Abstract
Catchment Morphing (CM) is a newly proposed approach to apply fully distributed models for ungauged catchments and has been
experimented in several catchments in the UK. As one of the most important input datasets for hydrological models, rainfall spatial variability is influential to the stream variabilities and simulation performance. A homogenous rainfall was utilized in the previous experiments with Catchment Morphing. This study applied a spatially distributed rainfall from CEH-GEAR rainfall dataset in the morphed catchment for ungauged catchments as the follow-on study. Three catchments in the UK were used for rainfall spatial analysis and CEH-GEAR rainfall data were adopted for additional spatial analysis. The results demonstrate the influence of rainfall spatial information to the model performance with CM and illustrate the ability of morphed catchment to tackle with spatially varied information. More spatially distributed information is expected to be introduced for a wider application of CM.
experimented in several catchments in the UK. As one of the most important input datasets for hydrological models, rainfall spatial variability is influential to the stream variabilities and simulation performance. A homogenous rainfall was utilized in the previous experiments with Catchment Morphing. This study applied a spatially distributed rainfall from CEH-GEAR rainfall dataset in the morphed catchment for ungauged catchments as the follow-on study. Three catchments in the UK were used for rainfall spatial analysis and CEH-GEAR rainfall data were adopted for additional spatial analysis. The results demonstrate the influence of rainfall spatial information to the model performance with CM and illustrate the ability of morphed catchment to tackle with spatially varied information. More spatially distributed information is expected to be introduced for a wider application of CM.
| Original language | English |
|---|---|
| Pages (from-to) | 1344-1356 |
| Number of pages | 13 |
| Journal | Hydrology Research |
| Volume | 52 |
| Issue number | 6 |
| DOIs | |
| Publication status | Published - 11 Oct 2021 |
Bibliographical note
Funding Information:The author Qiang Dai was supported by the National Natural Science Foundation of China (Grant No. 41871299, 91846203). The authors acknowledge the British Atmospheric Data Centre for providing the dataset used in this study. The authors acknowledge the Dr Stephen Birkinshaw for the help with SHETRAN in this study.
Publisher Copyright:
© 2021 IWA Publishing. All rights reserved.
Structured keywords
- Water and Environmental Engineering