  In this paper, we propose a framework to solve a demand-supply optimization
problem of long-term water resource allocation on a multi-connection reservoir
network which, in two aspects, is different to the problem considered in
previous works. First, while all previous works consider a problem where each
reservoir can transfer water to only one fixed reservoir, we consider a
multi-connection network being constructed in Thailand in which each reservoir
can transfer water to many reservoirs in one period of time. Second, a
demand-supply plan considered here is static, in contrast to a dynamic policy
considered in previous works. Moreover, in order to efficiently develop a
long-term static plan, a severe loss (a risk) is taken into account, i.e. a
risk occurs if the real amount of water stored in each reservoir in each time
period is less than what planned by the optimizer. The multi-connection
function and the risk make the problem rather complex such that traditional
stochastic dynamic programming and deterministic/heuristic approaches are
inappropriate. Our framework is based on a novel convex programming formulation
in which stochastic information can be naturally taken into account and an
optimal solution is guaranteed to be found efficiently. Extensive experimental
results show promising results of the framework.
