Wind speed and direction are fundamental data in many fields such as power generation, and hydrological modeling. Within the hydrological domain, among other uses, wind data are used to compute evapotranspiration and correct precipitation measurement. Wind measurements are sparse, hence spatial interpolation of wind data is required. In mountainous area with complex topography, accurate interpolation of wind data should consider topographic effects. The wind field can be generated by several methods, including: 1) applying a physically based, full atmospheric model which satisfy all relevant momentum and continuity equations, 2) applying an atmospheric model in which1only mass continuity is satisfied, 3) interpolation using wind-speed and direction observations in conjunction with empirical wind-topography relationships. Due to computational constraints, methods 1 and 2 can not be applied for long time simulations like the ones required for assessing climate change impacts. The aim of this work is to compare different techniques to interpolate wind speed in a complex topography area. The subject area is the upper Po River basin and covers 38000 km2. This is predominantly an alpine region located in Northern Italy that is bounded on three sides by mountain chains covering 73% of its territory. Impact of wind data interpolation accuracy is assessed by running the FEST-WB model (Flash Flood Event based Spatially distributed rainfall runoff Transformation, including Water Balance), a spatially distributed model that computes the main processes of the hydrological cycle: evapotranspiration, infiltration, surface runoff, flow routing, subsurface flow, and snow melt and accumulation. Results show that the use of empirical methods based on wind-topography relationships provide good accuracy for river basin hydrological analysis at a fraction of the computational cost required by physically based atmospheric models.
Wind speed interpolation for hydrological modeling in complex topograhy area
S Davolio;
2016
Abstract
Wind speed and direction are fundamental data in many fields such as power generation, and hydrological modeling. Within the hydrological domain, among other uses, wind data are used to compute evapotranspiration and correct precipitation measurement. Wind measurements are sparse, hence spatial interpolation of wind data is required. In mountainous area with complex topography, accurate interpolation of wind data should consider topographic effects. The wind field can be generated by several methods, including: 1) applying a physically based, full atmospheric model which satisfy all relevant momentum and continuity equations, 2) applying an atmospheric model in which1only mass continuity is satisfied, 3) interpolation using wind-speed and direction observations in conjunction with empirical wind-topography relationships. Due to computational constraints, methods 1 and 2 can not be applied for long time simulations like the ones required for assessing climate change impacts. The aim of this work is to compare different techniques to interpolate wind speed in a complex topography area. The subject area is the upper Po River basin and covers 38000 km2. This is predominantly an alpine region located in Northern Italy that is bounded on three sides by mountain chains covering 73% of its territory. Impact of wind data interpolation accuracy is assessed by running the FEST-WB model (Flash Flood Event based Spatially distributed rainfall runoff Transformation, including Water Balance), a spatially distributed model that computes the main processes of the hydrological cycle: evapotranspiration, infiltration, surface runoff, flow routing, subsurface flow, and snow melt and accumulation. Results show that the use of empirical methods based on wind-topography relationships provide good accuracy for river basin hydrological analysis at a fraction of the computational cost required by physically based atmospheric models.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
