LAUSR

Abstract Forest disturbances influence water quantities and qualities in catchments, but these disturbances cannot be easily measured and quantified directly. The two main options are direct tree counting and the use of satellite images, from which forest disturbance indices are calculated. The problem with the first option is that it is time consuming. To overcome this problem, we used a catchment-scale infrared (IR) index for a Picea abies mountain forest catchment, validated by tree counting, as a predictor in regression modeling to assess the water chemical property response to disturbances. This enabled us to quantify the time delay with which chemical compounds in surface waters reacted to disturbances. The results showed that there was an insignificant correlation between dissolved organic carbon (DOC) concentration and the disturbance index from the same year that the disturbance occurred (R2 = 0.02; p = 0.27), but correlations gradually improved and became more significant, with correlations after a 6-year delay being strongest (R2 = 0.69; p ≤ 0.001). The significant time delays with which other compounds responded to the disturbance ranged from 0 years (NO3-N, total nitrogen, Ca2+, Mg2+, labile aluminium) to 5 years (total organic nitrogen). Our results suggest the potential use of such an index for predicting water quality changes in disturbed areas of Picea abies mountain forests.