Application of Stochastic Dynamic Programming (SDP) for the optimal allocation of irrigation water under capacity sharing arrangements

This study attempts to arrive at an optimal allocation of irrigation water using capacity sharing (CS) as an institutional arrangement, and stochastic dynamic programming (SDP) as an optimisation model. It determines the value of an additional unit of water under a crop enterprise mix of lucerne-maize-wheat (LMW). SDP is an improvement on linear programming (LP) under stochastic conditions. The SIM-DY-SIM Model was used to simulate optimal returns, decision and policy variables under varying conditions of capacity share. LP results show that wheat has the highest MVP of R0.39/m3, with maize exhibiting the lowest value of R0.09/m3. The MVPs generated with SDP range between R0.06/m3 and R0.35/m3 on the whole farm basis, with revenue to the farmer increasing with an increase in CS content and increased percentage water release. However, the MVP of water decreased with the increased supply of the resource – a phenomenon that follows the general rule of decreasing marginal utility of a resource as more of it is used.Resource /Energy Economics and Policy,

A methodological perspective on valuing water: a comparison between linear programming and stochastic dynamic programming

Information on the value of water in use is a prerequisite for the efficient allocation, utilization, trading and transfer thereof. These issues are becoming very important for South Africa. Linear programming (LP) and stochastic dynamic programming (SDP) are two techniques that can be applied to value water. Based on a simulated irrigation farming situation downstream of the Vanderkloof Dam wherein farmers hold a capacity share (CS) this paper draws a comparison between the marginal value products (MVP’s) obtained from applying LP and SDP simultaneously. Linear programming is used to optimize water use on the farm during the immediate season while SDP is used to optimize the use of water in storage in the farmers capacity share (CS) in the Vanderkloof Dam through time. Emphasis is placed on the interpretation of the results which are presented graphically

Application of Stochastic Dynamic Programming (SDP) for the optimal allocation of irrigation water under capacity sharing arrangements

This study attempts to arrive at an optimal allocation of irrigation water using capacity sharing (CS) as an institutional arrangement, and stochastic dynamic programming (SDP) as an optimisation model. It determines the value of an additional unit of water under a crop enterprise mix of lucerne-maize-wheat (LMW). SDP is an improvement on linear programming (LP) under stochastic conditions. The SIM-DY-SIM Model was used to simulate optimal returns, decision and policy variables under varying conditions of capacity share. LP results show that wheat has the highest MVP of R0.39/m3, with maize exhibiting the lowest value of R0.09/m3. The MVPs generated with SDP range between R0.06/m3 and R0.35/m3 on the whole farm basis, with revenue to the farmer increasing with an increase in CS content and increased percentage water release. However, the MVP of water decreased with the increased supply of the resource - a phenomenon that follows the general rule of decreasing marginal utility of a resource as more of it is used