Prediction of snowmelt rates in a deciduous forest

A model is presented for the prediction of the energy available for the melting of snow in a deciduous forest. The turbulent exchanges H and LE can be estimated using physically based equations, but are small at the forest floor, accounting typically for less than 10% of daily melt totals, largely because of the much reduced windspeed within the forest. Net allwave radiative energy flux density ( Q★) alone is a good predictor of snowmelt rates. Physical modelling of Q★ is not operationally possible, and the simple regression of Q★ on solar energy flux ( K↓), a technique used with success in some circumstances, is shown to be inappropriate in a forest during snowmelt. A multivariate model using two commonly available variables: K↓ and air temperature in the forest, explains over 3 4 of the variance of Q★.