Assume that we have a (directed) graph $G(V \cup \{s, t\}, E)$ and an (integer) capacity function $c : E \mapsto \mathbb{N}$. Let $f : E \mapsto \mathbb{N}$ be a maximum $s-t$ flow on this graph. Suppose that some edge capacities are suddenly reduced; i.e. we now have to work with a capacity function $c_R : E \mapsto \mathbb{N}$ such that $c_R(e) \leq c(e)$ for all $e \in E$.
Can we efficiently "adjust" our old optimal flow $f$ to find the new optimal flow $f_R$ instead of recomputing the latter from scratch?
Note 1: Assume that the reduction is consequential; i.e. $c_R(e) < f(e)$ for at least one $e \in E$. Also, for the sake of simplicity, you can assume that the capacity is reduced for only one edge.
Note 2: One approach would be to treat the problem as an LP. In this case, capacity reductions will simply change variable bounds. Thus, we can use a warm-start capable LP solving method to get from $f$ to $f_R$. For example, if we used the dual simplex method (DSM), we can compute $f_R$ from $f$ via a (hopefully) small number of pivots, each of which involves $O(|V| \cdot |E|)$ arithmetic operations.
Note 3: This discussion tries to tackle the related (harder?) problem of adding/removing vertices and modifying the maximum flow.