AQUAPLAN-SDDP is a stochastic hydro-economic model that represents the water economy of a regional water system (typically a river basin). The main features are:

• It relies on an arc-node representation of a river basin
• It integrates the essential hydrologic, institutional and economic processes of a river basin
• It can handle complex systems with a large number of reservoirs and demand sites
• Typical formulation seeks to maximize expected basin-wide net benefits subject to operational constraints (physical, environmental, legal, …)
• It considers the hydrologic uncertainty through a probabilistic description of future inflows
• It can handle different hydrologic information: previous inflows, snowpack, sea surface temperature, seasonal forecasts as well as climate states (e.g. dry, normal, wet)
• The optimization problem is solved using the SDDP algorithm (Stochastic Dual Dynamic Programming), which is extensively used in the power sector.

The code is written in Python and relies on the GUROBI solver. Input data are stored in two Excel files. A version of the code is also available as a MATLAB toolbox.

The output consists of:

Per node j, per hydrologic scenario m, per time period t:

• Allocation decisions: water abstractions, downstream releases, storage volumes, spillage losses, evaporation losses, etc.
• Marginal water values ($/m³)
• Shadow prices ($/m³) associated with the constraints: max/min storage capacity (reservoirs); max/min water diversion capacity (irrigation, industrial, municipal and domestic); max/min turbining capacity (hydropower); min flow requirements (e-flows, navigation, etc.); max flow (flood control)