
A Protocol for Conducting Rainfall Simulation to Study Soil Runoff
Published on: April 3, 2014
Comparison of genetic programming and HEC-HMS as a conceptual model in simulating rainfall-runoff time series
Reza Sepahvand1, Mehrdad Khoshoei2, Mohammad H Golmohammadi1
1Department of Civil Engineering, Isfahan University of Technology, Khoramabad River basin, Iran.
Scientific Reports
|June 2, 2026
Summary
Accurate rainfall-runoff forecasting is crucial. A genetic programming (GP) model outperformed the HEC-HMS model in simulating river discharge, demonstrating superior accuracy in data-rich environments for hydrological modeling.
Area of Science:
- Hydrology
- Computational Intelligence
- Environmental Modeling
Background:
- Rainfall-runoff process forecasting is vital for water resource management but complicated by spatiotemporal variability, leading to modeling inaccuracies.
- Accurate hydrological simulations are essential for predicting water availability and managing flood risks.
Purpose of the Study:
- To assess the performance of a genetic programming (GP) model in simulating the rainfall-runoff process.
- To compare the accuracy of the GP model against the conceptual HEC-HMS model for runoff forecasting in the Khorramabad River basin.
Main Methods:
- Employed a genetic programming (GP) model for data-driven rainfall-runoff simulation.
- Utilized the HEC-HMS model, calibrated for four flood events, as a benchmark for comparison.
- Conducted sensitivity analysis by excluding sub-watersheds and investigated the Curve Number (CN) parameter.
Main Results:
- The GP model achieved higher accuracy, with R² values ranging from 0.88 to 0.94.
- The HEC-HMS model yielded R² values between 0.65 and 0.79.
- The GP model demonstrated superior performance in simulating peak discharge and overall runoff compared to HEC-HMS.
Conclusions:
- Genetic programming offers a more accurate approach to rainfall-runoff simulation in data-rich conditions.
- The GP model's effectiveness in the Khorramabad River basin suggests its potential for improving hydrological forecasting in similar environments.
- Event-calibrated HEC-HMS models may be less accurate than data-driven GP models when extensive historical hydrological data is available.
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