A Framework for Estimating the Probability Distribution of Event Runoff Coefficient in Ungauged Catchments
Abstract The derived distribution method is a promising approach for flood estimation in ungauged catchments. In this approach, event runoff coefficient (ERC) is often adopted to behave as the runoff generation component since the behavior of ERC is closely related to flood generation mechanisms and...
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| Format: | Article |
| Language: | English |
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Wiley
2023-01-01
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| Series: | Water Resources Research |
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| Online Access: | https://doi.org/10.1029/2022WR033227 |
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| author | Yanchen Zheng Gemma Coxon Ross Woods Jianzhu Li Ping Feng |
| author_facet | Yanchen Zheng Gemma Coxon Ross Woods Jianzhu Li Ping Feng |
| author_sort | Yanchen Zheng |
| collection | DOAJ |
| description | Abstract The derived distribution method is a promising approach for flood estimation in ungauged catchments. In this approach, event runoff coefficient (ERC) is often adopted to behave as the runoff generation component since the behavior of ERC is closely related to flood generation mechanisms and its distribution reflects catchment climatological and landscape characteristics. However, there is a lack of understanding of how to transfer the information on ERC characteristics from gauged to ungauged catchments at catchment scale. Hence, here, we propose a generalized framework to estimate the probability distribution of ERC for ungauged catchments based on knowledge of the spatial and temporal controls on ERC from gauged catchments. Key components of the framework include cluster analysis based on ERC characteristics, linking clusters with catchment attributes, and constructing typical probability distribution of ERC conditioned on its temporal indicators. A total of 290,743 rainfall‐runoff events observed in 431 GB catchments during the period 1990–2014 have been employed to verify the framework. Good estimations are obtained with the median value of coefficient of determination (R2) reaching 0.85 across all test catchments. The results indicate that similar pre‐event catchment conditions may cause distinct runoff response in different catchments, thus predicting the correct spatial cluster is crucial to the estimation accuracy. This work sheds light on constructing a stochastic generator model of ERC according to its spatial pattern and temporal dynamic, facilitating a new alternative for flood estimation method in ungauged catchments. |
| format | Article |
| id | doaj-art-babc4bcb35a64f3dba12a68c8628f6e4 |
| institution | Matheson Library |
| issn | 0043-1397 1944-7973 |
| language | English |
| publishDate | 2023-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | Water Resources Research |
| spelling | doaj-art-babc4bcb35a64f3dba12a68c8628f6e42025-06-26T10:43:14ZengWileyWater Resources Research0043-13971944-79732023-01-01591n/an/a10.1029/2022WR033227A Framework for Estimating the Probability Distribution of Event Runoff Coefficient in Ungauged CatchmentsYanchen Zheng0Gemma Coxon1Ross Woods2Jianzhu Li3Ping Feng4State Key Laboratory of Hydraulic Engineering Simulation and Safety Tianjin University Tianjin ChinaSchool of Geographical Sciences University of Bristol Bristol UKDepartment of Civil Engineering University of Bristol Bristol UKState Key Laboratory of Hydraulic Engineering Simulation and Safety Tianjin University Tianjin ChinaState Key Laboratory of Hydraulic Engineering Simulation and Safety Tianjin University Tianjin ChinaAbstract The derived distribution method is a promising approach for flood estimation in ungauged catchments. In this approach, event runoff coefficient (ERC) is often adopted to behave as the runoff generation component since the behavior of ERC is closely related to flood generation mechanisms and its distribution reflects catchment climatological and landscape characteristics. However, there is a lack of understanding of how to transfer the information on ERC characteristics from gauged to ungauged catchments at catchment scale. Hence, here, we propose a generalized framework to estimate the probability distribution of ERC for ungauged catchments based on knowledge of the spatial and temporal controls on ERC from gauged catchments. Key components of the framework include cluster analysis based on ERC characteristics, linking clusters with catchment attributes, and constructing typical probability distribution of ERC conditioned on its temporal indicators. A total of 290,743 rainfall‐runoff events observed in 431 GB catchments during the period 1990–2014 have been employed to verify the framework. Good estimations are obtained with the median value of coefficient of determination (R2) reaching 0.85 across all test catchments. The results indicate that similar pre‐event catchment conditions may cause distinct runoff response in different catchments, thus predicting the correct spatial cluster is crucial to the estimation accuracy. This work sheds light on constructing a stochastic generator model of ERC according to its spatial pattern and temporal dynamic, facilitating a new alternative for flood estimation method in ungauged catchments.https://doi.org/10.1029/2022WR033227event runoff coefficientungauged catchmentsregionalizationflood estimationcatchment attributesprobability distribution |
| spellingShingle | Yanchen Zheng Gemma Coxon Ross Woods Jianzhu Li Ping Feng A Framework for Estimating the Probability Distribution of Event Runoff Coefficient in Ungauged Catchments Water Resources Research event runoff coefficient ungauged catchments regionalization flood estimation catchment attributes probability distribution |
| title | A Framework for Estimating the Probability Distribution of Event Runoff Coefficient in Ungauged Catchments |
| title_full | A Framework for Estimating the Probability Distribution of Event Runoff Coefficient in Ungauged Catchments |
| title_fullStr | A Framework for Estimating the Probability Distribution of Event Runoff Coefficient in Ungauged Catchments |
| title_full_unstemmed | A Framework for Estimating the Probability Distribution of Event Runoff Coefficient in Ungauged Catchments |
| title_short | A Framework for Estimating the Probability Distribution of Event Runoff Coefficient in Ungauged Catchments |
| title_sort | framework for estimating the probability distribution of event runoff coefficient in ungauged catchments |
| topic | event runoff coefficient ungauged catchments regionalization flood estimation catchment attributes probability distribution |
| url | https://doi.org/10.1029/2022WR033227 |
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