We are in a drought, but people keep watering their lawns. The water company wants to know how much water it will need to supply. On average, the lawns in this city need 1 million gallons per day. But, if it rains, the rain might supply 0-2 million gallons per day. On average, rain in the drought supplies 5 million gallons per month. Rain at a rate of more than what the lawns need runs off into the sewer and cannot be reclaimed or used.

Part 1A: Use this information to produce a simulation to determine how much the water utility must purchase for the next 3 months. The simulation must be user-friendly.

Part 1B : Run your simulation a number of times and interpret the statistics. How much should the utility purchase each month to guarantee a service level of 90%?

Part 2A : The town is stepping up enforcement of watering violations. 90% of the people each month who violate watering restrictions get away with it (Freebirds). Of those who get caught (Jailbirds), 80% won't do it again (and become Angels). Angels are rarely tempted to violate the restrictions next month (10%). Build a Markov Process model using these three states and given 50% of the town is estimated to initially be Angels, is the policing effective? What percentage of the population violates restrictions after 10 months.

Part 2B : Run your Markov model to determine which is more effective: Policing to catch 20% of the violators each month or public service announcements to reduce the Angel temptation rate to 3%.