About this Research Topic
Hydrological modelling is crucial for the management and planning of water resources. Global warming resulted in an increase in extreme events, such as floods and droughts. Hydrological modeling is the first step to understanding the trajectory of hydrological processes to plan for adaptation. This research collection aims to develop and analyze the performance of the conceptual, physically-based, data-driven, or hybrid models combining physics and data-driven approaches for hydrological modelling in different semi-arid and arid catchments in a changing environment. A particular emphasis can be given to the performance of the approaches under extreme scenarios (especially low-flow analysis).
The aims of this research topic can be summarized as follows:
-Implementing and comparing different rainfall-runoff modelling approaches
- Observing the applicability of the conceptual, physically-based models, data-driven and hybrid models in semi-arid or arid catchments
-Observing the potential advantages of the hybrid models, which combine the conceptual and data-driven models or physically-based and data-driven models in semi-arid or arid catchments.
- Investigating the performance of the models for extreme flow conditions.
In this research topic, the authors should develop and analyze the performance of different rainfall-runoff modelling approaches, including the hybrid model approach in semi-arid or arid catchments. The articles should show a clear way forward on the applicability of models in developing early warning systems for the extremes and developing the trajectories of future hydrological extreme events driven by climate and land use land cover changes. The articles may also be extended to perform hydrological detection and attribution analysis.
The aims of this research topic can be summarized as follows:
-Implementing and comparing different rainfall-runoff modelling approaches
- Observing the applicability of the conceptual, physically-based models, data-driven and hybrid models in semi-arid or arid catchments
-Observing the potential advantages of the hybrid models, which combine the conceptual and data-driven models or physically-based and data-driven models in semi-arid or arid catchments.
- Investigating the performance of the models for extreme flow conditions.
In this research topic, the authors should develop and analyze the performance of different rainfall-runoff modelling approaches, including the hybrid model approach in semi-arid or arid catchments. The articles should show a clear way forward on the applicability of models in developing early warning systems for the extremes and developing the trajectories of future hydrological extreme events driven by climate and land use land cover changes. The articles may also be extended to perform hydrological detection and attribution analysis.
Keywords: Climate change, conceptual, data-driven, hydrological modelling, physically-based, Arid Catchments, Hybrid Model
Important Note: All contributions to this Research Topic must be within the scope of the section and journal to which they are submitted, as defined in their mission statements. Frontiers reserves the right to guide an out-of-scope manuscript to a more suitable section or journal at any stage of peer review.
