Abstract
Adopting new technologies to calibrate hydrological models to produce good simulations for water resources or flood risk management is one of the important research topics in hydrology field. Incorporating hydrological signatures and concepts in hydrological model calibration becomes prevalent in recent years. A good realistic simulation of hydrological processes within the catchment is more significant than only achieving good performance at watershed outlet with single-statistical-objective function. This research adopts the concept of flood scaling property, which describes the statistical relationship between flood peak, its contributing areas and additional catchment attributes, to behave as one of the constraints under multi-objective model calibration framework. Several designed calibration scenarios are tested by employing the soil and water assessment tool hydrological model. In comparison with single-objective calibration scenarios, multi-objective calibration method is recommended to obtain both good simulation at catchment outlet and sub-basins reaches. The multi-objective calibration method assists in improving the model performance in terms of flow duration curve and also in reducing the bias of long-term runoff ratio. The proposed model calibration approach reflects the hydrological interaction of flood peaks across sub-basins and takes into account the catchment antecedent wetness and climatic condition for each flood event.
| Original language | English |
|---|---|
| Pages (from-to) | 267-292 |
| Number of pages | 26 |
| Journal | Natural Hazards |
| Volume | 117 |
| Issue number | 1 |
| DOIs | |
| Publication status | Published - 1 Mar 2023 |
Bibliographical note
Funding Information:This work was supported by the National natural science foundation of China under Grant (52079086). Financial support from the Natural Science Foundation of Tianjin (Grant number: 20JCQNJC01960) is also gratefully acknowledged.
Funding Information:
We would like to give great thanks to China Scholarship Council (No. 202006250090) for providing necessary support for Yanchen Zheng on this research.
Publisher Copyright:
© 2023, The Author(s), under exclusive licence to Springer Nature B.V.