WRM optimization scenarios

The OptimizationScenario OBJECT CLASS builds on

1. a WRM base scenario
2. a matching STREAM scenario

1. the header and META DATA including a description !
2. scenario level information that provides the link to the WRM (and STREAM) scenarios;
3. a set of CONSTRAINTS
4. a set of INSTRUMENTS

Generic INSTRUMENTS are managed in the Water Technologies data base.

The top level scenario object shows a summary of these two sets.

CONSTRAINTS

The biggest advantage of this seemingly simple approach is that is makes representation of multi-criteria multi-objective problems easy: any number of CONSTRAINTS can be expressed in a problem oriented natural language without any regard to preferences and trade-off, different constraints usually corresponding to different stakeholders and interests.

The CONSTRAINTS define a desirable or at least acceptable region in model behaviour space: they represent what the various stakeholders want or expect from the system in terms of the model. CONSTRAINTS can be valid for the entire simulation period or only some part of it (if they apply to seasonal requirements).

1. Global Constraints

   The global (default) CONSTRAINTS are formulated in terms of:

   • The concept name (the Descriptor display name from the systems knowledge base)
   • strategy (minimize, maximize, minimize deviation from a norm)
   • the nuumerical value the constraint is set at;
   • the unit of measurement
   • a tick box to toggle contraints on or off;
   • at the results level:
     • the number of trials that failed violating this constraint
     • the reslut value for the current feasible solution
     • the average, minimal and maximal values for the feasible subset and total set of trials.

2. Sectoral and Node Specific Constraints
   NOT YET INPLEMENTED

INSTRUMENTS

INSTRUMENTS can be

• Discrete, integer, or binary (selected or not, e.g., a new reservoir); the models selects either on (1) or off (0).
• Continuous (i.e., they can be applied to some degree from 0 (not at all) to 100% e.g., lining an irrigation canal: out of the 10 km any part or percentage could be affected. The model selects an appropriate percentage of application.
• Mutually exclusive (can not be combined with certain other INSTRUMENTS);
• Additive or multiplicative (can be combined with other INSTRUMENTS);

1. different SCOPE: an INSTRUMENT can, in principle, affect
   • the entire basin (for example, overall policy or an education campaign)
   • a specific sector (sectoral policy, incentives);
   • a specific local NODE.
   Please note: in the first installation, SCOPE is restricted to the local or NODE level to simplify the implementation as well as scenario definition.

2. NODE TYPE: At the local or NODE level, INSTRUMENTS can be defined for:
   • START NODES, for example, inter basin transfer, desalination, or stronger pumps for deeper well and well fields;
   • RESERVOIR NODES, that can switch on or off individual/new reservoirs;
   • DIVERSIONS that can be used to modify diversion rules by:
     • modifying the diversion percentage split within a user defined range around the original value;
     • modifying the diversion target flow (multiplier);
     • modifyinh the downstream target flow (multiplier).
   • DEMAND NODES that affect demand, losses, and consumptive use for this NODE CLASS.

1. Name and META DATA
2. optional link to a Water Technology from which its parameters (Descriptors) get imported as defaults, that can be overloaded at the scenario level. The Water Technology Object also provides a textual description of the technology.
3. Any or all of the parameters listed below may be set to zero or 1.0 and thus, depending on their nature, render them ineffective as the technology does NOT affect the corresponding concept (e.g., consumptive use).
   For each instance of SCOPE (a specific demand node) the data set includes:
   • minimum application rate: the minimum level at which this technology can be applied, can be non zero The interpretation is as follows: a given technology is either applied not at all (0), or at least for N (say, 20%) of the corresponding node; for example, a project lining an irrigation canal partly would have to cover at least 20% to be feasible at all due to the fixed costs involved.
   • maximum application rate: may be less than 100%; a technology may not be realistically be applied to 100% of a demand node, for example, water saving shower heads in a city.
     The optimization will find the best value within this range. For a discrete alternative (no scaling, can only be selected or nor), the minimum as well as maximum are set 100%.

   • demand multiplier: scales the demand, corresponding to the application rate;
   • consumptive use multiplier: scales the consumptive use, represents different efficiency of water use of the technology; according to the application rate;
   • conveyance loss multiplier :
   • return flow loss multiplier:
   • Cost factors FIXED (annualized investment) and VARIABLE (operations and maintenance); these are meant to refer to a 100% application rate. initially represented with a simple linear function of flow:   cost = FIXED * application rate + VARIABLE * reference_unit where the ORM reference unit can be: per day, per m³ or by investment reference unit, in the latter case to be scaled by the application rate.

Generating Alternatives

The generation of alternatives is using a complex heuristic strategy. Currently, however, only a simple Monte Carlo scheme is implemented.

A two-step proceudre is used:

1. In a first step, we select which instruments should be applied; this is based on a pseudo-random number in the intervall between 0.0 and 1.0 values below 0.5 lead to rejecting the instrument, values >e; 0.5 will select the instrument. The instrument specific weight is used as a multiplier to increase or decrease the probability of an instrument to be chosem by multiplying the original random number.
2. In the second step, the instrument configured: another random number is generated, its value is mapped in the intervall between the minimum and maximum application rate defined for the instrument, the resulting application level is applied.

Combinations of INSTRUMENTS

For a given optimization scenario and its set of INSTRUMENTS, an EXCLUSION MATRIX needs to be constructed that specifies which INSTRUMENTS can jointly be considered for any SCOPE instance.