On hydrological predictability

2005 ◽  
Vol 19 (19) ◽  
pp. 3923-3929 ◽  
Author(s):  
Günter Blöschl ◽  
Erwin Zehe
Keyword(s):  
Hydrological Predictability

Sensitivity of seasonal hydrological predictability sources to catchment properties

2020 ◽  
Author(s):  
Maria Stergiadi ◽  
Nicola Di Marco ◽  
Diego Avesani ◽  
Marco Borga ◽  
Maurizio Righetti
Keyword(s):  
Forecast Skill ◽  
Added Value ◽  
Climate Forcing ◽  
Hydrological Response ◽  
Elevation Range ◽  
Start Date ◽  
Production Water ◽  
Hydropower Production ◽  
The Impact ◽  
Hydrological Predictability

<p>Seasonal hydrological forecasts are a powerful tool for water-related decision making associated to hydropower production, water supply and irrigation. The skill of these forecasts depends mainly on knowledge of the initial hydrologic conditions (ICs) on the start date of the forecast and knowledge of climate forcing (CF) during the forecast period. Identification of the sensitivity of the forecast skill to these two main predictability sources is crucial to funnel the efforts into improving the appropriate predictive tools, by either improving the ICs estimates or by enhancing the quality of the CF. This work aims at investigating the impact of catchment properties in terms of soil permeability on the contribution of the dominant predictability sources (ICs, CF) to the seasonal forecast skill. To this end, we apply the End Point Blending (EPB) framework to create forecasts with intermediate levels of uncertainty concerning ICs and CF. The methodology is applied in two catchments in the upper Adige River Basin that are representative of the two extremes of hydrological response: the Gadera catchment closed at Mantana (area: 390 km<sup>2</sup>, elevation range: 810–3050 m a.s.l.) that is highly permeable, hence slow-responding and the Passirio catchment closed at Merano (area: 402 km<sup>2</sup>, elevation range: 360–3500 m a.s.l.) that is characterized by low permeability, hence by a fast-responding regime. Our analysis highlights the contribution of each predictability source to the forecast skill over catchments of contradicting hydrological response, as well as the added value of the elasticity framework introduced by the EPB in comparison to the traditional ESP/revESP approach for identifying the sources of seasonal hydrological predictability in alpine areas.</p>

scholarly journals Impact of Geology on Seasonal Hydrological Predictability in Alpine Regions by a Sensitivity Analysis Framework

Water ◽  
2020 ◽  
Vol 12 (8) ◽  
pp. 2255 ◽  
Author(s):  
Maria Stergiadi ◽  
Nicola Di Marco ◽  
Diego Avesani ◽  
Maurizio Righetti ◽  
Marco Borga
Keyword(s):  
Initial Conditions ◽  
Forecast Skill ◽  
Added Value ◽  
Climate Forcing ◽  
Major Influence ◽  
Analysis Framework ◽  
Alpine Regions ◽  
End Members ◽  
Seasonal Streamflow ◽  
Hydrological Predictability

Catchment geology has a major influence on the relative impact of the main seasonal hydrological predictability sources (initial conditions (IC), climate forcing (CF)) on the forecast skill as it defines the system’s persistence. A quantification of its effect, though, on the contribution of the predictability sources to the forecast skill has not been previously investigated. In this work we apply the End Point Blending (EPB) framework to assess the contribution of IC and CF to the seasonal streamflow forecast skill over two catchments that represent the end members of a set of catchments of contrasting geology, hence contrasting hydrological response: a highly-permeable, hence slow-responding catchment and a fast-responding catchment of low permeability. Our results show that the contribution of IC in the slow-responding catchment is higher by up to 44% for forecasts initialized in winter and spring and by up to 21% for forecasts initialized in summer. IC are important for up to 4 months of lead in the slow-responding catchment and 2 months of lead in the flashier catchment. Our analysis highlights the added value of the EPB in comparison to the traditional ESP/revESP approach for identifying the sources of seasonal hydrological predictability, on the basis of catchment geology.

Spatial Pattern of Hydrological Predictability of Landslide-Prone Areas

2015 ◽  
pp. 1611-1613
Author(s):  
Diodato Nazzareno ◽  
Guerriero Luigi ◽  
Revellino Paola ◽  
Grelle Gerardo ◽  
Guadagno Francesco Maria
Keyword(s):  
Spatial Pattern ◽  
Hydrological Predictability

Ensemble strategies for Flash Flood Forecasting: the 29 October 2018 event in the Eastern Italian Alps

2021 ◽  
Author(s):  
Teresa Pérez Ciria ◽  
Mattia Zaramella ◽  
Eleonora Dallan ◽  
Lorenzo Giovannini ◽  
Dino Zardi ◽  
...  
Keyword(s):  
Large Scale ◽  
Global Analysis ◽  
Hydrologic Model ◽  
Precipitation Event ◽  
Second Phase ◽  
Italian Alps ◽  
River Systems ◽  
Extreme Flood ◽  
Grid Based ◽  
Hydrological Predictability

<p>On 27-29 October 2018, heavy precipitation over the Eastern Italian Alps (the so-called “Vaia Storm”) led to an extreme flood, causing several casualties and extensive damages to buildings and infrastructures. The event, which occurred at the end of a climatic anomaly of prolonged drought, developed into two phases: a first phase (October 27-28) and a short, but more intense second phase on the 29th. The event was characterized by extreme accumulated precipitation, and several flash floods in the second phase. A previous work focused on the implementation of two NWP models (MOLOCH and WRF) at convection permitting resolution and showed a general good predictability of the precipitation event, associated with a well-defined large-scale forcing. This work aims at providing an outline of the hydrological predictability, focusing on different river systems in the area (the Upper Adige, the Piave and the Bacchiglione-Astico river systems), with different characteristics in terms of drainage areas, elevations and positions within the region hit by the event. For this, the hydro-meteorological forecasting chain includes the two mesoscale models (MOLOCH and WRF), driven by two global analysis systems (GFS-NCEP and IFS-ECMWF), and a grid-based spatially distributed hydrologic model termed GRIS (Grid-based runoff simulation model). We examine different ensemble strategies for the initialization of the hydro-meteorological chain and focus on the assessment of hydrological predictability, paying specific attention to basins with high regulation capacity thanks to the presence of hydropower storage.</p>

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