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Improved Runoff Estimation Using Event-Based Rainfall-Runoff Models

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  • Muhammad Ajmal
  • Muhammad Waseem
  • Jae-Hyun Ahn
  • Tae-Woong Kim

Abstract

Event-based rainfall-runoff models are effective tools in operational hydrological forecasting and preparedness for extreme events. In the current study, the popular Natural Resources Soil Conservation curve number (NRCS-CN) model and the proposed simple nonlinear models were employed for runoff estimation. The runoff prediction capability of the NRCS model for the CN values obtained from tables was very poor in comparison to those calculated from the measured rainfall-runoff (storm-events) data. The proposed models were calibrated based on the rank-order, measured rainfall-runoff data (1,005 events) from 25 watersheds and validated in six watersheds for runoff estimation (170 events). The quantitative models’ performances were evaluated and compared based on the root mean square error (RMSE), Nash-Sutcliffe efficiency (NSE), and percent bias (PBIAS). Using tabulated CNs, the NRCS model exhibited comparatively insignificant results in the maximum number of watersheds (high RMSE, low NSE, and statistically poor PBIAS values). Using storm-event based calibrated CNs, the NRCS model showed improvement for runoff estimation. Furthermore, the proposed models without the CN concept were superior (with comparatively low RMSE, high NSE, and statistically significant PBIAS values) for depicting improved performance in almost all of the watersheds. Copyright Springer Science+Business Media Dordrecht 2015

Suggested Citation

  • Muhammad Ajmal & Muhammad Waseem & Jae-Hyun Ahn & Tae-Woong Kim, 2015. "Improved Runoff Estimation Using Event-Based Rainfall-Runoff Models," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 29(6), pages 1995-2010, April.
    • Handle: RePEc:spr:waterr:v:29:y:2015:i:6:p:1995-2010
    DOI: 10.1007/s11269-015-0924-z
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    References listed on IDEAS

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    1. Sushindra Kumar Gupta & Jaivir Tyagi & Gunwant Sharma & A. S. Jethoo & P. K. Singh, 2019. "An Event-Based Sediment Yield and Runoff Modeling Using Soil Moisture Balance/Budgeting (SMB) Method," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 33(11), pages 3721-3741, September.
    2. Pingjin Jiao & Di Xu & Shaoli Wang & Yingduo Yu & Songjun Han, 2015. "Improved SCS-CN Method Based on Storage and Depletion of Antecedent Daily Precipitation," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 29(13), pages 4753-4765, October.
    3. Xiaoli Du & Mingzhe Yang & Zijie Yin & Xing Fang, 2023. "Influence of Initial Abstraction Ratios in NRCS-CN Model on Runoff Estimation of Permeable Brick Pavement Affected by Clogging," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 37(8), pages 3211-3225, June.
    4. Shirisha Pulukuri & Venkata Reddy Keesara & Pratap Deva, 2018. "Flow Forecasting in a Watershed using Autoregressive Updating Model," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 32(8), pages 2701-2716, June.
    5. P. Shirisha & K. Venkata Reddy & Deva Pratap, 2019. "Real-Time Flow Forecasting in a Watershed Using Rainfall Forecasting Model and Updating Model," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 33(14), pages 4799-4820, November.
    6. Xianhong Meng & Min Zhang & Jiahong Wen & Shiqiang Du & Hui Xu & Luyang Wang & Yan Yang, 2019. "A Simple GIS-Based Model for Urban Rainstorm Inundation Simulation," Sustainability, MDPI, vol. 11(10), pages 1-19, May.
    7. Hakan Tongal & Martijn Booij, 2016. "A Comparison of Nonlinear Stochastic Self-Exciting Threshold Autoregressive and Chaotic k-Nearest Neighbour Models in Daily Streamflow Forecasting," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 30(4), pages 1515-1531, March.
    8. Hakan Tongal & Martijn J. Booij, 2016. "A Comparison of Nonlinear Stochastic Self-Exciting Threshold Autoregressive and Chaotic k-Nearest Neighbour Models in Daily Streamflow Forecasting," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 30(4), pages 1515-1531, March.
    9. Zahra Eslami & Khodayar Abdollahi & Ataollah Ebrahimi‬, 2023. "On the Role of Hydrological Losses in Estimating Event Runoff Coefficients Using the NRCS Method," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 37(11), pages 4233-4252, September.
    10. Sanat Nalini Sahoo & P. Sreeja, 2016. "Relationship between peak rainfall intensity (PRI) and maximum flood depth (MFD) in an urban catchment of Northeast India," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 83(3), pages 1527-1544, September.
    11. P. Singh & S. Mishra & R. Berndtsson & M. Jain & R. Pandey, 2015. "Development of a Modified SMA Based MSCS-CN Model for Runoff Estimation," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 29(11), pages 4111-4127, September.

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