There are several tools within RiverSim that allow the modeler to influence how the model will operate. Basically, the storage in a reservoir may be controlled as may the release from any water handling object and the diversion from a diversion object.

The idea is that the things the modeler may control correspond to the things that a reservoir operator may control. (Note that storage may not be controlled directly in a real reservoir, but is adjusted through changing release. As a convenience, a model may be set automatically to maintain some storage level by varying inflow or release as appropriate.)

Inflow may not be controlled by the object that is receiving it. Rather, if there is a controllable object upstream, the release of the upstream object may be controlled and so change the inflow downstream. Similarly, loss terms may not be controlled.

All of the policy tools are applied within the context of a control cycle. The control cycle is based on the assumption that water systems are managed cyclically. The cycle might be annual for planning storage targets, weekly for planning hydropower operations, or daily for planning pump back storage operations.

The control cycle is set from the "Settings" menu in the simulation window. In the same menu, choosing "Scheduler" gets the following dialog:

As can be seen in the figure, control may change with each step in the cycle (in the figure, there are 12 monthly steps in an annual cycle).

RiverSim has three different tools with which to control the model's operation, demands, constraints and rules. Each of these tools behaves differently, acts at a different point in the time step and has a different precedence. To get the results you want, it is important to understand each of these tools and its place within the meta algorithm.

• Rules: Rules are like little Hewlett Packard calculators which operate to determine the value of a slot during the begin time step phase of the meta algorithm. The rule has access to the end of period value of any other slot in the model. Thus, rules can be used to set the value of one slot based on some combination of the values in other slots.

• Constraints: Constraints cause the simulation engine to attempt to maintain the value of either storage or release either above or below some value. Constraints are applied during the task step of the meta algorithm. They may be applied multiple times during a time step. This means that they will override rules if necessary. Constraints are economic in nature, imposing a cost which is linearly proportional to deviation from the desired value. (The metaphor used during their development is that of a set of directional linear springs. As the value of the slot deviates from the target in the direction which compresses the springs, they generated a counter force.) During each time step, the simulation engine minimizes the net force on all springs in the system.

• Demands: Demands are the strongest means of setting policy. A demand is set by setting the value on the outflow slot of any water handling object. This value may be set either with a time , or it may be set using a rule. It is important to understand that from the interface perspective, demands are set in exactly the same manner as user series and rules on other slots. The thing that makes a demand is that the slot being set is the outflow slot.

These policy writing tools may freely be mixed in any combination that proves useful. A model also may be run with none of these tools.