Application of Climate Downscaled Data for the Design of Micro-Hydroelectric Power Plants
In this paper, changes in annual average precipitation levels from the statistical downscaling (multi linear regression) of RegCM3 data for the meteorological station of Aymaville (Aosta Valley Region, NW Italy) are applied to assess the effect of climate change on stream discharge in presence of a micro-hydroelectric power plant. Impacts were assessed by comparing minimum stream discharge for present days condition with the required water withdrawn under future annual precipitation scenarios (A2 and B2). Equations used to calculate monthly and minimum stream discharge are those provided by the Valle d’Aosta Region Water quality management plan. Modifications in annual average precipitation levels are useful to assess future impacts for months from October to May. Water discharge for the period from June to October, is solely or partially a function of catchment mean altitude (=snowmelt contribution), thus an assessment of climate change effects is not possible. Taking into account the effects of climate change on snow precipitation level and snow accumulation, we suggest that catchment mean altitude is not a suitable parameter for depicting climate change effects on stream discharge during months characterised by prevalent snowmelt contribution.
KeywordsClimate change Environmental impact assessment Statistical downscaling Micro-hydroelectric power plants Stream minimum discharge
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