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<p>As climate change intensifies the variability of rainfall patterns, understanding runoff behavior and the trend of the rising limb of the hydrograph under diverse scenarios becomes increasingly essential. This research addresses the gap by examining the influence of rainfall intensity and duration on sandy slopes through controlled laboratory experiments. This study delves into the intricate relationship between rainfall characteristics and runoff dynamics, focusing on enhancing accurate runoff prediction and the hydrograph’s rising limb, a critical element for effective water and flood management. Current models, such as the Natural Resources Conservation Service Curve Number (NRCS-CN) method, simplify runoff estimation despite their complexity and accuracy variability. Artificially created and simulated rainfall was applied across a range of intensities (150 to 700&#xa0;L per hour, LPH), durations (10, 20, and 30&#xa0;min), and slope gradients of slight (1º), moderate (2º), and steep (3º), resulting in 108 simulations. The regression-based model developed in this study offers a robust framework for capturing Rainfall-Runoff interactions, demonstrating strong predictive performance with Nash-Sutcliffe Efficiency (NSE) and coefficient of determination (R²) values exceeding 0.8 and Percent Bias (PBIAS) below 10% during both calibration and validation. Nonlinear regression emerged as the most accurate and reliable prediction approach. These findings underscore the methodology’s potential to predict runoff and rising limb trends, providing valuable insights for hydrological modeling and water resource management. Furthermore, this study’s approach contributes to advancing predictive hydrology and supports the development of adaptive strategies for managing water resources in the face of climate change.</p>

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Exploring Runoff Response to Simulated Rainfall: A Study of the Rising Limb of a Hydrograph on Sandy Slopes

  • 期刊论文

  • 发表日期：

    2025年1月27日

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  • Radha S. Mohril,
  • Avinash D. Vasudeo

摘要

As climate change intensifies the variability of rainfall patterns, understanding runoff behavior and the trend of the rising limb of the hydrograph under diverse scenarios becomes increasingly essential. This research addresses the gap by examining the influence of rainfall intensity and duration on sandy slopes through controlled laboratory experiments. This study delves into the intricate relationship between rainfall characteristics and runoff dynamics, focusing on enhancing accurate runoff prediction and the hydrograph’s rising limb, a critical element for effective water and flood management. Current models, such as the Natural Resources Conservation Service Curve Number (NRCS-CN) method, simplify runoff estimation despite their complexity and accuracy variability. Artificially created and simulated rainfall was applied across a range of intensities (150 to 700 L per hour, LPH), durations (10, 20, and 30 min), and slope gradients of slight (1º), moderate (2º), and steep (3º), resulting in 108 simulations. The regression-based model developed in this study offers a robust framework for capturing Rainfall-Runoff interactions, demonstrating strong predictive performance with Nash-Sutcliffe Efficiency (NSE) and coefficient of determination (R²) values exceeding 0.8 and Percent Bias (PBIAS) below 10% during both calibration and validation. Nonlinear regression emerged as the most accurate and reliable prediction approach. These findings underscore the methodology’s potential to predict runoff and rising limb trends, providing valuable insights for hydrological modeling and water resource management. Furthermore, this study’s approach contributes to advancing predictive hydrology and supports the development of adaptive strategies for managing water resources in the face of climate change.