Search engine for discovering works of Art, research articles, and books related to Art and Culture
Javascript must be enabled to continue!
A seamless hydrologic forecasting system for Germany
View through CrossRef
An experimental hydrological forecasting system has been developed for Germany (https://www.ufz.de/HS2SForcasts4Germany) at high resolution (1 km). Since early 2021, the hydrological forecasting system provides operational ensemble forecasts for soil moisture droughts at sub-seasonal time scale (HS2S). In the next year, it will be upgraded to streamflow and inundation areas. The mesoscale Hydrologic Model (mHM- www.ufz.de/mhm) with the Multiscale Parameter Regionalization scheme [1,2,3] is used to simulate hydrological forecasts across German catchments. This model is forced with the extended large atmospheric ensemble forecasts from the European Centre for Medium-Range Weather Forecast (ECMWF). The soil moisture index is updated twice per week with associated uncertainties of the initial atmospheric conditions. The initial conditions are obtained with the DWD precipitation and temperature data, similar to the German Drought Monitor (www.ufz.de/droughtmonitor). The hydrological forecasting system was also evaluated for 2021 summer flood in west Germany [4]. The system has shown promising results in flood forecasting as well. This system is based on the EDgE system [5] and can easily be developed across other regions around the world.Refrences[1] Samaniego L., Kumar R., & Attinger, S. (2010). Multiscale parameter regionalization of a grid-based hydrologic model at the mesoscale. Water Resour. Res., 46,W05523, doi:10.1029/2008WR007327. WRR Editors' Choice Award 2010[2] Samaniego L., et al. (2021). mesoscale Hydrologic Model. Zenodo. doi:10.5281/zenodo.1069202, https://doi.org/10.5281/zenodo.1069202[3] Kumar, R., Samaniego, L., & Attinger, S. (2013). Implications of distributed hydrologic model parameterization on water fluxes at multiple scales and locations. Water Resour. Res., 49(1), 360-379. https://doi.org/10.1029/2012WR012195.[4] Najafi, H., Rakovec, O., Kumar Shrestha, P., Thober, S., & Samaniego, L. (2022). Post-Assessment of ECMWF-mHM ensemble flood forecasting for 2021 summer flood in west Germany. 2022 AGU Fall meeting. Chicago, IL & online everywhere.[5] Samaniego et al. (2019). Hydrological Forecasts and Projections for Improved Decision-Making in the Water Sector in Europe. BAMS, 100(12), 2451–2472. https://doi.org/10.1175/BAMS-D-17-0274.
Copernicus GmbH
Title: A seamless hydrologic forecasting system for Germany
Description:
An experimental hydrological forecasting system has been developed for Germany (https://www.
ufz.
de/HS2SForcasts4Germany) at high resolution (1 km).
Since early 2021, the hydrological forecasting system provides operational ensemble forecasts for soil moisture droughts at sub-seasonal time scale (HS2S).
In the next year, it will be upgraded to streamflow and inundation areas.
The mesoscale Hydrologic Model (mHM- www.
ufz.
de/mhm) with the Multiscale Parameter Regionalization scheme [1,2,3] is used to simulate hydrological forecasts across German catchments.
This model is forced with the extended large atmospheric ensemble forecasts from the European Centre for Medium-Range Weather Forecast (ECMWF).
The soil moisture index is updated twice per week with associated uncertainties of the initial atmospheric conditions.
The initial conditions are obtained with the DWD precipitation and temperature data, similar to the German Drought Monitor (www.
ufz.
de/droughtmonitor).
The hydrological forecasting system was also evaluated for 2021 summer flood in west Germany [4].
The system has shown promising results in flood forecasting as well.
This system is based on the EDgE system [5] and can easily be developed across other regions around the world.
Refrences[1] Samaniego L.
, Kumar R.
, & Attinger, S.
(2010).
Multiscale parameter regionalization of a grid-based hydrologic model at the mesoscale.
Water Resour.
Res.
, 46,W05523, doi:10.
1029/2008WR007327.
WRR Editors' Choice Award 2010[2] Samaniego L.
, et al.
(2021).
mesoscale Hydrologic Model.
Zenodo.
doi:10.
5281/zenodo.
1069202, https://doi.
org/10.
5281/zenodo.
1069202[3] Kumar, R.
, Samaniego, L.
, & Attinger, S.
(2013).
Implications of distributed hydrologic model parameterization on water fluxes at multiple scales and locations.
Water Resour.
Res.
, 49(1), 360-379.
https://doi.
org/10.
1029/2012WR012195.
[4] Najafi, H.
, Rakovec, O.
, Kumar Shrestha, P.
, Thober, S.
, & Samaniego, L.
(2022).
Post-Assessment of ECMWF-mHM ensemble flood forecasting for 2021 summer flood in west Germany.
2022 AGU Fall meeting.
Chicago, IL & online everywhere.
[5] Samaniego et al.
(2019).
Hydrological Forecasts and Projections for Improved Decision-Making in the Water Sector in Europe.
BAMS, 100(12), 2451–2472.
https://doi.
org/10.
1175/BAMS-D-17-0274.
Related Results
Coupling the Data-driven Weather Forecasting Model with 4D Variational Assimilation
Coupling the Data-driven Weather Forecasting Model with 4D Variational Assimilation
In recent years, the development of artificial intelligence has led to rapid advances in data-driven weather forecasting models, some of which rival or even surpass traditional met...
Multi-order hydrologic position: a high-resolution dataset for the conterminous United States
Multi-order hydrologic position: a high-resolution dataset for the conterminous United States
The location of a point within a stream network can be an important measure in hydrology. Hydrologic position (HP) is defined here by two metrics: lateral position (LP) and distanc...
Establishment and Application of the Multi-Peak Forecasting Model
Establishment and Application of the Multi-Peak Forecasting Model
Abstract
After the development of the oil field, it is an important task to predict the production and the recoverable reserve opportunely by the production data....
Forecasting
Forecasting
The history of forecasting goes back at least as far as the Oracle at Delphi in Greece. Stripped of its mystique, this was what we now refer to as “unaided judgment,” the only fore...
Quantifying uncertainty in estimation of hydrologic metrics for ecohydrological studies
Quantifying uncertainty in estimation of hydrologic metrics for ecohydrological studies
AbstractHydrologic metrics have been used extensively in ecology and hydrology to summarize the characteristics of riverine flow regimes at various temporal scales but there has be...
Flood forecasting by means of dynamical downscaling of global NWPs coupling with a hydrologic model at Nong Son-Thanh My River basins
Flood forecasting by means of dynamical downscaling of global NWPs coupling with a hydrologic model at Nong Son-Thanh My River basins
Abstract
Almost every year, Vietnam suffers floods resulting in the loss of many lives and considerable costs for damaged and lost properties. This s...
Regional scale projections of future change in wetland hydrologic regimes in Australia
Regional scale projections of future change in wetland hydrologic regimes in Australia
Wetlands provide key habitat for many species but are threatened by climate change. However, quantitatively projecting climate change impacts on wetland hydrologic regimes is diffi...
SOCIAL FORECASTING AS A TECHNOLOGY OF SOCIAL WORK
SOCIAL FORECASTING AS A TECHNOLOGY OF SOCIAL WORK
The article considers social forecasting as a technology of social work. The importance of social forecasting as a tool that allows analyzing current tendencies and assessing the p...