Prediction Of Glacial Lake Outburst Floods Using Stochastic Cellular Automata Over The Region Of Shishper

Rapid snow melting and consequent decrease in the snow cover of a particular location plays a significant role in the occurrence of glacial lake outburst floods (GLOFs). Therefore, determination of the rate of depletion in the snow covered area (SCA) and understanding the underlying causes is of utmost importance for early detection of such disasters. This work employs cellular automata (CA) for predicting the spatio-temporal change of SCA in and around the Shishper glacier, Baltistan, which has experienced recurrent annual occurrences of GLOFs. The CA forecasts the future state of a cell, taking into account it’s current snow cover as well as terrain and climatic factors. The major contribution of this work is in the formulation of a unique ternary CA model, with the 3-classes being snow, land, and lake, which effortlessly captures the decrease in SCA and concomitant increase in lake area with a notable prediction accuracy of 84%.