A cellular automata model for simulating the evolution of positive–negative terrains in a small loess watershed

Cellular automata (CA) have been used increasingly to simulate complex geographical phenomena. This paper proposes a CA model for simulating the evolution of dynamic positive and negative (P–N) terrains in a small loess watershed. The CA model involves a large number of attributes, including the state of P–N terrains, distance to the shoulder-line, neighbourhood condition and topographic factors. Topographic factors include the slope gradient, aspect, slope length, slope variation, aspect variation, plan curvature, profile curvature, relief amplitude and flow accumulation. The CA model was applied to simulate the evolution of P–N terrains in an indoor, small loess watershed under artificial rainfall. The transition rules for CA were constructed automatically using a decision-tree algorithm. The derived transition rules are explicit for decision-makers and helpful for generating more reliable terrains. The simulation produces encouraging results in terms of numeric accuracy and spatial distribution, in agreement with natural P–N terrains. The iterative processes show that loess negative terrains continuously erode positive terrains. The development of a loess sinkhole near the centre gully head was reproduced as well, which shows the function of loess sinkholes in the formation of loess channel systems.