Statistical Processing And Modeling For Performance Tuning Of Integrated River Basin Physical Modeling
Abstract
To benefit from ecosystem services, human activities have altered flow regimes resulting in increased pressures and threats on water resources. Data-driven approaches could be implemented to drive robust cause-and-effect relationships between hydrology and influencing stressors overcoming the necessity of prior understanding of complex underlying processes. Statistical investigation has been used to evaluate how land cover changes and related management practices could influence and/or alter the soils hydrological functioning. This is in particular critical in drought-sensitive regions vulnerable to climate change consequences. Two adjacent catchments in central Germany assumed to be similar (e.g. in terms of climatic conditions, soil types and slopes) are put to analysis. To quantify the hydrological response of environmentally critical stream flows (e.g., environmental flows) to the impacting factors of climate change and management practices (e.g. land covers & water withdrawals), a prominent prior characterisation of e-flows on seasonal basis is performed producing multiple hydrological thresholds. This is followed using Trend-Free-Pre-whitening-Mann-Kendall (TFPW-MK) approach by investigating change points in the hydrological system and trending. Generalized-Additive-Modelling (GAMs) to attribute driver-impact associations in order to inspect and quantify the spatiotemporal dynamics of drought risk in study areas. Trend results are variating between the two catchments indicating higher management level in one of the catchment. Decreased trend of rainfall intensity with increased trend of drought intensity has been observed in both catchments. ). A SWAT+ (Soil and Water Assessment Tool) process-based model is being set up with a detailed description in land and water management. Comparing the outputs between statistical and physical modelling may clear up some uncertainties caused by inaccurate definition of underlying processes and/or initial and boundary conditions and consequently pinpoint key areas where further research may be most useful thereby permitting better future model refinements.
- Publication:
-
AGU Fall Meeting Abstracts
- Pub Date:
- December 2020
- Bibcode:
- 2020AGUFMH172.0023K
- Keywords:
-
- 1812 Drought;
- HYDROLOGY;
- 1817 Extreme events;
- HYDROLOGY;
- 1821 Floods;
- HYDROLOGY;
- 1874 Ungaged basins;
- HYDROLOGY