estimation of catchment wetness for the wupper ... - bingo · estimation of catchment wetness for...
TRANSCRIPT
Estimation of catchment wetness for the Wupper River Basin, Germany
Marc Scheibel, Paula Lorza
Contacts: Marc Scheibel - Tel. +49-202/583-246 - Mobile: +49-160/989-322-21 - Email: [email protected] Lorza - Tel. +49-202/583-333 - Mobile: +49-160/963-437-03 - Email: [email protected] - Untere Lichtenplatzer Str. 100 - 42289 Wuppertal, Germany
Context•In the frame of the Horizon 2020 project BINGO (Bringing
INnovation to onGOing water management), the impacts ofclimate change on the water cycle in the Wupper River catchmentarea are being currently investigated. On one hand, dry periodsaffect fresh water supply reliability; on the other hand, flashfloods during summer periods are the most expected (and alreadyexperienced) effects.
Enhancement of the operational forecasting model Application of future climate scenarios for flood and reservoir
management (i.e., MiKlip, ReKliEs-De) Regionalisation of precipitation patterns and scenarios Identification of past weather extremes and anomalies Determination of flood and dry periods warning thresholds
based on initial soil moisture conditions and expected rainfall
a
Objectives
Methodology• Installation of a soil moisture monitoring and lysimeter network at representative sites in the Wupper River Basin
Estimation of spatial distribution of soil wetness and precipitation using near-real time soil moisture remote sensing products (e.g., SMAP and SMOS), radar data (from the German Weather Service – DWD), and reanalysis products (e.g., ERA-Interim)
Application of indices to establish initial conditions as well as past and future trends
Study area with risks•
Monitoring network•
Spatial distribution with radar data Drought scenarios•
API for a wet period (left figure) and a dry period (right figure), estimated with radar data
June 2011 June 2018(Realisation 1)
Determination and comparison of further indices (SPEI, WEI, API, etc.) Hydrological modelling using climate, land and water use scenarios
Next steps• Application of other spatial interpolation methods
(e.g., Krigging)
©Lufft
Ground station network compared to the spatial distribution of radar Essen
Mean annual precipitation (MAP) estimated with radar data
©Eijkelkamp
©truebner
©Decagon
Matrix potential, soil moisture sensors, climate station, and lysimeter (for first test site, see figure above)
Drop size distribution (DSD) for selecting radar Z-R relationship according to rain type (estimated with disdrometer -see picture on the right)
First approaches with historical and climate realisations (not bias corrected yet) to estimate Standardised Precipitation Index (SPI) – picture shows the effect on the “Große Dhünn” reservoir after a three-year dry period
Wupper river - tributary to the Rhine Catchment