Facilitating sensitivity analysis of hydrological models through knowledge-driven configuration and distributed online model services
Oct 1, 2025·
,,,,,,,,,·
1 min read
Peilong Ma
Min Chen
Shuo Zhang
Zhiyi Zhu
Zhen Qian
Zaiyang Ma
Fengyuan Zhang
Wenwen Li
Songshan Yue
Yongning Wen
Abstract
This paper proposes a knowledge-driven workflow for configuring hydrological models and connecting them with distributed online model services, making sensitivity analysis more reusable, scalable, and easier to operate in service-based environments.
Type
Publication
Journal of Hydrology, 660, 133406
This work studies how configuration knowledge and service-oriented model execution can be combined to support more efficient sensitivity analysis for hydrological models.
