scholarly journals Supplementary material to "Contribution of Potential Evaporation Forecasts to 10-day streamflow forecast skill for the Rhine river"

2018 ◽  
Author(s):  
Bart van Osnabrugge ◽  
Remko Uijlenhoet ◽  
Albrecht Weerts
Keyword(s):  
Forecast Skill ◽  
Rhine River ◽  
Potential Evaporation ◽  
Streamflow Forecast ◽  
Supplementary Material

scholarly journals Contribution of Potential Evaporation Forecasts to 10-day streamflow forecast skill for the Rhine river

2018 ◽  
Author(s):  
Bart van Osnabrugge ◽  
Remko Uijlenhoet ◽  
Albrecht Weerts
Keyword(s):  
Radiative Forcing ◽  
Potential Evapotranspiration ◽  
Global Radiation ◽  
Forecast Skill ◽  
Meteorological Variables ◽  
Rhine River ◽  
Potential Evaporation ◽  
Streamflow Forecasting ◽  
Streamflow Forecast ◽  
Rhine Basin

Abstract. Medium term hydrologic forecast uncertainty is strongly dependent on the forecast quality of meteorological variables. Of these variables, the influence of precipitation has been studied most widely, while temperature, radiative forcing and their derived product potential evapotranspiration (PET) have received little attention from the perspective of hydrological forecasting. This study aims to fill this gap by assessing the usability of potential evaporation forecasts for 10-day-ahead streamflow forecasting in the Rhine basin, Europe. In addition, the forecasts of the meteorological variables are compared with observations. Streamflow reforecasts were performed with the daily wflow_hbv model used in previous studies of the Rhine using the ECMWF 20-year meteorological reforecast dataset. Meteorological forecasts were compared with observed rainfall, temperature, global radiation and potential evaporation for 148 subbasins. Secondly, the effect of using PET climatology versus using observation-based estimates of PET was assessed for hydrological state and for streamflow forecast skill. We find that: (1) there is considerable skill in the ECMWF reforecasts to predict PET for all seasons, (2) using dynamical PET forcing based on observed temperature and satellite global radiation estimates results in lower evaporation and wetter initial states, but (3) the effect on forecasted 10-day streamflow is limited. Implications of this finding are that it is reasonable to use meteorological forecasts to forecast potential evaporation and use this is in medium-range streamflow forecasts. However, it can be concluded that an approach using PET climatology is also sufficient, most probably not only for the application shown here, but for most models similar to the HBV concept and for moderate climate zones. As a by-product, this research resulted in gridded datasets for temperature, radiation and potential evaporation based on the Makkink equation for the Rhine basin. The datasets have a spatial resolution of 1.2 × 1.2 km and an hourly timestep for the period from July 1996 through 2015. This dataset complements an earlier precipitation dataset for the same area, period and resolution.

scholarly journals Contribution of potential evaporation forecasts to 10-day streamflow forecast skill for the Rhine River

2019 ◽  
Vol 23 (3) ◽  
pp. 1453-1467 ◽  
Author(s):  
Bart van Osnabrugge ◽  
Remko Uijlenhoet ◽  
Albrecht Weerts
Keyword(s):  
Radiative Forcing ◽  
Potential Evapotranspiration ◽  
Global Radiation ◽  
Forecast Skill ◽  
Meteorological Variables ◽  
Potential Evaporation ◽  
Streamflow Forecasting ◽  
Time Step ◽  
Streamflow Forecast ◽  
Rhine Basin

Abstract. Medium-term hydrologic forecast uncertainty is strongly dependent on the forecast quality of meteorological variables. Of these variables, the influence of precipitation has been studied most widely, while temperature, radiative forcing and their derived product potential evapotranspiration (PET) have received little attention from the perspective of hydrological forecasting. This study aims to fill this gap by assessing the usability of potential evaporation forecasts for 10-day-ahead streamflow forecasting in the Rhine basin, Europe. In addition, the forecasts of the meteorological variables are compared with observations. Streamflow reforecasts were performed with the daily wflow_hbv model used in previous studies of the Rhine using the ECMWF 20-year meteorological reforecast dataset. Meteorological forecasts were compared with observed rainfall, temperature, global radiation and potential evaporation for 148 subbasins. Secondly, the effect of using PET climatology versus using observation-based estimates of PET was assessed for hydrological state and for streamflow forecast skill. We find that (1) there is considerable skill in the ECMWF reforecasts to predict PET for all seasons, and (2) using dynamical PET forcing based on observed temperature and satellite global radiation estimates results in lower evaporation and wetter initial states, but (3) the effect on forecasted 10-day streamflow is limited. Implications of this finding are that it is reasonable to use meteorological forecasts to forecast potential evaporation and use this is in medium-range streamflow forecasts. However, it can be concluded that an approach using PET climatology is also sufficient, most probably not only for the application shown here, but also for most models similar to the HBV concept and for moderate climate zones. As a by-product, this research resulted in gridded datasets for temperature, radiation and potential evaporation based on the Makkink equation for the Rhine basin. The datasets have a spatial resolution of 1.2×1.2 km and an hourly time step for the period from July 1996 through 2015. This dataset complements an earlier precipitation dataset for the same area, period and resolution.

Supplementary material to "Potential evaporation at eddy-covariance sites across the globe"

2018 ◽  
Author(s):  
Wouter H. Maes ◽  
Pierre Gentine ◽  
Niko E. C. Verhoest ◽  
Diego G. Miralles
Keyword(s):  
Eddy Covariance ◽  
Potential Evaporation ◽  
Supplementary Material

scholarly journals Benchmarking Real-Time Streamflow Forecast Skill in the Himalayan Region

Forecasting ◽  
2020 ◽  
Vol 2 (3) ◽  
pp. 230-247
Author(s):  
Ganesh R. Ghimire ◽  
Sanjib Sharma ◽  
Jeeban Panthi ◽  
Rocky Talchabhadel ◽  
Binod Parajuli ◽  
...  
Keyword(s):  
Real Time ◽  
Water Policy ◽  
Low Complexity ◽  
Critical Issue ◽  
Forecast Skill ◽  
Streamflow Forecasting ◽  
Streamflow Forecast ◽  
Time Flow ◽  
Wide Range ◽  
Streamflow Forecasts

Improving decision-making in various areas of water policy and management (e.g., flood and drought preparedness, reservoir operation and hydropower generation) requires skillful streamflow forecasts. Despite the recent advances in hydrometeorological prediction, real-time streamflow forecasting over the Himalayas remains a critical issue and challenge, especially with complex basin physiography, shifting weather patterns and sparse and biased in-situ hydrometeorological monitoring data. In this study, we demonstrate the utility of low-complexity data-driven persistence-based approaches for skillful streamflow forecasting in the Himalayan country Nepal. The selected approaches are: (1) simple persistence, (2) streamflow climatology and (3) anomaly persistence. We generated the streamflow forecasts for 65 stream gauge stations across Nepal for short-to-medium range forecast lead times (1 to 12 days). The selected gauge stations were monitored by the Department of Hydrology and Meteorology (DHM) Nepal, and they represent a wide range of basin size, from ~17 to ~54,100 km2. We find that the performance of persistence-based forecasting approaches depends highly upon the lead time, flow threshold, basin size and flow regime. Overall, the persistence-based forecast results demonstrate higher forecast skill in snow-fed rivers over intermittent ones, moderate flows over extreme ones and larger basins over smaller ones. The streamflow forecast skill obtained in this study can serve as a benchmark (reference) for the evaluation of many operational forecasting systems over the Himalayas.

Supplementary material to "Potential evaporation at eddy-covariance sites across the globe"

2018 ◽  
Author(s):  
Wouter H. Maes ◽  
Pierre Gentine ◽  
Niko E. C. Verhoest ◽  
Diego G. Miralles
Keyword(s):  
Eddy Covariance ◽  
Potential Evaporation ◽  
Supplementary Material

Hydrological Model Diversity Enhances Streamflow Forecast Skill at Short‐ to Medium‐Range Timescales

2019 ◽  
Vol 55 (2) ◽  
pp. 1510-1530 ◽  
Author(s):  
Sanjib Sharma ◽  
Ridwan Siddique ◽  
Seann Reed ◽  
Peter Ahnert ◽  
Alfonso Mejia
Keyword(s):  
Hydrological Model ◽  
Forecast Skill ◽  
Streamflow Forecast ◽  
Medium Range

scholarly journals Attribution of hydrologic forecast uncertainty within scalable forecast windows

2013 ◽  
Vol 10 (9) ◽  
pp. 11795-11828 ◽  
Author(s):  
L. Yang ◽  
F. Tian ◽  
Y. Sun ◽  
X. Yuan ◽  
H. Hu
Keyword(s):  
Model Calibration ◽  
Transition Period ◽  
Hydrologic Model ◽  
Dry Season ◽  
Forecast Skill ◽  
Model Parameters ◽  
Combined Effects ◽  
Wet Season ◽  
Streamflow Forecast ◽  
Monthly Streamflow

Abstract. Hindcasts based on the Extended Streamflow Prediction (ESP) approach are carried out in a typical rainfall-dominated basin in China, aiming to examine the roles of initial condition (IC), future atmospheric forcing (FC) and hydrologic model uncertainty (MU) in the streamflow forecast skill. The combined effects of IC and FC are explored within the framework of a forecast window. By implementing virtual numerical simulations without the consideration of MU, it is found that the dominance of IC could last up to 90 days in dry season, while its impact gives way to FC for lead times exceeding 30 days in the wet season. The combined effects of IC and FC on the forecast skill are further investigated by proposing a dimensionless parameter (β) that represents the ratio of the total amount of initial water storage and the incoming rainfall. The forecast skill increases exponentially with β, and varies greatly in different forecast windows. Moreover, the influence of MU on forecast skill is examined by focusing on the uncertainty of model parameters. Two different hydrologic model calibration strategies are carried out. The results indicate that the uncertainty of model parameters exhibits a more significant influence on the forecast skill in the dry season than in the wet season. The ESP approach is more skillful in monthly streamflow forecast during the transition period from wet to dry than otherwise. For the transition period from dry to wet, the low skill of the forecasts could be attributed to the combined effects of IC and FC, but less to the biases in the hydrologic model parameters. For the forecasting in dry season, the usefulness of the ESP approach is heavily dependent on the strategy of the model calibration.

Added seasonal forecasting skill from land surface parameterization detail

2020 ◽  
Author(s):  
Bart van den Hurk ◽  
Ruud Hurkmans ◽  
Fredrik Wetterhal ◽  
Ilias Pechlivanidis ◽  
Albrecht Weerts
Keyword(s):  
Land Surface ◽  
River Discharge ◽  
Initial Conditions ◽  
Water Reservoir ◽  
Forecast Skill ◽  
Rhine River ◽  
Distributed Hydrological Model ◽  
Lake Levels ◽  
Surface Parameterization ◽  
Dry Spell

<p><span>During dry spells, a large part of the Netherlands depends on water from the IJssel lake, a large surface water reservoir. Water is extracted for a number of purposes, such as irrigation, water quality, shipping and drinking water. Besides local precipitation, the main source of water flowing into the lake is the river IJssel; a distributary of the Rhine. To keep water available for extraction by the surrounding regions, lake levels cannot be allowed to fall more than about 20 cm under the regular summer maintenance level. Prior to the onset of a drought, therefore, it might be desirable to raise lake levels to maintain sufficient water availability during the dry spell. For adequate management of the reservoir, therefore, long-range forecasting of precipitation and river discharge would be extremely helpful. However, meteorological forecast skill is known to be nearly absent for lead times longer than about a month in northwestern Europe. The land surface contains a number of components that may increase forecast skill for Rhine river discharge; examples are the amount of snow in the Alps, groundwater, and soil moisture. We investigate to what extent this is the case and whether the forecast skill of Rhine river discharge forecasts increases with increasing detail in the land surface parameterization of the initial conditions. We collected streamflow reforecasts from various sources: ECMWF SEAS5, EFAS, SMHI-HYPE and a high-resolution distributed hydrological model (WFLOW), forced by ECMWF SEAS5 meteorological forecasts. </span></p>

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